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Cabral HV, Cudicio A, Bonardi A, Del Vecchio A, Falciati L, Orizio C, Martinez-Valdes E, Negro F. Neural Filtering of Physiological Tremor Oscillations to Spinal Motor Neurons Mediates Short-Term Acquisition of a Skill Learning Task. eNeuro 2024; 11:ENEURO.0043-24.2024. [PMID: 38866498 PMCID: PMC11255391 DOI: 10.1523/eneuro.0043-24.2024] [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: 01/30/2024] [Revised: 04/17/2024] [Accepted: 05/23/2024] [Indexed: 06/14/2024] Open
Abstract
The acquisition of a motor skill involves adaptations of spinal and supraspinal pathways to alpha motoneurons. In this study, we estimated the shared synaptic contributions of these pathways to understand the neural mechanisms underlying the short-term acquisition of a new force-matching task. High-density surface electromyography (HDsEMG) was acquired from the first dorsal interosseous (FDI; 7 males and 6 females) and tibialis anterior (TA; 7 males and 4 females) during 15 trials of an isometric force-matching task. For two selected trials (pre- and post-skill acquisition), we decomposed the HDsEMG into motor unit spike trains, tracked motor units between trials, and calculated the mean discharge rate and the coefficient of variation of interspike interval (COVISI). We also quantified the post/pre ratio of motor units' coherence within delta, alpha, and beta bands. Force-matching improvements were accompanied by increased mean discharge rate and decreased COVISI for both muscles. Moreover, the area under the curve within alpha band decreased by ∼22% (TA) and ∼13% (FDI), with no delta or beta bands changes. These reductions correlated significantly with increased coupling between force/neural drive and target oscillations. These results suggest that short-term force-matching skill acquisition is mediated by attenuation of physiological tremor oscillations in the shared synaptic inputs. Supported by simulations, a plausible mechanism for alpha band reductions may involve spinal interneuron phase-cancelling descending oscillations. Therefore, during skill learning, the central nervous system acts as a matched filter, adjusting synaptic weights of shared inputs to suppress neural components unrelated to the specific task.
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Affiliation(s)
- Hélio V Cabral
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
| | - Alessandro Cudicio
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
| | - Alberto Bonardi
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
| | - Alessandro Del Vecchio
- Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander University, Erlangen 91052, Germany
| | - Luca Falciati
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
| | - Claudio Orizio
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
| | - Eduardo Martinez-Valdes
- School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham B152TT, United Kingdom
| | - Francesco Negro
- Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia 25123, Italy
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Chang M, Suzuki S, Kurose T, Ibaraki T. Pretraining alpha rhythm enhancement by neurofeedback facilitates short-term perceptual learning and improves visual acuity by facilitated consolidation. FRONTIERS IN NEUROERGONOMICS 2024; 5:1399578. [PMID: 38894852 PMCID: PMC11184131 DOI: 10.3389/fnrgo.2024.1399578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024]
Abstract
Introduction Learning through perceptual training using the Gabor patch (GP) has attracted attention as a new vision restoration technique for myopia and age-related deterioration of visual acuity (VA). However, the task itself is monotonous and painful and requires numerous training sessions and some time before being effective, which has been a challenge for its widespread application. One effective means of facilitating perceptual learning is the empowerment of EEG alpha rhythm in the sensory cortex before neurofeedback (NF) training; however, there is a lack of evidence for VA. Methods We investigated whether four 30-min sessions of GP training, conducted over 2 weeks with/without EEG NF to increase alpha power (NF and control group, respectively), can improve vision in myopic subjects. Contrast sensitivity (CS) and VA were measured before and after each GP training. Results The NF group showed an improvement in CS at the fourth training session, not observed in the control group. In addition, VA improved only in the NF group at the third and fourth training sessions, this appears as a consolidation effect (maintenance of the previous training effect). Participants who produced stronger alpha power during the third training session showed greater VA recovery during the fourth training session. Discussion These results indicate that enhanced pretraining alpha empowerment strengthens the subsequent consolidation of perceptual learning and that even a short period of GP training can have a positive effect on VA recovery. This simple protocol may facilitate use of a training method to easily recover vision.
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Affiliation(s)
| | - Shuntaro Suzuki
- Vie, Inc., Kamakura, Japan
- NTT Data Institute of Management Consulting, Inc., Tokyo, Japan
| | | | - Takuya Ibaraki
- Vie, Inc., Kamakura, Japan
- NTT Data Institute of Management Consulting, Inc., Tokyo, Japan
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3
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Kang JH, Bae JH, Jeon YJ. Age-Related Characteristics of Resting-State Electroencephalographic Signals and the Corresponding Analytic Approaches: A Review. Bioengineering (Basel) 2024; 11:418. [PMID: 38790286 PMCID: PMC11118246 DOI: 10.3390/bioengineering11050418] [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: 03/15/2024] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/26/2024] Open
Abstract
The study of the effects of aging on neural activity in the human brain has attracted considerable attention in neurophysiological, neuropsychiatric, and neurocognitive research, as it is directly linked to an understanding of the neural mechanisms underlying the disruption of the brain structures and functions that lead to age-related pathological disorders. Electroencephalographic (EEG) signals recorded during resting-state conditions have been widely used because of the significant advantage of non-invasive signal acquisition with higher temporal resolution. These advantages include the capability of a variety of linear and nonlinear signal analyses and state-of-the-art machine-learning and deep-learning techniques. Advances in artificial intelligence (AI) can not only reveal the neural mechanisms underlying aging but also enable the assessment of brain age reliably by means of the age-related characteristics of EEG signals. This paper reviews the literature on the age-related features, available analytic methods, large-scale resting-state EEG databases, interpretations of the resulting findings, and recent advances in age-related AI models.
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Affiliation(s)
- Jae-Hwan Kang
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Jang-Han Bae
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Young-Ju Jeon
- Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon 34054, Republic of Korea; (J.-H.K.); (J.-H.B.)
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
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4
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Soplata AE, Adam E, Brown EN, Purdon PL, McCarthy MM, Kopell N. Rapid thalamocortical network switching mediated by cortical synchronization underlies propofol-induced EEG signatures: a biophysical model. J Neurophysiol 2023; 130:86-103. [PMID: 37314079 PMCID: PMC10312318 DOI: 10.1152/jn.00068.2022] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 06/08/2023] [Accepted: 06/08/2023] [Indexed: 06/15/2023] Open
Abstract
Propofol-mediated unconsciousness elicits strong alpha/low-beta and slow oscillations in the electroencephalogram (EEG) of patients. As anesthetic dose increases, the EEG signal changes in ways that give clues to the level of unconsciousness; the network mechanisms of these changes are only partially understood. Here, we construct a biophysical thalamocortical network involving brain stem influences that reproduces transitions in dynamics seen in the EEG involving the evolution of the power and frequency of alpha/low-beta and slow rhythm, as well as their interactions. Our model suggests that propofol engages thalamic spindle and cortical sleep mechanisms to elicit persistent alpha/low-beta and slow rhythms, respectively. The thalamocortical network fluctuates between two mutually exclusive states on the timescale of seconds. One state is characterized by continuous alpha/low-beta-frequency spiking in thalamus (C-state), whereas in the other, thalamic alpha spiking is interrupted by periods of co-occurring thalamic and cortical silence (I-state). In the I-state, alpha colocalizes to the peak of the slow oscillation; in the C-state, there is a variable relationship between an alpha/beta rhythm and the slow oscillation. The C-state predominates near loss of consciousness; with increasing dose, the proportion of time spent in the I-state increases, recapitulating EEG phenomenology. Cortical synchrony drives the switch to the I-state by changing the nature of the thalamocortical feedback. Brain stem influence on the strength of thalamocortical feedback mediates the amount of cortical synchrony. Our model implicates loss of low-beta, cortical synchrony, and coordinated thalamocortical silent periods as contributing to the unconscious state.NEW & NOTEWORTHY GABAergic anesthetics induce alpha/low-beta and slow oscillations in the EEG, which interact in dose-dependent ways. We constructed a thalamocortical model to investigate how these interdependent oscillations change with propofol dose. We find two dynamic states of thalamocortical coordination, which change on the timescale of seconds and dose-dependently mirror known changes in EEG. Thalamocortical feedback determines the oscillatory coupling and power seen in each state, and this is primarily driven by cortical synchrony and brain stem neuromodulation.
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Affiliation(s)
- Austin E Soplata
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
| | - Elie Adam
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
| | - Emery N Brown
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
| | - Patrick L Purdon
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States
| | - Michelle M McCarthy
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
| | - Nancy Kopell
- Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, United States
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Michael E, Covarrubias LS, Leong V, Kourtzi Z. Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions. Cereb Cortex 2023; 33:5382-5394. [PMID: 36352510 PMCID: PMC10152088 DOI: 10.1093/cercor/bhac426] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 09/24/2022] [Accepted: 09/26/2022] [Indexed: 11/11/2022] Open
Abstract
Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.
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Affiliation(s)
- Elizabeth Michael
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
| | | | - Victoria Leong
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
- Psychology, School of Social Sciences, Nanyang Technological University (NTU), Singapore 6398818, Singapore
- Lee Kong Chian School of Medicine, NTU, Singapore 308232, Singapore
| | - Zoe Kourtzi
- Department of Psychology, University of Cambridge, Downing St, Cambridge CB2 3EB, United Kingdom
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Wu T, Cai Y, Zhang R, Wang Z, Tao L, Xiao ZC. Multi-band oscillations emerge from a simple spiking network. CHAOS (WOODBURY, N.Y.) 2023; 33:043121. [PMID: 37097932 DOI: 10.1063/5.0106884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 03/14/2023] [Indexed: 06/19/2023]
Abstract
In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), and gamma (30-120 Hz) oscillations, among others. These rhythms are believed to underlie information processing and cognitive functions and have been subjected to intense experimental and theoretical scrutiny. Computational modeling has provided a framework for the emergence of network-level oscillatory behavior from the interaction of spiking neurons. However, due to the strong nonlinear interactions between highly recurrent spiking populations, the interplay between cortical rhythms in multiple frequency bands has rarely been theoretically investigated. Many studies invoke multiple physiological timescales (e.g., various ion channels or multiple types of inhibitory neurons) or oscillatory inputs to produce rhythms in multi-bands. Here, we demonstrate the emergence of multi-band oscillations in a simple network consisting of one excitatory and one inhibitory neuronal population driven by constant input. First, we construct a data-driven, Poincaré section theory for robust numerical observations of single-frequency oscillations bifurcating into multiple bands. Then, we develop model reductions of the stochastic, nonlinear, high-dimensional neuronal network to capture the appearance of multi-band dynamics and the underlying bifurcations theoretically. Furthermore, when viewed within the reduced state space, our analysis reveals conserved geometrical features of the bifurcations on low-dimensional dynamical manifolds. These results suggest a simple geometric mechanism behind the emergence of multi-band oscillations without appealing to oscillatory inputs or multiple synaptic or neuronal timescales. Thus, our work points to unexplored regimes of stochastic competition between excitation and inhibition behind the generation of dynamic, patterned neuronal activities.
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Affiliation(s)
- Tianyi Wu
- School of Mathematical Sciences, Peking University, Beijing 100871, China
- Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, School of Life Sciences, Peking University, Beijing 100871, China
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10003, USA
| | - Yuhang Cai
- Department of Mathematics, University of California, Berkeley, Berkeley, California 94720, USA
| | - Ruilin Zhang
- Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, School of Life Sciences, Peking University, Beijing 100871, China
- Yuanpei College, Peking University, Beijing 100871, China
| | - Zhongyi Wang
- School of Mathematical Sciences, Peking University, Beijing 100871, China
- Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, School of Life Sciences, Peking University, Beijing 100871, China
| | - Louis Tao
- Center for Bioinformatics, National Laboratory of Protein Engineering and Plant Genetic Engineering, School of Life Sciences, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Peking University, Beijing 100871, China
| | - Zhuo-Cheng Xiao
- Courant Institute of Mathematical Sciences, New York University, New York, New York 10003, USA
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7
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Riahi N, D’Arcy R, Menon C. A Method for Estimating Longitudinal Change in Motor Skill from Individualized Functional-Connectivity Measures. SENSORS (BASEL, SWITZERLAND) 2022; 22:9857. [PMID: 36560228 PMCID: PMC9781498 DOI: 10.3390/s22249857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 12/04/2022] [Accepted: 12/09/2022] [Indexed: 06/17/2023]
Abstract
Pragmatic, objective, and accurate motor assessment tools could facilitate more frequent appraisal of longitudinal change in motor function and subsequent development of personalized therapeutic strategies. Brain functional connectivity (FC) has shown promise as an objective neurophysiological measure for this purpose. The involvement of different brain networks, along with differences across subjects due to age or existing capabilities, motivates an individualized approach towards the evaluation of FC. We advocate the use of EEG-based resting-state FC (rsFC) measures to address the pragmatic requirements. Pertaining to appraisal of accuracy, we suggest using the acquisition of motor skill by healthy individuals that could be quantified at small incremental change. Computer-based tracing tasks are a good candidate in this regard when using spatial error in tracing as an objective measure of skill. This work investigates the application of an individualized method that utilizes Partial Least Squares analysis to estimate the longitudinal change in tracing error from changes in rsFC. Longitudinal data from participants yielded an average accuracy of 98% (standard deviation of 1.2%) in estimating tracing error. The results show potential for an accurate individualized motor assessment tool that reduces the dependence on the expertise and availability of trained examiners, thereby facilitating more frequent appraisal of function and development of personalized training programs.
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Affiliation(s)
- Nader Riahi
- Schools of Engineering Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
| | - Ryan D’Arcy
- Schools of Engineering Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
- DM Centre for Brain Health, Department of Radiology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
- HealthTech Connex, Surrey, BC V3V 0E8, Canada
| | - Carlo Menon
- Schools of Engineering Science, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
- Biomedical and Mobile Health Technology Laboratory, Department of Health Sciences and Technology, ETH Zurich, 8008 Zurich, Switzerland
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8
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Ippolito G, Bertaccini R, Tarasi L, Di Gregorio F, Trajkovic J, Battaglia S, Romei V. The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research. Biomedicines 2022; 10:biomedicines10123189. [PMID: 36551945 PMCID: PMC9775381 DOI: 10.3390/biomedicines10123189] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 12/03/2022] [Accepted: 12/05/2022] [Indexed: 12/14/2022] Open
Abstract
Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.
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Affiliation(s)
- Giuseppe Ippolito
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Riccardo Bertaccini
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Luca Tarasi
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Francesco Di Gregorio
- UO Medicina Riabilitativa e Neuroriabilitazione, Azienda Unità Sanitaria Locale, 40133 Bologna, Italy
| | - Jelena Trajkovic
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
| | - Simone Battaglia
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Dipartimento di Psicologia, Università di Torino, 10124 Torino, Italy
| | - Vincenzo Romei
- Centro Studi e Ricerche in Neuroscienze Cognitive, Dipartimento di Psicologia, Alma Mater Studiorum—Università di Bologna, 47521 Cesena, Italy
- Correspondence:
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Biophysical mechanism underlying compensatory preservation of neural synchrony over the adult lifespan. Commun Biol 2022; 5:567. [PMID: 35681107 PMCID: PMC9184644 DOI: 10.1038/s42003-022-03489-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 05/12/2022] [Indexed: 11/17/2022] Open
Abstract
We propose that the preservation of functional integration, estimated from measures of neural synchrony, is a key objective of neurocompensatory mechanisms associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at the peak alpha frequency in Magnetoencephalography recordings remains invariant over the lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delays associated with age-related degeneration of white matter tracts, albeit at slower network frequencies. By deriving analytical solutions for simplified connection topologies, we further establish the theoretical principles underlying compensatory network re-organization. Our findings suggest that frequency slowing with age- frequently observed in the alpha band in diverse populations- may be viewed as an epiphenomenon of the underlying compensatory mechanism. Analysis of MEG data from healthy participants and whole-brain network modeling suggests that the brain compensates for age-related disruptions in connectivity by slowing down the frequency of neural synchronization.
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Kostyalik D, Kelemen K, Lendvai B, Hernádi I, Román V, Lévay G. Response-related sensorimotor rhythms under scopolamine and MK-801 exposures in the touchscreen visual discrimination test in rats. Sci Rep 2022; 12:8168. [PMID: 35581280 PMCID: PMC9114334 DOI: 10.1038/s41598-022-12146-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 04/21/2022] [Indexed: 11/10/2022] Open
Abstract
The human mu rhythm has been suggested to represent an important function in information processing. Rodent homologue rhythms have been assumed though no study has investigated them from the cognitive aspect yet. As voluntary goal-directed movements induce the desynchronization of mu rhythm, we aimed at exploring whether the response-related brain activity during the touchscreen visual discrimination (VD) task is suitable to detect sensorimotor rhythms and their change under cognitive impairment. Different doses of scopolamine or MK-801 were injected subcutaneously to rats, and epidural electroencephalogram (EEG) was recorded during task performance. Arciform ~ 10 Hz oscillations appeared during visual processing, then two characteristic alpha/beta desynchronization-resynchronization patterns emerged mainly above the sensorimotor areas, serving presumably different motor functions. Beyond causing cognitive impairment, both drugs supressed the touch-related upper alpha (10–15 Hz) reactivity for desynchronization. Reaction time predominantly correlated positively with movement-related alpha and beta power both in normal and impaired conditions. These results support the existence of a mu homologue rodent rhythm whose upper alpha component appeared to be modulated by cholinergic and glutamatergic mechanisms and its power change might indicate a potential EEG correlate of processing speed. The VD task can be utilized for the investigation of sensorimotor rhythms in rats.
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Affiliation(s)
- Diána Kostyalik
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary
| | - Kristóf Kelemen
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary
| | - Balázs Lendvai
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary
| | - István Hernádi
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary.,Department of Experimental Zoology and Neurobiology, Faculty of Sciences, University of Pécs, Pécs, 7622, Hungary.,Institute of Physiology, Medical School, University of Pécs, Pécs, 7622, Hungary.,Grastyán Translational Research Center, University of Pécs, Pécs, 7622, Hungary.,Szentágothai Research Center, University of Pécs, Pécs, 7622, Hungary
| | - Viktor Román
- Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Budapest, 1103, Hungary
| | - György Lévay
- Cognitive Pharmacology Laboratory, Department of Pharmacology and Drug Safety, Gedeon Richter Plc., Gyömrői út 19-21, Budapest, 1103, Hungary. .,Department of Morphology and Physiology, Faculty of Health Sciences, Semmelweis University, Budapest, 1085, Hungary.
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Sasi S, Sen Bhattacharya B. In silico Effects of Synaptic Connections in the Visual Thalamocortical Pathway. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 4:856412. [PMID: 35450154 PMCID: PMC9016146 DOI: 10.3389/fmedt.2022.856412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/08/2022] [Indexed: 12/23/2022] Open
Abstract
We have studied brain connectivity using a biologically inspired in silico model of the visual pathway consisting of the lateral geniculate nucleus (LGN) of the thalamus, and layers 4 and 6 of the primary visual cortex. The connectivity parameters in the model are informed by the existing anatomical parameters from mammals and rodents. In the base state, the LGN and layer 6 populations in the model oscillate with dominant alpha frequency, while the layer 4 oscillates in the theta band. By changing intra-cortical hyperparameters, specifically inhibition from layer 6 to layer 4, we demonstrate a transition to alpha mode for all the populations. Furthermore, by increasing the feedforward connectivities in the thalamo-cortico-thalamic loop, we could transition into the beta band for all the populations. On looking closely, we observed that the origin of this beta band is in the layer 6 (infragranular layers); lesioning the thalamic feedback from layer 6 removed the beta from the LGN and the layer 4. This agrees with existing physiological studies where it is shown that beta rhythm is generated in the infragranular layers. Lastly, we present a case study to demonstrate a neurological condition in the model. By changing connectivities in the network, we could simulate the condition of significant (P < 0.001) decrease in beta band power and a simultaneous increase in the theta band power, similar to that observed in Schizophrenia patients. Overall, we have shown that the connectivity changes in a simple visual thalamocortical in silico model can simulate state changes in the brain corresponding to both health and disease conditions.
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12
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Ross B, Dobri S, Jamali S, Bartel L. Entrainment of somatosensory beta and gamma oscillations accompany improvement in tactile acuity after periodic and aperiodic repetitive sensory stimulation. Int J Psychophysiol 2022; 177:11-26. [DOI: 10.1016/j.ijpsycho.2022.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 03/18/2022] [Accepted: 04/08/2022] [Indexed: 11/27/2022]
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Johnson JT, de Mari D, Doherty H, Hammond FL, Wheaton LA. Alpha-band activity in parietofrontal cortex predicts future availability of vibrotactile feedback in prosthesis use. Exp Brain Res 2022; 240:1387-1398. [PMID: 35257195 DOI: 10.1007/s00221-022-06340-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 02/21/2022] [Indexed: 01/01/2023]
Abstract
Prosthesis disuse and abandonment is an ongoing issue in upper-limb amputation. In addition to lost structural and motor function, amputation also results in decreased task-specific sensory information. One proposed remedy is augmenting somatosensory information using vibrotactile feedback to provide tactile feedback of grasping objects. While the role of frontal and parietal areas in motor tasks is well established, the neural and kinematic effects of this augmented vibrotactile feedback remain in question. In this study, we sought to understand the neurobehavioral effects of providing augmented feedback during a reach-grasp-transport task. Ten persons with sound limbs performed a motor task while wearing a prosthesis simulator with and without vibrotactile feedback. We hypothesized that providing vibrotactile feedback during prosthesis use would increase activity in frontal and parietal areas and improve grasp-related behavior. Results show that anticipation of upcoming vibrotactile feedback may be encoded in motor and parietal areas during the reach-to-grasp phase of the task. While grasp aperture is unaffected by vibrotactile feedback, the availability of vibrotactile feedback does lead to a reduction in velocity during object transport. These results help shed light on how engineered feedback is utilized by prostheses users and provide methodologies for further assessment in advanced prosthetics research.
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Affiliation(s)
- John T Johnson
- Georgia Institute of Technology, 575 14 TH Street Northwest, Atlanta, GA, 30318, USA
| | - Daniele de Mari
- Georgia Institute of Technology, 575 14 TH Street Northwest, Atlanta, GA, 30318, USA
| | - Harper Doherty
- Georgia Institute of Technology, 575 14 TH Street Northwest, Atlanta, GA, 30318, USA
| | - Frank L Hammond
- Georgia Institute of Technology, 575 14 TH Street Northwest, Atlanta, GA, 30318, USA
| | - Lewis A Wheaton
- Georgia Institute of Technology, 575 14 TH Street Northwest, Atlanta, GA, 30318, USA.
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14
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Pino O, Romano G. Engagement and Arousal effects in predicting the increase of cognitive functioning following a neuromodulation program. ACTA BIO-MEDICA : ATENEI PARMENSIS 2022; 93:e2022248. [PMID: 35775751 PMCID: PMC9335441 DOI: 10.23750/abm.v93i3.13145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND AND AIM Research in the field of Brain-Computer Interfaces (BCIs) has increased exponentially over the past few years, demonstrating their effectiveness and application in several areas. The main purpose of the present paper was to explore the relevance of user engagement during interaction with a BCI prototype (Neuro-Upper, NU), which aimed at brainwave synchronization through audio-visual entrainment, in the improvement of cognitive performance. METHODS This paper presents findings on data collected from a sample of 18 subjects with clinical disorders who completed about 55 consecutive sessions of 30 min of audio-visual stimulation. The relationship between engagement and improvement of cognitive function (measured through the Intelligence Quotient - IQ) during NU neuromodulation was evaluated through the Index of Cognitive Engagement (ICE) measured by the Pope ratio (Beta / (Alpha + Theta), and Arousal [(High Beta + Low Beta) / (High Alpha + Low Alpha)]. RESULTS A significant correlation between engagement and IQ improvement, but no correlation between arousal and IQ improvement emerged, as expected. CONCLUSIONS Future research aiming at clarifying the role of arousal in psychological disorders and related symptoms will be essential.
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Affiliation(s)
- Olimpia Pino
- University of Parma, Department of Medicine & Surgery, Neuroscience Unit.
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15
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Preferred music listening is associated with perceptual learning enhancement at the expense of self-focused attention. Psychon Bull Rev 2022; 29:2108-2121. [PMID: 35668293 PMCID: PMC9722857 DOI: 10.3758/s13423-022-02127-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2022] [Indexed: 12/14/2022]
Abstract
Can preferred music listening improve following attentional and learning performances? Here we suggest that this may be the case. In Experiment 1, following preferred and non-preferred musical-piece listening, we recorded electrophysiological responses to an auditory roving-paradigm. We computed the mismatch negativity (MMN - the difference between responses to novel and repeated stimulation), as an index of perceptual learning, and we measured the correlation between trial-by-trial EEG responses and the fluctuations in Bayesian Surprise, as a quantification of the neural attunement with stimulus informational value. Furthermore, during music listening, we recorded oscillatory cortical activity. MMN and trial-by-trial correlation with Bayesian surprise were significantly larger after subjectively preferred versus non-preferred music, indicating the enhancement of perceptual learning. The analysis on oscillatory activity during music listening showed a selective alpha power increased in response to preferred music, an effect often related to cognitive enhancements. In Experiment 2, we explored whether this learning improvement was realized at the expense of self-focused attention. Therefore, after preferred versus non-preferred music listening, we collected Heart-Beat Detection (HBD) accuracy, as a measure of the attentional focus toward the self. HBD was significantly lowered following preferred music listening. Overall, our results suggest the presence of a specific neural mechanism that, in response to aesthetically pleasing stimuli, and through the modulation of alpha oscillatory activity, redirects neural resources away from the self and toward the environment. This attentional up-weighting of external stimuli might be fruitfully exploited in a wide area of human learning activities, including education, neurorehabilitation and therapy.
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Abstract
In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model's fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.
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17
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Janssens SEW, Sack AT, Ten Oever S, de Graaf TA. Calibrating rhythmic stimulation parameters to individual EEG markers: the consistency of individual alpha frequency in practical lab settings. Eur J Neurosci 2021; 55:3418-3437. [PMID: 34363269 PMCID: PMC9541964 DOI: 10.1111/ejn.15418] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/18/2021] [Accepted: 08/02/2021] [Indexed: 11/27/2022]
Abstract
Rhythmic stimulation can be applied to modulate neuronal oscillations. Such 'entrainment' is optimized when stimulation frequency is individually-calibrated based on magneto/encephalography markers. It remains unknown how consistent such individual markers are across days/sessions, within a session, or across cognitive states, hemispheres, and estimation methods, especially in a realistic, practical, lab setting. We here estimated individual alpha frequency (IAF) repeatedly from short EEG measurements at rest or during an attention task (cognitive state), using single parieto-occipital electrodes in 24 participants on four days (between-sessions), with multiple measurements over an hour on one day (within-session). First, we introduce an algorithm to automatically reject power spectra without a sufficiently clear peak to ensure unbiased IAF estimations. Then we estimated IAF via the traditional 'maximum' method and a 'Gaussian fit' method. IAF was reliable within- and between-sessions for both cognitive states and hemispheres, though task-IAF estimates tended to be more variable. Overall, the 'Gaussian fit' method was more reliable than the 'maximum' method. Furthermore, we evaluated how far from an approximated 'true' task-related IAF the selected 'stimulation frequency' was, when calibrating this frequency based on a short rest-EEG, a short task-EEG, or simply selecting 10Hertz for all participants. For the 'maximum' method, rest-EEG calibration was best, followed by task-EEG, and then 10 Hertz. For the 'Gaussian fit' method, rest-EEG and task-EEG-based calibration were similarly accurate, and better than 10 Hertz. These results lead to concrete recommendations about valid, and automated, estimation of individual oscillation markers in experimental and clinical settings.
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Affiliation(s)
- Shanice E W Janssens
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht, the Netherlands
| | - Alexander T Sack
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht, the Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Brain+Nerve Centre , Maastricht University Medical Centre+ (MUMC+), Maastricht, the Netherlands.,Center for Integrative Neuroscience (CIN), Maastricht University, Maastricht, the Netherlands
| | - Sanne Ten Oever
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.,Language and Computation in Neural Systems Group, Max Planck Institute for Psycholinguistics, Nijmegen, the Netherlands.,Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, the Netherlands
| | - Tom A de Graaf
- Section Brain Stimulation and Cognition, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands.,Maastricht Brain Imaging Centre (MBIC), Maastricht, the Netherlands.,Center for Integrative Neuroscience (CIN), Maastricht University, Maastricht, the Netherlands
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18
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Pino O. A randomized controlled trial (RCT) to explore the effect of audio-visual entrainment among psychological disorders. ACTA BIO-MEDICA : ATENEI PARMENSIS 2021; 92:e2021408. [PMID: 35075067 PMCID: PMC8823583 DOI: 10.23750/abm.v92i6.12089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 07/31/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND AND AIM Although many mental disorders have relevant proud in neurobiological dysfunctions, most intervention approaches neglect neurophysiological features or use pharmacological intervention alone. Non-invasive Brain-Computer Interfaces (BCIs), providing natural ways of modulating mood states, can be promoted as an alternative intervention to cope with neurobiological dysfunction. METHODS A BCI prototype was proposed to feedback a person's affective state such that a closed-loop interaction between the participant's brain responses and the musical stimuli is established. It feedbacks in real-time flickering lights matching with the individual's brain rhythms undergo to auditory stimuli. A RCT was carried out on 15 individuals of both genders (mean age = 49.27 years) with anxiety and depressive spectrum disorders randomly assigned to 2 groups (experimental vs. active control). RESULTS Outcome measures revealed either a significant decrease in Hamilton Rating Scale for Depression (HAM-D) scores and gains in cognitive functions only for participants who undergone to the experimental treatment. Variability in HAM-D scores seems explained by the changes in beta 1, beta 2 and delta bands. Conversely, the rise in cognitive function scores appear associated with theta variations. CONCLUSIONS Future work needs to validate the relationship proposed here between music and brain responses. Findings of the present study provided support to a range of research examining BCI brain modulation and contributes to the understanding of this technique as instruments to alternative therapies We believe that Neuro-Upper can be used as an effective new tool for investigating affective responses, and emotion regulation (www.actabiomedica.it).
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Affiliation(s)
- Olimpia Pino
- University of Parma, Department of Medicine & Surgery, Neuroscience Unit.
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19
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Sarasso P, Neppi-Modona M, Sacco K, Ronga I. "Stopping for knowledge": The sense of beauty in the perception-action cycle. Neurosci Biobehav Rev 2020; 118:723-738. [PMID: 32926914 DOI: 10.1016/j.neubiorev.2020.09.004] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/23/2020] [Accepted: 09/01/2020] [Indexed: 01/07/2023]
Abstract
According to a millennial-old philosophical debate, aesthetic emotions have been connected to knowledge acquisition. Recent scientific evidence, collected across different disciplinary domains, confirms this link, but also reveals that motor inhibition plays a crucial role in the process. In this review, we discuss multidisciplinary results and propose an original account of aesthetic appreciation (the stopping for knowledge hypothesis) framed within the predictive coding theory. We discuss evidence showing that aesthetic emotions emerge in correspondence with an inhibition of motor behavior (i.e., minimizing action), promoting a simultaneous perceptual processing enhancement, at the level of sensory cortices (i.e., optimizing learning). Accordingly, we suggest that aesthetic appreciation may represent a hedonic feedback over learning progresses, motivating the individual to inhibit motor routines to seek further knowledge acquisition. Furthermore, the neuroimaging and neuropsychological studies we review reveal the presence of a strong association between aesthetic appreciation and the activation of the dopaminergic reward-related circuits. Finally, we propose a number of possible applications of the stopping for knowledge hypothesis in the clinical and education domains.
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Affiliation(s)
- P Sarasso
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Italy
| | - M Neppi-Modona
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Italy
| | - K Sacco
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Italy
| | - I Ronga
- BIP (BraIn Plasticity and Behaviour Changes) Research Group, Department of Psychology, University of Turin, Italy.
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20
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Cai L, Wei X, Liu J, Zhu L, Wang J, Deng B, Yu H, Wang R. Functional Integration and Segregation in Multiplex Brain Networks for Alzheimer's Disease. Front Neurosci 2020; 14:51. [PMID: 32132892 PMCID: PMC7040198 DOI: 10.3389/fnins.2020.00051] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2019] [Accepted: 01/14/2020] [Indexed: 01/14/2023] Open
Abstract
Growing evidence links impairment of brain functions in Alzheimer's disease (AD) with disruptions of brain functional connectivity. However, whether the AD brain shows similar changes from a dynamic or cross-frequency view remains poorly explored. This paper provides an effective framework to investigate the properties of multiplex brain networks in AD considering inter-frequency and temporal dynamics. Using resting-state EEG signals, two types of multiplex networks were reconstructed separately considering the network interactions between different frequency bands or time points. We further applied multiplex network features to characterize functional integration and segregation of the cross-frequency or time-varying networks. Finally, machine learning methods were employed to evaluate the performance of multiplex-network-based indexes for detection of AD. Results revealed that the brain networks of AD patients are disrupted with reduced segregation particularly in the left occipital area for both cross-frequency and time-varying networks. However, the alteration of integration differs among brain regions and may show an increasing trend in the frontal area of AD brain. By combining the features of integration and segregation in time-varying networks, the best classification performance was achieved with an accuracy of 92.5%. These findings suggest that our multiplex framework can be applied to explore functional integration and segregation of brain networks and characterize the abnormalities of brain function. This may shed new light on the brain network analysis and extend our understanding of brain function in patients with neurological diseases.
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Affiliation(s)
- Lihui Cai
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Xile Wei
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jing Liu
- Department of Neurology, Tangshan Gongren Hospital, Tangshan, Hebei, China
| | - Lin Zhu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Bin Deng
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Haitao Yu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Ruofan Wang
- School of Information Technology Engineering, Tianjin University of Technology and Education, Tianjin, China
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21
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Deiber MP, Hasler R, Colin J, Dayer A, Aubry JM, Baggio S, Perroud N, Ros T. Linking alpha oscillations, attention and inhibitory control in adult ADHD with EEG neurofeedback. NEUROIMAGE-CLINICAL 2019; 25:102145. [PMID: 31911342 PMCID: PMC6948256 DOI: 10.1016/j.nicl.2019.102145] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 12/17/2019] [Accepted: 12/21/2019] [Indexed: 01/01/2023]
Abstract
Resting alpha power is reduced in adult ADHD suggesting cortical hyper-activation. Adult ADHD patients successfully reduce alpha power during neurofeedback. A post-neurofeedback rebound normalizes alpha power in adult ADHD. Alpha power rebound correlates with improvement of inhibitory control in adult ADHD.
Abnormal patterns of electrical oscillatory activity have been repeatedly described in adult ADHD. In particular, the alpha rhythm (8–12 Hz), known to be modulated during attention, has previously been considered as candidate biomarker for ADHD. In the present study, we asked adult ADHD patients to self-regulate their own alpha rhythm using neurofeedback (NFB), in order to examine the modulation of alpha oscillations on attentional performance and brain plasticity. Twenty-five adult ADHD patients and 22 healthy controls underwent a 64-channel EEG-recording at resting-state and during a Go/NoGo task, before and after a 30 min-NFB session designed to reduce (desynchronize) the power of the alpha rhythm. Alpha power was compared across conditions and groups, and the effects of NFB were statistically assessed by comparing behavioral and EEG measures pre-to-post NFB. Firstly, we found that relative alpha power was attenuated in our ADHD cohort compared to control subjects at baseline and across experimental conditions, suggesting a signature of cortical hyper-activation. Both groups demonstrated a significant and targeted reduction of alpha power during NFB. Interestingly, we observed a post-NFB increase in resting-state alpha (i.e. rebound) in the ADHD group, which restored alpha power towards levels of the normal population. Importantly, the degree of post-NFB alpha normalization during the Go/NoGo task correlated with individual improvements in motor inhibition (i.e. reduced commission errors) only in the ADHD group. Overall, our findings offer novel supporting evidence implicating alpha oscillations in inhibitory control, as well as their potential role in the homeostatic regulation of cortical excitatory/inhibitory balance.
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Affiliation(s)
- Marie-Pierre Deiber
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Department of Psychiatry, University of Geneva, Geneva, Switzerland.
| | - Roland Hasler
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland
| | - Julien Colin
- Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Alexandre Dayer
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Department of Psychiatry, University of Geneva, Geneva, Switzerland; Department of Basic Neurosciences, Geneva Medical Center, University of Geneva, Geneva, Switzerland
| | - Jean-Michel Aubry
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Stéphanie Baggio
- Division of Prison Health, University Hospitals of Geneva, Geneva, Switzerland
| | - Nader Perroud
- Division of Psychiatric Specialties, Department of Psychiatry, University Hospitals of Geneva, Geneva, Switzerland; Department of Psychiatry, University of Geneva, Geneva, Switzerland; Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Tomas Ros
- Department of Psychiatry, University of Geneva, Geneva, Switzerland
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22
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Sarasso P, Ronga I, Kobau P, Bosso T, Artusio I, Ricci R, Neppi-Modona M. Beauty in mind: Aesthetic appreciation correlates with perceptual facilitation and attentional amplification. Neuropsychologia 2019; 136:107282. [PMID: 31770549 DOI: 10.1016/j.neuropsychologia.2019.107282] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 11/21/2019] [Accepted: 11/22/2019] [Indexed: 12/11/2022]
Abstract
Neuroaesthetic research suggests that aesthetic appreciation results from the interaction between the object perceptual features and the perceiver's sensory processing dynamics. In the present study, we investigated the relationship between aesthetic appreciation and attentional modulation at a behavioural and psychophysiological level. In a first experiment, fifty-eight healthy participants performed a visual search task with abstract stimuli containing more or less natural spatial frequencies and subsequently were asked to give an aesthetic evaluation of the images. The results evidenced that response times were faster for more appreciated stimuli. In a second experiment, we recorded visual evoked potentials (VEPs) during exposure to the same stimuli. The results showed, only for more appreciated images, an enhancement in C1 and N1, P3 and N4 VEP components. Moreover, we found increased attention-related occipital alpha desynchronization for more appreciated images. We interpret these data as indicative of the existence of a correlation between aesthetic appreciation and perceptual processing enhancement, both at a behavioural and at a neurophysiological level.
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Affiliation(s)
- P Sarasso
- SAMBA (SpAtial Motor & Bodily Awareness) Research Group, Department of Psychology, University of Turin, Italy; Imaging and Cerebral Plasticity Research Group, Department of Psychology, University of Turin, Italy.
| | - I Ronga
- Imaging and Cerebral Plasticity Research Group, Department of Psychology, University of Turin, Italy.
| | - P Kobau
- Department of Philosophy and Education Sciences, University of Turin, Italy
| | - T Bosso
- SAMBA (SpAtial Motor & Bodily Awareness) Research Group, Department of Psychology, University of Turin, Italy
| | - I Artusio
- SAMBA (SpAtial Motor & Bodily Awareness) Research Group, Department of Psychology, University of Turin, Italy
| | - R Ricci
- SAMBA (SpAtial Motor & Bodily Awareness) Research Group, Department of Psychology, University of Turin, Italy
| | - M Neppi-Modona
- SAMBA (SpAtial Motor & Bodily Awareness) Research Group, Department of Psychology, University of Turin, Italy
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Manuel AL, Guggisberg AG, Thézé R, Turri F, Schnider A. Resting-state connectivity predicts visuo-motor skill learning. Neuroimage 2018; 176:446-453. [DOI: 10.1016/j.neuroimage.2018.05.003] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 04/30/2018] [Accepted: 05/01/2018] [Indexed: 02/06/2023] Open
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Kumar GV, Kumar N, Roy D, Banerjee A. Segregation and Integration of Cortical Information Processing Underlying Cross-Modal Perception. Multisens Res 2018; 31:481-500. [DOI: 10.1163/22134808-00002574] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 04/17/2017] [Indexed: 11/19/2022]
Abstract
Visual cues from the speaker’s face influence the perception of speech. An example of this influence is demonstrated by the McGurk-effect where illusory (cross-modal) sounds are perceived following presentation of incongruent audio–visual (AV) stimuli. Previous studies report the engagement of specific cortical modules that are spatially distributed during cross-modal perception. However, the limits of the underlying representational space and the cortical network mechanisms remain unclear. In this combined psychophysical and electroencephalography (EEG) study, the participants reported their perception while listening to a set of synchronous and asynchronous incongruent AV stimuli. We identified the neural representation of subjective cross-modal perception at different organizational levels — at specific locations in sensor space and at the level of the large-scale brain network estimated from between-sensor interactions. We identified an enhanced positivity in the event-related potential peak around 300 ms following stimulus onset associated with cross-modal perception. At the spectral level, cross-modal perception involved an overall decrease in power at the frontal and temporal regions at multiple frequency bands and at all AV lags, along with an increased power at the occipital scalp region for synchronous AV stimuli. At the level of large-scale neuronal networks, enhanced functional connectivity at the gamma band involving frontal regions serves as a marker of AV integration. Thus, we report in one single study that segregation of information processing at individual brain locations and integration of information over candidate brain networks underlie multisensory speech perception.
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Affiliation(s)
- G. Vinodh Kumar
- Cognitive Brain Lab, National Brain Research Centre, NH 8, Manesar, Gurgaon 122051, India
| | - Neeraj Kumar
- Cognitive Brain Lab, National Brain Research Centre, NH 8, Manesar, Gurgaon 122051, India
| | - Dipanjan Roy
- Centre of Behavioural and Cognitive Sciences, University of Allahabad, Allahabad 211002, India
| | - Arpan Banerjee
- Cognitive Brain Lab, National Brain Research Centre, NH 8, Manesar, Gurgaon 122051, India
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Jankowski MM, Islam MN, O'Mara SM. Dynamics of spontaneous local field potentials in the anterior claustrum of freely moving rats. Brain Res 2017; 1677:101-117. [DOI: 10.1016/j.brainres.2017.09.021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2017] [Revised: 09/18/2017] [Accepted: 09/19/2017] [Indexed: 12/19/2022]
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26
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Muller-Gass A, Duncan M, Campbell K. Brain states predict individual differences in perceptual learning. PERSONALITY AND INDIVIDUAL DIFFERENCES 2017. [DOI: 10.1016/j.paid.2017.03.066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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27
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Barzegaran E, Vildavski VY, Knyazeva MG. Fine Structure of Posterior Alpha Rhythm in Human EEG: Frequency Components, Their Cortical Sources, and Temporal Behavior. Sci Rep 2017; 7:8249. [PMID: 28811538 PMCID: PMC5557761 DOI: 10.1038/s41598-017-08421-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 07/10/2017] [Indexed: 12/23/2022] Open
Abstract
Heterogeneity of the posterior alpha rhythm (AR) is a widely assumed but rarely tested phenomenon. We decomposed the posterior AR in the cortical source space with a 3-way PARAFAC technique, taking into account the spatial, frequency, and temporal aspects of mid-density EEG. We found a multicomponent AR structure in 90% of a group of 29 healthy adults. The typical resting-state structure consisted of a high-frequency occipito-parietal component of the AR (ARC1) and a low-frequency occipito-temporal component (ARC2), characterized by individual dynamics in time. In a few cases, we found a 3-component structure, with two ARC1s and one ARC2. The AR structures were stable in their frequency and spatial features over weeks to months, thus representing individual EEG alpha phenotypes. Cortical topography, individual stability, and similarity to the primate AR organization link ARC1 to the dorsal visual stream and ARC2 to the ventral one. Understanding how many and what kind of posterior AR components contribute to the EEG is essential for clinical neuroscience as an objective basis for AR segmentation and for interpreting AR dynamics under various conditions, both normal and pathological, which can selectively affect individual components.
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Affiliation(s)
- Elham Barzegaran
- Laboratoire de recherche en neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Leenaards Memory Centre and Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | | | - Maria G Knyazeva
- Laboratoire de recherche en neuroimagerie (LREN), Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Leenaards Memory Centre and Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland.
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28
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Toosi T, K Tousi E, Esteky H. Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance. J Neurophysiol 2017; 118:771-777. [PMID: 28515289 DOI: 10.1152/jn.00969.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 05/02/2017] [Accepted: 05/12/2017] [Indexed: 11/22/2022] Open
Abstract
Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations.NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of events.
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Affiliation(s)
- Tahereh Toosi
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; and
| | - Ehsan K Tousi
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; and
| | - Hossein Esteky
- School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran; and.,Research Center for Brain and Cognitive Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Tsuchimoto S, Shibusawa S, Mizuguchi N, Kato K, Ebata H, Liu M, Hanakawa T, Ushiba J. Resting-State Fluctuations of EEG Sensorimotor Rhythm Reflect BOLD Activities in the Pericentral Areas: A Simultaneous EEG-fMRI Study. Front Hum Neurosci 2017; 11:356. [PMID: 28729830 PMCID: PMC5498521 DOI: 10.3389/fnhum.2017.00356] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2017] [Accepted: 06/21/2017] [Indexed: 01/27/2023] Open
Abstract
Blockade of the scalp electroencephalographic (EEG) sensorimotor rhythm (SMR) is a well-known phenomenon following attempted or executed motor functions. Such a frequency-specific power attenuation of the SMR occurs in the alpha and beta frequency bands and is spatially registered at primary somatosensory and motor cortices. Here, we hypothesized that resting-state fluctuations of the SMR in the alpha and beta frequency bands also covary with resting-state sensorimotor cortical activity, without involving task-related neural dynamics. The present study employed functional magnetic resonance imaging (fMRI) to investigate the neural regions whose activities were correlated with the simultaneously recorded SMR power fluctuations. The SMR power fluctuations were convolved with a canonical hemodynamic response function and correlated with blood-oxygen-level dependent (BOLD) signals obtained from the entire brain. Our findings show that the alpha and beta power components of the SMR correlate with activities of the pericentral area. Furthermore, brain regions with correlations between BOLD signals and the alpha-band SMR fluctuations were located posterior to those with correlations between BOLD signals and the beta-band SMR. These results are consistent with those of event-related studies of SMR modulation induced by sensory input or motor output. Our findings may help to understand the role of the sensorimotor cortex activity in contributing to the amplitude modulation of SMR during the resting state. This knowledge may be applied to the diagnosis of pathological conditions in the pericentral areas or the refinement of brain–computer interfaces using SMR in the future.
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Affiliation(s)
- Shohei Tsuchimoto
- School of Fundamental Science and Technology, Graduate School of Keio UniversityKanagawa, Japan
| | - Shuka Shibusawa
- School of Fundamental Science and Technology, Graduate School of Keio UniversityKanagawa, Japan
| | - Nobuaki Mizuguchi
- The Japan Society for the Promotion of ScienceTokyo, Japan.,Department of Biosciences and Informatics, Faculty of Science and Technology, Keio UniversityKanagawa, Japan
| | - Kenji Kato
- Department of Rehabilitation Medicine, Keio University School of MedicineTokyo, Japan
| | | | - Meigen Liu
- Department of Rehabilitation Medicine, Keio University School of MedicineTokyo, Japan
| | - Takashi Hanakawa
- Integrative Brain Imaging Center, National Center of Neurology and PsychiatryTokyo, Japan.,Japan Science and Technology Agency, Precursory Research for Embryonic Science and TechnologySaitama, Japan
| | - Junichi Ushiba
- Department of Biosciences and Informatics, Faculty of Science and Technology, Keio UniversityKanagawa, Japan.,Keio Institute of Pure and Applied SciencesKanagawa, Japan
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30
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Dagar S, Chowdhury SR, Bapi RS, Dutta A, Roy D. Near-Infrared Spectroscopy - Electroencephalography-Based Brain-State-Dependent Electrotherapy: A Computational Approach Based on Excitation-Inhibition Balance Hypothesis. Front Neurol 2016; 7:123. [PMID: 27551273 PMCID: PMC4976097 DOI: 10.3389/fneur.2016.00123] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 07/25/2016] [Indexed: 12/16/2022] Open
Abstract
Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The poststroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS) techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG) and functional-near-infrared spectroscopy (fNIRS) can be leveraged for Brain State Dependent Electrotherapy (BSDE). In this hypothesis and theory article, we propose a computational approach based on excitation–inhibition (E–I) balance hypothesis to objectively quantify the poststroke individual brain state using online fNIRS–EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local E–I (that is the ratio of Glutamate/GABA), which may be targeted with NIBS using a computational pipeline that includes individual “forward models” to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons, which can be captured with E–I-based brain models. Furthermore, E–I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing, which can then be implicated in changes in function. We first review the evidence that shows how this local imbalance between E–I leading to functional dysfunction can be restored in targeted sites with NIBS (motor cortex and somatosensory cortex) resulting in large-scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Second, we show evidence how BSDE based on E–I balance hypothesis may target a specific brain site or network as an adjuvant treatment. Hence, computational neural mass model-based integration of neurostimulation with online neuroimaging systems may provide less ambiguous, robust optimization of NIBS, and its application in neurological conditions and disorders across individual patients.
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Affiliation(s)
- Snigdha Dagar
- Cognitive Science Lab, International Institute of Information Technology , Hyderabad , India
| | - Shubhajit Roy Chowdhury
- School of Computing and Electrical Engineering, Indian Institute of Technology , Mandi , India
| | - Raju Surampudi Bapi
- Cognitive Science Lab, International Institute of Information Technology, Hyderabad, India; School of Computer and Information Sciences, University of Hyderabad, Hyderabad, India
| | - Anirban Dutta
- Leibniz-Institut für Arbeitsforschung an der TU Dortmund , Dortmund , Germany
| | - Dipanjan Roy
- Centre of Behavioral and Cognitive Sciences, University of Allahabad , Allahabad , India
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31
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Bays BC, Visscher KM, Le Dantec CC, Seitz AR. Alpha-band EEG activity in perceptual learning. J Vis 2015; 15:7. [PMID: 26370167 DOI: 10.1167/15.10.7] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Abstract
In studies of perceptual learning (PL), subjects are typically highly trained across many sessions to achieve perceptual benefits on the stimuli in those tasks. There is currently significant debate regarding what sources of brain plasticity underlie these PL-based learning improvements. Here we investigate the hypothesis that PL, among other mechanisms, leads to task automaticity, especially in the presence of the trained stimuli. To investigate this hypothesis, we trained participants for eight sessions to find an oriented target in a field of near-oriented distractors and examined alpha-band activity, which modulates with attention to visual stimuli, as a possible measure of automaticity. Alpha-band activity was acquired via electroencephalogram (EEG), before and after training, as participants performed the task with trained and untrained stimuli. Results show that participants underwent significant learning in this task (as assessed by threshold, accuracy, and reaction time improvements) and that alpha power increased during the pre-stimulus period and then underwent greater desynchronization at the time of stimulus presentation following training. However, these changes in alpha-band activity were not specific to the trained stimuli, with similar patterns of posttraining alpha power for trained and untrained stimuli. These data are consistent with the view that participants were more efficient at focusing resources at the time of stimulus presentation and are consistent with a greater automaticity of task performance. These findings have implications for PL, as transfer effects from trained to untrained stimuli may partially depend on differential effort of the individual at the time of stimulus processing.
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32
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Dutta A. Bidirectional interactions between neuronal and hemodynamic responses to transcranial direct current stimulation (tDCS): challenges for brain-state dependent tDCS. Front Syst Neurosci 2015; 9:107. [PMID: 26321925 PMCID: PMC4530593 DOI: 10.3389/fnsys.2015.00107] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Accepted: 07/13/2015] [Indexed: 12/04/2022] Open
Abstract
Transcranial direct current stimulation (tDCS) has been shown to modulate cortical neural activity. During neural activity, the electric currents from excitable membranes of brain tissue superimpose in the extracellular medium and generate a potential at scalp, which is referred as the electroencephalogram (EEG). Respective neural activity (energy demand) has been shown to be closely related, spatially and temporally, to cerebral blood flow (CBF) that supplies glucose (energy supply) via neurovascular coupling. The hemodynamic response can be captured by near-infrared spectroscopy (NIRS), which enables continuous monitoring of cerebral oxygenation and blood volume. This neurovascular coupling phenomenon led to the concept of neurovascular unit (NVU) that consists of the endothelium, glia, neurons, pericytes, and the basal lamina. Here, recent works suggest NVU as an integrated system working in concert using feedback mechanisms to enable proper brain homeostasis and function where the challenge remains in capturing these mostly nonlinear spatiotemporal interactions within NVU for brain-state dependent tDCS. In principal accordance, we propose EEG-NIRS-based whole-head monitoring of tDCS-induced neuronal and hemodynamic alterations during tDCS.
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Affiliation(s)
- Anirban Dutta
- INRIA (Sophia Antipolis) - CNRS: UMR5506 - Université Montpellier Montpellier, France ; Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), CNRS: UMR5506 - Université Montpellier Montpellier, France
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33
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Kovacevic N, Ritter P, Tays W, Moreno S, McIntosh AR. 'My Virtual Dream': Collective Neurofeedback in an Immersive Art Environment. PLoS One 2015; 10:e0130129. [PMID: 26154513 PMCID: PMC4496007 DOI: 10.1371/journal.pone.0130129] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Accepted: 05/17/2015] [Indexed: 01/15/2023] Open
Abstract
While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored. Motivated to overcome this limitation, we conducted a large-scale experiment with electroencephalography (EEG) based brain-computer interface (BCI) technology as part of an immersive multi-media science-art installation. Data from 523 participants were collected in a single night. The exploratory experiment was designed as a collective computer game where players manipulated mental states of relaxation and concentration with neurofeedback targeting modulation of relative spectral power in alpha and beta frequency ranges. Besides validating robust time-of-night effects, gender differences and distinct spectral power patterns for the two mental states, our results also show differences in neurofeedback learning outcome. The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min). Moreover, we found that participants' baseline brain activity predicted subsequent neurofeedback beta training, indicating state-dependent learning. Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions.
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Affiliation(s)
- Natasha Kovacevic
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
- * E-mail:
| | - Petra Ritter
- Max Planck Institute for Cognitive and Brain Science, Leipzig, Germany
- Department of Neurology, Charité –Universitätsmedizin Berlin, Berlin, Germany
| | - William Tays
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
| | - Sylvain Moreno
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Ontario, Canada
| | - Anthony Randal McIntosh
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Ontario, Canada
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34
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Ritter P, Jirsa VK, McIntosh AR, Breakspear M. Editorial: State-dependent brain computation. Front Comput Neurosci 2015; 9:77. [PMID: 26157384 PMCID: PMC4477138 DOI: 10.3389/fncom.2015.00077] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2015] [Accepted: 06/10/2015] [Indexed: 12/16/2022] Open
Affiliation(s)
- Petra Ritter
- Minerva Research Group Brain Modes, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Deparment of Neurology, Charité - University Medicine Berlin, Germany ; Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience Berlin, Germany ; Berlin School of Mind and Brain and Mind and Brain Institute, Humboldt University Berlin, Germany
| | - Viktor K Jirsa
- Institut de Neurosciences des Systèmes UMR INSERM 1106, Aix-Marseille Université Faculté de Médecine Marseille, France
| | - Anthony R McIntosh
- Rotman Research Institute of Baycrest Centre, University of Toronto Toronto, ON, Canada
| | - Michael Breakspear
- Systems Neuroscience Group, QIMR Berghofer Brisbane, QLD, Australia ; The Royal Brisbane and Woman's Hospital Brisbane, QLD, Australia
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35
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Ritter P, Born J, Brecht M, Dinse HR, Heinemann U, Pleger B, Schmitz D, Schreiber S, Villringer A, Kempter R. State-dependencies of learning across brain scales. Front Comput Neurosci 2015; 9:1. [PMID: 25767445 PMCID: PMC4341560 DOI: 10.3389/fncom.2015.00001] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 01/06/2015] [Indexed: 01/09/2023] Open
Abstract
Learning is a complex brain function operating on different time scales, from milliseconds to years, which induces enduring changes in brain dynamics. The brain also undergoes continuous “spontaneous” shifts in states, which, amongst others, are characterized by rhythmic activity of various frequencies. Besides the most obvious distinct modes of waking and sleep, wake-associated brain states comprise modulations of vigilance and attention. Recent findings show that certain brain states, particularly during sleep, are essential for learning and memory consolidation. Oscillatory activity plays a crucial role on several spatial scales, for example in plasticity at a synaptic level or in communication across brain areas. However, the underlying mechanisms and computational rules linking brain states and rhythms to learning, though relevant for our understanding of brain function and therapeutic approaches in brain disease, have not yet been elucidated. Here we review known mechanisms of how brain states mediate and modulate learning by their characteristic rhythmic signatures. To understand the critical interplay between brain states, brain rhythms, and learning processes, a wide range of experimental and theoretical work in animal models and human subjects from the single synapse to the large-scale cortical level needs to be integrated. By discussing results from experiments and theoretical approaches, we illuminate new avenues for utilizing neuronal learning mechanisms in developing tools and therapies, e.g., for stroke patients and to devise memory enhancement strategies for the elderly.
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Affiliation(s)
- Petra Ritter
- Minerva Research Group BrainModes, Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany ; Department of Neurology, Charité University Medicine Berlin Berlin, Germany ; Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt-Universität zu Berlin Berlin, Germany
| | - Jan Born
- Department of Medical Psychology and Behavioral Neurobiology & Center for Integrative Neuroscience (CIN), University of Tübingen Tübingen, Germany
| | - Michael Brecht
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany
| | - Hubert R Dinse
- Neural Plasticity Lab, Institute for Neuroinformatics, Ruhr-University Bochum Bochum, Germany ; Department of Neurology, BG University Hospital Bergmannsheil, Ruhr-University Bochum Bochum, Germany
| | - Uwe Heinemann
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; NeuroCure Cluster of Excellence Berlin, Germany
| | - Burkhard Pleger
- Clinic for Cognitive Neurology, University Hospital Leipzig Leipzig, Germany ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Dietmar Schmitz
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; NeuroCure Cluster of Excellence Berlin, Germany ; Neuroscience Research Center NWFZ, Charité University Medicine Berlin Berlin, Germany ; Max-Delbrück Center for Molecular Medicine, MDC Berlin, Germany ; Center for Neurodegenerative Diseases (DZNE) Berlin, Germany
| | - Susanne Schreiber
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Department of Biology, Institute for Theoretical Biology (ITB), Humboldt-Universität zu Berlin Berlin, Germany
| | - Arno Villringer
- Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt-Universität zu Berlin Berlin, Germany ; Clinic for Cognitive Neurology, University Hospital Leipzig Leipzig, Germany ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany
| | - Richard Kempter
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin Berlin, Germany ; Department of Biology, Institute for Theoretical Biology (ITB), Humboldt-Universität zu Berlin Berlin, Germany
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36
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Jindal U, Sood M, Chowdhury SR, Das A, Kondziella D, Dutta A. Corticospinal excitability changes to anodal tDCS elucidated with NIRS-EEG joint-imaging: An ischemic stroke study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2015; 2015:3399-402. [PMID: 26737022 DOI: 10.1109/embc.2015.7319122] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Transcranial direct current stimulation (tDCS) has been shown to modulate corticospinal excitability. We used near-infrared spectroscopy (NIRS)-electroencephalography (EEG) joint-imaging during and after anodal tDCS to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along with changes in the log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. In two separate studies, we investigated local post-tDCS alterations from baseline at the site of anodal tDCS using NIRS-EEG/tDCS joint-imaging as well as local post-tDCS alterations in motor evoked potentials (MEP)-measure of corticospinal excitability. In the first study, we found that post-tDCS changes in the mean rSO2 from baseline mostly correlated with the corresponding post-tDCS change in log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. Moreover, a decrease in log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz corresponded with an increase in the MEP-measure of corticospinal excitability--found in the second study. Therefore, we propose to combine NIRS-EEG/tDCS joint-imaging with corticospinal excitability investigation in a single study to confirm these finding. Furthermore, we postulate that the innovative technologies for portable NIRS-EEG neuroimaging may be leveraged to objectively quantify the progress (e.g., corticospinal excitability alterations) and dose tDCS intervention as an adjuvant treatment during neurorehabilitation.
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37
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Use of electroencephalography (EEG) to assess CNS changes produced by pesticides with different modes of action: Effects of permethrin, deltamethrin, fipronil, imidacloprid, carbaryl, and triadimefon. Toxicol Appl Pharmacol 2015; 282:184-94. [DOI: 10.1016/j.taap.2014.11.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2014] [Revised: 11/22/2014] [Accepted: 11/24/2014] [Indexed: 01/20/2023]
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38
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Roy D, Sigala R, Breakspear M, McIntosh AR, Jirsa VK, Deco G, Ritter P. Using the Virtual Brain to Reveal the Role of Oscillations and Plasticity in Shaping Brain's Dynamical Landscape. Brain Connect 2014; 4:791-811. [DOI: 10.1089/brain.2014.0252] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023] Open
Affiliation(s)
- Dipanjan Roy
- Department of Neurology, Charité—University Medicine, Berlin, Germany
- Bernstein Focus State Dependencies of Learning & Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Rodrigo Sigala
- Department of Neurology, Charité—University Medicine, Berlin, Germany
- Bernstein Focus State Dependencies of Learning & Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Michael Breakspear
- Division of Mental Health Research, Queensland Institute of Medical Research, Brisbane, QLD, Australia
- School of Psychiatry, University of New South Wales and The Black Dog Institute, Sydney, NSW, Australia
- The Royal Brisbane and Woman's Hospital, Brisbane, QLD, Australia
| | | | - Viktor K. Jirsa
- Institut de Neurosciences des Systèmes UMR INSERM 1106, Aix-Marseille Université Faculté de Médecine, Marseille, France
| | - Gustavo Deco
- Center for Brain and Cognition, Universitat Pompeu Fabra, ICREA (Institut Catala Recerca i Estudis Avancats), Barcelona, Spain
| | - Petra Ritter
- Department of Neurology, Charité—University Medicine, Berlin, Germany
- Bernstein Focus State Dependencies of Learning & Bernstein Center for Computational Neuroscience, Berlin, Germany
- Minerva Research Group BrainModes, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Berlin School of Mind and Brain & Mind and Brain Institute, Humboldt University, Berlin, Germany
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39
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Lehmann D, Faber PL, Pascual-Marqui RD, Milz P, Herrmann WM, Koukkou M, Saito N, Winterer G, Kochi K. Functionally aberrant electrophysiological cortical connectivities in first episode medication-naive schizophrenics from three psychiatry centers. Front Hum Neurosci 2014; 8:635. [PMID: 25191252 PMCID: PMC4138932 DOI: 10.3389/fnhum.2014.00635] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2014] [Accepted: 07/30/2014] [Indexed: 01/08/2023] Open
Abstract
Functional dissociation between brain processes is widely hypothesized to account for aberrations of thought and emotions in schizophrenic patients. The typically small groups of analyzed schizophrenic patients yielded different neurophysiological findings, probably because small patient groups are likely to comprise different schizophrenia subtypes. We analyzed multichannel eyes-closed resting EEG from three small groups of acutely ill, first episode productive schizophrenic patients before start of medication (from three centers: Bern N = 9; Osaka N = 9; Berlin N = 12) and their controls. Low resolution brain electromagnetic tomography (LORETA) was used to compute intracortical source model-based lagged functional connectivity not biased by volume conduction effects between 19 cortical regions of interest (ROIs). The connectivities were compared between controls and patients of each group. Conjunction analysis determined six aberrant cortical functional connectivities that were the same in the three patient groups. Four of these six concerned the facilitating EEG alpha-1 frequency activity; they were decreased in the patients. Another two of these six connectivities concerned the inhibiting EEG delta frequency activity; they were increased in the patients. The principal orientation of the six aberrant cortical functional connectivities was sagittal; five of them involved both hemispheres. In sum, activity in the posterior brain areas of preprocessing functions and the anterior brain areas of evaluation and behavior control functions were compromised by either decreased coupled activation or increased coupled inhibition, common across schizophrenia subtypes in the three patient groups. These results of the analyzed three independent groups of schizophrenics support the concept of functional dissociation.
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Affiliation(s)
- Dietrich Lehmann
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
| | - Pascal L Faber
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
| | - Roberto D Pascual-Marqui
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
| | - Patricia Milz
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
| | - Werner M Herrmann
- Laboratory of Clinical Psychophysiology, Department of Psychiatry, University Hospital Benjamin Franklin, Free University of Berlin Berlin, Germany
| | - Martha Koukkou
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
| | | | - Georg Winterer
- Experimental and Clinical Research Center, Charité - University Medicine Berlin Berlin, Germany
| | - Kieko Kochi
- Department of Psychiatry, Psychotherapy and Psychosomatics, The KEY Institute for Brain-Mind Research, University Hospital for Psychiatry Zurich, Switzerland
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40
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Pascual-Marqui RD, Biscay RJ, Bosch-Bayard J, Lehmann D, Kochi K, Kinoshita T, Yamada N, Sadato N. Assessing direct paths of intracortical causal information flow of oscillatory activity with the isolated effective coherence (iCoh). Front Hum Neurosci 2014; 8:448. [PMID: 24999323 PMCID: PMC4064566 DOI: 10.3389/fnhum.2014.00448] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2014] [Accepted: 06/03/2014] [Indexed: 11/13/2022] Open
Abstract
Functional connectivity is of central importance in understanding brain function. For this purpose, multiple time series of electric cortical activity can be used for assessing the properties of a network: the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections. The partial directed coherence (PDC) of Baccala and Sameshima (2001) is a widely used method for this problem. The three aims of this study are: (1) To show that the PDC can misrepresent the frequency response under plausible realistic conditions, thus defeating the main purpose for which the measure was developed; (2) To provide a solution to this problem, namely the "isolated effective coherence" (iCoh), which consists of estimating the partial coherence under a multivariate autoregressive model, followed by setting all irrelevant associations to zero, other than the particular directional association of interest; and (3) To show that adequate iCoh estimators can be obtained from non-invasively computed cortical signals based on exact low resolution electromagnetic tomography (eLORETA) applied to scalp EEG recordings. To illustrate the severity of the problem with the PDC, and the solution achieved by the iCoh, three examples are given, based on: (1) Simulated time series with known dynamics; (2) Simulated cortical sources with known dynamics, used for generating EEG recordings, which are then used for estimating (with eLORETA) the source signals for the final connectivity assessment; and (3) EEG recordings in rats. Lastly, real human recordings are analyzed, where the iCoh between six cortical regions of interest are calculated and compared under eyes open and closed conditions, using 61-channel EEG recordings from 109 subjects. During eyes closed, the posterior cingulate sends alpha activity to all other regions. During eyes open, the anterior cingulate sends theta-alpha activity to other frontal regions.
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Affiliation(s)
- Roberto D. Pascual-Marqui
- The KEY Institute for Brain-Mind Research, University of ZurichZurich, Switzerland
- Department of Neuropsychiatry, Kansai Medical UniversityOsaka, Japan
| | | | | | - Dietrich Lehmann
- The KEY Institute for Brain-Mind Research, University of ZurichZurich, Switzerland
| | - Kieko Kochi
- The KEY Institute for Brain-Mind Research, University of ZurichZurich, Switzerland
| | | | - Naoto Yamada
- Department of Psychiatry, Shiga University of Medical ScienceShiga, Japan
| | - Norihiro Sadato
- Division of Cerebral Integration, National Institute for Physiological SciencesOkazaki, Japan
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