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Wilken S, Böttcher A, Adelhöfer N, Raab M, Beste C, Hoffmann S. Neural oscillations guiding action during effects imagery. Behav Brain Res 2024; 469:115063. [PMID: 38777262 DOI: 10.1016/j.bbr.2024.115063] [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: 12/19/2023] [Revised: 05/02/2024] [Accepted: 05/18/2024] [Indexed: 05/25/2024]
Abstract
Goal-directed acting requires the integration of sensory information but can also be performed without direct sensory input. Examples of this can be found in sports and can be conceptualized by feedforward processes. There is, however, still a lack of understanding of the temporal neural dynamics and neuroanatomical structures involved in such processes. In the current study, we used EEG beamforming methods and examined 37 healthy participants in two well-controlled experiments varying the necessity of anticipatory processes during goal-directed action. We found that alpha and beta activity in the medial and posterior cingulate cortex enabled feedforward predictions about the position of an object based on the latest sensorimotor state. On this basis, theta band activity seems more related to sensorimotor representations, while beta band activity would be more involved in setting up the structure of the neural representations themselves. Alpha band activity in sensory cortices reflects an intensified gating of the anticipated perceptual consequences of the to-be-executed action. Together, the findings indicate that goal-directed acting through the anticipation of the predicted state of an effector is based on accompanying processes in multiple frequency bands in midcingulate and sensory brain regions.
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Affiliation(s)
- Saskia Wilken
- General Psychology: Judgment, Decision Making, & Action, Institute of Psychology, University of Hagen, Hagen, Germany
| | - Adriana Böttcher
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany; University Neuropsychology Center, Faculty of Medicine, TU Dresden, Germany
| | - Nico Adelhöfer
- Donders Institute of Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Markus Raab
- Performance Psychology, Institute of Psychology, German Sport University Cologne, Cologne, Germany; School of Applied Sciences, London South Bank University, London, UK
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Dresden, Germany; University Neuropsychology Center, Faculty of Medicine, TU Dresden, Germany; Shandong Normal University, Jinan, PR China
| | - Sven Hoffmann
- General Psychology: Judgment, Decision Making, & Action, Institute of Psychology, University of Hagen, Hagen, Germany.
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2
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Alejandro RJ, Holroyd CB. Hierarchical control over foraging behavior by anterior cingulate cortex. Neurosci Biobehav Rev 2024; 160:105623. [PMID: 38490499 DOI: 10.1016/j.neubiorev.2024.105623] [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: 11/03/2023] [Revised: 02/14/2024] [Accepted: 03/13/2024] [Indexed: 03/17/2024]
Abstract
Foraging is a natural behavior that involves making sequential decisions to maximize rewards while minimizing the costs incurred when doing so. The prevalence of foraging across species suggests that a common brain computation underlies its implementation. Although anterior cingulate cortex is believed to contribute to foraging behavior, its specific role has been contentious, with predominant theories arguing either that it encodes environmental value or choice difficulty. Additionally, recent attempts to characterize foraging have taken place within the reinforcement learning framework, with increasingly complex models scaling with task complexity. Here we review reinforcement learning foraging models, highlighting the hierarchical structure of many foraging problems. We extend this literature by proposing that ACC guides foraging according to principles of model-based hierarchical reinforcement learning. This idea holds that ACC function is organized hierarchically along a rostral-caudal gradient, with rostral structures monitoring the status and completion of high-level task goals (like finding food), and midcingulate structures overseeing the execution of task options (subgoals, like harvesting fruit) and lower-level actions (such as grabbing an apple).
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Affiliation(s)
| | - Clay B Holroyd
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
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3
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Pscherer C, Wendiggensen P, Mückschel M, Bluschke A, Beste C. Alpha and theta band activity share information relevant to proactive and reactive control during conflict-modulated response inhibition. Hum Brain Mapp 2023; 44:5936-5952. [PMID: 37728249 PMCID: PMC10619371 DOI: 10.1002/hbm.26486] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 07/28/2023] [Accepted: 09/04/2023] [Indexed: 09/21/2023] Open
Abstract
Response inhibition is an important instance of cognitive control and can be complicated by perceptual conflict. The neurophysiological mechanisms underlying these processes are still not understood. Especially the relationship between neural processes directly preceding cognitive control (proactive control) and processes underlying cognitive control (reactive control) has not been examined although there should be close links. In the current study, we investigate these aspects in a sample of N = 50 healthy adults. Time-frequency and beamforming approaches were applied to analyze the interrelation of brain states before (pre-trial) and during (within-trial) cognitive control. The behavioral data replicate a perceptual conflict-dependent modulation of response inhibition. During the pre-trial period, insular, inferior frontal, superior temporal, and precentral alpha activity was positively correlated with theta activity in the same regions and the superior frontal gyrus. Additionally, participants with a stronger pre-trial alpha activity in the primary motor cortex showed a stronger (within-trial) conflict effect in the theta band in the primary motor cortex. This theta conflict effect was further related to a stronger theta conflict effect in the midcingulate cortex until the end of the trial. The temporal cascade of these processes suggests that successful proactive preparation (anticipatory information gating) entails a stronger reactive processing of the conflicting stimulus information likely resulting in a realization of the need to adapt the current action plan. The results indicate that theta and alpha band activity share and transfer aspects of information when it comes to the interrelationship between proactive and reactive control during conflict-modulated motor inhibition.
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Affiliation(s)
- Charlotte Pscherer
- Cognitive Neurophysiology, Department of Child and Adolescent PsychiatryFaculty of Medicine of the TU DresdenDresdenGermany
- University Neuropsychology CenterFaculty of Medicine, TU DresdenDresdenGermany
| | - Paul Wendiggensen
- Cognitive Neurophysiology, Department of Child and Adolescent PsychiatryFaculty of Medicine of the TU DresdenDresdenGermany
- University Neuropsychology CenterFaculty of Medicine, TU DresdenDresdenGermany
| | - Moritz Mückschel
- Cognitive Neurophysiology, Department of Child and Adolescent PsychiatryFaculty of Medicine of the TU DresdenDresdenGermany
- University Neuropsychology CenterFaculty of Medicine, TU DresdenDresdenGermany
| | - Annet Bluschke
- Cognitive Neurophysiology, Department of Child and Adolescent PsychiatryFaculty of Medicine of the TU DresdenDresdenGermany
- University Neuropsychology CenterFaculty of Medicine, TU DresdenDresdenGermany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent PsychiatryFaculty of Medicine of the TU DresdenDresdenGermany
- University Neuropsychology CenterFaculty of Medicine, TU DresdenDresdenGermany
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4
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Moss ME, Mayr U. What's so hard about hierarchical control? Pinpointing processing constraints within cue-based and serial-order control structures. Cogn Psychol 2023; 144:101582. [PMID: 37352807 DOI: 10.1016/j.cogpsych.2023.101582] [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: 09/15/2022] [Revised: 04/04/2023] [Accepted: 06/06/2023] [Indexed: 06/25/2023]
Abstract
Most task spaces require a hierarchical structure, where decisions on one level are contingent on previous decisions made on one or more higher levels. While it is a truism that increasing the number of hierarchical levels makes it harder to solve a given task, the exact nature of this "number-of-levels" effect is not clear. On the one hand, processing costs might be strictly "local," incurred only when higher-level settings need to be updated, while otherwise lower-level decisions are insulated from the presence of higher-level settings (local updating costs with ballistic control). On the other hand, maintaining and integrating more complex hierarchical structures could require overall greater representational resources, negatively affecting each individual decision within the represented task space (global integration/maintenance costs). Further, navigation through hierarchical structures can be guided either through prompts in the environment (cue-based), or through sequential plans (serial-order based), with potentially distinct maintenance and updating demands. In two experiments, we assessed performance as a function of hierarchical level and format (serial-order vs. cue-based). Model comparisons showed that the pattern of costs in the serial-order format was consistent with a global maintenance/integration account. In contrast, in the cue-based format, costs arose at updating points and when one additional relevant level beyond the current decision was relevant, while additional levels produced no further costs. This overall constellation of costs can be explained by assuming that each decision requires checking the immediately relevant higher-level context for that decision. For cue-based control, this context involves the "next-level-up" rule, whereas in the serial-order format, each trial requires updating of the current position within the sequence, which in turn requires integration across all relevant hierarchical levels.
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Affiliation(s)
| | - Ulrich Mayr
- University of Oregon, Eugene, OR, United States.
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5
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Zeng J, You L, Sheng H, Luo Y, Yang X. The differential neural substrates for reward choice under gain-loss contexts and risk in alcohol use disorder: Evidence from a voxel-based meta-analysis. Drug Alcohol Depend 2023; 248:109912. [PMID: 37182355 DOI: 10.1016/j.drugalcdep.2023.109912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 04/15/2023] [Accepted: 04/30/2023] [Indexed: 05/16/2023]
Abstract
BACKGROUND Making a risky decision is a complex process that involves the evaluation of both the values of the options and the associated risk level; this process is distinct from reward processing in gain versus loss contexts. Although disrupted reward processing in mesolimbic dopamine circuitry is suggested to underlie pathological incentive processing in patients with alcohol use disorder (AUD), the differential neural processes subserving these motivational tendencies for risk situations or gain/loss choices in decision-making have not been identified. METHODS To examine the common or distinct neural mechanisms in the evaluation of risk versus outcomes for AUD, we conducted two separate coordinate-based meta-analyses of functional neuroimaging studies by using Seed-Based d Mapping software to evaluate 13 studies investigating gain and loss processing and 10 studies investigating risky decision-making. RESULTS During gain and loss processing, relative to healthy controls, AUD patients showed reduced activation in the mesocortical-limbic circuit, including the orbital prefrontal cortex (OFC), dorsal striatum, insula, hippocampus, cerebellum, cuneus cortex and superior temporal gyrus, but hyperactivation in the inferior temporal gyrus and paracentral lobule (extending to the middle cingulate cortex (MCC) and precuneus). During decision-making under risk, AUD patients exhibited hypoactivity of the prefrontal and cingulate cortices, including the posterior cingulate cortex (extending to the MCC), middle frontal gyrus, medial prefrontal cortex, dorsolateral prefrontal cortex, OFC and anterior cingulate cortex. CONCLUSIONS Our results extend existing neurological evidence by showing that a reduced response in the mesocortical-limbic circuit is found in gain versus loss processing, with decreased responsivity in cortical regions in risk decision-making. Our results implicate dissociable neural circuit responses for gain-loss processing and risk decision-making, which contribute to a better understanding of the pathophysiological mechanism underlying nondrug incentive and risk processing in individuals with AUD.
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Affiliation(s)
- Jianguang Zeng
- School of Economics and Business Administration, Chongqing University, Chongqing, China
| | - Lantao You
- School of Economics and Business Administration, Chongqing University, Chongqing, China
| | - Haoxuan Sheng
- School of Public Policy and Administration, Chongqing University, Chongqing, China
| | - Ya Luo
- Department of Psychiatry, State Key Lab of Biotherapy, West China Hospital of Sichuan University, Chengdu, China
| | - Xun Yang
- School of Public Policy and Administration, Chongqing University, Chongqing, China.
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6
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Sullivan M, Fernandez-Aranda F, Camacho-Barcia L, Harkin A, Macrì S, Mora-Maltas B, Jiménez-Murcia S, O'Leary A, Ottomana AM, Presta M, Slattery D, Scholtz S, Glennon JC. Insulin and Disorders of Behavioural Flexibility. Neurosci Biobehav Rev 2023; 150:105169. [PMID: 37059405 DOI: 10.1016/j.neubiorev.2023.105169] [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: 12/30/2022] [Revised: 04/03/2023] [Accepted: 04/10/2023] [Indexed: 04/16/2023]
Abstract
Behavioural inflexibility is a symptom of neuropsychiatric and neurodegenerative disorders such as Obsessive-Compulsive Disorder, Autism Spectrum Disorder and Alzheimer's Disease, encompassing the maintenance of a behaviour even when no longer appropriate. Recent evidence suggests that insulin signalling has roles apart from its regulation of peripheral metabolism and mediates behaviourally-relevant central nervous system (CNS) functions including behavioural flexibility. Indeed, insulin resistance is reported to generate anxious, perseverative phenotypes in animal models, with the Type 2 diabetes medication metformin proving to be beneficial for disorders including Alzheimer's Disease. Structural and functional neuroimaging studies of Type 2 diabetes patients have highlighted aberrant connectivity in regions governing salience detection, attention, inhibition and memory. As currently available therapeutic strategies feature high rates of resistance, there is an urgent need to better understand the complex aetiology of behaviour and develop improved therapeutics. In this review, we explore the circuitry underlying behavioural flexibility, changes in Type 2 diabetes, the role of insulin in CNS outcomes and mechanisms of insulin involvement across disorders of behavioural inflexibility.
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Affiliation(s)
- Mairéad Sullivan
- Conway Institute of Biomedical and Biomolecular Research, School of Medicine, University College Dublin, Dublin, Ireland.
| | - Fernando Fernandez-Aranda
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain; Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Program, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Barcelona, Spain; Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Lucía Camacho-Barcia
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain; Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Program, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Barcelona, Spain
| | - Andrew Harkin
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Ireland
| | - Simone Macrì
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, 00161 Rome, Italy
| | - Bernat Mora-Maltas
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain; Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Program, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Susana Jiménez-Murcia
- Department of Psychiatry, University Hospital of Bellvitge, Barcelona, Spain; Psychoneurobiology of Eating and Addictive Behaviors Group, Neurosciences Program, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBER Fisiopatología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Barcelona, Spain; Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
| | - Aet O'Leary
- University Hospital Frankfurt, Frankfurt, Germany
| | - Angela Maria Ottomana
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, 00161 Rome, Italy; Neuroscience Unit, Department of Medicine, University of Parma, 43100 Parma, Italy
| | - Martina Presta
- Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, 00161 Rome, Italy; Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
| | | | | | - Jeffrey C Glennon
- Conway Institute of Biomedical and Biomolecular Research, School of Medicine, University College Dublin, Dublin, Ireland
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7
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Kajimura S, Hoshino T, Murayama K. Stimulus-specific random effects inflate false-positive classification accuracy in multivariate-voxel-pattern-analysis: A solution with generalized mixed-effects modelling. Neuroimage 2023; 269:119901. [PMID: 36706939 DOI: 10.1016/j.neuroimage.2023.119901] [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: 08/20/2022] [Revised: 11/28/2022] [Accepted: 01/23/2023] [Indexed: 01/25/2023] Open
Abstract
When conducting multivariate-voxel pattern analysis (MVPA), researchers typically compute the average accuracy for each subject and statistically test if the average accuracy is different from the chance level across subjects (by-subject analysis). We argue that this traditional by-subject analysis leads to inflated Type-1 error rates, regardless of the type of machine learning method used (e.g., support vector machine). This is because by-subject analysis does not consider the variance attributed to the idiosyncratic features of the stimuli that have a common influence on all subjects (i.e., the random stimulus effect). As a solution, we proposed the use of generalized linear mixed-effects modelling to evaluate average accuracy. This method only requires post-classification data (i.e., it does not consider the type of classification methods used) and is easily implemented in the analysis pipeline with common statistical software (SPSS, R, Python, etc.). Using both statistical simulation and real fMRI data analysis, we demonstrated that the traditional by-subject method indeed increases Type-1 error rates to a considerable degree, while generalized mixed-effects modelling that incorporates random stimulus effects can indeed maintain the nominal Type-1 error rates.
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Affiliation(s)
- Shogo Kajimura
- Faculty of Information and Human Science, Kyoto Institute of Technology, Matsugasakihashigami-cho, Sakyo-ku, Kyoto-shi, Kyoto 606-8585, Japan.
| | | | - Kou Murayama
- Hector Research Institute of Education Sciences and Psychology, University of Tübingen, Germany; School of Psychology and Clinical Language Sciences, University of Reading, UK
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8
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Stoyanov D, Khorev V, Paunova R, Kandilarova S, Simeonova D, Badarin A, Hramov A, Kurkin S. Resting-State Functional Connectivity Impairment in Patients with Major Depressive Episode. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:14045. [PMID: 36360924 PMCID: PMC9656256 DOI: 10.3390/ijerph192114045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/14/2022] [Accepted: 10/25/2022] [Indexed: 06/16/2023]
Abstract
AIM This study aims to develop new approaches to characterize brain networks to potentially contribute to a better understanding of mechanisms involved in depression. METHOD AND SUBJECTS We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed investigating functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were developed at a functional network level, using a false discovery rate method. Linear discriminant analysis was used to differentiate between the two groups. RESULTS AND DISCUSSION Significant differences in functional connectivity (FC) between depressed patients vs. healthy controls was demonstrated, with brain regions including the lingual gyrus, cerebellum, midcingulate cortex and thalamus more prominent in healthy subjects as compared to depression where the orbitofrontal cortex emerged as a key node. Linear discriminant analysis demonstrated that full-connectivity matrices were the most precise in differentiating between depression vs. health subjects. CONCLUSION The study provides supportive evidence for impaired functional connectivity networks in MDE patients.
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Affiliation(s)
- Drozdstoy Stoyanov
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Vladimir Khorev
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
| | - Rositsa Paunova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Denitsa Simeonova
- Department of Psychiatry and Medical Psychology, Research Institute, Medical University Plovdiv, 4002 Plovdiv, Bulgaria
| | - Artem Badarin
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
| | - Alexander Hramov
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
| | - Semen Kurkin
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, 236041 Kaliningrad, Russia
- Neuroscience Research Institute, Samara State Medical University, 443001 Samara, Russia
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9
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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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10
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Zhang X, Qiu Y, Li J, Jia C, Liao J, Chen K, Qiu L, Yuan Z, Huang R. Neural correlates of transitive inference: An SDM meta-analysis on 32 fMRI studies. Neuroimage 2022; 258:119354. [PMID: 35659997 DOI: 10.1016/j.neuroimage.2022.119354] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 05/02/2022] [Accepted: 05/31/2022] [Indexed: 11/28/2022] Open
Abstract
Transitive inference (TI) is a critical capacity involving the integration of relevant information into prior knowledge structure for drawing novel inferences on unobserved relationships. To date, the neural correlates of TI remain unclear due to the small sample size and heterogeneity of various experimental tasks from individual studies. Here, the meta-analysis on 32 fMRI studies was performed to detect brain activation patterns of TI and its three paradigms (spatial inference, hierarchical inference, and associative inference). We found the hippocampus, prefrontal cortex (PFC), putamen, posterior parietal cortex (PPC), retrosplenial cortex (RSC), supplementary motor area (SMA), precentral gyrus (PreCG), and median cingulate cortex (MCC) were engaged in TI. Specifically, the RSC was implicated in the associative inference, whereas PPC, SMA, PreCG, and MCC were implicated in the hierarchical inference. In addition, the hierarchical inference and associative inference both evoked activation in the hippocampus, medial PFC, and PCC. Although the meta-analysis on spatial inference did not generate a reliable result due to insufficient amount of investigations, the present work still offers a new insight for better understanding the neural basis underlying TI.
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Affiliation(s)
- Xiaoying Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Yidan Qiu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Jinhui Li
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Chuchu Jia
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Jiajun Liao
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Kemeng Chen
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Lixin Qiu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Zhen Yuan
- Centre for Cognitive and Brain Sciences, University of Macau, Macau SAR, China.
| | - Ruiwang Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education; School of Psychology; Center for Studies of Psychological Application; Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China.
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11
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Theta oscillations shift towards optimal frequency for cognitive control. Nat Hum Behav 2022; 6:1000-1013. [PMID: 35449299 DOI: 10.1038/s41562-022-01335-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 03/10/2022] [Indexed: 12/19/2022]
Abstract
Cognitive control allows to flexibly guide behaviour in a complex and ever-changing environment. It is supported by theta band (4-7 Hz) neural oscillations that coordinate distant neural populations. However, little is known about the precise neural mechanisms permitting such flexible control. Most research has focused on theta amplitude, showing that it increases when control is needed, but a second essential aspect of theta oscillations, their peak frequency, has mostly been overlooked. Here, using computational modelling and behavioural and electrophysiological recordings, in three independent datasets, we show that theta oscillations adaptively shift towards optimal frequency depending on task demands. We provide evidence that theta frequency balances reliable set-up of task representation and gating of task-relevant sensory and motor information and that this frequency shift predicts behavioural performance. Our study presents a mechanism supporting flexible control and calls for a reevaluation of the mechanistic role of theta oscillations in adaptive behaviour.
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12
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Pondelis NJ, Moulton EA. Supraspinal Mechanisms Underlying Ocular Pain. Front Med (Lausanne) 2022; 8:768649. [PMID: 35211480 PMCID: PMC8862711 DOI: 10.3389/fmed.2021.768649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 12/27/2021] [Indexed: 12/04/2022] Open
Abstract
Supraspinal mechanisms of pain are increasingly understood to underlie neuropathic ocular conditions previously thought to be exclusively peripheral in nature. Isolating individual causes of centralized chronic conditions and differentiating them is critical to understanding the mechanisms underlying neuropathic eye pain and ultimately its treatment. Though few functional imaging studies have focused on the eye as an end-organ for the transduction of noxious stimuli, the brain networks related to pain processing have been extensively studied with functional neuroimaging over the past 20 years. This article will review the supraspinal mechanisms that underlie pain as they relate to the eye.
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Affiliation(s)
- Nicholas J Pondelis
- Brain and Eye Pain Imaging Lab, Pain and Affective Neuroscience Center, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
| | - Eric A Moulton
- Brain and Eye Pain Imaging Lab, Pain and Affective Neuroscience Center, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States.,Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, MA, United States
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13
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Rivas-Fernández MÁ, Lindín M, Díaz F, Zurrón M, Galdo-Álvarez S. Changes in brain activity related to episodic memory retrieval in adults with single domain amnestic mild cognitive impairment. Biol Psychol 2021; 166:108208. [PMID: 34688826 DOI: 10.1016/j.biopsycho.2021.108208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 10/12/2021] [Accepted: 10/13/2021] [Indexed: 11/27/2022]
Abstract
The present fMRI study aimed to characterize the performance and the brain activity changes related to episodic memory retrieval in adults with single domain aMCI (sdaMCI), relative to cognitively unimpaired adults. Participants performed an old/new recognition memory task with words while BOLD signal was acquired. The sdaMCI group showed lower hits (correct recognition of old words), lower ability to discriminate old and new words, higher errors and longer reaction times for hits. This group also displayed brain hypoactivation in left precuneus and the left midcingulate cortex during the successful recognition of old words. These changes in brain activity suggest the presence of neural dysregulations in brain regions involved during successful episodic memory retrieval. Moreover, hypoactivation in these brain areas discriminated both groups with moderate sensitivity and specificity values, suggesting that it might constitute a potential neurocognitive biomarker of sdaMCI.
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Affiliation(s)
- Miguel Ángel Rivas-Fernández
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Galicia, Spain
| | - Mónica Lindín
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Galicia, Spain.
| | - Fernando Díaz
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Galicia, Spain
| | - Montserrat Zurrón
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Galicia, Spain
| | - Santiago Galdo-Álvarez
- Laboratorio de Neurociencia Cognitiva, Departamento de Psicoloxía Clínica e Psicobioloxía, Facultade de Psicoloxía, Universidade de Santiago de Compostela, Galicia, Spain
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14
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Hunt LT, Daw ND, Kaanders P, MacIver MA, Mugan U, Procyk E, Redish AD, Russo E, Scholl J, Stachenfeld K, Wilson CRE, Kolling N. Formalizing planning and information search in naturalistic decision-making. Nat Neurosci 2021; 24:1051-1064. [PMID: 34155400 DOI: 10.1038/s41593-021-00866-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 03/23/2021] [Indexed: 02/05/2023]
Abstract
Decisions made by mammals and birds are often temporally extended. They require planning and sampling of decision-relevant information. Our understanding of such decision-making remains in its infancy compared with simpler, forced-choice paradigms. However, recent advances in algorithms supporting planning and information search provide a lens through which we can explain neural and behavioral data in these tasks. We review these advances to obtain a clearer understanding for why planning and curiosity originated in certain species but not others; how activity in the medial temporal lobe, prefrontal and cingulate cortices may support these behaviors; and how planning and information search may complement each other as means to improve future action selection.
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Affiliation(s)
- L T Hunt
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
| | - N D Daw
- Princeton Neuroscience Institute and Department of Psychology, Princeton University, Princeton, NJ, USA
| | - P Kaanders
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - M A MacIver
- Center for Robotics and Biosystems, Department of Neurobiology, Department of Biomedical Engineering, Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - U Mugan
- Center for Robotics and Biosystems, Department of Neurobiology, Department of Biomedical Engineering, Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA
| | - E Procyk
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Bron, France
| | - A D Redish
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - E Russo
- Department of Theoretical Neuroscience, Central Institute of Mental Health, Mannheim, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - J Scholl
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | - C R E Wilson
- Univ Lyon, Université Claude Bernard Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, Bron, France
| | - N Kolling
- Department of Psychiatry, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
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15
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Freund MC, Etzel JA, Braver TS. Neural Coding of Cognitive Control: The Representational Similarity Analysis Approach. Trends Cogn Sci 2021; 25:622-638. [PMID: 33895065 PMCID: PMC8279005 DOI: 10.1016/j.tics.2021.03.011] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 03/17/2021] [Accepted: 03/18/2021] [Indexed: 01/07/2023]
Abstract
Cognitive control relies on distributed and potentially high-dimensional frontoparietal task representations. Yet, the classical cognitive neuroscience approach in this domain has focused on aggregating and contrasting neural measures - either via univariate or multivariate methods - along highly abstracted, 1D factors (e.g., Stroop congruency). Here, we present representational similarity analysis (RSA) as a complementary approach that can powerfully inform representational components of cognitive control theories. We review several exemplary uses of RSA in this regard. We further show that most classical paradigms, given their factorial structure, can be optimized for RSA with minimal modification. Our aim is to illustrate how RSA can be incorporated into cognitive control investigations to shed new light on old questions.
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Affiliation(s)
- Michael C Freund
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO 63130, USA
| | - Joset A Etzel
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO 63130, USA
| | - Todd S Braver
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, MO 63130, USA; Department of Radiology, Washington University in St Louis, School of Medicine, St Louis, MO 63110, USA; Department of Neuroscience, Washington University in St Louis, School of Medicine, St Louis, MO 63110, USA.
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16
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A Hierarchy of Functional States in Working Memory. J Neurosci 2021; 41:4461-4475. [PMID: 33888611 PMCID: PMC8152603 DOI: 10.1523/jneurosci.3104-20.2021] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 11/21/2022] Open
Abstract
Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requiring the prolonged maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for memories that were selected to guide the next decision from states coding for concurrently held memories that were maintained for later use, and to examine how these states contribute to WM-based decisions. Selected memories were encoded in a functionally active state. This state was reflected in spontaneous brain activity during the delay period, closely tracked moment-to-moment fluctuations in the quality of evidence integration, and also predicted when memories would interfere with each other. In contrast, concurrently held memories were encoded in a functionally latent state. This state was reflected only in stimulus-evoked brain activity, tracked memory precision at longer timescales, but did not engage with ongoing decision dynamics. Intriguingly, the two functional states were highly flexible, as priority could be dynamically shifted back and forth between memories without degrading their precision. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision circuits to guide flexible behavior.SIGNIFICANCE STATEMENT Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how.
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17
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Shahnazian D, Senoussi M, Krebs RM, Verguts T, Holroyd CB. Neural Representations of Task Context and Temporal Order During Action Sequence Execution. Top Cogn Sci 2021; 14:223-240. [PMID: 33836116 DOI: 10.1111/tops.12533] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 03/29/2021] [Accepted: 03/29/2021] [Indexed: 12/22/2022]
Abstract
Routine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded the blood-oxygen level dependent (BOLD) response in a newly developed coffee-tea making task. The task involves the execution of four action sequences that each comprise six consecutive decision states, which allows for examining the maintenance of contextual and temporal information. Here, we report a reanalysis of this dataset using a data-driven approach, namely multivariate pattern analysis, that examines context-dependent neural activity across several predefined regions of interest. Results highlight involvement of the inferior-temporal gyrus and lateral prefrontal cortex in maintaining temporal and contextual information for the execution of hierarchically organized action sequences. Furthermore, temporal information seems to be more strongly encoded in areas over the left hemisphere.
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Affiliation(s)
| | | | - Ruth M Krebs
- Department of Experimental Psychology, Ghent University
| | - Tom Verguts
- Department of Experimental Psychology, Ghent University
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18
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Philiastides MG, Tu T, Sajda P. Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI. Annu Rev Neurosci 2021; 44:315-334. [PMID: 33761268 DOI: 10.1146/annurev-neuro-100220-093239] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Advances in the instrumentation and signal processing for simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) have enabled new ways to observe the spatiotemporal neural dynamics of the human brain. Central to the utility of EEG-fMRI neuroimaging systems are the methods for fusing the two data streams, with machine learning playing a key role. These methods can be dichotomized into those that are symmetric and asymmetric in terms of how the two modalities inform the fusion. Studies using these methods have shown that fusion yields new insights into brain function that are not possible when each modality is acquired separately. As technology improves and methods for fusion become more sophisticated, the future of EEG-fMRI for noninvasive measurement of brain dynamics includes mesoscale mapping at ultrahigh magnetic resonance fields, targeted perturbation-based neuroimaging, and using deep learning to uncover nonlinear representations that link the electrophysiological and hemodynamic measurements.
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Affiliation(s)
- Marios G Philiastides
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8AD, Scotland;
| | - Tao Tu
- Department of Biomedical Engineering, Columbia University, New York, NY 10027, USA
| | - Paul Sajda
- Departments of Biomedical Engineering, Electrical Engineering, and Radiology and the Data Science Institute, Columbia University, New York, NY 10027, USA;
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19
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Alexandre F. A global framework for a systemic view of brain modeling. Brain Inform 2021; 8:3. [PMID: 33591440 PMCID: PMC7886931 DOI: 10.1186/s40708-021-00126-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 02/05/2021] [Indexed: 11/23/2022] Open
Abstract
The brain is a complex system, due to the heterogeneity of its structure, the diversity of the functions in which it participates and to its reciprocal relationships with the body and the environment. A systemic description of the brain is presented here, as a contribution to developing a brain theory and as a general framework where specific models in computational neuroscience can be integrated and associated with global information flows and cognitive functions. In an enactive view, this framework integrates the fundamental organization of the brain in sensorimotor loops with the internal and the external worlds, answering four fundamental questions (what, why, where and how). Our survival-oriented definition of behavior gives a prominent role to pavlovian and instrumental conditioning, augmented during phylogeny by the specific contribution of other kinds of learning, related to semantic memory in the posterior cortex, episodic memory in the hippocampus and working memory in the frontal cortex. This framework highlights that responses can be prepared in different ways, from pavlovian reflexes and habitual behavior to deliberations for goal-directed planning and reasoning, and explains that these different kinds of responses coexist, collaborate and compete for the control of behavior. It also lays emphasis on the fact that cognition can be described as a dynamical system of interacting memories, some acting to provide information to others, to replace them when they are not efficient enough, or to help for their improvement. Describing the brain as an architecture of learning systems has also strong implications in Machine Learning. Our biologically informed view of pavlovian and instrumental conditioning can be very precious to revisit classical Reinforcement Learning and provide a basis to ensure really autonomous learning.
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Affiliation(s)
- Frederic Alexandre
- INRIA Bordeaux Sud-Ouest, Talence, France. .,Institute of Neurodegenerative Diseases, University of Bordeaux, CNRS UMR 5293, 146 rue Leo Saignat, 33076, Bordeaux, France. .,LaBRI, University of Bordeaux, Bordeaux INP, CNRS UMR 5800, Talence, France.
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20
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The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex. Trends Cogn Sci 2021; 25:316-329. [PMID: 33593641 DOI: 10.1016/j.tics.2021.01.008] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 01/17/2021] [Accepted: 01/19/2021] [Indexed: 12/26/2022]
Abstract
Despite continual debate for the past 30 years about the function of anterior cingulate cortex (ACC), its key contribution to neurocognition remains unknown. However, recent computational modeling work has provided insight into this question. Here we review computational models that illustrate three core principles of ACC function, related to hierarchy, world models, and cost. We also discuss four constraints on the neural implementation of these principles, related to modularity, binding, encoding, and learning and regulation. These observations suggest a role for ACC in hierarchical model-based hierarchical reinforcement learning (HMB-HRL), which instantiates a mechanism motivating the execution of high-level plans.
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21
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Delfin C, Ruzich E, Wallinius M, Björnsdotter M, Andiné P. Trait Disinhibition and NoGo Event-Related Potentials in Violent Mentally Disordered Offenders and Healthy Controls. Front Psychiatry 2020; 11:577491. [PMID: 33362599 PMCID: PMC7759527 DOI: 10.3389/fpsyt.2020.577491] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/17/2020] [Indexed: 12/21/2022] Open
Abstract
Trait disinhibition may function as a dispositional liability toward maladaptive behaviors relevant in the treatment of mentally disordered offenders (MDOs). Reduced amplitude and prolonged latency of the NoGo N2 and P3 event-related potentials have emerged as promising candidates for transdiagnostic, biobehavioral markers of trait disinhibition, yet no study has specifically investigated these two components in violent, inpatient MDOs. Here, we examined self-reported trait disinhibition, experimentally assessed response inhibition, and NoGo N2 and P3 amplitude and latency in male, violent MDOs (N = 27) and healthy controls (N = 20). MDOs had a higher degree of trait disinhibition, reduced NoGo P3 amplitude, and delayed NoGo P3 latency compared to controls. The reduced NoGo P3 amplitude and delayed NoGo P3 latency in MDOs may stem from deficits during monitoring or evaluation of behavior. NoGo P3 latency was associated with increased trait disinhibition in the whole sample, suggesting that trait disinhibition may be associated with reduced neural efficiency during later stages of outcome monitoring or evaluation. Findings for NoGo N2 amplitude and latency were small and non-robust. With several limitations in mind, this is the first study to demonstrate attenuated NoGo P3 amplitude and delayed NoGo P3 latency in violent, inpatient MDOs compared to healthy controls.
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Affiliation(s)
- Carl Delfin
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Research Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden
| | - Emily Ruzich
- MedTech West, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Märta Wallinius
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Research Department, Regional Forensic Psychiatric Clinic, Växjö, Sweden
- Lund Clinical Research on Externalizing and Developmental Psychopathology, Child and Adolescent Psychiatry, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Malin Björnsdotter
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Affective Psychiatry, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Peter Andiné
- Centre for Ethics, Law and Mental Health, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Forensic Psychiatric Clinic, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Forensic Psychiatry, National Board of Forensic Medicine, Gothenburg, Sweden
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22
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Hierarchical Representation of Multistep Tasks in Multiple-Demand and Default Mode Networks. J Neurosci 2020; 40:7724-7738. [PMID: 32868460 PMCID: PMC7531550 DOI: 10.1523/jneurosci.0594-20.2020] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/08/2020] [Accepted: 07/31/2020] [Indexed: 12/31/2022] Open
Abstract
Task episodes consist of sequences of steps that are performed to achieve a goal. We used fMRI to examine neural representation of task identity, component items, and sequential position, focusing on two major cortical systems—the multiple-demand (MD) and default mode networks (DMN). Human participants (20 males, 22 females) learned six tasks each consisting of four steps. Inside the scanner, participants were cued which task to perform and then sequentially identified the target item of each step in the correct order. Univariate time course analyses indicated that intra-episode progress was tracked by a tonically increasing global response, plus an increasing phasic step response specific to MD regions. Inter-episode boundaries evoked a widespread response at episode onset, plus a marked offset response specific to DMN regions. Representational similarity analysis (RSA) was used to examine representation of task identity and component steps. Both networks represented the content and position of individual steps, however the DMN preferentially represented task identity while the MD network preferentially represented step-level information. Thus, although both MD and DMN networks are sensitive to step-level and episode-level information in the context of hierarchical task performance, they exhibit dissociable profiles in terms of both temporal dynamics and representational content. The results suggest collaboration of multiple brain regions in control of multistep behavior, with MD regions particularly involved in processing the detail of individual steps, and DMN adding representation of broad task context. SIGNIFICANCE STATEMENT Achieving one's goals requires knowing what to do and when. Tasks are typically hierarchical, with smaller steps nested within overarching goals. For effective, flexible behavior, the brain must represent both levels. We contrast response time courses and information content of two major cortical systems—the multiple-demand (MD) and default mode networks (DMN)—during multistep task episodes. Both networks are sensitive to step-level and episode-level information, but with dissociable profiles. Intra-episode progress is tracked by tonically increasing global responses, plus MD-specific increasing phasic step responses. Inter-episode boundaries evoke widespread responses at episode onset, plus DMN-specific offset responses. Both networks represent content and position of individual steps; however, the DMN and MD networks favor task identity and step-level information, respectively.
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23
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Griffiths BJ, Mayhew SD, Mullinger KJ, Jorge J, Charest I, Wimber M, Hanslmayr S. Alpha/beta power decreases track the fidelity of stimulus-specific information. eLife 2019; 8:e49562. [PMID: 31782730 PMCID: PMC6904219 DOI: 10.7554/elife.49562] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 11/28/2019] [Indexed: 12/11/2022] Open
Abstract
Massed synchronised neuronal firing is detrimental to information processing. When networks of task-irrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, such synchronisation can contribute to alpha/beta (8-30 Hz) oscillations. Reducing the amplitude of these oscillations, therefore, may enhance information processing. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as post-stimulus alpha/beta power decreased, stimulus-specific information increased. Critically, we found this effect in three unique tasks: visual perception, auditory perception, and visual memory retrieval, indicating that this phenomenon transcends both stimulus modality and cognitive task. These results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internally-generated stimulus-specific information represented within the cortex.
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Affiliation(s)
- Benjamin James Griffiths
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
| | - Stephen D Mayhew
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
| | - Karen J Mullinger
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUnited Kingdom
| | - João Jorge
- Laboratory for Functional and Metabolic ImagingÉcole Polytechnique Fédérale de LausanneLausanneSwitzerland
| | - Ian Charest
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
| | - Maria Wimber
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
| | - Simon Hanslmayr
- School of PsychologyUniversity of BirminghamBirminghamUnited Kingdom
- Centre for Human Brain HealthUniversity of BirminghamBirminghamUnited Kingdom
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