Faculty Opinions recommendation of Resting-state neural activity across face-selective cortical regions is behaviorally relevant.

2011 ◽  
Author(s):  
Cheryl Grady
Keyword(s):  
Neural Activity ◽  
Resting State ◽  
Cortical Regions

scholarly journals Resting-State Neural Activity across Face-Selective Cortical Regions Is Behaviorally Relevant

2011 ◽  
Vol 31 (28) ◽  
pp. 10323-10330 ◽  
Author(s):  
Q. Zhu ◽  
J. Zhang ◽  
Y. L. L. Luo ◽  
D. D. Dilks ◽  
J. Liu
Keyword(s):  
Neural Activity ◽  
Resting State ◽  
Cortical Regions

scholarly journals Scale-Free Coupled Dynamics in Brain Networks Captured by Bivariate Focus-Based Multifractal Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Orestis Stylianou ◽  
Frigyes Samuel Racz ◽  
Andras Eke ◽  
Peter Mukli
Keyword(s):  
Resting State ◽  
Functional Coupling ◽  
Dependent Manner ◽  
Coupled Dynamics ◽  
Scale Free ◽  
Neural Processes ◽  
Eeg Recordings ◽  
Cortical Regions ◽  
The Brain

While most connectivity studies investigate functional connectivity (FC) in a scale-dependent manner, coupled neural processes may also exhibit broadband dynamics, manifesting as power-law scaling of their measures of interdependence. Here we introduce the bivariate focus-based multifractal (BFMF) analysis as a robust tool for capturing such scale-free relations and use resting-state electroencephalography (EEG) recordings of 12 subjects to demonstrate its performance in reconstructing physiological networks. BFMF was employed to characterize broadband FC between 62 cortical regions in a pairwise manner, with all investigated connections being tested for true bivariate multifractality. EEG channels were also grouped to represent the activity of six resting-state networks (RSNs) in the brain, thus allowing for the analysis of within- and between- RSNs connectivity, separately. Most connections featured true bivariate multifractality, which could be attributed to the genuine scale-free coupling of neural dynamics. Bivariate multifractality showed a characteristic topology over the cortex that was highly concordant among subjects. Long-term autocorrelation was higher in within-RSNs, while the degree of multifractality was generally found stronger in between-RSNs connections. These results offer statistical evidence of the bivariate multifractal nature of functional coupling in the brain and validate BFMF as a robust method to capture such scale-independent coupled dynamics.

scholarly journals Patterns of EEG Activity in Individuals with Autism Spectrum Disorders

2016 ◽  
Vol 21 (3) ◽  
pp. 47-55
Author(s):  
M.A. Zhukova
Keyword(s):  
Autism Spectrum Disorders ◽  
Neural Activity ◽  
Low Frequency ◽  
Strong Relationship ◽  
Autism Spectrum ◽  
Semantic Integration ◽  
Adults With Autism ◽  
Eeg Activity ◽  
Spectrum Disorders ◽  
Cortical Regions

The article reviews most recent findings on neural activity in children and adults with autism spectrum disorders (ASD). Most of the studies demonstrate decreased connectivity in cortical regions, excitatory/inhibitory imbalance and atypical processing of language in people with ASD. It is argued that difficulties in semantic integration are connected to selective insensitivity to language, which is manifested in atypical N400 ERP component. In the article we analyze the data suggesting a strong relationship between ASD and epilepsy and argue that the comorbidity is more prevalent among individuals who have cognitive dysfunction. The EEG profile of people with ASD suggests U-shaped alterations with excess in high- and low-frequency EEG bands. We critically analyze the “broken mirror” hypothesis of ASD and demonstrate findings which challenge this theory.

scholarly journals Disrupted Spontaneous Neural Activity in Patients With Thyroid-Associated Ophthalmopathy: A Resting-State fMRI Study Using Amplitude of Low-Frequency Fluctuation

2021 ◽  
Vol 15 ◽  
Author(s):  
Wen Chen ◽  
Qian Wu ◽  
Lu Chen ◽  
Jiang Zhou ◽  
Huan-Huan Chen ◽  
...  
Keyword(s):  
Neural Activity ◽  
Resting State ◽  
Low Frequency ◽  
Occipital Lobe ◽  
Frequency Fluctuation ◽  
Clinical Activity ◽  
Spontaneous Neural Activity ◽  
Thyroid Associated Ophthalmopathy ◽  
Middle Occipital Gyrus ◽  
Left Middle

PurposeThe purpose of the study was to investigate the brain functional alteration in patients with thyroid-associated ophthalmopathy (TAO) by evaluating the spontaneous neural activity changes using resting-state functional magnetic resonance imaging (rs-fMRI) with the amplitude of low-frequency fluctuation (ALFF) method.Materials and MethodsThe rs-fMRI data of 30 TAO patients (15 active and 15 inactive) and 15 healthy controls (HCs) were included for analyses. The ALFF values were calculated and compared among groups. Correlations between ALFF values and clinical metrics were assessed.ResultsCompared with HCs, active TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, and cuneus. Compared with inactive TAOs, active TAOs showed significantly increased ALFF values in the bilateral precuneus. Additionally, inactive TAOs showed significantly decreased ALFF values in the left middle occipital gyrus, superior occipital gyrus, cuneus, and bilateral precuneus than HCs. The ALFF value in the right precuneus of TAOs was positively correlated with clinical activity score (r = 0.583, P < 0.001) and Mini-Mental State Examination (MMSE) score (r = 0.377, P = 0.040), and negatively correlated with disease duration (r = −0.382, P = 0.037). Moreover, the ALFF value in the left middle occipital gyrus of TAOs was positively correlated with visual acuity (r = 0.441, P = 0.015).ConclusionTAO patients had altered spontaneous brain activities in the left occipital lobe and bilateral precuneus. The neuropsychological aspect of the disease should be noticed during clinical diagnosis and treatment.

Individual Differences in Mental Imagery Modulate Effective Connectivity of Scene-Selective Regions During Resting State

2021 ◽  
Author(s):  
Maria Giulia Tullo ◽  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Valentina Sulpizio ◽  
Daniele Marinazzo ◽  
...  
Keyword(s):  
Individual Differences ◽  
Mental Imagery ◽  
Resting State ◽  
Effective Connectivity ◽  
Relevant Information ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Inhibitory Influence ◽  
Cortical Regions ◽  
Intrinsic Fluctuation

Abstract Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals’ ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex (RSC), and Occipital Place Area (OPA) using Dynamic Causal Modelling (DCM) for resting-state functional magnetic resonance (rs-fMRI) data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire (VVIQ). We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

Abstract WMP117: Regional Homogeneity Changes In Patients With Transient Ischemic Attack: A Resting-state Functional Magnetic Resonance Imaging Study

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jian Guo ◽  
Ning Chen ◽  
Muke Zhou ◽  
Pian Wang ◽  
Li He
Keyword(s):  
Transient Ischemic Attack ◽  
Neural Activity ◽  
Resting State ◽  
Right Hemisphere ◽  
Brain Activity ◽  
Imaging Study ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Ischemic Attack

Background: Transient ischemic attack (TIA) can increase the risk of some neurologic dysfunctions, of which the mechanism remains unclear. Resting-state functional MRI (rfMRI) is suggested to be a valuable tool to study the relation between spontaneous brain activity and behavioral performance. However, little is known about whether the local synchronization of spontaneous neural activity is altered in TIA patients. The purpose of this study is to detect differences in regional spontaneous activities throughout the whole brain between TIAs and normal controls. Methods: Twenty one TIA patients suffered an ischemic event in the right hemisphere and 21 healthy volunteers were enrolled in the study. All subjects were investigated using cognitive tests and rfMRI. The regional homogeneity (ReHo) was calculate and compared between two groups. Then a correlation analysis was performed to explore the relationship between ReHo values of brain regions showing abnormal resting-state properties and clinical variables in TIA group. Results: Compared with controls, TIA patients exhibited decreased ReHo in right dorsolateral prefrontal cortex (DLPFC), right inferior prefrontal gyrus, right ventral anterior cingulate cortex and right dorsal posterior cingular cortex. Moreover, the mean ReHo in right DLPFC and right inferior prefrontal gyrus were significantly correlated with MoCA in TIA patients. Conclusions: Neural activity in the resting state is changed in patients with TIA. The positive correlation between regional homogeneity of rfMRI and cognition suggests that ReHo may be a promising tool to better our understanding of the neurobiological consequences of TIA.

Is Our Brain an Open or Closed System? Prediction Model of Brain and World–Brain Relation

2018 ◽  
pp. 55-76
Author(s):  
Georg Northoff
Keyword(s):  
Prediction Model ◽  
Closed System ◽  
Neural Activity ◽  
Resting State ◽  
Clinical Symptoms ◽  
Predictive Coding ◽  
Human Cognition ◽  
The World ◽  
World Brain ◽  
The Brain

Some recent philosophical discussions consider whether the brain is best understood as an open or closed system. This issue has major epistemic consequences akin to the scepticism engendered by the famous Cartesian demon. Specifically, one and the same empirical theory of brain function, predictive coding, entailing a prediction model of brain, have been associated with contradictory views of the brain as either open (Clark, 2012, 2013) or closed (Hohwy, 2013, 2014). Based on recent empirical evidence, the present paper argues that contrary to appearances, these views of the brain are compatible with one another. I suggest that there are two main forms of neural activity in the brain, one of which can be characterized as open, and the other as closed. Stimulus-induced activity, because it relies on predictive coding is indeed closed to the world, which entails that in certain respects, the brain is an inferentially secluded and self-evidencing system. In contrast, the brain’s resting state or spontaneous activity is best taken as open because it is a world-evidencing system that allows for the brain’s neural activity to align with the statistically-based spatiotemporal structure of objects and events in the world. This model requires an important caveat, however. Due to its statistically-based nature, the resting state’s alignment to the world comes in degrees. In extreme cases, the degree of alignment can be extremely low, resulting in a resting state that is barely if at all aligned to the world. This is for instance the case in schizophrenia. Clinical symptoms such as delusions and hallucinations in schizophrenics are indicative of the fundamental delicateness of the alignment between the brain’s resting-state and the world’s phenomena. Nevertheless, I argue that so long as we are dealing with a well-functioning brain, the more dire epistemic implications of predictive coding can be forestalled. That the brain is in part a self-evidencing system does not yield any generalizable reason to worry that human cognition is out of step with the real world. Instead, the brain is aligned to the world accounting for “world-brain relation” that mitigates sceptistic worries.

Sign in / Sign up

Export Citation Format

Share Document