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Hirabayashi T, Nagai Y, Hori Y, Hori Y, Oyama K, Mimura K, Miyakawa N, Iwaoki H, Inoue KI, Suhara T, Takada M, Higuchi M, Minamimoto T. Multiscale chemogenetic dissection of fronto-temporal top-down regulation for object memory in primates. Nat Commun 2024; 15:5369. [PMID: 38987235 PMCID: PMC11237144 DOI: 10.1038/s41467-024-49570-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: 11/17/2023] [Accepted: 06/07/2024] [Indexed: 07/12/2024] Open
Abstract
Visual object memory is a fundamental element of various cognitive abilities, and the underlying neural mechanisms have been extensively examined especially in the anterior temporal cortex of primates. However, both macroscopic large-scale functional network in which this region is embedded and microscopic neuron-level dynamics of top-down regulation it receives for object memory remains elusive. Here, we identified the orbitofrontal node as a critical partner of the anterior temporal node for object memory by combining whole-brain functional imaging during rest and a short-term object memory task in male macaques. Focal chemogenetic silencing of the identified orbitofrontal node downregulated both the local orbitofrontal and remote anterior temporal nodes during the task, in association with deteriorated mnemonic, but not perceptual, performance. Furthermore, imaging-guided neuronal recordings in the same monkeys during the same task causally revealed that orbitofrontal top-down modulation enhanced stimulus-selective mnemonic signal in individual anterior temporal neurons while leaving bottom-up perceptual signal unchanged. Furthermore, similar activity difference was also observed between correct and mnemonic error trials before silencing, suggesting its behavioral relevance. These multifaceted but convergent results provide a multiscale causal understanding of dynamic top-down regulation of the anterior temporal cortex along the ventral fronto-temporal network underpinning short-term object memory in primates.
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Affiliation(s)
- Toshiyuki Hirabayashi
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan.
| | - Yuji Nagai
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Yuki Hori
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Yukiko Hori
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Kei Oyama
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Koki Mimura
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Naohisa Miyakawa
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Haruhiko Iwaoki
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Ken-Ichi Inoue
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi, 484-8506, Japan
| | - Tetsuya Suhara
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Masahiko Takada
- Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Aichi, 484-8506, Japan
| | - Makoto Higuchi
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
| | - Takafumi Minamimoto
- Advanced Neuroimaging Center, National Institutes for Quantum Science and Technology, Chiba, 263-8555, Japan
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Tang H, Bartolo-Orozco R, Averbeck BB. Ventral frontostriatal circuitry mediates the computation of reinforcement from symbolic gains and losses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587097. [PMID: 38617219 PMCID: PMC11014508 DOI: 10.1101/2024.04.03.587097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Reinforcement learning (RL), particularly in primates, is often driven by symbolic outcomes. However, it is usually studied with primary reinforcers. To examine the neural mechanisms underlying learning from symbolic outcomes, we trained monkeys on a task in which they learned to choose options that led to gains of tokens and avoid choosing options that led to losses of tokens. We then recorded simultaneously from the orbitofrontal cortex (OFC), ventral striatum (VS), amygdala (AMY), and the mediodorsal thalamus (MDt). We found that the OFC played a dominant role in coding token outcomes and token prediction errors. The other areas contributed complementary functions with the VS coding appetitive outcomes and the AMY coding the salience of outcomes. The MDt coded actions and relayed information about tokens between the OFC and VS. Thus, OFC leads the process of symbolic reinforcement learning in the ventral frontostriatal circuitry.
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Rozzi S, Gravante A, Basile C, Cappellaro G, Gerbella M, Fogassi L. Ventrolateral prefrontal neurons of the monkey encode instructions in the 'pragmatic' format of the associated behavioral outcomes. Prog Neurobiol 2023; 229:102499. [PMID: 37429374 DOI: 10.1016/j.pneurobio.2023.102499] [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: 03/08/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/12/2023]
Abstract
The prefrontal cortex plays an important role in coding rules and producing context-appropriate behaviors. These processes necessarily require the generation of goals based on current context. Indeed, instructing stimuli are prospectively encoded in prefrontal cortex in relation to behavioral demands, but the coding format of this neural representation is, to date, largely unknown. In order to study how instructions and behaviors are encoded in prefrontal cortex, we recorded the activity of monkeys (Macaca mulatta) ventrolateral prefrontal neurons in a task requiring to perform (Action condition) or withhold (Inaction condition) grasping actions on real objects. Our data show that there are neurons responding in different task phases, and that the neuronal population discharge is stronger in the Inaction condition when the instructing cue is presented, and in the Action condition in the subsequent phases, from object presentation to action execution. Decoding analyses performed on neuronal populations showed that the neural activity recorded during the initial phases of the task shares the same type of format with that recorded during the final phases. We propose that this format has a pragmatic nature, that is instructions and goals are encoded by prefrontal neurons as predictions of the behavioral outcome.
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Affiliation(s)
- Stefano Rozzi
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy.
| | - Alfonso Gravante
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy
| | - Claudio Basile
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy
| | - Giorgio Cappellaro
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy
| | - Marzio Gerbella
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy
| | - Leonardo Fogassi
- Department of Medicine and Surgery, University of Parma, Via Volturno 39, 43125 Parma, Italy
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4
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Xu X, Ruan W, Liu F, Liu Q, Gai Y, Su Y, Liang Z, Sun X, Lan X. Characterizing Early-Onset Alzheimer Disease Using Multiprobe PET/MRI: An AT(N) Framework-Based Study. Clin Nucl Med 2023; 48:474-482. [PMID: 37075301 DOI: 10.1097/rlu.0000000000004663] [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: 04/21/2023]
Abstract
PURPOSE Early-onset Alzheimer disease (EOAD) is rare, highly heterogeneous, and associated with poor prognosis. This AT(N) Framework-based study aimed to compare multiprobe PET/MRI findings between EOAD and late-onset Alzheimer disease (LOAD) patients and explore potential imaging biomarkers for characterizing EOAD. METHODS Patients with AD who underwent PET/MRI in our PET center were retrospectively reviewed and grouped according to the age at disease onset: EOAD, younger than 60 years; and LOAD, 60 years or older. Clinical characteristics were recorded. All study patients had positive β-amyloid PET imaging; some patients also underwent 18 F-FDG and 18 F-florzolotau PET. Imaging of the EOAD and LOAD groups was compared using region-of-interest and voxel-based analysis. Correlation of onset age and regional SUV ratios were also evaluated. RESULTS One hundred thirty-three patients were analyzed (75 EOAD and 58 LOAD patients). Sex ( P = 0.515) and education ( P = 0.412) did not significantly differ between groups. Mini-Mental State Examination score was significantly lower in the EOAD group (14.32 ± 6.74 vs 18.67 ± 7.20, P = 0.004). β-Amyloid deposition did not significantly differ between groups. Glucose metabolism in the frontal, parietal, precuneus, temporal, occipital lobe, and supramarginal and angular gyri was significantly lower in the EOAD group (n = 49) than in the LOAD group (n = 44). In voxel-based morphometry analysis, right posterior cingulate/precuneus atrophy was more obvious in the EOAD ( P < 0.001), although no voxel survived family-wise error correction. Tau deposition in the precuneus, parietal lobe, and angular, supramarginal, and right middle frontal gyri was significantly higher in the EOAD group (n = 18) than in the LOAD group (n = 13). CONCLUSIONS Multiprobe PET/MRI showed that tau burden and neuronal damage are more severe in EOAD than in LOAD. Multiprobe PET/MRI may be useful to assess the pathologic characteristics of EOAD.
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Affiliation(s)
| | | | | | | | | | - Ying Su
- Departments of Neurology, Union Hospital, Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhihou Liang
- Departments of Neurology, Union Hospital, Medical College, Huazhong University of Science and Technology, Wuhan, China
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Amiez C, Sallet J, Giacometti C, Verstraete C, Gandaux C, Morel-Latour V, Meguerditchian A, Hadj-Bouziane F, Ben Hamed S, Hopkins WD, Procyk E, Wilson CRE, Petrides M. A revised perspective on the evolution of the lateral frontal cortex in primates. SCIENCE ADVANCES 2023; 9:eadf9445. [PMID: 37205762 DOI: 10.1126/sciadv.adf9445] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 04/14/2023] [Indexed: 05/21/2023]
Abstract
Detailed neuroscientific data from macaque monkeys have been essential in advancing understanding of human frontal cortex function, particularly for regions of frontal cortex without homologs in other model species. However, precise transfer of this knowledge for direct use in human applications requires an understanding of monkey to hominid homologies, particularly whether and how sulci and cytoarchitectonic regions in the frontal cortex of macaques relate to those in hominids. We combine sulcal pattern analysis with resting-state functional magnetic resonance imaging and cytoarchitectonic analysis to show that old-world monkey brains have the same principles of organization as hominid brains, with the notable exception of sulci in the frontopolar cortex. This essential comparative framework provides insights into primate brain evolution and a key tool to drive translation from invasive research in monkeys to human applications.
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Affiliation(s)
- Céline Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Jérôme Sallet
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
- Wellcome Integrative Neuroimaging Centre, Department of Experimental Psychology, University of Oxford, Oxford OX1 3SR, UK
| | - Camille Giacometti
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Charles Verstraete
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Clémence Gandaux
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Valentine Morel-Latour
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Adrien Meguerditchian
- Laboratoire de Psychologie Cognitive, UMR7290, Université Aix-Marseille, CNRS, 13331 Marseille, France
- Station de Primatologie CNRS, UPS846, 13790 Rousset, France
- Brain and Language Research Institute, Université Aix-Marseille, CNRS, 13604 Aix-en-Provence, France
| | - Fadila Hadj-Bouziane
- Integrative Multisensory Perception Action and Cognition Team (ImpAct), INSERM U1028, CNRS UMR5292, Lyon Neuroscience Research Center (CRNL), Lyon, France; University of Lyon 1, Lyon, France
| | - Suliann Ben Hamed
- Institut des Sciences Cognitives Marc Jeannerod, UMR5229, CNRS-Université Claude Bernard Lyon I, Bron, France
| | - William D Hopkins
- Department of Comparative Medicine, University of Texas MD Anderson Cancer Center, Bastrop, TX, 78602, USA
| | - Emmanuel Procyk
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Charles R E Wilson
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, 69500 Bron, France
| | - Michael Petrides
- Department of Neurology and Neurosurgery and Department of Psychology, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
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6
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Kadohisa M, Kusunoki M, Mitchell DJ, Bhatia C, Buckley MJ, Duncan J. Frontal and temporal coding dynamics in successive steps of complex behavior. Neuron 2023; 111:430-443.e3. [PMID: 36473483 DOI: 10.1016/j.neuron.2022.11.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 06/21/2022] [Accepted: 11/03/2022] [Indexed: 12/12/2022]
Abstract
Ventrolateral prefrontal cortex (vlPFC), dorsolateral prefrontal cortex (dlPFC), and temporal cortex (TE) all contribute to visual decision-making. Accumulating evidence suggests that vlPFC may play a central role in multiple cognitive operations, perhaps resembling domain-general regions of the human frontal lobe. We trained monkeys in a task calling for learning, retrieval, and spatial selection of rewarded target objects. Recordings of neural activity covered large areas of vlPFC, dlPFC, and TE. Results suggested a central role for vlPFC in each cognitive operation with strong coding of each task feature, while only location was strongly coded in dlPFC and current object identity in TE. During target selection, target location was communicated first from vlPFC to dlPFC, followed by extensive mutual support. In vlPFC, stimulus identities were independently coded in different task operations. The results suggest a central role for the inferior frontal convexity in controlling successive operations of a complex, multi-step task.
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Affiliation(s)
- Mikiko Kadohisa
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK; Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Makoto Kusunoki
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK; Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - Daniel J Mitchell
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK
| | - Cheshta Bhatia
- Department of Organismic and Evolutionary Biology, Harvard University, 26 Oxford St, Cambridge, MA 02138, USA
| | - Mark J Buckley
- Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
| | - John Duncan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK; Department of Experimental Psychology, University of Oxford, Anna Watts Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK.
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7
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Janssen M, LeWarne C, Burk D, Averbeck BB. Hierarchical Reinforcement Learning, Sequential Behavior, and the Dorsal Frontostriatal System. J Cogn Neurosci 2022; 34:1307-1325. [PMID: 35579977 PMCID: PMC9274316 DOI: 10.1162/jocn_a_01869] [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] [Indexed: 11/04/2022]
Abstract
To effectively behave within ever-changing environments, biological agents must learn and act at varying hierarchical levels such that a complex task may be broken down into more tractable subtasks. Hierarchical reinforcement learning (HRL) is a computational framework that provides an understanding of this process by combining sequential actions into one temporally extended unit called an option. However, there are still open questions within the HRL framework, including how options are formed and how HRL mechanisms might be realized within the brain. In this review, we propose that the existing human motor sequence literature can aid in understanding both of these questions. We give specific emphasis to visuomotor sequence learning tasks such as the discrete sequence production task and the M × N (M steps × N sets) task to understand how hierarchical learning and behavior manifest across sequential action tasks as well as how the dorsal cortical-subcortical circuitry could support this kind of behavior. This review highlights how motor chunks within a motor sequence can function as HRL options. Furthermore, we aim to merge findings from motor sequence literature with reinforcement learning perspectives to inform experimental design in each respective subfield.
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Affiliation(s)
| | | | - Diana Burk
- National Institute of Mental Health, Bethesda, MD
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8
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Klein-Flügge MC, Bongioanni A, Rushworth MFS. Medial and orbital frontal cortex in decision-making and flexible behavior. Neuron 2022; 110:2743-2770. [PMID: 35705077 DOI: 10.1016/j.neuron.2022.05.022] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 05/17/2022] [Accepted: 05/19/2022] [Indexed: 11/15/2022]
Abstract
The medial frontal cortex and adjacent orbitofrontal cortex have been the focus of investigations of decision-making, behavioral flexibility, and social behavior. We review studies conducted in humans, macaques, and rodents and argue that several regions with different functional roles can be identified in the dorsal anterior cingulate cortex, perigenual anterior cingulate cortex, anterior medial frontal cortex, ventromedial prefrontal cortex, and medial and lateral parts of the orbitofrontal cortex. There is increasing evidence that the manner in which these areas represent the value of the environment and specific choices is different from subcortical brain regions and more complex than previously thought. Although activity in some regions reflects distributions of reward and opportunities across the environment, in other cases, activity reflects the structural relationships between features of the environment that animals can use to infer what decision to take even if they have not encountered identical opportunities in the past.
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Affiliation(s)
- Miriam C Klein-Flügge
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK; Department of Psychiatry, University of Oxford, Warneford Lane, Headington, Oxford OX3 7JX, UK.
| | - Alessandro Bongioanni
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK
| | - Matthew F S Rushworth
- Wellcome Centre for Integrative Neuroimaging (WIN), Department of Experimental Psychology, University of Oxford, Tinsley Building, Mansfield Road, Oxford OX1 3TA, UK; Wellcome Centre for Integrative Neuroimaging (WIN), Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Nuffield Department of Clinical Neurosciences, Level 6, West Wing, John Radcliffe Hospital, Oxford OX3 9DU, UK
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9
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Xu R, Bichot NP, Takahashi A, Desimone R. The cortical connectome of primate lateral prefrontal cortex. Neuron 2022; 110:312-327.e7. [PMID: 34739817 PMCID: PMC8776613 DOI: 10.1016/j.neuron.2021.10.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 09/09/2021] [Accepted: 10/11/2021] [Indexed: 01/21/2023]
Abstract
The lateral prefrontal cortex (LPFC) of primates plays an important role in executive control, but how it interacts with the rest of the cortex remains unclear. To address this, we densely mapped the cortical connectome of LPFC, using electrical microstimulation combined with functional MRI (EM-fMRI). We found isomorphic mappings between LPFC and five major processing domains composing most of the cerebral cortex except early sensory and motor areas. An LPFC grid of ∼200 stimulation sites topographically mapped to separate grids of activation sites in the five domains, coarsely resembling how the visual cortex maps the retina. The temporal and parietal maps largely overlapped in LPFC, suggesting topographically organized convergence of the ventral and dorsal streams, and the other maps overlapped at least partially. Thus, the LPFC contains overlapping, millimeter-scale maps that mirror the organization of major cortical processing domains, supporting LPFC's role in coordinating activity within and across these domains.
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Affiliation(s)
- Rui Xu
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Narcisse P Bichot
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Atsushi Takahashi
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Robert Desimone
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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10
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Tang H, Riley MR, Singh B, Qi XL, Blake DT, Constantinidis C. Prefrontal cortical plasticity during learning of cognitive tasks. Nat Commun 2022; 13:90. [PMID: 35013248 PMCID: PMC8748623 DOI: 10.1038/s41467-021-27695-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 11/30/2021] [Indexed: 11/30/2022] Open
Abstract
Training in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands. In every training phase, changes induced by the actively learned task were also observed in a control task, which remained the same across the training period. Our results reveal how learning to perform cognitive tasks induces plasticity of prefrontal cortical activity, and how activity changes may generalize between tasks.
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Affiliation(s)
- Hua Tang
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
- Center for Neuropsychiatric Diseases, Institute of Life Science, Nanchang University, Nanchang, 330031, Jiangxi, China
- Laboratory of Neuropsychology, National Institutes of Mental Health, NIH, Bethesda, MD, 20892, USA
| | - Mitchell R Riley
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Balbir Singh
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
| | - Xue-Lian Qi
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - David T Blake
- Department of Neuroscience and Regenerative Medicine, Medical College of Georgia, Augusta University, Augusta, GA, 30912, USA
| | - Christos Constantinidis
- Department of Neurobiology & Anatomy, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA.
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
- Neuroscience Program, Vanderbilt University, Nashville, TN, 37235, USA.
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
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11
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Differential coding of goals and actions in ventral and dorsal corticostriatal circuits during goal-directed behavior. Cell Rep 2022; 38:110198. [PMID: 34986350 PMCID: PMC9608360 DOI: 10.1016/j.celrep.2021.110198] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/08/2021] [Accepted: 12/10/2021] [Indexed: 02/04/2023] Open
Abstract
Goal-directed behavior requires identifying objects in the environment that can satisfy internal needs and executing actions to obtain those objects. The current study examines ventral and dorsal corticostriatal circuits that support complementary aspects of goal-directed behavior. We analyze activity from the amygdala, ventral striatum, orbitofrontal cortex, and lateral prefrontal cortex (LPFC) while monkeys perform a three-armed bandit task. Information about chosen stimuli and their value is primarily encoded in the amygdala, ventral striatum, and orbitofrontal cortex, while the spatial information is primarily encoded in the LPFC. Before the options are presented, information about the to-be-chosen stimulus is represented in the amygdala, ventral striatum, and orbitofrontal cortex; at the time of choice, the information is passed to the LPFC to direct a saccade. Thus, learned value information specifying behavioral goals is maintained throughout the ventral corticostriatal circuit, and it is routed through the dorsal circuit at the time actions are selected.
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12
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Engel TA, Schölvinck ML, Lewis CM. The diversity and specificity of functional connectivity across spatial and temporal scales. Neuroimage 2021; 245:118692. [PMID: 34751153 PMCID: PMC9531047 DOI: 10.1016/j.neuroimage.2021.118692] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/27/2021] [Accepted: 10/28/2021] [Indexed: 01/01/2023] Open
Abstract
Macroscopic neuroimaging modalities in humans have revealed the organization of brain-wide activity into distributed functional networks that re-organize according to behavioral demands. However, the inherent coarse-graining of macroscopic measurements conceals the diversity and specificity in responses and connectivity of many individual neurons contained in each local region. New invasive approaches in animals enable recording and manipulating neural activity at meso- and microscale resolution, with cell-type specificity and temporal precision down to milliseconds. Determining how brain-wide activity patterns emerge from interactions across spatial and temporal scales will allow us to identify the key circuit mechanisms contributing to global brain states and how the dynamic activity of these states enables adaptive behavior.
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Affiliation(s)
- Tatiana A Engel
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, United States.
| | - Marieke L Schölvinck
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main, Germany.
| | - Christopher M Lewis
- Laboratory of Neural Circuit Dynamics, Brain Research Institute, University of Zürich, Zürich 8057, Switzerland.
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13
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Maisson DJN, Cash-Padgett TV, Wang MZ, Hayden BY, Heilbronner SR, Zimmermann J. Choice-relevant information transformation along a ventrodorsal axis in the medial prefrontal cortex. Nat Commun 2021; 12:4830. [PMID: 34376663 PMCID: PMC8355277 DOI: 10.1038/s41467-021-25219-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Accepted: 07/27/2021] [Indexed: 11/17/2022] Open
Abstract
Choice-relevant brain regions in prefrontal cortex may progressively transform information about options into choices. Here, we examine responses of neurons in four regions of the medial prefrontal cortex as macaques performed two-option risky choices. All four regions encode economic variables in similar proportions and show similar putative signatures of key choice-related computations. We provide evidence to support a gradient of function that proceeds from areas 14 to 25 to 32 to 24. Specifically, we show that decodability of twelve distinct task variables increases along that path, consistent with the idea that regions that are higher in the anatomical hierarchy make choice-relevant variables more separable. We also show progressively longer intrinsic timescales in the same series. Together these results highlight the importance of the medial wall in choice, endorse a specific gradient-based organization, and argue against a modular functional neuroanatomy of choice.
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Affiliation(s)
- David J-N Maisson
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA.
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA.
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
| | - Tyler V Cash-Padgett
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Maya Z Wang
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Benjamin Y Hayden
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
- Center for Neuroengineering, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
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