Magnetoencephalography

2017 ◽  
Author(s):  
Riitta Hari
Keyword(s):  
Sensory Processing ◽  
Quantum Interference ◽  
Sensor Technology ◽  
Brain Dynamics ◽  
Clinical Neuroscience ◽  
Sensory Stimuli ◽  
Superconducting Quantum Interference Devices ◽  
Brain Signals ◽  
Basic Characteristics ◽  
The Brain

This chapter introduces magnetoencephalography (MEG), a tool to study brain dynamics in basic and clinical neuroscience. MEG picks up brain signals with millisecond resolution, as does electroencephalography, but without distortion by skull and scalp. The chapter describes current instrumentation based on superconducting quantum interference devices (SQUIDs). It delineates basic characteristics of measured signals: (1) brain rhythms and their reactivity during sensory processing and various tasks and (2) evoked responses elicited by sensory stimuli, and the dependence of these responses on various stimulus characteristics. Signals are described from healthy and diseased brains. The chapter presents studies of the brain basis of cognition and social interaction studied in dual-MEG setups and describes how MEG applications can be broadened by innovative setups, including frequency tagging. Progress in the field is predicted regarding sensor technology, data analysis, and multimodal brain imaging, all of which could strengthen MEG’s role in the study of brain dynamics.

scholarly journals Ayres Theories of Autism and Sensory Integration Revisited: What Contemporary Neuroscience Has to Say

2019 ◽  
Vol 9 (3) ◽  
pp. 68 ◽  
Author(s):  
Emily Kilroy ◽  
Lisa Aziz-Zadeh ◽  
Sharon Cermak
Keyword(s):  
Sensory Processing ◽  
Sensory Integration ◽  
Autism Spectrum ◽  
Therapeutic Interventions ◽  
Brain Areas ◽  
Sensory Stimuli ◽  
Spectrum Disorders ◽  
Neural Underpinnings ◽  
The Brain ◽  
Neuroimaging Techniques

Abnormal sensory-based behaviors are a defining feature of autism spectrum disorders (ASD). Dr. A. Jean Ayres was the first occupational therapist to conceptualize Sensory Integration (SI) theories and therapies to address these deficits. Her work was based on neurological knowledge of the 1970’s. Since then, advancements in neuroimaging techniques make it possible to better understand the brain areas that may underlie sensory processing deficits in ASD. In this article, we explore the postulates proposed by Ayres (i.e., registration, modulation, motivation) through current neuroimaging literature. To this end, we review the neural underpinnings of sensory processing and integration in ASD by examining the literature on neurophysiological responses to sensory stimuli in individuals with ASD as well as structural and network organization using a variety of neuroimaging techniques. Many aspects of Ayres’ hypotheses about the nature of the disorder were found to be highly consistent with current literature on sensory processing in children with ASD but there are some discrepancies across various methodological techniques and ASD development. With additional characterization, neurophysiological profiles of sensory processing in ASD may serve as valuable biomarkers for diagnosis and monitoring of therapeutic interventions, such as SI therapy.

PHASE TRANSITIONS IN THE HUMAN BRAIN: SPATIAL MODE DYNAMICS

1992 ◽  
Vol 02 (04) ◽  
pp. 917-939 ◽  
Author(s):  
ARMIN FUCHS ◽  
J.A. SCOTT KELSO ◽  
HERMANN HAKEN
Keyword(s):  
Phase Transitions ◽  
Quantum Interference ◽  
Brain Activity ◽  
Superconducting Quantum Interference Device ◽  
Slowing Down ◽  
Self Organized ◽  
Brain Signals ◽  
Spatial Modes ◽  
The Brain ◽  
Qualitative Changes

Pattern formation and switching between self-organized states are often associated with instabilities in open, nonequilibrium systems. We describe an experiment which shows that systematically changing a control parameter induces qualitative changes in sensorimotor coordination and brain activity, as registered by a 37-SQUID (Superconducting Quantum Interference Device) array. Near the instability point, predicted features of nonequilibrium phase transitions (critical slowing down, fluctuation enhancement) are observed in both the psychophysical data and the brain signals obtained from single SQUID sensors. Further analysis reveals that activity from the entire array displays spatial patterns evolving in time. Such spatiotemporal patterns are characterized by the dynamics of only a few coherent spatial modes.

scholarly journals Minimum Standards for Clinical Evoked Potential Studies

1994 ◽  
Vol 21 (1) ◽  
pp. 75-77 ◽  
Author(s):  
Keyword(s):  
Evoked Potentials ◽  
Sensory Processing ◽  
Sensory Function ◽  
Sensory Response ◽  
Sensory Stimuli ◽  
Sensory Pathways ◽  
Neurological Patients ◽  
Electrical Activities ◽  
The Brain ◽  
Averaging Techniques

Evoked potentials are the electrical changes that occur in the brain in response to sensory stimuli. They can be recorded from scalp electrodes using sensitive amplifiers. Averaging techniques are necessary to separate the evoked potentials from other electrical activities. Evoked potentials can provide helpful information for the clinical evaluation of neurological patients. They can assess sensory function by demonstrating the brain's response to sensory stimuli. They can localize dysfunction in sensory pathways by showing where and when a sensory response becomes abnormal. They can identify abnormalities of sensory processing that are not apparent during the usual clinical examination. They can assess the extent of normal or abnormal function and thereby assist prognosis in patients with brain-damage.

scholarly journals Rapid changes in brain activity during learning of grapheme-phoneme associations in adults

2020 ◽  
Author(s):  
Weiyong Xu ◽  
Orsolya Beatrix Kolozsvari ◽  
Robert Oostenveld ◽  
Jarmo Arvid Hämäläinen
Keyword(s):  
Learning Process ◽  
Speech Sound ◽  
Cortical Reorganization ◽  
Source Analysis ◽  
Brain Dynamics ◽  
Large Network ◽  
Speech Sounds ◽  
Sensory Stimuli ◽  
Brain Responses ◽  
The Brain

ABSTRACTLearning to associate written letters with speech sounds is crucial for the initial phase of acquiring reading skills. However, little is known about the cortical reorganization for supporting letter-speech sound learning, particularly the brain dynamics during the learning of grapheme-phoneme associations. In the present study, we trained 30 Finnish participants (mean age: 24.33 years, SD: 3.50 years) to associate novel foreign letters with familiar Finnish speech sounds on two consecutive days (first day ~ 50 minutes; second day ~ 25 minutes), while neural activity was measured using magnetoencephalography (MEG). Two sets of audiovisual stimuli were used for the training in which the grapheme-phoneme association in one set (Learnable) could be learned based on the different learning cues provided, but not in the other set (Control). The learning progress was tracked at a trial-by-trial basis and used to segment different learning stages for the MEG source analysis. The learning-related changes were examined by comparing the brain responses to Learnable and Control uni/multi-sensory stimuli, as well as the brain responses to learning cues at different learning stages over the two days. We found dynamic changes in brain responses related to multi-sensory processing when grapheme-phoneme associations were learned. Further, changes were observed in the brain responses to the novel letters during the learning process. We also found that some of these learning effects were observed only after memory consolidation the following day. Overall, the learning process modulated the activity in a large network of brain regions, including the superior temporal cortex and the dorsal (parietal) pathway. Most interestingly, middle- and inferior-temporal regions were engaged during multi-sensory memory encoding after the cross-modal relationship was extracted from the learning cues. Our findings highlight the brain dynamics and plasticity related to the learning of letter-speech sound associations and provide a more refined model of grapheme-phoneme learning in reading acquisition.

NON-INVASIVE BCI METHOD: EEG - ELECTROENCEPHALOGRAPHY

2019 ◽  
pp. 139-145
Author(s):  
Selma Büyükgöze
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Electrode Placement ◽  
Eeg Signals ◽  
Non Invasive ◽  
Brain Signals ◽  
Brain States ◽  
The Brain

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.

scholarly journals Implication of the Sensory Environment in Children with Autism Spectrum Disorder: Perspectives from School

2021 ◽  
Vol 18 (14) ◽  
pp. 7670
Author(s):  
Ana Gentil-Gutiérrez ◽  
José Luis Cuesta-Gómez ◽  
Paula Rodríguez-Fernández ◽  
Jerónimo Javier González-Bernal
Keyword(s):  
Autism Spectrum Disorder ◽  
Sensory Processing ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Sensory Profile ◽  
School Factors ◽  
Cross Sectional ◽  
Sensory Stimuli ◽  
Children With Asd

(1) Background: Children with Autism Spectrum Disorder (ASD) frequently have difficulties in processing sensory information, which is a limitation when participating in different contexts, such as school. The objective of the present study was to compare the sensory processing characteristics of children with ASD in the natural context of school through the perception of professionals in the field of education, in comparison with neurodevelopmental children (2) Methods: A cross-sectional descriptive study as conducted with study population consisting of children between three and ten years old, 36 of whom were diagnosed with ASD and attended the Autismo Burgos association; the remaining 24 had neurotypical development. The degree of response of the children to sensory stimuli at school was evaluated using the Sensory Profile-2 (SP-2) questionnaire in its school version, answered by the teachers. (3) Results: Statistically significant differences were found in sensory processing patterns (p = 0.001), in sensory systems (p = 0.001) and in school factors (p = 0.001). Children with ASD who obtained worse results. (4) Conclusions: Children with ASD are prone to present sensory alterations in different contexts, giving nonadapted behavioral and learning responses.

scholarly journals The brain dynamics of architectural affordances during transition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zakaria Djebbara ◽  
Lars Brorson Fich ◽  
Klaus Gramann
Keyword(s):  
Occipital Cortex ◽  
The Body ◽  
Brain Dynamics ◽  
Alpha Band ◽  
Time Frequency ◽  
Posterior Cingulate ◽  
Sensory Signals ◽  
Event Related Desynchronization ◽  
The Brain ◽  
Attentional Mechanisms

AbstractAction is a medium of collecting sensory information about the environment, which in turn is shaped by architectural affordances. Affordances characterize the fit between the physical structure of the body and capacities for movement and interaction with the environment, thus relying on sensorimotor processes associated with exploring the surroundings. Central to sensorimotor brain dynamics, the attentional mechanisms directing the gating function of sensory signals share neuronal resources with motor-related processes necessary to inferring the external causes of sensory signals. Such a predictive coding approach suggests that sensorimotor dynamics are sensitive to architectural affordances that support or suppress specific kinds of actions for an individual. However, how architectural affordances relate to the attentional mechanisms underlying the gating function for sensory signals remains unknown. Here we demonstrate that event-related desynchronization of alpha-band oscillations in parieto-occipital and medio-temporal regions covary with the architectural affordances. Source-level time–frequency analysis of data recorded in a motor-priming Mobile Brain/Body Imaging experiment revealed strong event-related desynchronization of the alpha band to originate from the posterior cingulate complex, the parahippocampal region as well as the occipital cortex. Our results firstly contribute to the understanding of how the brain resolves architectural affordances relevant to behaviour. Second, our results indicate that the alpha-band originating from the occipital cortex and parahippocampal region covaries with the architectural affordances before participants interact with the environment, whereas during the interaction, the posterior cingulate cortex and motor areas dynamically reflect the affordable behaviour. We conclude that the sensorimotor dynamics reflect behaviour-relevant features in the designed environment.

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