Biology subjects

Gail, A.

Publications and source records attributed to Gail, A..

15 recordsLinked to original sources

bioRxiv2026

Multivariate Transfer Entropy Quantifies Information Transfer Between Dyadic Partners During Real-Time Perceptual Decision-Making

1Many social behaviours unfold continuously in time, yet most studies of social influence rely on discrete, trial-based paradigms. To quantify how humans actually integrate sensory and social signals during ongoing perceptual decision-making we here apply an information-theoretic analysis to data obtained with the Continuous Perceptual Report (CPR) paradigm. In the CPR task, pairs of participants tracked a dynamic random-dot motion stimulus, continuously reporting perceived direction and their confidence. Crucially, each participant had access to their partners moment-by-moment direction and confidence reports embedded within the stimulus display. We quantified information flow between the stimulus and behavioural responses using multivariate transfer entropy, allowing us to detect whether participants acquired additional information from their partner once stimulus information had been received and integrated it into their behavioural response. We show that real-time social interactions predominantly occur within matching behavioural dimensions: partners perceptual choices influence participants own choices, and partners confidence influences participants confidence. Using both, more stimulus and social information contributed to improved task performance, and participants selectively acquired more information from better-performing partners. Crucially, information integration was flexibly modulated by stimulus reliability: as sensory evidence became noisier, participants relied more on social information, but only when interacting with a highly reliable (e.g. computer-controlled) partner. Latency analyses further revealed that participants responded faster to changes in their partners perceptual choices of direction than to changes in stimulus direction. They also responded more slowly to changes in their partners confidence than to changes in their partners choice of direction. Together, these findings demonstrate that humans dynamically and adaptively integrate social information in a time-continuous manner, and they establish multivariate information-theoretic analyses as a powerful framework for studying real-time social cognition.

animal behavior and cognition↗

bioRxiv2025

Continuous dynamics of cooperation and competition in social foraging

Real-life social interactions often unfold continuously and involve dynamic cooperation and competition, yet most studies rely on discrete games that do not capture the adaptive and graded nature of continuous sensorimotor decisions. To address this gap, we developed the Cooperation-Competition Foraging game -- an ecologically grounded paradigm in which pairs of participants (dyads) navigate a continuous shared space under face-to-face visibility, deciding in real-time to collect rewarded targets either individually or jointly. Dyads (n=58, 116 participants) spontaneously converged on distinct stable strategies along the cooperation-competition spectrum, forming three groups: cooperative, intermediate, and competitive. Despite the behavioral complexity, our computational model, which incorporated travel path minimization, sensorimotor communication, and recent choice history, predicted dyadic decisions with 87% accuracy, and linked prediction certainty with ensuing dynamics of spatiotemporal coordination. Further modeling revealed how sensorimotor factors, such as movement speed and skill, shape distinct strategies and payoffs. Crucially, we quantify the cost of cooperation, demonstrating that in many dyads prosocial tendencies outweigh the individual benefits of exploiting skill advantages. Our versatile framework provides a predictive, mechanistic account of how social and embodied drivers promote the emergence of dynamic cooperation and competition, and offers rigorous metrics for investigating the neural basis of naturalistic social interactions, and for linking personality traits to distinct strategies.

neuroscience↗

bioRxiv2024

Planning and movement activities co-adapt in a motor-reference frame during 3D BCI-controlled reach adaptation in monkey frontal and parietal cortices

Perturbing visual feedback is a powerful tool for studying visuomotor adaptation. However, unperturbed proprioceptive signals in common paradigms inherently co-varies with physical movements and causes incongruency with the visual input. This can create challenges when interpreting underlying neurophysiological mechanisms. We employed a brain-computer interface (BCI) in rhesus monkeys to investigate spatial encoding in frontal and parietal areas during a 3D visuomotor rotation task where only visual feedback was movement-contingent. We found that both brain regions better reflected the adapted motor commands than the perturbed visual feedback during movement preparation and execution. This adaptive response was observed in both local and remote neurons, even when they did not directly contribute to the BCI input signals. The transfer of adaptive changes in planning activity to corresponding movement corrections was stronger in the frontal than in the parietal cortex. Our results suggest an integrated large-scale visuomotor adaptation mechanism in a motor-reference frame spanning across frontoparietal cortices.

neuroscience↗

bioRxiv2024

Freely foraging macaques value information in ambiguous terrains

Among non-human primates, macaques are recognized for thriving in a wide range of novel environments. Previous studies show macaques affinity for new information. However, little is known about how information-seeking manifests in their spatial navigation pattern in ambiguous foraging terrains, where the location and distribution of the food are unknown. We investigated the spatial pattern of foraging in free-moving macaques in an ambiguous terrain, lacking sensory cues about the reward distribution. Rewards were hidden in a uniform grid of woodchip piles spread over a 15 sqm open terrain and spatially distributed according to different patchy distributions. We observed Levy-like random walks in macaques spatial search pattern, balancing relocation effort with exploration. Encountering rewards altered the foraging path to favor the vicinity of discovered rewards temporarily, without preventing longer-distance travels. These results point toward continuous exploration, suggesting that explicit information-seeking is a part of macaques foraging strategy. We further quantified the role of information seeking using a kernel-based model, combining a map of ambiguity, promoting information seeking, with a map of discovered rewards and a map of proximity. Fitting this model to the foraging paths of our macaques revealed individual differences in their relative preference for information, reward, or proximity. The model predicted that a balanced contribution of all three factors performs and adapts to an ambiguous terrain with semi-scattered rewards, a prediction we confirmed using further experimental evidence. We postulate an explicit role for seeking information as a valuable entity to reduce ambiguity in macaques foraging strategies, suggesting an ecologically valid way of foraging ambiguous terrains. Author SummaryIn a novel and ambiguous terrain lacking sensory information about the location or distribution of food, foragers obtain information by sampling. This process is crucial for animals thriving in a new habitat. We allowed free-roaming macaques to forage at their own pace in a controlled terrain to which they had limited prior exposure. Based on their foraging paths, we developed a computational model representing an individuals drive for reward-seeking, information-seeking, or energy preservation. These drives were represented as superimposing maps from the foragers perspective. We found that information-seeking, continuous exploration of unknown areas, is crucial for foraging under ambiguity. This finding is consistent with a theory suggesting that animals, specifically humans and other primates, seek information to reduce their uncertainty about the environment. Our study suggests that the statistical properties of primates random foraging patterns reveal their complex decision-making process, including adaptation to novel environments.

animal behavior and cognition↗

bioRxiv2024

PriMAT: A robust multi-animal tracking model for primates in the wild

O_LIDetection and tracking of animals is an important first step for automated behavioral studies using videos. Animal tracking is currently done mostly using deep learning frameworks based on keypoints, which show remarkable results in lab settings with fixed cameras, backgrounds, and lighting. However, multi-animal tracking in the wild presents several challenges such as high variability in background and lighting conditions, complex motion, and occlusion. C_LIO_LIWe propose a multi-animal tracking model, PriMAT, for nonhuman primates in the wild. The model learns to detect and track primates and other objects of interest from labeled videos or single images using bounding boxes instead of keypoints. Using bounding boxes significantly facilitates data annotation and robustness. Our one-stage model is conceptually simple but highly flexible, and we add a classification branch that allows us to train individual identification. C_LIO_LITo evaluate the performance of our model, we applied it in two case studies with Assamese macaques (Macaca assamensis) and redfronted lemurs (Eulemur rufifrons) in the wild. We show that with only a few hundred frames labeled with bounding boxes, we can achieve robust tracking results. Combining these results with the classification branch for the lemur videos, our model shows an accuracy of 84% in predicting lemur identities. C_LIO_LIOur approach presents a promising solution for accurately tracking and identifying animals in the wild, offering researchers a tool to study animal behavior in their natural habitats. Our code, models, training images, and evaluation video sequences are publicly available1, facilitating their use for animal behavior analyses and future research in this field. C_LI

animal behavior and cognition↗

bioRxiv2024

Confidence over competence: Real-time integration of social information in human continuous perceptual decision-making

Human perceptual decision-making is susceptible to social influences. To determine if and how individuals opportunistically integrate real-time social information about noisy stimuli into their judgment, we tracked perceptual accuracy and confidence in social (dyadic) and non-social (solo) settings using a novel continuous perceptual report (CPR) task with peri-decision wagering. In the dyadic setting, most participants showed a higher degree of perceptual confidence. In contrast, average accuracy did not improve compared to solo performance. Underlying these net effects, partners in a dyad exhibit mutual convergence of accuracy and confidence, benefiting less competent or confident individuals, at the expense of the better-performing partner. In conclusion, real-time social information asymmetrically shapes human perceptual decision-making, with most dyads expressing more confidence without a matching gain in overall competence.

neuroscience↗

bioRxiv2024

A model for cortical activity sequences

Networks of neurons in the brain, that act on a timescale of milliseconds, can intrinsically generate reliable sequential activity on slow behavioral timescales of seconds. A possible mechanism for intrinsic sequence generation based on theoretical evidence points to distance-dependent connectivity with correlated spatial asymmetries, establishing an anisotropic network connectivity. We show that networks with such correlated asymmetric connectivity as well as symmetric distance-dependent connectivity match experimental data of connectivity motifs as well as neuronal activity statistics from rat and monkey cortex. At the network level, however, only the correlated asymmetric connectivity pattern generates spatiotemporal activity sequences on behaviorally relevant timescales, while the symmetric connectivity results in transient but stationary spatial bumps of neural activity. Our results strongly support the role of correlated asymmetries in connectivity for the generation of sequential activity in neural networks.

neuroscience↗

bioRxiv2022

Position- and scale-invariant object-centered spatial selectivity in monkey frontoparietal cortex dynamically adapts to task demand

Humans utilize egocentric and allocentric spatial information to guide goal-directed movements. Egocentric encoding is a well-known property of brain areas along the dorsal pathway. We ask if dorsal stream reach planning areas like parietal reach region (PRR) and dorsal premotor cortex (PMd) also encode object-centered (allocentric) information. During two consecutive instructed delay periods, rhesus monkeys first memorized an object-relative target position and then planned a reach to this position after the object re-occurred at variable positions with potentially different size. In both areas, we find predominant object-centered encoding during visual memory, which is invariant to object position and object size, and predominant egocentric encoding during reach planning. Such dynamic transition from allo- to egocentric encoding within individual dorsal stream areas contrasts the idea of task-independent functional segregation between processing pathways. Instead, demand-specific local computations might facilitate spatial cognition in dynamic environments to facilitate motor planning towards objects changing their location. Significance statementHuman and non-human primates interact with their environment by manipulating objects. This requires planning and executing reaches to transport the hand to object-relative positions close to or on the object. Previous studies showed that frontal and parietal lobe areas encode reach goals in coordinate systems anchored to different parts of the subjects body, such as hand position or gaze direction, and modulated by pose. We show that neurons in the same areas can encode object-centered allocentric spatial information, independent of object location and object size, or egocentric information, depending on dynamically changing task demands. Such dynamic adaptation seems inconsistent with a functional segregation for ego- and allocentric encoding between processing streams.

neuroscience↗

bioRxiv2022

Universal guide for skull extraction and custom-fitting of implants to continuous and discontinuous skulls

Intracranial neurophysiological recordings require chronic implants to provide transcranial access to the brain. Especially in larger animals, which participate in experiments over extended periods of time, implants should match the skull curvature to promote osseointegration and avoid tissue and bacterial ingress over time. Proposed CAD methods for designing implants to date have focused on naive animals with continuous and even skull surfaces and calculate Boolean differences between implant and skull surface to fit the implant to the skull curvature. However, custom-fitting by calculating the difference fails, if a discontinuous skull surface needs to be matched. Also, the difference method does not allow designs with constant material thickness along the skull curvature, e.g. to allow fixed screw lengths. We present a universal step-by-step guide for custom-fitting implants which overcomes these limitations. It is suited for unusual skull conditions, like surface discontinuities or irregularities and includes virtual bending as a process to match skull surfaces while maintaining implant thickness. We demonstrate its applicability for a wide spectrum of scenarios, ranging from complex-shaped single-pieced implants to detailed multi-component implant systems built on even or discontinuous skull. The guide uses only a few software tools and the final virtual product can be manufactured using CNC milling or 3D printing. A detailed description of this process is available on GitHub including step-by-step video instructions suitable for users without any prior knowledge in CAD programming. We report the experience with these implants over several years in 11 rhesus monkeys. Significance StatementChronic implants are essential for intracranial neurophysiological recordings. In this study we show how to custom-design and -fit such implants for rhesus monkeys (Macacca mulatta). Different to existing approaches, our procedure is not limited to even skull surfaces but can be applied to discontinuous or irregular surfaces. It furthermore presents a description of virtual implant bending to match the skull curvature while maintaining implant thickness. The final virtual product can be manufactured using CNC milling or 3D printing. In contrast to previous studies, this guide is suited for users without any prior expertise in CAD programming using our step-by-step video instructions.

neuroscience↗

bioRxiv2021

Statistical determinants of visuomotor adaptation in a virtual reality three-dimensional environment

Neurorehabilitation in patients suffering from motor deficits relies on relearning or re-adapting motor skills. Yet our understanding of motor learning is based mostly on results from one or two-dimensional experimental paradigms with highly confined movements. Since everyday movements are conducted in three-dimensional space, it is important to further our understanding about the effect that gravitational forces or perceptual anisotropy might or might not have on motor learning along all different dimensions relative to the body. Here we test how well existing concepts of motor learning generalize to movements in 3D. We ask how a subjects variability in movement planning and sensory perception influences motor adaptation along three different body axes. To extract variability and relate it to adaptation rate, we employed a novel hierarchical two-state space model using Bayesian modeling via Hamiltonian Monte Carlo procedures. Our results show that differences in adaptation rate occur between the coronal, sagittal and horizontal planes and can be explained by the Kalman gain, i.e., a statistically optimal solution integrating planning and sensory information weighted by the inverse of their variability. This indicates that optimal integration theory for error correction holds for 3D movements and explains adaptation rate variation between movements in different planes.

neuroscience↗

bioRxiv2020

The Cone Method: Inferring Decision Times from Single-Trial 3D Movement Trajectories in Choice Behavior

Ongoing goal-directed movements can be rapidly adjusted following new environmental information, e.g. when chasing pray or foraging. This makes movement trajectories in go-before-you-know decision-making a suitable behavioral readout of the ongoing decision process. Yet, existing methods of movement analysis are often based on statistically comparing two groups of trial-averaged trajectories and are not easily applied to three-dimensional data, preventing them from being applicable to natural free behavior. We developed and tested the cone method to estimate the point of overt commitment (POC) along a single two- or three-dimensional trajectory, i.e. the position where movement is adjusted towards a newly selected spatial target. In Experiment 1, we established a "ground truth" data set in which the cone method successfully identified the experimentally constrained POCs across a wide range of all but the shallowest adjustment angles. In Experiment 2, we demonstrate the power of the method in a typical decision-making task with expected decision time differences known from previous findings. The POCs identified by cone method matched these expected effects. In both experiments, we compared the cone methods single trial performance with a trial-averaging method and obtained comparable results. We discuss the advantages of the single-trajectory cone method over trial-averaging methods and possible applications beyond the examples presented in this study. The cone method provides a distinct addition to existing tools used to study decisions during ongoing movement behavior, which we consider particularly promising towards studies of non-repetitive free behavior.

neuroscience↗

bioRxiv2020

Human and macaque pairs coordinate differently in a dyadic decision game with face-to-face action visibility

Many real-world decisions in social contexts are made while observing a partners actions. To study dynamic interactions during such decisions, we developed a setup where two agents seated face-to-face engage in game-theoretical tasks on a shared transparent touchscreen display ("transparent games"). We compared human and macaque pairs in a transparent version of the coordination game "Bach-or-Stravinsky", which entails a conflict about which of two individually-preferred opposing options to choose to achieve coordination. Most human pairs developed coordinated behavior and adopted dynamic turn-taking to equalize the payoffs. All macaque pairs converged on simpler, static coordination. Remarkably, two animals learned to coordinate dynamically after training with a human confederate. This pair selected the faster agents preferred option, exhibiting turn-taking behavior that was captured by modeling the visibility of the partners action before ones own movement. Such competitive turn-taking was unlike the prosocial turn-taking in humans, who equally often initiated switches to and from their preferred option. Thus, the dynamic coordination is not restricted to humans, but can occur on the background of different social attitudes and cognitive capacities in rhesus monkeys. Overall, our results illustrate how action visibility promotes emergence and maintenance of coordination when agents can observe and time their mutual actions.

neuroscience↗

bioRxiv2019

Comparing open-source toolboxes for processing and analysis of spike and local field potentials data

Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific research. Today there exist many open-source toolboxes for spike and LFP data analysis implementing various functionality. Here we aim to provide a practical guidance for neuroscientists in the choice of an open-source toolbox best satisfying their needs. We overview major open-source toolboxes for spike and LFP data analysis as well as toolboxes with tools for connectivity analysis, dimensionality reduction and generalized linear modeling. We focus on comparing toolboxes functionality, statistical and visualization tools, documentation and support quality. To give a better insight, we compare and illustrate functionality of the toolboxes on open-access dataset or simulated data and make corresponding MATLAB scripts publicly available.

neuroscience↗

bioRxiv2018

The Reach Cage environment for wireless neural recordings during structured goal-directed behavior of unrestrained monkeys

System neuroscience of motor cognition regarding the space beyond immediate reach mandates free, yet experimentally controlled movements. We present an experimental environment (Reach Cage) and a versatile visuo-haptic interaction system (MaCaQuE) for investigating goal-directed whole-body movements of unrestrained monkeys. Two rhesus monkeys conducted instructed walk-and-reach movements towards targets flexibly positioned in the cage. We tracked 3D multi-joint arm and head movements using markerless motion capture. Movements show small trial-to-trial variability despite being unrestrained. We wirelessly recorded 192 broad-band neural signals from three cortical sensorimotor areas simultaneously. Single unit activity is selective for different reach and walk-and-reach movements. Walk-and-reach targets could be decoded from premotor and parietal but not motor cortical activity during movement planning. The Reach Cage allows systems-level sensorimotor neuroscience studies with full-body movements in a configurable 3D spatial setting with unrestrained monkeys. We conclude that the primate frontoparietal network encodes reach goals beyond immediate reach during movement planning.

neuroscience↗

bioRxiv2018

Using imaging photoplethysmography for heart rate estimation in non-human primates

For humans and for non-human primates heart rate is a reliable indicator of an individuals current physiological state, with applications ranging from health checks to experimental studies of cognitive and emotional state. In humans, changes in the optical properties of the skin tissue correlated with cardiac cycles (imaging photoplethysmogram, iPPG) allow non-contact estimation of heart rate by its proxy, pulse rate. Yet, there is no established simple and non-invasive technique for pulse rate measurements in awake and behaving animals. Using iPPG, we here demonstrate that pulse rate in rhesus monkeys can be accurately estimated from facial videos. We computed iPPGs from seven color facial videos of three awake head-stabilized rhesus monkeys. Pulse rate estimated from iPPGs was in good agreement with reference data from a pulse-oximeter with error of pulse rate estimation below 5% for 82% of all epochs, and below 10% for 98% of the epochs. We conclude that iPPG allows non-invasive and non-contact estimation of pulse rate in non-human primates, which is useful for physiological studies and can be used toward welfare-assessment of non-human primates in research.

bioengineering↗