About

Damon Clark, Ph.D., is a Professor in the Department of Molecular, Cellular, and Developmental Biology at Yale University, with secondary appointments in the Departments of Physics and Neuroscience. His academic background includes an A.B. in physics from Princeton University and a Ph.D. in physics from Harvard University, where he studied how the small nervous system in C. elegans encodes temperature preference behaviors. During his postdoctoral work at Stanford, he researched how early visual neurons guide behavior in the fruit fly Drosophila. His lab at Yale focuses on understanding how small networks of neurons perform sophisticated computations that guide behavior. The research aims to understand neural computations at three levels: the behavioral purpose served by neural circuits, the mathematical operations performed by these circuits, and the biophysical and synaptic properties that generate these operations. The lab uses visual and olfactory behaviors in Drosophila, employing tools such as behavioral measurements, visual stimuli, genetic manipulation, in vivo neural imaging, and quantitative modeling.

Research topics

• Artificial Intelligence
• Computer Science
• Biology
• Neuroscience
• Machine Learning
• Biological system
• Cell biology
• Genetics
• Algorithm
• Botany
• Statistics
• Medicine
• Computer vision
• Immunology
• Physics
• Mathematics
• Geometry
• Pathology
• Endocrinology

Selected publications

• Afterimages drive a shared visual motion-reversal illusion in <i>Drosophila</i>

  bioRxiv (Cold Spring Harbor Laboratory) · 2026-01-21

  articleOpen accessSenior authorCorresponding

  Abstract Illusions expose core computations in perception. In one visual apparent-motion illusion, perceptual direction is reversed when phase-shifted gratings are interleaved with uniform frames. Here, we demonstrate that Drosophila exhibits the same direction reversal reported in mammals. Combining behavior, targeted silencing, two-photon imaging, and modeling, we localize the origin of this illusion to elementary motion pathways. Silencing direction-selective T4/T5 neurons abolishes the reversal, and recordings reveal that downstream wide-field neurons invert their directional preference as interleave duration increases. Replacing periodic gratings with random binary patterns preserves the reversal, implicating afterimages rather than spatial periodicity. Imaging neurons upstream of T4/T5 shows signatures of an afterimage, whose emergence depends on interleave luminance. Critically, dark interleaves suppress afterimages and eliminate both the neural and behavioral reversal, whereas light interleaves preserve or enhance it. Thus, afterimages are central to this shared illusion and explain a deficiency of canonical motion-energy accounts. These results link a classic apparent-motion phenomenon to identified circuit elements and reveal a simple stimulus manipulation that switches an illusion on and off.

  PublisherOA PDFDOI

• Humans can use positive and negative spectrotemporal correlations to detect rising and falling pitch

  Nature Human Behaviour · 2026-02-09

  articleOpen accessSenior author

  To discern speech or appreciate music, the human auditory system detects how pitch changes over time (pitch motion). Here, using psychophysics, computational modelling, functional neuroimaging and analysis of recorded speech, we ask whether humans can detect pitch motion using computations analogous to those used by the visual system. We adapted stimuli from studies of vision to create novel auditory correlated noise stimuli that elicited robust pitch motion percepts. In psychophysical experiments, we discovered that humans can judge pitch direction from spectrotemporal intensity correlations. Robust sensitivity to negative spectrotemporal correlations is a direct analogue of illusory 'reverse-phi' motion in vision, constituting a new auditory illusion. Functional MRI measurements in auditory cortex supported the hypothesis that human auditory processing may employ pitch direction opponency. Linking lab findings to real-world perception, we analysed recordings of English and Mandarin speech and found that pitch direction was signalled by both positive and negative spectrotemporal correlations, suggesting that sensitivity to both types confers ecological benefits. This work reveals how motion detection algorithms sensitive to local correlations are deployed by the central nervous system across disparate modalities (vision and audition) and dimensions (space and frequency).

  PublisherOA PDFDOI

• Examining disparities in management and outcomes among unhoused patients with traumatic brain injury

  The American Journal of Surgery · 2025-07-17

  article
  PublisherDOI

• Visual circuitry for distance estimation in Drosophila

  Current Biology · 2025-09-27 · 3 citations

  articleOpen accessSenior author

  Animals must infer the three-dimensional structure of their environment from two-dimensional retinal images. They use visual cues like motion parallax and binocular disparity to judge distances to objects, and studies across several animal models have found and characterized neural signals that correlate with visual distance. However, the causal role of these neurons in distance estimation and the range of their possible neural properties remain poorly understood. Here, we show that both directional and non-directional feature-selective neurons in the Drosophila visual system are involved in estimating distance during free locomotion. We used a high-throughput behavioral assay to perform a targeted silencing screen of visual neurons, and we subsequently characterized distance tuning using in vivo two-photon microscopy, thus linking distance perception directly to neural signals. Silencing the primary motion detectors eliminated distance-dependent behavior, consistent with reliance on motion parallax. Our screen also identified a visual feature-detecting neuron that encodes a non-canonical motion parallax signal: the signal is not direction selective for object or background motion, but it is tuned to the relative speeds of foreground and background, resulting in a signal that can measure relative distance. Our results demonstrate the behavioral roles of direction-selective and distance-tuned neurons in fly distance estimation and provide a framework for considering broader classes of neurons that encode distance through motion parallax.

  PublisherOA PDFDOI

• Broken time-reversal symmetry in visual motion detection

  Proceedings of the National Academy of Sciences · 2025-03-06 · 4 citations

  articleOpen accessSenior authorCorresponding

  Our intuition suggests that when a movie is played in reverse, our perception of motion at each location in the reversed movie will be perfectly inverted compared to the original. This intuition is also reflected in classical theoretical and practical models of motion estimation, in which velocity flow fields invert when inputs are reversed in time. However, here we report that this symmetry of motion perception upon time reversal is broken in real visual systems. We designed a set of visual stimuli to investigate time reversal symmetry breaking in the fruit fly Drosophila ’s well-studied optomotor rotation behavior. We identified a suite of stimuli with a wide variety of properties that can uncover broken time reversal symmetry in fly behavioral responses. We then trained neural network models to predict the velocity of scenes with both natural and artificial contrast distributions. Training with naturalistic contrast distributions yielded models that broke time reversal symmetry, even when the training data themselves were time reversal symmetric. We show analytically and numerically that the breaking of time reversal symmetry in the model responses can arise from contrast asymmetry in the training data, but can also arise from other features of the contrast distribution. Furthermore, shallower neural network models can exhibit stronger symmetry breaking than deeper ones, suggesting that less flexible neural networks may be more prone to time reversal symmetry breaking. Overall, these results reveal a surprising feature of biological motion detectors and suggest that it could arise from constrained optimization in natural environments.

  PublisherOA PDFDOI

• Spatial and morphological organization of mitochondria in neurons across a connectome

  Science · 2025-12-11 · 2 citations

  articleOpen accessSenior authorCorresponding

  connectome, we uncovered quantitative rules governing the morphology and positioning of hundreds of thousands of mitochondria across thousands of neurons. We discovered that mitochondrial morphological features are specific to cell and neurotransmitter type, which provides fingerprints to identify neurons. Mitochondria are positioned with 2- to 3-micrometer precision relative to synaptic and structural features, with systematic differences across neuron types and compartments. Mitochondrial localization correlates with regional activity and postsynaptic targets. Analysis of a mouse visual cortex connectome confirms cell type-specific morphology and identifies partially divergent positioning rules. These results establish mitochondria as circuit-embedded organelles whose distribution links subcellular architecture to brain connectivity.

  PublisherOA PDFDOI

• Fly navigational responses to odor motion and gradient cues are tuned to plume statistics

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-04-03 · 1 citations

  preprintOpen access

  Abstract Odor cues guide animals to food and mates. Different environmental conditions can create differently patterned odor plumes, making navigation more challenging. Prior work has shown that animals turn upwind when they detect odor and cast crosswind when they lose it. Animals with bilateral olfactory sensors can also detect directional odor cues, such as odor gradient and odor motion. It remains unknown how animals use these two directional odor cues to guide crosswind navigation in odor plumes with distinct statistics. Here, we investigate this problem theoretically and experimentally. We show that these directional odor cues provide complementary information for navigation in different plume environments. We numerically analyzed real plumes to show that odor gradient cues are more informative about crosswind directions in relatively smooth odor plumes, while odor motion cues are more informative in turbulent or complex plumes. Neural networks trained to optimize crosswind turning converge to distinctive network structures that are tuned to odor gradient cues in smooth plumes and to odor motion cues in complex plumes. These trained networks improve the performance of artificial agents navigating plume environments that match the training environment. By recording Drosophila fruit flies as they navigated different odor plume environments, we verified that flies show the same correspondence between informative cues and plume types. Fly turning in the crosswind direction is correlated with odor gradients in smooth plumes and with odor motion in complex plumes. Overall, these results demonstrate that these directional odor cues are complementary across environments, and that animals exploit this relationship. Significance Many animals use smell to find food and mates, often navigating complex odor plumes shaped by environmental conditions. While upwind movement upon odor detection is well established, less is known about how animals steer crosswind to stay in the plume. We show that directional odor cues—gradients and motion—guide crosswind navigation differently depending on plume structure. Gradients carry more information in smooth plumes, while motion dominates in turbulent ones. Neural network trained to optimize crosswind navigation reflect this distinction, developing gradient sensitivity in smooth environments and motion sensitivity in complex ones. Experimentally, fruit flies adjust their turning behavior to prioritize the most informative cue in each context. These findings likely generalize to other animals navigating similarly structured odor plumes.

  PublisherOA PDFDOI

• Adaptation to visual sparsity enhances responses to infrequent stimuli

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-03-14

  preprintOpen accessSenior authorCorresponding

  Sensory systems adapt their response properties to the statistics of their inputs. For instance, visual systems adapt to low-order statistics like mean and variance to encode the stimulus efficiently or to facilitate specific downstream computations. However, it remains unclear how other statistical features affect sensory adaptation. Here, we explore how Drosophila's visual motion circuits adapt to stimulus sparsity, a measure of the signal's intermittency not captured by low-order statistics alone. Early visual neurons in both ON and OFF pathways alter their responses dramatically with stimulus sparsity, responding positively to both light and dark sparse stimuli but linearly to dense stimuli. These changes extend to downstream ON and OFF direction-selective neurons, which are activated by sparse stimuli of both polarities, but respond with opposite signs to light and dark regions of dense stimuli. Thus, sparse stimuli activate both ON and OFF pathways, recruiting a larger fraction of the circuit and potentially enhancing the salience of infrequent stimuli. Overall, our results reveal visual response properties that increase the fraction of the circuit responding to sparse, infrequent stimuli.

  PublisherOA PDFDOI

• Optimization in Visual Motion Estimation

  Annual Review of Vision Science · 2024-04-25 · 8 citations

  reviewOpen access1st authorCorresponding

  Sighted animals use visual signals to discern directional motion in their environment. Motion is not directly detected by visual neurons, and it must instead be computed from light signals that vary over space and time. This makes visual motion estimation a near universal neural computation, and decades of research have revealed much about the algorithms and mechanisms that generate directional signals. The idea that sensory systems are optimized for performance in natural environments has deeply impacted this research. In this article, we review the many ways that optimization has been used to quantitatively model visual motion estimation and reveal its underlying principles. We emphasize that no single optimization theory has dominated the literature. Instead, researchers have adeptly incorporated different computational demands and biological constraints that are pertinent to the specific brain system and animal model under study. The successes and failures of the resulting optimization models have thereby provided insights into how computational demands and biological constraints together shape neural computation.

  PublisherDOI

• Humans can use positive and negative spectrotemporal correlations to detect rising and falling pitch

  bioRxiv (Cold Spring Harbor Laboratory) · 2024-08-03 · 1 citations

  preprintOpen accessSenior authorCorresponding

  To discern speech or appreciate music, the human auditory system detects how pitch increases or decreases over time. However, the algorithms used to detect changes in pitch, or pitch motion, are incompletely understood. Here, using psychophysics, computational modeling, functional neuroimaging, and analysis of recorded speech, we ask if humans can detect pitch motion using computations analogous to those used by the visual system. We adapted stimuli from studies of vision to create novel auditory correlated noise stimuli that elicited robust pitch motion percepts. Crucially, these stimuli are inharmonic and possess no persistent features across frequency or time, but do possess positive or negative local spectrotemporal correlations in intensity. In psychophysical experiments, we found clear evidence that humans can judge pitch direction based only on positive or negative spectrotemporal intensity correlations. The key behavioral result-robust sensitivity to the negative spectrotemporal correlations-is a direct analogue of illusory "reverse-phi" motion in vision, and thus constitutes a new auditory illusion. Our behavioral results and computational modeling led us to hypothesize that human auditory processing may employ pitch direction opponency. fMRI measurements in auditory cortex supported this hypothesis. To link our psychophysical findings to real-world pitch perception, we analyzed recordings of English and Mandarin speech and found that pitch direction was robustly signaled by both positive and negative spectrotemporal correlations, suggesting that sensitivity to both types of correlations confers ecological benefits. Overall, this work reveals how motion detection algorithms sensitive to local correlations are deployed by the central nervous system across disparate modalities (vision and audition) and dimensions (space and frequency).

  PublisherOA PDFDOI

Recent grants

• Integrating visual counterevidence to detect self-motion in a small visual circuit

  NIH · $4.0M · 2016–2027

• Understanding how Neural Nonlinearities Tune Motion Detection in the Fly Eye

  NSF · $461k · 2016–2021

Frequent coauthors

• Bara A. Badwan

  Yale University

  17 shared

• Aravinthan D. T. Samuel

  Harvard University Press

  14 shared

• Jacob A. Zavatone-Veth

  Harvard University Press

  13 shared

• Omer Mano

  Yale University

  13 shared

• Ryosuke Tanaka

  13 shared

• Thomas R. Clandinin

  Stanford University

  13 shared

• Catherine A. Matulis

  Yale University

  12 shared

• Matthew S. Creamer

  12 shared

Awards & honors

• Searle Scholar Award
• Alfred P. Sloan Research Fellowship in Neuroscience
• Smith Family Award