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Martin E, Chowdury A, Kopchick J, Thomas P, Khatib D, Rajan U, Zajac-Benitez C, Haddad L, Amirsadri A, Robison AJ, Thakkar KN, Stanley JA, Diwadkar VA. The mesolimbic system and the loss of higher order network features in schizophrenia when learning without reward. Front Psychiatry 2024; 15:1337882. [PMID: 39355381 PMCID: PMC11443173 DOI: 10.3389/fpsyt.2024.1337882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 08/16/2024] [Indexed: 10/03/2024] Open
Abstract
Introduction Schizophrenia is characterized by a loss of network features between cognition and reward sub-circuits (notably involving the mesolimbic system), and this loss may explain deficits in learning and cognition. Learning in schizophrenia has typically been studied with tasks that include reward related contingencies, but recent theoretical models have argued that a loss of network features should be seen even when learning without reward. We tested this model using a learning paradigm that required participants to learn without reward or feedback. We used a novel method for capturing higher order network features, to demonstrate that the mesolimbic system is heavily implicated in the loss of network features in schizophrenia, even when learning without reward. Methods fMRI data (Siemens Verio 3T) were acquired in a group of schizophrenia patients and controls (n=78; 46 SCZ, 18 ≤ Age ≤ 50) while participants engaged in associative learning without reward-related contingencies. The task was divided into task-active conditions for encoding (of associations) and cued-retrieval (where the cue was to be used to retrieve the associated memoranda). No feedback was provided during retrieval. From the fMRI time series data, network features were defined as follows: First, for each condition of the task, we estimated 2nd order undirected functional connectivity for each participant (uFC, based on zero lag correlations between all pairs of regions). These conventional 2nd order features represent the task/condition evoked synchronization of activity between pairs of brain regions. Next, in each of the patient and control groups, the statistical relationship between all possible pairs of 2nd order features were computed. These higher order features represent the consistency between all possible pairs of 2nd order features in that group and embed within them the contributions of individual regions to such group structure. Results From the identified inter-group differences (SCZ ≠ HC) in higher order features, we quantified the respective contributions of individual brain regions. Two principal effects emerged: 1) SCZ were characterized by a massive loss of higher order features during multiple task conditions (encoding and retrieval of associations). 2) Nodes in the mesolimbic system were over-represented in the loss of higher order features in SCZ, and notably so during retrieval. Discussion Our analytical goals were linked to a recent circuit-based integrative model which argued that synergy between learning and reward circuits is lost in schizophrenia. The model's notable prediction was that such a loss would be observed even when patients learned without reward. Our results provide substantial support for these predictions where we observed a loss of network features between the brain's sub-circuits for a) learning (including the hippocampus and prefrontal cortex) and b) reward processing (specifically constituents of the mesolimbic system that included the ventral tegmental area and the nucleus accumbens. Our findings motivate a renewed appraisal of the relationship between reward and cognition in schizophrenia and we discuss their relevance for putative behavioral interventions.
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Affiliation(s)
- Elizabeth Martin
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
- Department of Psychiatry, University of Texas Austin, Austin, TX, United States
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI, United States
| | - John Kopchick
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Patricia Thomas
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Dalal Khatib
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Usha Rajan
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Caroline Zajac-Benitez
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Luay Haddad
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alireza Amirsadri
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alfred J. Robison
- Department of Physiology, Michigan State University, East Lansing, MI, United States
| | - Katherine N. Thakkar
- Department of Psychology, Michigan State University, East Lansing, MI, United States
| | - Jeffrey A. Stanley
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Vaibhav A. Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
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Li H, Rodríguez-Nieto G, Chalavi S, Seer C, Mikkelsen M, Edden RAE, Swinnen SP. MRS-assessed brain GABA modulation in response to task performance and learning. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:22. [PMID: 39217354 PMCID: PMC11366171 DOI: 10.1186/s12993-024-00248-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 08/16/2024] [Indexed: 09/04/2024]
Abstract
Gamma-aminobutyric acid (GABA), the most important inhibitory neurotransmitter in the human brain, has long been considered essential in human behavior in general and learning in particular. GABA concentration can be quantified using magnetic resonance spectroscopy (MRS). Using this technique, numerous studies have reported associations between baseline GABA levels and various human behaviors. However, regional GABA concentration is not fixed and may exhibit rapid modulation as a function of environmental factors. Hence, quantification of GABA levels at several time points during the performance of tasks can provide insights into the dynamics of GABA levels in distinct brain regions. This review reports on findings from studies using repeated measures (n = 41) examining the dynamic modulation of GABA levels in humans in response to various interventions in the perceptual, motor, and cognitive domains to explore associations between GABA modulation and human behavior. GABA levels in a specific brain area may increase or decrease during task performance or as a function of learning, depending on its precise involvement in the process under investigation. Here, we summarize the available evidence and derive two overarching hypotheses regarding the role of GABA modulation in performance and learning. Firstly, training-induced increases in GABA levels appear to be associated with an improved ability to differentiate minor perceptual differences during perceptual learning. This observation gives rise to the 'GABA increase for better neural distinctiveness hypothesis'. Secondly, converging evidence suggests that reducing GABA levels may play a beneficial role in effectively filtering perceptual noise, enhancing motor learning, and improving performance in visuomotor tasks. Additionally, some studies suggest that the reduction of GABA levels is related to better working memory and successful reinforcement learning. These observations inspire the 'GABA decrease to boost learning hypothesis', which states that decreasing neural inhibition through a reduction of GABA in dedicated brain areas facilitates human learning. Additionally, modulation of GABA levels is also observed after short-term physical exercise. Future work should elucidate which specific circumstances induce robust GABA modulation to enhance neuroplasticity and boost performance.
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Affiliation(s)
- Hong Li
- Movement Control and Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium
| | - Geraldine Rodríguez-Nieto
- Movement Control and Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium
| | - Sima Chalavi
- Movement Control and Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium
| | - Caroline Seer
- Movement Control and Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium
- Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium
| | - Mark Mikkelsen
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Stephan P Swinnen
- Movement Control and Neuroplasticity Research Group, Group Biomedical Sciences, KU Leuven, Leuven, Belgium.
- Leuven Brain Institute (LBI), KU Leuven, Leuven, Belgium.
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Jia K, Wang M, Steinwurzel C, Ziminski JJ, Xi Y, Emir U, Kourtzi Z. Recurrent inhibition refines mental templates to optimize perceptual decisions. SCIENCE ADVANCES 2024; 10:eado7378. [PMID: 39083601 PMCID: PMC11290482 DOI: 10.1126/sciadv.ado7378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Accepted: 06/26/2024] [Indexed: 08/02/2024]
Abstract
Translating sensory inputs to perceptual decisions relies on building internal representations of features critical for solving complex tasks. Yet, we still lack a mechanistic account of how the brain forms these mental templates of task-relevant features to optimize decision-making. Here, we provide evidence for recurrent inhibition: an experience-dependent plasticity mechanism that refines mental templates by enhancing γ-aminobutyric acid (GABA)-mediated (GABAergic) inhibition and recurrent processing in superficial visual cortex layers. We combine ultrahigh-field (7 T) functional magnetic resonance imaging at submillimeter resolution with magnetic resonance spectroscopy to investigate the fine-scale functional and neurochemical plasticity mechanisms for optimized perceptual decisions. We demonstrate that GABAergic inhibition increases following training on a visual (i.e., fine orientation) discrimination task, enhancing the discriminability of orientation representations in superficial visual cortex layers that are known to support recurrent processing. Modeling functional and neurochemical plasticity interactions reveals that recurrent inhibitory processing optimizes brain computations for perpetual decisions and adaptive behavior.
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Affiliation(s)
- Ke Jia
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Mengxin Wang
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | | | - Joseph J. Ziminski
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Yinghua Xi
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, IN 47906, USA
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
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Koyun AH, Talebi N, Werner A, Wendiggensen P, Kuntke P, Roessner V, Beste C, Stock AK. Interactions of catecholamines and GABA+ in cognitive control: Insights from EEG and 1H-MRS. Neuroimage 2024; 293:120619. [PMID: 38679186 DOI: 10.1016/j.neuroimage.2024.120619] [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: 01/11/2024] [Revised: 04/17/2024] [Accepted: 04/17/2024] [Indexed: 05/01/2024] Open
Abstract
Catecholamines and amino acid transmitter systems are known to interact, the exact links and their impact on cognitive control functions have however remained unclear. Using a multi-modal imaging approach combining EEG and proton-magnetic resonance spectroscopy (1H-MRS), we investigated the effect of different degrees of pharmacological catecholaminergic enhancement onto theta band activity (TBA) as a measure of interference control during response inhibition and execution. It was central to our study to evaluate the predictive impact of in-vivo baseline GABA+ concentrations in the striatum, the anterior cingulate cortex (ACC) and the supplemental motor area (SMA) of healthy adults under varying degrees of methylphenidate (MPH) stimulation. We provide evidence for a predictive interrelation of baseline GABA+ concentrations in cognitive control relevant brain areas onto task-induced TBA during response control stimulated with MPH. Baseline GABA+ concentrations in the ACC, the striatum, and the SMA had a differential impact on predicting interference control-related TBA in response execution trials. GABA+ concentrations in the ACC appeared to be specifically important for TBA modulations when the cognitive effort needed for interference control was high - that is when no prior task experience exists, or in the absence of catecholaminergic enhancement with MPH. The study highlights the predictive role of baseline GABA+ concentrations in key brain areas influencing cognitive control and responsiveness to catecholaminergic enhancement, particularly in high-effort scenarios.
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Affiliation(s)
- Anna Helin Koyun
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany
| | - Nasibeh Talebi
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany
| | - Annett Werner
- Institute of Diagnostic and Interventional Neuroradiology, TU Dresden, Germany
| | - Paul Wendiggensen
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany
| | - Paul Kuntke
- Institute of Diagnostic and Interventional Neuroradiology, TU Dresden, Germany
| | - Veit Roessner
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany
| | - Christian Beste
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany
| | - Ann-Kathrin Stock
- Cognitive Neurophysiology, Department of Child and Adolescent Psychiatry, Faculty of Medicine, TU Dresden, Schubertstrasse 42, Dresden D-01307, Germany.
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Visibelli E, Vigna G, Nascimben C, Benavides-Varela S. Neurobiology of numerical learning. Neurosci Biobehav Rev 2024; 158:105545. [PMID: 38220032 DOI: 10.1016/j.neubiorev.2024.105545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 12/29/2023] [Accepted: 01/09/2024] [Indexed: 01/16/2024]
Abstract
Numerical abilities are complex cognitive skills essential for dealing with requirements of the modern world. Although the brain structures and functions underlying numerical cognition in different species have long been appreciated, genetic and molecular techniques have more recently expanded the knowledge about the mechanisms underlying numerical learning. In this review, we discuss the status of the research related to the neurobiological bases of numerical abilities. We consider how genetic factors have been associated with mathematical capacities and how these link to the current knowledge of brain regions underlying these capacities in human and non-human animals. We further discuss the extent to which significant variations in the levels of specific neurotransmitters may be used as potential markers of individual performance and learning difficulties and take into consideration the therapeutic potential of brain stimulation methods to modulate learning and improve interventional outcomes. The implications of this research for formulating a more comprehensive view of the neural basis of mathematical learning are discussed.
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Affiliation(s)
- Emma Visibelli
- Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Giulia Vigna
- Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy
| | - Chiara Nascimben
- Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy
| | - Silvia Benavides-Varela
- Department of Developmental Psychology and Socialization, University of Padova, Padova, Italy; Padova Neuroscience Center, University of Padova, Padova, Italy.
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Wards Y, Ehrhardt SE, Filmer HL, Mattingley JB, Garner KG, Dux PE. Neural substrates of individual differences in learning generalization via combined brain stimulation and multitasking training. Cereb Cortex 2023; 33:11679-11694. [PMID: 37930735 DOI: 10.1093/cercor/bhad406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 10/05/2023] [Accepted: 10/11/2023] [Indexed: 11/07/2023] Open
Abstract
A pervasive limitation in cognition is reflected by the performance costs we experience when attempting to undertake two tasks simultaneously. While training can overcome these multitasking costs, the more elusive objective of training interventions is to induce persistent gains that transfer across tasks. Combined brain stimulation and cognitive training protocols have been employed to improve a range of psychological processes and facilitate such transfer, with consistent gains demonstrated in multitasking and decision-making. Neural activity in frontal, parietal, and subcortical regions has been implicated in multitasking training gains, but how the brain supports training transfer is poorly understood. To investigate this, we combined transcranial direct current stimulation of the prefrontal cortex and multitasking training, with functional magnetic resonance imaging in 178 participants. We observed transfer to a visual search task, following 1 mA left or right prefrontal cortex transcranial direct current stimulation and multitasking training. These gains persisted for 1-month post-training. Notably, improvements in visual search performance for the right hemisphere stimulation group were associated with activity changes in the right hemisphere dorsolateral prefrontal cortex, intraparietal sulcus, and cerebellum. Thus, functional dynamics in these task-general regions determine how individuals respond to paired stimulation and training, resulting in enhanced performance on an untrained task.
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Affiliation(s)
- Yohan Wards
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
| | - Shane E Ehrhardt
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
| | - Hannah L Filmer
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
| | - Jason B Mattingley
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
- Queensland Brain Institute, The University of Queensland, Building 79, Upland Road, St Lucia, Queensland 4072, Australia
- Canadian Institute for Advanced Research, MaRS Centre, West tower, 661 University Ave., Suite 505, Toronto, Ontario M5G 1M1, Canada
| | - Kelly G Garner
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
- Queensland Brain Institute, The University of Queensland, Building 79, Upland Road, St Lucia, Queensland 4072, Australia
- School of Psychology, University of New South Wales, Mathews Building, Gate 11, Botany Street, Randwick, New South Wales 2052, Australia
- School of Psychology, University of Birmingham, Hills Building, Edgbaston Park Rd, Birmingham B15 2TT, United Kingdom
| | - Paul E Dux
- School of Psychology, The University of Queensland, McElwain Building, Campbell Road, St Lucia, Queensland 4072, Australia
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He Q, Zhu X, Fang F. Enhancing visual perceptual learning using transcranial electrical stimulation: Transcranial alternating current stimulation outperforms both transcranial direct current and random noise stimulation. J Vis 2023; 23:2. [PMID: 38054934 PMCID: PMC10702794 DOI: 10.1167/jov.23.14.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 10/23/2023] [Indexed: 12/07/2023] Open
Abstract
Diverse strategies can be employed to enhance visual skills, including visual perceptual learning (VPL) and transcranial electrical stimulation (tES). Combining VPL and tES is a popular method that holds promise for producing significant improvements in visual acuity within a short time frame. However, there is still a lack of comprehensive evaluation regarding the effects of combining different types of tES and VPL on enhancing visual function, especially with a larger sample size. In the present study, we recruited four groups of subjects (26 subjects each) to learn an orientation discrimination task with five daily training sessions. During training, the occipital region of each subject was stimulated by one type of tES-anodal transcranial direct current stimulation (tDCS), alternating current stimulation (tACS) at 10 Hz, high-frequency random noise stimulation (tRNS), and sham tACS-while the subject performed the training task. We found that, compared with the sham stimulation, both the high-frequency tRNS and the 10-Hz tACS facilitated VPL efficiently in terms of learning rate and performance improvement, but there was little modulatory effect in the anodal tDCS condition. Remarkably, the 10-Hz tACS condition exhibited superior modulatory effects compared with the tRNS condition, demonstrating the strongest modulation among the most commonly used tES types for further enhancing vision when combined with VPL. Our results suggest that alpha oscillations play a vital role in VPL. Our study provides a practical guide for vision rehabilitation.
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Affiliation(s)
- Qing He
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xinyi Zhu
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
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Zacharopoulos G, Sella F, Emir U, Cohen Kadosh R. Dissecting the chain of information processing and its interplay with neurochemicals and fluid intelligence across development. eLife 2023; 12:e84086. [PMID: 37772958 PMCID: PMC10541179 DOI: 10.7554/elife.84086] [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: 10/10/2022] [Accepted: 08/23/2023] [Indexed: 09/30/2023] Open
Abstract
Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in perceptual, cognitive, and motor tasks. However, the exact involvement of these neurochemical mechanisms in the chain of information processing, and across human development, is unclear. In a cross-sectional longitudinal design, we used a computational approach to dissociate cognitive, decision, and visuomotor processing in 293 individuals spanning early childhood to adulthood. We found that glutamate and GABA within the intraparietal sulcus (IPS) explained unique variance in visuomotor processing, with higher glutamate predicting poorer visuomotor processing in younger participants but better visuomotor processing in mature participants, while GABA showed the opposite pattern. These findings, which were neurochemically, neuroanatomically and functionally specific, were replicated ~21 mo later and were generalized in two further different behavioral tasks. Using resting functional MRI, we revealed that the relationship between IPS neurochemicals and visuomotor processing is mediated by functional connectivity in the visuomotor network. We then extended our findings to high-level cognitive behavior by predicting fluid intelligence performance. We present evidence that fluid intelligence performance is explained by IPS GABA and glutamate and is mediated by visuomotor processing. However, this evidence was obtained using an uncorrected alpha and needs to be replicated in future studies. These results provide an integrative biological and psychological mechanistic explanation that links cognitive processes and neurotransmitters across human development and establishes their potential involvement in intelligent behavior.
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Affiliation(s)
- George Zacharopoulos
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- School of Psychology, Swansea UniversitySwanseaUnited Kingdom
| | - Francesco Sella
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Centre for Mathematical Cognition, Loughborough UniversityLoughboroughUnited Kingdom
| | - Uzay Emir
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- School of Health Sciences, College of Health and Human Sciences, Purdue UniversityWest LafayetteUnited States
| | - Roi Cohen Kadosh
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- School of Psychology, University of SurreyGuildfordUnited Kingdom
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Liu CL, Cheng X, Choo BL, Hong M, Teo JL, Koo WL, Tan JYJ, Ubrani MB, Suckling J, Gulyás B, Leong V, Kourtzi Z, Sahakian B, Robbins T, Chen ASH. Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial. Trials 2023; 24:517. [PMID: 37568212 PMCID: PMC10422731 DOI: 10.1186/s13063-023-07551-2] [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: 06/02/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023] Open
Abstract
BACKGROUND Cognitive flexibility refers to the capacity to shift between conceptual representations particularly in response to changes in instruction and feedback. It enables individuals to swiftly adapt to changes in their environment and has significant implications for learning. The present study focuses on investigating changes in cognitive flexibility following an intervention programme-Structure Learning training. METHODS Participants are pseudo-randomised to either the Training or Control group, while matched on age, sex, intelligence and cognitive flexibility performance. In the Training group, participants undergo around 2 weeks of training (at least 13 sessions) on Structure Learning. In the Control group, participants do not have to undergo any training and are never exposed to the Structure Learning task. The effects of Structure Learning training are investigated at both the behavioural and neural level. We measured covariates that can influence an individual's training performance before the training phase and outcome measures that can potentially show training benefits after the training phase. At the behavioural level, we investigated outcomes in both cognitive and social aspects with a primary focus on executive functions. At the neural level, we employed a multimodality approach and investigated potential changes to functional connectivity patterns, neurometabolite concentration in the frontal brain regions, and brain microstructure and myelination. DISCUSSION We reported the development of a novel training programme based on Structure Learning that aims to hone a general learning ability to potentially achieve extensive transfer benefits across various cognitive constructs. Potential transfer benefits can be exhibited through better performance in outcome measures between Training and Control participants, and positive associations between training performance and outcomes after the training in Training participants. Moreover, we attempt to substantiate behavioural findings with evidence of neural changes across different imaging modalities by the Structure Learning training. TRIAL REGISTRATION National Institutes of Health U.S. National Library of Medicine ClinicalTrials.gov NCT05611788. Registered on 7 November 2022. PROTOCOL VERSION 11 May 2023.
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Affiliation(s)
- Chia-Lun Liu
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore.
| | - Xiaoqin Cheng
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
- Department of Psychology, University of Innsbruck, Innsbruck, Austria
| | - Boon Linn Choo
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
| | - Min Hong
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
| | - Jia Li Teo
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
- School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Wei Ler Koo
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
| | - Jia Yuan Janet Tan
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
| | - Marisha Barth Ubrani
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
| | - John Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Balázs Gulyás
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Victoria Leong
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
- School of Social Sciences, Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
| | - Barbara Sahakian
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 0SZ, UK
| | - Trevor Robbins
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK
- Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, CB2 3EB, UK
| | - Annabel Shen-Hsing Chen
- Centre for Research and Development in Learning (CRADLE), Nanyang Technological University, Singapore, Singapore
- School of Social Sciences, Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- National Institute of Education, Nanyang Technological University, Singapore, Singapore
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10
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Hasan SM, Huq MS, Chowdury AZ, Baajour S, Kopchick J, Robison AJ, Thakkar KN, Haddad L, Amirsadri A, Thomas P, Khatib D, Rajan U, Stanley JA, Diwadkar VA. Learning without contingencies: A loss of synergy between memory and reward circuits in schizophrenia. Schizophr Res 2023; 258:21-35. [PMID: 37467677 PMCID: PMC10521382 DOI: 10.1016/j.schres.2023.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 02/09/2023] [Accepted: 06/11/2023] [Indexed: 07/21/2023]
Abstract
Motivational deficits in schizophrenia may interact with foundational cognitive processes including learning and memory to induce impaired cognitive proficiency. If such a loss of synergy exists, it is likely to be underpinned by a loss of synchrony between the brains learning and reward sub-networks. Moreover, this loss should be observed even during tasks devoid of explicit reward contingencies given that such tasks are better models of real world performance than those with artificial contingencies. Here we applied undirected functional connectivity (uFC) analyses to fMRI data acquired while participants engaged in an associative learning task without contingencies or feedback. uFC was estimated and inter-group differences (between schizophrenia patients and controls, n = 54 total, n = 28 patients) were assessed within and between reward (VTA and NAcc) and learning/memory (Basal Ganglia, DPFC, Hippocampus, Parahippocampus, Occipital Lobe) sub-networks. The task paradigm itself alternated between Encoding, Consolidation, and Retrieval conditions, and uFC differences were quantified for each of the conditions. Significantly reduced uFC dominated the connectivity profiles of patients across all conditions. More pertinent to our motivations, these reductions were observed within and across classes of sub-networks (reward-related and learning/memory related). We suggest that disrupted functional connectivity between reward and learning sub-networks may drive many of the performance deficits that characterize schizophrenia. Thus, cognitive deficits in schizophrenia may in fact be underpinned by a loss of synergy between reward-sensitivity and cognitive processes.
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Affiliation(s)
- Sazid M Hasan
- Oakland University William Beaumont School of Medicine, USA
| | - Munajj S Huq
- Michigan State University, College of Osteopathic Medicine, USA
| | - Asadur Z Chowdury
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Shahira Baajour
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - John Kopchick
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - A J Robison
- Dept. of Physiology, Michigan State University, USA
| | | | - Luay Haddad
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Alireza Amirsadri
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Patricia Thomas
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Dalal Khatib
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Usha Rajan
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Jeffrey A Stanley
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA
| | - Vaibhav A Diwadkar
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, USA.
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11
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Contò F, Tyler S, Paletta P, Battelli L. The role of the parietal lobe in task-irrelevant suppression during learning. Brain Stimul 2023; 16:715-723. [PMID: 37062348 DOI: 10.1016/j.brs.2023.04.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 04/07/2023] [Accepted: 04/13/2023] [Indexed: 04/18/2023] Open
Abstract
BACKGROUND Attention optimizes the selection of visual information, while suppressing irrelevant visual input through cortical mechanisms that are still unclear. We set to investigate these processes using an attention task with an embedded to-be-ignored interfering visual input. OBJECTIVE We delivered electrical stimulation to attention-related brain areas to modulate these facilitatory/inhibitory attentional mechanisms. We asked whether overtly training on a task while being covertly exposed to visual features from a visually identical but different task tested at baseline might influence post-training performance on the baseline task. METHODS In Experiment one, at baseline subjects performed an orientation discrimination (OD) task using a pair of gratings presented at individual's psychophysical threshold. We then trained participants over three-day separate sessions on a temporal order judgment task (TOJ), using the exact same gratings but presented with different time offsets. On the last post-training session we re-tested OD. We coupled training with transcranial random noise stimulation (tRNS) over the parietal cortex, the human middle temporal area or sham, in three separate groups. In Experiment two, subjects performed the same OD task at baseline and post-training, while tRNS was delivered at rest during the same sessions and stimulation conditions as in Experiment one. RESULTS Results showed that tRNS over parietal cortex facilitated learning of the trained TOJ task. Moreover, we found a detrimental effect on the untrained OD task when subjects received parietal tRNS coupled with training (Experiment one), but a benefit on OD when subjects received stimulation while at rest (Experiment two). CONCLUSIONS These results clearly indicate that task-irrelevant information is actively suppressed during learning, and that this prioritization mechanism of selection likely resides in the parietal cortex.
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Affiliation(s)
- F Contò
- Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068, Rovereto (TN), Italy.
| | - S Tyler
- Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068, Rovereto (TN), Italy; Butte College, Oroville, CA, 95965, USA
| | - P Paletta
- Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068, Rovereto (TN), Italy
| | - L Battelli
- Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068, Rovereto (TN), Italy; Department of Neurology, Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA; Department of Psychology, Harvard University, Cambridge, MA, 01238, USA.
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12
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Michael E, Covarrubias LS, Leong V, Kourtzi Z. Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions. Cereb Cortex 2023; 33:5382-5394. [PMID: 36352510 PMCID: PMC10152088 DOI: 10.1093/cercor/bhac426] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 09/24/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022] Open
Abstract
Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.
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Affiliation(s)
- Elizabeth Michael
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
| | | | - Victoria Leong
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
- Psychology, School of Social Sciences, Nanyang Technological University (NTU), Singapore 6398818, Singapore
- Lee Kong Chian School of Medicine, NTU, Singapore 308232, Singapore
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
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13
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Ziminski JJ, Frangou P, Karlaftis VM, Emir U, Kourtzi Z. Microstructural and neurochemical plasticity mechanisms interact to enhance human perceptual decision-making. PLoS Biol 2023; 21:e3002029. [PMID: 36897881 PMCID: PMC10032544 DOI: 10.1371/journal.pbio.3002029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 03/22/2023] [Accepted: 02/08/2023] [Indexed: 03/11/2023] Open
Abstract
Experience and training are known to boost our skills and mold the brain's organization and function. Yet, structural plasticity and functional neurotransmission are typically studied at different scales (large-scale networks, local circuits), limiting our understanding of the adaptive interactions that support learning of complex cognitive skills in the adult brain. Here, we employ multimodal brain imaging to investigate the link between microstructural (myelination) and neurochemical (GABAergic) plasticity for decision-making. We test (in males, due to potential confounding menstrual cycle effects on GABA measurements in females) for changes in MRI-measured myelin, GABA, and functional connectivity before versus after training on a perceptual decision task that involves identifying targets in clutter. We demonstrate that training alters subcortical (pulvinar, hippocampus) myelination and its functional connectivity to visual cortex and relates to decreased visual cortex GABAergic inhibition. Modeling interactions between MRI measures of myelin, GABA, and functional connectivity indicates that pulvinar myelin plasticity interacts-through thalamocortical connectivity-with GABAergic inhibition in visual cortex to support learning. Our findings propose a dynamic interplay of adaptive microstructural and neurochemical plasticity in subcortico-cortical circuits that supports learning for optimized decision-making in the adult human brain.
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Affiliation(s)
- Joseph J Ziminski
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Polytimi Frangou
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Vasilis M Karlaftis
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, Indiana, United States of America
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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14
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Wu D, Zhang P, Wang Y, Liu N, Sun K, Wang P, Xiao W. Anodal online transcranial direct current stimulation facilitates visual motion perceptual learning. Eur J Neurosci 2023; 57:479-489. [PMID: 36511948 DOI: 10.1111/ejn.15895] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 12/07/2022] [Accepted: 12/08/2022] [Indexed: 12/15/2022]
Abstract
Visual perceptual learning (VPL) has great potential implications for clinical populations, but adequate improvement often takes weeks to months to obtain; therefore, practical applications of VPL are limited. Strategies that enhance visual performance acquisition make great practical sense. Transcranial direct current stimulation (tDCS) could be beneficial to VPL, but thus far, the results are inconsistent. The current study had two objectives: (1) to investigate the effect of anodal tDCS on VPL and (2) to determine whether the timing sequence of anodal tDCS and training influences VPL. Anodal tDCS was applied on the left human middle temporal (hMT+) during training on a coherent motion discrimination task (online), anodal tDCS was also applied before training (offline) and sham tDCS was applied during training (sham). The coherent thresholds were measured without stimulation before, 2 days after and 1 month after training. All participants trained for five consecutive days. Anodal tDCS resulted in more performance improvement when applied during daily training but not when applied before training. Additionally, neither within-session improvement nor between-session improvement differed among the online, offline and sham tDCS conditions. These findings contribute to the development of efficient stimulation protocols and a deep understanding of the mechanisms underlying the effect of tDCS on VPL.
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Affiliation(s)
- Di Wu
- Department of Medical Psychology, Air Force Medical University, Xi'an, China
- Department of Neurobiology, Basic Medical School, Air Force Medical University, Xi'an, China
| | - Pan Zhang
- Department of Psychology, Hebei Normal University, Shijiazhuang, China
| | - Yifan Wang
- Department of Medical Psychology, Air Force Medical University, Xi'an, China
| | - Na Liu
- Department of Nursing, Air Force Medical University, Xi'an, China
| | - Kewei Sun
- Department of Medical Psychology, Air Force Medical University, Xi'an, China
| | - Panhui Wang
- Department of Medical Psychology, Air Force Medical University, Xi'an, China
| | - Wei Xiao
- Department of Medical Psychology, Air Force Medical University, Xi'an, China
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15
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He Q, Yang XY, Zhao D, Fang F. Enhancement of visual perception by combining transcranial electrical stimulation and visual perceptual training. MEDICAL REVIEW (BERLIN, GERMANY) 2022; 2:271-284. [PMID: 37724187 PMCID: PMC10388778 DOI: 10.1515/mr-2022-0010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 06/16/2022] [Indexed: 09/20/2023]
Abstract
The visual system remains highly malleable even after its maturity or impairment. Our visual function can be enhanced through many ways, such as transcranial electrical stimulation (tES) and visual perceptual learning (VPL). TES can change visual function rapidly, but its modulation effect is short-lived and unstable. By contrast, VPL can lead to a substantial and long-lasting improvement in visual function, but extensive training is typically required. Theoretically, visual function could be further improved in a shorter time frame by combining tES and VPL than by solely using tES or VPL. Vision enhancement by combining these two methods concurrently is both theoretically and practically significant. In this review, we firstly introduced the basic concept and possible mechanisms of VPL and tES; then we reviewed the current research progress of visual enhancement using the combination of two methods in both general and clinical population; finally, we discussed the limitations and future directions in this field. Our review provides a guide for future research and application of vision enhancement and restoration by combining VPL and tES.
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Affiliation(s)
- Qing He
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Xin-Yue Yang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Daiqing Zhao
- Department of Psychology, The Pennsylvania State University, University Park, State College, PA, USA
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
- Key Laboratory of Machine Perception, Ministry of Education, Peking University, Beijing, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
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16
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Frangou P, Clarke WT. Where functional MRI stops, metabolism starts. eLife 2022; 11:78327. [PMID: 35467531 PMCID: PMC9038188 DOI: 10.7554/elife.78327] [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] [Indexed: 11/13/2022] Open
Abstract
Combining techniques that track blood oxygenation and biochemicals during neuronal activity reveals how the brain computes perceived and unperceived stimuli.
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Affiliation(s)
- Polytimi Frangou
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
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17
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Liu X, Zou X, Ji Z, Tian G, Mi Y, Huang T, Michael Wong K, Wu S. Neural feedback facilitates rough-to-fine information retrieval. Neural Netw 2022; 151:349-364. [DOI: 10.1016/j.neunet.2022.03.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 03/08/2022] [Accepted: 03/29/2022] [Indexed: 10/18/2022]
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18
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Jia K, Frangou P, Karlaftis VM, Ziminski JJ, Giorgio J, Rideaux R, Zamboni E, Hodgson V, Emir U, Kourtzi Z. Neurochemical and functional interactions for improved perceptual decisions through training. J Neurophysiol 2022; 127:900-912. [PMID: 35235415 PMCID: PMC8977131 DOI: 10.1152/jn.00308.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 02/11/2022] [Accepted: 02/28/2022] [Indexed: 11/22/2022] Open
Abstract
Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.
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Affiliation(s)
- Ke Jia
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Polytimi Frangou
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Vasilis M Karlaftis
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Joseph J Ziminski
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Joseph Giorgio
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Reuben Rideaux
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Victoria Hodgson
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
| | - Uzay Emir
- Purdue University School of Health Sciences, West Lafayette, Indiana
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, United Kingdom
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19
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Mechanisms of Surround Suppression Effect on the Contrast Sensitivity of V1 Neurons in Cats. Neural Plast 2022; 2022:5677655. [PMID: 35299618 PMCID: PMC8923783 DOI: 10.1155/2022/5677655] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 01/30/2022] [Accepted: 02/19/2022] [Indexed: 12/14/2022] Open
Abstract
Surround suppression (SS) is a phenomenon that a neuron’s response to visual stimuli within the classical receptive field (cRF) is suppressed by a concurrent stimulation in the surrounding receptive field (sRF) beyond the cRF. Studies show that SS affects neuronal response contrast sensitivity in the primary visual cortex (V1). However, the underlying mechanisms remain unclear. Here, we examined SS effect on the contrast sensitivity of cats’ V1 neurons with different preferred SFs using external noise-masked visual stimuli and perceptual template model (PTM) analysis at the system level. The contrast sensitivity was evaluated by the inverted threshold contrast of neurons in response to circular gratings of different contrasts in the cRF with or without an annular grating in the sRF. Our results showed that SS significantly reduced the contrast sensitivity of cats’ V1 neurons. The SS-induced reduction of contrast sensitivity was not correlated with SS strength but was dependent on neuron’s preferred SF, with a larger reduction for neurons with low preferred SFs than those with high preferred SFs. PTM analysis of threshold versus external noise contrast (TvC) functions indicated that SS decreased contrast sensitivity by increasing both the internal additive noise and impact of external noise for neurons with low preferred SFs, but improving only internal additive noise for neurons with high preferred SFs. Furthermore, the SS effect on the contrast-response function of low- and high-SF neurons also exhibited different mechanisms in contrast gain and response gain. Collectively, these results suggest that the mechanisms of SS effect on neuronal contrast sensitivity may depend on neuronal populations with different SFs.
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20
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Boosting visual perceptual learning by transcranial alternating current stimulation over the visual cortex at alpha frequency. Brain Stimul 2022; 15:546-553. [DOI: 10.1016/j.brs.2022.02.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 11/17/2022] Open
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21
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Ekhtiari H, Ghobadi-Azbari P, Thielscher A, Antal A, Li LM, Shereen AD, Cabral-Calderin Y, Keeser D, Bergmann TO, Jamil A, Violante IR, Almeida J, Meinzer M, Siebner HR, Woods AJ, Stagg CJ, Abend R, Antonenko D, Auer T, Bächinger M, Baeken C, Barron HC, Chase HW, Crinion J, Datta A, Davis MH, Ebrahimi M, Esmaeilpour Z, Falcone B, Fiori V, Ghodratitoostani I, Gilam G, Grabner RH, Greenspan JD, Groen G, Hartwigsen G, Hauser TU, Herrmann CS, Juan CH, Krekelberg B, Lefebvre S, Liew SL, Madsen KH, Mahdavifar-Khayati R, Malmir N, Marangolo P, Martin AK, Meeker TJ, Ardabili HM, Moisa M, Momi D, Mulyana B, Opitz A, Orlov N, Ragert P, Ruff CC, Ruffini G, Ruttorf M, Sangchooli A, Schellhorn K, Schlaug G, Sehm B, Soleimani G, Tavakoli H, Thompson B, Timmann D, Tsuchiyagaito A, Ulrich M, Vosskuhl J, Weinrich CA, Zare-Bidoky M, Zhang X, Zoefel B, Nitsche MA, Bikson M. A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement. Nat Protoc 2022; 17:596-617. [PMID: 35121855 PMCID: PMC7612687 DOI: 10.1038/s41596-021-00664-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 11/12/2021] [Indexed: 11/09/2022]
Abstract
Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. The objective of this work was to develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency and reproducibility (ContES checklist). A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists through the International Network of the tES-fMRI Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC on the basis of a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed by using the checklist. Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (i) technological factors, (ii) safety and noise tests and (iii) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. In conclusion, use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies and increase methodological transparency and reproducibility.
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Affiliation(s)
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Andrea Antal
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Lucia M Li
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, London, UK
| | - A Duke Shereen
- Advanced Science Research Center, The Graduate Center, City University of New York, New York, NY, USA
| | - Yuranny Cabral-Calderin
- Research Group Neural and Environmental Rhythms, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany
- Department of Radiology, University Hospital LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU Munich, Munich, Germany
| | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
- Department of Neurology and Stroke and Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Asif Jamil
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Jorge Almeida
- Proaction Lab, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
- CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Marcus Meinzer
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rany Abend
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA
| | - Daria Antonenko
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Tibor Auer
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Marc Bächinger
- Neural Control of Movement Lab, Department of Health Sciences and Technology, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Chris Baeken
- Department of Psychiatry and Medical Psychology, University Hospital Ghent, Ghent, Belgium
- Department of Psychiatry, Vrije Universiteit Brussel, University Hospital Brussels, Brussels, Belgium
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Helen C Barron
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jenny Crinion
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Abhishek Datta
- Research and Development, Soterix Medical, New York, USA
- The City College of the City University of New York, New York, USA
| | - Matthew H Davis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Mohsen Ebrahimi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
| | - Brian Falcone
- Northrop Grumman Company, Mission Systems, Falls Church, VA, USA
| | - Valentina Fiori
- Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Iman Ghodratitoostani
- Neurocognitive Engineering Laboratory (NEL), Center for Engineering Applied to Health, Institute of Mathematics and Computer Science (ICMC), University of Sao Paulo, Sao Paulo, Brazil
| | - Gadi Gilam
- Systems Neuroscience and Pain Laboratory, Division of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA
- The Institute of Biomedical and Oral Research, Faculty of Dental Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Roland H Grabner
- Educational Neuroscience, Institute of Psychology, University of Graz, Graz, Austria
| | - Joel D Greenspan
- Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, USA
| | - Georg Groen
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Christoph S Herrmann
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
- Neuroimaging Unit, European Medical School, University of Oldenburg, Oldenburg, Germany
- Research Centre Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA
| | - Stephanie Lefebvre
- Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Sook-Lei Liew
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
- Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA
| | - Kristoffer H Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, K, Lyngby, Denmark
| | | | - Nastaran Malmir
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Paola Marangolo
- Department of Humanities Studies, University Federico II, Naples, Italy
- Aphasia Research Lab, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Andrew K Martin
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Psychology, University of Kent, Canterbury, UK
| | - Timothy J Meeker
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Hossein Mohaddes Ardabili
- Psychiatry and Behavioral Sciences Research Center, Ibn-e-Sina Hospital, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Marius Moisa
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Davide Momi
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Natasza Orlov
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Department of Psychology, Jagiellonian University, Cracow, Poland
| | - Patrick Ragert
- Institute for General Kinesiology and Exercise Science, University of Leipzig, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian C Ruff
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Giulio Ruffini
- Neuroelectrics Corporation, Cambridge, Cambridge, MA, USA
- Neuroelectrics Corporation, Barcelona, Barcelona, Spain
| | - Michaela Ruttorf
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arshiya Sangchooli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Gottfried Schlaug
- Neuroimaging-Neuromodulation and Stroke Recovery Laboratories, Department of Neurology, Baystate-University of Massachusetts Medical School, and Department of Biomedical Engineering, Institute of Applied Life Sciences, University of Massachusetts, Amherst, MA, USA
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Ghazaleh Soleimani
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Hosna Tavakoli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Department of Cognitive Neuroscience, Institute for Cognitive Sciences Studies, Tehran, Iran
| | - Benjamin Thompson
- School of Optometry and Vision Science, University of Auckland, Auckland, New Zealand
- School of Optometry and Vision Science, University of Waterloo, Waterloo, Ontario, Canada
- Centre for Eye and Vision Research, Hong Kong, Hong Kong
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | | | - Martin Ulrich
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Johannes Vosskuhl
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Christiane A Weinrich
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
- Department of Cognitive Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Mehran Zare-Bidoky
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Shahid-Sadoughi University of Medical Sciences, Yazd, Iran
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, China
| | - Benedikt Zoefel
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Centre de Recherche Cerveau et Cognition (CerCo), CNRS, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
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22
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Yang XY, He Q, Fang F. Transcranial direct current stimulation over the visual cortex facilitates awake consolidation of visual perceptual learning. Brain Stimul 2022; 15:380-382. [PMID: 35123143 DOI: 10.1016/j.brs.2022.01.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 11/02/2022] Open
Affiliation(s)
- Xin-Yue Yang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, China; Key Laboratory of Machine Perception, Ministry of Education, China; IDG/McGovern Institute for Brain Research, USA; Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China
| | - Qing He
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, China; Key Laboratory of Machine Perception, Ministry of Education, China; IDG/McGovern Institute for Brain Research, USA; Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, China; Key Laboratory of Machine Perception, Ministry of Education, China; IDG/McGovern Institute for Brain Research, USA; Peking-Tsinghua Center for Life Sciences, Peking University, 100871, Beijing, China.
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23
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Song Y, Lally PJ, Yanez Lopez M, Oeltzschner G, Nebel MB, Gagoski B, Kecskemeti S, Hui SCN, Zöllner HJ, Shukla D, Arichi T, De Vita E, Yedavalli V, Thayyil S, Fallin D, Dean DC, Grant PE, Wisnowski JL, Edden RAE. Edited magnetic resonance spectroscopy in the neonatal brain. Neuroradiology 2022; 64:217-232. [PMID: 34654960 PMCID: PMC8887832 DOI: 10.1007/s00234-021-02821-9] [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: 07/13/2021] [Accepted: 09/20/2021] [Indexed: 10/20/2022]
Abstract
J-difference-edited spectroscopy is a valuable approach for the detection of low-concentration metabolites with magnetic resonance spectroscopy (MRS). Currently, few edited MRS studies are performed in neonates due to suboptimal signal-to-noise ratio, relatively long acquisition times, and vulnerability to motion artifacts. Nonetheless, the technique presents an exciting opportunity in pediatric imaging research to study rapid maturational changes of neurotransmitter systems and other metabolic systems in early postnatal life. Studying these metabolic processes is vital to understanding the widespread and rapid structural and functional changes that occur in the first years of life. The overarching goal of this review is to provide an introduction to edited MRS for neonates, including the current state-of-the-art in editing methods and editable metabolites, as well as to review the current literature applying edited MRS to the neonatal brain. Existing challenges and future opportunities, including the lack of age-specific reference data, are also discussed.
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Affiliation(s)
- Yulu Song
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Peter J Lally
- Department of Brain Sciences, Imperial College London, London, UK
| | - Maria Yanez Lopez
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Borjan Gagoski
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | | | - Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Deepika Shukla
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Tomoki Arichi
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Department of Bioengineering, Imperial College London, South Kensington Campus, London, UK
| | - Enrico De Vita
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.,Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, St Thomas's Hospital, Westminster Bridge Road, Lambeth Wing, 3rd Floor, London, SE1 7EH, UK
| | - Vivek Yedavalli
- Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA
| | - Sudhin Thayyil
- Centre for Perinatal Neuroscience, Department of Brain Sciences, Imperial College London, London, UK
| | - Daniele Fallin
- Wendy Klag Center for Autism and Developmental Disabilities, Johns Hopkins University, Baltimore, USA.,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
| | - Douglas C Dean
- Waisman Center, University of WI-Madison, Madison, WI, 53705, USA.,Department of Pediatrics, Division of Neonatology and Newborn Nursery, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA.,Department of Medical Physics, University of WI-Madison, School of Medicine and Public Health, Madison, WI, 53705, USA
| | - P Ellen Grant
- Department of Radiology, Division of Neuroradiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Medicine, Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jessica L Wisnowski
- Children's Hospital Los Angeles, Los Angeles, CA, 90027, USA.,Department of Radiology and Fetal and Neonatal Institute, CHLA Division of Neonatology, Department of Pediatrics, Children's Hospital of Los Angeles, University of Southern California, Los Angeles, CA, 90033, USA
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA. .,Division of Neuroradiology, Park 367G, The Johns Hopkins University School of Medicine, 600 N. Wolfe St. B-112 D, Baltimore, MD, 21287, USA.
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24
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Karlaftis VM, Giorgio J, Zamboni E, Frangou P, Rideaux R, Ziminski JJ, Kourtzi Z. Functional Interactions between Sensory and Memory Networks for Adaptive Behavior. Cereb Cortex 2021; 31:5319-5330. [PMID: 34185848 PMCID: PMC8568003 DOI: 10.1093/cercor/bhab160] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/12/2021] [Accepted: 05/12/2021] [Indexed: 11/13/2022] Open
Abstract
The brain's capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown. Here, we combine multimodal brain imaging (functional magnetic resonance imaging [fMRI], magnetic resonance spectroscopy) with behavioral measures of orientation-specific adaptation (i.e., tilt aftereffect) to investigate the functional and neurochemical mechanisms that support adaptive processing. Our results reveal two functional brain networks: 1) a sensory-adaptation network including occipital and dorsolateral prefrontal cortex regions that show decreased fMRI responses for repeated stimuli and 2) a perceptual-memory network including regions in the parietal memory network (PMN) and dorsomedial prefrontal cortex that relate to perceptual bias (i.e., tilt aftereffect). We demonstrate that adaptation relates to increased occipito-parietal connectivity, while decreased connectivity between sensory-adaptation and perceptual-memory networks relates to GABAergic inhibition in the PMN. Thus, our findings provide evidence that suppressive interactions between sensory-adaptation (i.e., occipito-parietal) and perceptual-memory (i.e., PMN) networks support adaptive processing and behavior, proposing a key role of memory systems in efficient sensory processing.
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Affiliation(s)
| | - Joseph Giorgio
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Elisa Zamboni
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Polytimi Frangou
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Reuben Rideaux
- Department of Psychology, University of Cambridge, Cambridge, UK
| | | | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Cambridge, UK
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25
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Zacharopoulos G, Sella F, Emir U, Cohen Kadosh R. The relation between parietal GABA concentration and numerical skills. Sci Rep 2021; 11:17656. [PMID: 34480033 PMCID: PMC8417296 DOI: 10.1038/s41598-021-95370-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 05/12/2021] [Indexed: 11/21/2022] Open
Abstract
Several scientific, engineering, and medical advancements are based on breakthroughs made by people who excel in mathematics. Our current understanding of the underlying brain networks stems primarily from anatomical and functional investigations, but our knowledge of how neurotransmitters subserve numerical skills, the building block of mathematics, is scarce. Using 1H magnetic resonance spectroscopy (N = 54, 3T, semi-LASER sequence, TE = 32 ms, TR = 3.5 s), the study examined the relation between numerical skills and the brain's major inhibitory (GABA) and excitatory (glutamate) neurotransmitters. A negative association was found between the performance in a number sequences task and the resting concentration of GABA within the left intraparietal sulcus (IPS), a key region supporting numeracy. The relation between GABA in the IPS and number sequences was specific to (1) parietal but not frontal regions and to (2) GABA but not glutamate. It was additionally found that the resting functional connectivity of the left IPS and the left superior frontal gyrus was positively associated with number sequences performance. However, resting GABA concentration within the IPS explained number sequences performance above and beyond the resting frontoparietal connectivity measure. Our findings further motivate the study of inhibition mechanisms in the human brain and significantly contribute to our current understanding of numerical cognition's biological bases.
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Affiliation(s)
- George Zacharopoulos
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
- Department of Psychology, Swansea University, Swansea, UK.
| | - Francesco Sella
- Centre for Mathematical Cognition, Loughborough University, Loughborough, UK
| | - Uzay Emir
- School of Health Sciences, College of Health and Human Sciences, Purdue University, West Lafayette, IN, 47907-2051, USA
| | - Roi Cohen Kadosh
- Department of Experimental Psychology, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK.
- School of Psychology, University of Surrey, Guildford, UK.
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26
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Tandoc MC, Bayda M, Poskanzer C, Cho E, Cox R, Stickgold R, Schapiro AC. Examining the effects of time of day and sleep on generalization. PLoS One 2021; 16:e0255423. [PMID: 34339459 PMCID: PMC8328323 DOI: 10.1371/journal.pone.0255423] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 07/16/2021] [Indexed: 12/26/2022] Open
Abstract
Extracting shared structure across our experiences allows us to generalize our knowledge to novel contexts. How do different brain states influence this ability to generalize? Using a novel category learning paradigm, we assess the effect of both sleep and time of day on generalization that depends on the flexible integration of recent information. Counter to our expectations, we found no evidence that this form of generalization is better after a night of sleep relative to a day awake. Instead, we observed an effect of time of day, with better generalization in the morning than the evening. This effect also manifested as increased false memory for generalized information. In a nap experiment, we found that generalization did not benefit from having slept recently, suggesting a role for time of day apart from sleep. In follow-up experiments, we were unable to replicate the time of day effect for reasons that may relate to changes in category structure and task engagement. Despite this lack of consistency, we found a morning benefit for generalization when analyzing all the data from experiments with matched protocols (n = 136). We suggest that a state of lowered inhibition in the morning may facilitate spreading activation between otherwise separate memories, promoting this form of generalization.
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Affiliation(s)
- Marlie C. Tandoc
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Mollie Bayda
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychology, University of California-Los Angeles, Los Angeles, California, United States of America
| | - Craig Poskanzer
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Psychology and Neuroscience, Boston College, Chestnut Hill, Massachusetts, United States of America
| | - Eileen Cho
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
| | - Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
| | - Anna C. Schapiro
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Psychiatry, Beth Israel Deaconess Medical Center / Harvard Medical School, Boston, Massachusetts, United States of America
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27
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Zacharopoulos G, Sella F, Cohen Kadosh K, Hartwright C, Emir U, Cohen Kadosh R. Predicting learning and achievement using GABA and glutamate concentrations in human development. PLoS Biol 2021; 19:e3001325. [PMID: 34292934 PMCID: PMC8297926 DOI: 10.1371/journal.pbio.3001325] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Accepted: 06/15/2021] [Indexed: 11/25/2022] Open
Abstract
Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in learning and plasticity. What is currently unknown is how this knowledge translates to real-life complex cognitive abilities that emerge slowly and how the link between these neurotransmitters and human learning and plasticity is shaped by development. While some have suggested a generic role of glutamate and GABA in learning and plasticity, others have hypothesized that their involvement shapes sensitive periods during development. Here we used a cross-sectional longitudinal design with 255 individuals (spanning primary school to university) to show that glutamate and GABA in the intraparietal sulcus explain unique variance both in current and future mathematical achievement (approximately 1.5 years). Furthermore, our findings reveal a dynamic and dissociable role of GABA and glutamate in predicting learning, which is reversed during development, and therefore provide novel implications for models of learning and plasticity during childhood and adulthood.
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Affiliation(s)
- George Zacharopoulos
- Department of Experimental Psychology, University of Oxford, United Kingdom
- Department of Psychology, Swansea University, United Kingdom
| | - Francesco Sella
- Department of Experimental Psychology, University of Oxford, United Kingdom
- Centre for Mathematical Cognition, Loughborough University, United Kingdom
| | - Kathrin Cohen Kadosh
- Department of Experimental Psychology, University of Oxford, United Kingdom
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Charlotte Hartwright
- Department of Experimental Psychology, University of Oxford, United Kingdom
- School of Psychology, Aston University, United Kingdom
| | - Uzay Emir
- Department of Experimental Psychology, University of Oxford, United Kingdom
- School of Health Sciences, College of Health and Human Sciences, Purdue University, United States of America
| | - Roi Cohen Kadosh
- Department of Experimental Psychology, University of Oxford, United Kingdom
- School of Psychology, University of Surrey, Guildford, United Kingdom
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28
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Zacharopoulos G, Sella F, Cohen Kadosh R. The impact of a lack of mathematical education on brain development and future attainment. Proc Natl Acad Sci U S A 2021; 118:e2013155118. [PMID: 34099561 PMCID: PMC8214709 DOI: 10.1073/pnas.2013155118] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Formal education has a long-term impact on an individual's life. However, our knowledge of the effect of a specific lack of education, such as in mathematics, is currently poor but is highly relevant given the extant differences between countries in their educational curricula and the differences in opportunities to access education. Here we examined whether neurotransmitter concentrations in the adolescent brain could classify whether a student is lacking mathematical education. Decreased γ-aminobutyric acid (GABA) concentration within the middle frontal gyrus (MFG) successfully classified whether an adolescent studies math and was negatively associated with frontoparietal connectivity. In a second experiment, we uncovered that our findings were not due to preexisting differences before a mathematical education ceased. Furthermore, we showed that MFG GABA not only classifies whether an adolescent is studying math or not, but it also predicts the changes in mathematical reasoning ∼19 mo later. The present results extend previous work in animals that has emphasized the role of GABA neurotransmission in synaptic and network plasticity and highlight the effect of a specific lack of education on MFG GABA concentration and learning-dependent plasticity. Our findings reveal the reciprocal effect between brain development and education and demonstrate the negative consequences of a specific lack of education during adolescence on brain plasticity and cognitive functions.
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Affiliation(s)
- George Zacharopoulos
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom;
| | - Francesco Sella
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom
- Centre for Mathematical Cognition, Loughborough University, Loughborough LE11 3TU, United Kingdom
| | - Roi Cohen Kadosh
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, United Kingdom;
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29
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Chen G, Zhu Z, He Q, Fang F. Offline transcranial direct current stimulation improves the ability to perceive crowded targets. J Vis 2021; 21:1. [PMID: 33533878 PMCID: PMC7862736 DOI: 10.1167/jov.21.2.1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
The deleterious effect of nearby flankers on target identification in the periphery is known as visual crowding. Studying visual crowding can advance our understanding of the mechanisms of visual awareness and object recognition. Alleviating visual crowding is one of the major ways to improve peripheral vision. The aim of the current study was to examine whether transcranial direct current stimulation (tDCS) was capable of alleviating visual crowding at different visual eccentricities and with different visual tasks. In the present single-blind sham-controlled study, subjects were instructed to perform an orientation discrimination task or a letter identification task with isolated and crowded targets in the periphery, before and after applying 20 minutes of 2 mA anodal tDCS to visual cortex of the hemisphere contralateral or ipsilateral to visual stimuli. Contralateral tDCS significantly alleviated the orientation crowding effect at two different eccentricities and the letter crowding effect. This alleviation was absent after sham or ipsilateral stimulation and could not be fully explained by the performance improvement with the isolated targets. These findings demonstrated that offline tDCS was effective in alleviating visual crowding across different visual eccentricities and tasks, therefore providing a promising way to improve spatial vision rapidly in crowded scenes.
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Affiliation(s)
- Guanpeng Chen
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, People's Republic of China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, People's Republic of China.,
| | - Ziyun Zhu
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, People's Republic of China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, People's Republic of China.,
| | - Qing He
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, People's Republic of China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, People's Republic of China.,
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, People's Republic of China.,IDG/McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, People's Republic of China.,
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30
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Ip IB, Bridge H. Investigating the neurochemistry of the human visual system using magnetic resonance spectroscopy. Brain Struct Funct 2021; 227:1491-1505. [PMID: 33900453 PMCID: PMC9046312 DOI: 10.1007/s00429-021-02273-0] [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: 01/26/2021] [Accepted: 04/09/2021] [Indexed: 11/29/2022]
Abstract
Biochemical processes underpin the structure and function of the visual cortex, yet our understanding of the fundamental neurochemistry of the visual brain is incomplete. Proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive brain imaging tool that allows chemical quantification of living tissue by detecting minute differences in the resonant frequency of molecules. Application of MRS in the human brain in vivo has advanced our understanding of how the visual brain consumes energy to support neural function, how its neural substrates change as a result of disease or dysfunction, and how neural populations signal during perception and plasticity. The aim of this review is to provide an entry point to researchers interested in investigating the neurochemistry of the visual system using in vivo measurements. We provide a basic overview of MRS principles, and then discuss recent findings in four topics of vision science: (i) visual perception, plasticity in the (ii) healthy and (iii) dysfunctional visual system, and (iv) during visual stimulation. Taken together, evidence suggests that the neurochemistry of the visual system provides important novel insights into how we perceive the world.
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Affiliation(s)
- I Betina Ip
- Wellcome Centre for Integrative Neuroimaging, FMRIB Building, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Holly Bridge
- Wellcome Centre for Integrative Neuroimaging, FMRIB Building, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DU, UK.
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fMRI and transcranial electrical stimulation (tES): A systematic review of parameter space and outcomes. Prog Neuropsychopharmacol Biol Psychiatry 2021; 107:110149. [PMID: 33096158 DOI: 10.1016/j.pnpbp.2020.110149] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/09/2020] [Revised: 08/12/2020] [Accepted: 10/17/2020] [Indexed: 12/12/2022]
Abstract
The combination of non-invasive brain stimulation interventions with human brain mapping methods have supported research beyond correlational associations between brain activity and behavior. Functional MRI (fMRI) partnered with transcranial electrical stimulation (tES) methods, i.e., transcranial direct current (tDCS), transcranial alternating current (tACS), and transcranial random noise (tRNS) stimulation, explore the neuromodulatory effects of tES in the targeted brain regions and their interconnected networks and provide opportunities for individualized interventions. Advances in the field of tES-fMRI can be hampered by the methodological variability between studies that confounds comparability/replicability. In order to explore variability in the tES-fMRI methodological parameter space (MPS), we conducted a systematic review of 222 tES-fMRI experiments (181 tDCS, 39 tACS and 2 tRNS) published before February 1, 2019, and suggested a framework to systematically report main elements of MPS across studies. Publications dedicated to tRNS-fMRI were not considered in this systematic review. We have organized main findings in terms of fMRI modulation by tES. tES modulates activation and connectivity beyond the stimulated areas particularly with prefrontal stimulation. There were no two studies with the same MPS to replicate findings. We discuss how to harmonize the MPS to promote replication in future studies.
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Levi DM, Li RW, Silver MA, Chung STL. Sequential perceptual learning of letter identification and "uncrowding" in normal peripheral vision: Effects of task, training order, and cholinergic enhancement. J Vis 2021; 20:24. [PMID: 32347910 PMCID: PMC7405719 DOI: 10.1167/jov.20.4.24] [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] [Indexed: 11/24/2022] Open
Abstract
Human adults with normal vision are capable of improving performance on visual tasks through repeated practice. Previous work has shown that enhancing synaptic levels of acetylcholine (ACh) in healthy human adults with donepezil (trade name: Aricept) can increase the magnitude and specificity of perceptual learning (PL) for motion direction discrimination in the perifovea. In the current study, we ask whether increasing the synaptic levels of ACh in healthy human adults with donepezil boosts learning of low-contrast isolated letter identification and high-contrast flanked letter identification in normal peripheral vision. Two groups of observers performed sequential training over multiple days while ingesting donepezil. One group trained on isolated low-contrast letters in Phase 1 and crowded high-contrast letters in Phase 2, and the other group performed the reverse sequence, thereby enabling us to differentiate possible effects of drug and training order on PL of letter identification. All testing and training were performed monocularly in peripheral vision, at an eccentricity of 10 degrees along the lower vertical meridian. Our experimental design allowed us to evaluate the effects of sequential training and to ask whether increasing cholinergic signaling boosted learning and/or transfer of low-contrast isolated letter identification and high-contrast flanked letter identification in normal peripheral vision. We found that both groups improved on each of the two tasks. However, our results revealed an effect of training task order on flanked letter identification: Observers who trained on isolated targets first showed rapid early improvement in flanked letter identification but little to no additional improvement after 30 training blocks, while observers who first trained with flanked letters improved gradually on flanked letter identification over the entire 100-block course of training. In addition, we found no effect of donepezil on PL of either isolated or flanked letter identification. In other words, donepezil neither boosted nor blocked learning to identify isolated low-contrast letters or learning to uncrowd in normal peripheral vision.
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Ehrhardt SE, Filmer HL, Wards Y, Mattingley JB, Dux PE. The influence of tDCS intensity on decision-making training and transfer outcomes. J Neurophysiol 2020; 125:385-397. [PMID: 33174483 DOI: 10.1152/jn.00423.2020] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
Transcranial direct current stimulation (tDCS) has been shown to improve single- and dual-task performance in healthy participants and enhance transferable training gains following multiple sessions of combined stimulation and task practice. However, it has yet to be determined what the optimal stimulation dose is for facilitating such outcomes. We aimed to test the effects of different tDCS intensities, with a commonly used electrode montage, on performance outcomes in a multisession single/dual-task training and transfer protocol. In a preregistered study, 123 participants, who were pseudorandomized across four groups, each completed six sessions (pre- and posttraining sessions and four combined tDCS and training sessions) and received 20 min of prefrontal anodal tDCS at 0.7, 1.0, or 2.0 mA or 15-s sham stimulation. Response time and accuracy were assessed in trained and untrained tasks. The 1.0-mA group showed substantial improvements in single-task reaction time and dual-task accuracy, with additional evidence for improvements in dual-task reaction times, relative to sham performance. This group also showed near transfer to the single-task component of an untrained multitasking paradigm. The 0.7- and 2.0-mA intensities varied in which performance measures they improved on the trained task, but in sum, the effects were less robust than for the 1.0-mA group, and there was no evidence for the transfer of performance. Our study highlights that training performance gains are augmented by tDCS, but their magnitude and nature are not uniform across stimulation intensity.NEW & NOTEWORTHY Using techniques such as transcranial direct current stimulation to modulate cognitive performance is an alluring endeavor. However, the optimal parameters to augment performance are unknown. Here, in a preregistered study with a large sample (123 subjects), three different stimulation dosages (0.7, 1.0, and 2.0 mA) were applied during multitasking training. Different cognitive training performance outcomes occurred across the dosage conditions, with only one of the doses (1.0 mA) leading to training transfer.
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Affiliation(s)
- Shane E Ehrhardt
- School of Psychology, The University of Queensland, St. Lucia, Australia
| | - Hannah L Filmer
- School of Psychology, The University of Queensland, St. Lucia, Australia
| | - Yohan Wards
- School of Psychology, The University of Queensland, St. Lucia, Australia
| | - Jason B Mattingley
- School of Psychology, The University of Queensland, St. Lucia, Australia.,Queensland Brain Institute, The University of Queensland, St. Lucia, Australia.,Canadian Institute for Advanced Research, Toronto, Ontario, Canada
| | - Paul E Dux
- School of Psychology, The University of Queensland, St. Lucia, Australia
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