scholarly journals Publisher Correction: Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jelena Trajkovic ◽  
Francesco Di Gregorio ◽  
Francesca Ferri ◽  
Chiara Marzi ◽  
Stefano Diciotti ◽  
...  
Keyword(s):  
Resting State ◽  
Oscillatory Activity ◽  
Reliable Marker

AbstractAn amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Resting state alpha oscillatory activity is a valid and reliable marker of schizotypy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jelena Trajkovic ◽  
Francesco Di Gregorio ◽  
Francesca Ferri ◽  
Chiara Marzi ◽  
Stefano Diciotti ◽  
...  
Keyword(s):  
At Risk ◽  
Resting State ◽  
Right Hemisphere ◽  
Normal Population ◽  
Alpha Activity ◽  
Oscillatory Activity ◽  
Loop Current ◽  
Clinical Tool ◽  
Reliable Marker ◽  
The Right

AbstractSchizophrenia is among the most debilitating neuropsychiatric disorders. However, clear neurophysiological markers that would identify at-risk individuals represent still an unknown. The aim of this study was to investigate possible alterations in the resting alpha oscillatory activity in normal population high on schizotypy trait, a physiological condition known to be severely altered in patients with schizophrenia. Direct comparison of resting-state EEG oscillatory activity between Low and High Schizotypy Group (LSG and HSG) has revealed a clear right hemisphere alteration in alpha activity of the HSG. Specifically, HSG shows a significant slowing down of right hemisphere posterior alpha frequency and an altered distribution of its amplitude, with a tendency towards a reduction in the right hemisphere in comparison to LSG. Furthermore, altered and reduced connectivity in the right fronto-parietal network within the alpha range was found in the HSG. Crucially, a trained pattern classifier based on these indices of alpha activity was able to successfully differentiate HSG from LSG on tested participants further confirming the specific importance of right hemispheric alpha activity and intrahemispheric functional connectivity. By combining alpha activity and connectivity measures with a machine learning predictive model optimized in a nested stratified cross-validation loop, current research offers a promising clinical tool able to identify individuals at-risk of developing psychosis (i.e., high schizotypy individuals).

scholarly journals The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

2019 ◽  
Vol 9 (1) ◽  
pp. 11 ◽  
Author(s):  
Ángel Romero-Martínez ◽  
Macarena González ◽  
Marisol Lila ◽  
Enrique Gracia ◽  
Luis Martí-Bonmatí ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Effective Treatment ◽  
Resting State ◽  
Brain Structures ◽  
Prevention Programs ◽  
Angular Gyrus ◽  
Resting State Functional Connectivity ◽  
Treatment And Prevention ◽  
Reliable Marker ◽  
The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

scholarly journals Changes in the Resting-State Cortical Oscillatory Activity 6 Months After Modified Tinnitus Retraining Therapy

2019 ◽  
Vol 13 ◽  
Author(s):  
Sang-Yeon Lee ◽  
Jihye Rhee ◽  
Ye Ji Shim ◽  
Yoonjoong Kim ◽  
Ja-Won Koo ◽  
...  
Keyword(s):  
Resting State ◽  
Oscillatory Activity ◽  
Tinnitus Retraining Therapy ◽  
Retraining Therapy

scholarly journals High-definition tDCS to the right temporoparietal junction modulates slow-wave resting state power and coherence in healthy adults

2019 ◽  
Vol 122 (4) ◽  
pp. 1735-1744 ◽  
Author(s):  
Peter H. Donaldson ◽  
Melissa Kirkovski ◽  
Joel S. Yang ◽  
Soukayna Bekkali ◽  
Peter G. Enticott
Keyword(s):  
Direct Current ◽  
Transcranial Direct Current Stimulation ◽  
Resting State ◽  
Oscillatory Activity ◽  
High Definition ◽  
Temporoparietal Junction ◽  
Eyes Open ◽  
Right Temporoparietal Junction ◽  
The Right ◽  
Cathodal Stimulation

The right temporoparietal junction (rTPJ) is a multisensory integration hub that is increasingly utilized as a target of stimulation studies exploring its rich functional network roles and potential clinical applications. While transcranial direct current stimulation (tDCS) is frequently employed in such studies, there is still relatively little known regarding its local and network neurophysiological effects, particularly at important nonmotor sites such as the rTPJ. The current study applied either anodal, cathodal, or sham high-definition tDCS to the rTPJ of 53 healthy participants and used offline EEG to assess the impacts of stimulation on resting state (eyes open and eyes closed) band power and coherence. Temporoparietal and central region delta power was increased after anodal stimulation (the latter trend only), whereas cathodal stimulation increased frontal region delta and theta power. Increased coherence between right and left temporoparietal regions was also observed after anodal stimulation. All significant effects occurred in the eyes open condition. These findings are discussed with reference to domain general and mechanistic theories of rTPJ function. Low-frequency oscillatory activity may exert long-range inhibitory network influences that enable switching between and integration of endogenous/exogenous processing streams. NEW & NOTEWORTHY Through the novel use of high-definition transcranial direct current stimulation (tDCS) and EEG, we provide evidence that both anodal and cathodal stimulation of the right temporoparietal junction selectively modulate slow-wave power and coherence in distributed network regions of known relevance to proposed temporoparietal junction functionality. These results also provide direct evidence of the ability of tDCS to modulate oscillatory activity at a long-range network level, which may have explanatory power in terms of both neurophysiological and behavioral effects.

EEG Event-Related Desynchronization and Event-Related Synchronization

2017 ◽  
Author(s):  
Gert Pfurtscheller ◽  
Fernando Lopes da Silva
Keyword(s):  
Resting State ◽  
Rhythmic Activity ◽  
Oscillatory Activity ◽  
Motor Tasks ◽  
Stroke Patients ◽  
Phase Coupling ◽  
Pressure Oscillations ◽  
Frequency Bands ◽  
Event Related Desynchronization ◽  
Evoked Response Potentials

Event-related desynchronization (ERD) reflects a decrease of oscillatory activity related to internally or externally paced events. The increase of rhythmic activity is called event-related synchronization (ERS). They represent dynamical states of thalamocortical networks associated with cortical information-processing changes. This chapter discusses differences between ERD/ERS and evoked response potentials and methodologies for quantifying ERD/ERS and selecting frequency bands. It covers the interpretation of ERD/ERS in the alpha and beta bands and theta ERS and alpha ERD in behavioral tasks. ERD/ERS in scalp and subdural recordings, in various frequency bands, is discussed. Also presented is the modulation of alpha and beta rhythms by 0.1-Hz oscillations in the resting state and phase-coupling of the latter with slow changes of prefrontal hemodynamic signals (HbO2), blood pressure oscillations, and heart rate interval variations in the resting state and in relation to behavioral motor tasks. Potential uses of ERD-based strategies in stroke patients are discussed.

scholarly journals Resting-State Oscillatory Activity in Autism Spectrum Disorders

2011 ◽  
Vol 42 (9) ◽  
pp. 1884-1894 ◽  
Author(s):  
Lauren Cornew ◽  
Timothy P. L. Roberts ◽  
Lisa Blaskey ◽  
J. Christopher Edgar
Keyword(s):  
Autism Spectrum Disorders ◽  
Resting State ◽  
Autism Spectrum ◽  
Oscillatory Activity ◽  
Spectrum Disorders

Cholinergic modulation of MEG resting-state oscillatory activity in Parkinson’s disease related dementia

2009 ◽  
Vol 120 (5) ◽  
pp. 910-915 ◽  
Author(s):  
J.L.W. Bosboom ◽  
D. Stoffers ◽  
C.J. Stam ◽  
H.W. Berendse ◽  
E.Ch. Wolters
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Resting State ◽  
Oscillatory Activity ◽  
Cholinergic Modulation

scholarly journals Frontoparietal network dynamics impairments in juvenile myoclonic epilepsy revealed by MEG energy landscape

2019 ◽  
Author(s):  
Dominik Krzemiński ◽  
Naoki Masuda ◽  
Khalid Hamandi ◽  
Krish D Singh ◽  
Bethany Routley ◽  
...  
Keyword(s):  
Resting State ◽  
Energy Landscape ◽  
Network Dynamics ◽  
Juvenile Myoclonic Epilepsy ◽  
Myoclonic Epilepsy ◽  
Oscillatory Activity ◽  
Functional Networks ◽  
Occurrence Probability ◽  
Energy Landscapes ◽  
Frontoparietal Network

AbstractJuvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy affecting brain activity. It is unclear to what extent JME leads to abnormal network dynamics across functional networks. Here, we proposed a method to characterise network dynamics in MEG resting-state data, combining a pairwise maximum entropy model (pMEM) and the associated energy landscape analysis. Fifty-two JME patients and healthy controls underwent a resting-state MEG recording session. We fitted the pMEM to the oscillatory power envelopes in theta (4-7 Hz), alpha (8-13 Hz), beta (15-25 Hz) and gamma (30-60 Hz) bands in three source-localised resting-state networks: the frontoparietal network (FPN), the default mode network (DMN), and the sensorimotor network (SMN). The pMEM provided an accurate fit to the MEG oscillatory activity in both patient and control groups, and allowed estimation of the occurrence probability of each network state, with its regional activity and pairwise regional co-activation constrained by empirical data. We used energy values derived from the pMEM to depict an energy landscape of each network, with a higher energy state corresponding to a lower occurrence probability. When comparing the energy landscapes between groups, JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta and gamma-bands. Furthermore, numerical simulation of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of characteristic energy minima was shortened in JME patients. These network alterations were confirmed by a significant leave-one-out classification of individual participants based on a support vector machine employing the energy values of pMEM as features. Our findings suggested that JME patients had altered multi-stability in selective functional networks and frequency bands in the frontoparietal cortices.HighlightsAn energy landscape analysis characterises the dynamics of MEG oscillatory activityPatients with JME exhibit fewer local minima of the energy in their energy landscapesJME affects the network dynamics in the frontoparietal network.Energy landscape measures allow good single-patient classification.

scholarly journals Alterations in resting-state activity and functional connectivity in children with 22q11.2 deletion syndrome

2021 ◽  
Author(s):  
Joanne L Doherty ◽  
Adam C Cunningham ◽  
Samuel JRA Chawner ◽  
Hayley M Moss ◽  
Diana C Dima ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Genetic Risk ◽  
Risk Group ◽  
22Q11.2 Deletion Syndrome ◽  
High Risk Group ◽  
Oscillatory Activity ◽  
Deletion Syndrome ◽  
22Q11.2 Deletion ◽  
Band Activity

Background While genetic risk factors for psychiatric and neurodevelopmental disorders have been identified, the neurobiological route from genetic risk to neuropsychiatric outcome remains unclear. 22q11.2 deletion syndrome (22q11.2DS) is a copy number variant (CNV) syndrome associated with high rates of neurodevelopmental and psychiatric disorders including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD) and schizophrenia. Alterations in neural integration and cortical connectivity have been linked to the spectrum of neuropsychiatric disorders seen in 22q11.2DS and may be a mechanism by which the CNV acts to increase risk. Despite this, few studies have investigated electrophysiological connectivity in this high-risk group. Studying children with 22q11.2DS provides a unique paradigm to identify brain markers of neurodevelopmental impairment and to relate these to underlying biology. Methods Magnetoencephalography (MEG) was used to investigate resting-state cortical oscillatory patterns in 34 children with 22q11.2DS and 25 controls aged 10-17 years old. Oscillatory activity and functional connectivity across six frequency bands were compared between groups. Regression analyses were used to explore the relationships between these measures, IQ and neurodevelopmental symptoms. Results Children with 22q11.2DS had atypical oscillatory activity and functional connectivity across multiple frequency bands (delta, beta and gamma bands). In the 22q11.2DS group, low frequency (alpha band) activity was negatively associated with cognitive ability and positively associated with ASD and ADHD symptoms. Frontal high frequency (gamma band) activity and connectivity were positively associated with ASD and ADHD symptoms, while posterior gamma activity was negatively associated with ASD symptoms. Conclusions These findings highlight that haploinsufficiency at the 22q11.2 locus alters both local and long-range cortical circuitry, which could be a mechanism underlying neurodevelopmental vulnerability in this high risk group.

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