Identifying Neural Abnormalities in Schizophrenia

2020 ◽  
pp. 359-374
Author(s):  
J. Christopher Edgar ◽  
Gregory A. Miller
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Brain Dysfunction ◽  
Comprehensive Review ◽  
And Task ◽  
Auditory Encoding

This chapter considers the use of magnetoencephalography (MEG) in understanding brain dysfunction in schizophrenia. Rather than provide a comprehensive review of the MEG schizophrenia literature, this chapter focuses on MEG brain measures that have received the most attention: resting-state studies and studies examining auditory encoding processes. Studies indicate that continued research in this area is of interest, with findings suggesting a focus on resting-state and task-related low-frequency activity.

scholarly journals Quasi-periodic patterns contribute to functional connectivity in the brain

2018 ◽  
Author(s):  
Anzar Abbas ◽  
Michaël Belloy ◽  
Amrit Kashyap ◽  
Jacob Billings ◽  
Maysam Nezafati ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Neural Activity ◽  
Resting State ◽  
Low Frequency ◽  
Spatiotemporal Pattern ◽  
List Type ◽  
Periodic Patterns ◽  
Default Mode ◽  
The Brain ◽  
And Task

AbstractFunctional connectivity is widely used to study the coordination of activity between brain regions over time. Functional connectivity in the default mode and task positive networks is particularly important for normal brain function. However, the processes that give rise to functional connectivity in the brain are not fully understood. It has been postulated that low-frequency neural activity plays a key role in establishing the functional architecture of the brain. Quasi-periodic patterns (QPPs) are a reliably observable form of low-frequency neural activity that involve the default mode and task positive networks. Here, QPPs from resting-state and working memory task-performing individuals were acquired. The spatiotemporal pattern, strength, and frequency of the QPPs between the two groups were compared and the contribution of QPPs to functional connectivity in the brain was measured. In task-performing individuals, the spatiotemporal pattern of the QPP changes, particularly in task-relevant regions, and the QPP tends to occur with greater strength and frequency. Differences in the QPPs between the two groups could partially account for the variance in functional connectivity between resting-state and task-performing individuals. The QPPs contribute strongly to connectivity in the default mode and task positive networks and to the strength of anti-correlation seen between the two networks. Many of the connections affected by QPPs are also disrupted during several neurological disorders. These findings contribute to understanding the dynamic neural processes that give rise to functional connectivity in the brain and how they may be disrupted during disease.HighlightsQuasi-periodic patterns (QPPs) of low-frequency activity contribute to functional connectivityThe spatiotemporal pattern of QPPs differs between resting-state and task-performing individualsQPPs account for significant functional connectivity in the DMN and TPN during rest and task performanceChanges in functional connectivity in these networks may reflect differences in QPPs

Can we measure spontaneous thinking? Regional amplitude of low-frequency fluctuation of cortical BOLD signal during resting state and task execution

NeuroImage ◽  
2001 ◽  
Vol 13 (6) ◽  
pp. 261
Author(s):  
Motoaki Sugiura ◽  
Ryuta Kawashima ◽  
Job Watanabe ◽  
Yuko Sato ◽  
Yasuhiro Maeda ◽  
...  
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Frequency Fluctuation ◽  
Bold Signal ◽  
Task Execution ◽  
And Task

scholarly journals The impact of hyperoxia on brain activity: A resting-state and task-evoked electroencephalography (EEG) study

PLoS ONE ◽  
2017 ◽  
Vol 12 (5) ◽  
pp. e0176610 ◽  
Author(s):  
Min Sheng ◽  
Peiying Liu ◽  
Deng Mao ◽  
Yulin Ge ◽  
Hanzhang Lu
Keyword(s):  
Resting State ◽  
Brain Activity ◽  
The Impact ◽  
And Task

Functional abnormalities in Broca’s area in adolescents with ADHD: A resting-state fMRI study

2015 ◽  
Vol 51 (1) ◽  
Author(s):  
Michał Pikusa ◽  
Rafał Jończyk
Keyword(s):  
Resting State ◽  
Low Frequency ◽  
Resting State Fmri ◽  
Broca’S Area ◽  
Broca's Area ◽  
Hyperactivity Disorder ◽  
Spontaneous Neural Activity ◽  
Fmri Study ◽  
Brodmann Areas ◽  
Underlying Causes

AbstractThere is evidence that attention-deficit/hyperactivity disorder (ADHD) is associated with linguistic difficulties. However, the pathophysiology underlying these difficulties is yet to be determined. This study investigates functional abnormalities in Broca’s area, which is associated with speech production and processing, in adolescents with ADHD by means of resting-state fMRI. Data for the study was taken from the ADHD-200 project and included 267 ADHD patients (109 with combined inattentive/hyperactive subtype and 158 with inattentive subtype) and 478 typically-developing control (TDC) subjects. An analysis of fractional amplitude of low-frequency fluctuations (fALFF), which reflects spontaneous neural activity, in Broca’s area (Brodmann Areas 44/45) was performed on the data and the results were compared statistically across the participant groups. fALFF was found to be significantly lower in the ADHD inattentive group as compared to TDC in BA 44, and in the ADHD combined group as compared to TDC in BA 45. The results suggest that there are functional abnormalities in Broca’s area with people suffering from ADHD, and that the localization of these abnormalities might be connected to particular language deficits associated with ADHD subtypes, which we discuss in the article. The findings might help explore the underlying causes of specific language difficulties in ADHD.

scholarly journals Neural basis underlying the trait of attachment anxiety and avoidance revealed by the amplitude of low-frequency fluctuations and resting-state functional connectivity

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Min Deng ◽  
Xing Zhang ◽  
Xiaoyan Bi ◽  
Chunhai Gao
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Low Frequency ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Attachment Anxiety ◽  
Frequency Fluctuation ◽  
Resting State Functional Connectivity ◽  
Attachment Avoidance ◽  
Posterior Cingulate

Abstract Background Attachment theory demonstrates that early attachment experience shapes internal working models with mental representations of self and close relationships, which affects personality traits and interpersonal relationships in adulthood. Although research has focused on brain structural and functional underpinnings to disentangle attachment styles in healthy individuals, little is known about the spontaneous brain activity associated with self-reported attachment anxiety and avoidance during the resting state. Methods One hundred and nineteen individuals participated in the study, completing the Experience in Close Relationship scale immediately after an 8-min fMRI scanning. We used the resting-state functional magnetic resonance imaging (rs-fMRI) signal of the amplitude of low-frequency fluctuation and resting-state functional connectivity to identify attachment-related regions and networks. Results Consequently, attachment anxiety is closely associated with the amplitude of low-frequency fluctuations in the right posterior cingulate cortex, over-estimating emotional intensity and exaggerating outcomes. Moreover, the functional connectivity between the posterior cingulate cortex and fusiform gyrus increases detection ability for potential threat or separation information, facilitating behavior motivation. The attachment avoidance is positively correlated with the amplitude of low-frequency fluctuation in the bilateral lingual gyrus and right postcentral and negatively correlated with the bilateral orbital frontal cortex and inferior temporal gyrus. Functional connection with attachment avoidance contains critical nodes in the medial temporal lobe memory system, frontal-parietal network, social cognition, and default mode network necessary to deactivate the attachment system and inhibit attachment-related behavior. Conclusion and implications These findings clarify the amplitude of low-frequency fluctuation and resting-state functional connectivity neural signature of attachment style, associated with attachment strategies in attachment anxiety and attachment avoidance individuals. These findings may improve our understanding of the pathophysiology of the attachment-related disorder.

scholarly journals Detecting functional connectivity disruptions in a translational pediatric traumatic brain injury porcine model using resting-state and task-based fMRI

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gregory Simchick ◽  
Kelly M. Scheulin ◽  
Wenwu Sun ◽  
Sydney E. Sneed ◽  
Madison M. Fagan ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Functional Connectivity ◽  
Resting State ◽  
Correlation Coefficients ◽  
Brain Network ◽  
Network Activity ◽  
Anatomical Structures ◽  
Healthy Control ◽  
And Task

AbstractFunctional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

Evaluation of fNIRS Signal Components Elicited by Cognitive and Hypercapnic Stimuli

2021 ◽  
Author(s):  
Pratusha Reddy ◽  
Meltem Izzetoglu ◽  
Patricia Shewokis ◽  
Michael Sangobowale ◽  
Ramon Diaz-Arrastia ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared ◽  
Low Frequency ◽  
Hemispheric Differences ◽  
Functional Versus ◽  
Functional Near Infrared Spectroscopy ◽  
Global Response ◽  
Very Low Frequency ◽  
Systemic Responses ◽  
And Task

Abstract Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.

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