Changes in power and coherence of brain activity in human sensorimotor cortex during performance of visuomotor tasks

Biosystems ◽  
2001 ◽  
Vol 63 (1-3) ◽  
pp. 89-99 ◽  
Author(s):  
F Aoki ◽  
E.E Fetz ◽  
L Shupe ◽  
E Lettich ◽  
G.A Ojemann
Keyword(s):  
Sensorimotor Cortex ◽  
Brain Activity ◽  
Visuomotor Tasks

Time Course of Changes in Brain Activity and Functional Connectivity Associated With Long-Term Adaptation to a Rotational Transformation

2005 ◽  
Vol 93 (4) ◽  
pp. 2254-2262 ◽  
Author(s):  
Valeria Della-Maggiore ◽  
Anthony R. McIntosh
Keyword(s):  
Functional Connectivity ◽  
Sensorimotor Cortex ◽  
Time Course ◽  
Brain Activity ◽  
Visuomotor Adaptation ◽  
Middle Temporal Gyrus ◽  
Middle Temporal ◽  
Functional Connections ◽  
Rotational Transformation

The purpose of this study was to examine the time course of changes in cerebral activity and functional connectivity during long-term adaptation to a visuomotor transformation. Positron emission tomography was used to measure changes in brain activity as subjects tracked a target under the influence of a rotational transformation that distorted visual feedback. The experiment was 1 week long and consisted of two scanning sessions (obtained on days 2 and 7), aimed at examining early and late stages of learning. On average, visuomotor adaptation was achieved within 3 days. During early stages of adaptation, better performance was associated with greater activity in brain areas related to attention including bilateral dorso- and ventrolateral prefrontal cortices, frontal eye fields, and the human homologue of area MT. However, as adaptation proceeded, improvements in performance were associated with greater activity in motor regions such as the left (contralateral) sensorimotor cortex, bilateral anterior cerebellum, left cingulate motor area, right putamen, and a nonmotor region within the middle temporal gyrus. This learning-specific shift in brain activity was associated with a progressive change in the functional connectivity of these regions toward the end of the first session. Interestingly, only the functional connections between the anterior cerebellum, left middle temporal gyrus, and left sensorimotor cortex remained strong once visuomotor adaptation was achieved. Our findings suggest that visuomotor adaptation is not only reflected in persistent changes in activity in motor-related regions, but also in the strengthening and maintenance of specific functional connections.

Increased gamma-range activity in human sensorimotor cortex during performance of visuomotor tasks

1999 ◽  
Vol 110 (3) ◽  
pp. 524-537 ◽  
Author(s):  
F. Aoki ◽  
E.E. Fetz ◽  
L. Shupe ◽  
E. Lettich ◽  
G.A. Ojemann
Keyword(s):  
Sensorimotor Cortex ◽  
Gamma Range ◽  
Visuomotor Tasks

scholarly journals Measurement of the mapping between intracranial EEG and fMRI recordings in the human brain

2017 ◽  
Author(s):  
DW Carmichael ◽  
S Vulliemoz ◽  
T Murta ◽  
U. Chaudhary ◽  
S Perani ◽  
...  
Keyword(s):  
Human Brain ◽  
Sensorimotor Cortex ◽  
Brain Activity ◽  
Spatial Scales ◽  
Electrophysiological Response ◽  
Intracranial Eeg ◽  
Eeg Activity ◽  
High Gamma ◽  
Gamma Power ◽  
Patients With Epilepsy

AbstractThere are considerable gaps in our understanding of the relationship between human brain activity measured at different temporal and spatial scales by intracranial electroencephalography and fMRI. By comparing individual features and summary descriptions of intracranial EEG activity we determined which best predict fMRI changes in the sensorimotor cortex in two brain states: at rest and during motor performance. We also then examine the specificity of this relationship to spatial colocalisation of the two signals.We acquired electrocorticography and fMRI simultaneously (ECoG-fMRI) in the sensorimotor cortex of 3 patients with epilepsy. During motor activity, high gamma power was the only frequency band where the electrophysiological response was colocalised with fMRI measures across all subjects. The best model of fMRI changes was its principal components, a parsimonious description of the entire ECoG spectrogram. This model performed much better than a model based on the classical frequency bands both during task and rest periods or models derived on a summary of cross spectral changes (e.g. ‘root mean squared EEG frequency’). This suggests that the region specific fMRI signal is reflected in spatially and spectrally distributed EEG activity.

Inducing Neuroplasticity through Intracranial Theta Burst Stimulation in the Human Sensorimotor Cortex

2021 ◽  
Author(s):  
Jose L Herrero ◽  
Alexander Smith ◽  
Akash Mishra ◽  
Noah Markowitz ◽  
Ashesh D Mehta ◽  
...  
Keyword(s):  
Sensorimotor Cortex ◽  
Brain Activity ◽  
Activity Patterns ◽  
Oscillatory Activity ◽  
Theta Burst Stimulation ◽  
Burst Stimulation ◽  
Beta Band ◽  
Sensorimotor Network ◽  
Intracranial Electrodes ◽  
Theta Burst

The progress of therapeutic neuromodulation greatly depends on improving stimulation parameters to most efficiently induce neuroplasticity effects. Intermittent Theta Burst stimulation (iTBS), a form of electrical stimulation that mimics natural brain activity patterns, has proved to efficiently induce such effects in animal studies and rhythmic Transcranial Magnetic Stimulation studies in humans. However, little is known about the potential neuroplasticity effects of iTBS applied through intracranial electrodes in humans. This study characterizes the physiological effects of intracranial iTBS in humans and compare them with alpha frequency stimulation, another frequently used neuromodulatory pattern. We applied these two stimulation patterns to well-defined regions in the sensorimotor cortex, which elicited contralateral hand muscle contractions during clinical mapping, in epilepsy patients implanted with intracranial electrodes. Treatment effects were evaluated using oscillatory coherence across areas connected to the treatment site, as defined with cortico-cortical evoked potentials. Our results show that iTBS increases coherence in the beta frequency band within the sensorimotor network indicating a potential neuroplasticity effect. The effect is specific to the sensorimotor system, the beta-band and the stimulation pattern, and outlasted the stimulation period by ~3 minutes. The effect occurred in 4/7 subjects depending on the build-up of the effect during iTBS treatment and other patterns of oscillatory activity related to ceiling effects within the beta-band and to pre-existent coherence within the alpha-band. By characterizing the neurophysiological effects of iTBS within well-defined cortical networks, we hope to provide an electrophysiological framework that allows clinicians/researchers to optimize brain stimulation protocols which may have translational value.

scholarly journals Mu rhythm suppression over sensorimotor regions is associated with greater empathic accuracy

2018 ◽  
Author(s):  
Desmond C. Ong ◽  
jamil zaki ◽  
Anat Perry
Keyword(s):  
Sensorimotor Cortex ◽  
Brain Activity ◽  
Empathic Accuracy ◽  
Self Report ◽  
Oscillatory Activity ◽  
Motor Simulation ◽  
Mu Rhythm ◽  
Low Level ◽  
Mu Suppression ◽  
Emotional Events

When people encounter others' emotions, they engage multiple brain systems, including parts of sensorimotor cortex associated with motor simulation. Simulation-related brain activity is commonly described as a "low-level" component of empathy and social cognition. As such, it has been studied predominantly using simple, non-naturalistic tasks, such as viewing facial expressions or biological motion. This leaves unclear whether and how sensorimotor simulation contributes to more complex empathic judgments. Here we explore this phenomenon by combining a naturalistic social paradigm with a reliable index of sensorimotor cortex-based simulation: EEG suppression of oscillatory activity in the mu (8-13 Hz) frequency band. We recruited participants to watch naturalistic video clips of people ("targets") describing emotional events in their lives. Participants viewed these clips (i) with both video and sound, (ii) with only video, or (iii) with only sound. Participants provided continuous ratings of how they believed the target in the video felt. We calculated participants' empathic accuracy as the correlation between their inferences and targets' self-report. Across all conditions, right-lateralized mu suppression tracked empathic accuracy. This was true when examining accuracy for videos as a whole, as well as when examining accuracy over 3-second intervals within each video. Our results provide novel evidence that motor representations—as measured through mu suppression—play an important role not only in low-level motor simulation, but also in higher-level inferences about others' emotions.

scholarly journals Ipsilateral finger representations in the sensorimotor cortex are driven by active movement processes, not passive sensory input

2019 ◽  
Vol 121 (2) ◽  
pp. 418-426 ◽  
Author(s):  
Eva Berlot ◽  
George Prichard ◽  
Jill O’Reilly ◽  
Naveed Ejaz ◽  
Jörn Diedrichsen
Keyword(s):  
Sensorimotor Cortex ◽  
High Field ◽  
Sensory Input ◽  
Brain Activity ◽  
Activity Patterns ◽  
Sensory Information ◽  
Sensory Stimulation ◽  
Active Movement ◽  
Contralateral Hemisphere ◽  
Ipsilateral Hemisphere

Hand and finger movements are mostly controlled through crossed corticospinal projections from the contralateral hemisphere. During unimanual movements, activity in the contralateral hemisphere is increased while the ipsilateral hemisphere is suppressed below resting baseline. Despite this suppression, unimanual movements can be decoded from ipsilateral activity alone. This indicates that ipsilateral activity patterns represent parameters of ongoing movement, but the origin and functional relevance of these representations is unclear. In this study, we asked whether ipsilateral representations are caused by active movement or whether they are driven by sensory input. Participants alternated between performing single finger presses and having fingers passively stimulated while we recorded brain activity using high-field (7T) functional imaging. We contrasted active and passive finger representations in sensorimotor areas of ipsilateral and contralateral hemispheres. Finger representations in the contralateral hemisphere were equally strong under passive and active conditions, highlighting the importance of sensory information in feedback control. In contrast, ipsilateral finger representations in the sensorimotor cortex were stronger during active presses. Furthermore, the spatial distribution of finger representations differed between hemispheres: the contralateral hemisphere showed the strongest finger representations in Brodmann areas 3a and 3b, whereas the ipsilateral hemisphere exhibited stronger representations in premotor and parietal areas. Altogether, our results suggest that finger representations in the two hemispheres have different origins: contralateral representations are driven by both active movement and sensory stimulation, whereas ipsilateral representations are mainly engaged during active movement. NEW & NOTEWORTHY Movements of the human body are mostly controlled by contralateral cortical regions. The function of ipsilateral activity during movements remains elusive. Using high-field neuroimaging, we investigated how human contralateral and ipsilateral hemispheres represent active and passive finger presses. We found that representations in contralateral sensorimotor cortex are equally strong during both conditions. Ipsilateral representations were mostly present during active movement, suggesting that sensorimotor areas do not receive direct sensory input from the ipsilateral hand.

scholarly journals Classification of Articulator Movements and Movement Direction from Sensorimotor Cortex Activity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
E. Salari ◽  
Z. V. Freudenburg ◽  
M. P. Branco ◽  
E. J. Aarnoutse ◽  
M. J. Vansteensel ◽  
...  
Keyword(s):  
Neural Activity ◽  
Sensorimotor Cortex ◽  
Muscle Activity ◽  
Cortical Area ◽  
Brain Activity ◽  
Activity Patterns ◽  
Movement Direction ◽  
Computer Interfaces ◽  
Small Parts

Abstract For people suffering from severe paralysis, communication can be difficult or nearly impossible. Technology systems called brain-computer interfaces (BCIs) are being developed to assist these people with communication by using their brain activity to control a computer without any muscle activity. To benefit the development of BCIs that employ neural activity related to speech, we investigated if neural activity patterns related to different articulator movements can be distinguished from each other. We recorded with electrocorticography (ECoG), the neural activity related to different articulator movements in 4 epilepsy patients and classified which articulator participants moved based on the sensorimotor cortex activity patterns. The same was done for different movement directions of a single articulator, the tongue. In both experiments highly accurate classification was obtained, on average 92% for different articulators and 85% for different tongue directions. Furthermore, the data show that only a small part of the sensorimotor cortex is needed for classification (ca. 1 cm2). We show that recordings from small parts of the sensorimotor cortex contain information about different articulator movements which might be used for BCI control. Our results are of interest for BCI systems that aim to decode neural activity related to (actual or attempted) movements from a contained cortical area.

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