scholarly journals Bioceramic Material Stimulation Affects Perceptual Consciousness: A Study Combining Descriptive Observation and Functional MRI Connectivity Analysis

2022 ◽  
Author(s):  
Ting-Kai Leung ◽  
Chia-Wei Li ◽  
Yu-Chun Lo ◽  
Ping-Yen Tsai ◽  
Jia-Yi Wang
Keyword(s):  
Brain Infarction ◽  
Threshold Value ◽  
Resting State Fmri ◽  
Angular Gyrus ◽  
Parahippocampal Gyrus ◽  
Light Spectrum ◽  
Perceptual Consciousness ◽  
Brain Functions ◽  
Clear Explanation ◽  
Material Stimulation

Abstract There is still no clear explanation of the process of perceptual consciousness that connects our body with brain. Innovation on the technology of bioceramic has now advanced towards clinical applications, including rehabilitation of brain infarction, therapies of insomnia and migraine. To demonstrate how ‘resonant energy transfer through the bioceramic material with tempo sound and visible light spectrum’ (bioceramic material stimulation, BMS) non-invasively affects perceptual consciousness, we investigated the responses of participants to BMS on perceptual consciousness by questionnaire of subjective descriptions and analyzed resting state fMRI during BMS. There were 61.3% participants who were categorized as positive group with various types of perceptual consciousness. By setting a threshold value at ‘p<0.001’, enhanced connections of ‘parahippocampal gyrus to cerebellar lobule V’ and ‘angular gyrus to precuneus’ were found. However, decreased connection of ‘caudate nucleus to cerebellar lobule VIIb’ was found. We conclude that the most affected brain functions by BMS including somatosensory, audio-visual perception and social cognition. The analysis of functional connectivity during BMS may help us gain more knowledge of consciousness and related division of neuroscience in humans.

Ventrolateral Preoptic Nucleus of Hypothalamus: A Possible Target for Deep Brain Stimulation for Treating Sexual Dysfunction

2020 ◽  
Vol 5 (3 And 4) ◽  
pp. 99-102
Author(s):  
Fariborz Ghaffarpasand ◽  
◽  
Mousa Taghipour ◽  
Keyword(s):  
Deep Brain Stimulation ◽  
Sexual Dysfunction ◽  
Sexual Function ◽  
Brain Stimulation ◽  
Sexual Behaviors ◽  
Angular Gyrus ◽  
Parahippocampal Gyrus ◽  
Left Caudate ◽  
Ventrolateral Preoptic Nucleus ◽  
Deep Brain

Sexual function and orientation is a complex platform of human personality which is being modulated by several brain circuities which is less understood currently. Recently, several studies have demonstrated interesting results regarding the role of several brain locations in sexual behaviors and orientation. Sexual arousal in homosexual men is associated with activation of the left angular gyrus, left caudate nucleus, Ventrolateral Preoptic (VLPO) Nucleus of Hypothalamus and right pallidum; while it is associated with bilateral lingual gyrus, right hippocampus, and right parahippocampal gyrus in heterosexual men. We postulate that sexual-orientation behaviors are being mediated by several circuits in the brain in the center of which the VLPO is playing an indistinguishable role. We hypothesize that the different aspects of the sexual dysfunction could be associated with innate or acquired lesions of VLPO. Accordingly, the electrical stimulation of the nucleus in those with sexual dysfunction would be a treatment option. Thus the VLPO could be considered a target for Deep Brain Stimulation (DBS) in individuals with impaired sexual function.

Abnormal Brain Functions in Neuromyelitis Optica: a Resting-state fMRI Study

NeuroImage ◽  
2009 ◽  
Vol 47 ◽  
pp. S90
Author(s):  
Q-Z Wu ◽  
D-D Zhao ◽  
D He ◽  
X-Q Huang ◽  
T-J Zhang ◽  
...  
Keyword(s):  
Neuromyelitis Optica ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Functions ◽  
Fmri Study ◽  
Abnormal Brain

scholarly journals Music reduces pain and increases resting state fMRI BOLD signal amplitude in the left angular gyrus in fibromyalgia patients

2015 ◽  
Vol 6 ◽  
Author(s):  
Eduardo A. Garza-Villarreal ◽  
Zhiguo Jiang ◽  
Peter Vuust ◽  
Sarael Alcauter ◽  
Lene Vase ◽  
...  
Keyword(s):  
Resting State ◽  
Signal Amplitude ◽  
Resting State Fmri ◽  
Angular Gyrus ◽  
Bold Signal ◽  
Left Angular Gyrus

scholarly journals Additive and interaction effects of working memory and motor sequence training on brain functional connectivity

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Priska Zuber ◽  
Laura Gaetano ◽  
Alessandra Griffa ◽  
Manuel Huerbin ◽  
Ludovico Pedullà ◽  
...  
Keyword(s):  
Working Memory ◽  
Functional Connectivity ◽  
Processing Speed ◽  
Resting State ◽  
Resting State Fmri ◽  
Interactive Effects ◽  
Angular Gyrus ◽  
Precentral Gyrus ◽  
Motor Sequence ◽  
Brain Functional Connectivity

AbstractAlthough shared behavioral and neural mechanisms between working memory (WM) and motor sequence learning (MSL) have been suggested, the additive and interactive effects of training have not been studied. This study aimed at investigating changes in brain functional connectivity (FC) induced by sequential (WM + MSL and MSL + WM) and combined (WM × MSL) training programs. 54 healthy subjects (27 women; mean age: 30.2 ± 8.6 years) allocated to three training groups underwent twenty-four 40-min training sessions over 6 weeks and four cognitive assessments including functional MRI. A double-baseline approach was applied to account for practice effects. Test performances were compared using linear mixed-effects models and t-tests. Resting state fMRI data were analysed using FSL. Processing speed, verbal WM and manual dexterity increased following training in all groups. MSL + WM training led to additive effects in processing speed and verbal WM. Increased FC was found after training in a network including the right angular gyrus, left superior temporal sulcus, right superior parietal gyrus, bilateral middle temporal gyri and left precentral gyrus. No difference in FC was found between double baselines. Results indicate distinct patterns of resting state FC modulation related to sequential and combined WM and MSL training suggesting a relevance of the order of training performance. These observations could provide new insight for the planning of effective training/rehabilitation.

scholarly journals Subgenual cingulate-amygdala functional disconnection and vulnerability to melancholic depression

2021 ◽  
Author(s):  
Clifford Ian Workman ◽  
Karen E. Lythe ◽  
Shane McKie ◽  
Jorge Moll ◽  
Jennifer A. Gethin ◽  
...  
Keyword(s):  
Resting State ◽  
A Priori ◽  
Resting State Fmri ◽  
Parahippocampal Gyrus ◽  
Melancholic Depression ◽  
Neural Signature ◽  
The Right ◽  
Depressive Episodes ◽  
Resting State Connectivity ◽  
Subgenual Cingulate

The syndromic heterogeneity of major depressive disorder (MDD) hinders understanding of the etiology of predisposing vulnerability traits and underscores the importance of identifying neurobiologically valid phenotypes. Distinctive fMRI biomarkers of vulnerability to MDD subtypes are currently lacking. This study investigated whether remitted melancholic MDD patients, who are at an elevated lifetime risk for depressive episodes, demonstrate distinctive patterns of resting-state connectivity with the subgenual cingulate cortex (SCC), known to be of core pathophysiological importance for severe and familial forms of MDD. We hypothesized that patterns of disrupted SCC connectivity would be a distinguishing feature of melancholia. A total of 63 medication-free remitted MDD (rMDD) patients (33 melancholic and 30 nonmelancholic) and 39 never-depressed healthy controls (HC) underwent resting-state fMRI scanning. SCC connectivity was investigated with closely connected bilateral a priori regions of interest (ROIs) relevant to MDD (anterior temporal, ventromedial prefrontal, dorsomedial prefrontal cortices, amygdala, hippocampus, septal region, and hypothalamus). Decreased (less positive) SCC connectivity with the right parahippocampal gyrus and left amygdala distinguished melancholic rMDD patients from the nonmelancholic rMDD and HC groups (cluster-based familywise error-corrected p⩽0.007 over individual a priori ROIs corresponding to approximate Bonferroni-corrected p⩽0.05 across all seven a priori ROIs). No areas demonstrating increased (more positive) connectivity were observed. Abnormally decreased connectivity of the SCC with the amygdala and parahippocampal gyrus distinguished melancholic from nonmelancholic rMDD. These results provide the first resting-state neural signature distinctive of melancholic rMDD and may reflect a subtype-specific primary vulnerability factor given a lack of association with the number of previous episodes.

scholarly journals Deep learning-based classification of resting-state fMRI independent-component analysis

2020 ◽  
Author(s):  
Victor Nozais ◽  
Philippe Boutinaud ◽  
Violaine Verrecchia ◽  
Marie-Fateye Gueye ◽  
Pierre Yves Hervé ◽  
...  
Keyword(s):  
Deep Learning ◽  
Resting State ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Independent Component ◽  
Angular Gyrus ◽  
Automated Classification ◽  
Dimensional Parameter ◽  
Spatial Level

Functional connectivity analyses of fMRI data have shown that the activity of the brain at rest is spatially organized into resting-state networks (RSNs). RSNs appear as groups of anatomically distant but functionally tightly connected brain regions. Inter-RSN intrinsic connectivity analyses may provide an optimal spatial level of integration to analyze the variability of the functional connectome. Here, we propose a deep learning approach to enable the automated classification of individual independent-component (IC) decompositions into a set of predefined RSNs. Two databases were used in this work, BIL&GIN and MRi-Share, with 427 and 1811 participants respectively. We trained a multi-layer perceptron (MLP) to classify each IC as one of 45 RSNs, using the IC classification of 282 participants in BIL&GIN for training and a 5-dimensional parameter grid search for hyperparameter optimization. It reached an accuracy of 92%. Predictions on the remaining individuals in BIL&GIN were tested against the original classification and demonstrated good spatial overlap between the cortical RSNs. As a first application, we created an RSN atlas based on MRi-Share. This atlas defined a brain parcellation in 29 RSNs covering 96% of the gray matter. Second, we proposed an individual-based analysis of the subdivision of the default-mode network into 4 networks. Minimal overlap between RSNs was found except in the angular gyrus and potentially in the precuneus. We thus provide the community with an individual IC classifier that can be used to analyze one dataset or to statistically compare different datasets for RSN spatial definitions.

scholarly journals Cerebral Responses to Stationary Emotional Stimuli Measured by fMRI in Women with Persistent Postural-Perceptual Dizziness

2020 ◽  
Author(s):  
Eliane Maria Dias von Söhsten Lins ◽  
Roseli Saraiva Moreira Bittar ◽  
Paulo Rodrigo Bazán ◽  
Edson Amaro Júnior ◽  
Jeffrey Paul Staab
Keyword(s):  
Spatial Perception ◽  
Visual Stimuli ◽  
Threat Assessment ◽  
Vestibular Stimulation ◽  
Anterior Cingulate ◽  
Angular Gyrus ◽  
Parahippocampal Gyrus ◽  
Vestibular Disorder ◽  
Fmri Study ◽  
Increased Activity

Abstract Introduction Persistent postural-perceptual dizziness (PPPD) is a functional vestibular disorder characterized by chronic dizziness, unsteadiness, and hypersensitivity to motion. Preexisting anxiety disorders and neurotic personality traits confer vulnerability to PPPD. High anxiety during acute vertigo or dizziness incites it. A functional magnetic resonance imaging (fMRI) study of chronic subjective dizziness found unexpectedly hypoactive responses to vestibular stimulation in cortical regions that integrate threat assessment and spatial perception. Objective This fMRI study used non-moving, but emotionally charged visual stimuli to investigate the brain's activity of PPPD patients and control subjects. Methods The participants included 16 women with PPPD and 16 age-matched women who recovered completely from acute episodes of vertigo or dizziness capable of triggering PPPD. Brain responses to positive, neutral, and negative figures from the International Affective Picture System were measured with fMRI and compared between the groups. Dizziness handicap, anxiety, and depression were assessed with validated questionnaires. Results Between group analyses: Participants with PPPD showed reduced activity in anterior cingulate cortex and increased activity in left angular gyrus in response to negative versus positive stimuli, which was not observed in recovered individuals. Within group analyses: Participants with PPPD had increased activity in visuospatial areas (parahippocampal gyrus, intraparietal sulcus) in negative versus positive and negative versus neutral contrasts, whereas recovered individuals had increased activity in anxiety regions (amygdala, orbitofrontal cortex). Conclusion Patients with PPPD may be more attuned to spatial elements than to the content of emotionally charged visual stimuli.

scholarly journals Network Mapping of Connectivity Alterations in Disorder of Consciousness: Towards Targeted Neuromodulation

2020 ◽  
Vol 9 (3) ◽  
pp. 828 ◽  
Author(s):  
Lucia Mencarelli ◽  
Maria Chiara Biagi ◽  
Ricardo Salvador ◽  
Sara Romanella ◽  
Giulio Ruffini ◽  
...  
Keyword(s):  
Brain Stimulation ◽  
Resting State ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Therapeutic Interventions ◽  
Angular Gyrus ◽  
Biophysical Modeling ◽  
Disorder Of Consciousness ◽  
Positron Emission ◽  
Clinical Conditions

Disorder of consciousness (DoC) refers to a group of clinical conditions that may emerge after brain injury, characterized by a varying decrease in the level of consciousness that can last from days to years. An understanding of its neural correlates is crucial for the conceptualization and application of effective therapeutic interventions. Here we propose a quantitative meta-analysis of the neural substrate of DoC emerging from functional magnetic resonance (fMRI) and positron emission tomography (PET) studies. We also map the relevant networks of resulting areas to highlight similarities with Resting State Networks (RSNs) and hypothesize potential therapeutic solutions leveraging network-targeted noninvasive brain stimulation. Available literature was reviewed and analyzed through the activation likelihood estimate (ALE) statistical framework to describe resting-state or task-dependent brain activation patterns in DoC patients. Results show that task-related activity is limited to temporal regions resembling the auditory cortex, whereas resting-state fMRI data reveal a diffuse decreased activation affecting two subgroups of cortical (angular gyrus, middle frontal gyrus) and subcortical (thalamus, cingulate cortex, caudate nucleus) regions. Clustering of their cortical functional connectivity projections identify two main altered functional networks, related to decreased activity of (i) the default mode and frontoparietal networks, as well as (ii) the anterior salience and visual/auditory networks. Based on the strength and topography of their connectivity profile, biophysical modeling of potential brain stimulation solutions suggests the first network as the most feasible target for tES, tDCS neuromodulation in DoC patients.

scholarly journals Individual Thresholding of Voxel-based Functional Connectivity Maps

2015 ◽  
Vol 54 (03) ◽  
pp. 227-231 ◽  
Author(s):  
F. Baglio ◽  
M. M. Laganà ◽  
M. G. Preti ◽  
P. Cecconi ◽  
M. Clerici ◽  
...  
Keyword(s):  
Time Series ◽  
Functional Connectivity ◽  
Threshold Value ◽  
Resting State Fmri ◽  
Posterior Cingulate Cortex ◽  
Single Subject ◽  
Random Errors ◽  
Global Threshold ◽  
Correlation Threshold ◽  
The Brain

SummaryIntroduction: This article is part of the Focus Theme of Methods of Information in Medicine on “Biosignal Interpretation: Advanced Methods for Neural Signals and Images”.Background: Voxel-based functional connectivity analysis is a common method for resting state fMRI data. However, correlations between the seed and other brain voxels are corrupted by random estimate errors yielding false connections within the functional connectivity map (FCmap). These errors must be taken into account for a correct interpretation of single-subject results.Objectives: We estimated the statistical range of random errors and propose two methods for an individual setting of correlation threshold for FCmaps.Methods: We assessed the amount of random errors by means of surrogate time series and described its distribution within the brain. On the basis of these results, the FCmaps of the posterior cingulate cortex (PCC) from 15 healthy subjects were thresholded with two innovative methods: the first one consisted in the computation of a unique (global) threshold value to be applied to all brain voxels, while the second method is to set a different (local) threshold of each voxel of the FCmap.Results: The distribution of random errors within the brain was observed to be homogeneous and, after thresholding with both methods, the default mode network areas were well identifiable. The two methods yielded similar results, however the application of a global threshold to all brain voxels requires a reduced computational load. The inter-subject variability of the global threshold was observed to be very low and not correlated with age. Global threshold values are also almost independent from the number of surrogates used for their computation, so the analyses can be optimized using a reduced number of surrogate time series.Conclusions: We demonstrated the efficacy of FCmaps thresholding based on random error estimation. This method can be used for a reliable single-subject analysis and could also be applied in clinical setting, to compute individual measures of disease progression or quantitative response to pharmacological or rehabilitation treatments.

scholarly journals Estudio de los correlatos neurales de la percepción emocional por análisis de patrones en multitud de voxeles

2021 ◽  
Author(s):  
Isaac David
Keyword(s):  
Brain Activity ◽  
Univariate Analysis ◽  
Parahippocampal Gyrus ◽  
Neural Basis ◽  
Basic Emotions ◽  
Negative Valence ◽  
Brain Functions ◽  
Data Points ◽  
Emotional System ◽  
Multivariate Pattern

Emotion and its perception are fundamental psychological faculties for the survival of animals and social interaction. This is recognized by the emergence of whole areas of neuroscience devoted to understanding its neural basis. Although the basic components of such emotional system have been identified, the segregation of the milieu of affective experiences into different patterns of brain signals remains poorly understood. Recent functional imaging studies have implicated simultaneous distributed activity as a better correlate of emotional state than its univariate counterpart; however, those attempts have still restricted themselves to regions of interest and severely-filtered data. In this work we tested whether the visual perception of three basic emotions can be decoded from full brain activity using multivariate pattern classification, while keeping localizationist and encoding assumptions at a minimum. Beyond stimuli prediction, we also provide proof of-concept anatomical mapping and discovery of relevant structures.To this end, we ran a face perception experiment on a sample of 16 neurotypical participants while recording their brain activity using fMRI. Per-subject SVM classifiers were trained on the fMRI data, so that they could recognize the emotion class brains were presented with. Results were cross-validated and compared against performance by chance using resampling techniques; and the whole of our reproducible pipeline was further validated using more trivial contrasts embedded within the main emotional task. Thorough assessment of behavioral data points towards the validity of our task.Results show a robust and distributed representation of (perceived) happiness in humans, but not of negative-valence anger and sadness; contrary to the more optimistic (though less diligent) existing studies. Overall, our approach proved more sensitive and anatomically specific than the classical mass-univariate analysis, amidst high-dimensionality concerns. Group inference of SVM parameters suggests the defining information-bearing pattern emanates from known structures in the ventral visual pathway and emotion-related areas. Namely: the primary visual cortex (V1) and surroundings, the middle collateral sulcus and parahippocampal gyrus (mCS, mPHG), the amygdala, the medial prefrontal cortex (mPFC) and the anterior cerebellum around the vermis; all of them in bilateral fashion. Our work paves the way for further multivariate studies to provide a complementary picture of emotions (and other brain functions), according to its macroscale dynamics.

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