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Li M, Yang L, Liu Y, Shang Z, Wan H. Dynamic temporal neural patterns based on multichannel LFPs Identify different brain states during anesthesia in pigeons: comparison of three anesthetics. Med Biol Eng Comput 2024; 62:3249-3262. [PMID: 38819673 DOI: 10.1007/s11517-024-03132-w] [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: 01/08/2024] [Accepted: 05/15/2024] [Indexed: 06/01/2024]
Abstract
Anesthetic-induced brain activity study is crucial in avian cognitive-, consciousness-, and sleep-related research. However, the neurobiological mechanisms underlying the generation of brain rhythms and specific connectivity of birds during anesthesia are poorly understood. Although different kinds of anesthetics can be used to induce an anesthesia state, a comparison study of these drugs focusing on the neural pattern evolution during anesthesia is lacking. Here, we recorded local field potentials (LFPs) using a multi-channel micro-electrode array inserted into the nidopallium caudolateral (NCL) of adult pigeons (Columba livia) anesthetized with chloral hydrate, pelltobarbitalum natricum or urethane. Power spectral density (PSD) and functional connectivity analyses were used to measure the dynamic temporal neural patterns in NCL during anesthesia. Neural decoding analysis was adopted to calculate the probability of the pigeon's brain state and the kind of injected anesthetic. In the NCL during anesthesia, we found elevated power activity and functional connectivity at low-frequency bands and depressed power activity and connectivity at high-frequency bands. Decoding results based on the spectral and functional connectivity features indicated that the pigeon's brain states during anesthesia and the injected anesthetics can be effectively decoded. These findings provide an important foundation for future investigations on how different anesthetics induce the generation of specific neural patterns.
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Affiliation(s)
- Mengmeng Li
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China
- Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou, 450001, China
| | - Lifang Yang
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China
- Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou, 450001, China
| | - Yuhuai Liu
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
- National Center for International Joint Research of Electronic Materials and Systems, Zhengzhou, 450001, China.
- International Joint Laboratory of Electronic Materials and Systems of Henan Province, Zhengzhou, 450001, China.
| | - Zhigang Shang
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
- Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou, 450001, China.
- Institute of Medical Engineering Technology and Data Mining, Zhengzhou University, Zhengzhou, 450001, China.
| | - Hong Wan
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China.
- Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou, 450001, China.
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2
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Liljefors J, Almeida R, Rane G, Lundström JN, Herman P, Lundqvist M. Distinct functions for beta and alpha bursts in gating of human working memory. Nat Commun 2024; 15:8950. [PMID: 39419974 DOI: 10.1038/s41467-024-53257-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 10/07/2024] [Indexed: 10/19/2024] Open
Abstract
Multiple neural mechanisms underlying gating to working memory have been proposed with divergent results obtained in human and animal studies. Previous findings from non-human primates suggest prefrontal beta frequency bursts as a correlate of transient inhibition during selective encoding. Human studies instead suggest a similar role for sensory alpha power fluctuations. To cast light on these discrepancies we employed a sequential working memory task with distractors for human participants. In particular, we examined their whole-brain electrophysiological activity in both alpha and beta bands with the same single-trial burst analysis earlier performed on non-human primates. Our results reconcile earlier findings by demonstrating that both alpha and beta bursts in humans correlate with the filtering and control of memory items, but with region and task-specific differences between the two rhythms. Occipital beta burst patterns were selectively modulated during the transition from sensory processing to memory retention whereas prefrontal and parietal beta bursts tracked sequence order and were proactively upregulated prior to upcoming target encoding. Occipital alpha bursts instead increased during the actual presentation of unwanted sensory stimuli. Source reconstruction additionally suggested the involvement of striatal and thalamic alpha and beta. Thus, specific whole-brain burst patterns correlate with different aspects of working memory control.
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Affiliation(s)
- Johan Liljefors
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Rita Almeida
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Stockholm University Brain Imaging Centre, Stockholm University, Stockholm, Sweden
| | - Gustaf Rane
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Johan N Lundström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Monell Chemical Senses Center, Philadelphia, PA, United States of America
| | - Pawel Herman
- School of Electrical Engineering and Computer Science, and Digital Futures, KTH Royal Institute of Technology, 10044, Stockholm, Sweden
| | - Mikael Lundqvist
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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3
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Lee TW, Almeida S, Tramontano G. Attention improvement to transcranial alternating current stimulation at gamma frequency over the right frontoparietal network: a preliminary report. Acta Neuropsychiatr 2024:1-5. [PMID: 39355959 DOI: 10.1017/neu.2024.35] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/03/2024]
Abstract
Applying transcranial alternating current stimulation (tACS) at 40 Hz to the frontal and parietal regions, either unilaterally (left or right) or bilaterally, can improve cognitive dysfunctions. This study aimed to explore the influence of tACS at gamma frequency over right fronto-parietal (FP) region on attention. The analysis is based on retrospective data from a clinical intervention. We administered test of variables of attention (TOVA; visual mode) to 44 participants with various neuropsychiatric diagnoses before and after 12 sessions of tACS treatment. Alternating currents at 2.0 mA were delivered to the electrode positions F4 and P4, following the 10-20 EEG convention, for 20 mins in each session. We observed significant improvement across 3 indices of the TOVA, including reduction of variability in reaction time (p = 0.0002), increase in d-Prime (separability of targets and non-targets; p = 0.0157), and decrease in commission error rate (p = 0.0116). The mean RT and omission error rate largely remained unchanged. Artificial injection of tACS at 40 Hz over right FP network may improve attention function, especially in the domains of consistency in performance, target/non-target discrimination, and inhibitory control.
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Affiliation(s)
- Tien-Wen Lee
- The NeuroCognitive Institute (NCI) Clinical Research Foundation, Mount Arlington, NJ, USA
| | - Sergio Almeida
- The NeuroCognitive Institute (NCI) Clinical Research Foundation, Mount Arlington, NJ, USA
| | - Gerald Tramontano
- The NeuroCognitive Institute (NCI) Clinical Research Foundation, Mount Arlington, NJ, USA
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Pacheco-Estefan D, Fellner MC, Kunz L, Zhang H, Reinacher P, Roy C, Brandt A, Schulze-Bonhage A, Yang L, Wang S, Liu J, Xue G, Axmacher N. Maintenance and transformation of representational formats during working memory prioritization. Nat Commun 2024; 15:8234. [PMID: 39300141 DOI: 10.1038/s41467-024-52541-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 09/11/2024] [Indexed: 09/22/2024] Open
Abstract
Visual working memory depends on both material-specific brain areas in the ventral visual stream (VVS) that support the maintenance of stimulus representations and on regions in the prefrontal cortex (PFC) that control these representations. How executive control prioritizes working memory contents and whether this affects their representational formats remains an open question, however. Here, we analyzed intracranial EEG (iEEG) recordings in epilepsy patients with electrodes in VVS and PFC who performed a multi-item working memory task involving a retro-cue. We employed Representational Similarity Analysis (RSA) with various Deep Neural Network (DNN) architectures to investigate the representational format of prioritized VWM content. While recurrent DNN representations matched PFC representations in the beta band (15-29 Hz) following the retro-cue, they corresponded to VVS representations in a lower frequency range (3-14 Hz) towards the end of the maintenance period. Our findings highlight the distinct coding schemes and representational formats of prioritized content in VVS and PFC.
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Affiliation(s)
- Daniel Pacheco-Estefan
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, 44801, Bochum, Germany.
| | - Marie-Christin Fellner
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, 44801, Bochum, Germany
| | - Lukas Kunz
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Hui Zhang
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, 44801, Bochum, Germany
| | - Peter Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Fraunhofer Institute for Laser Technology, Aachen, Germany
| | - Charlotte Roy
- Epilepsy Center, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Armin Brandt
- Epilepsy Center, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center - Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Linglin Yang
- Department of Psychiatry, Second Affiliated Hospital, School of medicine, Zhejiang University, Hangzhou, China
| | - Shuang Wang
- Department of Neurology, Epilepsy center, Second Affiliated Hospital, School of medicine, Zhejiang University, Hangzhou, China
| | - Jing Liu
- Department of Applied Social Sciences, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR
| | - Gui Xue
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, PR China
| | - Nikolai Axmacher
- Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, 44801, Bochum, Germany
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, PR China
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Mohamadpour H, Farkhondeh Tale Navi F, Heysieattalab S, Irak M, Vahabie AH, Nikzad B. How is social dominance related to our short-term memory? An EEG/ERP investigation of encoding and retrieval during a working memory task. Heliyon 2024; 10:e37389. [PMID: 39296172 PMCID: PMC11408820 DOI: 10.1016/j.heliyon.2024.e37389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 08/24/2024] [Accepted: 09/02/2024] [Indexed: 09/21/2024] Open
Abstract
Social hierarchies exist in all societies and impact cognitive functions, brain mechanisms, social interactions, and behaviors. High status individuals often exhibit enhanced working memory (WM) performance compared to lower status individuals. This study examined whether individual differences in social dominance, as a predictor of future status, relate to WM abilities. Five hundred and twenty-five students completed the Personality Research Form dominance subscale questionnaire. From this sample, students with the highest and lowest scores were invited to participate in the study. Sixty-four participants volunteered to take part and were subsequently categorized into high- and low-dominance groups based on their dominance subscale questionnaire (PRF_d) scores. They performed a Sternberg WM task with set sizes of 1, 4, or 7 letters while their EEG was recorded. Event-related potential (ERP) and power spectral analysis revealed significantly reduced P3b amplitude and higher event-related synchronization (ERS) of theta and beta during encoding and retrieval phases in the high-than low-dominance group. Despite these neural processing differences, behavioral performance was equivalent between groups, potentially reflecting comparable cognitive load demands of the task across dominance levels. Further, there were similar P3b patterns for each set-size within groups. These findings provide initial evidence that individual differences in social dominance trait correlate with WM functioning, as indexed by neural processing efficiency during WM performance.
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Affiliation(s)
- Hadi Mohamadpour
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Farhad Farkhondeh Tale Navi
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Soomaayeh Heysieattalab
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Metehan Irak
- Department of Psychology, Bahçeşehir University, Istanbul, Turkey
| | - Abdol-Hossein Vahabie
- Cognitive Systems Laboratory, Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Department of Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran
| | - Behzad Nikzad
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
- Neurobioscience Division, Research Center of Bioscience and Biotechnology, University of Tabriz, Tabriz, Iran
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Kucewicz MT, Cimbalnik J, Garcia-Salinas JS, Brazdil M, Worrell GA. High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams? Brain 2024; 147:2966-2982. [PMID: 38743818 PMCID: PMC11370809 DOI: 10.1093/brain/awae159] [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: 02/07/2024] [Revised: 04/16/2024] [Accepted: 04/21/2024] [Indexed: 05/16/2024] Open
Abstract
Despite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected in the human mesial temporal lobe and neocortical intracranial recordings spanning gamma/epsilon (60-150 Hz), ripple (80-250 Hz) and higher frequency ranges. Separate from other non-oscillatory activities, these brief electrophysiological oscillations of distinct duration, frequency and amplitude are thought to be generated by coordinated spiking of neuronal ensembles within volumes as small as a single cortical column. Although the exact origins, mechanisms and physiological roles in health and disease remain elusive, they have been associated with human memory consolidation and cognitive processing. Recent studies suggest their involvement in encoding and recall of episodic memory with a possible role in the formation and reactivation of memory traces. High frequency oscillations are detected during encoding, throughout maintenance, and right before recall of remembered items, meeting a basic definition for an engram activity. The temporal coordination of high frequency oscillations reactivated across cortical and subcortical neural networks is ideally suited for integrating multimodal memory representations, which can be replayed and consolidated during states of wakefulness and sleep. High frequency oscillations have been shown to reflect coordinated bursts of neuronal assembly firing and offer a promising substrate for tracking and modulation of the hypothetical electrophysiological engram.
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Affiliation(s)
- Michal T Kucewicz
- BioTechMed Center, Brain & Mind Electrophysiology laboratory, Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland
- Bioelectronics, Neurophysiology and Engineering Laboratory, Mayo Clinic, Departments of Neurology and Biomedical Engineering & Physiology, Mayo Clinic, Rochester, MN 55902, USA
| | - Jan Cimbalnik
- BioTechMed Center, Brain & Mind Electrophysiology laboratory, Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland
- Department of Biomedical Engineering, St. Anne’s University Hospital in Brno & International Clinical Research Center, Brno 602 00, Czech Republic
- Brno Epilepsy Center, 1th Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, member of the ERN-EpiCARE, Brno 602 00, Czech Republic
| | - Jesus S Garcia-Salinas
- BioTechMed Center, Brain & Mind Electrophysiology laboratory, Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland
| | - Milan Brazdil
- BioTechMed Center, Brain & Mind Electrophysiology laboratory, Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland
- Brno Epilepsy Center, 1th Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, member of the ERN-EpiCARE, Brno 602 00, Czech Republic
- Behavioural and Social Neuroscience Research Group, CEITEC—Central European Institute of Technology, Masaryk University, Brno 625 00, Czech Republic
| | - Gregory A Worrell
- BioTechMed Center, Brain & Mind Electrophysiology laboratory, Department of Multimedia Systems, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk 80-233, Poland
- Bioelectronics, Neurophysiology and Engineering Laboratory, Mayo Clinic, Departments of Neurology and Biomedical Engineering & Physiology, Mayo Clinic, Rochester, MN 55902, USA
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Wen W, Grover S, Hazel D, Berning P, Baumgardt F, Viswanathan V, Tween O, Reinhart RMG. Beta-band neural variability reveals age-related dissociations in human working memory maintenance and deletion. PLoS Biol 2024; 22:e3002784. [PMID: 39259713 PMCID: PMC11389900 DOI: 10.1371/journal.pbio.3002784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 08/02/2024] [Indexed: 09/13/2024] Open
Abstract
Maintaining and removing information in mind are 2 fundamental cognitive processes that decline sharply with age. Using a combination of beta-band neural oscillations, which have been implicated in the regulation of working memory contents, and cross-trial neural variability, an undervalued property of brain dynamics theorized to govern adaptive cognitive processes, we demonstrate an age-related dissociation between distinct working memory functions-information maintenance and post-response deletion. Load-dependent decreases in beta variability during maintenance predicted memory performance of younger, but not older adults. Surprisingly, the post-response phase emerged as the predictive locus of working memory performance for older adults, with post-response beta variability correlated with memory performance of older, but not younger adults. Single-trial analysis identified post-response beta power elevation as a frequency-specific signature indexing memory deletion. Our findings demonstrate the nuanced interplay between age, beta dynamics, and working memory, offering valuable insights into the neural mechanisms of cognitive decline in agreement with the inhibition deficit theory of aging.
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Affiliation(s)
- Wen Wen
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Shrey Grover
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Douglas Hazel
- Tufts University, Department of Biology, Medford, Massachusetts, United States of America
| | - Peyton Berning
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Frederik Baumgardt
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Vighnesh Viswanathan
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Olivia Tween
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
| | - Robert M G Reinhart
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
- Center for Systems Neuroscience, Boston University, Boston, Massachusetts, United States of America
- Cognitive Neuroimaging Center, Boston University, Boston, Massachusetts, United States of America
- Center for Research in Sensory Communication and Emerging Neural Technology, Boston University, Boston, Massachusetts, United States of America
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Simpson TG, Godfrey W, Torrecillos F, He S, Herz DM, Oswal A, Muthuraman M, Pogosyan A, Tan H. Cortical beta oscillations help synchronise muscles during static posture holding in healthy motor control. Neuroimage 2024; 298:120774. [PMID: 39103065 DOI: 10.1016/j.neuroimage.2024.120774] [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: 01/19/2024] [Revised: 07/31/2024] [Accepted: 08/02/2024] [Indexed: 08/07/2024] Open
Abstract
How cortical oscillations are involved in the coordination of functionally coupled muscles and how this is modulated by different movement contexts (static vs dynamic) remains unclear. Here, this is investigated by recording high-density electroencephalography (EEG) and electromyography (EMG) from different forearm muscles while healthy participants (n = 20) performed movement tasks (static and dynamic posture holding, and reaching) with their dominant hand. When dynamic perturbation was applied, beta band (15-35 Hz) activities in the motor cortex contralateral to the performing hand reduced during the holding phase, comparative to when there was no perturbation. During static posture holding, transient periods of increased cortical beta oscillations (beta bursts) were associated with greater corticomuscular coherence and increased phase synchrony between muscles (intermuscular coherence) in the beta frequency band compared to the no-burst period. This effect was not present when resisting dynamic perturbation. The results suggest that cortical beta bursts assist synchronisation of different muscles during static posture holding in healthy motor control, contributing to the maintenance and stabilisation of functional muscle groups. Theoretically, increased cortical beta oscillations could lead to exaggerated synchronisation in different muscles making the initialisation of movements more difficult, as observed in Parkinson's disease.
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Affiliation(s)
- Thomas G Simpson
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - William Godfrey
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Flavie Torrecillos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Shenghong He
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Damian M Herz
- Movement Disorders and Neurostimulation, Department of Neurology, Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Ashwini Oswal
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Muthuraman Muthuraman
- Neural Engineering with Signal Analytics and Artificial Intelligence (NESA-AI), Department of Neurology, Universitätsklinikum Würzburg, Würzburg, Germany
| | - Alek Pogosyan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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Liu Y, Lao W, Mao H, Zhong Y, Wang J, Ouyang W. Comparison of alterations in local field potentials and neuronal firing in mouse M1 and CA1 associated with central fatigue induced by high-intensity interval training and moderate-intensity continuous training. Front Neurosci 2024; 18:1428901. [PMID: 39211437 PMCID: PMC11357951 DOI: 10.3389/fnins.2024.1428901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Accepted: 07/31/2024] [Indexed: 09/04/2024] Open
Abstract
Background The mechanisms underlying central fatigue (CF) induced by high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) are still not fully understood. Methods In order to explore the effects of these exercises on the functioning of cortical and subcortical neural networks, this study investigated the effects of HIIT and MICT on local field potential (LFP) and neuronal firing in the mouse primary motor cortex (M1) and hippocampal CA1 areas. HIIT and MICT were performed on C57BL/6 mice, and simultaneous multichannel recordings were conducted in the M1 motor cortex and CA1 hippocampal region. Results A range of responses were elicited, including a decrease in coherence values of LFP rhythms in both areas, and an increase in slow and a decrease in fast power spectral density (PSD, n = 7-9) respectively. HIIT/MICT also decreased the gravity frequency (GF, n = 7-9) in M1 and CA1. Both exercises decreased overall firing rates, increased time lag of firing, declined burst firing rates and the number of spikes in burst, and reduced burst duration (BD) in M1 and CA1 (n = 7-9). While several neuronal firing properties showed a recovery tendency, the alterations of LFP parameters were more sustained during the 10-min post-HIIT/MICT period. MICT appeared to be more effective than HIIT in affecting LFP parameters, neuronal firing rate, and burst firing properties, particularly in CA1. Both exercises significantly affected neural network activities and local neuronal firing in M1 and CA1, with MICT associated with a more substantial and consistent suppression of functional integration between M1 and CA1. Conclusion Our study provides valuable insights into the neural mechanisms involved in exercise-induced central fatigue by examining the changes in functional connectivity and coordination between the M1 and CA1 regions. These findings may assist individuals engaged in exercise in optimizing their exercise intensity and timing to enhance performance and prevent excessive fatigue. Additionally, the findings may have clinical implications for the development of interventions aimed at managing conditions related to exercise-induced fatigue.
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Affiliation(s)
| | | | | | | | | | - Wei Ouyang
- College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, China
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Peng J, Zikereya T, Shao Z, Shi K. The neuromechanical of Beta-band corticomuscular coupling within the human motor system. Front Neurosci 2024; 18:1441002. [PMID: 39211436 PMCID: PMC11358111 DOI: 10.3389/fnins.2024.1441002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 07/26/2024] [Indexed: 09/04/2024] Open
Abstract
Beta-band activity in the sensorimotor cortex is considered a potential biomarker for evaluating motor functions. The intricate connection between the brain and muscle (corticomuscular coherence), especially in beta band, was found to be modulated by multiple motor demands. This coherence also showed abnormality in motion-related disorders. However, although there has been a substantial accumulation of experimental evidence, the neural mechanisms underlie corticomuscular coupling in beta band are not yet fully clear, and some are still a matter of controversy. In this review, we summarized the findings on the impact of Beta-band corticomuscular coherence to multiple conditions (sports, exercise training, injury recovery, human functional restoration, neurodegenerative diseases, age-related changes, cognitive functions, pain and fatigue, and clinical applications), and pointed out several future directions for the scientific questions currently unsolved. In conclusion, an in-depth study of Beta-band corticomuscular coupling not only elucidates the neural mechanisms of motor control but also offers new insights and methodologies for the diagnosis and treatment of motor rehabilitation and related disorders. Understanding these mechanisms can lead to personalized neuromodulation strategies and real-time neurofeedback systems, optimizing interventions based on individual neurophysiological profiles. This personalized approach has the potential to significantly improve therapeutic outcomes and athletic performance by addressing the unique needs of each individual.
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Affiliation(s)
| | | | | | - Kaixuan Shi
- Physical Education Department, China University of Geosciences Beijing, Beijing, China
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11
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Cho S, Han HB, Jung D, Kim J, Choi JH. Mouse Escape Behaviors and mPFC-BLA Activity Dataset: Understanding Flexible Defensive Strategies Under Threat. Sci Data 2024; 11:861. [PMID: 39127738 DOI: 10.1038/s41597-024-03688-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
Responding to threats in the real world demands a sophisticated orchestration of freeze and flight behaviors dynamically modulated by the neural activity. While the medial prefrontal cortex-basolateral amygdala (mPFC-BLA) network is known to play a pivotal role in coordinating these responses, the mechanisms underlying its population dynamics remain vague. As traditional Pavlovian fear conditioning models fall short in encapsulating the breadth of natural escape behaviors, we introduce a novel dataset to bridge this gap, capturing the defensive strategies of mice against a spider robot in a natural-like environment. The adaptive escape behaviors and concurrent mPFC-BLA activity in eight mice were monitored using wireless local field potential (LFP) and video recordings, both individually and in groups. Our data offers a unique avenue to explore the neural dynamics that govern fear- and vigilance-induced threat responses in isolated and social contexts. Supplemented by detailed methodologies and validation, the dataset allows for the analysis of the transient neural oscillatory dynamics, with prospective implications for the fields of neuroscience, robotics, and artificial intelligence.
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Affiliation(s)
- SungJun Cho
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK
| | - Hio-Been Han
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar Street, Cambridge, MA, 02139, USA
- School of Convergence, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea
| | - DaYoung Jung
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Biotechnology, Korea University, Seoul, 02841, Republic of Korea
| | - Jisoo Kim
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3EG, UK
| | - Jee Hyun Choi
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea.
- Division of Bio-Medical Science & Technology, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea.
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12
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Xiao J, Adkinson JA, Myers J, Allawala AB, Mathura RK, Pirtle V, Najera R, Provenza NR, Bartoli E, Watrous AJ, Oswalt D, Gadot R, Anand A, Shofty B, Mathew SJ, Goodman WK, Pouratian N, Pitkow X, Bijanki KR, Hayden B, Sheth SA. Beta activity in human anterior cingulate cortex mediates reward biases. Nat Commun 2024; 15:5528. [PMID: 39009561 PMCID: PMC11250824 DOI: 10.1038/s41467-024-49600-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 06/07/2024] [Indexed: 07/17/2024] Open
Abstract
The rewards that we get from our choices and actions can have a major influence on our future behavior. Understanding how reward biasing of behavior is implemented in the brain is important for many reasons, including the fact that diminution in reward biasing is a hallmark of clinical depression. We hypothesized that reward biasing is mediated by the anterior cingulate cortex (ACC), a cortical hub region associated with the integration of reward and executive control and with the etiology of depression. To test this hypothesis, we recorded neural activity during a biased judgment task in patients undergoing intracranial monitoring for either epilepsy or major depressive disorder. We found that beta (12-30 Hz) oscillations in the ACC predicted both associated reward and the size of the choice bias, and also tracked reward receipt, thereby predicting bias on future trials. We found reduced magnitude of bias in depressed patients, in whom the beta-specific effects were correspondingly reduced. Our findings suggest that ACC beta oscillations may orchestrate the learning of reward information to guide adaptive choice, and, more broadly, suggest a potential biomarker for anhedonia and point to future development of interventions to enhance reward impact for therapeutic benefit.
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Affiliation(s)
- Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | | | - Raissa K Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ricardo Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Andrew J Watrous
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Denise Oswalt
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Adrish Anand
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, 84112, USA
| | - Sanjay J Mathew
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Wayne K Goodman
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, 75390, USA
| | - Xaq Pitkow
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA
- Center for Neuroscience and Artificial Intelligence, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Benjamin Hayden
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA.
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13
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Lundqvist M, Miller EK, Nordmark J, Liljefors J, Herman P. Beta: bursts of cognition. Trends Cogn Sci 2024; 28:662-676. [PMID: 38658218 DOI: 10.1016/j.tics.2024.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 03/11/2024] [Accepted: 03/20/2024] [Indexed: 04/26/2024]
Abstract
Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.
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Affiliation(s)
- Mikael Lundqvist
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden; The Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Earl K Miller
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jonatan Nordmark
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Johan Liljefors
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Pawel Herman
- School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden; Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
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14
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Morgan AM, Devinsky O, Doyle WK, Dugan P, Friedman D, Flinker A. A low-activity cortical network selectively encodes syntax. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.20.599931. [PMID: 38948730 PMCID: PMC11212956 DOI: 10.1101/2024.06.20.599931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Syntax, the abstract structure of language, is a hallmark of human cognition. Despite its importance, its neural underpinnings remain obscured by inherent limitations of non-invasive brain measures and a near total focus on comprehension paradigms. Here, we address these limitations with high-resolution neurosurgical recordings (electrocorticography) and a controlled sentence production experiment. We uncover three syntactic networks that are broadly distributed across traditional language regions, but with focal concentrations in middle and inferior frontal gyri. In contrast to previous findings from comprehension studies, these networks process syntax mostly to the exclusion of words and meaning, supporting a cognitive architecture with a distinct syntactic system. Most strikingly, our data reveal an unexpected property of syntax: it is encoded independent of neural activity levels. We propose that this "low-activity coding" scheme represents a novel mechanism for encoding information, reserved for higher-order cognition more broadly.
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Affiliation(s)
- Adam M. Morgan
- Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
| | - Orrin Devinsky
- Neurosurgery Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
| | - Werner K. Doyle
- Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
| | - Patricia Dugan
- Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
| | - Daniel Friedman
- Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
| | - Adeen Flinker
- Neurology Department, NYU Grossman School of Medicine, 550 1st Ave, New York, 10016, NY, USA
- Biomedical Engineering Department, NYU Tandon School of Engineering, 6 MetroTech Center Ave, Brooklyn, 11201, NY, USA
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15
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Pailthorpe BA. Simulated dynamical transitions in a heterogeneous marmoset pFC cluster. Front Comput Neurosci 2024; 18:1398898. [PMID: 38863681 PMCID: PMC11165126 DOI: 10.3389/fncom.2024.1398898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 05/06/2024] [Indexed: 06/13/2024] Open
Abstract
Network analysis of the marmoset cortical connectivity data indicates a significant 3D cluster in and around the pre-frontal cortex. A multi-node, heterogeneous neural mass model of this six-node cluster was constructed. Its parameters were informed by available experimental and simulation data so that each neural mass oscillated in a characteristic frequency band. Nodes were connected with directed, weighted links derived from the marmoset structural connectivity data. Heterogeneity arose from the different link weights and model parameters for each node. Stimulation of the cluster with an incident pulse train modulated in the standard frequency bands induced a variety of dynamical state transitions that lasted in the range of 5-10 s, suggestive of timescales relevant to short-term memory. A short gamma burst rapidly reset the beta-induced transition. The theta-induced transition state showed a spontaneous, delayed reset to the resting state. An additional, continuous gamma wave stimulus induced a new beating oscillatory state. Longer or repeated gamma bursts were phase-aligned with the beta oscillation, delivering increasing energy input and causing shorter transition times. The relevance of these results to working memory is yet to be established, but they suggest interesting opportunities.
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Affiliation(s)
- Bernard A. Pailthorpe
- Brain Dynamics Group, School of Physics, University of Sydney, Sydney, NSW, Australia
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16
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Busch A, Roussy M, Luna R, Leavitt ML, Mofrad MH, Gulli RA, Corrigan B, Mináč J, Sachs AJ, Palaniyappan L, Muller L, Martinez-Trujillo JC. Neuronal activation sequences in lateral prefrontal cortex encode visuospatial working memory during virtual navigation. Nat Commun 2024; 15:4471. [PMID: 38796480 PMCID: PMC11127969 DOI: 10.1038/s41467-024-48664-9] [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: 10/14/2023] [Accepted: 05/01/2024] [Indexed: 05/28/2024] Open
Abstract
Working memory (WM) is the ability to maintain and manipulate information 'in mind'. The neural codes underlying WM have been a matter of debate. We simultaneously recorded the activity of hundreds of neurons in the lateral prefrontal cortex of male macaque monkeys during a visuospatial WM task that required navigation in a virtual 3D environment. Here, we demonstrate distinct neuronal activation sequences (NASs) that encode remembered target locations in the virtual environment. This NAS code outperformed the persistent firing code for remembered locations during the virtual reality task, but not during a classical WM task using stationary stimuli and constraining eye movements. Finally, blocking NMDA receptors using low doses of ketamine deteriorated the NAS code and behavioral performance selectively during the WM task. These results reveal the versatility and adaptability of neural codes supporting working memory function in the primate lateral prefrontal cortex.
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Affiliation(s)
- Alexandra Busch
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Mathematics, University of Western Ontario, London, ON, Canada
| | - Megan Roussy
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Rogelio Luna
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | | | - Maryam H Mofrad
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Mathematics, University of Western Ontario, London, ON, Canada
| | - Roberto A Gulli
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Benjamin Corrigan
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Ján Mináč
- Department of Mathematics, University of Western Ontario, London, ON, Canada
| | - Adam J Sachs
- The Ottawa Hospital, University of Ottawa, Ottawa, ON, Canada
| | - Lena Palaniyappan
- Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Psychiatry, University of Western Ontario, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
| | - Lyle Muller
- Robarts Research Institute, University of Western Ontario, London, ON, Canada.
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada.
- Department of Mathematics, University of Western Ontario, London, ON, Canada.
| | - Julio C Martinez-Trujillo
- Robarts Research Institute, University of Western Ontario, London, ON, Canada.
- Brain and Mind Institute, University of Western Ontario, London, ON, Canada.
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada.
- Lawson Health Research Institute, London, ON, Canada.
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17
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Di Bello F, Falcone R, Genovesio A. Simultaneous oscillatory encoding of "hot" and "cold" information during social interactions in the monkey medial prefrontal cortex. iScience 2024; 27:109559. [PMID: 38646179 PMCID: PMC11033171 DOI: 10.1016/j.isci.2024.109559] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/27/2023] [Accepted: 03/22/2024] [Indexed: 04/23/2024] Open
Abstract
Social interactions in primates require social cognition abilities such as anticipating the partner's future choices as well as pure cognitive skills involving processing task-relevant information. The medial prefrontal cortex (mPFC) has been implicated in these cognitive processes. Here, we investigated the neural oscillations underlying the complex social behaviors involving the interplay of social roles (Actor vs. Observer) and interaction types (whether working with a "Good" or "Bad" partner). We found opposite power modulations of the beta and gamma bands by social roles, indicating dedicated processing for task-related information. Concurrently, the interaction type was conveyed by lower frequencies, which are commonly associated with neural circuits linked to performance and reward monitoring. Thus, the mPFC exhibits parallel coding of both "cold" processes (purely cognitive) and "hot" processes (reward and social-related). This allocation of neural resources gives the mPFC a key neural node, flexibly integrating multiple sources of information during social interactions.
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Affiliation(s)
- Fabio Di Bello
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Rossella Falcone
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
- Leo M. Davidoff Department of Neurological Surgery, Albert Einstein College of Medicine Montefiore Medical Center Bronx, Bronx, NY, USA
| | - Aldo Genovesio
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
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18
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Pagnotta MF, Santo-Angles A, Temudo A, Barbosa J, Compte A, D'Esposito M, Sreenivasan KK. Alpha phase-coding supports feature binding during working memory maintenance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.21.576561. [PMID: 38328154 PMCID: PMC10849498 DOI: 10.1101/2024.01.21.576561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The ability to successfully retain and manipulate information in working memory (WM) requires that objects' individual features are bound into cohesive representations; yet, the mechanisms supporting feature binding remain unclear. Binding (or swap) errors, where memorized features are erroneously associated with the wrong object, can provide a window into the intrinsic limits in capacity of WM that represent a key bottleneck in our cognitive ability. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and that swap errors result from perturbations in this synchrony. Using magnetoencephalography data collected from human subjects in a task designed to induce swap errors, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention, as predicted by an attractor model of spiking neural networks. Further, we found that this reduction arises from increased phase-coding variability in the alpha-band over a distributed network of sensorimotor areas. Our findings demonstrate that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.
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19
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Yu Y, Oh Y, Kounios J, Beeman M. Electroencephalography Spectral-power Volatility Predicts Problem-solving Outcomes. J Cogn Neurosci 2024; 36:901-915. [PMID: 38437171 DOI: 10.1162/jocn_a_02136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2024]
Abstract
Temporal variability is a fundamental property of brain processes and is functionally important to human cognition. This study examined how fluctuations in neural oscillatory activity are related to problem-solving performance as one example of how temporal variability affects high-level cognition. We used volatility to assess step-by-step fluctuations of EEG spectral power while individuals attempted to solve word-association puzzles. Inspired by recent results with hidden-state modeling, we tested the hypothesis that spectral-power volatility is directly associated with problem-solving outcomes. As predicted, volatility was lower during trials solved with insight compared with those solved analytically. Moreover, volatility during prestimulus preparation for problem-solving predicted solving outcomes, including solving success and solving time. These novel findings were replicated in a separate data set from an anagram-solving task, suggesting that less-rapid transitions between neural oscillatory synchronization and desynchronization predict better solving performance and are conducive to solving with insight for these types of problems. Thus, volatility can be a valuable index of cognition-related brain dynamics.
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Affiliation(s)
- Yuhua Yu
- Northwestern University, Evanston, IL
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20
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Sharma D, Lupkin SM, McGinty VB. Orbitofrontal high-gamma reflects spike-dissociable value and decision mechanisms. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587758. [PMID: 38617349 PMCID: PMC11014579 DOI: 10.1101/2024.04.02.587758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
The orbitofrontal cortex (OFC) plays a crucial role in value-based decision-making. While previous research has focused on spiking activity in OFC neurons, the role of OFC local field potentials (LFPs) in decision-making remains unclear. LFPs are important because they can reflect synaptic and subthreshold activity not directly coupled to spiking, and because they are potential targets for less invasive forms of brain-machine interface (BMI). We recorded LFPs and spiking activity using multi-channel vertical probes while monkeys performed a two-option value-based decision-making task. We compared the value- and decision-coding properties of high-gamma range LFPs (HG, 50-150 Hz) to the coding properties of spiking multi-unit activity (MUA) recorded concurrently on the same electrodes. Results show that HG and MUA both represent the values of decision targets, and that their representations have similar temporal profiles in a trial. However, we also identified value-coding properties of HG that were dissociable from the concurrently-measured MUA. On average across channels, HG amplitude increased monotonically with value, whereas the average value encoding in MUA was net neutral. HG also encoded a signal consistent with a comparison between the values of the two targets, a signal which was much weaker in MUA. In individual channels, HG was better able to predict choice outcomes than MUA; however, when simultaneously recorded channels were combined in population-based decoder, MUA provided more accurate predictions than HG. Interestingly, HG value representations were accentuated in channels in or near shallow cortical layers, suggesting a dissociation between neuronal sources of HG and MUA. In summary, we find that HG signals are dissociable from MUA with respect to cognitive variables encoded in prefrontal cortex, evident in the monotonic encoding of value, stronger encoding of value comparisons, and more accurate predictions about behavior. High-frequency LFPs may therefore be a viable - or even preferable - target for BMIs to assist cognitive function, opening the possibility for less invasive access to mental contents that would otherwise be observable only with spike-based measures.
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Affiliation(s)
- Dixit Sharma
- Center for Molecular and Behavioral Neuroscience, Rutgers University – Newark
- Graduate Program in Neuroscience, Rutgers University – Newark
| | - Shira M. Lupkin
- Center for Molecular and Behavioral Neuroscience, Rutgers University – Newark
- Graduate Program in Neuroscience, Rutgers University – Newark
| | - Vincent B. McGinty
- Center for Molecular and Behavioral Neuroscience, Rutgers University – Newark
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21
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Alamia A, VanRullen R. A Traveling Waves Perspective on Temporal Binding. J Cogn Neurosci 2024; 36:721-729. [PMID: 37172133 DOI: 10.1162/jocn_a_02004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Brain oscillations are involved in many cognitive processes, and several studies have investigated their role in cognition. In particular, the phase of certain oscillations has been related to temporal binding and integration processes, with some authors arguing that perception could be an inherently rhythmic process. However, previous research on oscillations mostly overlooked their spatial component: how oscillations propagate through the brain as traveling waves, with systematic phase delays between brain regions. Here, we argue that interpreting oscillations as traveling waves is a useful paradigm shift to understand their role in temporal binding and address controversial results. After a brief definition of traveling waves, we propose an original view on temporal integration that considers this new perspective. We first focus on cortical dynamics, then speculate about the role of thalamic nuclei in modulating the waves, and on the possible consequences for rhythmic temporal binding. In conclusion, we highlight the importance of considering oscillations as traveling waves when investigating their role in cognitive functions.
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Affiliation(s)
- Andrea Alamia
- CNRS Centre de Recherche Cerveau et Cognition (CERCO, UMR 5549), Toulouse, France
| | - Rufin VanRullen
- CNRS Centre de Recherche Cerveau et Cognition (CERCO, UMR 5549), Toulouse, France
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22
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Yiling Y, Klon-Lipok J, Shapcott K, Lazar A, Singer W. Dynamic fading memory and expectancy effects in the monkey primary visual cortex. Proc Natl Acad Sci U S A 2024; 121:e2314855121. [PMID: 38354261 PMCID: PMC10895277 DOI: 10.1073/pnas.2314855121] [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: 08/30/2023] [Accepted: 01/10/2024] [Indexed: 02/16/2024] Open
Abstract
In order to investigate the involvement of the primary visual cortex (V1) in working memory (WM), parallel, multisite recordings of multi-unit activity were obtained from monkey V1 while the animals performed a delayed match-to-sample (DMS) task. During the delay period, V1 population firing rate vectors maintained a lingering trace of the sample stimulus that could be reactivated by intervening impulse stimuli that enhanced neuronal firing. This fading trace of the sample did not require active engagement of the monkeys in the DMS task and likely reflects the intrinsic dynamics of recurrent cortical networks in lower visual areas. This renders an active, attention-dependent involvement of V1 in the maintenance of WM contents unlikely. By contrast, population responses to the test stimulus depended on the probabilistic contingencies between sample and test stimuli. Responses to tests that matched expectations were reduced which agrees with concepts of predictive coding.
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Affiliation(s)
- Yang Yiling
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main60528, Germany
| | - Johanna Klon-Lipok
- Max Planck Institute for Brain Research, Frankfurt am Main60438, Germany
| | - Katharine Shapcott
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main60528, Germany
| | - Andreea Lazar
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main60528, Germany
| | - Wolf Singer
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main60528, Germany
- Max Planck Institute for Brain Research, Frankfurt am Main60438, Germany
- Frankfurt Institute for Advanced Studies, Frankfurt am Main60438, Germany
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23
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Su M, Hu K, Liu W, Wu Y, Wang T, Cao C, Sun B, Zhan S, Ye Z. Theta Oscillations Support Prefrontal-hippocampal Interactions in Sequential Working Memory. Neurosci Bull 2024; 40:147-156. [PMID: 37847448 PMCID: PMC10838883 DOI: 10.1007/s12264-023-01134-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/28/2023] [Indexed: 10/18/2023] Open
Abstract
The prefrontal cortex and hippocampus may support sequential working memory beyond episodic memory and spatial navigation. This stereoelectroencephalography (SEEG) study investigated how the dorsolateral prefrontal cortex (DLPFC) interacts with the hippocampus in the online processing of sequential information. Twenty patients with epilepsy (eight women, age 27.6 ± 8.2 years) completed a line ordering task with SEEG recordings over the DLPFC and the hippocampus. Participants showed longer thinking times and more recall errors when asked to arrange random lines clockwise (random trials) than to maintain ordered lines (ordered trials) before recalling the orientation of a particular line. First, the ordering-related increase in thinking time and recall error was associated with a transient theta power increase in the hippocampus and a sustained theta power increase in the DLPFC (3-10 Hz). In particular, the hippocampal theta power increase correlated with the memory precision of line orientation. Second, theta phase coherences between the DLPFC and hippocampus were enhanced for ordering, especially for more precisely memorized lines. Third, the theta band DLPFC → hippocampus influence was selectively enhanced for ordering, especially for more precisely memorized lines. This study suggests that theta oscillations may support DLPFC-hippocampal interactions in the online processing of sequential information.
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Affiliation(s)
- Minghong Su
- Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Kejia Hu
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Wei Liu
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yunhao Wu
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Tao Wang
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Chunyan Cao
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Shikun Zhan
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Zheng Ye
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
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24
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Ibanez A, Northoff G. Intrinsic timescales and predictive allostatic interoception in brain health and disease. Neurosci Biobehav Rev 2024; 157:105510. [PMID: 38104789 PMCID: PMC11184903 DOI: 10.1016/j.neubiorev.2023.105510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/29/2023] [Accepted: 12/12/2023] [Indexed: 12/19/2023]
Abstract
The cognitive neuroscience of brain diseases faces challenges in understanding the complex relationship between brain structure and function, the heterogeneity of brain phenotypes, and the lack of dimensional and transnosological explanations. This perspective offers a framework combining the predictive coding theory of allostatic interoceptive overload (PAIO) and the intrinsic neural timescales (INT) theory to provide a more dynamic understanding of brain health in psychiatry and neurology. PAIO integrates allostasis and interoception to assess the interaction between internal patterns and environmental stressors, while INT shows that different brain regions operate on different intrinsic timescales. The allostatic overload can be understood as a failure of INT, which involves a breakdown of proper temporal integration and segregation. This can lead to dimensional disbalances between exteroceptive/interoceptive inputs across brain and whole-body levels (cardiometabolic, cardiovascular, inflammatory, immune). This approach offers new insights, presenting novel perspectives on brain spatiotemporal hierarchies and interactions. By integrating these theories, the paper opens innovative paths for studying brain health dynamics, which can inform future research in brain health and disease.
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Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), CA, USA; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile; Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina; Trinity College Dublin, Dublin, Ireland.
| | - Georg Northoff
- Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China; Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, People's Republic of China; Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.
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25
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Junker FB, Schmidt‐Wilcke T, Schnitzler A, Lange J. Temporal dynamics of oscillatory activity during nonlexical language decoding: Evidence from Morse code and magnetoencephalography. Hum Brain Mapp 2023; 44:6185-6197. [PMID: 37792277 PMCID: PMC10619365 DOI: 10.1002/hbm.26505] [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: 04/28/2023] [Revised: 08/27/2023] [Accepted: 09/14/2023] [Indexed: 10/05/2023] Open
Abstract
Understanding encoded languages, such as written script or Morse code, requires nonlexical and lexical processing components that act in a parallel and interactive fashion. Decoding written script-as for example in reading-is typically very fast, making the investigation of the lexical and nonlexical components and their underlying neural mechanisms challenging. In the current study, we aimed to accomplish this problem by using Morse code as a model for language decoding. The decoding of Morse code is slower and thus allows a better and more fine-grained investigation of the lexical and nonlexical components of language decoding. In the current study, we investigated the impact of various components of nonlexical decoding of Morse code using magnetoencephalography. For this purpose, we reconstructed the time-frequency responses below 40 Hz in brain regions significantly involved in Morse code decoding and word comprehension that were identified in a previous study. Event-related reduction in beta- and alpha-band power were found in left inferior frontal cortex and angular gyrus, respectively, while event-related theta-band power increase was found at frontal midline. These induced oscillations reflect working-memory encoding, long-term memory retrieval as well as demanding cognitive control, respectively. In sum, by using Morse code and MEG, we were able to identify a cortical network underlying language decoding in a time- and frequency-resolved manner.
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Affiliation(s)
- Frederick Benjamin Junker
- Institute of Clinical Neuroscience and Medical Psychology, Medical FacultyHeinrich‐Heine‐UniversityDüsseldorfGermany
| | - Tobias Schmidt‐Wilcke
- Institute of Clinical Neuroscience and Medical Psychology, Medical FacultyHeinrich‐Heine‐UniversityDüsseldorfGermany
- Neurological Center MainkofenDeggendorfGermany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical FacultyHeinrich‐Heine‐UniversityDüsseldorfGermany
| | - Joachim Lange
- Institute of Clinical Neuroscience and Medical Psychology, Medical FacultyHeinrich‐Heine‐UniversityDüsseldorfGermany
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26
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Zhao S, Zhou J, Zhang Y, Wang DH. γ And β Band Oscillation in Working Memory Given Sequential or Concurrent Multiple Items: A Spiking Network Model. eNeuro 2023; 10:ENEURO.0373-22.2023. [PMID: 37903618 PMCID: PMC10630927 DOI: 10.1523/eneuro.0373-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 10/10/2023] [Accepted: 10/22/2023] [Indexed: 11/01/2023] Open
Abstract
Working memory (WM) can maintain sequential and concurrent information, and the load enhances the γ band oscillation during the delay period. To provide a unified account for these phenomena in working memory, we investigated a continuous network model consisting of pyramidal cells, high-threshold fast-spiking interneurons (FS), and low-threshold nonfast-spiking interneurons (nFS) for working memory of sequential and concurrent directional cues. Our model exhibits the γ (30-100 Hz) and β (10-30 Hz) band oscillation during the retention of both concurrent cues and sequential cues. We found that the β oscillation results from the interaction between pyramidal cells and nFS, whereas the γ oscillation emerges from the interaction between pyramidal cells and FS because of the strong excitation elicited by cue presentation, shedding light on the mechanism underlying the enhancement of γ power in many cognitive executions.
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Affiliation(s)
- Shukuo Zhao
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Jinpu Zhou
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Yongwen Zhang
- School of Systems Science, Beijing Normal University, Beijing 100875, China
| | - Da-Hui Wang
- School of Systems Science, Beijing Normal University, Beijing 100875, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
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27
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Yoshiiwa S, Takano H, Ido K, Kawato M, Morishige KI. Group analysis and classification of working memory task conditions using electroencephalogram cortical currents during an n-back task. Front Neurosci 2023; 17:1222749. [PMID: 37942143 PMCID: PMC10627866 DOI: 10.3389/fnins.2023.1222749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 10/03/2023] [Indexed: 11/10/2023] Open
Abstract
Electroencephalographic studies of working memory have demonstrated cortical activity and oscillatory representations without clarifying how the stored information is retained in the brain. To address this gap, we measured scalp electroencephalography data, while participants performed a modified n-back working memory task. We calculated the current intensities from the estimated cortical currents by introducing a statistical map generated using Neurosynth as prior information. Group analysis of the cortical current level revealed that the current amplitudes and power spectra were significantly different between the modified n-back and delayed match-to-sample conditions. Additionally, we classified information on the working memory task conditions using the amplitudes and power spectra of the currents during the encoding and retention periods. Our results indicate that the representation of executive control over memory retention may be mediated through both persistent neural activity and oscillatory representations in the beta and gamma bands over multiple cortical regions that contribute to visual working memory functions.
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Affiliation(s)
| | - Hironobu Takano
- Department of Intelligent Robotics, Toyama Prefectural University, Imizu, Japan
| | - Keisuke Ido
- Center of Liberal Arts and Science, Toyama Prefectural University, Imizu, Japan
| | - Mitsuo Kawato
- Department of Intelligent Robotics, Toyama Prefectural University, Imizu, Japan
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Ken-ichi Morishige
- Department of Intelligent Robotics, Toyama Prefectural University, Imizu, Japan
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
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28
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Dubey A, Markowitz DA, Pesaran B. Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex. Neuron 2023; 111:3321-3334.e5. [PMID: 37499660 PMCID: PMC10935562 DOI: 10.1016/j.neuron.2023.06.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 11/30/2022] [Accepted: 06/26/2023] [Indexed: 07/29/2023]
Abstract
Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, we trained two rhesus monkeys on a two-target, free-choice luminance-reward selection task. We demonstrate that visual-movement (VM) neurons and nonvisual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.
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Affiliation(s)
- Agrita Dubey
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - David A Markowitz
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Bijan Pesaran
- Center for Neural Science, New York University, New York, NY 10003, USA; Departments of Neurosurgery, Neuroscience, and Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
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29
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Li S, Rosen MC, Chang S, David S, Freedman DJ. Alterations of neural activity in the prefrontal cortex associated with deficits in working memory performance. Front Behav Neurosci 2023; 17:1213435. [PMID: 37915531 PMCID: PMC10616307 DOI: 10.3389/fnbeh.2023.1213435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 08/31/2023] [Indexed: 11/03/2023] Open
Abstract
Working memory (WM), a core cognitive function, enables the temporary holding and manipulation of information in mind to support ongoing behavior. Neurophysiological recordings conducted in nonhuman primates have revealed neural correlates of this process in a network of higher-order cortical regions, particularly the prefrontal cortex (PFC). Here, we review the circuit mechanisms and functional importance of WM-related activity in these areas. Recent neurophysiological data indicates that the absence of these neural correlates at different stages of WM is accompanied by distinct behavioral deficits, which are characteristic of various disease states/normal aging and which we review here. Finally, we discuss emerging evidence of electrical stimulation ameliorating these WM deficits in both humans and non-human primates. These results are important for a basic understanding of the neural mechanisms supporting WM, as well as for translational efforts to developing therapies capable of enhancing healthy WM ability or restoring WM from dysfunction.
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Affiliation(s)
- Sihai Li
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Matthew C. Rosen
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Suha Chang
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - Samuel David
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
| | - David J. Freedman
- Department of Neurobiology, The University of Chicago, Chicago, IL, United States
- Neuroscience Institute, The University of Chicago, Chicago, IL, United States
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30
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Garwood IC, Major AJ, Antonini MJ, Correa J, Lee Y, Sahasrabudhe A, Mahnke MK, Miller EK, Brown EN, Anikeeva P. Multifunctional fibers enable modulation of cortical and deep brain activity during cognitive behavior in macaques. SCIENCE ADVANCES 2023; 9:eadh0974. [PMID: 37801492 PMCID: PMC10558126 DOI: 10.1126/sciadv.adh0974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/05/2023] [Indexed: 10/08/2023]
Abstract
Recording and modulating neural activity in vivo enables investigations of the neurophysiology underlying behavior and disease. However, there is a dearth of translational tools for simultaneous recording and localized receptor-specific modulation. We address this limitation by translating multifunctional fiber neurotechnology previously only available for rodent studies to enable cortical and subcortical neural recording and modulation in macaques. We record single-neuron and broader oscillatory activity during intracranial GABA infusions in the premotor cortex and putamen. By applying state-space models to characterize changes in electrophysiology, we uncover that neural activity evoked by a working memory task is reshaped by even a modest local inhibition. The recordings provide detailed insight into the electrophysiological effect of neurotransmitter receptor modulation in both cortical and subcortical structures in an awake macaque. Our results demonstrate a first-time application of multifunctional fibers for causal studies of neuronal activity in behaving nonhuman primates and pave the way for clinical translation of fiber-based neurotechnology.
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Affiliation(s)
- Indie C. Garwood
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alex J. Major
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Marc-Joseph Antonini
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Josefina Correa
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Youngbin Lee
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Atharva Sahasrabudhe
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Meredith K. Mahnke
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Earl K. Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emery N. Brown
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Anaesthesia, Harvard Medical School, Boston, MA, USA
| | - Polina Anikeeva
- Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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31
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Jensen M, Hyder R, Westner BU, Højlund A, Shtyrov Y. Speech comprehension across time, space, frequency, and age: MEG-MVPA classification of intertrial phase coherence. Neuropsychologia 2023; 188:108602. [PMID: 37270028 DOI: 10.1016/j.neuropsychologia.2023.108602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 04/24/2023] [Accepted: 05/31/2023] [Indexed: 06/05/2023]
Abstract
Language is a key part of human cognition, essential for our well-being at all stages of our lives. Whereas many neurocognitive abilities decline with age, for language the picture is much less clear, and how exactly speech comprehension changes with ageing is still unknown. To investigate this, we employed magnetoencephalography (MEG) and recorded neuromagnetic brain responses to auditory linguistic stimuli in healthy participants of younger and older age using a passive task-free paradigm and a range of different linguistic stimulus contrasts, which enabled us to assess neural processing of spoken language at multiple levels (lexical, semantic, morphosyntactic). Using machine learning-based classification algorithms to scrutinise intertrial phase coherence of MEG responses in cortical source space, we found that patterns of oscillatory neural activity diverged between younger and older participants across several frequency bands (alpha, beta, gamma) for all tested linguistic information types. The results suggest multiple age-related changes in the brain's neurolinguistic circuits, which may be due to both healthy ageing in general and compensatory processes in particular.
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Affiliation(s)
- Mads Jensen
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Research Unit for Robophilosophy and Integrative Social Robotics, School of Culture and Society, Aarhus University, Aarhus, Denmark; Interacting Minds Centre, School of Culture and Society, Aarhus University, Aarhus, Denmark.
| | - Rasha Hyder
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Britta U Westner
- Radboud University, Donders Centre for Cognition, Nijmegen, the Netherlands
| | - Andreas Højlund
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Linguistics, Cognitive Science and Semiotics, School of Communication and Culture, Aarhus University, Aarhus, Denmark
| | - Yury Shtyrov
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
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32
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Chaudhari A, Wang X, Wu A, Liu H. Repeated Transcranial Photobiomodulation with Light-Emitting Diodes Improves Psychomotor Vigilance and EEG Networks of the Human Brain. Bioengineering (Basel) 2023; 10:1043. [PMID: 37760145 PMCID: PMC10525861 DOI: 10.3390/bioengineering10091043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/16/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023] Open
Abstract
Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group's singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.
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Affiliation(s)
| | | | | | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd, Arlington, TX 76019, USA; (A.C.); (X.W.); (A.W.)
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33
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Boo YJ, Kim DW, Park JY, Kim BS, Chang JW, Kang JI, Kim SJ. Altered prefrontal beta oscillatory activity during removal of information from working memory in obsessive-compulsive disorder. BMC Psychiatry 2023; 23:645. [PMID: 37667294 PMCID: PMC10478376 DOI: 10.1186/s12888-023-05149-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 08/28/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) is related to working memory impairment. Since patients with OCD have difficulty controlling their obsessive thoughts, removal of irrelevant information might be important in the pathophysiology of OCD. However, little is known about brain activity during the removal of information from working memory in patients with OCD. Our goal was to explore potential deficits in inhibitory function related to working memory processes in patients with OCD. METHODS Sixteen OCD patients and 20 healthy controls (HCs) were recruited. We compared in prefrontal alpha and beta band activity derived from magnetoencephalography (MEG) between patients with OCD and HCs during multiple phases of information processing associated with working memory, especially in post-trial period of the visuospatial working memory task (the delayed matching-to-sample task), which is presumed to be related to the information removal process of working memory. RESULTS Prefrontal post-trial beta power change (presumed to occur at high levels during the post-trial period) exhibited significant reductions in patients with OCD compared to HCs. In addition, the post-trial beta power change was negatively correlated with Obsessive-Compulsive Inventory-Revised total scores in patients with OCD. CONCLUSIONS These findings suggest that impairment in the removal of information from working memory might be a key mechanism underlying the inability of OCD patients to rid themselves of their obsessions.
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Affiliation(s)
- Young Jun Boo
- Department of Psychiatry, Graduate School, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Do-Won Kim
- Department of Biomedical Engineering, College of Engineering Sciences, Chonnam National University, 50 Daehak-ro, Yeosu, Republic of Korea
- School of Healthcare and Biomedical Engineering, College of Engineering Sciences, Chonnam National University, 50 Daehak-ro, Yeosu, Republic of Korea
| | - Jin Young Park
- Department of Psychiatry, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea
- Department of Psychiatry, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea
| | - Bong Soo Kim
- Department of Neurosurgery, Brain Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jin Woo Chang
- Department of Neurosurgery, Brain Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jee In Kang
- Department of Psychiatry, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
| | - Se Joo Kim
- Department of Psychiatry, Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
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34
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Paulo DL, Qian H, Subramanian D, Johnson GW, Zhao Z, Hett K, Kang H, Chris Kao C, Roy N, Summers JE, Claassen DO, Dhima K, Bick SK. Corticostriatal beta oscillation changes associated with cognitive function in Parkinson's disease. Brain 2023; 146:3662-3675. [PMID: 37327379 PMCID: PMC10681666 DOI: 10.1093/brain/awad206] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/08/2023] [Accepted: 05/16/2023] [Indexed: 06/18/2023] Open
Abstract
Cognitive impairment is the most frequent non-motor symptom in Parkinson's disease and is associated with deficits in a number of cognitive functions including working memory. However, the pathophysiology of Parkinson's disease cognitive impairment is poorly understood. Beta oscillations have previously been shown to play an important role in cognitive functions including working memory encoding. Decreased dopamine in motor cortico-striato-thalamo-cortical (CSTC) circuits increases the spectral power of beta oscillations and results in Parkinson's disease motor symptoms. Analogous changes in parallel cognitive CSTC circuits involving the caudate and dorsolateral prefrontal cortex (DLPFC) may contribute to Parkinson's disease cognitive impairment. The objective of our study is to evaluate whether changes in beta oscillations in the caudate and DLPFC contribute to cognitive impairment in Parkinson's disease patients. To investigate this, we used local field potential recordings during deep brain stimulation surgery in 15 patients with Parkinson's disease. Local field potentials were recorded from DLPFC and caudate at rest and during a working memory task. We examined changes in beta oscillatory power during the working memory task as well as the relationship of beta oscillatory activity to preoperative cognitive status, as determined from neuropsychological testing results. We additionally conducted exploratory analyses on the relationship between cognitive impairment and task-based changes in spectral power in additional frequency bands. Spectral power of beta oscillations decreased in both DLPFC and caudate during working memory encoding and increased in these structures during feedback. Subjects with cognitive impairment had smaller decreases in caudate and DLPFC beta oscillatory power during encoding. In our exploratory analysis, we found that similar differences occurred in alpha frequencies in caudate and theta and alpha in DLPFC. Our findings suggest that oscillatory power changes in cognitive CSTC circuits may contribute to cognitive symptoms in patients with Parkinson's disease. These findings may inform the future development of novel neuromodulatory treatments for cognitive impairment in Parkinson's disease.
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Affiliation(s)
- Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Helen Qian
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37212, USA
| | - Deeptha Subramanian
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Graham W Johnson
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- School of Medicine, Vanderbilt University, Nashville, TN 37212, USA
| | - Zixiang Zhao
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Kilian Hett
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - C Chris Kao
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Noah Roy
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Jessica E Summers
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Daniel O Claassen
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Kaltra Dhima
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37212 USA
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37212, USA
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Pinotsis DA, Miller EK. In vivo ephaptic coupling allows memory network formation. Cereb Cortex 2023; 33:9877-9895. [PMID: 37420330 PMCID: PMC10472500 DOI: 10.1093/cercor/bhad251] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/20/2023] [Accepted: 06/23/2023] [Indexed: 07/09/2023] Open
Abstract
It is increasingly clear that memories are distributed across multiple brain areas. Such "engram complexes" are important features of memory formation and consolidation. Here, we test the hypothesis that engram complexes are formed in part by bioelectric fields that sculpt and guide the neural activity and tie together the areas that participate in engram complexes. Like the conductor of an orchestra, the fields influence each musician or neuron and orchestrate the output, the symphony. Our results use the theory of synergetics, machine learning, and data from a spatial delayed saccade task and provide evidence for in vivo ephaptic coupling in memory representations.
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Affiliation(s)
- Dimitris A Pinotsis
- Department of Psychology, Centre for Mathematical Neuroscience and Psychology, University of London, London EC1V 0HB, United Kingdom
- The Picower Institute for Learning & Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Earl K Miller
- The Picower Institute for Learning & Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
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Cho S, Choi JH. A guide towards optimal detection of transient oscillatory bursts with unknown parameters. J Neural Eng 2023; 20:046007. [PMID: 37339619 DOI: 10.1088/1741-2552/acdffd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 06/20/2023] [Indexed: 06/22/2023]
Abstract
Objectives. Recent event-based analyses of transient neural activities have characterized the oscillatory bursts as a neural signature that bridges dynamic neural states to cognition and behaviors. Following this insight, our study aimed to (1) compare the efficacy of common burst detection algorithms under varying signal-to-noise ratios and event durations using synthetic signals and (2) establish a strategic guideline for selecting the optimal algorithm for real datasets with undefined properties.Approach.We tested the robustness of burst detection algorithms using a simulation dataset comprising bursts of multiple frequencies. To systematically assess their performance, we used a metric called 'detection confidence', quantifying classification accuracy and temporal precision in a balanced manner. Given that burst properties in empirical data are often unknown in advance, we then proposed a selection rule to identify an optimal algorithm for a given dataset and validated its application on local field potentials of basolateral amygdala recorded from male mice (n=8) exposed to a natural threat.Main Results.Our simulation-based evaluation demonstrated that burst detection is contingent upon event duration, whereas accurately pinpointing burst onsets is more susceptible to noise level. For real data, the algorithm chosen based on the selection rule exhibited superior detection and temporal accuracy, although its statistical significance differed across frequency bands. Notably, the algorithm chosen by human visual screening differed from the one recommended by the rule, implying a potential misalignment between human priors and mathematical assumptions of the algorithms.Significance.Therefore, our findings underscore that the precise detection of transient bursts is fundamentally influenced by the chosen algorithm. The proposed algorithm-selection rule suggests a potentially viable solution, while also emphasizing the inherent limitations originating from algorithmic design and volatile performances across datasets. Consequently, this study cautions against relying solely on heuristic-based approaches, advocating for a careful algorithm selection in burst detection studies.
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Affiliation(s)
- SungJun Cho
- Center for Neuroscience, Korea Institute of Science and Technology, Hwarang-ro 14-gil 5, Seongbuk-gu, Seoul 02792, Republic of Korea
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, United Kingdom
| | - Jee Hyun Choi
- Center for Neuroscience, Korea Institute of Science and Technology, Hwarang-ro 14-gil 5, Seongbuk-gu, Seoul 02792, Republic of Korea
- Department of Neural Sciences, University of Science and Technology, 217, Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea
- Department of Physics and Center for Theoretical Physics, Seoul National University, Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
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McKeon SD, Calabro F, Thorpe RV, de la Fuente A, Foran W, Parr AC, Jones SR, Luna B. Age-related differences in transient gamma band activity during working memory maintenance through adolescence. Neuroimage 2023; 274:120112. [PMID: 37105338 PMCID: PMC10214866 DOI: 10.1016/j.neuroimage.2023.120112] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 04/06/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
Adolescence is a stage of development characterized by neurodevelopmental specialization of cognitive processes. In particular, working memory continues to improve through adolescence, with increases in response accuracy and decreases in response latency continuing well into the twenties. Human electroencephalogram (EEG) studies indicate that gamma oscillations (35-65 Hz) during the working memory delay period support the maintenance of mnemonic information guiding subsequent goal-driven behavior, which decrease in power with development. Importantly, recent electrophysiological studies have shown that gamma events, more so than sustained activity, may underlie working memory maintenance during the delay period. However, developmental differences in gamma events during working memory have not been studied. Here, we used EEG in conjunction with a novel spectral event processing approach to investigate age-related differences in transient gamma band activity during a memory guided saccade (MGS) task in 164 10- to 30-year-olds. Total gamma power was found to significantly decrease through adolescence, replicating prior findings. Results from the spectral event pipeline showed age-related decreases in the mean power of gamma events and trial-by-trial power variability across both the delay period and fixation epochs of the MGS task. In addition, we found that while event number decreased with age during the fixation period, the developmental decrease during the delay period was more dramatic, resulting in an increase in event spiking from fixation to delay in adolescence but not adulthood. While average power of the transient gamma events was found to mediate age-related differences in total gamma power in the fixation and delay periods, the number of gamma events was related to total power in only the delay period, suggesting that the power of gamma events may underlie the sustained gamma activity seen in EEG literature while the number of events may directly support age-related improvements in working memory maintenance. Our findings provide compelling new evidence for mechanistic changes in neural processing characterized by refinements in neural function as behavior becomes optimized in adulthood.
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Affiliation(s)
- Shane D McKeon
- Department of Bioengineering, University of Pittsburgh, PA, 15213, United States; The Center for the Neural Basis of Cognition, University of Pittsburgh, PA, 15213, United States.
| | - Finnegan Calabro
- Department of Bioengineering, University of Pittsburgh, PA, 15213, United States; The Center for the Neural Basis of Cognition, University of Pittsburgh, PA, 15213, United States; Department of Psychiatry, University of Pittsburgh, PA, 15213, United States
| | - Ryan V Thorpe
- Department of Neuroscience, Brown University, Providence, RI, United States
| | - Alethia de la Fuente
- Department of Physics, University of Buenos Aires, Argentina; Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, Buenos Aires, Argentina; National Scientific and Technical Research Council, Buenos Aires, Argentina
| | - Will Foran
- Department of Psychiatry, University of Pittsburgh, PA, 15213, United States
| | - Ashley C Parr
- The Center for the Neural Basis of Cognition, University of Pittsburgh, PA, 15213, United States; Department of Psychiatry, University of Pittsburgh, PA, 15213, United States
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI, United States
| | - Beatriz Luna
- The Center for the Neural Basis of Cognition, University of Pittsburgh, PA, 15213, United States; Department of Psychiatry, University of Pittsburgh, PA, 15213, United States.
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Hernández O, Zurek E, Barbosa J, Villasana M. A comparative study of the cortical function during the interpretation of algorithms in pseudocode and the solution of first-order algebraic equations. PLoS One 2023; 18:e0274713. [PMID: 37368883 DOI: 10.1371/journal.pone.0274713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 06/11/2023] [Indexed: 06/29/2023] Open
Abstract
This study intends to determine whether similarities of the functioning of the cerebral cortex exist, modeled as a graph, during the execution of mathematical tasks and programming related tasks. The comparison is done using network parameters and during the development of computer programming tasks and the solution of first-order algebraic equations. For that purpose, electroencephalographic recordings (EEG) were made with a volunteer group of 16 students of systems engineering of Universidad del Norte in Colombia, while they were performing computer programming tasks and solving first-order algebraic equations with three levels of difficulty. Then, based on the Synchronization Likelihood method, graph models of functional cortical networks were developed, whose parameters of Small-Worldness (SWN), global(Eg) and local (El) efficiency were compared between both types of tasks. From this study, it can be highlighted, first, the novelty of studying cortical function during the solution of algebraic equations and during programming tasks; second, significant differences between both types of tasks observed only in the delta and theta bands. Likewise, the differences between simpler mathematical tasks with the other levels in both types of tasks; third, the Brodmann areas 21 and 42, associated with auditory sensory processing, can be considered as differentiating elements of programming tasks; as well as Brodmann area 8, during equation solving.
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Affiliation(s)
- Oscar Hernández
- Departamento de Química y Biología, Universidad del Norte, Barranquilla, Atlántico, Colombia
| | - Eduardo Zurek
- Departamento de Ingeniería de sistemas, Universidad del Norte, Barranquilla, Atlántico, Colombia
| | - John Barbosa
- Departamento de Ingeniería de sistemas, Universidad del Norte, Barranquilla, Atlántico, Colombia
| | - Minaya Villasana
- Departamento de Cómputo Científico y Estadística, Universidad Simón Bolivar, Caracas, Venezuela
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Slotnick SD. No convincing evidence the hippocampus is associated with working memory. Cogn Neurosci 2023. [PMID: 37300307 DOI: 10.1080/17588928.2023.2223919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/03/2023] [Indexed: 06/12/2023]
Abstract
In a previous discussion paper , twenty-six working memory fMRI studies that reported activity in the hippocampus were systematically analyzed. None of these studies provided convincing evidence that the hippocampus was active during the late delay phase, the only period in which working memory can be isolated from long-term memory processes. Based on these results, it was concluded that working memory does not activate the hippocampus. Six commentaries on the discussion paper were received from Courtney (2022), Kessels & Bergmann (2022), Peters and Reithler (2022), Rose and Chao (2022), Stern & Hasselmo (2022), and Wood, Clark, and Nee (2022). Based on these commentaries, the present response paper considered whether there is evidence of sustained hippocampal activity during the working memory delay period based on depth-electrode recording, whether there are activity-silent working memory mechanisms in the hippocampus, and whether there is hippocampal lesion evidence indicating this region is important for working memory. There was no convincing electrophysiological or neuropsychological evidence that the hippocampus is associated with working memory maintenance, and activity-silent mechanisms were arguably speculative. Given that only a small fraction (approximately 5%) of fMRI studies have reported hippocampal activity in working memory tasks and lesion evidence indicates the hippocampus is not necessary for working memory, the burden of proof is on proponents of view that the hippocampus is important for working memory to provide compelling evidence to support their position. To date, in my view, there is no convincing evidence that the hippocampus is associated with working memory.
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Singh B, Wang Z, Constantinidis C. Neuronal selectivity for stimulus information determines prefrontal LFP gamma power regardless of task execution. Commun Biol 2023; 6:505. [PMID: 37169826 PMCID: PMC10175284 DOI: 10.1038/s42003-023-04855-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/20/2023] [Indexed: 05/13/2023] Open
Abstract
Local field potential (LFP) power in the gamma frequency is modulated by cognitive variables during task execution. We sought to examine whether such modulations only emerge when task rules are established. We therefore analyzed neuronal firing and LFPs in different prefrontal subdivisions before and after the same monkeys were trained to perform cognitive tasks. Prior to task rule learning, sites containing neurons selective for stimuli already exhibited increased gamma power during and after the passive viewing of stimuli compared to the baseline period. Unexpectedly, when the same monkeys learned to maintain these stimuli in working memory, the elevation of gamma power above the baseline was diminished, despite an overall increase in firing rate. Learning and executing the task further decoupled LFP power from single neuron firing. Gamma power decreased at the time when subjects needed to make a judgment about whether two stimuli were the same or not, and differential gamma power was observed for matching and nonmatching stimuli. Our results indicate that prefrontal gamma power emerges spontaneously, not necessarily tied to a cognitive task being executed.
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Affiliation(s)
- Balbir Singh
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA.
| | - Zhengyang Wang
- Neuroscience Program, Vanderbilt University, Nashville, TN, 37235, USA
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, 37235, USA
- Neuroscience Program, Vanderbilt University, Nashville, TN, 37235, USA
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
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41
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Chen Z, Headley DB, Gomez-Alatorre LF, Kanta V, Ho KC, Pare D, Nair SS. Approaches to characterizing oscillatory burst detection algorithms for electrophysiological recordings. J Neurosci Methods 2023; 391:109865. [PMID: 37086753 PMCID: PMC10175206 DOI: 10.1016/j.jneumeth.2023.109865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 04/12/2023] [Accepted: 04/17/2023] [Indexed: 04/24/2023]
Abstract
BACKGROUND Cognitive processes are associated with fast oscillations of the local field potential and electroencephalogram. There is a growing interest in targeting them because these are disrupted by aging and disease. This has proven challenging because they often occur as short-lasting bursts. Moreover, they are obscured by broad-band aperiodic activity reflecting other neural processes. These attributes have made it exceedingly difficult to develop analytical tools for estimating the reliability of detection methods. NEW METHOD To address this challenge, we developed an open-source toolkit with four processing steps, that can be tailored to specific brain states and individuals. First, the power spectrum is decomposed into periodic and aperiodic components, each of whose properties are estimated. Second, the properties of the transient oscillatory bursts that contribute to the periodic component are derived and optimized to account for contamination from the aperiodic component. Third, using the burst properties and aperiodic power spectrum, surrogate neural signals are synthesized that match the observed signal's spectrotemporal properties. Lastly, oscillatory burst detection algorithms run on the surrogate signals are subjected to a receiver operating characteristic analysis, providing insight into their performance. RESULTS The characterization algorithm extracted features of oscillatory bursts across multiple frequency bands and brain regions, allowing for recording-specific evaluation of detection performance. For our dataset, the optimal detection threshold for gamma bursts was found to be lower than the one commonly used. COMPARISON WITH EXISTING METHODS Existing methods characterize the power spectrum, while ours evaluates the detection of oscillatory bursts. CONCLUSIONS This pipeline facilitates the evaluation of thresholds for detection algorithms from individual recordings.
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Affiliation(s)
- Ziao Chen
- Electrical Engineering & Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Drew B Headley
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA
| | - Luisa F Gomez-Alatorre
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA; Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA
| | - Vasiliki Kanta
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA; Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA
| | - K C Ho
- Electrical Engineering & Computer Science, University of Missouri, Columbia, MO 65211, USA
| | - Denis Pare
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, 197 University Ave, Newark, NJ 07102, USA
| | - Satish S Nair
- Electrical Engineering & Computer Science, University of Missouri, Columbia, MO 65211, USA.
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Williams N, Wang S, Arnulfo G, Nobili L, Palva S, Palva J. Modules in connectomes of phase-synchronization comprise anatomically contiguous, functionally related regions. Neuroimage 2023; 272:120036. [PMID: 36966852 DOI: 10.1016/j.neuroimage.2023.120036] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 03/14/2023] [Indexed: 04/05/2023] Open
Abstract
Modules in brain functional connectomes are essential to balancing segregation and integration of neuronal activity. Connectomes are the complete set of pairwise connections between brain regions. Non-invasive Electroencephalography (EEG) and Magnetoencephalography (MEG) have been used to identify modules in connectomes of phase-synchronization. However, their resolution is suboptimal because of spurious phase-synchronization due to EEG volume conduction or MEG field spread. Here, we used invasive, intracerebral recordings from stereo-electroencephalography (SEEG, N = 67), to identify modules in connectomes of phase-synchronization. To generate SEEG-based group-level connectomes affected only minimally by volume conduction, we used submillimeter accurate localization of SEEG contacts and referenced electrode contacts in cortical gray matter to their closest contacts in white matter. Combining community detection methods with consensus clustering, we found that the connectomes of phase-synchronization were characterized by distinct and stable modules at multiple spatial scales, across frequencies from 3 to 320 Hz. These modules were highly similar within canonical frequency bands. Unlike the distributed brain systems identified with functional Magnetic Resonance Imaging (fMRI), modules up to the high-gamma frequency band comprised only anatomically contiguous regions. Notably, the identified modules comprised cortical regions involved in shared repertoires of sensorimotor and cognitive functions including memory, language and attention. These results suggest that the identified modules represent functionally specialised brain systems, which only partially overlap with the brain systems reported with fMRI. Hence, these modules might regulate the balance between functional segregation and functional integration through phase-synchronization.
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43
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Morris AT, Temereanca S, Zandvakili A, Thorpe R, Sliva DD, Greenberg BD, Carpenter LL, Philip NS, Jones SR. Fronto-central resting-state 15-29 Hz transient beta events change with therapeutic transcranial magnetic stimulation for posttraumatic stress disorder and major depressive disorder. Sci Rep 2023; 13:6366. [PMID: 37076496 PMCID: PMC10115889 DOI: 10.1038/s41598-023-32801-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 04/03/2023] [Indexed: 04/21/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD) and shows promise for posttraumatic stress disorder (PTSD), yet effectiveness varies. Electroencephalography (EEG) can identify rTMS-associated brain changes. EEG oscillations are often examined using averaging approaches that mask finer time-scale dynamics. Recent advances show some brain oscillations emerge as transient increases in power, a phenomenon termed "Spectral Events," and that event characteristics correspond with cognitive functions. We applied Spectral Event analyses to identify potential EEG biomarkers of effective rTMS treatment. Resting 8-electrode EEG was collected from 23 patients with MDD and PTSD before and after 5 Hz rTMS targeting the left dorsolateral prefrontal cortex. Using an open-source toolbox ( https://github.com/jonescompneurolab/SpectralEvents ), we quantified event features and tested for treatment associated changes. Spectral Events in delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz) bands occurred in all patients. rTMS-induced improvement in comorbid MDD PTSD were associated with pre- to post-treatment changes in fronto-central electrode beta event features, including frontal beta event frequency spans and durations, and central beta event maxima power. Furthermore, frontal pre-treatment beta event duration correlated negatively with MDD symptom improvement. Beta events may provide new biomarkers of clinical response and advance the understanding of rTMS.
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Affiliation(s)
- Alexander T Morris
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA
| | - Simona Temereanca
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA.
- Department of Neuroscience, Brown University, Providence, RI, USA.
- Carney Institute for Brain Science, Brown University, Providence, RI, USA.
| | - Amin Zandvakili
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
| | - Ryan Thorpe
- Department of Neuroscience, Brown University, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Danielle D Sliva
- Department of Neuroscience, Brown University, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Benjamin D Greenberg
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
- COBRE Center for Neuromodulation, Butler Hospital, Providence, RI, USA
| | - Linda L Carpenter
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
- COBRE Center for Neuromodulation, Butler Hospital, Providence, RI, USA
- Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - Noah S Philip
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
- COBRE Center for Neuromodulation, Butler Hospital, Providence, RI, USA
| | - Stephanie R Jones
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence, Providence, RI, USA.
- Department of Neuroscience, Brown University, Providence, RI, USA.
- Carney Institute for Brain Science, Brown University, Providence, RI, USA.
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Morris AT, Temereanca S, Zandvakili A, Thorpe R, Sliva DD, Greenberg BD, Carpenter LL, Philip NS, Jones SR. Fronto-central resting-state 15-29Hz transient beta events change with therapeutic transcranial magnetic stimulation for posttraumatic stress disorder and major depressive disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.11.23286902. [PMID: 36993547 PMCID: PMC10055566 DOI: 10.1101/2023.03.11.23286902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is an established treatment for major depressive disorder (MDD) and shows promise for posttraumatic stress disorder (PTSD), yet effectiveness varies. Electroencephalography (EEG) can identify rTMS-associated brain changes. EEG oscillations are often examined using averaging approaches that mask finer time-scale dynamics. Recent advances show some brain oscillations emerge as transient increases in power, a phenomenon termed "Spectral Events," and that event characteristics correspond with cognitive functions. We applied Spectral Event analyses to identify potential EEG biomarkers of effective rTMS treatment. Resting 8-electrode EEG was collected from 23 patients with MDD and PTSD before and after 5Hz rTMS targeting the left dorsolateral prefrontal cortex. Using an open-source toolbox ( https://github.com/jonescompneurolab/SpectralEvents ), we quantified event features and tested for treatment associated changes. Spectral Events in delta/theta (1-6 Hz), alpha (7-14 Hz), and beta (15-29 Hz) bands occurred in all patients. rTMS-induced improvement in comorbid MDD PTSD were associated with pre-to post-treatment changes in fronto-central electrode beta event features, including frontal beta event frequency spans and durations, and central beta event maxima power. Furthermore, frontal pre-treatment beta event duration correlated negatively with MDD symptom improvement. Beta events may provide new biomarkers of clinical response and advance the understanding of rTMS.
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45
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Hein TP, Gong Z, Ivanova M, Fedele T, Nikulin V, Herrojo Ruiz M. Anterior cingulate and medial prefrontal cortex oscillations underlie learning alterations in trait anxiety in humans. Commun Biol 2023; 6:271. [PMID: 36922553 PMCID: PMC10017780 DOI: 10.1038/s42003-023-04628-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
Anxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.
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Affiliation(s)
- Thomas P Hein
- Goldsmiths, University of London, Psychology Department, Whitehead Building New Cross, London, SE14 6NW, UK
| | - Zheng Gong
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Marina Ivanova
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Tommaso Fedele
- Centre for Cognition and Decision making, Institute for Cognitive Neuroscience, HSE University, Moscow, Russian Federation
| | - Vadim Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Maria Herrojo Ruiz
- Goldsmiths, University of London, Psychology Department, Whitehead Building New Cross, London, SE14 6NW, UK.
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Murphy E. ROSE: A Neurocomputational Architecture for Syntax. ARXIV 2023:arXiv:2303.08877v1. [PMID: 36994166 PMCID: PMC10055479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
A comprehensive model of natural language processing in the brain must accommodate four components: representations, operations, structures and encoding. It further requires a principled account of how these different components mechanistically, and causally, relate to each another. While previous models have isolated regions of interest for structure-building and lexical access, and have utilized specific neural recording measures to expose possible signatures of syntax, many gaps remain with respect to bridging distinct scales of analysis that map onto these four components. By expanding existing accounts of how neural oscillations can index various linguistic processes, this article proposes a neurocomputational architecture for syntax, termed the ROSE model (Representation, Operation, Structure, Encoding). Under ROSE, the basic data structures of syntax are atomic features, types of mental representations (R), and are coded at the single-unit and ensemble level. Elementary computations (O) that transform these units into manipulable objects accessible to subsequent structure-building levels are coded via high frequency broadband γ activity. Low frequency synchronization and cross-frequency coupling code for recursive categorial inferences (S). Distinct forms of low frequency coupling and phase-amplitude coupling (δ-θ coupling via pSTS-IFG; θ-γ coupling via IFG to conceptual hubs in lateral and ventral temporal cortex) then encode these structures onto distinct workspaces (E). Causally connecting R to O is spike-phase/LFP coupling; connecting O to S is phase-amplitude coupling; connecting S to E is a system of frontotemporal traveling oscillations; connecting E back to lower levels is low-frequency phase resetting of spike-LFP coupling. This compositional neural code has important implications for algorithmic accounts, since it makes concrete predictions for the appropriate level of study for psycholinguistic parsing models. ROSE is reliant on neurophysiologically plausible mechanisms, is supported at all four levels by a range of recent empirical research, and provides an anatomically precise and falsifiable grounding for the basic property of natural language syntax: hierarchical, recursive structure-building.
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Affiliation(s)
- Elliot Murphy
- Vivian L. Smith Department of Neurosurgery, McGovern Medical School, UTHealth, Houston, TX, USA
- Texas Institute for Restorative Neurotechnologies, UTHealth, Houston, TX, USA
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47
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Working memory control dynamics follow principles of spatial computing. Nat Commun 2023; 14:1429. [PMID: 36918567 PMCID: PMC10015009 DOI: 10.1038/s41467-023-36555-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 02/07/2023] [Indexed: 03/16/2023] Open
Abstract
Working memory (WM) allows us to remember and selectively control a limited set of items. Neural evidence suggests it is achieved by interactions between bursts of beta and gamma oscillations. However, it is not clear how oscillations, reflecting coherent activity of millions of neurons, can selectively control individual WM items. Here we propose the novel concept of spatial computing where beta and gamma interactions cause item-specific activity to flow spatially across the network during a task. This way, control-related information such as item order is stored in the spatial activity independent of the detailed recurrent connectivity supporting the item-specific activity itself. The spatial flow is in turn reflected in low-dimensional activity shared by many neurons. We verify these predictions by analyzing local field potentials and neuronal spiking. We hypothesize that spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension.
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Su X, Zhang X, Pei J, Deng M, Pan L, Liu J, Cui M, Zhan C, Wang J, Wu Y, Zhao L, Wang Z, Liu J, Song Y. Working memory-related alterations in neural oscillations reveal the influence of in-vehicle toluene on cognition at low concentration. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:21723-21734. [PMID: 36274073 DOI: 10.1007/s11356-022-23627-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
Although toluene is a typical in-vehicle pollutant, the impacts of in-vehicle toluene exposure on cognitive functions remain unestablished. Therefore, this study aimed to investigate the effects of short-term toluene exposure in vehicles on working memory based on neural oscillations. In total, 24 healthy adults were recruited. Each subject was exposed to four different concentrations of toluene and divided into 0 ppb, 17.5 ppb, 35 ppb, and 70 ppb groups for self-control studies. After 4 h of exposure to each concentration of toluene, a behavioral test of visual working memory was performed while 19-channel electroencephalogram (EEG) signals were collected. Meanwhile, the power spectral density (PSD) and spatial distribution of working memory encoding, maintenance, and extraction periods were calculated by short-time Fourier transform to clarify the characteristic frequency bands, major brain regions, and characteristic channels of each period. To compare the changes in the characteristic patterns of neural oscillations under the effect of different concentrations of toluene. There was no significant difference in working memory reaction time and correct rate between the groups at different toluene concentrations (p > 0.05). The characteristic frequency band of the working memory neural oscillations in each group was the theta frequency band; the PSD of the theta frequency band was predominantly concentrated in the frontal area, and the characteristic channel was the Fz channel. The whole brain (F = 3.817, p < 0.05; F = 4.758, p < 0.01; F = 3.694, p < 0.05), the frontal area (F = 2.505, p < 0.05; F = 2.839, p < 0.05; F = 6.068, p < 0.05), the Fz channel (F = 3.522, p < 0.05; F = 3.745, p < 0.05; F = 6.526, p < 0.05), and the PSD of working memory in the theta frequency band was significantly increased in the 70 ppb group compared with the other three groups during the coding, maintenance, and retrieval phases of working memory. When the in-vehicle toluene exposure concentration was 70 ppb, the PSD of the characteristic frequency bands of working memory was significantly increased in the whole brain, major brain regions, and characteristic channels.
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Affiliation(s)
- Xiao Su
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xin Zhang
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jingjing Pei
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Meili Deng
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Liping Pan
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jie Liu
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Mingrui Cui
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Changqin Zhan
- Department of Neurology, Wuhu No.2 People's Hospital, Wuhu, 241000, Anhui, China
| | - Jiajing Wang
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Yakun Wu
- Tianjin Medical University, Tianjin, 300070, China
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Lei Zhao
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Zunkun Wang
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China
| | - Junjie Liu
- Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Engineering, Tianjin University, Tianjin, China.
| | - Yijun Song
- Key Laboratory of Post-Neuroinjury Neuro-Repair and Regeneration in Central Nervous System, Ministry of Education and Tianjin City, Tianjin Neurological Institute, Tianjin, 300052, China.
- General Medicine Department, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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Dubey A, Markowitz DA, Pesaran B. Top-down control of exogenous attentional selection is mediated by beta coherence in prefrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.11.523664. [PMID: 36711697 PMCID: PMC9882082 DOI: 10.1101/2023.01.11.523664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/15/2023]
Abstract
Salience-driven exogenous and goal-driven endogenous attentional selection are two distinct forms of attention that guide selection of task-irrelevant and task-relevant targets in primates. During conflict i.e, when salience and goal each favor the selection of different targets, endogenous selection of the task-relevant target relies on top-down control. Top-down attentional control mechanisms enable selection of the task-relevant target by limiting the influence of sensory information. Although the lateral prefrontal cortex (LPFC) is known to mediate top-down control, the neuronal mechanisms of top-down control of attentional selection are poorly understood. Here, using a two-target free-choice luminance-reward selection task, we demonstrate that visual-movement neurons and not visual neurons or movement neurons encode exogenous and endogenous selection. We then show that coherent-beta activity selectively modulates mechanisms of exogenous selection specifically during conflict and consequently may support top-down control. These results reveal the VM-neuron-specific network mechanisms of attentional selection and suggest a functional role for beta-frequency coherent neural dynamics in the modulation of sensory communication channels for the top-down control of attentional selection.
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Affiliation(s)
- Agrita Dubey
- Center for Neural Science, New York University, New York 10003
- Department of Neurosurgery, University of Pennsylvania, Philadelphia 19104
| | | | - Bijan Pesaran
- Center for Neural Science, New York University, New York 10003
- Department of Neurosurgery, University of Pennsylvania, Philadelphia 19104
- Department of Neuroscience, University of Pennsylvania, Philadelphia 19104
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104
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50
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Yang H, Shew WL, Yu S, Luczak A, Stringer C, Okun M. Editorial: Deciphering population neuronal dynamics: from theories to experiments. Front Syst Neurosci 2023; 17:1193488. [PMID: 37152611 PMCID: PMC10157151 DOI: 10.3389/fnsys.2023.1193488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 05/09/2023] Open
Affiliation(s)
- Hongdian Yang
- Department of Molecular, Cell and Systems Biology, University of California, Riverside, Riverside, CA, United States
- *Correspondence: Hongdian Yang
| | - Woodrow L. Shew
- Department of Physics, University of Arkansas, Fayetteville, AR, United States
| | - Shan Yu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Artur Luczak
- Department of Neuroscience, Canadian Center for Behavioural Neuroscience, University of Lethbridge, Lethbridge, AB, Canada
| | - Carsen Stringer
- Howard Hughes Medical Institute (HHMI) Janelia Research Campus, Ashburn, VA, United States
| | - Michael Okun
- Department of Psychology and Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom
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