1
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Fang P, Gao Y, Li Y, Li C, Zhang T, Wu L, Zhu Y, Xie Y. Effects of computerized working memory training on neuroplasticity in healthy individuals: A combined neuroimaging and neurotransmitter study. Neuroimage 2024; 298:120785. [PMID: 39154869 DOI: 10.1016/j.neuroimage.2024.120785] [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: 12/16/2023] [Revised: 08/09/2024] [Accepted: 08/12/2024] [Indexed: 08/20/2024] Open
Abstract
Working memory (WM) is an essential cognitive function that underpins various higher-order cognitive processes. Improving WM capacity through targeted training interventions has emergered as a potential approach for enhancing cognitive abilities. The present study employed an 8-week regimen of computerized WM training (WMT) to investigate its effect on neuroplasticity in healthy individuals, utilizing neuroimaging data gathered both before and after the training. The key metrics assessed included the amplitude of low-frequency fluctuations (ALFF), voxel-based morphometry (VBM), and the spatial distribution correlations of neurotransmitter. The results indicated that post-training, compared to baseline, there was a reduction in ALFF in the medial superior frontal gyrus and an elevation in ALFF in the left middle occipital gyrus within the training group. In comparison to the control group, the training group also exhibited decreased ALFF in the anterior cingulate cortex, angular gyrus, and superior parietal lobule, along with increased ALFF in the postcentral gyrus post-training. VBM analysis revealed a significant increase in gray matter volume (GMV) in the right dorsal superior frontal gyrus after the training period, compared to the initial baseline measurement. Furthermore, the training group showed GMV increases in the dorsal superior frontal gyrus, Rolandic operculum, precentral gyrus, and postcentral gyrus when compared to the control group. In addition, significant associations were identifed between neuroimaging measurements (AFLL and VBM) and the spatial patterns of neurotransmitters such as serotonin (5-HT), dopamine (DA), and N-methyl-D-aspartate (NMDA), providing insights into the underlying neurochemical processes. These findings clarify the neuroplastic changes caused by WMT, offering a deeper understanding of brain plasticity and highlighting the potential advantages of cognitive training interventions.
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Affiliation(s)
- Peng Fang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China; Shaanxi Provincial Key Laboratory of Bioelectromagnetic Detection and Intelligent Perception, Xi'an, China; Military Medical Innovation Center, Fourth Military Medical University, Xi'an, China; School of Biomedical Engineering, Fourth Military Medical University, Xi'an, China
| | - Yuntao Gao
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Yijun Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Chenxi Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Tian Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Lin Wu
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Yuanqiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China.
| | - Yuanjun Xie
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China.
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2
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Xiang S, Jia T, Xie C, Zhu Z, Cheng W, Schumann G, Robbins TW, Feng J. Fractionation of neural reward processing into independent components by novel decoding principle. Neuroimage 2023; 284:120463. [PMID: 37989457 DOI: 10.1016/j.neuroimage.2023.120463] [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: 04/16/2023] [Revised: 11/12/2023] [Accepted: 11/17/2023] [Indexed: 11/23/2023] Open
Abstract
How to retrieve latent neurobehavioural processes from complex neurobiological signals is an important yet unresolved challenge. Here, we develop a novel approach, orthogonal-Decoding multi-Cognitive Processes (DeCoP), to reveal underlying latent neurobehavioural processing and show that its performance is superior to traditional non-orthogonal decoding in terms of both false inference and robustness. Processing value and salience information are two fundamental but mutually confounded pathways of reward reinforcement essential for decision making. During reward/punishment anticipation, we applied DeCoP to decode brain-wide responses into spatially overlapping, yet functionally independent, evaluation and readiness processes, which are modulated differentially by meso‑limbic vs nigro-striatal dopamine systems. Using DeCoP, we further demonstrated that most brain regions only encoded abstract information but not the exact input, except for dorsal anterior cingulate cortex and insula. Furthermore, we anticipate our novel analytical principle to be applied generally in decoding multiple latent neurobehavioral processes and thus advance both the design and hypothesis testing for cognitive tasks.
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Affiliation(s)
- Shitong Xiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China
| | - Tianye Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China; Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, SE5 8AF, United Kingdom; Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Chao Xie
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China
| | - Zhichao Zhu
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Psychiatry and Psychotherapy, Centre for Population Neuroscience and Precision Medicine (PONS), CCM, Charite Universitaetsmedizin, Berlin, Germany
| | - Trevor W Robbins
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China; Department of Psychology and Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education, Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), China; Department of Computer Science, University of Warwick, Coventry, United Kingdom; School of Mathematical Sciences and Centre for Computational Systems Biology, Fudan University, Shanghai, China.
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3
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Law CK, Kolling N, Chan CCH, Chau BKH. Frontopolar cortex represents complex features and decision value during choice between environments. Cell Rep 2023; 42:112555. [PMID: 37224014 PMCID: PMC10320831 DOI: 10.1016/j.celrep.2023.112555] [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: 05/31/2022] [Revised: 11/23/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
Important decisions often involve choosing between complex environments that define future item encounters. Despite its importance for adaptive behavior and distinct computational challenges, decision-making research primarily focuses on item choice, ignoring environment choice altogether. Here we contrast previously studied item choice in ventromedial prefrontal cortex with lateral frontopolar cortex (FPl) linked to environment choice. Furthermore, we propose a mechanism for how FPl decomposes and represents complex environments during decision making. Specifically, we trained a choice-optimized, brain-naive convolutional neural network (CNN) and compared predicted CNN activation with actual FPl activity. We showed that the high-dimensional FPl activity decomposes environment features to represent the complexity of an environment to make such choice possible. Moreover, FPl functionally connects with posterior cingulate cortex for guiding environment choice. Further probing FPl's computation revealed a parallel processing mechanism in extracting multiple environment features.
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Affiliation(s)
- Chun-Kit Law
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong.
| | - Nils Kolling
- Université Lyon 1, INSERM, Stem Cell and Brain Research Institute U1208, 18 Avenue Doyen Lepine, 69500 Bron, France; Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Chetwyn C H Chan
- Department of Psychology, The Education University of Hong Kong, Hong Kong
| | - Bolton K H Chau
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong; University Research Facility in Behavioral and Systems Neuroscience, The Hong Kong Polytechnic University, Hong Kong.
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4
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Jia R, Ruderman L, Pietrzak RH, Gordon C, Ehrlich D, Horvath M, Mirchandani S, DeFontes C, Southwick S, Krystal JH, Harpaz-Rotem I, Levy I. Neural valuation of rewards and punishments in posttraumatic stress disorder: a computational approach. Transl Psychiatry 2023; 13:101. [PMID: 36977676 PMCID: PMC10050320 DOI: 10.1038/s41398-023-02388-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 02/26/2023] [Accepted: 02/28/2023] [Indexed: 03/30/2023] Open
Abstract
Posttraumatic stress disorder (PTSD) is associated with changes in fear learning and decision-making, suggesting involvement of the brain's valuation system. Here we investigate the neural mechanisms of subjective valuation of rewards and punishments in combat veterans. In a functional MRI study, male combat veterans with a wide range of posttrauma symptoms (N = 48, Clinician Administered PTSD Scale, CAPS-IV) made a series of choices between sure and uncertain monetary gains and losses. Activity in the ventromedial prefrontal cortex (vmPFC) during valuation of uncertain options was associated with PTSD symptoms, an effect which was consistent for gains and losses, and specifically driven by numbing symptoms. In an exploratory analysis, computational modeling of choice behavior was used to estimate the subjective value of each option. The neural encoding of subjective value varied as a function of symptoms. Most notably, veterans with PTSD exhibited enhanced representations of the saliency of gains and losses in the neural valuation system, especially in ventral striatum. These results suggest a link between the valuation system and the development and maintenance of PTSD, and demonstrate the significance of studying reward and punishment processing within subject.
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Affiliation(s)
- Ruonan Jia
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Lital Ruderman
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Robert H Pietrzak
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Charles Gordon
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Daniel Ehrlich
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Mark Horvath
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Serena Mirchandani
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Clara DeFontes
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Steven Southwick
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - John H Krystal
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu-Tsai Institute, Yale University, New Haven, CT, USA
| | - Ilan Harpaz-Rotem
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu-Tsai Institute, Yale University, New Haven, CT, USA
| | - Ifat Levy
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA.
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA.
- National Center for PTSD, West Haven VA Medical Center, West Haven, CT, USA.
- Department of Psychology, Yale University, New Haven, CT, USA.
- Wu-Tsai Institute, Yale University, New Haven, CT, USA.
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA.
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5
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Haufler D, Liran O, Buchanan RJ, Pare D. Human anterior insula signals salience and deviations from expectations via bursts of beta oscillations. J Neurophysiol 2022; 128:160-180. [PMID: 35704705 DOI: 10.1152/jn.00106.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Functional imaging studies indicate that the insula encodes the salience of stimuli and deviations from expectations, signals that can mobilize cognitive resources and facilitate learning. However, there is no information about the physiological underpinnings of these phenomena beyond changing BOLD signals. To shed light on this question, we analyzed intracerebral local field potentials (LFPs) in five epileptic patients of both genders performing a virtual reality task that featured varying odds of monetary rewards and losses. Upon outcome disclosure, the anterior (but not the posterior) insula generated bursts of beta oscillations whose amplitudes were lower for neutral than positive and negative outcomes, consistent with a salience signal. Moreover, beta burst power was higher when outcomes deviated from expectations, whether the outcome was better or worse than expected, indicating that the insula provides an unsigned prediction error signal. Last, in relation to insular beta bursts, many higher-order cortical areas exhibited robust changes in LFP activity that ranged from spectrally non-specific or differentiated increases in gamma power to bursts of beta activity that closely resembled the insular beta bursts themselves. Critically, the activity of these other cortical regions was more closely tied in time to insular bursts than task events, suggesting that they are associated with particularly significant cognitive phenomena. Overall, our findings suggest that the insula signals salience and prediction errors via amplitude modulations of beta bursts, which coincide with the near simultaneous recruitment of vast cortical territories.
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Affiliation(s)
- Darrell Haufler
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States
| | - Omer Liran
- Department of Psychiatry and Behavioral Neurosciences, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Robert J Buchanan
- Departments of Neurosurgery, Neurology, and Psychiatry, Dell Medical School at The University Texas at Austin, Austin, TX, United States.,Seton Brain and Spine Institute, Austin, TX, United States
| | - Denis Pare
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States
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6
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Abstract
SignificanceWe often willingly experience pain to reach a goal. However, potential pain can also prevent reckless action. How do we consider future pain when deciding on the best course of action? To date, the precise neural mechanisms underlying the valuation of future pain remain unknown. Using functional MRI, we derive a whole-brain signature of the value of future pain capable of predicting participants' choices to accept pain in exchange for a reward. We show that this signature is characterized by a distributed pattern of activity with clear contributions from structures encoding reward and salience, notably the ventral and dorsal striatum. These findings highlight how the brain assigns value to future pain when choosing the best course of action.
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7
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Dan O, Wertheimer EK, Levy I. A Neuroeconomics Approach to Obesity. Biol Psychiatry 2022; 91:860-868. [PMID: 34861975 PMCID: PMC8960474 DOI: 10.1016/j.biopsych.2021.09.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 09/17/2021] [Accepted: 09/21/2021] [Indexed: 11/16/2022]
Abstract
Obesity is a heterogeneous condition that is affected by physiological, behavioral, and environmental factors. Value-based decision making is a useful framework for integrating these factors at the individual level. The disciplines of behavioral economics and reinforcement learning provide tools for identifying specific cognitive and motivational processes that may contribute to the development and maintenance of obesity. Neuroeconomics complements these disciplines by studying the neural mechanisms underlying these processes. We surveyed recent literature on individual decision characteristics that are most frequently implicated in obesity: discounting the value of future outcomes, attitudes toward uncertainty, and learning from rewards and punishments. Our survey highlighted both consistent and inconsistent behavioral findings. These findings underscore the need to examine multiple processes within individuals to identify unique behavioral profiles associated with obesity. Such individual characterization will inform future studies on the neurobiology of obesity as well as the design of effective interventions that are individually tailored.
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Affiliation(s)
- Ohad Dan
- Department of Comparative Medicine, Yale University, New Haven, Connecticut
| | - Emily K Wertheimer
- Department of Comparative Medicine, Yale University, New Haven, Connecticut
| | - Ifat Levy
- Department of Comparative Medicine, Yale University, New Haven, Connecticut; Department of Neuroscience, Yale University, New Haven, Connecticut; Department of Psychology, Yale University, New Haven, Connecticut; Wu Tsai Institute, Yale University, New Haven, Connecticut.
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8
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Abstract
Learned associations between stimuli in different sensory modalities can shape the way we perceive these stimuli. However, it is not well understood how these interactions are mediated or at what level of the processing hierarchy they occur. Here we describe a neural mechanism by which an auditory input can shape visual representations of behaviorally relevant stimuli through direct interactions between auditory and visual cortices in mice. We show that the association of an auditory stimulus with a visual stimulus in a behaviorally relevant context leads to experience-dependent suppression of visual responses in primary visual cortex (V1). Auditory cortex axons carry a mixture of auditory and retinotopically matched visual input to V1, and optogenetic stimulation of these axons selectively suppresses V1 neurons that are responsive to the associated visual stimulus after, but not before, learning. Our results suggest that cross-modal associations can be communicated by long-range cortical connections and that, with learning, these cross-modal connections function to suppress responses to predictable input.
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9
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Magrabi A, Ludwig VU, Stoppel CM, Paschke LM, Wisniewski D, Heekeren HR, Walter H. Dynamic Computation of Value Signals via a Common Neural Network in Multi-Attribute Decision-Making. Soc Cogn Affect Neurosci 2021; 17:683-693. [PMID: 34850226 PMCID: PMC9250299 DOI: 10.1093/scan/nsab125] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 10/12/2021] [Accepted: 11/25/2021] [Indexed: 11/14/2022] Open
Abstract
Studies in decision neuroscience have identified robust neural representations for the value of choice options. However, overall values often depend on multiple attributes, and it is not well understood how the brain evaluates different attributes and integrates them to combined values. In particular, it is not clear whether attribute values are computed in distinct attribute-specific regions or within the general valuation network known to process overall values. Here, we used an fMRI choice task in which abstract stimuli had to be evaluated based on variations of the attributes color and motion. The behavioral data showed that participants responded faster when overall values were high and attribute value differences were low. On the neural level, we did not find that attribute values were systematically represented in areas V4 and V5, even though these regions are associated with attribute-specific processing of color and motion, respectively. Instead, attribute values were associated with activity in the posterior cingulate cortex, ventral striatum, and posterior inferior temporal gyrus. Further, overall values were represented in dorsolateral and ventromedial prefrontal cortex, and attribute value differences in dorsomedial prefrontal cortex, which suggests that these regions play a key role for the neural integration of attribute values.
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Affiliation(s)
- Amadeus Magrabi
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany.,Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Vera U Ludwig
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany.,Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.,Wharton Neuroscience Initiative, University of Pennsylvania, Philadelphia, PA, USA
| | - Christian M Stoppel
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Lena M Paschke
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany.,Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.,Department of Psychology, Humboldt-Universität zu Berlin, Berlin 12489, Germany
| | - David Wisniewski
- Department of Experimental Psychology, Ghent University, Gent 9000, Belgium
| | - Hauke R Heekeren
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany.,Department of Education and Psychology, Freie Universität Berlin, Berlin 14195, Germany
| | - Henrik Walter
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin 10117, Germany.,Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin 10117, Germany.,Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin 10119, Germany
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10
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Perkins AQ, Rich EL. Identifying identity and attributing value to attributes: reconsidering mechanisms of preference decisions. Curr Opin Behav Sci 2021; 41:98-105. [DOI: 10.1016/j.cobeha.2021.04.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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11
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Levy I, Schiller D. Neural Computations of Threat. Trends Cogn Sci 2021; 25:151-171. [PMID: 33384214 PMCID: PMC8084636 DOI: 10.1016/j.tics.2020.11.007] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/16/2020] [Accepted: 11/18/2020] [Indexed: 12/26/2022]
Abstract
A host of learning, memory, and decision-making processes form the individual's response to threat and may be disrupted in anxiety and post-trauma psychopathology. Here we review the neural computations of threat, from the first encounter with a dangerous situation, through learning, storing, and updating cues that predict it, to making decisions about the optimal course of action. The overview highlights the interconnected nature of these processes and their reliance on shared neural and computational mechanisms. We propose an integrative approach to the study of threat-related processes, in which specific computations are studied across the various stages of threat experience rather than in isolation. This approach can generate new insights about the evolution, diagnosis, and treatment of threat-related psychopathology.
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Affiliation(s)
- Ifat Levy
- Departments of Comparative Medicine, Neuroscience, and Psychology, Yale University, New Haven, CT, USA.
| | - Daniela Schiller
- Department of Psychiatry, Department of Neuroscience, and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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12
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Bobadilla-Suarez S, Guest O, Love BC. Subjective value and decision entropy are jointly encoded by aligned gradients across the human brain. Commun Biol 2020; 3:597. [PMID: 33087799 PMCID: PMC7578785 DOI: 10.1038/s42003-020-01315-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 09/15/2020] [Indexed: 11/15/2022] Open
Abstract
Recent work has considered the relationship between value and confidence in both behavioural and neural representation. Here we evaluated whether the brain organises value and confidence signals in a systematic fashion that reflects the overall desirability of options. If so, regions that respond to either increases or decreases in both value and confidence should be widespread. We strongly confirmed these predictions through a model-based fMRI analysis of a mixed gambles task that assessed subjective value (SV) and inverse decision entropy (iDE), which is related to confidence. Purported value areas more strongly signalled iDE than SV, underscoring how intertwined value and confidence are. A gradient tied to the desirability of actions transitioned from positive SV and iDE in ventromedial prefrontal cortex to negative SV and iDE in dorsal medial prefrontal cortex. This alignment of SV and iDE signals could support retrospective evaluation to guide learning and subsequent decisions.
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Affiliation(s)
| | - Olivia Guest
- Department of Experimental Psychology, University College London, 26 Bedford Way, London, WC1H 0AP, UK
- Research Centre on Interactive Media, Smart Systems and Emerging Technologies - RISE, Nicosia, Cyprus
| | - Bradley C Love
- Department of Experimental Psychology, University College London, 26 Bedford Way, London, WC1H 0AP, UK
- The Alan Turing Institute, 96 Euston Road, London, NW1 2DB, UK
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13
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Ghazizadeh A, Fakharian MA, Amini A, Griggs W, Leopold DA, Hikosaka O. Brain Networks Sensitive to Object Novelty, Value, and Their Combination. Cereb Cortex Commun 2020; 1:tgaa034. [PMID: 32984816 PMCID: PMC7503454 DOI: 10.1093/texcom/tgaa034] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 07/17/2020] [Accepted: 07/20/2020] [Indexed: 11/12/2022] Open
Abstract
Novel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain responses to visual fractal patterns varying in either novelty or value dimensions and compared the results with the structure of functionally connected brain networks determined at rest. The results show that different brain networks possess unique combinations of novelty and value coding. One network identified in the ventral temporal cortex preferentially encoded object novelty, whereas another in the parietal cortex encoded the learned value. A third network, broadly composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, encoded both dimensions with similar activation dynamics. Our results support the emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.
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Affiliation(s)
- Ali Ghazizadeh
- Bio-intelligence Research Unit, Electrical Engineering Department, Sharif University of Technology, Tehran 11365-11155, Iran.,School of Cognitive Sciences, Institute for Research in Fundamental Sciences, Tehran 19395-5746, Iran
| | - Mohammad Amin Fakharian
- Bio-intelligence Research Unit, Electrical Engineering Department, Sharif University of Technology, Tehran 11365-11155, Iran
| | - Arash Amini
- Bio-intelligence Research Unit, Electrical Engineering Department, Sharif University of Technology, Tehran 11365-11155, Iran
| | - Whitney Griggs
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - David A Leopold
- Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA.,Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Okihide Hikosaka
- Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892, USA.,National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA
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14
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Four core properties of the human brain valuation system demonstrated in intracranial signals. Nat Neurosci 2020; 23:664-675. [PMID: 32284605 DOI: 10.1038/s41593-020-0615-9] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 02/21/2020] [Indexed: 01/08/2023]
Abstract
Estimating the value of alternative options is a key process in decision-making. Human functional magnetic resonance imaging and monkey electrophysiology studies have identified brain regions, such as the ventromedial prefrontal cortex (vmPFC) and lateral orbitofrontal cortex (lOFC), composing a value system. In the present study, in an effort to bridge across species and techniques, we investigated the neural representation of value ratings in 36 people with epilepsy, using intracranial electroencephalography. We found that subjective value was positively reflected in both vmPFC and lOFC high-frequency activity, plus several other brain regions, including the hippocampus. We then demonstrated that subjective value could be decoded (1) in pre-stimulus activity, (2) for various categories of items, (3) even during a distractive task and (4) as both linear and quadratic signals (encoding both value and confidence). Thus, our findings specify key functional properties of neural value signals (anticipation, generality, automaticity, quadraticity), which might provide insights into human irrational choice behaviors.
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15
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Serranová T, Sieger T, Růžička F, Bakštein E, Dušek P, Vostatek P, Novák D, Růžička E, Urgošík D, Jech R. Topography of emotional valence and arousal within the motor part of the subthalamic nucleus in Parkinson's disease. Sci Rep 2019; 9:19924. [PMID: 31882633 PMCID: PMC6934686 DOI: 10.1038/s41598-019-56260-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 12/02/2019] [Indexed: 01/24/2023] Open
Abstract
Clinical motor and non-motor effects of deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) seem to depend on the stimulation site within the STN. We analysed the effects of the position of the stimulation electrode within the motor STN on subjective emotional experience, expressed as emotional valence and arousal ratings to pictures representing primary rewards and aversive fearful stimuli in 20 PD patients. Patients' ratings from both aversive and erotic stimuli matched the mean ratings from a group of 20 control subjects at similar position within the STN. Patients with electrodes located more posteriorly reported both valence and arousal ratings from both the rewarding and aversive pictures as more extreme. Moreover, posterior electrode positions were associated with a higher occurrence of depression at a long-term follow-up. This brain-behavior relationship suggests a complex emotion topography in the motor part of the STN. Both valence and arousal representations overlapped and were uniformly arranged anterior-posteriorly in a gradient-like manner, suggesting a specific spatial organization needed for the coding of the motivational salience of the stimuli. This finding is relevant for our understanding of neuropsychiatric side effects in STN DBS and potentially for optimal electrode placement.
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Affiliation(s)
- Tereza Serranová
- Department of Neurology and Center of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital, Kateřinská 30, 128 08, Prague, Czech Republic.
| | - Tomáš Sieger
- Department of Neurology and Center of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital, Kateřinská 30, 128 08, Prague, Czech Republic.,Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27, Prague, Czech Republic
| | - Filip Růžička
- Department of Neurology and Center of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital, Kateřinská 30, 128 08, Prague, Czech Republic.,Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Roentgenova 2, 150 30, Prague, Czech Republic
| | - Eduard Bakštein
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27, Prague, Czech Republic.,National Institute of Mental Health, Klecany, Topolová 748, 250 67, Czech Republic
| | - Petr Dušek
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27, Prague, Czech Republic
| | - Pavel Vostatek
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27, Prague, Czech Republic
| | - Daniel Novák
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Center of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital, Kateřinská 30, 128 08, Prague, Czech Republic
| | - Dušan Urgošík
- Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Roentgenova 2, 150 30, Prague, Czech Republic
| | - Robert Jech
- Department of Neurology and Center of Clinical Neuroscience, Charles University, 1st Faculty of Medicine and General University Hospital, Kateřinská 30, 128 08, Prague, Czech Republic.,Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Roentgenova 2, 150 30, Prague, Czech Republic
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16
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Van de Steen F, Krebs RM, Colenbier N, Almgren H, Marinazzo D. Effective connectivity modulations related to win and loss outcomes. Neuroimage 2019; 207:116369. [PMID: 31747561 DOI: 10.1016/j.neuroimage.2019.116369] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 11/12/2019] [Accepted: 11/15/2019] [Indexed: 01/08/2023] Open
Abstract
Previous studies have characterized the brain regions involved in encoding monetary reward and punishment outcomes. The question of how this information is integrated across brain regions has received less attention. Here, we investigated changes in effective connectivity related to the processing of positive and negative monetary outcomes using functional magnetic resonance imaging data from the Human Connectome Project. Specifically, subjects engaged in a card guessing game which could yield win, loss, or neutral outcomes. A general linear model was used to define a network of regions involved in win and loss outcome processing, including anterior insula, anterior cingulate cortex, and ventral striatum. Dynamic causal modelling (DCM) was implemented to study between-region couplings and outcome-related modulations thereof within this network. In addition, we explored the relation between effective connectivity patterns and choice behavior in the gambling task. Parametric empirical Bayesian modelling was conducted for group-level inferences of both DCM and the choice behavior. Behaviorally, both win and loss outcomes increased the probability of choice switches in subsequent gambles. In terms of connectivity, win outcomes were associated with increased extrinsic connectivity across the network, while loss outcomes featured a balance between increased and decreased extrinsic connectivity. Moreover, self-inhibitory connections tended to decrease for both win and loss outcomes. Interestingly, a substantial discrepancy was observed for occipital cortex connectivity, which was characterized by intrinsic disinhibition in loss but not in win trials. The observed differences in effective connectivity during the processing of positive and negative outcomes, despite similarities in average regional activity and choice behavior, highlight the value of exploring network dynamics in the context of incentive manipulations.
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Affiliation(s)
| | - Ruth M Krebs
- Department of Experimental Psychology, Ghent University, Ghent, Belgium
| | - Nigel Colenbier
- Department of Data Analysis, Ghent University, Ghent, Belgium
| | - Hannes Almgren
- Department of Data Analysis, Ghent University, Ghent, Belgium
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17
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Piva M, Velnoskey K, Jia R, Nair A, Levy I, Chang SW. The dorsomedial prefrontal cortex computes task-invariant relative subjective value for self and other. eLife 2019; 8:44939. [PMID: 31192786 PMCID: PMC6565363 DOI: 10.7554/elife.44939] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 06/03/2019] [Indexed: 12/11/2022] Open
Abstract
Few studies have addressed the neural computations underlying decisions made for others despite the importance of this ubiquitous behavior. Using participant-specific behavioral modeling with univariate and multivariate fMRI approaches, we investigated the neural correlates of decision-making for self and other in two independent tasks, including intertemporal and risky choice. Modeling subjective valuation indicated that participants distinguished between themselves and others with dissimilar preferences. Activity in the dorsomedial prefrontal cortex (dmPFC) and ventromedial prefrontal cortex (vmPFC) was consistently modulated by relative subjective value. Multi-voxel pattern analysis indicated that activity in the dmPFC uniquely encoded relative subjective value and generalized across self and other and across both tasks. Furthermore, agent cross-decoding accuracy between self and other in the dmPFC was related to self-reported social attitudes. These findings indicate that the dmPFC emerges as a medial prefrontal node that utilizes a task-invariant mechanism for computing relative subjective value for self and other.
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Affiliation(s)
- Matthew Piva
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States
| | - Kayla Velnoskey
- Department of Psychology, Yale University, New Haven, United States
| | - Ruonan Jia
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States
| | - Amrita Nair
- Department of Psychology, Yale University, New Haven, United States
| | - Ifat Levy
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States.,Department of Psychology, Yale University, New Haven, United States.,Department of Comparative Medicine, Yale University School of Medicine, New Haven, United States.,Department of Neuroscience, Yale University School of Medicine, New Haven, United States
| | - Steve Wc Chang
- Interdepartmental Neuroscience Program, Yale University, New Haven, United States.,Department of Psychology, Yale University, New Haven, United States.,Department of Neuroscience, Yale University School of Medicine, New Haven, United States.,Kavli Institute for Neuroscience, Yale University School of Medicine, New Haven, United States
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18
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Zhang Z, Coppin G. To What Extent Memory Could Contribute to Impaired Food Valuation and Choices in Obesity? Front Psychol 2018; 9:2523. [PMID: 30618948 PMCID: PMC6297373 DOI: 10.3389/fpsyg.2018.02523] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 11/27/2018] [Indexed: 12/17/2022] Open
Abstract
Obesity is associated with a diverse array of cognitive and affective deficits, among which impairments in food valuation and choices have received increasing attention. The neural underpinnings of such impairments, however, remain poorly understood, partly because a complete understanding of these processes under normal conditions has yet to be achieved. A rapidly growing literature on the interaction between memory and decision-making has begun to highlight the integral role of memory in decision making especially in the real world, as well as the role of the hippocampus in supporting flexible decision making. Perhaps not coincidentally, altered memory performances in obesity have been well documented, and the underlying neurobiological bases of these memory alterations have also started to be better described, involving pathologies at the biochemical, cellular, and circuit levels. Despite such correspondence, the link between memory impairments and food valuation/choice deficits in obesity has received little attention. In this article, we first summarize the growing empirical support for the relevance of memory for decision making, focusing on flexible value-based decisions. We then describe converging evidence on different forms of memory impairments accompanying obesity. Building on these findings, we formulate a general neuropsychological framework and discuss how dysfunctions in the formation and retrieval of memory may interfere with adaptive decision making for food. Finally, we stress the important practical implications of this framework, arguing that memory deficits are likely a significant contributor to suboptimal food purchase and eating behavior exhibited by obese individuals.
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Affiliation(s)
- Zhihao Zhang
- Haas School of Business, University of California, Berkeley, Berkeley, CA, United States.,Department of Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Géraldine Coppin
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland.,Laboratory for the Study of Emotion Elicitation and Expression, Department of Psychology, University of Geneva, Geneva, Switzerland.,Department of Psychology, Distance Learning University Switzerland (Unidistance), Brig, Switzerland
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19
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Dalenberg JR, Weitkamp L, Renken RJ, ter Horst GJ. Valence processing differs across stimulus modalities. Neuroimage 2018; 183:734-744. [DOI: 10.1016/j.neuroimage.2018.08.059] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Revised: 08/06/2018] [Accepted: 08/24/2018] [Indexed: 12/15/2022] Open
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