Metrics details A long-standing goal in neuroscience is to understand how a circuit’s form influences its function we reconstruct and analyze a synaptic wiring diagram of the larval zebrafish brainstem to predict key functional properties and validate them through comparison with physiological data We identify modules of strongly connected neurons that turn out to be specialized for different behavioral functions The eye movement module is further organized into two three-block cycles that support the positive feedback long hypothesized to underlie low-dimensional attractor dynamics in oculomotor control We construct a neural network model based directly on the reconstructed wiring diagram that makes predictions for the cellular-resolution coding of eye position and neural dynamics These predictions are verified statistically with calcium imaging-based neural activity recordings This work demonstrates how connectome-based brain modeling can reveal previously unknown anatomical structure in a neural circuit and provide insights linking network form to function connectomics has provided a strong anatomical basis for the computations underlying motion processing within and across most vertebrate brain regions the connectivity is highly recurrent without obvious topographic structure it remains unclear how the neural coding properties of the system emerge from and relate to the underlying connectivity and cellular properties We reconstructed ~3,000 neurons as completely as the borders of the volume allow through human proofreading of an automated segmentation By applying graph clustering algorithms to the connectome we reveal that this naively disorganized structure hides a strongly modular hierarchical organization we find two anatomically defined modules that are specialized for different behaviors: one for eye movements and the other for body movements The oculomotor module is in turn subdivided into two submodules specialized for movements of each eye each submodule contains a three-block cyclic substructure Our linking of structure and behavior by modularity analysis at synaptic resolution is unique for the vertebrate nervous system we take a more direct approach: use the wiring diagram to estimate a synaptic weight matrix characterizing physiological interactions between neurons and literally insert that matrix into a network model incorporating a minimal number of additional constraints from physiology the predictions turn out to be statistically consistent at a population level with neural activity recorded by calcium imaging of larval zebrafish during oculomotor behavior Three-dimensional rendering of reconstructed neurons The large green cell body in the foreground is the Mauthner neuron (Mcell); Ro The inset (top left) shows the location of the unilateral EM volume (black box) relative to the olfactory bulb (OB) Automatic synapse detection and partner assignment Postsynaptic densities (PSDs) identified by a convolutional network Postsynaptic densities (red) overlaid onto the original raw image together with an exemplar presynaptic (blue) and postsynaptic (yellow) partnership identified by a second convolutional network Sagittal view of the identified ABDM (green) and ABDI (magenta) neurons overlaid over representative EM planes; R The asterisk (*) indicates the Mauthner cell soma Coronal planes showing the locations of the ABDM (left) and ABDI (right) neurons at the planes indicated by dotted black lines in the sagittal view Black boxes highlight nerve bundles from these populations Representative ABDM and ABDI neurons with arrows indicating the axons Reconstructions of large and small RS neurons and Ve2 neurons To demonstrate that this graph-theoretic procedure identified biologically relevant modules and to suggest functional roles of these modules we then examined the patterns of connections between the central and peripheral populations we present the resultant organization in a hierarchical manner matrix of connections in the ‘center’ of the wiring diagram with neurons clustered into two modules (modA and modO) matrix of connections from center to large RS and ABD neurons in the periphery example connected pair of modO neurons (light and dark blue) and the overlap of their axons with the dendrite of an ABD internuclear cell (magenta) The grid in the background is the same in both images to facilitate comparison Locations of reconstructed neuron somas (modA blue) projected onto the horizontal plane and one-dimensional (1D) densities along the mediolateral (bottom) and rostrocaudal (left) axes Closed circles are neurons with complete somas inside the reconstructed EM volume Open circles are locations of the primary neurites exiting the top of the EM volume for cells with somas above the volume The inset cartoon shows the region of the hindbrain in the figure Postsynapses of neurons in modA and modO along with 1D densities Every fifth postsynaptic density is plotted for clarity Presynapses of neurons in modA and modO along with 1D densities Every tenth presynaptic terminal is plotted for clarity Schematic illustrating the definition of a potential (that is false) synaptic connection identified when a presynaptic terminal (for example axon 2) is proximal (red) to a postsynaptic density (for example dendrite 1) but not actually in contact with it Ratio of the number of within-module to the number of between-module synapses versus threshold distance for true and potential synapses The table lists the actual true synapse densities for the data point with an asterisk (*) Ratio of numbers of synapses from neurons in modA and modO to peripheral neurons (ABD and RS) we decided to probe to what extent these distributions could be contributing to modularity We also identified, at the population level, statistical differences in other anatomical features of modA and modO neurons and synapses (Extended Data Fig. 2), such as total arbor length and synapse distance from the soma (Extended Data Fig. 2a–c) we note that the total number of synapses onto a neuron (regardless of origin) was 310 ± 261 for modA neurons 1,576 ± 1,555 for peripheral RS neurons and 411 ± 167 for ABD neurons the binary division into two modules is the first step in a hierarchical procedure that reveals further substructure a, Top, matrix of connections within modO organized into two submodules termed modOM and modOI. Bottom, projections of modOM and modOI onto ABDM and ABDI neuron populations. b, Locations of reconstructed neuron somata along with 1D densities for neurons within modOM (blue) or modOI (brown). The symbols, inset and orientation are as in Fig. 2c Postsynaptic densities (c) and presynaptic terminals (d) in modOI and modOM Every fifth synaptic site was plotted for clarity Ratio of the number of within-module synapses for modOM and modOI to the number of between-module synapses as a function of potential synapse distance The table lists the actual number of true synapses for the data point with an asterisk (*) Ratio of the number of synaptic contacts between a modO submodule and its preferred peripheral partner versus those between a modO submodule and its nonpreferred peripheral partner The numbers in the tables represent normalized synapse counts defined as the ratio of the sum of all synapses in a block to the product of the number of elements in the block Ocular preference index for modOM and modOI neurons A value of 1 or –1 indicates connections to only one ABD population A value of 0 indicates an equal number of connections to each ABD population Population-level differences between modOM and modOI and their interconnections were also evident in the statistical distributions of synapse size and synapse distance from the soma (Extended Data Fig. 2d,e) The results above suggest the existence of two weakly connected submodules within the oculomotor network To gain insight into whether these submodules contained substructure we next examined the eigenvalues of the modO connectivity matrix The set of eigenvalues of a connectivity matrix contains hallmark signatures of the matrix’s underlying structure To understand the relationship between the eigenspectrum and network structure a, Eigenvalue spectrum for modO when connections are shuffled (Methods) with modO treated as a single block (left) or as two blocks consisting of modOM and modOI with interconnections removed (middle) or intact (right) Eigenvalue spectrum for the actual connectome Matrix of synaptic connections for modO and its connections to the ABD Cells are grouped by block identity in a seven-block SBM The orange and purple boxes highlight cycles in the connections within blocks OM1–OM3 and blocks OI1–OI3 Gray ticks indicate the location of Ve2 cells Eigenvalue spectrum of modO after the cycles are decoupled by eliminating connections between the internuclear cycle and the other four blocks (d) and when the connections within the internuclear cycle are additionally shuffled (e) Diagram of connections between blocks in modO Solid lines indicate the most prominent connections and dashed lines indicate weaker connections orange) eigenvectors for modO (top) and modO with the two cycles decoupled as in d the leading eigenvectors approximately combine the eigenvectors found in the decoupled case The leading eigenvector approximates a scaled sum of the two decoupled eigenvectors and the second leading eigenvector approximates a scaled difference of the decoupled eigenvectors this suggests that activation of the pattern of modOM neurons corresponding to the first eigenvector may generate ‘conjugate eye movements’ (eyes moving together in the same direction which requires coactivation of the ABDM and ABDI populations) whereas activation of the second eigenvector may be critical for maintaining either disconjugate eye movements (eyes moving in opposite directions) or deviations from conjugate eye movements Two of these graph-theoretically derived blocks would not be easily identifiable as part of modO by naively tracing connections back from the periphery Block OM1 of the motor submodule projects extremely weakly to the motor neurons but has the strongest projections to and receipt of projections from the internuclear submodule it appears to be involved nearly solely in internal processing block OI3 of the internuclear cycle has relatively little connection to the ABD appear to divide into two halves with different functions for each half; for block OM3 whereas the other half provides the strongest projection to the \({{\rm{O}}}_{{{\rm{Ve}}}^{2}}\) block We hypothesized that modO contains the majority of the ‘neural integrator’ for horizontal eye movements that transforms angular velocity inputs into angular position outputs This transformation has been suggested to depend on a relatively high degree of recurrent interactions within the velocity-to-position neural integrator (VPNI) it is not known how these interactions shape the single-neuron coding properties of neurons within modO and its peripheral outputs in the ABD Relative eye position sensitivities from the connectome-based model (gray) and imaging of real cells (green) Same as d except that the model uses potential synapses instead of the actual connectome Cumulative variance explained for the leading principal components of the STA of the firing rates of the model (gray) or deconvolved fluorescence of imaged cells (green) for the period between 2 and 6 s after a saccade best-fit amplitudes of the exponentials for each cell in the model (gray) and each imaged cell (green) Note in d that VPNI cells were defined experimentally by having a sufficiently large correlation with eye position; thus the lowest sensitivity simulated VPNI cells would not have been counted if they occurred in a functional imaging dataset the final synaptic weight matrix took the form \({W}_{ij}=\pm \beta \frac{{N}_{ij}}{{\sum }_{k}{N}_{ik}}\) Because the imaged neurons come from different fish than the reconstructed one they cannot be placed in one-to-one correspondence with neurons in our EM volume we resorted to a population-level comparison although the bimodality seen in the model ABD populations was not clearly evident We compared these simulations to three classes of neurons (VPNI which could not easily distinguish between ABDM and ABDI neurons This suggests that the functional properties of the circuit depend on the spatially precise connections revealed by the EM connectome although the seven-block model is required to recover the cyclic connectivity of the network and the separate vestibular-dominated block \({{\rm{O}}}_{{{\rm{Ve}}}^{2}}\) it is not required to reveal the slowest timescale decay dynamics This work shows how the neural coding properties throughout a hindbrain network relate to its synapse-resolution structure Through connectomic reconstruction and analysis we reveal that hindbrain regions previously thought to be largely unstructured instead contain a hierarchical modular organization that closely aligns with known motor functions Directly inserting the connectome into a network model statistically predicts the single-neuron coding properties assessed with two-photon calcium imaging throughout the reconstructed volume representing a breakthrough in deriving neuronal properties within a topographically heterogeneous network from the connectome EM-resolution analysis was critical to revealing the above network structure and predictions as there were large discrepancies when lower-resolution analysis based on potential synapses was used to assess connectivity The resulting connectome and modular analysis tools are being provided as an open resource to the community Comparisons between model predictions and physiological data at the level of single cells might require more sophisticated modeling of cell- and synapse-specific biophysics As more connectomes become available in other settings it will be important to consider which physiological constraints need to be incorporated to make appropriate use of these powerful datasets Answers to this question depend on many factors including the breadth of behaviors to be produced in a single model the range of dynamics of the constituent components and the degree to which the model is to produce quantitative versus qualitative matches to data when guided by knowledge of the various behaviors a circuit participates in and appropriate physiological constraints gleaned from recordings and perturbations of activity it may be possible in even more complex circuits to identify physiological modules whose function can be well understood using the connectome-based analysis and modeling approach taken here and the linear system was solved using conjugate gradient descent The mean residual errors were in the range of 0.5–1.0 pixels after relaxation The intersection alignment was split into a translation step (pre-prealignment) a fast coarse elastic step (rough alignment) and a slow fine elastic step (fine alignment) a central patch of the given montaged section was matched to the previous montaged section to obtain the rough translation between two montaged sections the montaged images were offset by that translation and then a small number of correspondences were found between the two montaged sections The sections were then aligned using an affine transformation fit using least squares regularized with a 10% (empirically derived) weighting of the identity transformation to reduce shear accumulating and propagating across multiple sections Proceeding sequentially allowed the entire stack to get roughly in place The mean residual errors after prealignment were in the range of 3.5 pixels after relaxation In the subsequent rough and fine alignment steps the blockmatches were computed and filtered between bandpassed neighboring sections in a regular triangular mesh followed by a conjugate gradient descent on the linear system Splitting the elastic step into rough and fine alignments allowed the search radius to be reduced during the fine alignment relative to what would have been necessary with a direct attempt thereby lowering the likelihood of spurious matches as well as the computing time These labeled subvolumes were used as the ground truth for training convolutional networks to detect neuronal boundaries We used 187.7 million voxels for training and reserved 6.7 million voxels for validation neuronal reconstructions were checked and if necessary corrected by expert in-house image analysts who each had more than 5,000 h of experience The accuracy of the players in the crowd compared to experts (assuming experts are 100%) was >80% in the first round and ~95% after the second round of tracing The validated reconstructions were subsequently skeletonized for analysis purposes Player accuracy was calculated as an F1 score All scores were calculated as a sum over voxels TP was assigned when both the player and the expert agreed that the segmentation was correct FN was assigned when the player missed segments that were added in by the expert and FP was assigned when the player erroneously added segments that did not belong Two F1 scores were calculated for each player No player played the same neuron in both rounds Only the most experienced players on Eyewire were allowed to participate A small group of four highly experienced players received an invitation to test this new dataset The players were given the title of ‘Mystic’ which was a new status created to enable gameplay and became the highest achievable rank in the game Subsequent Mystic players had to apply for the status to unlock access to the zebrafish dataset within Eyewire There was a high threshold of achievement required for a player to gain Mystic status Each player was required to reach the previous highest status within the game as well as complete 200+ cubes a month and maintain 95% accuracy when resolving cell errors they were granted access to the zebrafish dataset and given the option to have a live tutorial session with an Eyewire Admin There was also a prerecorded tutorial video and written tutorial materials for players who could not attend the live session or who desired a review of the materials Newly promoted players were also given a special badge a new chat color and access to a new chat room exclusive to Mystics These rewards helped motivate players by showing their elevated status within the game as well as giving them a space to discuss issues specific to the zebrafish dataset Cells were parceled out in batches to players Each cell was reconstructed by only one player at a time Once this player had finished their reconstruction a second player would check over the cell for errors a final check was done by an Eyewire Admin a special graphical user interface was built into the game that allowed players to see the status of each cell currently online A cell could be at one of the following five statuses: ‘Need Player A’ These statuses indicated whether a cell needed to be checked or was in the process of being checked and whether it needed a first- the username of the player or Admin who had done a first It was made mandatory that the first and second checks were performed by two separate players Collaboration and feedback were important parts of the checking process If a player was unsure about an area of the cell they were working on they could leave a note with a screenshot and detail of the issue or create an alert that would notify an Admin If a ‘Player B’ or an Admin noticed a mistake made earlier in the pipeline they could inform the player of the issue via a ‘Review’ document or through an in-game notification (player tagging) To differentiate the zebrafish cells from the regular dataset This tag helped identify the cells as separate from the e2198 retinal Eyewire dataset and also populated them to a menu of active zebrafish cells within Eyewire Players were rewarded for their work in the zebrafish dataset with points Points earned while playing zebrafish were added to a player’s overall points score for all gameplay done on Eyewire and appeared in the Eyewire leaderboard we constructed a weighted undirected graph from the point cloud where the neighboring points are connected with an edge and the edge weight is computed from the DBF We then took the point with the largest DBF as source and found the furthest point as the target The shortest path from source to target in the graph was computed as the skeleton nodes The surrounding points were labeled as visited and the closest remaining unvisited point was taken as the new source We repeated this process until all the points were visited The skeleton node diameter was set as its DBF The skeleton nodes were postprocessed by removing redundant nodes merging single-child segments and smoothing the skeleton path All skeletonization was performed at multum in parvo level 4 All 361 synapses in the ground truth were labeled with their synaptic partners and the partner network used 204 synapses as a training set 73 as a validation set and the remaining 84 as a test set The final network was 95% accurate in assigning the correct partners of the test set after 380,000 training iterations The final cleft network was applied across the entire image volume and formed discrete predictions of synaptic clefts by running a distributed version of connected components Each cleft was assigned synaptic partners by applying the partner network to each predicted cleft within nonoverlapping regions of the dataset (1,024 × 1,024 × 1,792 voxels each) In the case where a cleft spanned multiple regions the assignment within the region that contained most of that cleft was accepted Cleft regions whose centroid coordinates were within 1 μm and were assigned the same synaptic partners were merged together to merge artificially split components postsynapses on axons and presynapses on dendrites) were cleaned by querying the identity of the ten nearest synapses to every synapse where each synapse was associated with its closest skeleton node on both the pre- and postsynaptic sides If the majority of the ten nearest neighbors were of the same identity (presynaptic or postsynaptic) If the majority were of an opposing identity these synapses were assigned incorrectly and were deleted This process eliminated 1,975 falsely assigned synapses (~2% of the total) These corresponding points were used to determine an affine transform using the MATLAB least squares solver (mldivide) the intermediate EM stack in the same reference frame as the Z-Brain atlas was used as the template to register the high-resolution EM stack This was performed in a similar manner by selecting corresponding points and fitting an affine transform This transform was used to map the reconstructed skeletons from high-resolution EM space to the reference atlas space We define the periphery as those cells with vanishing (<10−8) eigencentrality but nonzero degree centrality All but 62 of these 2,344 neurons had strictly 0 eigencentrality The remaining 540 recurrently connected neurons are defined as the ‘center’ of the graph See below for the effects of varying the eigencentrality threshold for center–periphery division We applied two graph clustering algorithms to divide the center into two supermodules and obtained similar results from each algorithm. The clustering from the Louvain algorithm is presented in the main text and that of the spectral algorithm in Extended Data Fig. 3 We further subdivided each supermodule into subclusters using an SBM In addition to the Louvain graph clustering algorithm we also clustered the ‘center’ with an alternative graph clustering algorithm We used a generalized spectral clustering algorithm for weighted directed graphs to bisect the zebrafish ‘center’ subgraph, as proposed by Chung39 E) and its weighted adjacency matrix \(A\in {{\mathbb{R}}}_{\ge 0}^{n\times n}\) where Aij indicates the number of synapses from neuron i to neuron j one can construct a Markov chain on the graph with a transition matrix Pα such that \({[{P}_{\alpha }]}_{ij}:= (1-\alpha )\cdot {A}_{ij}/{\sum }_{k}{A}_{ik}+\alpha /n\) The coefficient α > 0 ensures that the constructed Markov chain is irreducible and the Perron–Frobenius theorem guarantees that Pα has a unique positive left eigenvector π with eigenvalue 1 where π is also called the stationary distribution The normalized symmetric Laplacian of the Markov chain is \({\mathcal{L}}=I-\frac{1}{2}\left({\Pi }^{1/2}{P}_{\alpha }{\Pi }^{-1/2}+{\Pi }^{-1/2}{P}_{\alpha }^{\top }{\Pi }^{1/2}\right)\) We modified the directed_laplacian_matrix function in the NetworkX package (https://networkx.github.io) to calculate the symmetric Laplacian for sparse connectivity matrices The spectral gap for the eigenvector centrality subgraph is \({\lambda }_{2}^{{\mathrm{eigen}}}=0.137\) and for the partitioned oculomotor (modO) module is \({\lambda }_{2}^{{\mathrm{eigen}}_{{\mathrm{OM}}}}=0.256\) Categorization of functional cells into cell type was guided by registration to the EM dataset Candidate functional ABD neurons were identified by proximity (6 μm) to any ABD neuron from the registered EM dataset Functional Ve2 neurons were identified by proximity (6 μm) to any Ve2 neuron from the registered EM dataset; because the above restrictions filtered out all of the candidate Ve2 neurons which had very weak sensitivity to spontaneous eye movements in this case we simply used the constraint that these neurons be deemed active in the CaImAn-MATLAB step Candidate VPNI cells were determined to be the remaining cells in R4 to R7/8 that satisfied the above restrictions and were more than 30 μm away from the center of the abducens Comparison of the resulting relative firing rates across neurons in different populations was justified as we observed similar sensor expression levels and baseline noise levels in these populations because the eye position and fluorescence were recorded at different sampling rates we linearly interpolated the values of neuronal activity at the eye position sample times we determined \(\tilde{k}\) as the slope resulting from a linear regression (with offset) to r using E as a regressor Because we do not know the cell’s responsive direction or preferred eye a priori once with movements to the left as positive and once with movements to the right as positive) and used the value of \(\tilde{k}\) that resulted in the highest R2 value Directed connection weights between each pair of neurons were set in proportion to the number of synapses from the presynaptic neuron onto the postsynaptic neuron divided by the total number of synapses onto the postsynaptic neuron \({W}_{ij}=\pm \beta \frac{{N}_{ij}}{{\Sigma }_{k}{N}_{ik}}\) we assume that each element Wij corresponds to the fraction of total inputs to neuron i that are provided by neuron j We then constructed a linear rate model for the network governed by \(\tau \frac{d{r}_{i}}{dt}=-{r}_{i}+{W}_{ij}{r}_{j}\) where ri is the firing rate of the ith neuron and τ is an intrinsic cellular time constant τ for ABD and Ve2 neurons was fixed at 100 ms The scale factor β and the intrinsic time constant τ for the remaining putative VPNI neurons then provided two free parameters that could be used to set the timescale of persistence for the leading two eigenvectors of the network For a given choice of scale factor and VPNI neuron time constant we simulated the response of the network to a random pulse of excitatory input and compared the time course of the leading principal components of the simulated network to that of the calcium imaging data These parameters were tuned so that the simulations roughly matched the decay times of the leading two principal components in the data resulting in an intrinsic VPNI neuron time constant of 1 s and a scale factor set such that the leading eigenvalue of the network was equal to 0.9 These free parameters of the network model were not finely tuned and the precise values used are not critical to the results obtained here For both the simulated network and the calcium imaging data we fit each neuron’s firing rate during the period between 2 s and 6 s following a saccade to a double exponential function \(r(t)={a}_{1}{e}^{-t/{\tau }_{1}}+{a}_{2}{e}^{-t/{\tau }_{2}}\) where the time constants were fixed at 10 s and 4 s leaving the amplitudes of each exponential as the only free parameters These time constants were chosen because a simulated network with leading eigenvectors having these time constants had principal components of its neuronal firing rates that consisted of mixtures of exponentials whose summed time courses approximately matched those of the leading two principal components of the data We found that the correlation between these two amplitudes in simulation better matched the correlation seen in the data when the saccadic input consisted of fixed and random components The exact number of leading eigenvectors included in the fixed component is not important to achieve this tuning of the correlation between a1 and a2 We chose to use the leading three eigenvectors because the eigenvalues associated with them were clearly separated from the central disk of eigenvalues we briefly summarize factors relevant for rigor and reproducibility that have been addressed in more detail elsewhere in the manuscript Reconstructions were semiautomated and validated (and if necessary corrected) by in-house image analysis experts Synapses were automatically segmented with a convolutional network that was 95% accurate when tested on ground truth data; an error correction step checking for preidentity/postidentity eliminated 2% of the total During subsequent analysis of connectivity Randomization was used extensively in determination of modular organization Investigators were not blinded during these analyses Fluorescence microscopy data were previously acquired from 20 animals50 No statistical method was used to predetermine sample size A one-way ANOVA (with multiple comparison correction; normality was assumed) on STA activity was used to identify activity of significance Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article Raw EM images, segmentation information, neuronal skeletons and identified synapse data are 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R01 EY021581 and Simons Foundation Global Brain Initiative (E.R.F.A NIH-NINDS Brain initiative award 5U19NS104648 (M.S.G.) Intelligence Advanced Research Projects Activity via Department of Interior/Interior Business Center contract number D16PC0005 and assistance from Google decision to publish or preparation of the manuscript The US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon Present address: Center for Computational Neuroscience Present address: Department of Physiology and Pharmacology These authors contributed equally: Alex Sood These authors jointly supervised this work: H Institute for Computational Biomedicine and the Department of Physiology and Biophysics Department of Ophthalmology and Vision Science performed registration and data analysis and wrote the paper Sood designed and conceptualized the computational model performed data analysis and interpretation and wrote the paper developed the code for data generation and curation in Eyewire registered and analyzed the light microscopic data and interpreted the data performed the clustering algorithm comparisons performed synapse detection and partner assignment developed Eyewire algorithms and data manipulation software developed Eyewire algorithms and performed Eyewire system administration performed Eyewire moderation and data curation designed and conceptualized the computational model Eyewirers performed neuron reconstruction online The remaining authors declare no competing interests Nature Neuroscience thanks the anonymous reviewers for their contribution to the peer review of this work Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations a. Connectivity matrix (as in Fig. 2) with identification (arrows) of small RS neurons that were part of the center and inclusion into the periphery of the remaining small RS neurons along with the large RS neurons Visualization of the large and small classes of RS neurons in the periphery (ro - rostral; c - caudal; m - medial; l - lateral) Visualization of small vSPNs that are part of the ‘center’ in modA and are indicated by arrows above the rows in a Histogram of neuronal pathlength in modA (n = 251) and modO (n = 289) for all cells (left) those with somata in the reconstructed volume (middle) and those with somata outside the reconstructed volume (right) p is the significance value based on a two-sided Wilcoxon-rank sum test (RS-test) Histogram of synaptic size (detected PSD voxels [vx]) for connections within (left) and between (right) modules modA and modO Table (here and below) summarizes the mean and standard deviations distance from somata to synaptic site along the neurite Histogram of synapse sizes (detected PSD) of neurons within-module (left) and between-modules (right) for modOI and modOM Histogram of synapse locations for neurons within the oculomotor modules modOI and modOM Connectivity when the center is organized by spectral clustering into two modules Normalized number of synapses within and between relevant cell groups Connectome for modO and its connections to the abducens with the eigencentrality threshold for inclusion in the center raised to exclude 25% of the cells that were previously included in the center Cells are ordered by block identity after fitting a stochastic block model with 8 blocks an eighth block was needed to sequester the vestibular cells into their own block Colored rectangles highlight two cycles in the block structure one connecting primarily to ABDM (orange) and the other primarily to ABDI(purple) Association matrix for block assignments when segmentation of the center is repeated 100 times after random addition and deletion of synapses according to the estimated precision and recall of synapse detection (see Methods) a random variation of the connectome caused 0.5% of neurons to change block assignments Each dot indicates the presence of one or more synapses between two cells in the center network or from a cell in the center to a cell in the periphery determined by using Louvain clustering to split the center into an axial module (modA) and an oculomotor module (modO) followed by Stochastic Block Modeling to find substructure in each module Simulated firing rates for three neurons in response to a sequence of three simulated saccades at intervals of seven seconds (see Methods) Each trace is normalized to the peak firing rate reached by that neuron during the first fixation Error bars on the cumulative variance explained (mean) show the standard deviation across the 100 random variations of the network but for the variations of the network used in b middle) and eigenvalues (bottom) for 100 networks in which all synapses within modO were shuffled while maintaining the in-degree and out-degree of each cell the position sensitivities of all shuffled networks (green) are compared to the actual network (gray) for each cell class (VPNI shuffled networks (x-axis) are compared to the actual network (y-axis) on a cell-by-cell basis with the colors indicating which block each cell belonged to and opacity indicating the relative frequency of the eye position sensitivities produced for each cell across all of the shuffles Same as a except that modO was partitioned into two blocks using a stochastic block model (SBM) and each group of synapses within each block and between each pair of blocks was shuffled separately but with ModO split into two sub-blocks (b) or seven sub-blocks (c) using a stochastic block model Synapses were shuffled separately for each possible pairing of presynaptic block and postsynaptic block Stimulating a complex mode of a network gives rise to a linear combination of two spatial patterns of activity one corresponding to the real part of the eigenvector and one corresponding to the imaginary part The level of activity in each pattern oscillates over time while the overall amplitude decays so that each neuron follows a trajectory of the form Ae−ηt sin (ωt + φ) If the decay is fast enough relative to the frequency of oscillation as occurs for the complex modes of the internuclear and motor cycles oscillations will not be evident in the single-neuron firing rates for the complex mode of the internuclear cycle a range of potential single-neuron firing rate trajectories corresponding to different phase offsets from zero initial activity (purple) to maximal initial activity (blue) Download citation DOI: https://doi.org/10.1038/s41593-024-01784-3 Anyone you share the following link with will be able to read this content: a shareable link is not currently available for this article Sign up for the Nature Briefing newsletter — what matters in science The brain region that controls eye movement is structurally similar in fish and mammals but the zebrafish system contains only 500 neurons Working with week-old zebrafish larva, researchers at Weill Cornell Medicine and colleagues decoded how the connections formed by a network of neurons in the brainstem guide the fishes’ gaze. The study found that a simplified artificial circuit based on the architecture of this neuronal system In addition to shedding light on how the brain handles short-term memory the findings could lead to novel approaches for treating eye movement disorders Organisms are constantly taking in an array of sensory information about the environment that is changing from one moment to the next the brain must retain these informational nuggets long enough to use them to form a complete picture—for instance linking together the words in a sentence or allowing an animal to keep its eyes directed to an area of interest “Trying to understand how these short-term memory behaviors are generated at the level of neural mechanism is the core goal of the project,” said senior author Dr. Emre Aksay associate professor of physiology and biophysics at Weill Cornell Medicine Mark Goldman at the University of California Davis and Dr To decode the behavior of such neuronal circuits neuroscientists use the tools of dynamical systems This involves building mathematical models that describe how the state of a system changes over time where the current state determines its future states according to a set of rules will remain in a single preferred state until a new stimulus comes along causing it to settle into a new activity state each of these states can store the memory of where an animal should be looking But what parameters help to set up that type of dynamical system One possibility is the anatomy of the circuit: the connections that form between each neuron and how many connections they make Another likely possibility is physiological strength of those connections which is established by a myriad of factors like the amount of neurotransmitter being released the type of synaptic receptors and the concentration of those receptors To understand the contributions from circuit anatomy Aksay and his collaborators looked to larval zebrafish these fishlets are swimming around and hunting prey a skill that involves sustained visual attention the brain region that controls the animals’ eye movement is structurally similar in fish and mammals But the zebrafish system contains only 500 neurons we can analyze the entire circuit—microscopically and functionally,” Dr “That’s very difficult to do in other vertebrates.” Using an array of advanced imaging techniques Aksay and colleagues identified the neurons that participate in controlling the animals’ gaze and then determined how these neurons are wired together They discovered that the system consists of two prominent feedback loops each containing three clusters of tightly connected cells The researchers used this distinctive architecture to build a computational model They found that their artificial network could accurately predict activity patterns of the zebrafish circuit which they validated by comparing their results to physiological data I was surprised how much of the behavior of the circuit we could predict from the anatomical architecture alone.” the researchers will explore how the cells in each cluster contribute to the behavior of the circuit—and whether the neurons in the different clusters have distinct genetic signatures Such information could allow clinicians to therapeutically target those cells that may malfunction in eye movement disorders The findings also provide a blueprint for unraveling the more complex computational systems in the brain that rely on short-term memory such as those involved in deciphering visual scenes or understanding speech This study was supported in part by the National Institutes of Health grants from the National Institute of Neurological Disorders and Stroke R01 NS104926 and Brain initiative award 5U19NS104648; the National Eye Institute R01 EY027036 R01 EY021581 and K99 EY027017; and the National Cancer Institute UH2 CA203710 Back to News Follow me: X/ Twitter, Telegram and Facebook Yusuf Güner Aksay, a 41-year-old former teacher who was dismissed from his job by a government decree as part of a post-coup purge in Turkey, has died of brain cancer in the southern province of Mersin, the Kronos news website reported on Sunday Aksay’s death was announced on social media by opposition deputy and human rights advocate Ömer Faruk Gergerlioğlu Yine KHK, yine ölüm!Mersin-Tarsus-Olukkoyağıda Yusuf sınıf öğretmeni KHK'li Güner Aksay kolon kanseri ile verdiği mücadeleyi kaybetti, cenaze namazı bugündü.Eşi de KKHlıydı. 2 çocuğu vardı. Cezaevinde 60 ay kaldı, yatarını bitirdi ve tahliye sonrası kansere yakalanmıştı. pic.twitter.com/PuymJT3OGz Reports also said he was sentenced by a court to more than seven-and-a-half years in prison over his alleged links to faith-based Gülen movement His wife was also dismissed from her job by a government decree Aksay was one of the more than 100,000 civil servants summarily dismissed from their jobs as part of the Turkish government’s response to a failed military coup in July 2016 The government declared a state of emergency that lasted for two years during which a series of executive decree-laws saw the mass dismissal of civil servants without due process In addition to being removed from their jobs and permanently excluded from civil service the decree-laws also had secondary implications such as being flagged on the social security databases in a way that intimidates potential private sector employers and travel bans preventing victims from seeking employment abroad Those dismissed were also deprived of any meaningful legal remedy and a review commission set up by the government in the face of international pressure was slammed by human rights groups due to its lack of independence from political influence and its opaque review procedures The treatment of the purge victims has been described as “civil death.” Turkish President Recep Tayyip Erdoğan has been targeting followers of the Gülen movement inspired by Turkish Muslim cleric Fethullah Gülen since the corruption investigations of December 17-25 which implicated then-prime minister Erdoğan Dismissing the investigations as a Gülenist coup and conspiracy against his government Erdoğan designated the movement as a terrorist organization and began to target its members He intensified the crackdown on the movement following the 2016 abortive putsch that he accused Gülen of masterminding Gülen and the movement strongly deny involvement in the coup attempt or any terrorist activity In addition to the thousands who were jailed scores of other Gülen movement followers had to flee Turkey to avoid the government crackdown traverses have become one of the dominant ways of getting your name in the history books That’s what happened in Kyrgyzstan last month when a three-person team completed the first-ever traverse of the “Aksay horseshoe,” enchaining 15 peaks in the Tien Shan Mountains in a single The achievement was announced on the Russian climbing site Mountain.ru. Climbers Tikhon von Stackelberg and Roman Abildaev, led by Egor Matveenko, completed the traverse between Feb They started with the ascent of Box Peak (4,240m) on the Mikhailov route and finished with the peak of Semyonov-Tyan-Shansky (4,875m) but a guiding website said that the Aksay Glacier and its surrounding mountains offer some of Kyrgyzstan’s best hiking and climbing According to Mountain.ru, the horseshoe traverse completed last month includes the following peaks. The numbers correspond to a panoramic photo posted on the site and visible in the above Facebook post. (Russian climbing grade scale and explanation available here.) An award-winning journalist and photographer Andrew McLemore brings more than 14 years of experience to his position as Associate News Editor for Lola Digital Media climber and traveler who currently lives in Medellin he’s hanging out with his dog Campana Sign up to receive ExplorersWeb content direct to your inbox once a week School of Engineering and Applied SciencePrinceton The International SAMBO Federation (FIAS) is a non-governmental non-profit organization that unites National SAMBO Federations FIAS is the only internationally recognized organization responsible for the development of SAMBO worldwide The FIAS website regularly features SAMBO news as well as SAMBO videos and photos from SAMBO competitions It also includes the official competition calendar of the International SAMBO Federation and other documents regulating tournaments in Sport SAMBO The dates displayed for an article provide information on when various publication milestones were reached at the journal that has published the article activities on preceding journals at which the article was previously under consideration are not shown (for instance submission All content on this site: Copyright © 2025 Elsevier B.V. Metrics details Aksay Kazakhs are the easternmost branch of Kazakhs the genetic diversity of Aksay Kazakhs and its relationships with other Kazakhs still lack attention we analyzed the non-recombining portion of the Y-chromosome from 93 Aksay Kazakhs samples using a high-resolution analysis of 106 biallelic markers and 17 STRs The lowest haplogroup diversity (0.38) was observed in Aksay Kazakhs among all studied Kazakh populations The social and cultural traditions of the Kazakhs shaped their current pattern of genetic variation Aksay Kazakhs tended to migrate with clans and had limited paternal admixture with neighboring populations Aksay Kazakhs had the highest frequency (80%) of haplogroup C2b1a3a1-F3796 (previous C3*-Star Cluster) among the investigated Eurasian steppe populations which was now seen as the genetic marker of Kerei clan NETWORK analysis indicated that Aksay Kazakhs originated from sub-clan Kerei-Abakh in Kazakhstan with DYS448 = 23 TMRCA estimates of three recent descent clusters detected in C2*-M217 (xM48) network one of which incorporate nearly all of the C2b1a3a1-F3796 Aksay Kazakhs samples respectively; this is coherent with the 7th to the 11th centuries Altaic-speaking pastoral nomadic population expansion the Kazakhs lived in dome shaped felt tents called yurts present Kazakhs took up a semi-nomadic or sedentary lifestyle with only some Kazakhs maintaining the seasonal migrations The Kazakhs’ marriage system is monogamy in a patrilocal and exogamous way The genetic relationships of Aksay Kazakhs with other Kazakhs still lack attention we collected and tested 93 male Kazakh samples from Aksay Kazakh autonomous county in northwestern China Map with the sampling points of Aksay Kazakhs and other studied Kazakhs The distributions of the Kazakhs are shown in gray The phylogenetic relationship of Y-chromosome haplogroups surveyed in this study and their frequencies in the studied Kazakhs is exhibited in the lower half of the figure The marker names are shown along the branches and haplogroup names are shown on the right side according to ISOGG Y-DNA Haplogroup Tree 2018 Potentially paraphyletic undefined subgroups are distinguished from recognized haplogroups by the asterisk symbol Phylogenetic relationship between Aksay Kazakhs and reference populations analyzed by PCA with the frequencies of haplogroups Reduced Median joining network of Y-chromosome haplogroups C3*-M217(xM48) (a) and haplogroup C2a1a3-M504+s (b) Haplotypes are represented by circles with area proportional to the number of individual Different matrilineal contributions to genetic structure of ethnic groups in the silk road region in China Y-chromosome variation in Altaian Kazakhs reveals a common paternal gene pool for Kazakhs and the influence of Mongolian expansions Genetic variation in the enigmatic Altaian Kazakhs of South-Central Russia: insights into Turkic population history History of the Kazakhs in the Gansu province of China The Y-chromosome C3* Star-Cluster Attributed to Genghis Khan’s Descendants is Present at High Frequency in the Kerey Clan from Kazakhstan Mitochondrial and Y-chromosomal profile of the Kazakh population from East Kazakhstan A genetic landscape reshaped by recent events: Y-chromosomal insights into central Asia Development of the Kazakhstan Y-chromosome haplotype reference database: analysis of 27 Y-STR in Kazakh population cultural and geographic landscapes of transoxiana Genetic structure of qiangic populations residing in the western Sichuan corridor Present Y Chromosomes Refute the Roma/Gypsy Origin of the Xuejiawan People in Northwest China LI Hui (eds) Languages and Genes in Northwestern China and Adjacent Regions Hu K, Yan S, Liu K, Ning C, Wei LH, Li SL, et al. The dichotomy structure of Y chromosome Haplogroup N. arXiv:1504.06463 https://arxiv.org/abs/1504.06463v1 (2015) The effective mutation rate at Y chromosome short tandem repeats with application to human population-divergence time Zhang D, Cao G, Xie M, Cui X, Xiao L, Tian C, et al. Y Chromosomal STR haplotypes in Chinese Uyghur, Kazakh and Hui ethnic groups and genetic features of DYS448 null allele and DYS19 duplicated allele. Int J Legal Med. https://doi.org/10.1007/s00414-019-02049-6 (2019) Whole-sequence analysis indicates that the Y chromosome C2*-Star Cluster traces back to ordinary Mongols Phylogeography of the Y-chromosome haplogroup C in northern Eurasia Whole sequence analysis indicates a recent southern origin of Mongolian Y-chromosome C2c1a1a1-M407 Phylogeny of Y-chromosome haplogroup C3b-F1756 an important paternal lineage in Altaic-speaking populations Y-chromosome descent clusters and male differential reproductive success: young lineage expansions dominate Asian pastoral nomadic populations Inner Asian states and empires: theories and synthesis Annals of the autonomous prefecture of Aksai Kazaks Lanzhou: Gansu People’s Publishing House (1993) Simple study of the national characteristics Kazak Islamic religion Download references We are grateful for the trust of the sample donors This work was supported by National Social Science Foundation of China (19VJX074) Scientific and Technology Committee of Shanghai Municipality (18490750300) National Natural Science Foundation of China (91731303 Innovation Team Project of Fundamental Research Funds for the Central Universities (31920190030) These authors contributed equally: Shao-Qing Wen MOE Key Laboratory of Contemporary Anthropology and B&R International Joint Laboratory for Eurasian Anthropology Key Laboratory of Evidence Science of Gansu Province Gansu Institute of Political Science and Law China University of Political Science and Law Medical College of Northwest Minzu University The authors declare that they have no conflict of interest Download citation DOI: https://doi.org/10.1038/s10038-020-0759-1 The conflicts on this part of the Kyrgyz-Tajik border have become chronic but there is no progress in resolving this issue yet Follow us on LinkedIn  The presidents of Tajikistan and Kyrgyzstan are preparing for a meeting, during which issues of accelerating the demarcation and delimitation of the disputed parts of the joint border will be discussed. The exact date and place of the event is not reported by their representatives yet. It is known that Jeenbekov will travel to Tajikistan with a working visit, where negotiations on bilateral border cooperation are going to take place. On the eve of this meeting on July 22 at the Aksay – Voruh area, another conflict occurred between the residents, which resulted in the death of one citizen of Tajikistan and hospitalization of wounded people from both sides, including police officers and border guards. Since July 22, the Voruh – Isfara highway, which connects the Tajik enclave with its main territory, has been blocked by the residents of the Kyrgyz village of Aksay. In response, the military of Tajikistan blocked the Batken – Leilek highway, which passes through the territory of Tajikistan. According to the results of the meeting of the heads of the border agencies and the Ministry of Internal Affairs of the two republics, now, law enforcement agencies of Tajikistan and Kyrgyzstan are jointly patrolling the border, where the situation is stable. On the Aksai-Voruh area, conflicts occur annually between local residents due to the absence of the clear borderline. Despite the latest incident, the scheduled meeting of the two leaders will take place. Below we present a commentary by a political scientist from Bishkek, Emil Juraev, prepared on this issue: Bishkek did not forget about its villages in a remote region for so long, but it also leaves these areas of the Batken region with a lower level of attention, with a lower priority compared to larger areas. The Batken events of 1999 and 2000, because of which the Batken region itself was created, became a kind of an alarm clock and the authorities began to pay more attention to this area. At the moment, there are almost no realistic approaches to solving controversial issues along the border line. Leaving everything as it is, just trying to agree meters and centimeters of the border and drawing the dividing line, even if it is conceivable – it means many controversial issues on water, roads, pastures and other needs that will remain and continue to arise. To reconcile any exchange of territories, so that some villages can be completely relocated to new places and thus solve the issue of enclaves and other difficulties, is also an almost impossible option, entailing both cost and extreme resistance or dissatisfaction of the inhabitants affected by this exchange. It would be extremely disadvantageous for Kyrgyzstan to allocate a small territory in order to give way to the village of Voruh to connect with the main territory of Tajikistan – and it would leave the conflict potential of this area as it is. For a more complex and civilized resolution of the issue – so that the two countries and especially the residents of these areas do not need to line the borders, but live an interconnected, peaceful and good life, it will take even more. First, it is needed to ensure the economic and social development of these areas on a high level, to provide good quality of education, public and legal order, and the build the entire necessary infrastructure. Establishing peace and resolving these disputes, therefore, will require not only technical work, or only economic, but also sociable: neighboring communities will have to learn to accept each other with respect and trust, and not as enemies. This article was prepared as part of the Giving Voice, Driving Change – from the Borderland to the Steppes Project implemented with the financial support of the Foreign Ministry of Norway. The opinions expressed in the article do not reflect the position of the editorial or donor. notify us by selecting that text and pressing Ctrl+Enter Researchers at Weill Cornell Medicine have identified a population of neurons that drive animal brains to initiate actions without prompting from an external stimulus such as food or prey The preclinical finding is a significant step toward solving what has been one of the big unanswered questions in neuroscience The study, published July 6 in Nature Communications used advanced experimental techniques to monitor the activities of the neurons in larval zebrafish while also monitoring the fishes’ eye movements This approach allowed the investigators to identify neurons that are involved in triggering self-initiated scanning eye movements called saccades Prior studies in humans and animals have shown that decisions in response to stimuli are often preceded by changes in the firing rates of particular neurons after which the action occurs – suggesting that a certain level of massed neuronal activity is required for the brain’s “decision” to initiate action But experimentally demonstrating that this ramping of neuronal activity doesn’t merely precede an action but also triggers it has been more challenging especially when the action is internally generated rather than influenced by external stimuli “In this study we were able not only to identify neurons whose activity ramps before spontaneous eye movements, but also to demonstrate for the first time that such ramp activity actually initiates self-driven behavior,” said first author Dr. Alexandro Ramirez, a postdoctoral research associate in the laboratory of Dr. Emre Aksay an associate professor of physiology and biophysics at Weill Cornell Medicine Zebrafish are popular lab animals for biological research because they are easy to keep and study and have a quick life cycle compared to larger species such as mice their larvae have relatively transparent brains that are highly accessible to modern microscopic imaging while having a manageable number of neurons Ramirez and Aksay and their colleagues used advanced techniques including a high-resolution microscopy method called two-photon imaging to monitor the activities of all neurons in the hindbrain which prior studies have implicated in eye movements use intermittent saccades to scan their surroundings and these seemingly spontaneous eye movements happen even in the dark The researchers mapped the activity patterns in hundreds of thousands of hindbrain neurons in several individual zebrafish larvae and identified a specific set of these neurons whose activity reliably ramps up in the seconds prior to a saccade The scientists then showed that when they inactivated these pre-saccade neurons subsequent saccades were delayed – implying that these neurons are involved in initiating saccades and also suggesting that removal of these neurons reduced the brain’s ability to reach the needed threshold level of massed activity The findings on their own help demonstrate the causal role of ramping neurons in actions such as saccades but also demonstrate the broad potential of the zebrafish model for teasing apart the neural circuitry of volitional “We can observe and manipulate brain cells in real time with this system and that should allow us in time to get at the detailed cellular and circuit mechanisms that give rise to this pre-action ramping activity,” said Aksay who is also an associate professor of computational neuroscience in computational biomedicine in the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud Institute for Computational Biomedicine at Weill Cornell Medicine The researchers also hope eventually to set up a screening system to find small molecules that can enhance or inhibit the functions of specific sets of pre-action ramping neurons “Decision-making circuits similar to the one we examined in this study are involved in a range of behaviors including those involving higher cognitive functions that are impaired in diseases such as attention-deficit hyperactivity disorder,” Aksay said “Further understanding of the mechanisms by which this ramping activity arises and can be manipulated will foster treatments for disorders of volitional control.” Jim Schnabel is a freelance writer for Weill Cornell Medicine Get Cornell news delivered right to your inbox Eighteen Princeton University faculty members were transferred to emeritus status in recent action by the Board of Trustees Kofi Agawu has advanced the study of music across genres His research spans the disciplines of music scholarship to encompass music theory and analysis His subjects of inquiry include a broad swath of music — from works by Mozart and Mahler to Schubert and Stravinsky as well as the music of the Ewe people of his native Ghana He joined the Princeton faculty in 1998; in the 2006-07 he spent the academic year teaching at Harvard University He is the author of “Playing With Signs: A Semiotic Interpretation of Classical Music,” the landmark study “African Rhythm: A Northern Ewe Perspective,” “Representing African Music: Postcolonial Notes Agawu has served as director of graduate studies; mentored students in music history and ethnomusicology; and attracted scores of undergraduates to his courses on African music Behrman Award for Distinguished Achievement in the Humanities He earned his bachelor’s degree from the University of Reading University a master’s degree from King’s College London and a Ph.D Ilhan Aksay is a leading researcher in the science and technology of materials processing He earned his undergraduate degree from the University of Washington-Seattle and his Ph.D from the University of California-Berkeley he joined the Princeton faculty as professor in the (then called) Department of Chemical Engineering Aksay has a history of groundbreaking research throughout his career He was the principal force behind the measurement and understanding of phase equilibria in the Al2O3-SiO2 system in the 1970s colloidal processing of ceramics in the 1980s and bio-inspired processing of materials through self-assembly in the 1990s an invention led by Aksay and his Princeton colleague focused his attention on fundamental studies of the properties of these systems and their utility in engineering applications Many of his scientific studies have resulted in patents (more than 50 U.S patents issued on key aspects of his work) and been licensed by companies such as Dow Chemical His depth of understanding of fundamental issues and an innovative approach to problem solving have enabled him to tackle challenging problems in important emerging materials technology areas such as ceramic armor and high-temperature superconductors Douglas Arnold has broad research interests in American politics with special interests in congressional politics He is one of the nation’s leading congressional scholars He is the author of three core research books: “Congress and the Bureaucracy: A Theory of Influence,” “The Logic of Congressional Action” and “Congress the Press and Political Accountability.” He is the editor and contributor to two books on the future of Social Security and remains actively engaged in research on this area of public policy In addition to his service to the politics department Arnold directed two graduate programs in the Woodrow Wilson School He earned his bachelor’s degree from Union College and his Ph.D was founding director of the University’s Andlinger Center for Energy and the Environment and served as dean of the School of Engineering and Applied Science since 2016 She earned an undergraduate degree from the University of California-Berkeley and her Ph.D from the California Institute of Technology Carter has earned wide recognition for fundamental research contributions as well as for her vision for harnessing science and policy to produce lasting solutions to societal problems including those of energy and the environment Her research spans the fields of chemistry applied mathematics and engineering and has included creating quantum mechanical tools for understanding and analyzing the behaviors of large numbers of atoms and electrons in materials This highly influential work led in recent years to Carter’s research on creating effective fuel cells using sunlight to generate electricity and make liquid fuels from carbon dioxide and water and investigating lightweight metal alloys for vehicles and fusion reactor walls Carter is a member of the National Academy of Sciences She has written more than 300 scientific publications and delivered 500 invited and plenary lectures worldwide Among her most cited works are her pioneering advances in “orbital-free density functional theory,” which allow the study of the quantum mechanical interactions of a large number of atoms in a way that was previously impossible Such work is critical in developing new materials and relating the atomic-level structure of materials with their large-scale performance She will become the executive vice chancellor and provost of the University of California-Los Angeles Thomas Funkhouser is one of the world's foremost experts in computer graphics pioneering the use of computers to analyze human-computer interaction and machine learning He earned his bachelor’s degree from Stanford University and his Ph.D he has been exploring how the machine learning revolution can be extended to 3-D shapes: how deep neural networks can be trained to understand both the details and the overall structure of 3-D environments including how to predict what might be hidden in parts of the scene that cannot be observed directly He is a fellow of the Association for Computing Machinery (ACM) as well as the ACM SIGGRAPH Academy and has received numerous honors and awards including the ACM SIGGRAPH Computer Graphics Achievement Award Sloan Fellowship and the National Science Foundation CAREER Award especially in relation to inequality and public policy He is the author of “Affluence & Influence: Economic Inequality and Political Power in America” and “Why Americans Hate Welfare: Race Media and the Politics of Anti-Poverty Policy,” and co-author (with Benjamin Page) of “Democracy in America What Has Gone Wrong and What We Can Do About It.” Much of his research has been published in the most selective outlets in political science as well as widely recognized outside the discipline He is a member of the American Academy of Arts and Sciences and his work has been supported by nearly all of the most selective social science grants and fellowships available to scholars of American politics He has held fellowships at the Institute for Advanced Study in Princeton the Center for Advanced Study in the Behavioral Sciences at Stanford and the Russell Sage Foundation His work is influential and esteemed in and out of the academy and has garnered attention from leading news outlets around the globe and across the political spectrum Gilens earned his bachelor’s degree from the University of California-Santa Cruz and his Ph.D Carol Greenhouse focuses her research on the discursive and experiential dimensions of state power especially federal power in the United States and the reflexive and critical connections — in the U.S and elsewhere — between ethnography and democracy She joined the Princeton faculty in 2001 and is a recipient of the President’s Award for Distinguished Teaching “Praying for Justice: Faith Order and Community in an American Town,” was one of the inaugural texts in contemporary American legal studies within the discipline of anthropology legal anthropology focused primarily on cultures outside the United States Greenhouse is also the author of “The Paradox of Relevance: Ethnography and Citizenship in the United States,” “Transnational Law: Cases and Problems in an Interconnected World” (with Alfred Aman Jr) and “Law and Community in Three American Towns” (with Barbara Yngvesson and David Engel); as well as edited volumes “Democracy and Ethnography: Constructing Identities in Multicultural Liberal States” and “Ethnography in Unstable Places: Everyday Life in Contexts of Dramatic Political Change” (with Elizabeth Mertz and Kay Warren) Her forthcoming book is “Landscapes of Law: Practicing Sovereignty in Transnational Terrain” (co-edited with Christina Davis) She is a member of the American Philosophical Society and the American Academy of Arts and Sciences Hendrik “Dirk” Hartog is a leading historian of law and has spent his scholarly life focused on the difficulties and opportunities that come with studying how broad political and cultural themes have been expressed in everyday legal conflicts He has worked in a variety of areas of American legal history: on the history of city life on the history of constitutional rights claims on the history of slavery and emancipation and on the historiography of legal change and of legal history He is the author of “Public Property and Private Power: the Corporation of the City of New York in American Law 1730-1870,” “Man and Wife in America: a History,” “Someday All This Will Be Yours: A History of Inheritance and Old Age,” and “The Trouble with Minna: A Case of Slavery and Emancipation in the Antebellum North.” He was affiliated with Princeton’s Program in Law and Public Affairs and from 2006-15 he directed Princeton’s Program in American Studies diversifying the scope and content of American studies on multiple levels He received the President’s Award for Distinguished Teaching in 2011 and the Graduate Mentoring Award in 2018.  from New York University School of Law and his Ph.D Jeremy Kasdin is a leading researcher in the areas of space systems design He is co-chair of the Science Definition Team for the Wide Field Infra-Red Survey Telescope (WFIRST) mission and adjutant scientist for the Coronagraph Instrument He has accepted a position at the University of San Francisco and will be named the Eugene Higgins Professor of Mechanical and Aerospace Engineering Kasdin joined the Princeton faculty in 1999 he initiated an interdisciplinary group that drew from many areas including astrophysics as well as the Institute for Advanced Study in Princeton which met weekly to brainstorm about searching for Earth-like planets The coronagraph approach to planet imaging was an outcome of these conversations and it inspired NASA to change its perspective on the best method for exoplanet imaging.  Jeremy also had an affiliated appointment in the Department of Astrophysical Sciences Jeremy led a collaborative team investigating high-contrast imaging techniques for detecting and characterizing terrestrial exoplanets That group has pioneered the use of pupil-plane coronagraphs and external occulters for space-based imaging The Princeton team also developed some of the key techniques for wavefront control with a coronagraph He earned his bachelor’s degree from Princeton and his Ph.D as the number of undergraduates concentrating in computer science grew from 25 per year to more than 160 LaPaugh was one of the professors who organized and coordinated the advising of undergraduate independent work and served effectively as departmental representative from 2014-18 running the largest undergraduate concentration in the University’s history She also served 2000-04 as the head of Forbes College during which time she participated in the planning for Princeton’s transition to the four-year residential college system Anson Rabinbach is a specialist in modern European history with an emphasis on intellectual and cultural history who has served on Princeton’s faculty since 1996 He has published extensively on Nazi Germany Austria and European thought in the 19th and 20th centuries He earned his bachelor’s degree from Hofstra University and his Ph.D He is the author of “The Crisis of Austrian Socialism: From Red Vienna to Civil War 1927-1934,” “The Human Motor “In the Shadow of Catastrophe: German Intellectuals Between Enlightenment and Apocalypse” and “The Third Reich Sourcebook (with Sander Gilman) He helped co-found the journal New German Critique in 1974 and served for many years on the editorial board of Dissent magazine His current research is on concepts invented in the 20th century It emphasizes World War II exchanges between European and American intellectuals Harvey Rosen helped shaped the field of public finance as a researcher author and professor at Princeton for 45 years He also has served as the director of the Center for Economic Policy Studies at Princeton He has published over 80 academic articles many in the leading journals of economics.  His research interests span numerous areas in public finance including the effects of taxation on labor supply He wrote two undergraduate textbooks, “Microeconomics” (with Michael Katz) and “Public Finance.” Rosen served at the Treasury Department as the deputy assistant secretary (tax analysis) in the first Bush administration he served on the President’s Council of Economic Advisers in the second Bush administration he received the National Tax Association’s most prestigious award Holland Medal for distinguished lifetime contributions to the study and practice of public finance which opened as Princeton's sixth residential college in fall 2007 He was a member of the Four-Year College Program Planning Committee helping to develop the blueprint for the new system He earned his bachelor’s degree from the University of Michigan and his Ph.D Jorge Sarmiento studies and models ocean circulation and the impacts of circulation and metabolism on the oceanic distribution of those elements involved in biological cycles (primarily CO2 He came to Princeton as a 1978 as a research associate and became a faculty member in 1980 he also serves as the director of the Southern Ocean Carbon and Climate Observations and Modeling Program (SOCCOM) a six-year NSF funded program established in 2014 with scientists at eight American institutions and multiple foreign collaborators SOCCOM members are engaged in observing and modeling the physical circulation of the Southern Ocean and the large-scale processes linking biological carbon fluxes and ocean chemistry providing information about the nature and activity of Southern Ocean ecosystems He was the long-time director of the Program in Atmospheric and Oceanic Sciences at Princeton and the director and scientific leader of the Cooperative Institute for Climate Science a collaboration between Princeton and NOAA and the Cooperative Institute for Modeling the Earth System Sarmiento is co-author (with Nicolas Gruber) of the graduate textbook “Ocean Biogeochemical Dynamics.” He served as an associated faculty member with the Andlinger Center for Energy and the Environment the Department of Civil and Environmental Engineering He earned his bachelor’s degree from Swarthmore College and his Ph.D David Spergel is an astrophysicist with research interests ranging from the search for planets around nearby stars to the shape of the universe He joined the faculty in 1987 and received the President’s Award for Distinguished Teaching in 2013 Using microwave background observations from the Wilkinson Microwave Anisotropy Probe (WMAP) Satellite and the Atacama Cosmology Telescope These observations have played a significant role in establishing the standard model of cosmology He is one of the leaders of the Simons Observatory which will include a planned millimeter-wave telescope that will enable the next step in studying the microwave sky and probing the history of the universe Spergel is co-chair and is shaping the overall mission of the Wide Field Infrared Survey Telescope (WFIRST) science team which will study the nature of dark energy complete the demographic survey of extrasolar planets characterize the atmospheres of nearby planets and survey the universe with more than 100x the field of view of the Hubble Space Telescope He is an associate faculty member in the Department of Physics Spergel was awarded a MacArthur Foundation grant in 2001 and is the recipient of the 2010 Shaw Prize and the 2015 Dannie Heineman Prize for his breakthroughs in our understanding of the universe he received the Breakthrough Prize in Fundamental Physics as well as NASA’s Exceptional Public Service Medal awarded to any nongovernment individual for important contributions to NASA projects He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences Jacqueline Stone is an internationally acclaimed leader in the study of Japanese Buddhism Her current research areas include death and dying in Buddhist cultures and traditions of the “Lotus Sutra,” particularly Tendai and Nichiren She is the author of “Original Enlightenment and the Transformation of Medieval Japanese Buddhism,” and “Right Thoughts at the Last Moment: Buddhism and Deathbed Practices in Early Medieval Japan.” She has co-edited “The Buddhist Dead: Practices “Readings of the Lotus Sutra” (with Stephen F Suzuki Professor in Buddhist Studies at Princeton) she was elected to the American Academy of Arts and Sciences she received a President’s Award for Distinguished Teaching from Princeton She earned her bachelor’s degree from San Francisco State University and her Ph.D James Stone is a leading researcher on the use of large-scale direct numerical simulations to study the gas dynamics of a wide range of astrophysical systems from protostars to clusters of galaxies. He has also made important contributions to understanding the structure and evolution of the interstellar and intergalactic medium he received the Brouwer Award in recognition of outstanding contributions to the field of dynamical astronomy He received his bachelor’s from Queens University in Kingston Eric Wood works in the areas of hydroclimatology with an emphasis on land-atmosphere interactions for climate models and for water resource management He is also known for the enormous impact he has had on the field of hydrology — through teaching mentoring graduate students and professional service to the global scientific community he made significant advances that moves the field closer to realizing the promise of global hydrology Eric proposed the development of hyperresolution land surface models which enabled discovery of patterns of river flows floods and drought at scales ranging from regional to global in 2017 Eric was awarded the American Geophysical Union’s highest honor in hydrology He is widely recognized as a visionary in examining Earth's water cycle having shed new light on the role of water in the climate system and developing groundbreaking analytical tools He will remain at Princeton as a senior scholar continuing to develop hyperresolution land surface models He will pursue new research avenues modeling infectious disease transmission and its relation to highly resolved hydrologic processes Wood earned his bachelor’s degree from the University of British Columbia and his Ph.D Her research focuses on DNA replication and chromosome structure in yeast telomeres and replication fork progression She has contributed groundbreaking insights into the nature and function of telomeres the unusual structures at the ends of eukaryotic chromosomes Her lab also discovered and characterized the first eukaryotic accessory DNA helicases which are enzymes that allow the replication fork to move past hard-to-replicate sites such as stable protein complexes and DNA secondary structures Her influential contributions to the understanding of telomeres has been recognized by many honors including election to the National Academy of Sciences and to the American Academy of Arts and Sciences She has been continuously funded by the National Institutes of Health since 1979 and was awarded a prestigious Merit Award in 2000 A champion of expanding the participation of women and underrepresented minorities in science she has participated in efforts at both Princeton and around the country to bring greater diversity to the discipline She received her bachelor’s from Cornell University and her Ph.D Metrics details Organisms have the capacity to make decisions based solely on internal drives it is unclear how neural circuits form decisions in the absence of sensory stimuli Here we provide a comprehensive map of the activity patterns underlying the generation of saccades made in the absence of visual stimuli We perform calcium imaging in the larval zebrafish to discover a range of responses surrounding spontaneous saccades from cells that display tonic discharge only during fixations to neurons whose activity rises in advance of saccades by multiple seconds When we lesion cells in these populations we find that ablation of neurons with pre-saccadic rise delays saccade initiation We analyze spontaneous saccade initiation using a ramp-to-threshold model and are able to predict the times of upcoming saccades using pre-saccadic activity These findings suggest that ramping of neuronal activity to a bound is a critical component of self-initiated saccadic movements inputs that could be a source of confounding signals none of these studies could unambiguously report on the activity of individual neurons since calcium sensors were distributed throughout the cell potentially introducing neuropil contamination We combined two-photon calcium imaging and single-cell perturbations to identify a population of neurons controlling the timing of upcoming saccades Our combined imaging and perturbation study provides three notable findings we generated a comprehensive map of neuronal activity patterns underlying spontaneous saccades and subsequent fixations—these maps are generated while animals are in the dark ensuring that the signals are internally generated and with a nuclear-localized calcium sensor we found neurons in the hindbrain whose activity rises above baseline in a direction-selective manner multiple seconds before the decision to saccade the time and rate of rise of these cells is consistent with a ramp-to-threshold model which can be used to predict saccade timing evidence implicating these cells in controlling the proper patterning of spontaneous saccades These findings not only provide insights into the mechanisms controlling the choice of when to shift gaze but also establish a new model system for understanding the neuronal processes underlying spontaneous These results show that larval zebrafish can self-initiate a simple yet varying pattern of horizontal eye movements We will refer to cells with significant STAs as eye-movement responsive This pre-saccadic rise is suggestive of activity that is involved in the timing of upcoming saccades a role which we will explore further in the remainder of this paper we found that ~5% of hindbrain neurons in larval zebrafish had responses associated with spontaneous saccades and fixations and the response profile of this population was diverse The diversity included cells with step-like profiles expected for ABD neurons and integrator neurons and cells with burst-like responses expected for saccade generator neurons The distribution also contained neurons whose activity is better described as anticipating upcoming movements consistent with a role in saccade initiation Within the continuum described above were cells whose population average activity steadily rose ahead of the upcoming saccade Because this form of dynamics appears to anticipate a future movement it is reasonable to speculate that neurons with such activity play an important role in saccadic preparation or timing We now turn our attention to a closer examination of such neurons with a focus on single-trial and single-cell level analyses that can capture variations missed with averaging pre-saccadic rise events occurred ahead of saccades in one direction although there were occasions where cell activity also rose before saccades in the opposite direction or failed to rise dF/F for a small number of cells (n = 5) was significantly correlated with upcoming saccades in both directions Given the small number of these cells we did not consider them in further analyses Rise events generally lasted multiple seconds and there was variability in the duration and rate of the rise both within and across cells activity tended to rise to consistent values at the time of saccade even though duration of rise varied by 50% or more We will refer to these cells as pre-saccadic rise (SR) neurons To quantitatively characterize the dynamics of SR cells, we assessed several features of their activity before and at the time of saccade that could elucidate their role in initiating the upcoming spontaneous saccade (Fig. 4b and “Methods”) To examine how the initiation of activity related to saccade occurrence we measured the time when activity rose above baseline and compared that to the time of upcoming and previous saccades We also measured whether the time of activity rise scaled with fixation duration To determine whether neuronal activity consistently rose to similar values we measured activity at the time of saccade the activity of SR neurons is more informative of upcoming saccades than previous saccades we found that SR cell activity can rise within any fraction of the fixation time to begin rising later in the fixation for longer fixation durations If SR cell activity determines when a spontaneous saccade should occur we should be able to predict whether a saccade is about to happen based on the output of SR populations we show that SR pre-saccadic dynamics can be used to predict saccade direction and time we also detail the relationships between the time at which an SR cell begins rising ahead of a saccade and the speed at which activity rises and 94% using single-cell activity or population averages consisting of 4 or 16 cells an ideal observer who has knowledge of the saccade transition probabilities would guess that an upcoming saccade is directed towards the opposite direction of the previous saccade and be correct 77% of the time (given that successive saccades occur in the same direction 23% of the time see section Larval zebrafish generate spontaneous eye movements with a range of inter-saccade times) the CP performance is better than the performance of an ideal observer These results indicate that spontaneous SR population activity contain information regarding the upcoming saccade direction an ideal observer who has knowledge of the time of previous saccade and knowledge of the fixation duration probability distribution predicted saccade times with a timing error of 51% and could not produce predictions that are correlated to the actual saccade times (cc = 0.00; see “Methods”) the pre-saccadic dynamics of SR population activity can be used to predict when saccades will occur It is unknown where the signals to initiate spontaneous saccade arise The activity of the SR neurons we identified suggest that they initiate saccades when their population level activity reaches a threshold value In the simplest instantiation of this model activity is summed across cells and compared with a threshold value losses in the number of SR cells would lead to a longer time until saccades occur These results provide evidence for a hindbrain role in spontaneous saccade initiation but significant correlation between increase in fixation duration and estimated fraction of ablated SR cells we measured the effect on fixation duration after ablating single SR neurons we observed an increase in fixation duration after ablating a small number of hindbrain neurons The magnitude of the increase was largest when we specifically targeted SR cells Both cluster and single-cell ablation experiments suggest that SR neurons play a significant role in the preparation for spontaneous saccades We combined focal laser ablations and calcium imaging to comprehensively map neuronal function and activity during a self-initiated behavior We simultaneously measured eye movements and neuronal activity throughout the hindbrain of larval zebrafish while they made spontaneous saccades in the dark We discovered neurons in the hindbrain whose activity rises above baseline in a direction-selective manner multiple seconds before the occurrence of a saccade a causal role for these cells in the decision to perform a spontaneous saccade These data thus help elucidate the mechanism of a simple self-initiated behavior Our discovery of SR neurons in the hindbrain depended upon a comprehensive single-cell resolution map of activity during spontaneous eye movements in the dark Comprehensive spatial coverage was obtained by two-photon calcium imaging which allowed us to image activity even at the deepest regions of the hindbrain where one-photon approaches suffer from poor resolution and signal-to-noise Single-cell resolution of activity was ensured by coupling two-photon microscopy with nuclear-localization of the calcium sensor allowing us to distinguish the activity profiles of even closely packed neurons We maintained a focus on internally generated dynamics by monitoring activity while animals made spontaneous saccades in the absence of any visual cues This effort allowed us to identify both a broad spatial distribution of the various signal types and strong regional characteristics including a pronounced switch in the directional sensitivity of eye-position-related signals as one crosses from rhombomere 1 to 2 a clustering of burst neurons in the ventral portions of rhombomeres 2 and 3 and a high density of SR neurons in dorsal portions of rhombomeres 2 and 3 it will be of interest in the future to determine what role SR neurons play in orientation behaviors more broadly build a solid foundation for exploring and understanding how visual and volitional signals are combined and transformed into motor commands for oculomotor behavior and potentially other orientation tasks Our comprehensive mapping of this buildup activity enabled us to show a titration between the degree of disruption to the readiness signal and delays in the initiation of saccades single-cell ablations of SR neurons led to significant delay in saccade initiation that was two-fold greater than any delays following ablation of nearby non-SR cells These results suggest that the spontaneous decision to move the eyes requires the buildup of activity in SR cells Our work thus builds upon prior studies of signaling during voluntary movements by drawing a direct link between readiness signals and self-initiated movement which would preclude us from seeing certain dynamical properties such as approximate linear ramping activity of SR cells weaker nonlinearities not accounted for in our analysis can cause discrepancies in our estimates of firing rate particularly at low values and high values following saccades in burst and burst-tonic neurons These discrepancies can also cause the slope and time of rise of SR cells to be artificially shortened from the actual times the systematic nature of such nonlinearities would still allow us to observe the coarse dynamical profiles of cell responses and properties such as the dependence of slope on time of rise it is possible that the SR signal in the hindbrain provides the initial kernel of activity needed to prepare movement during cued behaviors The mechanistic insights that one can obtain on readiness in larval zebrafish will hopefully allow us to understand a broad set of decision-making processes the experimenter manually selected (using roipoly in MATLAB) a region-of-interest about which the eyes were free to move Pixels within the region-of-interest whose intensity values were below a manually selected threshold were classified as belonging to the eyes The threshold was chosen during the experiment by manually trying various values and selecting the one that achieved the best segmentation quality two ellipses were fit to the resulting binary image using the MATLAB regionprops function Eye position equaled the orientation of the fitted ellipse about its time-averaged value We used the MATLAB “\” operator to solve the affine transformation \({\bf{y}}={\bf{Tx}}\,{\boldsymbol{+}}\,{{\bf{T}}}_{{\bf{0}}}{\boldsymbol{\otimes }}{\bf{1}}\) for the 3 × 3 matrix and the 3 × 1 translation vector \({{\bf{T}}}_{{\bf{0}}}\) where \({\bf{y}}\) and \({\bf{x}}\) are the 3 × k matrices of points chosen from the bridge brain and brain being registered respectively \({\bf{1}}\) is a k × 1 vector of all ones and \({\boldsymbol{\otimes }}\) denotes the outer product We repeated this procedure to find corresponding points and an associated transformation matrix between the bridge brain and the Elavl3-H2B brain (Elavl3 is another name for the HuC gene) available on the Z-Brain website which implements image registration via cross-correlation The dftregistration algorithm estimates the peak in the two-dimensional cross-correlation between the reference image and movie frame being registered Each movie frame is then translated by an amount determined from the peak location the dftregistration algorithm works in Fourier space to calculate cross-correlations We used MATLAB’s built-in fast Fourier transform software (fft2) to compute each frame’s two-dimensional discrete Fourier transform (DFT) and to compute the two-dimensional DFT of the reference frame The motion-correction algorithm described above returned a scalar metric for each movie frame that indicated how well the frame matched the reference after correction the frame was considered too aberrant to be useful and the fluorescence of all pixels in this frame were replaced by NaNs the dftregistration algorithm returned an error value related to the square root of one minus peak normalized cross-correlation between a given frame and the reference we computed the median error across all frames and the median absolute deviation (MAD) of the error across all frames If a given frame’s error value was greater than five times the MAD plus the median that frame’s pixels were replaced by NaNs The algorithm models a calcium fluorescence movie as the product of two nonnegative matrices one containing spatial locations and the other containing calcium time series for each active cell To determine the nonnegative matrices that best-fit the data we implemented a procedure based on the demo_script.m file provided with the code After initializing the spatial and temporal components we ran one iteration of spatial and temporal updates where components correlated with each other were merged and components that were poorly correlated with the data were removed followed by a final spatial and temporal update We first found initial estimates for the spatial This function ran several steps: (1) it spatially filtered the fluorescence movies (Gaussian kernel with standard deviation set to 5 (2) It greedily selected locations where the spatial estimates explained the largest amount of spatio-temporal variance nonnegative matrix factorization to produce spatial (4) It refined these estimates using a hierarchical (5) It ran a rank 1 nonnegative matrix factorization on the spatio-temporal residual to initialize the background spatial and temporal components We updated the initial estimates of the spatial footprints and the background component using the constrained nonnegative Lasso algorithm implemented in the update_spatial_components function We used the dilate option which restricted the search of possible nonzero component values to a dilated version of that component’s nonzero values found in the previous iteration (dilation was performed using a 4-pixel radius (1.4 µm) disk-shaped structuring element) The new components are then post-processed by the following operations: (i) two-dimensional median filtering with a default size of 3 × 3 pixels (ii) morphological closing with a square-shaped structuring element (3 pixels long) and (iii) “energy” thresholding with threshold set to 0.99 We then updated the estimates of the temporal components using the update_temporal_components function with an auto-regressive parameter This function updated components using a block-coordinate descent algorithm (we used two iterations) which ran a thresholding operation (at a threshold of 0) on the activity of each component after removing the effect of all the other components we removed spatial or temporal components that were poorly correlated with the raw data (space and time r values returned by classify_comp_corr function were <0.05) or whose spatial footprint areas were smaller than a value of 16 pixels squared which equaled 2.1 µm2 We then merged spatially overlapping components with highly correlated temporal activity (cc > 0.95) VPNI cells were selected as cells in rhombomeres 5–8 whose Pearson correlation coefficient between fluorescence and eye position was reasonably high (>0.5) As an initial approximation of the effects of calcium buffering on the relationship between firing rate and eye position we convolved the eye position using an exponential decay kernel with a 1-s decay time before measuring the correlation We then fit a decaying exponential function (\(A{e}^{-t/\tau }+b\)) to the average fluorescence triggered around nasally directed saccades made by the eye ipsilateral to the cell \(b\) was chosen as the average value of the ipsiversive STA 1–2 s prior to saccade \(A\) and \(\tau\) were found by minimizing the squared error between the model and data using an interior-point algorithm (MATLAB fmincon) with \(\tau\) constrained to be positive and \(A\) constrained to be larger than \(b\) We used the median value of \(\tau\) from cells that were well fit by the exponential decay model (r2 > 0.8) as the parameter for the auto-regressive model (we converted the value from seconds to the equivalent discrete-time model) sparse deconvolved output from this temporal update as our estimate of deconvolved neural activity We estimated each component’s noisy fluorescence activity as the trace that resulted after spatially averaging the fluorescence video using that component’s spatial values as weights We registered each cell to a reference brain (see “Methods” section “Registration of individual planes to the Z-Brain atlas”) and excluded cells that were registered to the midbrain we analyzed time-averaged images to infer cell locations since the CaImAn algorithm cannot find non-active cells (non-active cells are included as part of a single background term) For each motion-corrected fluorescence movie we calculated the median intensity across time for each pixel and analyzed the resulting time-averaged image to find individual cell nuclei locations We performed a morphological opening on the time-averaged image (MATLAB function imopen) with a disk-shaped structuring element that had a radius equal to 4 pixels (1.4 µm) The opening operation with this structuring element tended to make it easier to segregate the disk-shaped nuclei in the image We then found local intensity maxima of the opened image by looking for connected pixels with equal intensity that were greater than the intensity of external boundary pixels (MATLAB function imregionalmax) We measured the locations of individual cell nuclei measuring the regions of connected pixels that corresponded to local intensity maxima we excluded any regions-of-interest that had an area greater than most cell nuclei areas which we determined by manual measurements (18.7 µm2 which translated to 144 pixels squared) We determined the times of saccade occurrence by calculating the crossing times of eye velocity past a threshold we first filtered out fluctuations in eye position using a median filter (medfilt1 in MATLAB) The exact value of the filter order depended on the eye position sampling rate but was chosen to correspond to 500 milliseconds We then approximated eye velocity as the difference in filtered eye position at consecutive time points divided by the time difference between these points The threshold was set to three standard deviations above the mean-absolute velocity or 10° s−1 A single saccadic event typically consisted of several consecutive points whose velocity was above the threshold We took the initial point as the time when the saccade occurs During head/body movements the eye position traces become corrupted One signature we used to determine when head/body movements occur is the time between threshold-crossing events (this signature was used in combination with the criteria listed in “Methods” section “Detecting samples corrupted by animal movement”) Separate experiments with video recordings of the entire body suggested that unusually short intervals between events typically indicate that the events occur during sudden head/body movements we did not consider threshold-crossing events that were spaced apart in time 1.4 s or less to be saccades We measured the lower and upper bounds of the confidence intervals as the 0.025 and 0.975 quantiles across the bootstrapped samples This procedure varied the significance level for each comparison by the formula \(\frac{\alpha }{N-j+1}\) where \(j\) was the index of the comparison after sorting p values from low to high \(\alpha\) was the desired family-wise error rate and \(N\) was the total number of comparisons We set \(\alpha\) to 0.01 and set the number of comparisons to 72,304 (36,152 active cells with STAs available for analysis times two to account for both saccade directions see “Methods” section “Saccade-triggered average calculation”) We rejected the null hypothesis for 6,712 cells (19% of 36,152 active cells) The probability that a hindbrain cell is eye-movement responsive is therefore 0.05 (the probability that a given active hindbrain cell is eye-movement responsive times the probability that a hindbrain cell is active We ran a PCA to search for lower-dimensional representations of STAs across the population of eye-movement responsive cells We combined STAs of deconvolved fluorescence from all eye-movement responsive cells (across all planes and fish recorded) and from both directions (around saccades to the left and right) resulting in a matrix that had \(N=13\text{,}424\) rows (6,712 cells times two directions) and \(T=31\) columns (time around the saccade is evaluated at 31 discrete-time bins of size 1/3 s) To focus our analysis on the variations in dynamics across cells we divided each STA by its L2 norm before performing PCA and \({c}_{i3}\) are plotted on the \({c}_{1}\)-axis We normalized these coefficients to have unit norm for \(i=1,\ldots ,N\), \(j=1,2,3\). We then transformed \({{\bf{c}}}^{\prime}\) into spherical coordinates (see Fig. 3c) Statistics and Machine Learning Toolbox function ksdensity with bandwidth parameter equal to 10° for \({\boldsymbol{\Phi }}\) and 3° for \({\boldsymbol{\Theta }}\)) Each population average shown in Fig. 3g is constructed by averaging together all non-normalized STAs triggered to saccades to the left with a specific value of \(\phi\) the average under the column \(\phi\) = 105 was constructed by first finding the STAs triggered to saccades to the left with \(\phi\) within 15° of 105 and then averaging these together Letting \({{\bf{f}}}_{i,:}\) denote the \({i}{{\rm{th}}}\) STA and \({{\mathcal{S}}}_{105}\) denote the set of integers that index leftward STAs with \(\phi\) = 105 \({{\mathcal{S}}}_{105}=\big\{i|{97.5\le \Phi }_{i} \,<\ 112.5,\text{and}{{\bf{f}}}_{{\boldsymbol{i}},}:\,\text{is}\,\ \text{leftward} \,\,\text{saccades}\big\}\) the population average under the column \(\phi\) = 105 is computed as are constructed using all principal components and only use the angles in \({\boldsymbol{\Phi }}\) to group STAs the population averages that are displayed can reflect variations not captured by the first three components K-means was used to cluster the normalized coefficients (defined in Eq. (3) and associated text) found by PCA on STAs from eye-movement responsive cells (Supplementary Fig. 2) we focused on the normalized coefficients that scale the first three principal components We created a six-dimensional vector by combining the normalized coefficients that correspond to the STA triggered to saccades to the left and right using a different number of clusters on each run (between 2 and 10) to group the combined coefficients and we used the silhouette value to measure cluster quality The silhouette value for an individual vector measures how close that vector is to other vectors in its own cluster relative to its distance with vectors in other clusters The value for the \({i}{{\rm{th}}}\) vector is defined as the minimum average distance from the \({i}{{\rm{th}}}\) vector to all vectors in different clusters than the \({i}{{\rm{th}}}\) vector minus the average distance from the \({i}{{\rm{th}}}\) vector to other vectors in the same cluster The silhouette value is normalized by max(ai bi) in order for it to range from +1 to −1 with vectors that are well matched to their cluster having values near +1 and with vectors that are randomly clustered having values near 0 The color displayed was determined by the value where the histogram peaked or in cases where the histogram had multiple modes was determined by the value at a randomly chosen peak An eye-movement responsive cell was classified as an SR cell if its dF/F response before upcoming saccades was significantly correlated with time before saccade We measured two Spearman correlations for each eye-movement responsive cell Statistics and Machine Learning Toolbox function corr with option type set to Spearman) on values of dF/F and time before saccade concatenated from all fixations before saccades to the left The other correlation was computed on values of dF/F and time before saccade concatenated from all fixations before saccades to the right The Spearman correlation can be used to measure monotonic (not only linear) relationships between two variables \(X\) and \(Y\) It is calculated as the standard Pearson correlation coefficient applied to the ranks of \(X\) and \(Y\) We did not interpolate fluorescence activity before computing the correlation coefficients Since we were interested in cells whose activity is related to upcoming saccade we did not include activity that was within 2 s of the previous saccade where eye-movement responsive cells might have post-saccadic fluorescence decays We computed a p value for each correlation by testing the hypothesis that rho = 0 against the alternative that the correlation was greater than 0 (tail option set to right) A neuron was considered to have significant pre-saccadic activity if we rejected the null hypothesis for any of the cell’s two correlation coefficients at a significance level of 0.01 we used the Holm–Bonferroni method (as described in “Methods” section “Selection of eye-movement responsive cells”) with the number of comparisons set to 13,424 (the number of eye-movement responsive cells times two directions) as the time point before its deconvolved fluorescence increased >0.1 We estimated the rate of pre-saccadic rise in SR cells by finding the slope of the best-fit line of pre-saccadic deconvolved fluorescence with time To construct the best-fit line we used time from pre-saccadic rise to the time of upcoming saccade as a regressor to a linear regression that fit deconvolved fluorescence values The linear approximation was reasonable for 72% of the fixations (correlation between regression fit and data was >0.4) We excluded fixations where we were unable to measure the slope with linear regression We predicted saccade direction using interpolated SR activity before saccadic events the phrase “interpolated SR activity” refers to linear interpolation of deconvolved fluorescence activity to a grid of equally spaced time points (using 1/3 s bins) starting from the previous saccade to the upcoming saccade the CP measures relationships between neuronal discharges and binary behavioral choices We adapted this metric by using the spontaneous decision to saccade to the left or the right as our binary behavioral variable and population average deconvolved fluorescence at a given time before saccade as our neural read-out At discrete time points before upcoming saccades we made two histograms of interpolated SR activity was comprised of values of interpolated SR activity before saccades to the right (left) from SR cells significantly correlated with upcoming saccades to the left (right) was comprised of interpolated SR activity before saccades to the left (right) from SR cells significantly correlated with upcoming saccades to the left (right) Saccade direction was predicted using a threshold on population activity We plotted the fraction of interpolated SR activity from the signal distribution that was above threshold (the true positive rate) versus the fraction of interpolated SR activity from the noise distribution that was above threshold (the false positive rate) across multiple threshold values The CP was calculated as the area under the resulting curve which would equal 0.5 if activity and upcoming saccade direction were not related we computed multiple CPs each conditioned on a different fixation duration (fixing durations to values 2–20 s) and then computed the CP SEM across fixation durations We modeled the population average dynamics at values of time \(t\) after population activity begins to rise where \(D\) is the population activity slope a saccade will occur and \(y\) should equal \(\kappa\) if the ramp-to-threshold model is accurate We constructed a running estimate of \(D\) by first measuring when the actual population activity, \(\widetilde{y}\left(t\right),\) began to rise. Note that we are distinguishing the population activity measured from data, \(\widetilde{y}\left(t\right)\), from the model of population activity, \(y(t)\), specified by Eq. (8) We measured when \(\widetilde{y}\left(t\right)\) began to rise as the time when the derivative in \(\widetilde{y}\left(t\right)\) crossed a threshold of 35 (arbitrary units) Note that under our convention we set this event to occur at time 0 The derivative was approximated as the difference between population activity at each time point divided by the interpolated time bin interval We created a running estimate of \(D\) using the median value of the derivative from time 0 until time We substituted our running estimate of the slope into Eq. (9) to yield a running estimate of \({t}_{r}\) We then tested this prediction against a new measurement of population activity constructed from the remaining 40% of cells we repeated this procedure on 10,000 randomly selected subsets from randomly chosen fixation durations we determined the fraction of saccades that could be accurately predicted given knowledge of the elapsed time since last saccade and the distribution of fixation durations an ideal observer could predict upcoming saccade times by guessing a time that minimizes some cost function that measures error between the actual saccade time and the guessed time We tried three cost functions (mean-squared error and all-or-none error) and report results in the text from the one that performed the best (all-or-none error) We repeated this procedure until we saw a lesion which we determined by looking for a multi-spectrum spot that was much brighter than the fluorescence of surrounding tissue Lesion sizes with this procedure were generally ~5 µm in diameter To increase the size of the lesion we lowered the average laser power to values of 30–50 mW and scanned the ablated region at these lower powers We stopped scanning the ablated region once it grew to ~30 µm in diameter We waited between 30 and 120 min after ablation before recording post-lesion eye movements The fraction ablated was equal to \({n}_{c}\) divided by the total number of SR cells used to construct the map ablations did not occur even after three to five attempts most likely due to laser power absorption from pigmentation We did not try to ablate a cell after attempts we repeated three cycles of finding cells of interest in a single plane then searching for more cells of interest in subsequent planes we took time-averaged images of the entire hindbrain dorsal of the Mauthner cell and used this stack to register ablated cells to the Z-Brain Atlas we performed the same procedure but targeted cells that failed to pass our criteria for being considered eye-movement responsive For each fish, we measured fractional changes in median fixation duration after ablation. Since we were concerned with a spontaneous behavior, we could not control the number of fixations that were recorded during the timeframe of each experiment. As a result, our measurements would have had different accuracies per animal (Supplementary Table 1) if we calculated fractional changes without accounting for the different number of samples per fish To control for this difference in accuracy we made repeated measurements of the fractional change per fish with each repeated measurement computed using the same number of fixations before and after ablation we randomly sampled without replacement \({N}_{{{\min }}}\) fixations before and after ablation The exact value of \({N}_{{{\min }}}\) was based on animals with the fewest number of fixations available after excluding animals that stopped making saccades after ablation; animals whose average saccade rate never increased above one saccade per direction per minute were excluded (n = 3 animals from cluster ablation experiments if we denote the number of fixations before or after ablation (indexed by \(i\)) from animal \(j\) then \({N}_{{{\min }}}=\mathop{{{\min }}}\nolimits_{i,j}{n}_{{ij}}\) The number of times we repeated each measurement of fractional change in median fixation duration varied per fish and was determined by how many more fixations each animal made compared to \({N}_{{{\min }}}\) the number of times we repeated each measurement for animal \(j\) equaled \({\rm{round}}\,(\frac{\mathop{{{\min }}}\nolimits_{i}{n}_{{ij}}}{{N}_{{{\min }}}})\) The fractional change in median fixation duration was computed as the difference in median fixation duration (after minus before ablation) divided by the median fixation duration before ablation Using \(l\) to denote the index of the repeated measurement in animal \(j\) and \({t}_{{ijml}}\) to denote the \({m}{{\mathrm{th}}}\) randomly sampled fixation duration (integer \({m}\) varies from 1 to \({N}_{{\rm{min }}}\)) in condition \(i\) (\(i\)=1 denotes before ablation and \(i\) = 2 denotes after ablation) the fractional change in fixation duration was computed as: \({\rm{round}}(\frac{\mathop{{{\min }}}\nolimits_{i}{n}_{{ij}}}{{N}_{{{\min }}}})\) and j = 1 For each sample of \({\bf{y}}\) for control and SR-targeted animals we ran a Wilcoxon rank-sum test (100 tests in total) of the null hypothesis that the medians are equal between the distribution of \({\bf{y}}\) for SR-targeted and the distribution of \({\bf{y}}\) from control animals against the alternative that the median is greater in SR-targeted animals and median p values across the 100 runs were also presented in the results MATLAB function ranksum with the appropriate value of tail was used to perform the one-sided Wilcoxon tests Further information on research design is available in the Nature Research Reporting Summary linked to this article Hirnpotentialänderungen bei Willkürbewegungen und passiven Bewegungen des Menschen: Bereitschaftspotential und reafferente Potentiale Neuronal activities in the primate motor fields of the agranular frontal cortex preceding visually triggered and 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D. & Aksay, E. R. F. Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades. figshare https://doi.org/10.6084/m9.figshare.14558064.v1 (2021) Ramirez, A. D. & Aksay, E. R. F. Ramp-to-threshold dynamics in a hindbrain population controls the timing of spontaneous saccades. Zenodo https://doi.org/10.5281/zenodo.4743159 (2021) Download references We thank Chao Young and Misha Ahrens for generating the Tg(HuC:GCaMP6f-H2B) line and sharing ahead of publication We thank the RARC team at Weill Cornell Medicine for animal care and husbandry and Karel Svoboda for helpful discussion and feedback on the manuscript Funding for this work was provided by NIH grant K99 EY027017 and the Simons Foundation Global Brain Initiative carried out the experiments and analyzed the data; A.D.R The authors declare no competing interests Peer review information Nature Communications thanks Martin Haesemeyer and the other anonymous reviewer(s) for their contribution to the peer review of this work Download citation DOI: https://doi.org/10.1038/s41467-021-24336-w A Tibetan fox is pictured after snow in Aksay Kazakh Autonomous County 2021 shows herdsmen driving camels on the way to summer pastures in Aksay Kazakh Autonomous County northwest China's Gansu Province.Photo:Xinhua 2021 shows camels on the way to summer pastures in Aksay Kazakh Autonomous County Wild yaks are seen at the Haltent grassland in the Kazak Autonomous County of Aksay Kiangs (Equus kiang) are seen at the Haltent grassland in the Kazak Autonomous County of Aksay Tibetan gazelles are seen at the Haltent grassland in the Kazak Autonomous County of Aksay Argali sheep are seen at the Haltent grassland in the Kazak Autonomous County of Aksay A wolf is seen at the Haltent grassland in the Kazak Autonomous County of Aksay 2024 shows the autumn scenery of Tianzi Mountain at the Zhangjiajie national forest park in Zhangjiajie 2024 shows the autumn scenery at the Wuxia Gorge one of the Three Gorges on the Yangtze River 2024 shows the autumn scenery at the Sanjiangkou ecological tourism area in Tongjiang City People visit the Binhe Park in Yiyang County Luoyang City of central China's Henan Province 2024 shows a train passing forest and fields in Shangzhi City 2024 shows elks wandering at the Tiaozini wetland in Dongtai City 2024 shows autumn scenery in Niangniangzhuang Town Zunhua City of north China's Hebei Province People visit the Huyangxia scenic spot in the Kazak Autonomous County of Aksay in northwest China's Gansu Province 2024 shows the autumn scenery in Xiji County of Guyuan City northwest China's Ningxia Hui Autonomous Region A new technique for printing extraordinarily thin lines quickly over wide areas could lead to larger less expensive and more versatile electronic displays as well new medical devices Solving a fundamental and long-standing quandary chemical engineers at Princeton developed a method for shooting stable jets of electrically charged liquids from a wide nozzle which produced lines just 100 nanometers wide (about one ten-thousandth of a millimeter) offers at least 10 times better resolution than ink-jet printing and far more speed and ease than conventional nanotechnology “It is a liquid delivery system on a micro scale,” said Ilhan Aksay “And it becomes a true writing technology.” Aksay and graduate student Sibel Korkut published the results Jan The paper also includes as a co-author Dudley Saville a chemical engineering professor who initiated the project but died in 2006 The research was funded by grants from the Army Research Office Developing a deep understanding of the fundamental physics behind the process rather than building highly specialized equipment the researchers were able to use a nozzle that is half a millimeter wide or 5,000 times wider than the lines it produced The key to the process is something called an “electrohydrodynamic (EHD) jet” -- a stream of liquid forced from a nozzle by a very strong electric field Such jets were first investigated in 1917 and are now commonly used in a variety of industrial processes one of the main features of EHD jets is that the stream of liquid becomes unstable soon after it leaves the nozzle and either whips around uncontrollably or breaks up into fine liquid drops Engineers have used these effects to their advantage in spinning fibers and in industrial electrospray painting but the reason for the whipping instability two researchers working independently -- Princeton graduate student Hak Poon and Cornell University physicist Harold Craighead -- found that the jet was stable for a very short distance after leaving the nozzle but the result was still not practical and the reasons were still elusive “To understand how to control the jet in any engineering application we had to understand why this was happening,” Aksay said Korkut took up the challenge and worked for nearly six years to nail down the mechanisms at play she found that a key factor was that the liquid jet was transferring some of its electrical charge to the surrounding gas which breaks into charged particles and carries some of the electrical current Korkut’s predecessors and other scientists had looked only at the density of the electrical charges on the surface of the liquid jet Expanding her view of the system led Korkut to a simple way to control the stability of the jet by changing the gas and the amount of water vapor She was able to produce an extremely straight and stable jet more than 8 millimeters from the nozzle (See video image of straight and whipping jets here: www.princeton.edu/~cml/html/EHDPself-assembly.html.) The result is highly practical not only because of the fineness of the stream but also because the large size of the nozzle and the distance from the nozzle to the printed surface will prevent clogs or jams Aksay said a chief use for the technique could be in printing electrically conducting organic polymers (plastics) that could be the basis for large electronic devices Conventional techniques for making wires of that size (100 nanometers) require laboriously etching the lines with a beam of electrons which can only be done in very small areas The new technique can lay down lines at the rate of meters per second as opposed to millionths of a meter per second Another application would be to use a liquid that solidifies into a fiber for making precise three-dimensional lattices Such a product could be used as a scaffold to promote blood clotting in wounds and in other medical devices Princeton University has filed for a patent on the discovery and has licensed rights to Vorbeck Materials Corp. a specialty chemical company based in Maryland “Electronics is a huge potential application for this discovery,” said John Lettow president of Vorbeck and a 1995 chemical engineering alumnus of Princeton “The printing technique could greatly increase the size of video displays and the speed with which high performance displays are made.” Lettow said the technique also could be used in creating large sensors that collect information over a wide area such as a sensor printed onto an airplane wing to detect metal fatigue publishing the results in the premier physics journal marks a gratifying conclusion to years of painstaking work that offered no guarantee of a practical answer “You are digging into a hole and you don’t know if you will hit the bottom,” Korkut said Even though she began to see improved stability of the jet after five years she still did not have a precise handle on the causes Aksay and Saville pressed her to have a deeper understanding before publishing the results “It took more than a year after we saw the clues We had to look at many possibilities,” Korkut said Aksay said Korkut succeeded because of her persistence are not responsible for the accuracy of news releases posted to EurekAlert by contributing institutions or for the use of any information through the EurekAlert system Copyright © 2025 by the American Association for the Advancement of Science (AAAS) Research: Hierarchically Structured Self-Assembled Materials We have also examined the structural evolution at the micron length scale (below) Mature particles possess distinctive curvatures while particles collected at earlier times show some evidence of amorphous structure (in the sense that the edges are not well defined) The aim of the biomaterials effort is to produce bone graft substitutes that mimic the properties of bone As pure ceramic proves to be too "brittle" for bone it has been proposed that a composite of the two materials would provide a better match with natural bone we are now able to fabricate prototype composites