1
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Li T, Sakthivelpathi V, Qian Z, Soetedjo R, Chung JH. Primate eye tracking with carbon-nanotube-paper-composite based capacitive sensors and machine learning algorithms. J Neurosci Methods 2024; 410:110249. [PMID: 39151657 PMCID: PMC11364525 DOI: 10.1016/j.jneumeth.2024.110249] [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: 01/09/2024] [Revised: 07/20/2024] [Accepted: 08/13/2024] [Indexed: 08/19/2024]
Abstract
BACKGROUND Accurate real-time eye tracking is crucial in oculomotor system research. While the scleral search coil system is the gold standard, its implantation procedure and bulkiness pose challenges. Camera-based systems are affected by ambient lighting and require high computational and electric power. NEW METHOD This study presents a novel eye tracker using proximity capacitive sensors made of carbon-nanotube-paper-composite (CPC). These sensors detect femtofarad-level capacitance changes caused by primate corneal movement during horizontal and vertical eye rotations. Data processing and machine learning algorithms are evaluated to enhance the accuracy of gaze angle prediction. RESULTS The system performance is benchmarked against the scleral coil during smooth pursuits, saccades tracking, and fixations. The eye tracker demonstrates up to 0.97 correlation with the coil in eye tracking and is capable of estimating gaze angle with a median absolute error as low as 0.30°. COMPARISON The capacitive eye tracker demonstrates good consistency and accuracy in comparison to the gold-standard scleral search coil method. CONCLUSIONS This lightweight, non-invasive capacitive eye tracker offers potential as an alternative to traditional coil and camera-based systems in oculomotor research and vision science.
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Affiliation(s)
- Tianyi Li
- Mechanical Engineering, University of Washington, Seattle, WA 98195, USA
| | | | - Zhongjie Qian
- Mechanical Engineering, University of Washington, Seattle, WA 98195, USA
| | - Robijanto Soetedjo
- Department of Physiology and Biophysics, University of Washington, Seattle, WA 98195, USA; Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Jae-Hyun Chung
- Mechanical Engineering, University of Washington, Seattle, WA 98195, USA.
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2
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Strittmatter Y, Spitzer MWH, Ging-Jehli N, Musslick S. A jsPsych touchscreen extension for behavioral research on touch-enabled interfaces. Behav Res Methods 2024; 56:7814-7830. [PMID: 38995520 DOI: 10.3758/s13428-024-02454-9] [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] [Accepted: 06/05/2024] [Indexed: 07/13/2024]
Abstract
Online experiments are increasingly gaining traction in the behavioral sciences. Despite this, behavioral researchers have largely continued to use keyboards as the primary input devices for such online studies, overlooking the ubiquity of touchscreens in everyday use. This paper presents an open-source touchscreen extension for jsPsych, a JavaScript framework designed for conducting online experiments. We additionally evaluated the touchscreen extension assessing whether typical behavioral findings from two distinct perceptual decision-making tasks - the random-dot kinematogram and the Stroop task - can similarly be observed when administered via touchscreen devices compared to keyboard devices. Our findings indicate similar performance metrics for each paradigm between the touchscreen and keyboard versions of the experiments. Specifically, we observe similar psychometric curves in the random-dot kinematogram across the touchscreen and keyboard versions. Similarly, in the Stroop task, we detect significant task, congruency, and sequential congruency effects in both experiment versions. We conclude that our open-source touchscreen extension serves as a promising tool for data collection in online behavioral experiments on forced-choice tasks.
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Affiliation(s)
- Younes Strittmatter
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA
| | - Markus W H Spitzer
- Department of Psychology, Martin-Luther University Halle-Wittenberg, Halle, Germany.
| | - Nadja Ging-Jehli
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA
| | - Sebastian Musslick
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA
- Institute of Cognitive Science, Osnabrück University, Osnabrück, Germany
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3
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Khilkevich A, Lohse M, Low R, Orsolic I, Bozic T, Windmill P, Mrsic-Flogel TD. Brain-wide dynamics linking sensation to action during decision-making. Nature 2024:10.1038/s41586-024-07908-w. [PMID: 39261727 DOI: 10.1038/s41586-024-07908-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/05/2024] [Indexed: 09/13/2024]
Abstract
Perceptual decisions rely on learned associations between sensory evidence and appropriate actions, involving the filtering and integration of relevant inputs to prepare and execute timely responses1,2. Despite the distributed nature of task-relevant representations3-10, it remains unclear how transformations between sensory input, evidence integration, motor planning and execution are orchestrated across brain areas and dimensions of neural activity. Here we addressed this question by recording brain-wide neural activity in mice learning to report changes in ambiguous visual input. After learning, evidence integration emerged across most brain areas in sparse neural populations that drive movement-preparatory activity. Visual responses evolved from transient activations in sensory areas to sustained representations in frontal-motor cortex, thalamus, basal ganglia, midbrain and cerebellum, enabling parallel evidence accumulation. In areas that accumulate evidence, shared population activity patterns encode visual evidence and movement preparation, distinct from movement-execution dynamics. Activity in movement-preparatory subspace is driven by neurons integrating evidence, which collapses at movement onset, allowing the integration process to reset. Across premotor regions, evidence-integration timescales were independent of intrinsic regional dynamics, and thus depended on task experience. In summary, learning aligns evidence accumulation to action preparation in activity dynamics across dozens of brain regions. This leads to highly distributed and parallelized sensorimotor transformations during decision-making. Our work unifies concepts from decision-making and motor control fields into a brain-wide framework for understanding how sensory evidence controls actions.
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Affiliation(s)
- Andrei Khilkevich
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
| | - Michael Lohse
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
| | - Ryan Low
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Ivana Orsolic
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Tadej Bozic
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Paige Windmill
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK
| | - Thomas D Mrsic-Flogel
- Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, London, UK.
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4
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Sengupta A, Banerjee S, Ganesh S, Grover S, Sridharan D. The right posterior parietal cortex mediates spatial reorienting of attentional choice bias. Nat Commun 2024; 15:6938. [PMID: 39138185 PMCID: PMC11322534 DOI: 10.1038/s41467-024-51283-z] [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: 09/20/2022] [Accepted: 08/02/2024] [Indexed: 08/15/2024] Open
Abstract
Attention facilitates behavior by enhancing perceptual sensitivity (sensory processing) and choice bias (decisional weighting) for attended information. Whether distinct neural substrates mediate these distinct components of attention remains unknown. We investigate the causal role of key nodes of the right posterior parietal cortex (rPPC) in the forebrain attention network in sensitivity versus bias control. Two groups of participants performed a cued attention task while we applied either inhibitory, repetitive transcranial magnetic stimulation (n = 28) or 40 Hz transcranial alternating current stimulation (n = 26) to the dorsal rPPC. We show that rPPC stimulation - with either modality - impairs task performance by selectively altering attentional modulation of bias but not sensitivity. Specifically, participants' bias toward the uncued, but not the cued, location reduced significantly following rPPC stimulation - an effect that was consistent across both neurostimulation cohorts. In sum, the dorsal rPPC causally mediates the reorienting of choice bias, one particular component of visual spatial attention.
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Affiliation(s)
- Ankita Sengupta
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
| | - Sanjna Banerjee
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
- Foundation of Art and Health India, Bangalore, 560066, India
| | - Suhas Ganesh
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
- Verily Life Sciences, San Francisco, CA, 94080, USA
| | - Shrey Grover
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - Devarajan Sridharan
- Centre for Neuroscience, Indian Institute of Science, Bangalore, 560012, India.
- Department of Computer Science and Automation, Indian Institute of Science, Bangalore, 560012, India.
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5
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Cecchini G, DePass M, Baspinar E, Andujar M, Ramawat S, Pani P, Ferraina S, Destexhe A, Moreno-Bote R, Cos I. Cognitive mechanisms of learning in sequential decision-making under uncertainty: an experimental and theoretical approach. Front Behav Neurosci 2024; 18:1399394. [PMID: 39188591 PMCID: PMC11346247 DOI: 10.3389/fnbeh.2024.1399394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 07/19/2024] [Indexed: 08/28/2024] Open
Abstract
Learning to make adaptive decisions involves making choices, assessing their consequence, and leveraging this assessment to attain higher rewarding states. Despite vast literature on value-based decision-making, relatively little is known about the cognitive processes underlying decisions in highly uncertain contexts. Real world decisions are rarely accompanied by immediate feedback, explicit rewards, or complete knowledge of the environment. Being able to make informed decisions in such contexts requires significant knowledge about the environment, which can only be gained via exploration. Here we aim at understanding and formalizing the brain mechanisms underlying these processes. To this end, we first designed and performed an experimental task. Human participants had to learn to maximize reward while making sequences of decisions with only basic knowledge of the environment, and in the absence of explicit performance cues. Participants had to rely on their own internal assessment of performance to reveal a covert relationship between their choices and their subsequent consequences to find a strategy leading to the highest cumulative reward. Our results show that the participants' reaction times were longer whenever the decision involved a future consequence, suggesting greater introspection whenever a delayed value had to be considered. The learning time varied significantly across participants. Second, we formalized the neurocognitive processes underlying decision-making within this task, combining mean-field representations of competing neural populations with a reinforcement learning mechanism. This model provided a plausible characterization of the brain dynamics underlying these processes, and reproduced each aspect of the participants' behavior, from their reaction times and choices to their learning rates. In summary, both the experimental results and the model provide a principled explanation to how delayed value may be computed and incorporated into the neural dynamics of decision-making, and to how learning occurs in these uncertain scenarios.
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Affiliation(s)
- Gloria Cecchini
- Facultat de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
- Center for Brain and Cognition, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
| | - Michael DePass
- Center for Brain and Cognition, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
| | - Emre Baspinar
- CNRS, Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Saclay, France
| | - Marta Andujar
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Surabhi Ramawat
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Pierpaolo Pani
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Stefano Ferraina
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Alain Destexhe
- CNRS, Institute of Neuroscience (NeuroPSI), Paris-Saclay University, Saclay, France
| | - Rubén Moreno-Bote
- Center for Brain and Cognition, DTIC, Universitat Pompeu Fabra, Barcelona, Spain
- Serra-Hunter Fellow Programme, Barcelona, Spain
| | - Ignasi Cos
- Facultat de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain
- Serra-Hunter Fellow Programme, Barcelona, Spain
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6
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Asinof SK, Card GM. Neural Control of Naturalistic Behavior Choices. Annu Rev Neurosci 2024; 47:369-388. [PMID: 38724026 DOI: 10.1146/annurev-neuro-111020-094019] [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] [Indexed: 08/09/2024]
Abstract
In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.
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Affiliation(s)
- Samuel K Asinof
- Laboratory of Molecular Biology, National Institute of Mental Health, Bethesda, Maryland, USA
- Janelia Research Campus, Ashburn, Virginia, USA
| | - Gwyneth M Card
- Howard Hughes Medical Institute, Department of Neuroscience, and Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA;
- Janelia Research Campus, Ashburn, Virginia, USA
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7
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Roumani D, Moutoussis K. Inattentional aftereffects: The role of attention on the strength of the motion aftereffect. Perception 2024; 53:544-562. [PMID: 38826086 DOI: 10.1177/03010066241252390] [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] [Indexed: 06/04/2024]
Abstract
The way that attention affects the processing of visual information is one of the most intriguing fields in the study of visual perception. One way to examine this interaction is by studying the way perceptual aftereffects are modulated by attention. In the present study, we have manipulated attention during adaptation to translational motion generated by coherently moving random dots, in order to investigate the effect of the distraction of attention on the strength of the peripheral dynamic motion aftereffect (MAE). A foveal rapid serial visual presentation task (RSVP) of varying difficulty was introduced during the adaptation period while the adaptation and test stimuli were presented peripherally. Furthermore, to examine the interaction between the physical characteristics of the stimulus and attention, we have manipulated the motion coherence level of the adaptation stimuli. Our results suggested that the removal of attention through an irrelevant task modulated the MAE's magnitude moderately and that such an effect depends on the stimulus strength. We also showed that the MAE still persists with subthreshold and unattended stimuli, suggesting that perhaps attention is not required for the complete development of the MAE.
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Affiliation(s)
- Daphne Roumani
- National and Kapodistrian University of Athens, Ilissia Athens, Greece
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8
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Weigard A, Angstadt M, Taxali A, Heathcote A, Heitzeg MM, Sripada C. Flexible adaptation of task-positive brain networks predicts efficiency of evidence accumulation. Commun Biol 2024; 7:801. [PMID: 38956310 PMCID: PMC11220037 DOI: 10.1038/s42003-024-06506-w] [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: 09/15/2023] [Accepted: 06/25/2024] [Indexed: 07/04/2024] Open
Abstract
Efficiency of evidence accumulation (EEA), an individual's ability to selectively gather goal-relevant information to make adaptive choices, is thought to be a key neurocomputational mechanism associated with cognitive functioning and transdiagnostic risk for psychopathology. However, the neural basis of individual differences in EEA is poorly understood, especially regarding the role of largescale brain network dynamics. We leverage data from 5198 participants from the Human Connectome Project and Adolescent Brain Cognitive Development Study to demonstrate a strong association between EEA and flexible adaptation to cognitive demand in the "task-positive" frontoparietal and dorsal attention networks. Notably, individuals with higher EEA displayed divergent task-positive network activation across n-back task conditions: higher activation under high cognitive demand (2-back) and lower activation under low demand (0-back). These findings suggest that brain networks' flexible adaptation to cognitive demands is a key neural underpinning of EEA.
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Affiliation(s)
| | - Mike Angstadt
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Aman Taxali
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Andrew Heathcote
- Department of Psychological Methods, University of Amsterdam, Amsterdam, Netherlands
| | - Mary M Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
| | - Chandra Sripada
- Department of Psychiatry, University of Michigan, Ann Arbor, USA
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9
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Queirazza F, Cavanagh J, Philiastides MG, Krishnadas R. Mild exogenous inflammation blunts neural signatures of bounded evidence accumulation and reward prediction error processing in healthy male participants. Brain Behav Immun 2024; 119:197-210. [PMID: 38555987 DOI: 10.1016/j.bbi.2024.03.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 03/21/2024] [Accepted: 03/28/2024] [Indexed: 04/02/2024] Open
Abstract
BACKGROUND Altered neural haemodynamic activity during decision making and learning has been linked to the effects of inflammation on mood and motivated behaviours. So far, it has been reported that blunted mesolimbic dopamine reward signals are associated with inflammation-induced anhedonia and apathy. Nonetheless, it is still unclear whether inflammation impacts neural activity underpinning decision dynamics. The process of decision making involves integration of noisy evidence from the environment until a critical threshold of evidence is reached. There is growing empirical evidence that such process, which is usually referred to as bounded accumulation of decision evidence, is affected in the context of mental illness. METHODS In a randomised, placebo-controlled, crossover study, 19 healthy male participants were allocated to placebo and typhoid vaccination. Three to four hours post-injection, participants performed a probabilistic reversal-learning task during functional magnetic resonance imaging. To capture the hidden neurocognitive operations underpinning decision-making, we devised a hybrid sequential sampling and reinforcement learning computational model. We conducted whole brain analyses informed by the modelling results to investigate the effects of inflammation on the efficiency of decision dynamics and reward learning. RESULTS We found that during the decision phase of the task, typhoid vaccination attenuated neural signatures of bounded evidence accumulation in the dorsomedial prefrontal cortex, only for decisions requiring short integration time. Consistent with prior work, we showed that, in the outcome phase, mild acute inflammation blunted the reward prediction error in the bilateral ventral striatum and amygdala. CONCLUSIONS Our study extends current insights into the effects of inflammation on the neural mechanisms of decision making and shows that exogenous inflammation alters neural activity indexing efficiency of evidence integration, as a function of choice discriminability. Moreover, we replicate previous findings that inflammation blunts striatal reward prediction error signals.
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Affiliation(s)
- Filippo Queirazza
- School of Health and Wellbeing, University of Glasgow, Glasgow G12 8TB, UK; School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QB, UK.
| | - Jonathan Cavanagh
- School of Infection and Immunity, University of Glasgow, Glasgow G12 8TA, UK
| | | | - Rajeev Krishnadas
- School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QB, UK; Department of Psychiatry, University of Cambridge, Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0AH, UK
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10
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Sharpley CF, Bitsika V, Evans ID, Vessey KA, Jesulola E, Agnew LL. Depression Severity, Slow- versus Fast-Wave Neural Activity, and Symptoms of Melancholia. Brain Sci 2024; 14:607. [PMID: 38928607 PMCID: PMC11202185 DOI: 10.3390/brainsci14060607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2024] [Revised: 06/01/2024] [Accepted: 06/14/2024] [Indexed: 06/28/2024] Open
Abstract
Melancholia is a major and severe subtype of depression, with only limited data regarding its association with neurological phenomena. To extend the current understanding of how particular aspects of melancholia are correlated with brain activity, electroencephalographic data were collected from 100 adults (44 males and 56 females, all aged 18 y or more) and investigated for the association between symptoms of melancholia and the ratios of alpha/beta activity and theta/beta activity at parietal-occipital EEG sites PO1 and PO2. The results indicate differences in these associations according to the depressive status of participants and the particular symptom of melancholia. Depressed participants exhibited meaningfully direct correlations between alpha/beta and theta/beta activity and the feeling that "Others would be better off if I was dead" at PO1, whereas non-depressed participants had significant inverse correlations between theta/beta activity and "Feeling useless and not needed" and "I find it hard to make decisions" at PO1. The results are discussed in terms of the relative levels of fast-wave (beta) versus slow-wave (alpha, theta) activity exhibited by depressed and non-depressed participants in the parietal-occipital region and the cognitive activities that are relevant to that region.
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Affiliation(s)
- Christopher F. Sharpley
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
| | - Vicki Bitsika
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
| | - Ian D. Evans
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
| | - Kirstan A. Vessey
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
| | - Emmanuel Jesulola
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
- Department of Neurosurgery, The Alfred Hospital, Melbourne, VIC 3000, Australia
| | - Linda L. Agnew
- Brain-Behaviour Research Group, University of New England, Armidale, NSW 2351, Australia; (V.B.); (I.D.E.); (K.A.V.); (E.J.); (L.L.A.)
- Department of Health, Griffith University, Gold Coast, QLD 4222, Australia
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11
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Bredenberg C, Savin C. Desiderata for Normative Models of Synaptic Plasticity. Neural Comput 2024; 36:1245-1285. [PMID: 38776950 DOI: 10.1162/neco_a_01671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 02/06/2024] [Indexed: 05/25/2024]
Abstract
Normative models of synaptic plasticity use computational rationales to arrive at predictions of behavioral and network-level adaptive phenomena. In recent years, there has been an explosion of theoretical work in this realm, but experimental confirmation remains limited. In this review, we organize work on normative plasticity models in terms of a set of desiderata that, when satisfied, are designed to ensure that a given model demonstrates a clear link between plasticity and adaptive behavior, is consistent with known biological evidence about neural plasticity and yields specific testable predictions. As a prototype, we include a detailed analysis of the REINFORCE algorithm. We also discuss how new models have begun to improve on the identified criteria and suggest avenues for further development. Overall, we provide a conceptual guide to help develop neural learning theories that are precise, powerful, and experimentally testable.
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Affiliation(s)
- Colin Bredenberg
- Center for Neural Science, New York University, New York, NY 10003, U.S.A
- Mila-Quebec AI Institute, Montréal, QC H2S 3H1, Canada
| | - Cristina Savin
- Center for Neural Science, New York University, New York, NY 10003, U.S.A
- Center for Data Science, New York University, New York, NY 10011, U.S.A.
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12
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Shallow MC, Tian L, Lin H, Lefton KB, Chen S, Dougherty JD, Culver JP, Lambo ME, Hengen KB. At the onset of active whisking, the input layer of barrel cortex exhibits a 24 h window of increased excitability that depends on prior experience. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.04.597353. [PMID: 38895408 PMCID: PMC11185658 DOI: 10.1101/2024.06.04.597353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The development of motor control over sensory organs is a critical milestone in sensory processing, enabling active exploration and shaping of the sensory environment. However, whether the onset of sensory organ motor control directly influences the development of corresponding sensory cortices remains unknown. Here, we exploit the late onset of whisking behavior in mice to address this question in the somatosensory system. Using ex vivo electrophysiology, we discovered a transient increase in the intrinsic excitability of excitatory neurons in layer IV of the barrel cortex, which processes whisker input, precisely coinciding with the onset of active whisking at postnatal day 14 (P14). This increase in neuronal gain was specific to layer IV, independent of changes in synaptic strength, and required prior sensory experience. Strikingly, the effect was not observed in layer II/III of the barrel cortex or in the visual cortex upon eye opening, suggesting a unique interaction between the development of active sensing and the thalamocortical input layer in the somatosensory system. Predictive modeling indicated that changes in active membrane conductances alone could reliably distinguish P14 neurons in control but not whisker-deprived hemispheres. Our findings demonstrate an experience-dependent, lamina-specific refinement of neuronal excitability tightly linked to the emergence of active whisking. This transient increase in the gain of the thalamic input layer coincides with a critical period for synaptic plasticity in downstream layers, suggesting a role in facilitating cortical maturation and sensory processing. Together, our results provide evidence for a direct interaction between the development of motor control and sensory cortex, offering new insights into the experience-dependent development and refinement of sensory systems. These findings have broad implications for understanding the interplay between motor and sensory development, and how the mechanisms of perception cooperate with behavior.
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Affiliation(s)
| | - Lucy Tian
- Department of Biology, Washington University in Saint Louis
| | - Hudson Lin
- Department of Biology, Washington University in Saint Louis
| | - Katheryn B Lefton
- Department of Biology, Washington University in Saint Louis
- Department of Neuroscience, Washington University in Saint Louis
| | - Siyu Chen
- Department of Genetics, Washington University in Saint Louis
| | | | - Joe P Culver
- Department of Radiology, Washington University in Saint Louis
| | - Mary E Lambo
- Department of Biology, Washington University in Saint Louis
| | - Keith B Hengen
- Department of Biology, Washington University in Saint Louis
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13
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Charlton JA, Goris RLT. Abstract deliberation by visuomotor neurons in prefrontal cortex. Nat Neurosci 2024; 27:1167-1175. [PMID: 38684894 PMCID: PMC11156582 DOI: 10.1038/s41593-024-01635-1] [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: 01/31/2023] [Accepted: 03/29/2024] [Indexed: 05/02/2024]
Abstract
During visually guided behavior, the prefrontal cortex plays a pivotal role in mapping sensory inputs onto appropriate motor plans. When the sensory input is ambiguous, this involves deliberation. It is not known whether the deliberation is implemented as a competition between possible stimulus interpretations or between possible motor plans. Here we study neural population activity in the prefrontal cortex of macaque monkeys trained to flexibly report perceptual judgments of ambiguous visual stimuli. We find that the population activity initially represents the formation of a perceptual choice before transitioning into the representation of the motor plan. Stimulus strength and prior expectations both bear on the formation of the perceptual choice, but not on the formation of the action plan. These results suggest that prefrontal circuits involved in action selection are also used for the deliberation of abstract propositions divorced from a specific motor plan, thus providing a crucial mechanism for abstract reasoning.
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Affiliation(s)
- Julie A Charlton
- Center for Perceptual Systems, The University of Texas at Austin, Austin, TX, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Robbe L T Goris
- Center for Perceptual Systems, The University of Texas at Austin, Austin, TX, USA.
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14
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Laamerad P, Liu LD, Pack CC. Decision-related activity and movement selection in primate visual cortex. SCIENCE ADVANCES 2024; 10:eadk7214. [PMID: 38809984 PMCID: PMC11135405 DOI: 10.1126/sciadv.adk7214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 04/24/2024] [Indexed: 05/31/2024]
Abstract
Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there is a longstanding debate about whether CP reflects a causal influence on decisions or an echo of decision-making activity elsewhere in the brain. Here, we show that CP can reflect a third variable, namely, the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of primate cortex responded more strongly during trials that involved a saccade toward their receptive fields. This variability accounted for much of the CP observed across the neuronal population, and it arose through training. Moreover, pharmacological inactivation of MT biased behavioral responses away from the corresponding visual field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions and that this plasticity can shape the neural circuitry of perceptual decision-making.
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Affiliation(s)
- Pooya Laamerad
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Liu D. Liu
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
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15
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Frank SM. Transfer of Tactile Learning to Untrained Body Parts: Emerging Cortical Mechanisms. Neuroscientist 2024:10738584241256277. [PMID: 38813891 DOI: 10.1177/10738584241256277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2024]
Abstract
Pioneering investigations in the mid-19th century revealed that the perception of tactile cues presented to the surface of the skin improves with training, which is referred to as tactile learning. Surprisingly, tactile learning also occurs for body parts and skin locations that are not physically involved in the training. For example, after training of a finger, tactile learning transfers to adjacent untrained fingers. This suggests that the transfer of tactile learning follows a somatotopic pattern and involves brain regions such as the primary somatosensory cortex (S1), in which the trained and untrained body parts and skin locations are represented close to each other. However, other results showed that transfer occurs between body parts that are not represented close to each other in S1-for example, between the hand and the foot. These and similar findings have led to the suggestion of additional cortical mechanisms to explain the transfer of tactile learning. Here, different mechanisms are reviewed, and the extent to which they can explain the transfer of tactile learning is discussed. What all of these mechanisms have in common is that they assume a representational or functional relationship between the trained and untrained body parts and skin locations. However, none of these mechanisms alone can explain the complex pattern of transfer results, and it is likely that different mechanisms interact to enable transfer, perhaps in concert with higher somatosensory and decision-making areas.
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Affiliation(s)
- Sebastian M Frank
- Institute for Experimental Psychology, University of Regensburg, Regensburg, Germany
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16
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van Ede F, Nobre AC. A Neural Decision Signal during Internal Sampling from Working Memory in Humans. J Neurosci 2024; 44:e1475232024. [PMID: 38538144 PMCID: PMC11079964 DOI: 10.1523/jneurosci.1475-23.2024] [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: 08/04/2023] [Revised: 01/11/2024] [Accepted: 02/16/2024] [Indexed: 05/12/2024] Open
Abstract
How humans transform sensory information into decisions that steer purposeful behavior is a central question in psychology and neuroscience that is traditionally investigated during the sampling of external environmental signals. The decision-making framework of gradual information sampling toward a decision has also been proposed to apply when sampling internal sensory evidence from working memory. However, neural evidence for this proposal remains scarce. Here we show (using scalp EEG in male and female human volunteers) that sampling internal visual representations from working memory elicits a scalp EEG potential associated with gradual evidence accumulation-the central parietal positivity. Consistent with an evolving decision process, we show how this signal (1) scales with the time participants require to reach a decision about the cued memory content and (2) is amplified when having to decide among multiple contents in working memory. These results bring the electrophysiology of decision-making into the domain of working memory and suggest that variability in memory-guided behavior may be driven (at least in part) by variations in the sampling of our inner mental contents.
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Affiliation(s)
- Freek van Ede
- Institute for Brain and Behavior Amsterdam, Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, 1081 BT, Amsterdam, The Netherlands
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, United Kingdom
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
- Wu Tsai Institute and Department of Psychology, Yale University, New Haven, Connecticut 06510
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17
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Riveland R, Pouget A. Natural language instructions induce compositional generalization in networks of neurons. Nat Neurosci 2024; 27:988-999. [PMID: 38499855 DOI: 10.1038/s41593-024-01607-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 02/15/2024] [Indexed: 03/20/2024]
Abstract
A fundamental human cognitive feat is to interpret linguistic instructions in order to perform novel tasks without explicit task experience. Yet, the neural computations that might be used to accomplish this remain poorly understood. We use advances in natural language processing to create a neural model of generalization based on linguistic instructions. Models are trained on a set of common psychophysical tasks, and receive instructions embedded by a pretrained language model. Our best models can perform a previously unseen task with an average performance of 83% correct based solely on linguistic instructions (that is, zero-shot learning). We found that language scaffolds sensorimotor representations such that activity for interrelated tasks shares a common geometry with the semantic representations of instructions, allowing language to cue the proper composition of practiced skills in unseen settings. We show how this model generates a linguistic description of a novel task it has identified using only motor feedback, which can subsequently guide a partner model to perform the task. Our models offer several experimentally testable predictions outlining how linguistic information must be represented to facilitate flexible and general cognition in the human brain.
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Affiliation(s)
- Reidar Riveland
- Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland.
| | - Alexandre Pouget
- Department of Basic Neuroscience, University of Geneva, Geneva, Switzerland
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18
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Oguz OC, Aydin B, Urgen BA. Biological motion perception in the theoretical framework of perceptual decision-making: An event-related potential study. Vision Res 2024; 218:108380. [PMID: 38479050 DOI: 10.1016/j.visres.2024.108380] [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: 09/28/2023] [Revised: 03/06/2024] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
Biological motion perception plays a critical role in various decisions in daily life. Failure to decide accordingly in such a perceptual task could have life-threatening consequences. Neurophysiology and computational modeling studies suggest two processes mediating perceptual decision-making. One of these signals is associated with the accumulation of sensory evidence and the other with response selection. Recent EEG studies with humans have introduced an event-related potential called Centroparietal Positive Potential (CPP) as a neural marker aligned with the sensory evidence accumulation while effectively distinguishing it from motor-related lateralized readiness potential (LRP). The present study aims to investigate the neural mechanisms of biological motion perception in the framework of perceptual decision-making, which has been overlooked before. More specifically, we examine whether CPP would track the coherence of the biological motion stimuli and could be distinguished from the LRP signal. We recorded EEG from human participants while they performed a direction discrimination task of a point-light walker stimulus embedded in various levels of noise. Our behavioral findings revealed shorter reaction times and reduced miss rates as the coherence of the stimuli increased. In addition, CPP tracked the coherence of the biological motion stimuli with a tendency to reach a common level during the response, albeit with a later onset than the previously reported results in random-dot motion paradigms. Furthermore, CPP was distinguished from the LRP signal based on its temporal profile. Overall, our results suggest that the mechanisms underlying perceptual decision-making generalize to more complex and socially significant stimuli like biological motion.
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Affiliation(s)
- Osman Cagri Oguz
- Department of Psychology, Bilkent University, Ankara 06800, Turkey; Department of Neuroscience, Bilkent University, Ankara 06800, Turkey.
| | - Berfin Aydin
- Department of Neuroscience, Bilkent University, Ankara 06800, Turkey
| | - Burcu A Urgen
- Department of Psychology, Bilkent University, Ankara 06800, Turkey; Department of Neuroscience, Bilkent University, Ankara 06800, Turkey; Aysel Sabuncu Brain Research Center and National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara 06800, Turkey.
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19
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Bogler C, Zangrossi A, Miller C, Sartori G, Haynes J. Have you been there before? Decoding recognition of spatial scenes from fMRI signals in precuneus. Hum Brain Mapp 2024; 45:e26690. [PMID: 38703117 PMCID: PMC11069338 DOI: 10.1002/hbm.26690] [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: 07/19/2023] [Revised: 01/23/2024] [Accepted: 04/08/2024] [Indexed: 05/06/2024] Open
Abstract
One potential application of forensic "brain reading" is to test whether a suspect has previously experienced a crime scene. Here, we investigated whether it is possible to decode real life autobiographic exposure to spatial locations using fMRI. In the first session, participants visited four out of eight possible rooms on a university campus. During a subsequent scanning session, subjects passively viewed pictures and videos from these eight possible rooms (four old, four novel) without giving any responses. A multivariate searchlight analysis was employed that trained a classifier to distinguish between "seen" versus "unseen" stimuli from a subset of six rooms. We found that bilateral precuneus encoded information that can be used to distinguish between previously seen and unseen rooms and that also generalized to the two stimuli left out from training. We conclude that activity in bilateral precuneus is associated with the memory of previously visited rooms, irrespective of the identity of the room, thus supporting a parietal contribution to episodic memory for spatial locations. Importantly, we could decode whether a room was visited in real life without the need of explicit judgments about the rooms. This suggests that recognition is an automatic response that can be decoded from fMRI data, thus potentially supporting forensic applications of concealed information tests for crime scene recognition.
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Affiliation(s)
- Carsten Bogler
- Bernstein Center for Computational NeuroscienceCharité‐Universitätsmedizin BerlinBerlinGermany
| | - Andrea Zangrossi
- Department of General PsychologyUniversity of PadovaPadovaItaly
- Padova Neuroscience Center (PNC)University of PadovaPadovaItaly
| | - Chantal Miller
- Berlin School of Mind and BrainHumboldt‐Universität zu BerlinBerlinGermany
| | | | - John‐Dylan Haynes
- Bernstein Center for Computational NeuroscienceCharité‐Universitätsmedizin BerlinBerlinGermany
- Berlin School of Mind and BrainHumboldt‐Universität zu BerlinBerlinGermany
- Max Planck School of CognitionLeipzigGermany
- Berlin Center for Advanced NeuroimagingCharité‐Universitätsmedizin BerlinBerlinGermany
- Clinic of NeurologyCharité‐Universitätsmedizin BerlinBerlinGermany
- Institute of PsychologyHumboldt‐Universität zu BerlinBerlinGermany
- Cluster of Excellence “Science of Intelligence”Berlin Institute of TechnologyBerlinGermany
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20
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Walsh K, McGovern DP, Dully J, Kelly SP, O'Connell RG. Prior probability cues bias sensory encoding with increasing task exposure. eLife 2024; 12:RP91135. [PMID: 38564237 PMCID: PMC10987094 DOI: 10.7554/elife.91135] [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] [Indexed: 04/04/2024] Open
Abstract
When observers have prior knowledge about the likely outcome of their perceptual decisions, they exhibit robust behavioural biases in reaction time and choice accuracy. Computational modelling typically attributes these effects to strategic adjustments in the criterion amount of evidence required to commit to a choice alternative - usually implemented by a starting point shift - but recent work suggests that expectations may also fundamentally bias the encoding of the sensory evidence itself. Here, we recorded neural activity with EEG while participants performed a contrast discrimination task with valid, invalid, or neutral probabilistic cues across multiple testing sessions. We measured sensory evidence encoding via contrast-dependent steady-state visual-evoked potentials (SSVEP), while a read-out of criterion adjustments was provided by effector-selective mu-beta band activity over motor cortex. In keeping with prior modelling and neural recording studies, cues evoked substantial biases in motor preparation consistent with criterion adjustments, but we additionally found that the cues produced a significant modulation of the SSVEP during evidence presentation. While motor preparation adjustments were observed in the earliest trials, the sensory-level effects only emerged with extended task exposure. Our results suggest that, in addition to strategic adjustments to the decision process, probabilistic information can also induce subtle biases in the encoding of the evidence itself.
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Affiliation(s)
- Kevin Walsh
- School of Psychological Sciences, Monash UniversityMelbourneAustralia
| | | | - Jessica Dully
- Institute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Simon P Kelly
- School of Electrical Engineering, University College DublinDublinIreland
- Trinity College Institute of Neuroscience, Trinity College DublinDublinIreland
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience, Trinity College DublinDublinIreland
- School of Psychology, Trinity College DublinDublinIreland
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21
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Sadeghnejad N, Ezoji M, Ebrahimpour R, Qodosi M, Zabbah S. A fully spiking coupled model of a deep neural network and a recurrent attractor explains dynamics of decision making in an object recognition task. J Neural Eng 2024; 21:026011. [PMID: 38506115 DOI: 10.1088/1741-2552/ad2d30] [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: 06/21/2022] [Accepted: 02/26/2024] [Indexed: 03/21/2024]
Abstract
Objective.Object recognition and making a choice regarding the recognized object is pivotal for most animals. This process in the brain contains information representation and decision making steps which both take different amount of times for different objects. While dynamics of object recognition and decision making are usually ignored in object recognition models, here we proposed a fully spiking hierarchical model, explaining the process of object recognition from information representation to making decision.Approach.Coupling a deep neural network and a recurrent attractor based decision making model beside using spike time dependent plasticity learning rules in several convolutional and pooling layers, we proposed a model which can resemble brain behaviors during an object recognition task. We also measured human choices and reaction times in a psychophysical object recognition task and used it as a reference to evaluate the model.Main results.The proposed model explains not only the probability of making a correct decision but also the time that it takes to make a decision. Importantly, neural firing rates in both feature representation and decision making levels mimic the observed patterns in animal studies (number of spikes (p-value < 10-173) and the time of the peak response (p-value < 10-31) are significantly modulated with the strength of the stimulus). Moreover, the speed-accuracy trade-off as a well-known characteristic of decision making process in the brain is also observed in the model (changing the decision bound significantly affect the reaction time (p-value < 10-59) and accuracy (p-value < 10-165)).Significance.We proposed a fully spiking deep neural network which can explain dynamics of making decision about an object in both neural and behavioral level. Results showed that there is a strong and significant correlation (r= 0.57) between the reaction time of the model and of human participants in the psychophysical object recognition task.
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Affiliation(s)
- Naser Sadeghnejad
- Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran
| | - Mehdi Ezoji
- Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran
| | - Reza Ebrahimpour
- Center for Cognitive Science, Institute for Convergence Science and Technology (ICST), Sharif University of Technology, Tehran, Iran
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mohamad Qodosi
- Department of Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
| | - Sajjad Zabbah
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom
- Max Planck UCL Centre for Computational Psychiatry and Aging Research, University College London, London, United Kingdom
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22
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Wang J, Du X, Yao S, Li L, Tanigawa H, Zhang X, Roe AW. Mesoscale organization of ventral and dorsal visual pathways in macaque monkey revealed by 7T fMRI. Prog Neurobiol 2024; 234:102584. [PMID: 38309458 DOI: 10.1016/j.pneurobio.2024.102584] [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: 08/17/2023] [Revised: 01/26/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
In human and nonhuman primate brains, columnar (mesoscale) organization has been demonstrated to underlie both lower and higher order aspects of visual information processing. Previous studies have focused on identifying functional preferences of mesoscale domains in specific areas; but there has been little understanding of how mesoscale domains may cooperatively respond to single visual stimuli across dorsal and ventral pathways. Here, we have developed ultrahigh-field 7 T fMRI methods to enable simultaneous mapping, in individual macaque monkeys, of response in both dorsal and ventral pathways to single simple color and motion stimuli. We provide the first evidence that anatomical V2 cytochrome oxidase-stained stripes are well aligned with fMRI maps of V2 stripes, settling a long-standing controversy. In the ventral pathway, a systematic array of paired color and luminance processing domains across V4 was revealed, suggesting a novel organization for surface information processing. In the dorsal pathway, in addition to high quality motion direction maps of MT, MST and V3A, alternating color and motion direction domains in V3 are revealed. As well, submillimeter motion domains were observed in peripheral LIPd and LIPv. In sum, our study provides a novel global snapshot of how mesoscale networks in the ventral and dorsal visual pathways form the organizational basis of visual objection recognition and vision for action.
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Affiliation(s)
- Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Xiao Du
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China
| | - Songping Yao
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Lihui Li
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Hisashi Tanigawa
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China
| | - Xiaotong Zhang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China; College of Electrical Engineering, Zhejiang University, Hangzhou, China.
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China; MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou, China.
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23
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El Hady A, Takahashi D, Sun R, Akinwale O, Boyd-Meredith T, Zhang Y, Charles AS, Brody CD. Chronic brain functional ultrasound imaging in freely moving rodents performing cognitive tasks. J Neurosci Methods 2024; 403:110033. [PMID: 38056633 PMCID: PMC10872377 DOI: 10.1016/j.jneumeth.2023.110033] [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: 08/01/2023] [Revised: 11/06/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Functional ultrasound imaging (fUS) is an emerging imaging technique that indirectly measures neural activity via changes in blood volume. Chronic fUS imaging during cognitive tasks in freely moving animals faces multiple exceptional challenges: performing large durable craniotomies with chronic implants, designing behavioral experiments matching the hemodynamic timescale, stabilizing the ultrasound probe during freely moving behavior, accurately assessing motion artifacts, and validating that the animal can perform cognitive tasks while tethered. NEW METHOD We provide validated solutions for those technical challenges. In addition, we present standardized step-by-step reproducible protocols, procedures, and data processing pipelines. Finally, we present proof-of-concept analysis of brain dynamics during a decision making task. RESULTS We obtain stable recordings from which we can robustly decode task variables from fUS data over multiple months. Moreover, we find that brain wide imaging through hemodynamic response is nonlinearly related to cognitive variables, such as task difficulty, as compared to sensory responses previously explored. COMPARISON WITH EXISTING METHODS Computational pipelines in fUS are nascent and we present an initial development of a full processing pathway to correct and segment fUS data. CONCLUSIONS Our methods provide stable imaging and analysis of behavior with fUS that will enable new experimental paradigms in understanding brain-wide dynamics in naturalistic behaviors.
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Affiliation(s)
- Ahmed El Hady
- Princeton Neuroscience Institute, Princeton University, Princeton, United States; Center for advanced study of collective behavior, University of Konstanz, Germany; Max Planck Institute of Animal Behavior, Konstanz, Germany
| | - Daniel Takahashi
- Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Ruolan Sun
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States
| | - Oluwateniola Akinwale
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States
| | - Tyler Boyd-Meredith
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Yisi Zhang
- Princeton Neuroscience Institute, Princeton University, Princeton, United States
| | - Adam S Charles
- Department of Biomedical Engineering, John Hopkins University, Baltimore, United States; Mathematical Institute for Data Science, Kavli Neuroscience Discovery Institute & Center for Imaging Science, John Hopkins University, Baltimore, United States.
| | - Carlos D Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, United States; Howard Hughes Medical Institute, Princeton University, Princeton, United States; Department of Molecular Biology, Princeton University, Princeton, United States.
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24
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Malach R. The neuronal basis of human creativity. Front Hum Neurosci 2024; 18:1367922. [PMID: 38476979 PMCID: PMC10929679 DOI: 10.3389/fnhum.2024.1367922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
Human creativity is a powerful cognitive ability underlying all uniquely human cultural and scientific advancement. However, the neuronal basis of this creative ability is unknown. Here, I propose that slow, spontaneous fluctuations in neuronal activity, also known as "resting state" fluctuations, constitute a universal mechanism underlying all facets of human creativity. Support for this hypothesis is derived from experiments that directly link spontaneous fluctuations and verbal creativity. Recent experimental and modeling advances in our understanding of the spontaneous fluctuations offer an explanation for the diversity and innovative nature of creativity, which is derived from a unique integration of random, neuronal noise on the one hand with individually specified, deterministic information acquired through learning, expertise training, and hereditary traits. This integration between stochasticity and order leads to a process that offers, on the one hand, original, unexpected outcomes but, on the other hand, endows these outcomes with knowledge-based meaning and significance.
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Affiliation(s)
- Rafael Malach
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
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25
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Gherman S, Markowitz N, Tostaeva G, Espinal E, Mehta AD, O'Connell RG, Kelly SP, Bickel S. Intracranial electroencephalography reveals effector-independent evidence accumulation dynamics in multiple human brain regions. Nat Hum Behav 2024:10.1038/s41562-024-01824-9. [PMID: 38366105 DOI: 10.1038/s41562-024-01824-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 01/10/2024] [Indexed: 02/18/2024]
Abstract
Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology; however, it is currently unclear where these originate in the brain. Here we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Participants undergoing invasive electrophysiological monitoring for epilepsy were asked to judge the direction of random-dot stimuli and respond either with a speeded button press (N = 24), or vocally, after a randomized delay (N = 12). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual buildup that was modulated by the strength of the sensory evidence, and an amplitude that predicted participants' choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision-making.
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Affiliation(s)
- Sabina Gherman
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
| | - Noah Markowitz
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Gelana Tostaeva
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Elizabeth Espinal
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, USA
| | - Ashesh D Mehta
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Departments of Neurology and Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Redmond G O'Connell
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Simon P Kelly
- School of Electrical and Electronic Engineering and UCD Centre for Biomedical Engineering, University College Dublin, Dublin, Ireland
| | - Stephan Bickel
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Departments of Neurology and Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA.
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26
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Kumano H, Uka T. Employment of time-varying sensory evidence to test the mechanisms underlying flexible decision-making. Neuroreport 2024; 35:107-114. [PMID: 38064356 PMCID: PMC10766094 DOI: 10.1097/wnr.0000000000001980] [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: 10/30/2023] [Accepted: 11/11/2023] [Indexed: 01/06/2024]
Abstract
To make flexible decisions in dynamic environments, the brain must integrate behaviorally relevant information while simultaneously discarding irrelevant information. This study aimed to investigate the mechanisms responsible for discarding irrelevant information during context-dependent decision-making. We trained two macaque monkeys to switch between direction and depth discrimination tasks in successive trials. During decision-making, the strength of the motion or depth signal changes transiently at various times, introducing a brief pulse. We assessed the effects of pulse on behavioral choices. Consistent with previous findings, early relevant pulses, such as motion pulses during direction discrimination, had a significantly larger effect compared to late pulses. Critically, the effects of irrelevant pulses, such as motion pulses during depth discrimination, exhibited an initial minimal effect, followed by an increase and subsequent decrease as a function of pulse timing. Gating mechanisms alone, aimed at discarding irrelevant information, did not account for the observed time course of pulse effects. Instead, the observed increase in the effects of irrelevant pulses with time suggested the involvement of a leaky integration mechanism. The results suggested that the brain controls the amount of disposal in accumulating sensory evidence during flexible decision-making.
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Affiliation(s)
- Hironori Kumano
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Yamanashi, Japan
| | - Takanori Uka
- Department of Integrative Physiology, Graduate School of Medicine, University of Yamanashi, Yamanashi, Japan
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27
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Del Río M, de Lange FP, Fritsche M, Ward J. Perceptual confirmation bias and decision bias underlie adaptation to sequential regularities. J Vis 2024; 24:5. [PMID: 38381426 PMCID: PMC10902869 DOI: 10.1167/jov.24.2.5] [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: 07/30/2023] [Accepted: 12/18/2023] [Indexed: 02/22/2024] Open
Abstract
Our perception does not depend exclusively on the immediate sensory input. It is also influenced by our internal predictions derived from prior observations and the temporal regularities of the environment, which can result in choice history biases. However, it is unclear how this flexible use of prior information to predict the future influences perceptual decisions. Prior information may bias decisions independently of the current sensory input, or it may modulate the weight of current sensory input based on its consistency with the expectation. To address this question, we used a visual decision-making task and manipulated the transitional probabilities between successive noisy grating stimuli. Using a reverse correlation analysis, we evaluated the contribution of stimulus-independent decision bias and stimulus-dependent sensitivity modulations to choice history biases. We found that both effects coexist, whereby there was increased bias to respond in line with the predicted orientation alongside modulations in perceptual sensitivity to favor perceptual information consistent with the prediction, akin to selective attention. Furthermore, at the individual differences level, we investigated the relationship between autistic-like traits and the adaptation of choice history biases to the sequential statistics of the environment. Over two studies, we found no convincing evidence of reduced adaptation to sequential regularities in individuals with high autistic-like traits. In sum, we present robust evidence for both perceptual confirmation bias and decision bias supporting adaptation to sequential regularities in the environment.
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Affiliation(s)
| | - Floris P de Lange
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Matthias Fritsche
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
- Department of Physiology, Anatomy & Genetics, University of Oxford, Oxford, UK
| | - Jamie Ward
- School of Psychology, University of Sussex, Brighton, UK
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Liu Z, Yan Y, Wang DH. Category representation in primary visual cortex after visual perceptual learning. Cogn Neurodyn 2024; 18:23-35. [PMID: 38406201 PMCID: PMC10881456 DOI: 10.1007/s11571-022-09926-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 11/15/2022] [Accepted: 12/19/2022] [Indexed: 01/31/2023] Open
Abstract
The visual perceptual learning (VPL) leads to long-term enhancement of visual task performance. The subjects are often trained to link different visual stimuli to several options, such as the widely used two-alternative forced choice (2AFC) task, which involves an implicit categorical decision. The enhancement of performance has been related to the specific changes of neural activities, but few studies investigate the effects of categorical responding on the changes of neural activities. Here we investigated whether the neural activities would exhibit the categorical characteristics if the subjects are requested to respond visual stimuli in a categorical manner during VPL. We analyzed the neural activities of two monkeys in a contour detection VPL. We found that the neural activities in primary visual cortex (V1) converge to one pattern if the contour can be detected by monkey and another pattern if the contour cannot be detected, exhibiting a kind of category learning that the neural representations of detectable contour become less selective for number of bars forming contour and diverge from the representations of undetectable contour. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09926-8.
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Affiliation(s)
- Zhaofan Liu
- School of Systems Science, Beijing Normal University, Beijing, 100875 China
| | - Yin Yan
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Xinjiekouwaidajie 19, Haidian, Beijing, 100875 China
- Chinese Institute for Brain Research, Beijing, China
| | - Da-Hui Wang
- School of Systems Science, Beijing Normal University, Beijing, 100875 China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Xinjiekouwaidajie 19, Haidian, Beijing, 100875 China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, 100875 China
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29
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Marshall TR, Ruesseler M, Hunt LT, O’Reilly JX. The representation of priors and decisions in the human parietal cortex. PLoS Biol 2024; 22:e3002383. [PMID: 38285671 PMCID: PMC10824454 DOI: 10.1371/journal.pbio.3002383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 12/11/2023] [Indexed: 01/31/2024] Open
Abstract
Animals actively sample their environment through orienting actions such as saccadic eye movements. Saccadic targets are selected based both on sensory evidence immediately preceding the saccade, and a "salience map" or prior built-up over multiple saccades. In the primate cortex, the selection of each individual saccade depends on competition between target-selective cells that ramp up their firing rate to saccade release. However, it is less clear how a cross-saccade prior might be implemented, either in neural firing or through an activity-silent mechanism such as modification of synaptic weights on sensory inputs. Here, we present evidence from magnetoencephalography for 2 distinct processes underlying the selection of the current saccade, and the representation of the prior, in human parietal cortex. While the classic ramping decision process for each saccade was reflected in neural firing rates (measured in the event-related field), a prior built-up over multiple saccades was implemented via modulation of the gain on sensory inputs from the preferred target, as evidenced by rapid frequency tagging. A cascade of computations over time (initial representation of the prior, followed by evidence accumulation and then an integration of prior and evidence) provides a mechanism by which a salience map may be built up across saccades in parietal cortex. It also provides insight into the apparent contradiction that inactivation of parietal cortex has been shown not to affect performance on single-trials, despite the presence of clear evidence accumulation signals in this region.
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Affiliation(s)
- Tom R. Marshall
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, Oxford University, Oxford, United Kingdom
| | - Maria Ruesseler
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, Oxford University, Oxford, United Kingdom
| | - Laurence T. Hunt
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, Oxford University, Oxford, United Kingdom
| | - Jill X. O’Reilly
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, Oxford University, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department for Clinical Neurosciences, Oxford University, Oxford, United Kingdom
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30
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Zheng Q, Gu Y. From Multisensory Integration to Multisensory Decision-Making. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1437:23-35. [PMID: 38270851 DOI: 10.1007/978-981-99-7611-9_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2024]
Abstract
Organisms live in a dynamic environment in which sensory information from multiple sources is ever changing. A conceptually complex task for the organisms is to accumulate evidence across sensory modalities and over time, a process known as multisensory decision-making. This is a new concept, in terms of that previous researches have been largely conducted in parallel disciplines. That is, much efforts have been put either in sensory integration across modalities using activity summed over a duration of time, or in decision-making with only one sensory modality that evolves over time. Recently, a few studies with neurophysiological measurements emerge to study how different sensory modality information is processed, accumulated, and integrated over time in decision-related areas such as the parietal or frontal lobes in mammals. In this review, we summarize and comment on these studies that combine the long-existed two parallel fields of multisensory integration and decision-making. We show how the new findings provide insight into our understanding about neural mechanisms mediating multisensory information processing in a more complete way.
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Affiliation(s)
- Qihao Zheng
- Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Yong Gu
- Systems Neuroscience, SInstitute of Neuroscience, Chinese Academy of Sciences, Shanghai, China.
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31
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Brown LS, Cho JR, Bolkan SS, Nieh EH, Schottdorf M, Tank DW, Brody CD, Witten IB, Goldman MS. Neural circuit models for evidence accumulation through choice-selective sequences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.01.555612. [PMID: 38234715 PMCID: PMC10793437 DOI: 10.1101/2023.09.01.555612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Decision making is traditionally thought to be mediated by populations of neurons whose firing rates persistently accumulate evidence across time. However, recent decision-making experiments in rodents have observed neurons across the brain that fire sequentially as a function of spatial position or time, rather than persistently, with the subset of neurons in the sequence depending on the animal's choice. We develop two new candidate circuit models, in which evidence is encoded either in the relative firing rates of two competing chains of neurons or in the network location of a stereotyped pattern ("bump") of neural activity. Encoded evidence is then faithfully transferred between neuronal populations representing different positions or times. Neural recordings from four different brain regions during a decision-making task showed that, during the evidence accumulation period, different brain regions displayed tuning curves consistent with different candidate models for evidence accumulation. This work provides mechanistic models and potential neural substrates for how graded-value information may be precisely accumulated within and transferred between neural populations, a set of computations fundamental to many cognitive operations.
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Esmaily J, Zabbah S, Ebrahimpour R, Bahrami B. Interpersonal alignment of neural evidence accumulation to social exchange of confidence. eLife 2023; 12:e83722. [PMID: 38128085 PMCID: PMC10746141 DOI: 10.7554/elife.83722] [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: 09/26/2022] [Accepted: 11/09/2023] [Indexed: 12/23/2023] Open
Abstract
Private, subjective beliefs about uncertainty have been found to have idiosyncratic computational and neural substrates yet, humans share such beliefs seamlessly and cooperate successfully. Bringing together decision making under uncertainty and interpersonal alignment in communication, in a discovery plus pre-registered replication design, we examined the neuro-computational basis of the relationship between privately held and socially shared uncertainty. Examining confidence-speed-accuracy trade-off in uncertainty-ridden perceptual decisions under social vs isolated context, we found that shared (i.e. reported confidence) and subjective (inferred from pupillometry) uncertainty dynamically followed social information. An attractor neural network model incorporating social information as top-down additive input captured the observed behavior and demonstrated the emergence of social alignment in virtual dyadic simulations. Electroencephalography showed that social exchange of confidence modulated the neural signature of perceptual evidence accumulation in the central parietal cortex. Our findings offer a neural population model for interpersonal alignment of shared beliefs.
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Affiliation(s)
- Jamal Esmaily
- Department of General Psychology and Education, Ludwig Maximillian UniversityMunichGermany
- Faculty of Computer Engineering, Shahid Rajaee Teacher Training UniversityTehranIslamic Republic of Iran
- Graduate School of Systemic Neurosciences, Ludwig Maximilian University MunichMunichGermany
| | - Sajjad Zabbah
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM)TehranIslamic Republic of Iran
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
- Max Planck UCL Centre for Computational Psychiatry and Aging Research, University College LondonLondonUnited Kingdom
| | - Reza Ebrahimpour
- Institute for Convergent Science and Technology, Sharif University of TechnologyTehranIslamic Republic of Iran
| | - Bahador Bahrami
- Department of General Psychology and Education, Ludwig Maximillian UniversityMunichGermany
- Centre for Adaptive Rationality, Max Planck Institute for Human DevelopmentBerlinGermany
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33
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Levitas DJ, Folco KL, James TW. Impact of aversive affect on neural mechanisms of categorization decisions. Brain Behav 2023; 13:e3312. [PMID: 37969052 PMCID: PMC10726818 DOI: 10.1002/brb3.3312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 09/13/2023] [Accepted: 10/24/2023] [Indexed: 11/17/2023] Open
Abstract
INTRODUCTION Many theories contend that evidence accumulation is a critical component of decision-making. Cognitive accumulation models typically interpret two main parameters: a drift rate and decision threshold. The former is the rate of accumulation, based on the quality of evidence, and the latter is the amount of evidence required for a decision. Some studies have found neural signals that mimic evidence accumulators and can be described by the two parameters. However, few studies have related these neural parameters to experimental manipulations of sensory data or memory representations. Here, we investigated the influence of affective salience on neural accumulation parameters. High affective salience has been repeatedly shown to influence decision-making, yet its effect on neural evidence accumulation has been unexamined. METHODS The current study used a two-choice object categorization task of body images (feet or hands). Half the images in each category were high in affective salience because they contained highly aversive features (gore and mutilation). To study such quick categorization decisions with a relatively slow technique like functional magnetic resonance imaging, we used a gradual reveal paradigm to lengthen cognitive processing time through the gradual "unmasking" of stimuli. RESULTS Because the aversive features were task-irrelevant, high affective salience produced a distractor effect, slowing decision time. In visual accumulation regions of interest, high affective salience produced a longer time to peak activation. Unexpectedly, the later peak appeared to be the product of changes to both drift rate and decision threshold. The drift rate for high affective salience was shallower, and the decision threshold was greater. To our knowledge, this is the first demonstration of an experimental manipulation of sensory data or memory representations that changed the neural decision threshold. CONCLUSION These findings advance our knowledge of the neural mechanisms underlying affective responses in general and the influence of high affective salience on object representations and categorization decisions.
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Affiliation(s)
- Daniel J. Levitas
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
| | - Kess L. Folco
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
| | - Thomas W. James
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonIndianaUSA
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34
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McGinty VB, Lupkin SM. Behavioral read-out from population value signals in primate orbitofrontal cortex. Nat Neurosci 2023; 26:2203-2212. [PMID: 37932464 PMCID: PMC11006434 DOI: 10.1038/s41593-023-01473-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 09/26/2023] [Indexed: 11/08/2023]
Abstract
The primate orbitofrontal cortex (OFC) has long been recognized for its role in value-based decisions; however, the exact mechanism linking value representations in the OFC to decision outcomes has remained elusive. Here, to address this question, we show, in non-human primates, that trial-wise variability in choices can be explained by variability in value signals decoded from many simultaneously recorded OFC neurons. Mechanistically, this relationship is consistent with the projection of activity within a low-dimensional value-encoding subspace onto a potentially higher-dimensional, behaviorally potent output subspace. Identifying this neural-behavioral link answers longstanding questions about the role of the OFC in economic decision-making and suggests population-level read-out mechanisms for the OFC similar to those recently identified in sensory and motor cortex.
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Affiliation(s)
- Vincent B McGinty
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA.
| | - Shira M Lupkin
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA
- Behavioral and Neural Sciences Graduate Program, Rutgers University-Newark, Newark, NJ, USA
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35
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Tiganj Z. Accumulating evidence by sampling from temporally organized memory. Learn Behav 2023; 51:351-352. [PMID: 36650395 DOI: 10.3758/s13420-022-00569-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/28/2022] [Indexed: 01/19/2023]
Abstract
A recent study by Shushruth et al. (2022, Current Biology 32[9], 1949-1960) demonstrated that monkeys postpone evidence accumulation until the relevant motor actions are revealed and then sequentially sample the evidence from memory. Here, we reflect on the insights this work provides into reinforcement learning in evidence accumulation tasks and neural mechanisms for the temporal organization of memory.
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Affiliation(s)
- Zoran Tiganj
- Department of Computer Science, Indiana University Bloomington, Bloomington, IN, USA.
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA.
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36
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James TW, Folco KL, Levitas DJ. Neural segregation and integration of sensory, decision, and action processes during object categorization. Neuropsychologia 2023; 190:108695. [PMID: 37769870 DOI: 10.1016/j.neuropsychologia.2023.108695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 09/20/2023] [Accepted: 09/25/2023] [Indexed: 10/03/2023]
Abstract
Neural and computational evidence suggests that perceptual decisions depend on an evidence accumulation process. The gradual reveal fMRI method, which prolongs a decision to match the slow temporal resolution of fMRI measurements, has classified dorsal visual stream regions as "Action" (alternatively, "Moment of Recognition" or "Commitment") and ventral visual stream regions as "Accumulator." Previous gradual reveal fMRI studies, however, only tested actions that were in response to decisions and, thus, related to evidence accumulation. To fully dissociate the contribution of sensory, decision, and motor components to Action and Accumulator regions in the dorsal and ventral visual streams, we extended the gradual reveal paradigm to also include responses made to cues where no decision was necessary. We found that the lateral occipital cortex in the ventral visual stream showed a highly selective Accumulator profile, whereas regions in the fusiform gyrus were influenced by action generation. Dorsal visual stream regions showed strikingly similar profiles as classical motor regions and also as regions of the salience network. These results suggest that the dorsal and ventral visual streams may appear highly segregated because they include a small number of regions that are highly selective for Accumulator or Action. However, the streams may be more integrated than previously thought and this integration may be accomplished by regions with graded responses that are less selective (i.e., more distributed).
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Affiliation(s)
- Thomas W James
- Psychological and Brain Sciences, Indiana University Bloomington, USA.
| | - Kess L Folco
- Psychological and Brain Sciences, Indiana University Bloomington, USA
| | - Daniel J Levitas
- Psychological and Brain Sciences, Indiana University Bloomington, USA
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37
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Pusch R, Packheiser J, Azizi AH, Sevincik CS, Rose J, Cheng S, Stüttgen MC, Güntürkün O. Working memory performance is tied to stimulus complexity. Commun Biol 2023; 6:1119. [PMID: 37923920 PMCID: PMC10624839 DOI: 10.1038/s42003-023-05486-7] [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: 07/28/2023] [Accepted: 10/18/2023] [Indexed: 11/06/2023] Open
Abstract
Working memory is the cognitive capability to maintain and process information over short periods. Behavioral and computational studies have shown that visual information is associated with working memory performance. However, the underlying neural correlates remain unknown. To identify how visual information affects working memory performance, we conducted behavioral experiments in pigeons (Columba livia) and single unit recordings in the avian prefrontal analog, the nidopallium caudolaterale (NCL). Complex pictures featuring luminance, spatial and color information, were associated with higher working memory performance compared to uniform gray pictures in conjunction with distinct neural coding patterns. For complex pictures, we found a multiplexed neuronal code displaying visual and value-related features that switched to a representation of the upcoming choice during a delay period. When processing gray stimuli, NCL neurons did not multiplex and exclusively represented the choice already during stimulus presentation and throughout the delay period. The prolonged representation possibly resulted in a decay of the memory trace ultimately leading to a decrease in performance. In conclusion, we found that high stimulus complexity is associated with neuronal multiplexing of the working memory representation possibly allowing a facilitated read-out of the neural code resulting in enhancement of working memory performance.
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Affiliation(s)
- Roland Pusch
- Department of Biopsychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany.
| | - Julian Packheiser
- Department of Biopsychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany
- Social Brain Lab, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Amir Hossein Azizi
- Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Karaj, Iran
| | - Celil Semih Sevincik
- Department of Biopsychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany
| | - Jonas Rose
- Neural Basis of Learning, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany
| | - Sen Cheng
- Institute for Neural Computation, Faculty of Computer Science, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany
| | - Maik C Stüttgen
- Institute of Pathophysiology, University Medical Center of the Johannes Gutenberg University, Duesbergweg 6, D-55128, Mainz, Germany
| | - Onur Güntürkün
- Department of Biopsychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstraße 150, D-44780, Bochum, Germany
- Research Center One Health Ruhr, Research Alliance Ruhr, Ruhr University Bochum, Bochum, Germany
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38
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Imani E, Radkani S, Hashemi A, Harati A, Pourreza H, Moazami Goudarzi M. Distributed Coding of Evidence Accumulation across the Mouse Brain Using Microcircuits with a Diversity of Timescales. eNeuro 2023; 10:ENEURO.0282-23.2023. [PMID: 37863657 PMCID: PMC10626503 DOI: 10.1523/eneuro.0282-23.2023] [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: 08/06/2023] [Revised: 09/11/2023] [Accepted: 09/25/2023] [Indexed: 10/22/2023] Open
Abstract
The gradual accumulation of noisy evidence for or against options is the main step in the perceptual decision-making process. Using brain-wide electrophysiological recording in mice (Steinmetz et al., 2019), we examined neural correlates of evidence accumulation across brain areas. We demonstrated that the neurons with drift-diffusion model (DDM)-like firing rate activity (i.e., evidence-sensitive ramping firing rate) were distributed across the brain. Exploring the underlying neural mechanism of evidence accumulation for the DDM-like neurons revealed different accumulation mechanisms (i.e., single and race) both within and across the brain areas. Our findings support the hypothesis that evidence accumulation is happening through multiple integration mechanisms in the brain. We further explored the timescale of the integration process in the single and race accumulator models. The results demonstrated that the accumulator microcircuits within each brain area had distinct properties in terms of their integration timescale, which were organized hierarchically across the brain. These findings support the existence of evidence accumulation over multiple timescales. Besides the variability of integration timescale across the brain, a heterogeneity of timescales was observed within each brain area as well. We demonstrated that this variability reflected the diversity of microcircuit parameters, such that accumulators with longer integration timescales had higher recurrent excitation strength.
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Affiliation(s)
- Elaheh Imani
- Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran
| | - Setayesh Radkani
- Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139
| | | | - Ahad Harati
- Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran
| | - Hamidreza Pourreza
- Department of Computer Engineering, Ferdowsi University of Mashhad, Mashhad, 9177948974, Iran
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Ruesseler M, Weber LA, Marshall TR, O'Reilly J, Hunt LT. Quantifying decision-making in dynamic, continuously evolving environments. eLife 2023; 12:e82823. [PMID: 37883173 PMCID: PMC10602589 DOI: 10.7554/elife.82823] [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: 08/18/2022] [Accepted: 10/13/2023] [Indexed: 10/27/2023] Open
Abstract
During perceptual decision-making tasks, centroparietal electroencephalographic (EEG) potentials report an evidence accumulation-to-bound process that is time locked to trial onset. However, decisions in real-world environments are rarely confined to discrete trials; they instead unfold continuously, with accumulation of time-varying evidence being recency-weighted towards its immediate past. The neural mechanisms supporting recency-weighted continuous decision-making remain unclear. Here, we use a novel continuous task design to study how the centroparietal positivity (CPP) adapts to different environments that place different constraints on evidence accumulation. We show that adaptations in evidence weighting to these different environments are reflected in changes in the CPP. The CPP becomes more sensitive to fluctuations in sensory evidence when large shifts in evidence are less frequent, and the potential is primarily sensitive to fluctuations in decision-relevant (not decision-irrelevant) sensory input. A complementary triphasic component over occipito-parietal cortex encodes the sum of recently accumulated sensory evidence, and its magnitude covaries with parameters describing how different individuals integrate sensory evidence over time. A computational model based on leaky evidence accumulation suggests that these findings can be accounted for by a shift in decision threshold between different environments, which is also reflected in the magnitude of pre-decision EEG activity. Our findings reveal how adaptations in EEG responses reflect flexibility in evidence accumulation to the statistics of dynamic sensory environments.
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Affiliation(s)
- Maria Ruesseler
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford Centre for Human Brain Activity (OHBA) University Department of Psychiatry Warneford HospitalOxfordUnited Kingdom
| | - Lilian Aline Weber
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford Centre for Human Brain Activity (OHBA) University Department of Psychiatry Warneford HospitalOxfordUnited Kingdom
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory QuarterOxfordUnited Kingdom
| | - Tom Rhys Marshall
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory QuarterOxfordUnited Kingdom
- Centre for Human Brain Health, University of BirminghamBirminghamUnited Kingdom
| | - Jill O'Reilly
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory QuarterOxfordUnited Kingdom
| | - Laurence Tudor Hunt
- Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford Centre for Human Brain Activity (OHBA) University Department of Psychiatry Warneford HospitalOxfordUnited Kingdom
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory QuarterOxfordUnited Kingdom
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40
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Yang Y, Zheng Z, Liu L, Zheng H, Zhen Y, Zheng Y, Wang X, Tang S. Enhanced brain structure-function tethering in transmodal cortex revealed by high-frequency eigenmodes. Nat Commun 2023; 14:6744. [PMID: 37875493 PMCID: PMC10598018 DOI: 10.1038/s41467-023-42053-4] [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: 07/12/2022] [Accepted: 09/28/2023] [Indexed: 10/26/2023] Open
Abstract
While the link between brain structure and function remains an ongoing challenge, the prevailing hypothesis is that the structure-function relationship may itself be gradually decoupling from unimodal to transmodal cortex. However, this hypothesis is constrained by the underlying models which may neglect requisite information. Here we relate structural and functional connectivity derived from diffusion and functional MRI through orthogonal eigenmodes governing frequency-specific diffusion patterns. We find that low-frequency eigenmodes contribute little to functional interactions in transmodal cortex, resulting in divergent structure-function relationships. Conversely, high-frequency eigenmodes predominantly support neuronal coactivation patterns in these areas, inducing structure-function convergence along a unimodal-transmodal hierarchy. High-frequency information, although weak and scattered, could enhance the structure-function tethering, especially in transmodal association cortices. Our findings suggest that the structure-function decoupling may not be an intrinsic property of brain organization, but can be narrowed through multiplexed and regionally specialized spatiotemporal propagation regimes.
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Affiliation(s)
- Yaqian Yang
- School of Mathematical Sciences, Beihang University, Beijing, 100191, China
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China
| | - Zhiming Zheng
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing, 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing, 100191, China
- Zhongguancun Laboratory, Beijing, China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, 100191, China
- PengCheng Laboratory, Shenzhen, 518055, China
- Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai, 264003, China
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China
| | - Longzhao Liu
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China
- Institute of Artificial Intelligence, Beihang University, Beijing, 100191, China
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing, 100191, China
- Zhongguancun Laboratory, Beijing, China
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, 100191, China
- PengCheng Laboratory, Shenzhen, 518055, China
| | - Hongwei Zheng
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, 100191, China
- Beijing Academy of Blockchain and Edge Computing (BABEC), Beijing, 100085, China
| | - Yi Zhen
- School of Mathematical Sciences, Beihang University, Beijing, 100191, China
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China
| | - Yi Zheng
- School of Mathematical Sciences, Beihang University, Beijing, 100191, China
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China
| | - Xin Wang
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China.
- Institute of Artificial Intelligence, Beihang University, Beijing, 100191, China.
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing, 100191, China.
- Zhongguancun Laboratory, Beijing, China.
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, 100191, China.
- PengCheng Laboratory, Shenzhen, 518055, China.
| | - Shaoting Tang
- Key Laboratory of Mathematics, Informatics and Behavioral Semantics (LMIB), Beihang University, Beijing, 100191, China.
- Institute of Artificial Intelligence, Beihang University, Beijing, 100191, China.
- State Key Lab of Software Development Environment (NLSDE), Beihang University, Beijing, 100191, China.
- Zhongguancun Laboratory, Beijing, China.
- Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University, Beijing, 100191, China.
- PengCheng Laboratory, Shenzhen, 518055, China.
- Institute of Medical Artificial Intelligence, Binzhou Medical University, Yantai, 264003, China.
- School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China.
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41
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Boucher PO, Wang T, Carceroni L, Kane G, Shenoy KV, Chandrasekaran C. Initial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex. Nat Commun 2023; 14:6510. [PMID: 37845221 PMCID: PMC10579235 DOI: 10.1038/s41467-023-41752-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 09/18/2023] [Indexed: 10/18/2023] Open
Abstract
We used a dynamical systems perspective to understand decision-related neural activity, a fundamentally unresolved problem. This perspective posits that time-varying neural activity is described by a state equation with an initial condition and evolves in time by combining at each time step, recurrent activity and inputs. We hypothesized various dynamical mechanisms of decisions, simulated them in models to derive predictions, and evaluated these predictions by examining firing rates of neurons in the dorsal premotor cortex (PMd) of monkeys performing a perceptual decision-making task. Prestimulus neural activity (i.e., the initial condition) predicted poststimulus neural trajectories, covaried with RT and the outcome of the previous trial, but not with choice. Poststimulus dynamics depended on both the sensory evidence and initial condition, with easier stimuli and fast initial conditions leading to the fastest choice-related dynamics. Together, these results suggest that initial conditions combine with sensory evidence to induce decision-related dynamics in PMd.
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Affiliation(s)
- Pierre O Boucher
- Department of Biomedical Engineering, Boston University, Boston, 02115, MA, USA
| | - Tian Wang
- Department of Biomedical Engineering, Boston University, Boston, 02115, MA, USA
| | - Laura Carceroni
- Undergraduate Program in Neuroscience, Boston University, Boston, 02115, MA, USA
| | - Gary Kane
- Department of Psychological and Brain Sciences, Boston University, Boston, 02115, MA, USA
| | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, 94305, CA, USA
- Department of Neurobiology, Stanford University, Stanford, 94305, CA, USA
- Howard Hughes Medical Institute, HHMI, Chevy Chase, 20815-6789, MD, USA
- Department of Bioengineering, Stanford University, Stanford, 94305, CA, USA
- Stanford Neurosciences Institute, Stanford University, Stanford, 94305, CA, USA
- Bio-X Program, Stanford University, Stanford, 94305, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, 94305, CA, USA
| | - Chandramouli Chandrasekaran
- Department of Biomedical Engineering, Boston University, Boston, 02115, MA, USA.
- Department of Psychological and Brain Sciences, Boston University, Boston, 02115, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, 02115, MA, USA.
- Department of Anatomy & Neurobiology, Boston University, Boston, 02118, MA, USA.
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42
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Sandhaeger F, Omejc N, Pape AA, Siegel M. Abstract perceptual choice signals during action-linked decisions in the human brain. PLoS Biol 2023; 21:e3002324. [PMID: 37816222 PMCID: PMC10564462 DOI: 10.1371/journal.pbio.3002324] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 09/04/2023] [Indexed: 10/12/2023] Open
Abstract
Humans can make abstract choices independent of motor actions. However, in laboratory tasks, choices are typically reported with an associated action. Consequentially, knowledge about the neural representation of abstract choices is sparse, and choices are often thought to evolve as motor intentions. Here, we show that in the human brain, perceptual choices are represented in an abstract, motor-independent manner, even when they are directly linked to an action. We measured MEG signals while participants made choices with known or unknown motor response mapping. Using multivariate decoding, we quantified stimulus, perceptual choice, and motor response information with distinct cortical distributions. Choice representations were invariant to whether the response mapping was known during stimulus presentation, and they occupied a distinct representational space from motor signals. As expected from an internal decision variable, they were informed by the stimuli, and their strength predicted decision confidence and accuracy. Our results demonstrate abstract neural choice signals that generalize to action-linked decisions, suggesting a general role of an abstract choice stage in human decision-making.
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Affiliation(s)
- Florian Sandhaeger
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- MEG Center, University of Tübingen, Tübingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tübingen, Tübingen, Germany
| | - Nina Omejc
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- MEG Center, University of Tübingen, Tübingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tübingen, Tübingen, Germany
| | - Anna-Antonia Pape
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- MEG Center, University of Tübingen, Tübingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tübingen, Tübingen, Germany
| | - Markus Siegel
- Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- MEG Center, University of Tübingen, Tübingen, Germany
- German Center for Mental Health (DZPG), Tübingen, Germany
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43
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Soans RS, Renken RJ, Saxena R, Tandon R, Cornelissen FW, Gandhi TK. A Framework for the Continuous Evaluation of 3D Motion Perception in Virtual Reality. IEEE Trans Biomed Eng 2023; 70:2933-2942. [PMID: 37104106 DOI: 10.1109/tbme.2023.3271288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
OBJECTIVE We present a novel framework for the detection and continuous evaluation of 3D motion perception by deploying a virtual reality environment with built-in eye tracking. METHODS We created a biologically-motivated virtual scene that involved a ball moving in a restricted Gaussian random walk against a background of 1/f noise. Sixteen visually healthy participants were asked to follow the moving ball while their eye movements were monitored binocularly using the eye tracker. We calculated the convergence positions of their gaze in 3D using their fronto-parallel coordinates and linear least-squares optimization. Subsequently, to quantify 3D pursuit performance, we employed a first-order linear kernel analysis known as the Eye Movement Correlogram technique to separately analyze the horizontal, vertical and depth components of the eye movements. Finally, we checked the robustness of our method by adding systematic and variable noise to the gaze directions and re-evaluating 3D pursuit performance. RESULTS We found that the pursuit performance in the motion-through depth component was reduced significantly compared to that for fronto-parallel motion components. We found that our technique was robust in evaluating 3D motion perception, even when systematic and variable noise was added to the gaze directions. CONCLUSION The proposed framework enables the assessment of 3D Motion perception by evaluating continuous pursuit performance through eye-tracking. SIGNIFICANCE Our framework paves the way for a rapid, standardized and intuitive assessment of 3D motion perception in patients with various eye disorders.
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44
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Zeng Z, Zhang C, Gu Y. Visuo-vestibular heading perception: a model system to study multi-sensory decision making. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220334. [PMID: 37545303 PMCID: PMC10404926 DOI: 10.1098/rstb.2022.0334] [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: 12/19/2022] [Accepted: 05/15/2023] [Indexed: 08/08/2023] Open
Abstract
Integrating noisy signals across time as well as sensory modalities, a process named multi-sensory decision making (MSDM), is an essential strategy for making more accurate and sensitive decisions in complex environments. Although this field is just emerging, recent extraordinary works from different perspectives, including computational theory, psychophysical behaviour and neurophysiology, begin to shed new light onto MSDM. In the current review, we focus on MSDM by using a model system of visuo-vestibular heading. Combining well-controlled behavioural paradigms on virtual-reality systems, single-unit recordings, causal manipulations and computational theory based on spiking activity, recent progress reveals that vestibular signals contain complex temporal dynamics in many brain regions, including unisensory, multi-sensory and sensory-motor association areas. This challenges the brain for cue integration across time and sensory modality such as optic flow which mainly contains a motion velocity signal. In addition, new evidence from the higher-level decision-related areas, mostly in the posterior and frontal/prefrontal regions, helps revise our conventional thought on how signals from different sensory modalities may be processed, converged, and moment-by-moment accumulated through neural circuits for forming a unified, optimal perceptual decision. This article is part of the theme issue 'Decision and control processes in multisensory perception'.
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Affiliation(s)
- Zhao Zeng
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, 200031 Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049 Beijing, People's Republic of China
| | - Ce Zhang
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, 200031 Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049 Beijing, People's Republic of China
| | - Yong Gu
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, 200031 Shanghai, People's Republic of China
- University of Chinese Academy of Sciences, 100049 Beijing, People's Republic of China
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45
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Fennell A, Ratcliff R. A spatially continuous diffusion model of visual working memory. Cogn Psychol 2023; 145:101595. [PMID: 37659278 PMCID: PMC10546276 DOI: 10.1016/j.cogpsych.2023.101595] [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: 01/10/2023] [Revised: 07/28/2023] [Accepted: 08/02/2023] [Indexed: 09/04/2023]
Abstract
We present results from five visual working memory (VWM) experiments in which participants were briefly shown between 2 and 6 colored squares. They were then cued to recall the color of one of the squares and they responded by choosing the color on a continuous color wheel. The experiments provided response proportions and response time (RT) measures as a function of angle for the choices. Current VWM models for this task include discrete models that assume an item is either within working memory or not and resource models that assume that memory strength varies as a function of the number of items. Because these models do not include processes that allow them to account for RT data, we implemented them within the spatially continuous diffusion model (SCDM, Ratcliff, 2018) and use the experimental data to evaluate these combined models. In the SCDM, evidence retrieved from memory is represented as a spatially continuous normal distribution and this drives the decision process until a criterion (represented as a 1-D line) is reached, which produces a decision. Noise in the accumulation process is represented by continuous Gaussian process noise over spatial position. The models that fit best from the discrete and resource-based classes converged on a common model that had a guessing component and that allowed the height of the normal memory-strength distribution to vary with number of items. The guessing component was implemented as a regular decision process driven by a flat evidence distribution, a zero-drift process. The combination of choice and RT data allows models that were not identifiable based on choice data alone to be discriminated.
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46
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Matsumiya K, Furukawa S. Perceptual decisions interfere more with eye movements than with reach movements. Commun Biol 2023; 6:882. [PMID: 37648896 PMCID: PMC10468498 DOI: 10.1038/s42003-023-05249-4] [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: 01/17/2023] [Accepted: 08/16/2023] [Indexed: 09/01/2023] Open
Abstract
Perceptual judgements are formed through invisible cognitive processes. Reading out these judgements is essential for advancing our understanding of decision making and requires inferring covert cognitive states based on overt motor actions. Although intuition suggests that these actions must be related to the formation of decisions about where to move body parts, actions have been reported to be influenced by perceptual judgements even when the action is irrelevant to the perceptual judgement. However, despite performing multiple actions in our daily lives, how perceptual judgements influence multiple judgement-irrelevant actions is unknown. Here we show that perceptual judgements affect only saccadic eye movements when simultaneous judgement-irrelevant saccades and reaches are made, demonstrating that perceptual judgement-related signals continuously flow into the oculomotor system alone when multiple judgement-irrelevant actions are performed. This suggests that saccades are useful for making inferences about covert perceptual decisions, even when the actions are not tied to decision making.
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Affiliation(s)
| | - Shota Furukawa
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
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47
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Emonds AMX, Srinath R, Nielsen KJ, Connor CE. Object representation in a gravitational reference frame. eLife 2023; 12:e81701. [PMID: 37561119 PMCID: PMC10414968 DOI: 10.7554/elife.81701] [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: 07/08/2022] [Accepted: 07/19/2023] [Indexed: 08/11/2023] Open
Abstract
When your head tilts laterally, as in sports, reaching, and resting, your eyes counterrotate less than 20%, and thus eye images rotate, over a total range of about 180°. Yet, the world appears stable and vision remains normal. We discovered a neural strategy for rotational stability in anterior inferotemporal cortex (IT), the final stage of object vision in primates. We measured object orientation tuning of IT neurons in macaque monkeys tilted +25 and -25° laterally, producing ~40° difference in retinal image orientation. Among IT neurons with consistent object orientation tuning, 63% remained stable with respect to gravity across tilts. Gravitational tuning depended on vestibular/somatosensory but also visual cues, consistent with previous evidence that IT processes scene cues for gravity's orientation. In addition to stability across image rotations, an internal gravitational reference frame is important for physical understanding of a world where object position, posture, structure, shape, movement, and behavior interact critically with gravity.
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Affiliation(s)
- Alexandriya MX Emonds
- Department of Biomedical Engineering, Johns Hopkins University School of MedicineBaltimoreUnited States
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
| | - Ramanujan Srinath
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Kristina J Nielsen
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of MedicineBaltimoreUnited States
| | - Charles E Connor
- Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreUnited States
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of MedicineBaltimoreUnited States
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48
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Cimeša L, Ciric L, Ostojic S. Geometry of population activity in spiking networks with low-rank structure. PLoS Comput Biol 2023; 19:e1011315. [PMID: 37549194 PMCID: PMC10461857 DOI: 10.1371/journal.pcbi.1011315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 08/28/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023] Open
Abstract
Recurrent network models are instrumental in investigating how behaviorally-relevant computations emerge from collective neural dynamics. A recently developed class of models based on low-rank connectivity provides an analytically tractable framework for understanding of how connectivity structure determines the geometry of low-dimensional dynamics and the ensuing computations. Such models however lack some fundamental biological constraints, and in particular represent individual neurons in terms of abstract units that communicate through continuous firing rates rather than discrete action potentials. Here we examine how far the theoretical insights obtained from low-rank rate networks transfer to more biologically plausible networks of spiking neurons. Adding a low-rank structure on top of random excitatory-inhibitory connectivity, we systematically compare the geometry of activity in networks of integrate-and-fire neurons to rate networks with statistically equivalent low-rank connectivity. We show that the mean-field predictions of rate networks allow us to identify low-dimensional dynamics at constant population-average activity in spiking networks, as well as novel non-linear regimes of activity such as out-of-phase oscillations and slow manifolds. We finally exploit these results to directly build spiking networks that perform nonlinear computations.
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Affiliation(s)
- Ljubica Cimeša
- Laboratoire de Neurosciences Cognitives Computationnelles, Département d’Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France
| | - Lazar Ciric
- Laboratoire de Neurosciences Cognitives Computationnelles, Département d’Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France
| | - Srdjan Ostojic
- Laboratoire de Neurosciences Cognitives Computationnelles, Département d’Études Cognitives, École Normale Supérieure, INSERM U960, PSL University, Paris, France
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49
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Yoo M, Yang YS, Rah JC, Choi JH. Different resting membrane potentials in posterior parietal cortex and prefrontal cortex in the view of recurrent synaptic strengths and neural network dynamics. Front Cell Neurosci 2023; 17:1153970. [PMID: 37519632 PMCID: PMC10372347 DOI: 10.3389/fncel.2023.1153970] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 06/27/2023] [Indexed: 08/01/2023] Open
Abstract
In this study, we introduce the importance of elevated membrane potentials (MPs) in the prefrontal cortex (PFC) compared to that in the posterior parietal cortex (PPC), based on new observations of different MP levels in these areas. Through experimental data and spiking neural network modeling, we investigated a possible mechanism of the elevated membrane potential in the PFC and how these physiological differences affect neural network dynamics and cognitive functions in the PPC and PFC. Our findings indicate that NMDA receptors may be a main contributor to the elevated MP in the PFC region and highlight the potential of using a modeling toolkit to investigate the means by which changes in synaptic properties can affect neural dynamics and potentiate desirable cognitive functions through population activities in the corresponding brain regions.
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Affiliation(s)
- Minsu Yoo
- Korea Brain Research Institute, Daegu, Republic of Korea
| | - Yoon-Sil Yang
- Korea Brain Research Institute, Daegu, Republic of Korea
| | - Jong-Cheol Rah
- Korea Brain Research Institute, Daegu, Republic of Korea
- Daegu Gyeongbuk Institute of Science and Technology, Daegu, Republic of Korea
| | - Joon Ho Choi
- Korea Brain Research Institute, Daegu, Republic of Korea
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50
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Webb TW, Miyoshi K, So TY, Rajananda S, Lau H. Natural statistics support a rational account of confidence biases. Nat Commun 2023; 14:3992. [PMID: 37414780 PMCID: PMC10326055 DOI: 10.1038/s41467-023-39737-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Previous work has sought to understand decision confidence as a prediction of the probability that a decision will be correct, leading to debate over whether these predictions are optimal, and whether they rely on the same decision variable as decisions themselves. This work has generally relied on idealized, low-dimensional models, necessitating strong assumptions about the representations over which confidence is computed. To address this, we used deep neural networks to develop a model of decision confidence that operates directly over high-dimensional, naturalistic stimuli. The model accounts for a number of puzzling dissociations between decisions and confidence, reveals a rational explanation of these dissociations in terms of optimization for the statistics of sensory inputs, and makes the surprising prediction that, despite these dissociations, decisions and confidence depend on a common decision variable.
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Affiliation(s)
| | | | - Tsz Yan So
- The University of Hong Kong, Hong Kong, Hong Kong
| | | | - Hakwan Lau
- Laboratory for Consciousness, RIKEN Center for Brain Science, Saitama, Japan.
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