Related Brain Networks Research Articles

P110 Transcranial direct current stimulation of the brain motor area generates a transient increase of small worldnessy in connectivity: An EEG graph theoretical analysis

Introduction Transcranial direct current stimulation (tDCS) is a non-invasive method modulating cortical excitability in a polarity-dependent way. At present, only few studies investigated the effects of tDCS on the modulation of functional connectivity between remote cortical areas. Objective In the present study we aimed to investigate the impact of bipolar tDCS on cortical networks connectivity through graph theoretical analysis. Materials & methods High-density EEG recordings were acquired before and after bipolar anodal, cathodal and sham tDCS applied over the primary motor cortex of the dominant hemisphere in 14 healthy subjects. Results Results showed that, after bipolar anodal tDCS stimulation over the dominant primary motor cortex the related brain network presented a more small-worldnessy, meaning a global tendency to be more random in its functional connections respect to prestimulus condition in both hemispheres. Conclusions Our results suggest that tDCS is able to modulate globally the cortical connectivity of the brain, modifying the underlying functional organization via complex pattern of direct and indirect cortical activations or inhibitions of the stimulated networks, which might be related to changes in synaptic efficiency of the motor network and related brain areas.

Brain Network Mechanisms Underlying Motor Enhancement by Transcranial Entrainment of Gamma Oscillations.

Recent research has suggested a causal role for gamma oscillations during movement preparation and execution. Here we combine transcranial alternating current stimulation (tACS) with functional magnetic resonance imaging (fMRI) to identify the neural mechanisms that accompany motor performance enhancements triggered by gamma tACS over the primary motor cortex. We show that the tACS-induced motor performance enhancements correlate with changed neural activity in the stimulated area and modulate, in a frequency- and task-specific manner, the neural activity in the dorsomedial prefrontal cortex. This suggests a regulatory role of this region for motor control. More generally, we show that combined tACS-fMRI can elucidate the causal link between brain oscillations, neural systems, and behavior.

Stimulus Dependent Dynamic Reorganization of the Human Face Processing Network.

Using the "face inversion effect", a hallmark of face perception, we examined network mechanisms supporting face representation by tracking functional magnetic resonance imaging (fMRI) stimulus-dependent dynamic functional connectivity within and between brain networks associated with the processing of upright and inverted faces. We developed a novel approach adapting the general linear model (GLM) framework classically used for univariate fMRI analysis to capture stimulus-dependent fMRI dynamic connectivity of the face network. We show that under the face inversion manipulation, the face and non-face networks have complementary roles that are evident in their stimulus-dependent dynamic connectivity patterns as assessed by network decomposition into components or communities. Moreover, we show that connectivity patterns are associated with the behavioral face inversion effect. Thus, we establish "a network-level signature" of the face inversion effect and demonstrate how a simple physical transformation of the face stimulus induces a dramatic functional reorganization across related brain networks. Finally, we suggest that the dynamic GLM network analysis approach, developed here for the face network, provides a general framework for modeling the dynamics of blocked stimulus-dependent connectivity experimental designs and hence can be applied to a host of neuroimaging studies.

Organizational topology of brain and its relationship to ADHD in adolescents with d‐transposition of the great arteries

ObjectiveLittle is currently known about the impact of congenital heart disease (CHD) on the organization of large‐scale brain networks in relation to neurobehavioral outcome. We investigated whether CHD might impact ADHD symptoms via changes in brain structural network topology in a cohort of adolescents with d‐transposition of the great arteries (d‐TGA) repaired with the arterial switch operation in early infancy and referent subjects. We also explored whether these effects might be modified by apolipoprotein E (APOE) genotype, as the APOE ε2 allele has been associated with worse neurodevelopmental outcomes after repair of d‐TGA in infancy.MethodsWe applied graph analysis techniques to diffusion tensor imaging (DTI) data obtained from 47 d‐TGA adolescents and 29 healthy referents to construct measures of structural topology at the global and regional levels. We developed statistical mediation models revealing the respective contributions of d‐TGA, APOE genotype, and structural network topology on ADHD outcome as measured by the Connors ADHD/DSM‐IV Scales (CADS).ResultsChanges in overall network connectivity, integration, and segregation mediated worse ADHD outcomes in d‐TGA patients compared to healthy referents; these changes were predominantly in the left and right intrahemispheric regional subnetworks. Exploratory analysis revealed that network topology also mediated detrimental effects of the APOE ε4 allele but improved neurobehavioral outcomes for the APOE ε2 allele.ConclusionOur results suggest that disruption of organization of large‐scale networks may contribute to neurobehavioral dysfunction in adolescents with CHD and that this effect may interact with APOE genotype.

DHA Status Associated with Cognitive Performance and Differential Patterns of Brain Activation in School Age Children

We assessed the associations between DHA intake (food frequency questionnaire) and DHA status [red blood cell (RBC)‐DHA/docosapentaenoic acid (DPA, n‐6) ratio] with cognitive performance [Kaufman Assessment Battery for Children (KABC‐III)] and brain functioning [measured by functional magnetic resonance imaging (fMRI)] in healthy children ~6 years of age (n=62). fMRI scanning of an n‐back numbers task was conducted, consisting of control and 1‐back task conditions (96 × 96 oblique axial EPI, 3mm thickness, no gap, TR/TE = 3000/30ms). Using Behavior Partial Least Squares (bPLS), the task‐specific correlation matrix between behavior and brain activity was computed and then decomposed using singular value decomposition. This yielded condition related brain network activation patterns, which were used to assess the association between DHA status and brain functioning. Median (interquartile range) DHA intake and RBC‐DHA/DPA were 76 (40–127) mg/d and 8.9 (6.0–12), respectively. DHA intake was positively correlated with: RBC‐DHA/DPA (r=0.62, p<0.0001), KABC indicators of short‐term memory (Sequential; r=0.29, p=0.03) and general mental processing ability (Mental Performance Index; r=0.34, p=0.018); RBC‐DHA/DPA was positively correlated with the KABC Sequential (r=0.26, p=0.042). The bPLS analysis (n=34 with acceptably low head motion) produced 2 latent variables (LV), which represent underlying condition related brain network activation patterns. LV1 showed activations in the Right (R) superior frontal, R middle temporal, Left (L) middle frontal gyri and the R insula with concomitant deactivations in the R cerebellum (lobules VI and IX) and the R lateral occipital gyrus that were negatively correlated with RBC‐DHA/DPA for both the control [r (95% confidence interval (CI) = −0.39 (−0.66, −0.05)] and 1‐back [r (95% CI) = −0.36 (−0.67, −0.12)] conditions. Therefore, activations were more activated with lower RBC‐DHA/DPA, while deactivations were more deactivated with higher RBC‐DHA/DPA. LV2 showed activations in the R superior temporal gyrus and R anterior cingulate with concomitant deactivations in the R hippocampus, L fusiform, and bilateral precuneus and post‐central gyri that were negatively correlated with the control condition [r (95% CI) = −0.46 (−0.71, −0.17)] and positively correlated with the 1‐back condition [r (95% CI) = 0.43 (0.06, 0.70)]. Therefore, activations were more activated with lower RBC‐DHA/DPA in the control condition, while the same activations were more activated with higher RBC‐DHA/DPA in the 1‐back condition. Similarly, deactivated regions showed more deactivation with higher RBC‐DHA/DPA in the control condition and more deactivation with lower RBC‐DHA/DPA in the 1‐back condition. In sum, DHA intake was positively associated with some aspects of cognitive performance; DHA status was positively associated with some aspects of cognitive performance as well as differential brain activation patterns.Support or Funding InformationFunded by Nestec, S.A.

Cortical Dynamic Causality Network for Auditory-Motor Tasks

Motor preparation and execution require the interactions of a large-scale brain network, while the study of the dynamic changes of their interactions could uncover the underlying neural mechanism of the corresponding information processing. This dynamic analysis requires high temporal resolution of the recorded signals. Electroencephalogram (EEG) with high temporal resolution has been widely used in related studies. However, studies based on scalp EEG always lead to distorted results, due to scalp volume conduction, compared with that of cortically recorded signals. In the current study, the dynamic networks of motor preparation and execution are investigated using Go/No-go tasks performed with the left/right hand. In the analysis, the EEG source localization and dynamic causal model are combined together to investigate the neural processes of motor preparation and execution. The results show that similar network patterns with nodes distributed in the bilateral occipital lobe, bilateral temporal lobe, bilateral dorsolateral prefrontal cortex, and contralateral supplementary motor area could be revealed for both the Go and No-go tasks. Statistical testing further indicates that stronger couplings with the supplementary motor area could be found in Go and right-hand response tasks compared with No-go and left-hand response tasks, respectively. The findings in the current study demonstrate that the information exchange within the motor related brain networks plays an important role for motor related functions, i.e., the different motor functions may have the different information exchange and processing network patterns.

Brain network changes in relation to beginning apathy in PD patients

Introduction: Brain frequency and network analyses are known to differentiate between disease stages in Parkinson’s disease (PD) and are possible biomarkers. They correlate with cognitive decline. Little is known about changes in brain networks in relation to apathy.

Altered brain network centrality in depressed Parkinson's disease patients.

Depression is a relatively common and serious nonmotor symptom of Parkinson's disease (PD), which reduces the quality of patients' life. Although disturbances in some related brain networks have been reported, the pathophysiology of depression in PD is still unclear. Here, we aim to investigate whole-brain functional connectivity patterns in depressed PD patients. We recruited 17 PD patients diagnosed with major depressive disorder, 17 PD patients without depression, and 17 healthy control subjects. Resting-state functional MRI and eigenvector centrality mapping were used to identify functional connectivity alterations among these groups. Results showed that depressed PD patients had decreased functional connectivity in the left dorsolateral prefrontal cortex and right superior temporal gyrus and increased functional connectivity in the right posterior cingulate cortex, compared to nondepressed patients. In addition, there was a significant negative correlation between functional connectivity and depression scores in the posterior cingulate cortex. This study suggests that functional connectivity changes in certain nodes of brain networks might contribute to depression in patients with PD.

Epileptogenic focus localization: a new approach.

Epilepsy is one of the most important chronic neurological disorders worldwide affecting more than 50 million people of all ages. Among these, almost 20% of epilepsy cases are uncontrollable and have an unknown source of this abnormal electrical activity. Present techniques for the detection of epileptogenic foci include electroencephalography (EEG), positron emission tomography, and multimodal EEG/functional magnetic resonance imaging (fMRI), all with limitations in terms of spatial and temporal resolutions. In order to overcome some of those limitations a novel approach using fMRI alone was developed based on the hypotheses that the epileptogenic focus shows Blood Oxygen Level Dependent (BOLD) temporal profiles distinct from the remaining brain parenchyma during interictal activity and that the epileptogenic focus BOLD signals show lower complexity than healthy parenchyma. In this novel approach, bi-dimensional temporal clustering analysis, a data-driven technique, was used to identify brain regions with similar temporal profiles. Then, the BOLD signals of these regions were assessed regarding complexity using detrended fluctuation analysis and also using a modified multiscale entropy algorithm in order to identify which of those regions corresponded to epileptogenic tissue. In order to demonstrate the applicability of the developed method three epileptic patients were analyzed comprising two types of epilepsy: unilateral and bilateral temporal lobe epilepsies. The results showed that this method is able to detect the brain regions associated with epileptogenic tissue. The results also showed that the epileptogenic focus influences the dynamics of related brain networks. This could be a key factor in the applicability of this method to other epilepsy cases. Finally, new perspectives are envisioned concerning the use of this method in the medical care of epilepsy. In particular, by improving this method using simultaneous structural, functional, and metabolic information with hybrid MRI-PET scanners for the validation of epileptogenic focus.

Reality TV and vicarious embarrassment: An fMRI study

BackgroundVicarious embarrassment (VE) is an emotion triggered by the observation of others' pratfalls or social norm violations. Several explanatory approaches have been suggested to explain the source of this phenomenon, including perspective taking abilities or ingroup identification. Knowledge about its biological bases, however, is scarce. To gain a better understanding, the present study investigated neural activation patterns in response to video clips from reality TV shows. Reality TV is well known for presenting social norm violations, flaws and pratfalls of its protagonists in real life situations thereby qualifying as an ecological valid trigger for VE. MethodsN=60 healthy participants viewed stand stills from previously watched video clips taken from German reality TV-shows while undergoing functional magnetic resonance imaging. The clips were preselected for high versus low VE content in a pilot study. Besides the investigation of differences in brain activation elicited by VE versus control stand stills (blocked design contrast), we performed additional exploratory functional connectivity analyses (psychophysiological interaction; PPI) to detect VE related brain networks. ResultsCompared to the low VE condition, participants in the high VE condition showed a higher activation in the middle temporal gyrus, the supramarginal gyrus, the right inferior frontal gyrus and the gyrus rectus. Functional connectivity analyses confirmed increased connectivity of these regions with the anterior cingulate in the VE condition. Moreover, self-ratings of VE and brain activity were correlated positively. ConclusionReality TV formats with high VE content activate brain regions associated with Theory of Mind, but also with empathic concern and social identity. Therefore, our results support the idea that the ability to put oneself in other person's shoes is a major prerequisite for VE.

A Proposed Neurological Interpretation of Language Evolution.

Since the very beginning of the aphasia history it has been well established that there are two major aphasic syndromes (Wernicke's-type and Broca's-type aphasia); each one of them is related to the disturbance at a specific linguistic level (lexical/semantic and grammatical) and associated with a particular brain damage localization (temporal and frontal-subcortical). It is proposed that three stages in language evolution could be distinguished: (a) primitive communication systems similar to those observed in other animals, including nonhuman primates; (b) initial communication systems using sound combinations (lexicon) but without relationships among the elements (grammar); and (c) advanced communication systems including word-combinations (grammar). It is proposed that grammar probably originated from the internal representation of actions, resulting in the creation of verbs; this is an ability that depends on the so-called Broca's area and related brain networks. It is suggested that grammar is the basic ability for the development of so-called metacognitive executive functions. It is concluded that while the lexical/semantic language system (vocabulary) probably appeared during human evolution long before the contemporary man (Homo sapiens sapiens), the grammatical language historically represents a recent acquisition and is correlated with the development of complex cognition (metacognitive executive functions).

Cerebellum Involvement in Obsessive-Compulsive Disorder related Brain Network Model

Conventional obsessive-compulsive disorder related brain network model relies mainly on cortico-striato-thalamo-cortical areas. However, recent findings consistently point cerebellar structural and functional differences in obsessive-compulsive disorder patients compared to healthy controls. Here we briefly reviewed these studies and argued that cerebellum should be involved in obsessive-compulsive disorder related brain network model for a better understanding of the nature of this disorder.

Changes of functional connectivity in the left frontoparietal network following aphasic stroke.

Language is an essential higher cognitive function supported by large-scale brain networks. In this study, we investigated functional connectivity changes in the left frontoparietal network (LFPN), a language-cognition related brain network in aphasic patients. We enrolled 13 aphasic patients who had undergone a stroke in the left hemisphere and age-, gender-, educational level-matched controls and analyzed the data by integrating independent component analysis (ICA) with a network connectivity analysis method. Resting state functional magnetic resonance imaging (fMRI) and clinical evaluation of language function were assessed at two stages: 1 and 2 months after stroke onset. We found reduced functional connectivity between the LFPN and the right middle frontal cortex, medial frontal cortex, and right inferior frontal cortex in aphasic patients as compared to controls. Correlation analysis showed that stronger functional connectivity between the LFPN and the right middle frontal cortex and medial frontal cortex coincided with more preserved language comprehension ability after stroke. Network connectivity analysis showed reduced LFPN connectivity as indicated by the mean network connectivity index of key regions in the LFPN of aphasic patients. The decreased LFPN connectivity in stroke patients was significantly associated with the impairment of language function in their comprehension ability. We also found significant association between recovery of comprehension ability and the mean changes in intrinsic LFPN connectivity. Our findings suggest that brain lesions may influence language comprehension by altering functional connectivity between regions and that the patterns of abnormal functional connectivity may contribute to the recovery of language deficits.

Mapping the Effect of the Apolipoprotein E Genotype on 4-Year Atrophy Rates in an Alzheimer Disease–related Brain Network

To determine the effect of the apolipoprotein E (APOE) genotype on atrophy rates of specific brain gray matter regions hypothesized to be key components of cognitive networks disrupted in Alzheimer disease. The Alzheimer's Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All subjects and their legal representatives gave written informed consent prior to data collection. The authors analyzed data from 237 subjects (mean age, 79.9 years; 40% female) with mild cognitive impairment (MCI) in the ADNI database and assessed the effect of the APOE ε4 and ε2 alleles on regional brain atrophy rates over a 12-48-month period. Brain regions were selected a priori: 15 experimental and five control regions were included. Regional atrophy rates were derived by using a fully automated algorithm applied to T1-weighted magnetic resonance (MR) imaging data. Analysis consisted of mixed-effects linear regression with repeated measures; results were adjusted for multiple testing with Bonferroni correction. Thirteen of 15 experimental regions showed a significant effect of ε4 for higher atrophy rates (P < .001 for all). Cohen d values ranged from 0.26 to 0.42, with the largest effects seen in the amygdalae and hippocampi. The transverse temporal cortex showed a trend (P = .02, but did not survive Bonferroni correction) for a protective effect (Cohen d value = 0.15) of ε2. No control region showed an APOE effect. The APOE ε4 allele is associated with accelerated rates of atrophy in 13 distinct brain regions in limbic and neocortical areas. This suggests the possibility of a genotype-specific network of related brain regions that undergo faster atrophy in MCI and potentially contribute to cognitive decline. Online supplemental material is available for this article.

Key Regions of the Cerebral Network are Altered after Electroacupuncture at the Baihui (GV20) and Yintang Acupuncture Points in Healthy Volunteers: An Analysis Based on Resting fcMRI

To identify the key cerebral functional region affected by acupuncture point needling by examining cerebral networks using functional connectivity MRI (fcMRI) and analysing changes in the key regions of these brain networks at different time points after needle removal. Twelve healthy volunteers received 30 min of electroacupuncture (EA) at the Baihui (GV20) and Yintang acupuncture points and then underwent two fMRI scans, one each at 5 and 15 min after needle removal. Related brain networks were analysed centred at different 'seeds', centres which functionally connect the other cerebral regions in an organised network, such as the anterior frontal lobe, anterior cingulate gyrus, parahippocampal gyrus, amygdala, hypothalamus, head of the caudate nucleus and anterior lobe of the cerebellum. Networks were analysed based on the resting cerebral functional connection, and the differences in the activities of the brain networks between the two time points were compared. At 5 min after needle removal, 12 brain functional regions were involved in organising the network centred at the caudate nucleus 'seed.' This number was greater than the number of related brain networks centred at the other 'seeds'. At 15 min after needle removal, 15 and 14 brain functional regions were involved in organised networks centred at the parahippocampal and hypothalamus 'seeds', respectively; these numbers were greater than the numbers of other related brain networks centred at the other 'seeds'. A brain network composed of a large number of cerebral functional regions was found after EA at GV20 and Yintang in healthy volunteers. The key brain 'seed' supporting the largest brain network changed between 5 and 15 min after needle removal.

Working Memory Related Brain Network Connectivity in Individuals with Schizophrenia and Their Siblings

A growing number of studies have reported altered functional connectivity in schizophrenia during putatively “task-free” states and during the performance of cognitive tasks. However, there have been few systematic examinations of functional connectivity in schizophrenia across rest and different task states to assess the degree to which altered functional connectivity reflects a stable characteristic or whether connectivity changes vary as a function of task demands. We assessed functional connectivity during rest and during three working memory loads of an N-back task (0-back, 1-back, 2-back) among: (1) individuals with schizophrenia (N = 19); (2) the siblings of individuals with schizophrenia (N = 28); (3) healthy controls (N = 10); and (4) the siblings of healthy controls (N = 17). We examined connectivity within and between four brain networks: (1) frontal–parietal (FP); (2) cingulo-opercular (CO); (3) cerebellar (CER); and (4) default mode (DMN). In terms of within-network connectivity, we found that connectivity within the DMN and FP increased significantly between resting state and 0-back, while connectivity within the CO and CER decreased significantly between resting state and 0-back. Additionally, we found that connectivity within both the DMN and FP was further modulated by memory load. In terms of between network connectivity, we found that the DMN became significantly more “anti-correlated” with the FP, CO, and CER networks during 0-back as compared to rest, and that connectivity between the FP and both CO and CER networks increased with memory load. Individuals with schizophrenia and their siblings showed consistent reductions in connectivity between both the FP and CO networks with the CER network, a finding that was similar in magnitude across rest and all levels of working memory load. These findings are consistent with the hypothesis that altered functional connectivity in schizophrenia reflects a stable characteristic that is present across cognitive states.

Functional Cliques in the Amygdala and Related Brain Networks Driven by Fear Assessment Acquired During Movie Viewing

One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

Implicit Artificial Syntax Processing: Genes, Preference, and Bounded Recursion

The first objective of this study was to compare the brain network engaged by preference classification and the standard grammaticality classification after implicit artificial syntax acquisition by re-analyzing previously reported event-related fMRI data. The results show that preference and grammaticality classification engage virtually identical brain networks, including Broca’s region, consistent with previous behavioral findings. Moreover, the results showed that the effects related to artificial syntax in Broca’s region were essentially the same when masked with variability related to natural syntax processing in the same participants. The second objective was to explore CNTNAP2-related effects in implicit artificial syntax learning by analyzing behavioral and event-related fMRI data from a subsample. The CNTNAP2 gene has been linked to specific language impairment and is con-trolled by the FOXP2 transcription factor. CNTNAP2 is expressed in language related brain networks in the developing human brain and the FOXP2–CNTNAP2 pathway provides a mechanistic link between clinically distinct syndromes involving disrupted language. Finally, we discuss the implication of taking natural language to be a neurobiological system in terms of bounded recursion and suggest that the left inferior frontal region is a generic on-line sequence processor that unifies information from various sources in an incremental and recursive manner.

Learning and Memory: While You Rest, Your Brain Keeps Working

A recent study shows that brain activity recorded while the human subject is at 'rest' is significantly affected by a prior learning episode. These results suggest that understanding resting brain activity may be critical to understanding how humans learn from experience.

The Resting Human Brain and Motor Learning

SummaryFunctionally related brain networks are engaged even in the absence of an overt behavior. The role of this resting state activity, evident as low-frequency fluctuations of BOLD (see [1] for review, [2–4]) or electrical [5, 6] signals, is unclear. Two major proposals are that resting state activity supports introspective thought or supports responses to future events [7]. An alternative perspective is that the resting brain actively and selectively processes previous experiences [8]. Here we show that motor learning can modulate subsequent activity within resting networks. BOLD signal was recorded during rest periods before and after an 11 min visuomotor training session. Motor learning but not motor performance modulated a fronto-parietal resting state network (RSN). Along with the fronto-parietal network, a cerebellar network not previously reported as an RSN was also specifically altered by learning. Both of these networks are engaged during learning of similar visuomotor tasks [9–22]. Thus, we provide the first description of the modulation of specific RSNs by prior learning—but not by prior performance—revealing a novel connection between the neuroplastic mechanisms of learning and resting state activity. Our approach may provide a powerful tool for exploration of the systems involved in memory consolidation.