Biology subjects

Hayden, B. Y.

Publications and source records attributed to Hayden, B. Y..

35 records · Page 2Linked to original sources

bioRxiv2022

Prefrontal control of actions in freely moving macaques

Our natural behavioral repertoires include complex coordinated actions of characteristic types. To better understand the organization of action and its neural underpinnings, we examined behavior and neural activity in rhesus macaques performing a freely moving foraging task in an open environment. We developed a novel analysis pipeline that can identify meaningful units of behavior, corresponding to recognizable actions such as sitting, walking, jumping, and climbing. On the basis of action transition probabilities, we found that behavior was organized in a modular and hierarchical fashion. We found that, after regressing out many potential confounders, actions are associated with specific patterns of firing in each of six prefrontal brain regions and that, overall, representation of actions is progressively stronger in more dorsal and more caudal prefrontal regions. Conversely, we found that switching between actions resulted in changed firing rates, with more rostral and more ventral regions showing stronger effects. Together, these results establish a link between control of action state and neuronal activity in prefrontal regions in the primate brain.

neuroscience↗

bioRxiv2022

Widespread coding of navigational variables in prefrontal cortex

To navigate, we must represent information about our place in the environment. Traditional research highlights the role of the hippocampal complex in this process. Spurred by recent research highlighting the widespread cortical encoding of cognitive and motor variables previously thought to have localized function, we hypothesized that navigational variables would be likewise encoded widely, especially in the prefrontal cortex, which is often associated with control of volitional behavior. We recorded neural activity from six prefrontal structures while macaques performed a foraging task in an open enclosure. In all six regions, we found strong encoding of allocentric position, head direction, egocentric boundary distance, and linear and angular velocity. These encodings were not accounted for by distance or time to reward. Strength of coding of all variables increase along a ventral-to-dorsal gradient. Together these results argue that encoding of navigational variables is not localized to the hippocampal complex and support the hypothesis that navigation is continuous with other forms of flexible cognition in the service of action.

neuroscience↗

bioRxiv2022

Distinct population and single-neuron selectivity for executive and episodic processing in human dorsal posterior cingulate

Posterior cingulate cortex (PCC) is an enigmatic region implicated in psychiatric and neurological disease, yet its role in cognition remains unclear. Human studies link PCC to episodic memory and default mode network (DMN), while findings from the non-human primate emphasize executive processes more associated with the cognitive control network (CCN) in humans. We hypothesized this difference reflects an important functional division between dorsal (executive) and ventral (episodic) PCC. To test this, we utilized human intracranial recordings of population and single unit activity targeting dorsal PCC during an alternated executive/episodic processing task. Dorsal PCC population responses were significantly enhanced for executive, compared to episodic, task conditions, consistent with the CCN. Single unit recordings, however, revealed four distinct functional types with unique executive (CCN) or episodic (DMN) response profiles. Our findings provide critical electrophysiological data from human PCC, bridging incongruent views within and across species, furthering our understanding of PCC function.

neuroscience↗

bioRxiv2022

Irrational choices via a curvilinear representational geometry for value

We make decisions by comparing values, but how is value represented in the brain? Many models assume, if only implicitly, that the representational geometry of value is linear. However, in part due to a historical focus on noisy single neurons, rather than neuronal populations, this hypothesis has not been rigorously tested. Here, we examined the representational geometry of value in the ventromedial prefrontal cortex (vmPFC), a part of the brain linked to economic decision-making. We found that values were encoded along a curved manifold in vmPFC. This curvilinear geometry predicted a specific pattern of irrational decision-making: that decision-makers will make worse choices when an irrelevant, decoy option is worse in value, compared to when it is better. Indeed, we observed these irrational choices in behavior. Together, these results not only suggest that the representational geometry of value is nonlinear, but that this nonlinearity could impose bounds on rational decision-making.

neuroscience↗

bioRxiv2021

Hierarchical organization of rhesus macaque behavior

Primatologists, psychologists and neuroscientists have long hypothesized that primate behavior is highly structured. However, fully delineating that structure has been impossible due to the difficulties of precision behavioral tracking. Here we analyzed a dataset consisting of continuous measures of the 3D position of fifteen body landmarks from two male rhesus macaques (Macaca mulatta) performing three different tasks in a large unrestrained environment over many hours. Using an unsupervised embedding approach on the tracked joints, we identified commonly repeated pose patterns, which we call postures. We found that macaques behavior is characterized by 49 distinct identifiable postures, lasting an average of 0.6 seconds each. We found evidence that behavior is hierarchically organized, in that transitions between poses tend to occur within larger modules, which correspond to intuitively identifiably actions; these actions are in turn organized hierarchically. Our behavioral decomposition allows us to identify universal (cross-individual and cross-task) and unique (specific to each individual and task) principles of behavior. These results demonstrate the hierarchical nature of primate behavior and provide a method for the automated "ethogramming" of primate behavior.

animal behavior and cognition↗

bioRxiv2021

OpenMonkeyChallenge: Dataset and Benchmark Challenges for Pose Tracking of Non-human Primates

The ability to automatically track non-human primates as they move through the world is important for several subfields in biology and biomedicine. Inspired by the recent success of computer vision models enabled by benchmark challenges (e.g., object detection), we propose a new benchmark challenge called OpenMonkeyChallenge that facilitates collective community efforts through an annual competition to build generalizable non- human primate pose tracking models. To host the benchmark challenge, we provide a new public dataset consisting of 111,529 annotated (17 body landmarks) photographs of non-human primates in naturalistic contexts obtained from various sources including the internet, three National Primate Research Centers, and the Minnesota Zoo. Such annotated datasets will be used for the training and testing datasets to develop generalizable models with standardized evaluation metrics. We demonstrate the effectiveness of our dataset quantitatively by comparing it with existing datasets based on seven state-of-the-art pose tracking models.

animal behavior and cognition↗

bioRxiv2021

Orthogonal but linked neural codes for value

Our ability to effectively choose between dissimilar options implies that information regarding the options values must be available, either explicitly or implicitly, in the brain. Explicit realizations of value involve single neurons whose responses depend on value and not on the specific features that determine it. Implicit realizations, by contrast, come from the coordinated action of neurons that encode specific features. One signature of implicit value coding is that population responses to offers with the same value but different features should occupy semi- or fully orthogonal neural subspaces that are nonetheless linked. Here, we examined responses of neurons in six core value-coding areas in a choice task with risky and safe options. Using stricter criteria than some past studies have used, we find, surprisingly, no evidence for abstract value neurons (i.e., neurons with the response to equally valued risky and safe options) in any of these regions. Moreover, population codes for value resided in orthogonal subspaces; these subspaces were linked through a linear transform of each of their constituent subspaces. These results suggest that in all six regions, populations of neurons embed value implicitly in a distributed population.

neuroscience↗

bioRxiv2020

A functional hierarchy for choice in medial prefrontal cortex

Hierarchical approaches to functional neuroanatomy propose that choice-relevant brain regions have overlapping functions and can be organized into a series that progressively transforms information about options into choices. Here, we examined responses of neurons in four regions of the medial prefrontal cortex as macaques performed two-option risky choices. All four regions encoded economic variables in similar proportions and showed putative signatures of key choice-related computations. We found evidence for a hierarchical organization proceeding from areas 14[->]25[->]32[->]24. Specifically, we found that decodability of eight distinct task variables increased along that path, consistent with the idea that hierarchically later regions make these variables more separable. We also found longer intrinsic timescales in the same series, further supporting the idea of a hierarchy. Together these results highlight the importance of the medial wall in choice, endorse a specific hierarchical organization, and argue against a modular functional neuroanatomy of choice.

neuroscience↗

bioRxiv2020

Ultra-high field (10.5 T) resting state fMRI in the macaque

Resting state functional connectivity refers to the temporal correlations between spontaneous hemodynamic signals obtained using functional magnetic resonance imaging. This technique has demonstrated that the structure and dynamics of identifiable networks are altered in psychiatric and neurological disease states. Thus, resting state network organizations can be used as a diagnostic, or prognostic recovery indicator. However, much about the physiological basis of this technique is unknown. Thus, providing a translational bridge to an optimal animal model, the macaque, in which invasive circuit manipulations are possible, is of utmost importance. Current approaches to resting state measurements in macaques face unique challenges associated with signal-to-noise, the need for invasive contrast agents, and within-subject designs. These limitations can, in principle, be overcome through ultra-high magnetic fields. However, ultra-high field imaging has yet to be adapted for fMRI in macaques. Here, we demonstrate that the combination of high channel count transmitter and receiver arrays, optimized pulse sequences, and careful anesthesia regimens, allows for detailed within-subject resting state analysis at ultra-high resolutions. In this study, we uncover thirty spatially detailed resting state components that are highly robust across individual macaques and closely resemble the quality and findings of connectomes from large human datasets. This detailed map of the rsfMRI macaque connectome will be the basis for future neurobiological circuit manipulation work, providing valuable biological insights into human connectomics.

neuroscience↗

bioRxiv2020

OpenMonkeyStudio: Automated Markerless Pose Estimation in Freely Moving Macaques

The rhesus macaque is an important model species in several branches of science, including neuroscience, psychology, ethology, and several fields of medicine. The utility of the macaque model would be greatly enhanced by the ability to precisely measure its behavior, specifically, its pose (position of multiple major body landmarks) in freely moving conditions. Existing approaches do not provide sufficient tracking. Here, we describe OpenMonkeyStudio, a novel deep learning-based markerless motion capture system for estimating 3D pose in freely moving macaques in large unconstrained environments. Our system makes use of 62 precisely calibrated and synchronized machine vision cameras that encircle an open 2.45mx2.45mx2.75m enclosure. The resulting multiview image streams allow for novel data augmentation via 3D reconstruction of hand-annotated images that in turn train a robust view-invariant deep neural network model. This view invariance represents an important advance over previous markerless 2D tracking approaches, and allows fully automatic pose inference on unconstrained natural motion. We show that OpenMonkeyStudio can be used to accurately recognize actions and track two monkey social interactions without human intervention. We also make the training data (195,228 images) and trained detection model publicly available.

neuroscience↗

bioRxiv2019

Overstaying in patchy foraging can be explained by behavioral variability

Foragers often systematically deviate from rate-maximizing choices in two ways: in accuracy and precision. That is, they both use suboptimal threshold values and show variability in their application of those thresholds. We hypothesized that these biases are related and, more specifically, that foragers widely known accuracy bias - over-staying - could be explained, at least in part, by their precision bias. To test this hypothesis, we analyzed choices made by three rhesus macaques in a computerized patch foraging task. Confirming previously observed findings, we find high levels of variability. We then show, through simulations, that this variability changes optimal thresholds, meaning that a forager aware of its own variability should increase its leaving threshold (i.e., over-stay) to increase performance. All subjects showed thresholds that were biased in the predicted direction. These results indicate that over-staying in patches may reflect, in part, an adaptation to behavioral variability.

animal behavior and cognition↗

bioRxiv2019

The Neural Basis of Predictive Pursuit

It remains unclear how and to what extent non-human animals make demanding on-the-fly predictions during pursuit. We studied this problem in a novel laboratory pursuit task that incentivizes prediction of future prey positions. We trained three macaques to perform joystick-controlled pursuit of prey that followed intelligent escape algorithms. Subjects reliably aimed towards the preys likely future positions, indicating that they generate internal predictions and use those predictions to guide behavior. We then developed a generative model that explains real-time pursuit trajectories and showed that our subjects use prey position, velocity, and acceleration to make predictions. We identified neurons in the dorsal anterior cingulate cortex (dACC) whose responses track these three variables. These neurons multiplexed prediction-related variables with a distinct and explicit representation of the preys future position. Our results provide a clear demonstration that the brain can explicitly represent future predictions and highlight the critical role of anterior cingulate cortex for future-oriented cognition.\n\nOne-sentence summaryIn a dynamic pursuit environment, monkeys actively predict future prey positions and dACC neurons encode these future positions.

neuroscience↗

bioRxiv2019

A Comparison of Non-human Primate and Deep Reinforcement Learning Agent Performance in a Virtual Pursuit-Avoidance Task

We compare the performance of non-human primates and deep reinforcement learning agents in a virtual pursuit-avoidance task, as part of an effort to understand the role that cognitive control plays in the deeply evolved skill of chase and escape behavior. Here we train two agents, a deep Q network and an actor-critic model, on a video game in which the player must capture a prey while avoiding a predator. A previously trained rhesus macaque performed well on this task, and in a manner that obeyed basic principles of Newtonian physics. We sought to compare the principles learned by artificial agents with those followed by the animal, as determined by the ability of one to predict the other. Our findings suggest that the agents learn primarily 1st order physics of motion, while the animal exhibited abilities consistent with the 2nd order physics of motion. We identify scenarios in which the actions taken by the animal and agents were consistent as well as ones in which they differed, including some surprising strategies exhibited by the agents. Finally, we remark on how the differences between how the agents and the macaque learn the task may affect their peak performance as well as their ability to generalize to other tasks.

neuroscience↗

bioRxiv2018

Risk aversion in macaques in a freely moving patch-leaving foraging task

Animals, including humans, are risk-averse in most contexts. A major exception is the rhesus macaque (Macaca mulatta), which is robustly risk-seeking. Macaques unique preferences may reflect their unique evolutionary history. Alternatively, they may derive from elements of task design associated with the demands of physiological recording, the source of nearly all macaque risk preference data. To disambiguate these possibilities we assessed macaques risk attitudes in a somewhat more naturalistic environment: subjects foraged at four feeding stations in a large enclosure. Stations (i.e. patches) provided either stochastically or non-stochastically depleting rewards. Subjects patch residence times were longer at safe than at risky stations, indicating a preference for safe options. This preference was not attributable to a win-stay-lose-shift heuristic. These findings highlight the lability of risk attitudes in macaques and support the hypothesis that observed differences between macaques and other species are ephemeral, not evolved.

animal behavior and cognition↗

bioRxiv2018

Exploratory noise governs both flexibility and spontaneous errors and is regulated by cocaine

In many cognitive processes, lapses (spontaneous errors) are attributed to nuisance processes like sensorimotor noise or disengagement. However, some lapses could also be caused by exploratory noise: behavioral randomness that facilitates learning in changing environments. If so, strategic processes would need only up-regulate (rather than generate) exploration to adapt to a changing environment. This view predicts that lapse rates should be correlated with flexibility because they share a common cause. We report that when macaques performed a set-shifting task, lapse rates were negatively correlated with perseverative error frequency. Furthermore, chronic exposure to cocaine, which impairs cognitive flexibility, increased perseverative errors, but, surprisingly, improved overall performance by reducing lapse rates. We reconcile these results with a model in which cocaine decreased exploration by deepening attractor basins corresponding to rules. These results support the idea that exploratory noise contributes to lapses, meaning that it affects rule-based decision-making even when it has no strategic value.

neuroscience↗

bioRxiv2018

Opposing pupil responses to offered and anticipated reward values

Previous studies have shown that the pupils dilate more in anticipation of larger rewards. This finding raises the possibility of a more general association between reward amount and pupil size. We tested this idea by characterizing macaque pupil responses to offered rewards during evaluation and comparison in a binary choice task. To control attention, we made use of a design in which offers occurred in sequence. By looking at pupil responses after choice but before reward, we confirmed the previously observed positive association between pupil size and anticipated reward values. Surprisingly, however, we find that pupil size is negatively correlated with the value of offered gambles before choice, during both evaluation and comparison stages of the task. These results demonstrate a functional distinction between offered and anticipated rewards, and present evidence against a narrow version of the simulation hypothesis, the idea that we represent offers by reactivating states associated with anticipating them. They also suggest that pupil size is correlated with relative, not absolute, values of offers, suggestive of an accept-reject model of comparison.

neuroscience↗

bioRxiv2018

Monkeys predict trajectories of virtual prey using basic variables from Newtonian physics.

The demands of foraging are a major driver in the evolution of cognitive faculties. To successfully pursue a mobile prey that is attempting to avoid capture, the ability to predict its flight path can provide a crucial advantage. We hypothesized that, during pursuit, rhesus macaques exploit patterns in preys behavior to predict the preys future positions. We modeled behavior of three macaques in a joystick-controlled pursuit task in which prey follow simple escape algorithms that involve repulsion from the subject and from the walls of the virtual enclosure. We find that, even in this artificial task, macaques actively predict and aim towards preys future positions, increasing their foraging success. Their predictions are derived from the three core variables in Newtonian dynamics: position, velocity, and acceleration. Even after extensive training, subjects favored these principles and ignored other regularities in prey behavior. Most notably, they ignored the effects their own actions would have on the prey, despite extensive training and even though doing so would have further improved performance. We conjecture that subjects have a strong bias towards using physical principles to pursue fleeing prey, possibly reflecting an evolved physics module. The observed predictive behavior suggests that foraging demands facilitate the development of prospection.

animal behavior and cognition↗