Comparative analysis of changes of bioelectrical activity of the brain during the neutral touch and during the performance of the myofascial release technique

2018 ◽  
pp. 46-55
Author(s):  
A. F. Belyaev ◽  
G. E. Piskunova
Keyword(s):  
Soft Tissue ◽  
Brain Activity ◽  
Direct Action ◽  
Brain Regions ◽  
Therapeutic Touch ◽  
Bioelectrical Activity ◽  
Therapeutic Action ◽  
Osteopathic Treatment ◽  
The Difference ◽  
Multiparameter Analysis

Introduction. One of the main tools of an osteopath are soft tissue techniques, which have a number of particular qualities such as minimization of force and duration of indirect techniques with an emphasis on muscle and ligamentous structures; combination of gestures, tendency to maximal relaxation and exclusion of direct action on pathological symptoms such as tension, overtone and pain. Minimization of the force applied during the performance of soft tissue techniques often invites a question whether there are differences between the usual touch and the therapeutic touch of an osteopath.Goal of research - to reveal the changes in the bioelectrical activity of the cerebral cortex arising in the process of osteopathic treatment in order to prove its specifi city in comparison with nonspecifi c tactile stimulation (neutral touch).Materials and methods. 75 people were examined with the use of multiparameter analysis of multichannel EEG in different times. 25 patients were clinically healthy adults, whereas 50 patients had signs of somatic dysfunctions.Results. Computer encephalography permits to perceive the difference between the neutral touch and the therapeutic action. An identifi cation reaction is a response to the neutral touch (changes in brain bioelectrical activity with an increase in statistically signifi cant connections in the temporal lobes), whereas the therapeutic action provokes the state of purposeful brain activity during still point (intensifi cation of frontooccipital interactions).Conclusions. Osteopathic action causes additional tension in the processing of incoming information, which requires participation of different brain regions, including interhemispheric mechanisms associated with analysis, maintenance of attention and regulation of targeted activities.

Differences in network centrality between high and low myopia: a voxel-level degree centrality study

2020 ◽  
Vol 61 (10) ◽  
pp. 1388-1397
Author(s):  
Yi Cheng ◽  
Li Yan ◽  
Liqun Hu ◽  
Hongyun Wu ◽  
Xin Huang ◽  
...  
Keyword(s):  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Anterior Lobe ◽  
Parahippocampal Gyrus ◽  
Functional Networks ◽  
Degree Centrality ◽  
Left Caudate ◽  
The Difference ◽  
The Right

Background Previous studies have linked high myopia (HM) to brain activity, and the difference between HM and low myopia (LM) can be assessed. Purpose To study the differences in functional networks of brain activity between HM and LM by the voxel-level degree centrality (DC) method. Material and Methods Twenty-eight patients with HM (10 men, 18 women), 18 patients with LM (4 men, 14 women), and 59 healthy controls (27 men, 32 women) were enrolled in this study. The voxel-level DC method was used to assess spontaneous brain activity. Correlation analysis was used to explore the change of average DC value in different brain regions, in order to analyze differences in brain activity between HM and LM. Results DC values of the right cerebellum anterior lobe/brainstem, right parahippocampal gyrus, and left caudate in HM patients were significantly higher than those in LM patients ( P < 0.05). In contrast, DC values of the left medial frontal gyrus, right inferior frontal gyrus, left middle frontal gyrus, and left inferior parietal lobule were significantly lower in patients with HM ( P < 0.05). However, there was no correlation between behavior and average DC values in different brain regions ( P < 0.05). Conclusion Different changes in brain regions between HM and LM may indicate differences in neural mechanisms between HM and LM. DC values could be useful as biomarkers for differences in brain activity between patients with HM and LM. This study provides a new method to assess differences in functional networks of brain activity between patients with HM and LM.

scholarly journals Ongoing dynamics in large-scale functional connectivity predict perception

2015 ◽  
Vol 112 (27) ◽  
pp. 8463-8468 ◽  
Author(s):  
Sepideh Sadaghiani ◽  
Jean-Baptiste Poline ◽  
Andreas Kleinschmidt ◽  
Mark D’Esposito
Keyword(s):  
Functional Connectivity ◽  
Network Structure ◽  
Large Scale ◽  
Brain Activity ◽  
Network Connectivity ◽  
Brain Regions ◽  
Modular Network ◽  
Auditory Detection ◽  
Correlation Strength ◽  
The Difference

Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22–40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.

scholarly journals Lower neural value signaling in the prefrontal cortex is related to childhood family income and depressive symptomatology during adolescence

2021 ◽  
Author(s):  
Esther E. Palacios-Barrios ◽  
Jamie L. Hanson ◽  
Kelly R. Barry ◽  
Dustin Albert ◽  
Stuart F. White ◽  
...  
Keyword(s):  
Decision Making ◽  
Prefrontal Cortex ◽  
Adolescent Depression ◽  
Family Income ◽  
Depressive Symptomatology ◽  
Brain Activity ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Reward Learning ◽  
The Difference

AbstractLower family income during childhood is related to increased rates of adolescent depression, though the specific mechanisms are poorly understood. Evidence suggests that individuals with depression demonstrate hypoactivation in brain regions involved in reward learning and decision-making processes (e.g., portions of the prefrontal cortex). Separately, lower family income has been associated with neural alterations in similar regions. We examined associations between family income, depression, and brain activity during a reward learning and decision-making fMRI task in a sample of adolescents (full n=94; usable n=78; mean age=15.4 years). We identified neural regions representing 1) expected value (EV), the learned subjective value of an object, and 2) prediction error, the difference between EV and the actual outcome received. Regions of interest related to reward learning were examined in connection to childhood family income and parent-reported adolescent depressive symptoms. As hypothesized, lower activity in the subgenual anterior cingulate (sACC) for EV in response to approach stimuli was associated with lower childhood family income, as well as greater symptoms of depression measured one-year after the neuroimaging session. These results are consistent with the hypothesis that lower early family income leads to disruptions in reward and decision-making brain circuitry, which leads to adolescent depression.

scholarly journals Role of the cortex in visuomotor control of arm stability

2019 ◽  
Vol 122 (5) ◽  
pp. 2156-2172
Author(s):  
Dylan B. Snyder ◽  
Scott A. Beardsley ◽  
Brian D. Schmit
Keyword(s):  
Brain Activity ◽  
Arm Movements ◽  
Cortical Activity ◽  
Brain Regions ◽  
Visuomotor Control ◽  
Beta Band ◽  
Arm Position ◽  
Motor Commands ◽  
The Difference ◽  
Cortical Involvement

Whereas numerous motor control theories describe the control of arm trajectory during reach, the control of stabilization in a constant arm position (i.e., visuomotor control of arm posture) is less clear. Three potential mechanisms have been proposed for visuomotor control of arm posture: 1) increased impedance of the arm through co-contraction of antagonistic muscles, 2) corrective muscle activity via spinal/supraspinal reflex circuits, and/or 3) intermittent voluntary corrections to errors in position. We examined the cortical mechanisms of visuomotor control of arm posture and tested the hypothesis that cortical error networks contribute to arm stabilization. We collected electroencephalography (EEG) data from 10 young healthy participants across four experimental planar movement tasks. We examined brain activity associated with intermittent voluntary corrections of position error and antagonist co-contraction during stabilization. EEG beta-band (13–26 Hz) power fluctuations were used as indicators of brain activity, and coherence between EEG electrodes was used as a measure of functional connectivity between brain regions. Cortical activity in the sensory, motor, and visual areas during arm stabilization was similar to activity during volitional arm movements and was larger than activity during co-contraction of the arm. However, cortical connectivity between the sensorimotor and visual regions was higher during arm stabilization compared with volitional arm movements and co-contraction of the arm. The difference in cortical activity and connectivity between tasks might be attributed to an underlying visuomotor error network used to update motor commands for visuomotor control of arm posture. NEW & NOTEWORTHY We examined cortical activity and connectivity during control of stabilization in a constant arm position (i.e., visuomotor control of arm posture). Our findings provide evidence for cortical involvement during control of stabilization in a constant arm position. A visuomotor error network appears to be active and may update motor commands for visuomotor control of arm posture.

scholarly journals The Effects of Acupuncture at Real or Sham Acupoints on the Intrinsic Brain Activity in Mild Cognitive Impairment Patients

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Baohui Jia ◽  
Zhishun Liu ◽  
Baoquan Min ◽  
Zhenchang Wang ◽  
Aihong Zhou ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Brain Activity ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Network ◽  
Healthy Controls ◽  
The Difference ◽  
The Brain

Accumulating neuroimaging studies in humans have shown that acupuncture can modulate a widely distributed brain network in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) patients. Acupuncture at different acupoints could exert different modulatory effects on the brain network. However, whether acupuncture at real or sham acupoints can produce different effects on the brain network in MCI or AD patients remains unclear. Using resting-state fMRI, we reported that acupuncture at Taixi (KI3) induced amplitude of low-frequency fluctuation (ALFF) change of different brain regions in MCI patients from those shown in the healthy controls. In MCI patients, acupuncture at KI3 increased or decreased ALFF in the different regions from those activated by acupuncture in the healthy controls. Acupuncture at the sham acupoint in MCI patients activated the different brain regions from those in healthy controls. Therefore, we concluded that acupuncture displays more significant effect on neuronal activities of the above brain regions in MCI patients than that in healthy controls. Acupuncture at KI3 exhibits different effects on the neuronal activities of the brain regions from acupuncture at sham acupoint, although the difference is only shown at several regions due to the close distance between the above points.

Time Course of Activity in Itch-Related Brain Regions: A Combined MEG–fMRI Study

2009 ◽  
Vol 102 (5) ◽  
pp. 2657-2666 ◽  
Author(s):  
Hideki Mochizuki ◽  
Koji Inui ◽  
Hiroki C. Tanabe ◽  
Lisa F. Akiyama ◽  
Naofumi Otsuru ◽  
...  
Keyword(s):  
Time Course ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Posterior Part ◽  
Brain Regions ◽  
Anterior Cingulate ◽  
Magnetic Response ◽  
Temporal Aspect ◽  
The Difference ◽  
Brain Processing

Functional neuroimaging studies have identified itch-related brain regions. However, no study has investigated the temporal aspect of itch-related brain processing. Here this issue was investigated using electrically evoked itch in ten healthy adults. Itch stimuli were applied to the left wrist and brain activity was measured using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI). In the MEG experiment, the magnetic responses evoked by the itch stimuli were observed in the contralateral and ipsilateral frontotemporal regions. The dipoles associated with the magnetic responses were mainly located in the contralateral (nine subjects) and ipsilateral (eight subjects) secondary somatosensory cortex (SII)/insula, which were also activated by the itch stimuli in the fMRI experiment. We also observed an itch-related magnetic response in the posterior part of the centroparietal region in six subjects. MEG and fMRI data showed that the magnetic response in this region was mainly associated with itch-related activation of the precuneus. The latency was significantly longer in the ipsilateral than that in the contralateral SII/insula, suggesting the difference to be associated with transmission in the callosal fibers. The timing of activation of the precuneus was between those of the contralateral and ipsilateral SII/insula. Other sources were located in the premotor, primary motor, and anterior cingulate cortices (one subject each). This study is the first to demonstrate part of the time course of itch-related brain processing. Combining methods with high temporal and spatial resolution (e.g., MEG and fMRI) would be useful to investigate the temporal aspect of the brain mechanism of itch.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

scholarly journals Visual predictions, neural oscillations and naïve physics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Blake W. Saurels ◽  
Wiremu Hohaia ◽  
Kielan Yarrow ◽  
Alan Johnston ◽  
Derek H. Arnold
Keyword(s):  
Brain Activity ◽  
Dynamic Environment ◽  
Predictive Performance ◽  
Brain Regions ◽  
Internal Models ◽  
Oscillatory Activity ◽  
Alpha Band ◽  
Core Property ◽  
Ball Tracking ◽  
Band Activity

AbstractPrediction is a core function of the human visual system. Contemporary research suggests the brain builds predictive internal models of the world to facilitate interactions with our dynamic environment. Here, we wanted to examine the behavioural and neurological consequences of disrupting a core property of peoples’ internal models, using naturalistic stimuli. We had people view videos of basketball and asked them to track the moving ball and predict jump shot outcomes, all while we recorded eye movements and brain activity. To disrupt people’s predictive internal models, we inverted footage on half the trials, so dynamics were inconsistent with how movements should be shaped by gravity. When viewing upright videos people were better at predicting shot outcomes, at tracking the ball position, and they had enhanced alpha-band oscillatory activity in occipital brain regions. The advantage for predicting upright shot outcomes scaled with improvements in ball tracking and occipital alpha-band activity. Occipital alpha-band activity has been linked to selective attention and spatially-mapped inhibitions of visual brain activity. We propose that when people have a more accurate predictive model of the environment, they can more easily parse what is relevant, allowing them to better target irrelevant positions for suppression—resulting in both better predictive performance and in neural markers of inhibited information processing.

scholarly journals Resting‐State EEG Microstates Parallel Age‐Related Differences in Allocentric Spatial Working Memory Performance

2021 ◽  
Author(s):  
Adeline Jabès ◽  
Giuliana Klencklen ◽  
Paolo Ruggeri ◽  
Christoph M. Michel ◽  
Pamela Banta Lavenex ◽  
...  
Keyword(s):  
Older Adults ◽  
Working Memory ◽  
Resting State ◽  
Cognitive Aging ◽  
Temporal Dynamics ◽  
Spatial Working Memory ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Age Related

AbstractAlterations of resting-state EEG microstates have been associated with various neurological disorders and behavioral states. Interestingly, age-related differences in EEG microstate organization have also been reported, and it has been suggested that resting-state EEG activity may predict cognitive capacities in healthy individuals across the lifespan. In this exploratory study, we performed a microstate analysis of resting-state brain activity and tested allocentric spatial working memory performance in healthy adult individuals: twenty 25–30-year-olds and twenty-five 64–75-year-olds. We found a lower spatial working memory performance in older adults, as well as age-related differences in the five EEG microstate maps A, B, C, C′ and D, but especially in microstate maps C and C′. These two maps have been linked to neuronal activity in the frontal and parietal brain regions which are associated with working memory and attention, cognitive functions that have been shown to be sensitive to aging. Older adults exhibited lower global explained variance and occurrence of maps C and C′. Moreover, although there was a higher probability to transition from any map towards maps C, C′ and D in young and older adults, this probability was lower in older adults. Finally, although age-related differences in resting-state EEG microstates paralleled differences in allocentric spatial working memory performance, we found no evidence that any individual or combination of resting-state EEG microstate parameter(s) could reliably predict individual spatial working memory performance. Whether the temporal dynamics of EEG microstates may be used to assess healthy cognitive aging from resting-state brain activity requires further investigation.

scholarly journals Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

2021 ◽  
Vol 11 (7) ◽  
pp. 885
Author(s):  
Maher Abujelala ◽  
Rohith Karthikeyan ◽  
Oshin Tyagi ◽  
Jing Du ◽  
Ranjana K. Mehta
Keyword(s):  
Machine Learning ◽  
Environmental Conditions ◽  
Brain Activity ◽  
Memory Task ◽  
Classification Problem ◽  
Brain Regions ◽  
Training Data ◽  
Information Encoding ◽  
Machine Learning Approach ◽  
Encoding And Retrieval

The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.

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