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Womelsdorf, T.

Publications and source records attributed to Womelsdorf, T..

At least 19 recordsLinked to original sources
bioRxiv2026

Planning in Nonhuman Primates Emerges from Structure Knowledge and is Distinct from Attention, Working Memory, Effort Control, and Learning

Forward planning involves mentally simulating future choices. Such mental simulation may constitute an independent cognitive operation, or it may be intricately linked to canonical cognitive operations supporting working memory of choice options, covert attentional information sampling, forming memory models of problem structure and effort control for pursuing future goals. Here, we test the relative independence of planning in non-human primates with an object-sequence planning task assessed together with an assay of simpler cognitive tasks. The sequence task unexpectedly masked objects at future serial positions probing NHPs to plan ahead serial future choices. We found that five of six subjects planned ahead 2-3 ordinal positions. Planning depth was predicted by knowledge of the serial structure but constituted a unique cognitive factor that was distinct from sequence memory, object memory, and learning efficacy. Similarly, planning was segregated from working memory capacity, attention, inhibitory control and effort control. These findings suggest that planning ahead constitutes a separate construct not reducible to other domain-general cognitive operations, and emerges in NHPs that successfully form an internal model of the problem structure.

animal behavior and cognition↗
bioRxiv2026

Cognitive engagement induces area-specific fingerprints of dopamine, acetylcholine, serotonin, glutamate and GABA in prefrontal cortex and striatum

Cholinergic, dopaminergic and serotonergic neuromodulation has pervasive effects on circuit functions in prefrontal cortex (PFC) and striatum and interact with glutamatergic and GABAergic transmission. But how these neurochemicals interact during cognitive engagement is largely unknown and inferred from studying few neuromodulators at a time. Here, we sampled the extracellular availabilities of five neurochemicals in the PFC and striatum of nonhuman primates and tested how they changed when subjects switched from rest to engage in a cognitive set shifting task using miniaturized probes for diffusion-based solid-phase microextraction. Cognitive engagement was best predicted by GABAergic and cholinergic changes in the PFC, and dopaminergic and cholinergic changes in the striatum. Glutamate co-modulated with acetylcholine across states in both the PFC and striatum, while serotonin changes in PFC and striatum correlated consistent with common external modulation. These findings document an area-specific multi-neuromodulatory fingerprint of an adaptive cognitive state in the fronto-striatal network of the nonhuman primate brain. TeaserEngaging in a cognitive task reshapes neurochemical profiles across the fronto-striatal network of the primate brain

neuroscience↗
bioRxiv2026

Inhibitory Control, Shifting, and Working Memory Updating Domains form Cognitive Phenotypes in Non-human Primates

Executive functions comprise at least four major subdomains: Inhibitory Control, Updating, Shifting, and Working Memory. Cognitive abilities in these subdomains are partially separable and partially unified in a common cognitive control factor in humans, but how these functions are organized in the nonhuman primate (NHP) is largely unknown. Here, we used a multi-task assessment approach and found that NHPs show within single sessions reliable cognitive markers of Inhibitory Control in an antisaccade task, (ii) Updating abilities in a multidimensional continuous updating task, (iii) Working Memory in a delayed matching task, and (iv) Shifting abilities in a feature-based rule learning task. First, we found that subjects performance fell into three separable cognitive phenotypes with unique strengths and weaknesses across cognitive subdomains. Second, beyond individual tasks cognitive metrics gave rise to four latent cognitive factors separating abilities for shifting/learning and working memory updating, and distinguishing abilities in inhibitory control of exogeneous versus endogenous interference. These results document four separable latent cognitive factors underlying executive control performance in this NHP sample, with inter-subject differences of these factors forming cognitive phenotypes.

animal behavior and cognition↗
bioRxiv2025

Two Distinct Attentional Priorities Guide Exploratory and Exploitative Gaze in Parallel

Gaze is directed to visual objects that are informative, reward-predictive, or novel. These gaze preferences may reflect the parallel influence of two separable attention systems: Exploratory attention prioritizing uncertainty and exploitative attention prioritizing learned information about reward. We tested this hypothesis in nonhuman primates learning feature-based attention to objects that had either previously learned reward associations or were novel. The reward history of features slowed down learning by attracting fixations of non-rewarded distractors that were previously targets. This reward history bias persisted in fixations used to choose objects even after choice accuracy stabilized. In contrast, fixational sampling that preceded a choice showed negligible history biases that were overcome quickly in favor of wider exploratory sampling. Quantifying the exploratory value object features with a Parallel Belief States model of attention confirmed that exploratory fixational sampling was unaffected by reward history, while exploitative fixations that committed to a decision showed persistent target history biases. These findings suggest that gaze is guided by two separable attentional priorities in parallel. Exploratory attention prioritizes uncertain items and instantiates information sampling, while exploitative attentional priority guides gaze to current and previously goal-relevant features.

animal behavior and cognition↗
bioRxiv2025

Parallel Belief States account for Learning and Updating of Attentional Priorities in Multidimensional Environments

Inferring the behavioral relevance of visual features is difficult in multidimensional environments as many features could be important. One solution could involve tracking the experience with multiple features and using attentional control to decide which subset of features to explore and chose. Here, we characterize this attentional control process with a model of parallel belief states and test it with a task requiring the learning and updating of attention to features with varying selection histories and motivational costs. We found that exploring and exploiting features was accounted for by a model that tracks the latent beliefs about the relevance of multiple features in parallel. These parallel belief states accounted for the fast learning of feature-based attention, for perseverative selection history effects for features that were previously relevant, and for enhanced learning performance when the motivational costs of making errors increased. Taken together, these results quantify how multiple parallel belief states guide exploration and exploitation of feature-based attention during learning. We suggest parallel belief states represent attentional priorities that are read out by a competitive attentional control process to explore and exploit those visual objects in multidimensional environments that are believed to be relevant. Significance statementDuring goal-directed behavior attention is allocated to features relevant for the behavioral goal. But in real-world settings with multidimensional objects, it is often unknown which features are maximally relevant and should be attentionally prioritized. We found a solution to this problem by quantifying the hidden beliefs about the relevance of multiple features in parallel. By tracking belief states about feature relevance we found that subjects consider multiple features in parallel during the learning of feature-based attention. These belief states correspond to attentional priorities and explained when attention is biased towards previously relevant but now irrelevant features, and when learning about relevant features is enhanced by motivational incentives. These findings quantify the parallel hidden beliefs that guide attention in complex environments.

neuroscience↗
bioRxiv2025

Neuronal Decoding of Decisions in Multidimensional Feature Space Using a Gated Recurrent Variational Autoencoder

Recent advances in neuroscience enable recording neuronal signals across hundreds of channels while subjects perform complex tasks involving multiple stimulus dimensions. In this study, we developed a novel encode-decode-classify framework employing a gated recurrent variational autoencoder (VAE) to decode decision-making processes from over 300 simultaneously recorded neuronal channels in the prefrontal cortex and basal ganglia of monkeys performing a multidimensional feature-learning task. Using hierarchical stratified sampling and balanced accuracy, we trained and evaluated the models ability to predict behavioral choices based on neuronal population dynamics. The results revealed distinct neural coding roles, with anterior cingulate cortex (ACC) channels encoding decision variables collectively and prefrontal cortex (PFC) channels contributing individually to decoding accuracy. This approach demonstrated decoding accuracy for decisions in multi-dimensional feature space that is comparable to single-label decoding accuracy for lower dimensional problems, highlighting the potential of machine learning frameworks to capture complex spatiotemporal neuronal interactions involved in multidimensional cognitive behaviors. The code has been released in https://github.com/cgerrity/Neural-Data-Reading

neuroscience↗
bioRxiv2025

KIASORT: Knowledge-Integrated Automated Spike Sorting for Geometry-Free Neuron Tracking

Modern high-density neural recordings demand spike sorting algorithms that can handle diverse probe geometries and complex, neuron-specific drift, yet existing methods often rely on rigid geometric assumptions and one-dimensional drift models. Here, we introduce KIASORT (Knowledge-Integrated Automated Spike Sorting), a geometry-free approach for per-neuron drift tracking. KIASORT trains channel-specific classifiers in a hybrid linear-nonlinear embedding space, capturing waveform features often missed by conventional linear methods. These classifiers then sort spikes by independently tracking each neuron, unconstrained by probe layout. Biophysical simulations showed that even sub-micron probe displacements induce neuron-specific waveform distortions that standard drift models cannot correct. In ground-truth benchmarks with heterogeneous, neuron-specific drift, KIASORT significantly outperformed Kilosort4 in recovering high-quality units, while maintaining real-time performance on standard CPUs. Its robustness was further validated on both primate and mouse data. KIASORT combines automated sorting with manual curation in a unified graphical interface, offering a complete and user-friendly spike sorting platform. The software is freely available at https://kiasort.com.

neuroscience↗
bioRxiv2025

Assessing Attentiveness and Cognitive Engagement across Tasks using Video-based Action Understanding in Non-Human Primates

BackgroundDistractibility and attentiveness are cognitive states that are expressed through observable behavior. The effective use of behavior observed in videos to diagnose periods of distractibility and attentiveness is still not well understood. Video-based tools for classifying cognitive states from behavior have high potential to serve as versatile diagnostic indicators of maladaptive cognition. New methodWe describe an analysis pipeline that classifies cognitive states using a 2-camera set-up for video-based estimation of attentiveness and screen engagement in nonhuman primates performing cognitive tasks. The procedure reconstructs 3D poses from 2D labeled DeepLabCut videos, reconstructs the head/yaw orientation relative to a task screen, and arm/hand/wrist engagements with task objects, to segment behavior into an attentiveness and engagement score. ResultsPerformance of different cognitive tasks were robustly classified from video within a few frames, reaching >90% decoding accuracy with [≤]3min time segments. The analysis procedure allows setting subject-specific thresholds for segmenting subject specific movements for a time-resolved scoring of attentiveness and screen engagement. Comparison with existing methodsCurrent methods also extract poses and segment action units; however, they havent been combined into a framework that enables subject-adjusted thresholding for specific task contexts. This integration is needed for inferring cognitive state variables and differentiating performance across various tasks. ConclusionThe proposed method integrates video segmentation, scoring of attentiveness and screen engagement, and classification of task performance at high temporal resolution. This integrated framework provides a tool for assessing attention functions from video.

animal behavior and cognition↗
bioRxiv2024

A Toolbox for Generating Multidimensional 3-D Objects with Fine-Controlled Feature Space: Quaddle 2.0

Multidimensional 3D-rendered objects are an important component of vision research and video- gaming applications, but it has remained challenging to parametrically control and efficiently generate those objects. Here, we describe a toolbox for controlling and efficiently generating 3D rendered objects composed of ten separate visual feature dimensions that can be fine-adjusted using python scripts. The toolbox defines objects as multi-dimensional feature vectors with primary dimensions (object body related features), secondary dimensions (head related features) and accessory dimensions (including arms, ears, or beaks). The toolkit interfaces with the freely available Blender software to create objects. The toolbox allows to gradually morph features of multiple feature dimensions, determine the desired feature similarity among objects, and automatize the generation of multiple objects in 3D object and 2D image formats. We document the use of multidimensional objects in a sequence learning task that embeds objects in a 3D- rendered augmented reality environment controlled by the gaming engine unity. Taken together, the toolbox enables the efficient generation of multidimensional objects with fine control of low- level features and higher-level object similarity useful for visual cognitive research and immersive visual environments.

animal behavior and cognition↗
bioRxiv2024

Flexible Learning and Re-ordering of Context-dependent Object Sequences in Nonhuman Primates

Intelligent behavior involves mentally arranging learned information in novel ways and is particularly well developed in humans. While nonhuman primates (NHP) will learn to arrange new items in complex serial order and re-arrange neighboring items within that order, it has remained contentious whether they are capable to re-assign items more flexibly to non-adjacent positions. Such mental re-indexing is facilitated by inferring the latent temporal structure of experiences as opposed to learning serial chains of item-item associations. Here, we tested the ability for flexible mental re-indexing in rhesus macaques. Subjects learned to serially order five objects. A change of the background context indicated when the object order changed, probing the subjects to mentally re-arrange objects to non-adjacent positions of the learned serial structure. Subjects successfully used the context cue to pro-actively re-index items to new, non-adjacent positions. Mental re-indexing was more likely when the initial order had been learned at a higher level, improved with more experience of the re-indexing rule and correlated with working memory performance in a delayed match-to-sample task. These findings suggest that NHPs inferred the latent serial structure of experiences beyond a chaining of item-item associations and mentally re-arrange items within that structure. The pattern of results indicates that NHPs form non-spatial cognitive maps of their experiences, which is a hallmark for flexible mental operations in many serially ordered behaviors including communication, counting or foraging.

animal behavior and cognition↗
bioRxiv2024

Anterior Cingulate Cortex Causally Supports Meta-Learning

Learning the reward structure of complex environments can be achieved using reinforcement learning processes augmented with cognitive strategies. Among these strategies is the adjustment of the exploration-exploitation trade-off to increase exploration when behavior gets stuck and increase exploitation when reward contingencies remain stable. Here we tested how the anterior cingulate cortex (ACC) and the striatum causally support adaptive cognitive strategies augmenting reinforcement learning. We electrically microstimulated the ACC or the striatum in nonhuman primates at the time they chose multidimensional objects to learn about their reward values, while varying target feature uncertainty and the motivational saliency of the chosen objects. We found that stimulation of the ACC and the striatum affected adaptive strategies and reinforcement learning when target feature uncertainty was high, but in opposite ways. ACC-stimulation impaired learning and sustaining correct responses, while striatum-stimulation on average improved learning from rewarding outcomes. Behavioral modeling showed that stimulation affected the same mechanisms but in opposite ways. ACC stimulation impaired the monitoring of outcome uncertainty for adapting exploration-exploitation and reduced the ability to lower prediction errors during learning, while striatum stimulation enhanced the monitoring of outcome uncertainty and prediction-error based updating of object values. Stimulation did not alter the use of working memory or attentional filtering as alternative learning strategy. These opposing behavioral stimulation effects were associated with the ACC having populations of neurons that fired stronger during choices that were more uncertain, had a lower value, and that tracked error history, while striatum neurons more likely encoded higher values and more certain choices. In summary, microstimulation during object choices suggest that ACC and the striatum causally adapt exploration-exploitation levels to guide exploration towards reward-relevant objects during periods of uncertainty. Short SummaryThe anterior cingulate cortex (ACC) and the striatum are core nodes of a network supporting reinforcement learning, but how they augment reinforcement learning with adaptive cognitive strategies has remained unresolved. This study uses electrical microstimulation to show that ACC and the striatum have causal roles adjusting the exploration-exploitation balance and optimize reinforcement learning in multidimensional environments, while not altering attentional filtering or working memory strategies.

neuroscience↗
bioRxiv2023

A Multi-task Platform for Profiling Cognitive and Motivational Constructs in Humans and Nonhuman Primates

BackgroundUnderstanding the neurobiological substrates of psychiatric disorders requires comprehensive evaluations of cognitive and motivational functions in preclinical research settings. The translational validity of such evaluations will be supported by (1) tasks with high construct validity that are engaging and easy to teach to human and nonhuman participants, (2) software that enables efficient switching between multiple tasks in single sessions, (3) software that supports tasks across a broad range of physical experimental setups, and (4) by platform architectures that are easily extendable and customizable to encourage future optimization and development. New MethodWe describe the Multi-task Universal Suite for Experiments (M-USE), a software platform designed to meet these requirements. It leverages the Unity video game engine and C# programming language to (1) support immersive and engaging tasks for humans and nonhuman primates, (2) allow experimenters or participants to switch between multiple tasks within-session, (3) generate builds that function across computers, tablets, and websites, and (4) is freely available online with documentation and tutorials for users and developers. M-USE includes a task library with seven pre-existing tasks assessing cognitive and motivational constructs of perception, attention, working memory, cognitive flexibility, motivational and affective self-control, relational long-term memory, and visuo-spatial problem solving. ResultsM-USE was used to test NHPs on up to six tasks per session, all available as part of the Task Library, and to extract performance metrics for all major cognitive and motivational constructs spanning the Research Domain Criteria (RDoC) of the National Institutes of Mental Health. Comparison with Existing MethodsOther experiment design and control systems exist, but do not provide the full range of features available in M-USE, including a pre-existing task library for cross-species assessments; the ability to switch seamlessly between tasks in individual sessions; cross-platform build capabilities; license-free availability; and its leveraging of video-engine capabilities used to gamify tasks. ConclusionsThe new multi-task platform facilitates cross-species translational research for understanding the neurobiological substrates of higher cognitive and motivational functions.

animal behavior and cognition↗
bioRxiv2023

Noradrenergic alpha-2a Receptor Stimulation Enhances Prediction Error Signaling in Anterior Cingulate Cortex and Striatum

The noradrenergic system is implicated to support behavioral flexibility by increasing exploration during periods of uncertainty and by enhancing working memory for goal-relevant stimuli. Possible sources mediating these pro-cognitive effects are 2A adrenoceptors (2AR) in prefrontal cortex or the anterior cingulate cortex facilitating fronto-striatal learning processes. We tested this hypothesis by selectively stimulating 2ARs using Guanfacine during feature-based attentional set shifting in nonhuman primates. We found that 2A stimulation improved learning from errors and facilitates updating the target feature of an attentional set. Neural recordings in the anterior cingulate cortex (ACC), the dorsolateral prefrontal cortex (dlPFC), and the striatum showed that 2A stimulation selectively enhanced the neural representation of negative reward prediction errors in neurons of the ACC and of positive prediction errors in the striatum, but not in dlPFC. This modulation was accompanied by enhanced encoding of the feature and location of the attended target across the fronto-striatal network. Enhanced learning was paralleled by enhanced encoding of outcomes in putative fast-spiking interneurons in the ACC, dlPFC, and striatum but not in broad spiking cells, pointing to an interneuron mediated mechanism of 2AR action. These results illustrate that 2A receptors causally support the noradrenergic enhancement of updating attention sets through an enhancement of prediction error signaling in the ACC and the striatum.

neuroscience↗
bioRxiv2022

Routing States Transition During Oscillatory Bursts and Attention States

Neural information routing relies on spatiotemporal activity dynamics across interconnected brain areas. However, it remains unclear how routing states emerge at fast spiking timescales and interact with the slower activity dynamics of larger networks during cognitive processes. Here, we show that localized neural spiking events generate long-range directional routing states with spiking activity in distant brain areas that dynamically switch or amplify during oscillatory bursts, selective attention, and decision-making. Computational modeling and neural recordings from lateral prefrontal cortex (LPFC), anterior cingulate cortex (ACC), and striatum of nonhuman primates revealed that cross-areal, directional routing states arise within [~]20 ms around spikes of single neurons. On average, LPFC spikes led activity in the ACC and striatum by few milliseconds. The routing state was amplified during LPFC beta bursts between the LPFC and striatum and switched direction during ACC theta/alpha bursts between ACC and LPFC. Selective attention amplified the lead of these theta/alpha-specific lead-ensembles in the ACC, while decision-making amplified the lead of ACC and LPFC spiking output over the striatum. Notably, the fast lead/lag relationships of cross-areal neuronal ensembles that were modulated by attention states or decision-making predicted firing rate dynamics of their neurons during those functional states at slower timescales. Overall, our findings demonstrate directional routing of spiking activity across nonhuman primate frontal and striatal areas, as well as the functional and network states that modulate the direction and magnitude of these interactions. SummaryFast spatio-temporal dynamics of brain activity subserves the routing of information across distant regions and is integral to flexible cognition, decision-making, and selective attention. This study demonstrates that routing dynamics emerge as 20 ms brief lead and lag relationships of spiking activities across distant brain areas. The direction and magnitude of the lead and lag relationships systematically switched during frequency-specific oscillatory bursts and when attention shifts to visual cues.

neuroscience↗
bioRxiv2022

M1 selective muscarinic allosteric modulation enhances cognitive flexibility and effective salience in nonhuman primates

Acetylcholine (ACh) in cortical neural circuits mediates how selective attention is sustained in the presence of distractors and how flexible cognition adjusts to changing task demands. The cognitive domains of attention and cognitive flexibility might be differentially supported by the M1 muscarinic cholinergic sub-receptor. Understanding how M1 mechanisms support these cognitive subdomains is of highest importance for advancing novel drug treatments for conditions with altered attention and reduced cognitive control including Alzheimers disease or schizophrenia. Here, we tested this question by assessing how the subtype selective M1-receptor specific positive allosteric modulator (M1 PAM VU0453595) affects visual search and flexible reward-learning in nonhuman primates. We found that allosteric potentiation of the M1 receptor enhanced flexible learning performance by improving extra-dimensional set shifting, by reducing latent inhibition of previously experienced distractors, and by reducing response perseveration in the absence of adverse side effects. These pro-cognitive effects occurred in the absence of apparent changes of attentional performance during visual search. In contrast, non-selective ACh modulation using the acetylcholinesterase inhibitor donepezil improved attention during visual search at doses that did not alter cognitive flexibility and that already triggered gastrointestinal cholinergic side effects. These findings illustrate that M1 positive allosteric modulation enhances cognitive flexibility without affecting attentional filtering of distraction, consistent with M1 activity boosting the effective salience of relevant over irrelevant objects. These results suggest that M1 PAMs are versatile compounds for enhancing cognitive flexibility in disorders spanning schizophrenia and Alzheimers diseases. Statement of significanceMuscarinic receptors mediate the pro-cognitive effects of acetylcholine, but it has remained unclear whether they differentially affect the cognitive subfunctions of attentional filtering, set shifting, and learning. To clarify the functional specificity of M1 receptors, we assessed these diverse functions using a recently developed, highly selective M1 PAM. This M1 PAM caused domain-specific cognitive improvement of flexible learning and extra-dimensional set shifting, reduced perseverations and enhanced target recognition during learning without altering attentional filtering functions. These domain-specific improvement contrasted to effects of a non-selective acetylcholinesterase inhibitor that primarily enhanced attention and caused dose limiting adverse side effects. These results demonstrate domain-specific improvements of cognitive flexibility suggesting M1 PAMs are versatile compounds for treating cognitive deficits in schizophrenia and Alzheimers disease.

neuroscience↗
bioRxiv2021

Dose-dependent dissociation of pro-cognitive effects of donepezil on attention and cognitive flexibility in rhesus monkeys

BACKGROUNDDonepezil exerts pro-cognitive effects by non-selectively enhancing acetylcholine (ACh) across multiple brain systems. The brain systems that mediate pro-cognitive effects of attentional control and cognitive flexibility are the prefrontal cortex and the anterior striatum which have different pharmacokinetic sensitivities to ACh modulation. We speculated that these area-specific ACh profiles lead to distinct optimal dose-ranges for donepezil to enhance the cognitive domains of attention and flexible learning. METHODSTo test for dose-specific effects of donepezil on different cognitive domains we devised a multi-task paradigm for nonhuman primates (NHPs) that assessed attention and cognitive flexibility. NHPs received either vehicle or variable doses of donepezil prior to task performance. We measured donepezil intracerebral and how strong it prevented the breakdown of ACh within prefrontal cortex and anterior striatum using solid-phase-microextraction neurochemistry. RESULTSThe highest administered donepezil dose improved attention and made subjects more robust against distractor interference, but it did not improve flexible learning. In contrast, only a lower dose range of donepezil improved flexible learning and reduced perseveration, but without distractor-dependent attentional improvement. Neurochemical measurements confirmed a dose-dependent increase of extracellular donepezil and decreases in choline within the prefrontal cortex and the striatum. CONCLUSIONSThe donepezil dose for maximally improving attention functions differed from the dose range that enhanced cognitive flexibility despite the availability of the drug in the major brain systems supporting these cognitive functions. Thus, the non-selective acetylcholine esterase inhibitor donepezil inherently trades improvement in the attention domain for improvement in the cognitive flexibility domain at a given dose range.

pharmacology and toxicology↗
bioRxiv2021

Transcranial Ultrasound Stimulation in Anterior Cingulate Cortex Impairs Information Sampling and Learning in Loss Contexts

Neuronal subgroups in anterior cingulate cortex (ACC) and the anterior striatum (STR) encode the reward structure of a given environment. But whether or how this reward information is used to guide information sampling, optimize decision making, or motivate behavior in cognitively challenging situations has remained elusive. Here, we causally tested these scenarios by transiently disrupting ACC and STR of rhesus monkeys with transcranial ultrasound with a learning task that independently varied cognitive and motivational demands. We found that disrupting the ACC, but not the STR, prolonged information sampling and reduced learning efficiency whenever the motivational payoff was low. These impairments were most pronounced at high cognitive demands and based on an inability to use loss experiences to improve performance. These results provide causal evidence that the ACC is necessary for motivation, to overcome anticipated costs from negative (loss) outcomes, and for cognition, to enhance visual information sampling during adaptive behavior. HIGHLIGHTSO_LITranscranial ultrasound stimulation of the anterior cingulate cortex disrupts learning after loss experience. C_LIO_LIThe ultrasound-induced learning deficit is exacerbated at high cognitive load. C_LIO_LIThe ultrasound-induced learning deficit is accompanied by inefficient fixational information sampling. C_LIO_LIAnterior cingulate cortex causally supports credit assignment of aversive outcomes to visual features. C_LI

neuroscience↗
bioRxiv2021

A Kiosk Station for the Assessment of Multiple Cognitive Domains and Enrichment of Monkeys

BackgroundNonhuman primates (NHPs) are self-motivated to perform cognitive tasks on touchscreens in their animal housing setting. To leverage this ability, fully integrated hardware and software solutions are needed, that work within housing and husbandry routines while also spanning cognitive task constructs of the Research Domain Criteria (RDoC). New MethodWe describe a Kiosk Station (KS-1) that provides robust hardware and software solutions for running cognitive tasks in cage-housed NHPs. KS-1 consists of a frame for mounting flexibly on housing cages, a touchscreen animal interface with mounts for receptables, reward pumps and cameras, and a compact computer cabinet with an interface for controlling behavior. Behavioral control is achieved with a unity3D program that is virtual-reality capable, allowing semi-naturalistic visual tasks to assess multiple cognitive domains. ResultsKS-1 is fully integrated into the regular housing routines of monkeys. A single person can operate multiple KS-1s. Monkeys engage with KS-1 at high motivation and cognitive performance levels at high intra-individual consistency. Comparison with Existing MethodsKS-1 is optimized for flexible mounting onto standard apartment cage systems. KS-1 has a robust animal interface with options for gaze/reach monitoring. It has an integrated user interface for controlling multiple cognitive task using a common naturalistic object space designed to enhance task engagement. All custom KS-1 components are open-sourced. ConclusionsKS-1 is a versatile tool for cognitive profiling and enrichment of cage-housed monkeys. It reliably measures multiple cognitive domains which promises to advance our understanding of animal cognition, inter-individual differences and underlying neurobiology in refined, ethologically meaningful behavioral foraging contexts.

animal behavior and cognition↗