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Pagan M, Tang VD, Aoi MC, Pillow JW, Mante V, Sussillo D, Brody CD. Individual variability of neural computations underlying flexible decisions. Nature 2025; 639:421-429. [PMID: 39608399 PMCID: PMC11903320 DOI: 10.1038/s41586-024-08433-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 11/20/2024] [Indexed: 11/30/2024]
Abstract
The ability to flexibly switch our responses to external stimuli according to contextual information is critical for successful interactions with a complex world. Context-dependent computations are necessary across many domains1-3, yet their neural implementations remain poorly understood. Here we developed a novel behavioural task in rats to study context-dependent selection and accumulation of evidence for decision-making4-6. Under assumptions supported by both monkey and rat data, we first show mathematically that this computation can be supported by three dynamical solutions and that all networks performing the task implement a combination of these solutions. These solutions can be identified and tested directly with experimental data. We further show that existing electrophysiological and modelling data are compatible with the full variety of possible combinations of these solutions, suggesting that different individuals could use different combinations. To study variability across individual subjects, we developed automated, high-throughput methods to train rats on our task and trained many subjects using these methods. Consistent with theoretical predictions, neural and behavioural analyses revealed substantial heterogeneity across rats, despite uniformly good task performance. Our theory further predicts a specific link between behavioural and neural signatures, which was robustly supported in the data. In summary, our results provide an experimentally supported theoretical framework to analyse individual variability in biological and artificial systems that perform flexible decision-making tasks, open the door to cellular-resolution studies of individual variability in higher cognition, and provide insights into neural mechanisms of context-dependent computation more generally.
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Affiliation(s)
- Marino Pagan
- Princeton Neuroscience Institute, Princeton, NJ, USA.
- Simons Initiative for the Developing Brain, Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK.
| | | | - Mikio C Aoi
- Princeton Neuroscience Institute, Princeton, NJ, USA
- Department of Neurobiology and Halıcıoğlu Data Science Institute, University of California, San Diego, CA, USA
| | | | - Valerio Mante
- University of Zurich, Zurich, Switzerland
- ETH Zurich, Zurich, Switzerland
| | - David Sussillo
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton, NJ, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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2
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Moneta N, Grossman S, Schuck NW. Representational spaces in orbitofrontal and ventromedial prefrontal cortex: task states, values, and beyond. Trends Neurosci 2024; 47:1055-1069. [PMID: 39547861 DOI: 10.1016/j.tins.2024.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 10/16/2024] [Accepted: 10/17/2024] [Indexed: 11/17/2024]
Abstract
The orbitofrontal cortex (OFC) and ventromedial-prefrontal cortex (vmPFC) play a key role in decision-making and encode task states in addition to expected value. We review evidence suggesting a connection between value and state representations and argue that OFC / vmPFC integrate stimulus, context, and outcome information. Comparable encoding principles emerge in late layers of deep reinforcement learning (RL) models, where single nodes exhibit similar forms of mixed-selectivity, which enables flexible readout of relevant variables by downstream neurons. Based on these lines of evidence, we suggest that outcome-maximization leads to complex representational spaces that are insufficiently characterized by linear value signals that have been the focus of most prior research on the topic. Major outstanding questions concern the role of OFC/ vmPFC in learning across tasks, in encoding of task-irrelevant aspects, and the role of hippocampus-PFC interactions.
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Affiliation(s)
- Nir Moneta
- Institute of Psychology, Universität Hamburg, 20146 Hamburg, Germany; Einstein Center for Neurosciences Berlin, Charité Universitätsmedizin Berlin, 10117, Berlin, Germany.
| | - Shany Grossman
- Institute of Psychology, Universität Hamburg, 20146 Hamburg, Germany.
| | - Nicolas W Schuck
- Institute of Psychology, Universität Hamburg, 20146 Hamburg, Germany; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, 14195 Berlin, Germany.
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3
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Ritz H, Shenhav A. Orthogonal neural encoding of targets and distractors supports multivariate cognitive control. Nat Hum Behav 2024; 8:945-961. [PMID: 38459265 PMCID: PMC11219097 DOI: 10.1038/s41562-024-01826-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/15/2024] [Indexed: 03/10/2024]
Abstract
The complex challenges of our mental life require us to coordinate multiple forms of neural information processing. Recent behavioural studies have found that people can coordinate multiple forms of attention, but the underlying neural control process remains obscure. We hypothesized that the brain implements multivariate control by independently monitoring feature-specific difficulty and independently prioritizing feature-specific processing. During functional MRI, participants performed a parametric conflict task that separately tags target and distractor processing. Consistent with feature-specific monitoring, univariate analyses revealed spatially segregated encoding of target and distractor difficulty in the dorsal anterior cingulate cortex. Consistent with feature-specific attentional priority, our encoding geometry analysis revealed overlapping but orthogonal representations of target and distractor coherence in the intraparietal sulcus. Coherence representations were mediated by control demands and aligned with both performance and frontoparietal activity, consistent with top-down attention. Together, these findings provide evidence for the neural geometry necessary to coordinate multivariate cognitive control.
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Affiliation(s)
- Harrison Ritz
- Cognitive, Linguistic & Psychological Science, Brown University, Providence, RI, USA.
- Carney Institute for Brain Science, Brown University, Providence, RI, USA.
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
| | - Amitai Shenhav
- Cognitive, Linguistic & Psychological Science, Brown University, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
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4
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Tafazoli S, Bouchacourt FM, Ardalan A, Markov NT, Uchimura M, Mattar MG, Daw ND, Buschman TJ. Building compositional tasks with shared neural subspaces. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578263. [PMID: 38352540 PMCID: PMC10862921 DOI: 10.1101/2024.01.31.578263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Cognition is remarkably flexible; we are able to rapidly learn and perform many different tasks1. Theoretical modeling has shown artificial neural networks trained to perform multiple tasks will re-use representations2 and computational components3 across tasks. By composing tasks from these sub-components, an agent can flexibly switch between tasks and rapidly learn new tasks4. Yet, whether such compositionality is found in the brain is unknown. Here, we show the same subspaces of neural activity represent task-relevant information across multiple tasks, with each task compositionally combining these subspaces in a task-specific manner. We trained monkeys to switch between three compositionally related tasks. Neural recordings found task-relevant information about stimulus features and motor actions were represented in subspaces of neural activity that were shared across tasks. When monkeys performed a task, neural representations in the relevant shared sensory subspace were transformed to the relevant shared motor subspace. Subspaces were flexibly engaged as monkeys discovered the task in effect; their internal belief about the current task predicted the strength of representations in task-relevant subspaces. In sum, our findings suggest that the brain can flexibly perform multiple tasks by compositionally combining task-relevant neural representations across tasks.
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Affiliation(s)
- Sina Tafazoli
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Adel Ardalan
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Nikola T. Markov
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Motoaki Uchimura
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | | | - Nathaniel D. Daw
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Timothy J. Buschman
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
- Department of Psychology, Princeton University, Princeton, NJ, USA
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5
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Muhle-Karbe PS, Sheahan H, Pezzulo G, Spiers HJ, Chien S, Schuck NW, Summerfield C. Goal-seeking compresses neural codes for space in the human hippocampus and orbitofrontal cortex. Neuron 2023; 111:3885-3899.e6. [PMID: 37725981 DOI: 10.1016/j.neuron.2023.08.021] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/10/2023] [Accepted: 08/18/2023] [Indexed: 09/21/2023]
Abstract
Humans can navigate flexibly to meet their goals. Here, we asked how the neural representation of allocentric space is distorted by goal-directed behavior. Participants navigated an agent to two successive goal locations in a grid world environment comprising four interlinked rooms, with a contextual cue indicating the conditional dependence of one goal location on another. Examining the neural geometry by which room and context were encoded in fMRI signals, we found that map-like representations of the environment emerged in both hippocampus and neocortex. Cognitive maps in hippocampus and orbitofrontal cortices were compressed so that locations cued as goals were coded together in neural state space, and these distortions predicted successful learning. This effect was captured by a computational model in which current and prospective locations are jointly encoded in a place code, providing a theory of how goals warp the neural representation of space in macroscopic neural signals.
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Affiliation(s)
- Paul S Muhle-Karbe
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; School of Psychology, University of Birmingham, Birmingham B15 2SA, UK; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, UK.
| | - Hannah Sheahan
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Google DeepMind, London EC4A 3TW, UK
| | - Giovanni Pezzulo
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Hugo J Spiers
- Department of Experimental Psychology, University College London, London WC1E 6BT, UK
| | - Samson Chien
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, 14195 Berlin, Germany
| | - Nicolas W Schuck
- Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, 14195 Berlin, Germany; Max Planck UCL Centre for Computational Psychiatry and Aging Research, 14195 Berlin, Germany; Institute of Psychology, Universität Hamburg, 20146 Hamburg, Germany
| | - Christopher Summerfield
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK; Centre for Human Brain Health, University of Birmingham, Birmingham B15 2SA, UK.
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Barbosa J, Proville R, Rodgers CC, DeWeese MR, Ostojic S, Boubenec Y. Early selection of task-relevant features through population gating. Nat Commun 2023; 14:6837. [PMID: 37884507 PMCID: PMC10603060 DOI: 10.1038/s41467-023-42519-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 10/12/2023] [Indexed: 10/28/2023] Open
Abstract
Brains can gracefully weed out irrelevant stimuli to guide behavior. This feat is believed to rely on a progressive selection of task-relevant stimuli across the cortical hierarchy, but the specific across-area interactions enabling stimulus selection are still unclear. Here, we propose that population gating, occurring within primary auditory cortex (A1) but controlled by top-down inputs from prelimbic region of medial prefrontal cortex (mPFC), can support across-area stimulus selection. Examining single-unit activity recorded while rats performed an auditory context-dependent task, we found that A1 encoded relevant and irrelevant stimuli along a common dimension of its neural space. Yet, the relevant stimulus encoding was enhanced along an extra dimension. In turn, mPFC encoded only the stimulus relevant to the ongoing context. To identify candidate mechanisms for stimulus selection within A1, we reverse-engineered low-rank RNNs trained on a similar task. Our analyses predicted that two context-modulated neural populations gated their preferred stimulus in opposite contexts, which we confirmed in further analyses of A1. Finally, we show in a two-region RNN how population gating within A1 could be controlled by top-down inputs from PFC, enabling flexible across-area communication despite fixed inter-areal connectivity.
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Affiliation(s)
- Joao Barbosa
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL Research University, 75005, Paris, France.
| | - Rémi Proville
- Tailored Data Solutions, 192 Cours Gambetta, 84300, Cavaillon, France
| | - Chris C Rodgers
- Department of Neurosurgery, Emory University, Atlanta, GA, 30033, USA
| | - Michael R DeWeese
- Department of Physics, Helen Wills Neuroscience Institute, and Redwood Center for Theoretical Neuroscience, University of California, Berkeley, CA, USA
| | - Srdjan Ostojic
- Laboratoire de Neurosciences Cognitives et Computationnelles, INSERM U960, Ecole Normale Superieure - PSL Research University, 75005, Paris, France
| | - Yves Boubenec
- Laboratoire des Systèmes Perceptifs, Département d'Études Cognitives, École Normale Supérieure PSL Research University, CNRS, Paris, France
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7
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Rawji V, Modi S, Rocchi L, Jahanshahi M, Rothwel J. Proactive inhibition is marked by differences in the pattern of motor cortex activity during movement preparation and execution. J Neurophysiol 2022; 127:819-828. [PMID: 35235439 PMCID: PMC8957347 DOI: 10.1152/jn.00359.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Successful human behavior relies on the ability to flexibly alter movements depending on the context in which they are made. One such context-dependent modulation is proactive inhibition, a type of behavioral inhibition used when anticipating the need to stop or change movements. We investigated how the motor cortex might prepare and execute movements made under different contexts. We used transcranial magnetic stimulation (TMS) in different coil orientations [postero-anterior (PA) and antero-posterior (AP) flowing currents] and pulse widths (120 and 30 µs) to probe the excitability of different inputs to corticospinal neurons while participants performed two reaction time tasks: a simple reaction time task and a stop-signal task requiring proactive inhibition. We took inspiration from state space models to assess whether the pattern of motor cortex activity changed due to proactive inhibition (PA and AP neuronal circuits represent the x and y axes of a state space upon which motor cortex activity unfolds during motor preparation and execution). We found that the rise in motor cortex excitability was delayed when proactive inhibition was required. State space visualizations showed altered patterns of motor cortex activity (combined PA120 and AP30 activity) during proactive inhibition, despite adjusting for reaction time. Overall, we show that the pattern of neural activity generated by the motor cortex during movement preparation and execution is dependent upon the context under which the movement is to be made. NEW & NOTEWORTHY Using directional TMS, we find that the human motor cortex flexibly changes its pattern of neural activity depending on the context in which a movement is due to be made. Interestingly, this occurs despite adjusting for reaction time. We also show that state space and dynamical systems models of movement can be noninvasively visualized in humans using TMS, thereby offering a novel method to study these powerful models in humans.
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Affiliation(s)
- Vishal Rawji
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sachin Modi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Lorenzo Rocchi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom.,Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Marjan Jahanshahi
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - John Rothwel
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom
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8
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Takagi Y, Hunt LT, Woolrich MW, Behrens TEJ, Klein-Flügge MC. Adapting non-invasive human recordings along multiple task-axes shows unfolding of spontaneous and over-trained choice. eLife 2021; 10:e60988. [PMID: 33973522 PMCID: PMC8143794 DOI: 10.7554/elife.60988] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 04/26/2021] [Indexed: 12/28/2022] Open
Abstract
Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here, we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to three task-axes, relevant and irrelevant sensory inputs and response direction, in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a progression from processing sensory input to processing the response. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive over-training common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after over-training.
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Affiliation(s)
- Yu Takagi
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Department of Psychiatry, University of Oxford, Warneford HospitalOxfordUnited Kingdom
- Department of Neuropsychiatry, Graduate School of Medicine, University of TokyoTokyoJapan
| | - Laurence Tudor Hunt
- Department of Psychiatry, University of Oxford, Warneford HospitalOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, John Radcliffe HospitalOxfordUnited Kingdom
| | - Mark W Woolrich
- Department of Psychiatry, University of Oxford, Warneford HospitalOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, John Radcliffe HospitalOxfordUnited Kingdom
| | - Timothy EJ Behrens
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, John Radcliffe HospitalOxfordUnited Kingdom
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London (UCL)LondonUnited Kingdom
| | - Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, John Radcliffe HospitalOxfordUnited Kingdom
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