Attention networks in adolescent anorexia nervosa.

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Weinbach, Noam; Sher, Helene; Lock, James D; Henik, Avishai

2018-03-01

Anorexia nervosa (AN) usually develops during adolescence when considerable structural and functional brain changes are taking place. Neurocognitive inefficiencies have been consistently found in adults with enduring AN and were suggested to play a role in maintaining the disorder. However, such findings are inconsistent in children and adolescents with AN. The current study conducted a comprehensive assessment of attention networks in adolescents with AN who were not severely underweight during the study using an approach that permits disentangling independent components of attention. Twenty partially weight-restored adolescents with AN (AN-WR) and 24 healthy adolescents performed the Attention Network Test which assesses the efficiency of three main attention networks-executive control, orienting, and alerting. The results revealed abnormal function in the executive control network among adolescents with AN-WR. Specifically, adolescents with AN-WR demonstrated superior ability to suppress attention to task-irrelevant information while focusing on a central task. Moreover, the alerting network modulated this ability. No difference was found between the groups in the speed of orienting attention, but reorienting attention to a target resulted in higher error rates in the AN-WR group. The findings suggest that adolescents with AN have attentional abnormalities that cannot be explained by a state of starvation. These attentional dysregulations may underlie clinical phenotypes of the disorder such as increased attention of details.

Irrelevant stimulus processing in ADHD: catecholamine dynamics and attentional networks

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Francisco eAboitiz

2014-03-01

Full Text Available A cardinal symptom of Attenion Deficit and Hyperactivity Disorder (ADHD is a general distractibility where children and adults shift their attentional focus to stimuli that are irrelevant to the ongoing behavior. This has been attributed to a deficit in dopaminergic signaling in cortico-striatal networks that regulate goal-directed behavior. Furthermore, recent imaging evidence points to an impairment of large scale, antagonistic brain networks that normally contribute to attentional engagement and disengagement, such as the task-positive networks and the Default Mode Network (DMN. Related networks are the ventral attentional network (VAN involved in attentional shifting, and the salience network (SN related to task expectancy. Here we discuss the tonic-phasic dynamics of catecholaminergic signaling in the brain, and attempt to provide a link between this and the activities of the large-scale cortical networks that regulate behavior. More specifically, we propose that a disbalance of tonic catecholamine levels during task performance produce an emphasis of phasic signaling and increased excitability of the VAN, yielding distractibility symptoms. Likewise, immaturity of the SN may relate to abnormal tonic signaling and an incapacity to build up a proper executive system during task performance. We discuss different lines of evidence including pharmacology, brain imaging and electrophysiology, that are consistent with our proposal. Finally, restoring the pharmacodynamics of catecholaminergic signaling seems crucial to alleviate ADHD symptoms; however, the possibility is open to explore cognitive rehabilitation strategies to top-down modulate network dynamics compensating the pharmacological deficits.

Antecedent acute cycling exercise affects attention control: an ERP study using attention network test

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Yu-Kai eChang

2015-04-01

Full Text Available The purpose of this study was to investigate the after-effects of an acute bout of moderate-intensity aerobic cycling exercise on neuroelectric and behavioral indices of efficiency of three attentional networks: alerting, orienting, and executive (conflict control. Thirty young, highly fit amateur basketball players performed a multifunctional attentional reaction time task, the attention network test (ANT, with a two-group randomized experimental design after an acute bout of moderate-intensity spinning wheel exercise or without antecedent exercise. The ANT combined warning signals prior to targets, spatial cueing of potential target locations and target stimuli surrounded by congruent or incongruent flankers, which were provided to assess three attentional networks. Event-related brain potentials and task performance were measured during the ANT. Exercise resulted in a larger P3 amplitude in the alerting and executive control subtasks across frontal, central and parietal midline sites that was paralleled by an enhanced reaction speed only on trials with incongruent flankers of the executive control network. The P3 latency and response accuracy were not affected by exercise. These findings suggest that after spinning, more resources are allocated to task-relevant stimuli in tasks that rely on the alerting and executive control networks. However, the improvement in performance was observed in only the executively challenging conflict condition, suggesting that whether the brain resources that are rendered available immediately after acute exercise translate into better attention performance depends on the cognitive task complexity.

Functional Connectivity of the Dorsal Attention Network Predicts Selective Attention in 4-7 year-old Girls.

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Rohr, Christiane S; Vinette, Sarah A; Parsons, Kari A L; Cho, Ivy Y K; Dimond, Dennis; Benischek, Alina; Lebel, Catherine; Dewey, Deborah; Bray, Signe

2017-09-01

Early childhood is a period of profound neural development and remodeling during which attention skills undergo rapid maturation. Attention networks have been extensively studied in the adult brain, yet relatively little is known about changes in early childhood, and their relation to cognitive development. We investigated the association between age and functional connectivity (FC) within the dorsal attention network (DAN) and the association between FC and attention skills in early childhood. Functional magnetic resonance imaging data was collected during passive viewing in 44 typically developing female children between 4 and 7 years whose sustained, selective, and executive attention skills were assessed. FC of the intraparietal sulcus (IPS) and the frontal eye fields (FEF) was computed across the entire brain and regressed against age. Age was positively associated with FC between core nodes of the DAN, the IPS and the FEF, and negatively associated with FC between the DAN and regions of the default-mode network. Further, controlling for age, FC between the IPS and FEF was significantly associated with selective attention. These findings add to our understanding of early childhood development of attention networks and suggest that greater FC within the DAN is associated with better selective attention skills. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Whole-brain structural topology in adult attention-deficit/hyperactivity disorder: Preserved global – disturbed local network organization

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Justina Sidlauskaite

2015-01-01

Full Text Available Prior studies demonstrate altered organization of functional brain networks in attention-deficit/hyperactivity disorder (ADHD. However, the structural underpinnings of these functional disturbances are poorly understood. In the current study, we applied a graph-theoretic approach to whole-brain diffusion magnetic resonance imaging data to investigate the organization of structural brain networks in adults with ADHD and unaffected controls using deterministic fiber tractography. Groups did not differ in terms of global network metrics — small-worldness, global efficiency and clustering coefficient. However, there were widespread ADHD-related effects at the nodal level in relation to local efficiency and clustering. The affected nodes included superior occipital, supramarginal, superior temporal, inferior parietal, angular and inferior frontal gyri, as well as putamen, thalamus and posterior cerebellum. Lower local efficiency of left superior temporal and supramarginal gyri was associated with higher ADHD symptom scores. Also greater local clustering of right putamen and lower local clustering of left supramarginal gyrus correlated with ADHD symptom severity. Overall, the findings indicate preserved global but altered local network organization in adult ADHD implicating regions underpinning putative ADHD-related neuropsychological deficits.

Cortical networks involved in visual awareness independent of visual attention.

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Webb, Taylor W; Igelström, Kajsa M; Schurger, Aaron; Graziano, Michael S A

2016-11-29

It is now well established that visual attention, as measured with standard spatial attention tasks, and visual awareness, as measured by report, can be dissociated. It is possible to attend to a stimulus with no reported awareness of the stimulus. We used a behavioral paradigm in which people were aware of a stimulus in one condition and unaware of it in another condition, but the stimulus drew a similar amount of spatial attention in both conditions. The paradigm allowed us to test for brain regions active in association with awareness independent of level of attention. Participants performed the task in an MRI scanner. We looked for brain regions that were more active in the aware than the unaware trials. The largest cluster of activity was obtained in the temporoparietal junction (TPJ) bilaterally. Local independent component analysis (ICA) revealed that this activity contained three distinct, but overlapping, components: a bilateral, anterior component; a left dorsal component; and a right dorsal component. These components had brain-wide functional connectivity that partially overlapped the ventral attention network and the frontoparietal control network. In contrast, no significant activity in association with awareness was found in the banks of the intraparietal sulcus, a region connected to the dorsal attention network and traditionally associated with attention control. These results show the importance of separating awareness and attention when testing for cortical substrates. They are also consistent with a recent proposal that awareness is associated with ventral attention areas, especially in the TPJ.

Can you hear me now? Musical training shapes functional brain networks for selective auditory attention and hearing speech in noise

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Dana L Strait

2011-06-01

Full Text Available Even in the quietest of rooms, our senses are perpetually inundated by a barrage of sounds, requiring the auditory system to adapt to a variety of listening conditions in order to extract signals of interest (e.g., one speaker’s voice amidst others. Brain networks that promote selective attention are thought to sharpen the neural encoding of a target signal, suppressing competing sounds and enhancing perceptual performance. Here, we ask: does musical training benefit cortical mechanisms that underlie selective attention to speech? To answer this question, we assessed the impact of selective auditory attention on cortical auditory-evoked response variability in musicians and nonmusicians. Outcomes indicate strengthened brain networks for selective auditory attention in musicians in that musicians but not nonmusicians demonstrate decreased prefrontal response variability with auditory attention. Results are interpreted in the context of previous work from our laboratory documenting perceptual and subcortical advantages in musicians for the hearing and neural encoding of speech in background noise. Musicians’ neural proficiency for selectively engaging and sustaining auditory attention to language indicates a potential benefit of music for auditory training. Given the importance of auditory attention for the development of language-related skills, musical training may aid in the prevention, habilitation and remediation of children with a wide range of attention-based language and learning impairments.

Infant joint attention, neural networks and social cognition.

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Mundy, Peter; Jarrold, William

2010-01-01

Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). In this paper we argue that a neural network approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one's own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one's own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. We also propose that with development, joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition. Copyright © 2010 Elsevier Ltd. All rights reserved.

Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial.

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Lin, Hsiang-Yuan; Gau, Susan Shur-Fen

2015-09-16

Although atomoxetine demonstrates efficacy in individuals with attention-deficit hyperactivity disorder, its treatment effects on brain resting-state functional connectivity remain unknown. Therefore, we aimed to investigate major brain functional networks in medication-naïve adults with attention-deficit hyperactivity disorder and the efficacy of atomoxetine treatment on resting-state functional connectivity. After collecting baseline resting-state functional MRI scans from 24 adults with attention-deficit hyperactivity disorder (aged 18-52 years) and 24 healthy controls (matched in demographic characteristics), the participants with attention-deficit hyperactivity disorder were randomly assigned to atomoxetine (n=12) and placebo (n=12) arms in an 8-week, double-blind, placebo-controlled trial. The primary outcome was functional connectivity assessed by a resting-state functional MRI. Seed-based functional connectivity was calculated and compared for the affective, attention, default, and cognitive control networks. At baseline, we found atypical cross talk between the default, cognitive control, and dorsal attention networks and hypoconnectivity within the dorsal attention and default networks in adults with attention-deficit hyperactivity disorder. Our first-ever placebo-controlled clinical trial incorporating resting-state functional MRI showed that treatment with atomoxetine strengthened an anticorrelated relationship between the default and task-positive networks and modulated all major brain networks. The strengthened anticorrelations were associated with improving clinical symptoms in the atomoxetine-treated adults. Our results support the idea that atypical default mode network task-positive network interaction plays an important role in the pathophysiology of adult attention-deficit hyperactivity disorder. Strengthening this atypical relationship following atomoxetine treatment suggests an important pathway to treat attention-deficit hyperactivity

Uncertainty, reward, and attention in the Bayesian brain

DEFF Research Database (Denmark)

Whiteley, Louise Emma

2008-01-01

results suggest that value a¿ects a fronto-striatal action selection network rather than directly impacting on sensory processing. Finally, we consider a major theoretical problem – the demonstrations of optimality that dominate the ¿eld have been obtained in tasks with a small number of objects...... in the focus of attention. When faced instead with a complex scene, the brain can’t be Bayes-optimal everywhere. We suggest that a general limitation on the representation of complex posteriors causes the brain to make approximations, which are then locally re¿ned by attention. This framework extends ideas...... of attention as Bayesian prior, and uni¿es apparently disparate attentional ‘bottlenecks’. We present simulations of three key paradigms, and discuss how such modelling could be extended to more detailed, neurally inspired settings. Broadening the Bayesian picture of perception and strengthening its connection...

Connectomic disturbances in attention-deficit/hyperactivity disorder: a whole-brain tractography analysis.

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Hong, Soon-Beom; Zalesky, Andrew; Fornito, Alex; Park, Subin; Yang, Young-Hui; Park, Min-Hyeon; Song, In-Chan; Sohn, Chul-Ho; Shin, Min-Sup; Kim, Bung-Nyun; Cho, Soo-Churl; Han, Doug Hyun; Cheong, Jae Hoon; Kim, Jae-Won

2014-10-15

Few studies have sought to identify, in a regionally unbiased way, the precise cortical and subcortical regions that are affected by white matter abnormalities in attention-deficit/hyperactivity disorder (ADHD). This study aimed to derive a comprehensive, whole-brain characterization of connectomic disturbances in ADHD. Using diffusion tensor imaging, whole-brain tractography, and an imaging connectomics approach, we characterized altered white matter connectivity in 71 children and adolescents with ADHD compared with 26 healthy control subjects. White matter differences were further delineated between patients with (n = 40) and without (n = 26) the predominantly hyperactive/impulsive subtype of ADHD. A significant network comprising 25 distinct fiber bundles linking 23 different brain regions spanning frontal, striatal, and cerebellar brain regions showed altered white matter structure in ADHD patients (p attentional disturbances. Attention-deficit/hyperactivity disorder subtypes were differentiated by a right-lateralized network (p attentional performance underscore the functional importance of these connectomic disturbances for the clinical phenotype of ADHD. A distributed pattern of white matter microstructural integrity separately involving frontal, striatal, and cerebellar brain regions, rather than direct frontostriatal connectivity, appears to be disrupted in children and adolescents with ADHD. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

X-Chromosome Effects on Attention Networks: Insights from Imaging Resting-State Networks in Turner Syndrome.

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Green, Tamar; Saggar, Manish; Ishak, Alexandra; Hong, David S; Reiss, Allan L

2017-07-18

Attention deficit hyperactivity disorder (ADHD) is strongly affected by sex, but sex chromosomes' effect on brain attention networks and cognition are difficult to examine in humans. This is due to significant etiologic heterogeneity among diagnosed individuals. In contrast, individuals with Turner syndrome (TS), who have substantially increased risk for ADHD symptoms, share a common genetic risk factor related to the absence of the X-chromosome, thus serving as a more homogeneous genetic model. Resting-state functional MRI was employed to examine differences in attention networks between girls with TS (n = 40) and age- sex- and Tanner-matched controls (n = 33). We compared groups on resting-state functional connectivity measures from data-driven independent components analysis (ICA) and hypothesis-based seed analysis. Using ICA, reduced connectivity was observed in both frontoparietal and dorsal attention networks. Similarly, using seeds in the bilateral intraparietal sulcus (IPS), reduced connectivity was observed between IPS and frontal and cerebellar regions. Finally, we observed a brain-behavior correlation between IPS-cerebellar connectivity and cognitive attention measures. These findings indicate that X-monosomy contributes affects to attention networks and cognitive dysfunction that might increase risk for ADHD. Our findings not only have clinical relevance for girls with TS, but might also serve as a biological marker in future research examining the effects of the intervention that targets attention skills. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Imaging functional and structural brain connectomics in attention-deficit/hyperactivity disorder.

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Cao, Miao; Shu, Ni; Cao, Qingjiu; Wang, Yufeng; He, Yong

2014-12-01

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopment disorders in childhood. Clinically, the core symptoms of this disorder include inattention, hyperactivity, and impulsivity. Previous studies have documented that these behavior deficits in ADHD children are associated with not only regional brain abnormalities but also changes in functional and structural connectivity among regions. In the past several years, our understanding of how ADHD affects the brain's connectivity has been greatly advanced by mapping topological alterations of large-scale brain networks (i.e., connectomes) using noninvasive neurophysiological and neuroimaging techniques (e.g., electroencephalograph, functional MRI, and diffusion MRI) in combination with graph theoretical approaches. In this review, we summarize the recent progresses of functional and structural brain connectomics in ADHD, focusing on graphic analysis of large-scale brain systems. Convergent evidence suggests that children with ADHD had abnormal small-world properties in both functional and structural brain networks characterized by higher local clustering and lower global integrity, suggesting a disorder-related shift of network topology toward regular configurations. Moreover, ADHD children showed the redistribution of regional nodes and connectivity involving the default-mode, attention, and sensorimotor systems. Importantly, these ADHD-associated alterations significantly correlated with behavior disturbances (e.g., inattention and hyperactivity/impulsivity symptoms) and exhibited differential patterns between clinical subtypes. Together, these connectome-based studies highlight brain network dysfunction in ADHD, thus opening up a new window into our understanding of the pathophysiological mechanisms of this disorder. These works might also have important implications on the development of imaging-based biomarkers for clinical diagnosis and treatment evaluation in ADHD.

Methylphenidate Modulates Functional Network Connectivity to Enhance Attention

OpenAIRE

Rosenberg, Monica D.; Zhang, Sheng; Hsu, Wei-Ting; Scheinost, Dustin; Finn, Emily S.; Shen, Xilin; Constable, R. Todd; Li, Chiang-Shan R.; Chun, Marvin M.

2016-01-01

Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained...

Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder.

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Kucyi, Aaron; Hove, Michael J; Biederman, Joseph; Van Dijk, Koene R A; Valera, Eve M

2015-09-01

Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. © 2015 Wiley Periodicals, Inc.

Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder

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Kucyi, Aaron; Hove, Michael J.; Biederman, Joseph; Van Dijk, Koene R.A.; Valera, Eve M.

2015-01-01

Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of the cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD. PMID:26109476

Disrupted functional connectivity in dorsal and ventral attention networks during attention orienting in autism spectrum disorders.

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Fitzgerald, Jacqueline; Johnson, Katherine; Kehoe, Elizabeth; Bokde, Arun L W; Garavan, Hugh; Gallagher, Louise; McGrath, Jane

2015-04-01

Attention orienting is a cognitive process that facilitates the movement of attention focus from one location to another: this may be impaired in autism spectrum disorder (ASD). Dorsal and ventral attention networks (DAN and VAN) sub-serve the process of attention orienting. This study investigated the functional connectivity of attention orienting in these networks in ASD using the Posner Cueing Task. Twenty-one adolescents with ASD and 21 age and IQ matched controls underwent functional magnetic resonance imaging. A psychophysical interaction (PPI) analysis was implemented to investigate task-dependent functional connectivity, measuring synchronicity of brain regions during the task. Regions of interest (ROI) were selected to explore functional connectivity in the DAN during cue-only conditions and in the VAN during invalid and valid trials. Behaviourally, the ASD and control groups performed the task in a similar manner. Functional MRI results indicated that the ASD and control groups activated similar brain regions. During invalid trials (VAN), the ASD group showed significant positive functional connectivity to multiple brain regions, whilst the control group demonstrated negative connectivity. During valid trials (VAN), the two groups also showed contrasting patterns of connectivity. In the cue-only conditions (DAN), the ASD group showed weaker functional connectivity. The DAN analysis suggests that the ASD group has weaker coherence between brain areas involved in goal-driven, endogenous attention control. The strong positive functional connectivity exhibited by the ASD group in the VAN during the invalid trials suggests that individuals with ASD may generate compensatory mechanisms to achieve neurotypical behaviour. These results support the theory of abnormal cortical connectivity in autism. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

Network-targeted cerebellar transcranial magnetic stimulation improves attentional control

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Esterman, Michael; Thai, Michelle; Okabe, Hidefusa; DeGutis, Joseph; Saad, Elyana; Laganiere, Simon E.; Halko, Mark A.

2018-01-01

Developing non-invasive brain stimulation interventions to improve attentional control is extremely relevant to a variety of neurologic and psychiatric populations, yet few studies have identified reliable biomarkers that can be readily modified to improve attentional control. One potential biomarker of attention is functional connectivity in the core cortical network supporting attention - the dorsal attention network (DAN). We used a network-targeted cerebellar transcranial magnetic stimulation (TMS) procedure, intended to enhance cortical functional connectivity in the DAN. Specifically, in healthy young adults we administered intermittent theta burst TMS (iTBS) to the midline cerebellar node of the DAN and, as a control, the right cerebellar node of the default mode network (DMN). These cerebellar targets were localized using individual resting-state fMRI scans. Participants completed assessments of both sustained (gradual onset continuous performance task, gradCPT) and transient attentional control (attentional blink) immediately before and after stimulation, in two sessions (cerebellar DAN and DMN). Following cerebellar DAN stimulation, participants had significantly fewer attentional lapses (lower commission error rates) on the gradCPT. In contrast, stimulation to the cerebellar DMN did not affect gradCPT performance. Further, in the DAN condition, individuals with worse baseline gradCPT performance showed the greatest enhancement in gradCPT performance. These results suggest that temporarily increasing functional connectivity in the DAN via network-targeted cerebellar stimulation can enhance sustained attention, particularly in those with poor baseline performance. With regard to transient attention, TMS stimulation improved attentional blink performance across both stimulation sites, suggesting increasing functional connectivity in both networks can enhance this aspect of attention. These findings have important implications for intervention applications

Attention shifts the language network reflecting paradigm presentation

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Kathrin eKollndorfer

2013-11-01

Full Text Available Objectives: Functional magnetic resonance imaging (fMRI is a reliable and non-invasive method with which to localize language function in pre-surgical planning. In clinical practice, visual stimulus presentation is often difficult or impossible, due to the patient’s restricted language or attention abilities. Therefore, our aim was to investigate modality-specific differences in visual and auditory stimulus presentation.Methods: Ten healthy subjects participated in an fMRI study comprising two experiments with visual and auditory stimulus presentation. In both experiments, two language paradigms (one for language comprehension and one for language production used in clinical practice were investigated. In addition to standard data analysis by the means of the general linear model (GLM, independent component analysis (ICA was performed to achieve more detailed information on language processing networks.Results: GLM analysis revealed modality-specific brain activation for both language paradigms for the contrast visual > auditory in the area of the intraparietal sulcus and the hippocampus, two areas related to attention and working memory. Using group ICA, a language network was detected for both paradigms independent of stimulus presentation modality. The investigation of language lateralization revealed no significant variations. Visually presented stimuli further activated an attention-shift network, which could not be identified for the auditory presented language.Conclusion: The results of this study indicate that the visually presented language stimuli additionally activate an attention-shift network. These findings will provide important information for pre-surgical planning in order to preserve reading abilities after brain surgery, significantly improving surgical outcomes. Our findings suggest that the presentation modality for language paradigms should be adapted on behalf of individual indication.

Analysis of a phase synchronized functional network based on the rhythm of brain activities

International Nuclear Information System (INIS)

Li Ling; Jin Zhen-Lan; Li Bin

2011-01-01

Rhythm of brain activities represents oscillations of postsynaptic potentials in neocortex, therefore it can serve as an indicator of the brain activity state. In order to check the connectivity of brain rhythm, this paper develops a new method of constructing functional network based on phase synchronization. Electroencephalogram (EEG) data were collected while subjects looking at a green cross in two states, performing an attention task and relaxing with eyes-open. The EEG from these two states was filtered by three band-pass filters to obtain signals of theta (4–7 Hz), alpha (8–13 Hz) and beta (14–30 Hz) bands. Mean resultant length was used to estimate strength of phase synchronization in three bands to construct networks of both states, and mean degree K and cluster coefficient C of networks were calculated as a function of threshold. The result shows higher cluster coefficient in the attention state than in the eyes-open state in all three bands, suggesting that cluster coefficient reflects brain state. In addition, an obvious fronto-parietal network is found in the attention state, which is a well-known attention network. These results indicate that attention modulates the fronto-parietal connectivity in different modes as compared with the eyes-open state. Taken together this method is an objective and important tool to study the properties of neural networks of brain rhythm. (interdisciplinary physics and related areas of science and technology)

Hemispheric lateralization of topological organization in structural brain networks.

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Caeyenberghs, Karen; Leemans, Alexander

2014-09-01

The study on structural brain asymmetries in healthy individuals plays an important role in our understanding of the factors that modulate cognitive specialization in the brain. Here, we used fiber tractography to reconstruct the left and right hemispheric networks of a large cohort of 346 healthy participants (20-86 years) and performed a graph theoretical analysis to investigate this brain laterality from a network perspective. Findings revealed that the left hemisphere is significantly more "efficient" than the right hemisphere, whereas the right hemisphere showed higher values of "betweenness centrality" and "small-worldness." In particular, left-hemispheric networks displayed increased nodal efficiency in brain regions related to language and motor actions, whereas the right hemisphere showed an increase in nodal efficiency in brain regions involved in memory and visuospatial attention. In addition, we found that hemispheric networks decrease in efficiency with age. Finally, we observed significant gender differences in measures of global connectivity. By analyzing the structural hemispheric brain networks, we have provided new insights into understanding the neuroanatomical basis of lateralized brain functions. Copyright © 2014 Wiley Periodicals, Inc.

Electrophysiological evidence for spatiotemporal flexibility in the ventrolateral attention network.

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Jelena Ristic

Full Text Available Successful completion of many everyday tasks depends on interactions between voluntary attention, which acts to maintain current goals, and reflexive attention, which enables responding to unexpected events by interrupting the current focus of attention. Past studies, which have mostly examined each attentional mechanism in isolation, indicate that volitional and reflexive orienting depend on two functionally specialized cortical networks in the human brain. Here we investigated how the interplay between these two cortical networks affects sensory processing and the resulting overt behavior. By combining measurements of human performance and electrocortical recordings with a novel analytical technique for estimating spatiotemporal activity in the human cortex, we found that the subregions that comprise the reflexive ventrolateral attention network dissociate both spatially and temporally as a function of the nature of the sensory information and current task demands. Moreover, we found that together with the magnitude of the early sensory gain, the spatiotemporal neural dynamics accounted for the high amount of the variance in the behavioral data. Collectively these data support the conclusion that the ventrolateral attention network is recruited flexibly to support complex behaviors.

Attention Network Dysfunction in Bulimia Nervosa - An fMRI Study.

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Jochen Seitz

Full Text Available Recent evidence has suggested an increased rate of comorbid ADHD and subclinical attentional impairments in bulimia nervosa (BN patients. However, little is known regarding the underlying neural mechanisms of attentional functions in BN.Twenty BN patients and twenty age- and weight-matched healthy controls (HC were investigated using a modified version of the Attention Network Task (ANT in an fMRI study. This design enabled an investigation of the neural mechanisms associated with the three attention networks involved in alerting, reorienting and executive attention.The BN patients showed hyperactivation in parieto-occipital regions and reduced deactivation of default-mode-network (DMN areas during alerting compared with HCs. Posterior cingulate activation during alerting correlated with the severity of eating-disorder symptoms within the patient group. Conversely, BN patients showed hypoactivation during reorienting and executive attention in anterior cingulate regions, the temporo-parietal junction (TPJ and parahippocampus compared with HCs, which was negatively associated with global ADHD symptoms and impulsivity, respectively.Our findings demonstrate altered brain mechanisms in BN associated with all three attentional networks. Failure to deactivate the DMN and increased parieto-occipital activation required for alerting might be associated with a constant preoccupation with food or body image-related thoughts. Hypoactivation of executive control networks and TPJ might increase the likelihood of inattentive and impulsive behaviors and poor emotion regulation. Thus, dysfunction in the attentional network in BN goes beyond an altered executive attentional domain and needs to be considered in the diagnosis and treatment of BN.

Attention Network Dysfunction in Bulimia Nervosa - An fMRI Study

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Dahmen, Brigitte; Schulte-Rüther, Martin; Legenbauer, Tanja; Herpertz-Dahlmann, Beate; Konrad, Kerstin

2016-01-01

Objective Recent evidence has suggested an increased rate of comorbid ADHD and subclinical attentional impairments in bulimia nervosa (BN) patients. However, little is known regarding the underlying neural mechanisms of attentional functions in BN. Method Twenty BN patients and twenty age- and weight-matched healthy controls (HC) were investigated using a modified version of the Attention Network Task (ANT) in an fMRI study. This design enabled an investigation of the neural mechanisms associated with the three attention networks involved in alerting, reorienting and executive attention. Results The BN patients showed hyperactivation in parieto-occipital regions and reduced deactivation of default-mode-network (DMN) areas during alerting compared with HCs. Posterior cingulate activation during alerting correlated with the severity of eating-disorder symptoms within the patient group. Conversely, BN patients showed hypoactivation during reorienting and executive attention in anterior cingulate regions, the temporo-parietal junction (TPJ) and parahippocampus compared with HCs, which was negatively associated with global ADHD symptoms and impulsivity, respectively. Discussion Our findings demonstrate altered brain mechanisms in BN associated with all three attentional networks. Failure to deactivate the DMN and increased parieto-occipital activation required for alerting might be associated with a constant preoccupation with food or body image-related thoughts. Hypoactivation of executive control networks and TPJ might increase the likelihood of inattentive and impulsive behaviors and poor emotion regulation. Thus, dysfunction in the attentional network in BN goes beyond an altered executive attentional domain and needs to be considered in the diagnosis and treatment of BN. PMID:27607439

Pupil size signals mental effort deployed during multiple object tracking and predicts brain activity in the dorsal attention network and the locus coeruleus.

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Alnæs, Dag; Sneve, Markus Handal; Espeseth, Thomas; Endestad, Tor; van de Pavert, Steven Harry Pieter; Laeng, Bruno

2014-04-01

Attentional effort relates to the allocation of limited-capacity attentional resources to meet current task demands and involves the activation of top-down attentional systems in the brain. Pupillometry is a sensitive measure of this intensity aspect of top-down attentional control. Studies relate pupillary changes in response to cognitive processing to activity in the locus coeruleus (LC), which is the main hub of the brain's noradrenergic system and it is thought to modulate the operations of the brain's attentional systems. In the present study, participants performed a visual divided attention task known as multiple object tracking (MOT) while their pupil sizes were recorded by use of an infrared eye tracker and then were tested again with the same paradigm while brain activity was recorded using fMRI. We hypothesized that the individual pupil dilations, as an index of individual differences in mental effort, as originally proposed by Kahneman (1973), would be a better predictor of LC activity than the number of tracked objects during MOT. The current results support our hypothesis, since we observed pupil-related activity in the LC. Moreover, the changes in the pupil correlated with activity in the superior colliculus and the right thalamus, as well as cortical activity in the dorsal attention network, which previous studies have shown to be strongly activated during visual tracking of multiple targets. Follow-up pupillometric analyses of the MOT task in the same individuals also revealed that individual differences to cognitive load can be remarkably stable over a lag of several years. To our knowledge this is the first study using pupil dilations as an index of attentional effort in the MOT task and also relating these to functional changes in the brain that directly implicate the LC-NE system in the allocation of processing resources.

Scholastic performance and functional connectivity of brain networks in children.

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Laura Chaddock-Heyman

Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

Brain Inspired Cognitive Model with Attention for Self-Driving Cars

OpenAIRE

Chen, Shitao; Zhang, Songyi; Shang, Jinghao; Chen, Badong; Zheng, Nanning

2017-01-01

Perception-driven approach and end-to-end system are two major vision-based frameworks for self-driving cars. However, it is difficult to introduce attention and historical information of autonomous driving process, which are the essential factors for achieving human-like driving into these two methods. In this paper, we propose a novel model for self-driving cars named brain-inspired cognitive model with attention (CMA). This model consists of three parts: a convolutional neural network for ...

Connectivity supporting attention in children with attention deficit hyperactivity disorder.

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Barber, Anita D; Jacobson, Lisa A; Wexler, Joanna L; Nebel, Mary Beth; Caffo, Brian S; Pekar, James J; Mostofsky, Stewart H

2015-01-01

Intra-subject variability (ISV) is the most consistent behavioral deficit in Attention Deficit Hyperactivity Disorder (ADHD). ISV may be associated with networks involved in sustaining task control (cingulo-opercular network: CON) and self-reflective lapses of attention (default mode network: DMN). The current study examined whether connectivity supporting attentional control is atypical in children with ADHD. Group differences in full-brain connection strength and brain-behavior associations with attentional control measures were examined for the late-developing CON and DMN in 50 children with ADHD and 50 typically-developing (TD) controls (ages 8-12 years). Children with ADHD had hyper-connectivity both within the CON and within the DMN. Full-brain behavioral associations were found for a number of between-network connections. Across both groups, more anti-correlation between DMN and occipital cortex supported better attentional control. However, in the TD group, this brain-behavior association was stronger and occurred for a more extensive set of DMN-occipital connections. Differential support for attentional control between the two groups occurred with a number of CON-DMN connections. For all CON-DMN connections identified, increased between-network anti-correlation was associated with better attentional control for the ADHD group, but worse attentional control in the TD group. A number of between-network connections with the medial frontal cortex, in particular, showed this relationship. Follow-up analyses revealed that these associations were specific to attentional control and were not due to individual differences in working memory, IQ, motor control, age, or scan motion. While CON-DMN anti-correlation is associated with improved attention in ADHD, other circuitry supports improved attention in TD children. Greater CON-DMN anti-correlation supported better attentional control in children with ADHD, but worse attentional control in TD children. On the other

Brain Connectivity Networks and the Aesthetic Experience of Music.

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Reybrouck, Mark; Vuust, Peter; Brattico, Elvira

2018-06-12

Listening to music is above all a human experience, which becomes an aesthetic experience when an individual immerses himself/herself in the music, dedicating attention to perceptual-cognitive-affective interpretation and evaluation. The study of these processes where the individual perceives, understands, enjoys and evaluates a set of auditory stimuli has mainly been focused on the effect of music on specific brain structures, as measured with neurophysiology and neuroimaging techniques. The very recent application of network science algorithms to brain research allows an insight into the functional connectivity between brain regions. These studies in network neuroscience have identified distinct circuits that function during goal-directed tasks and resting states. We review recent neuroimaging findings which indicate that music listening is traceable in terms of network connectivity and activations of target regions in the brain, in particular between the auditory cortex, the reward brain system and brain regions active during mind wandering.

Driving and driven architectures of directed small-world human brain functional networks.

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Chaogan Yan

Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

Attentional networks in developmental dyscalculia

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Henik Avishai

2010-01-01

Full Text Available Abstract Background Very little is known about attention deficits in developmental dyscalculia, hence, this study was designed to provide the missing information. We examined attention abilities of participants suffering from developmental dyscalculia using the attention networks test - interactions. This test was designed to examine three different attention networks--executive function, orienting and alerting--and the interactions between them. Methods Fourteen university students that were diagnosed as suffering from developmental dyscalculia--intelligence and reading abilities in the normal range and no indication of attention-deficit hyperactivity disorder--and 14 matched controls were tested using the attention networks test - interactions. All participants were given preliminary tests to measure mathematical abilities, reading, attention and intelligence. Results The results revealed deficits in the alerting network--a larger alerting effect--and in the executive function networks--a larger congruity effect in developmental dyscalculia participants. The interaction between the alerting and executive function networks was also modulated by group. In addition, developmental dyscalculia participants were slower to respond in the non-cued conditions. Conclusions These results imply specific attentional deficits in pure developmental dyscalculia. Namely, those with developmental dyscalculia seem to be deficient in the executive function and alertness networks. They suffer from difficulty in recruiting attention, in addition to the deficits in numerical processing.

Attentional networks in developmental dyscalculia.

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Askenazi, Sarit; Henik, Avishai

2010-01-07

Very little is known about attention deficits in developmental dyscalculia, hence, this study was designed to provide the missing information. We examined attention abilities of participants suffering from developmental dyscalculia using the attention networks test - interactions. This test was designed to examine three different attention networks--executive function, orienting and alerting--and the interactions between them. Fourteen university students that were diagnosed as suffering from developmental dyscalculia--intelligence and reading abilities in the normal range and no indication of attention-deficit hyperactivity disorder--and 14 matched controls were tested using the attention networks test-interactions. All participants were given preliminary tests to measure mathematical abilities, reading, attention and intelligence. The results revealed deficits in the alerting network--a larger alerting effect--and in the executive function networks--a larger congruity effect in developmental dyscalculia participants. The interaction between the alerting and executive function networks was also modulated by group. In addition, developmental dyscalculia participants were slower to respond in the non-cued conditions. These results imply specific attentional deficits in pure developmental dyscalculia. Namely, those with developmental dyscalculia seem to be deficient in the executive function and alertness networks. They suffer from difficulty in recruiting attention, in addition to the deficits in numerical processing.

Hyper-connectivity of functional networks for brain disease diagnosis.

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Jie, Biao; Wee, Chong-Yaw; Shen, Dinggang; Zhang, Daoqiang

2016-08-01

Exploring structural and functional interactions among various brain regions enables better understanding of pathological underpinnings of neurological disorders. Brain connectivity network, as a simplified representation of those structural and functional interactions, has been widely used for diagnosis and classification of neurodegenerative diseases, especially for Alzheimer's disease (AD) and its early stage - mild cognitive impairment (MCI). However, the conventional functional connectivity network is usually constructed based on the pairwise correlation among different brain regions and thus ignores their higher-order relationships. Such loss of high-order information could be important for disease diagnosis, since neurologically a brain region predominantly interacts with more than one other brain regions. Accordingly, in this paper, we propose a novel framework for estimating the hyper-connectivity network of brain functions and then use this hyper-network for brain disease diagnosis. Here, the functional connectivity hyper-network denotes a network where each of its edges representing the interactions among multiple brain regions (i.e., an edge can connect with more than two brain regions), which can be naturally represented by a hyper-graph. Specifically, we first construct connectivity hyper-networks from the resting-state fMRI (R-fMRI) time series by using sparse representation. Then, we extract three sets of brain-region specific features from the connectivity hyper-networks, and further exploit a manifold regularized multi-task feature selection method to jointly select the most discriminative features. Finally, we use multi-kernel support vector machine (SVM) for classification. The experimental results on both MCI dataset and attention deficit hyperactivity disorder (ADHD) dataset demonstrate that, compared with the conventional connectivity network-based methods, the proposed method can not only improve the classification performance, but also help

Shared and disorder-specific task-positive and default mode network dysfunctions during sustained attention in paediatric Attention-Deficit/Hyperactivity Disorder and obsessive/compulsive disorder

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Luke J. Norman

2017-01-01

Full Text Available Patients with Attention-Deficit/Hyperactivity Disorder (ADHD and obsessive/compulsive disorder (OCD share problems with sustained attention, and are proposed to share deficits in switching between default mode and task positive networks. The aim of this study was to investigate shared and disorder-specific brain activation abnormalities during sustained attention in the two disorders. Twenty boys with ADHD, 20 boys with OCD and 20 age-matched healthy controls aged between 12 and 18 years completed a functional magnetic resonance imaging (fMRI version of a parametrically modulated sustained attention task with a progressively increasing sustained attention load. Performance and brain activation were compared between groups. Only ADHD patients were impaired in performance. Group by sustained attention load interaction effects showed that OCD patients had disorder-specific middle anterior cingulate underactivation relative to controls and ADHD patients, while ADHD patients showed disorder-specific underactivation in left dorsolateral prefrontal cortex/dorsal inferior frontal gyrus (IFG. ADHD and OCD patients shared left insula/ventral IFG underactivation and increased activation in posterior default mode network relative to controls, but had disorder-specific overactivation in anterior default mode regions, in dorsal anterior cingulate for ADHD and in anterior ventromedial prefrontal cortex for OCD. In sum, ADHD and OCD patients showed mostly disorder-specific patterns of brain abnormalities in both task positive salience/ventral attention networks with lateral frontal deficits in ADHD and middle ACC deficits in OCD, as well as in their deactivation patterns in medial frontal DMN regions. The findings suggest that attention performance in the two disorders is underpinned by disorder-specific activation patterns.

Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

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Wang, Yi-Feng; Long, Zhiliang; Cui, Qian; Liu, Feng; Jing, Xiu-Juan; Chen, Heng; Guo, Xiao-Nan; Yan, Jin H; Chen, Hua-Fu

2016-01-01

Neural oscillations are essential for brain functions. Research has suggested that the frequency of neural oscillations is lower for more integrative and remote communications. In this vein, some resting-state studies have suggested that large scale networks function in the very low frequency range (frequency characteristics of brain networks because both resting-state studies and conventional frequency tagging approaches cannot simultaneously capture multiple large scale networks in controllable cognitive activities. In this preliminary study, we aimed to examine whether large scale networks can be modulated by task-induced low frequency steady-state brain responses (lfSSBRs) in a frequency-specific pattern. In a revised attention network test, the lfSSBRs were evoked in the triple network system and sensory-motor system, indicating that large scale networks can be modulated in a frequency tagging way. Furthermore, the inter- and intranetwork synchronizations as well as coherence were increased at the fundamental frequency and the first harmonic rather than at other frequency bands, indicating a frequency-specific modulation of information communication. However, there was no difference among attention conditions, indicating that lfSSBRs modulate the general attention state much stronger than distinguishing attention conditions. This study provides insights into the advantage and mechanism of lfSSBRs. More importantly, it paves a new way to investigate frequency-specific large scale brain activities. © 2015 Wiley Periodicals, Inc.

Regional brain network organization distinguishes the combined and inattentive subtypes of Attention Deficit Hyperactivity Disorder.

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Saad, Jacqueline F; Griffiths, Kristi R; Kohn, Michael R; Clarke, Simon; Williams, Leanne M; Korgaonkar, Mayuresh S

2017-01-01

Attention Deficit Hyperactivity Disorder (ADHD) is characterized clinically by hyperactive/impulsive and/or inattentive symptoms which determine diagnostic subtypes as Predominantly Hyperactive-Impulsive (ADHD-HI), Predominantly Inattentive (ADHD-I), and Combined (ADHD-C). Neuroanatomically though we do not yet know if these clinical subtypes reflect distinct aberrations in underlying brain organization. We imaged 34 ADHD participants defined using DSM-IV criteria as ADHD-I ( n  = 16) or as ADHD-C ( n  = 18) and 28 matched typically developing controls, aged 8-17 years, using high-resolution T1 MRI. To quantify neuroanatomical organization we used graph theoretical analysis to assess properties of structural covariance between ADHD subtypes and controls (global network measures: path length, clustering coefficient, and regional network measures: nodal degree). As a context for interpreting network organization differences, we also quantified gray matter volume using voxel-based morphometry. Each ADHD subtype was distinguished by a different organizational profile of the degree to which specific regions were anatomically connected with other regions (i.e., in "nodal degree"). For ADHD-I (compared to both ADHD-C and controls) the nodal degree was higher in the hippocampus. ADHD-I also had a higher nodal degree in the supramarginal gyrus, calcarine sulcus, and superior occipital cortex compared to ADHD-C and in the amygdala compared to controls. By contrast, the nodal degree was higher in the cerebellum for ADHD-C compared to ADHD-I and in the anterior cingulate, middle frontal gyrus and putamen compared to controls. ADHD-C also had reduced nodal degree in the rolandic operculum and middle temporal pole compared to controls. These regional profiles were observed in the context of no differences in gray matter volume or global network organization. Our results suggest that the clinical distinction between the Inattentive and Combined subtypes of ADHD may also be

Oscillatory Dynamics in the Frontoparietal Attention Network during Sustained Attention in the Ferret

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Kristin K. Sellers

2016-09-01

Full Text Available Sustained attention requires the coordination of neural activity across multiple cortical areas in the frontoparietal network, in particular the prefrontal cortex (PFC and posterior parietal cortex (PPC. Previous work has demonstrated that activity in these brain regions is coordinated by neuronal oscillations of the local field potential (LFP. However, the underlying coordination of activity in terms of organization of single unit (SU spiking activity has remained poorly understood, particularly in the freely moving animal. We found that long-range functional connectivity between anatomically connected PFC and PPC was mediated by oscillations in the theta frequency band. SU activity in PFC was phase locked to theta oscillations in PPC, and spiking activity in PFC and PPC was locked to local high-gamma activity. Together, our results support a model in which frequency-specific synchronization mediates functional connectivity between and within PFC and PPC of the frontoparietal attention network in the freely moving animal.

Selective vulnerability related to aging in large-scale resting brain networks.

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Zhang, Hong-Ying; Chen, Wen-Xin; Jiao, Yun; Xu, Yao; Zhang, Xiang-Rong; Wu, Jing-Tao

2014-01-01

Normal aging is associated with cognitive decline. Evidence indicates that large-scale brain networks are affected by aging; however, it has not been established whether aging has equivalent effects on specific large-scale networks. In the present study, 40 healthy subjects including 22 older (aged 60-80 years) and 18 younger (aged 22-33 years) adults underwent resting-state functional MRI scanning. Four canonical resting-state networks, including the default mode network (DMN), executive control network (ECN), dorsal attention network (DAN) and salience network, were extracted, and the functional connectivities in these canonical networks were compared between the younger and older groups. We found distinct, disruptive alterations present in the large-scale aging-related resting brain networks: the ECN was affected the most, followed by the DAN. However, the DMN and salience networks showed limited functional connectivity disruption. The visual network served as a control and was similarly preserved in both groups. Our findings suggest that the aged brain is characterized by selective vulnerability in large-scale brain networks. These results could help improve our understanding of the mechanism of degeneration in the aging brain. Additional work is warranted to determine whether selective alterations in the intrinsic networks are related to impairments in behavioral performance.

White matter integrity in brain networks relevant to anxiety and depression: evidence from the human connectome project dataset.

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De Witte, Nele A J; Mueller, Sven C

2017-12-01

Anxiety and depression are associated with altered communication within global brain networks and between these networks and the amygdala. Functional connectivity studies demonstrate an effect of anxiety and depression on four critical brain networks involved in top-down attentional control (fronto-parietal network; FPN), salience detection and error monitoring (cingulo-opercular network; CON), bottom-up stimulus-driven attention (ventral attention network; VAN), and default mode (default mode network; DMN). However, structural evidence on the white matter (WM) connections within these networks and between these networks and the amygdala is lacking. The current study in a large healthy sample (n = 483) observed that higher trait anxiety-depression predicted lower WM integrity in the connections between amygdala and specific regions of the FPN, CON, VAN, and DMN. We discuss the possible consequences of these anatomical alterations for cognitive-affective functioning and underscore the need for further theory-driven research on individual differences in anxiety and depression on brain structure.

Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

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Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

2017-10-01

The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Modality-specificity of Selective Attention Networks

OpenAIRE

Stewart, Hannah J.; Amitay, Sygal

2015-01-01

Objective: To establish the modality specificity and generality of selective attention networks. Method: Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resoluti...

Effects of age and sex on developmental neural networks of visual-spatial attention allocation.

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Rubia, Katya; Hyde, Zoe; Halari, Rozmin; Giampietro, Vincent; Smith, Anna

2010-06-01

Compared to our understanding of the functional maturation of brain networks underlying complex cognitive abilities, hardly anything is known of the neurofunctional development of simpler cognitive abilities such as visuo-spatial attention allocation. Furthermore, nothing is known on the effect of gender on the functional development of attention allocation. This study employed event related functional magnetic resonance imaging to investigate effects of age, sex, and sex by age interactions on the brain activation of 63 males and females, between 13 to 38years, during a visual-spatial oddball task. Behaviourally, with increasing age, speed was traded for accuracy, indicative of a less impulsive performance style in older subjects. Increasing age was associated with progressively increased activation in typical areas of selective attention of lateral fronto-striatal and temporo-parietal brain regions. Sex difference analysis showed enhanced activation in right-hemispheric inferior frontal and superior temporal regions in females, and in left-hemispheric inferior temporo-parietal regions in males. Importantly, the age by sex interaction findings showed that these sex-dimorphic patterns of brain activation may be the result of underlying sex differences in the functional maturation of these brain regions, as females had sex-specific progressive age-correlations in the same right inferior fronto-striato-temporal areas, while male-specific age-correlations were in left medial temporal and parietal areas. The findings demonstrate progressive functional maturation of fronto-striato-parieto-temporal networks of the relatively simple function of attention allocation between early adolescence and mid-adulthood. They furthermore show that sex-dimorphic patterns of enhanced reliance on right inferior frontal, striatal and superior temporal regions in females and of left temporo-parietal regions in males during attention allocation may be the result of underlying sex

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

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Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

2017-02-01

We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Brain differences between persistent and remitted attention deficit hyperactivity disorder.

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Mattfeld, Aaron T; Gabrieli, John D E; Biederman, Joseph; Spencer, Thomas; Brown, Ariel; Kotte, Amelia; Kagan, Elana; Whitfield-Gabrieli, Susan

2014-09-01

Previous resting state studies examining the brain basis of attention deficit hyperactivity disorder have not distinguished between patients who persist versus those who remit from the diagnosis as adults. To characterize the neurobiological differences and similarities of persistence and remittance, we performed resting state functional magnetic resonance imaging in individuals who had been longitudinally and uniformly characterized as having or not having attention deficit hyperactivity disorder in childhood and again in adulthood (16 years after baseline assessment). Intrinsic functional brain organization was measured in patients who had a persistent diagnosis in childhood and adulthood (n = 13), in patients who met diagnosis in childhood but not in adulthood (n = 22), and in control participants who never had attention deficit hyperactivity disorder (n = 17). A positive functional correlation between posterior cingulate and medial prefrontal cortices, major components of the default-mode network, was reduced only in patients whose diagnosis persisted into adulthood. A negative functional correlation between medial and dorsolateral prefrontal cortices was reduced in both persistent and remitted patients. The neurobiological dissociation between the persistence and remittance of attention deficit hyperactivity disorder may provide a framework for the relation between the clinical diagnosis, which indicates the need for treatment, and additional deficits that are common, such as executive dysfunctions. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Aging and functional brain networks

International Nuclear Information System (INIS)

Tomasi D.; Volkow, N.D.

2012-01-01

Aging is associated with changes in human brain anatomy and function and cognitive decline. Recent studies suggest the aging decline of major functional connectivity hubs in the 'default-mode' network (DMN). Aging effects on other networks, however, are largely unknown. We hypothesized that aging would be associated with a decline of short- and long-range functional connectivity density (FCD) hubs in the DMN. To test this hypothesis, we evaluated resting-state data sets corresponding to 913 healthy subjects from a public magnetic resonance imaging database using functional connectivity density mapping (FCDM), a voxelwise and data-driven approach, together with parallel computing. Aging was associated with pronounced long-range FCD decreases in DMN and dorsal attention network (DAN) and with increases in somatosensory and subcortical networks. Aging effects in these networks were stronger for long-range than for short-range FCD and were also detected at the level of the main functional hubs. Females had higher short- and long-range FCD in DMN and lower FCD in the somatosensory network than males, but the gender by age interaction effects were not significant for any of the networks or hubs. These findings suggest that long-range connections may be more vulnerable to aging effects than short-range connections and that, in addition to the DMN, the DAN is also sensitive to aging effects, which could underlie the deterioration of attention processes that occurs with aging.

Brain anatomical networks in early human brain development.

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Fan, Yong; Shi, Feng; Smith, Jeffrey Keith; Lin, Weili; Gilmore, John H; Shen, Dinggang

2011-02-01

Recent neuroimaging studies have demonstrated that human brain networks have economic small-world topology and modular organization, enabling efficient information transfer among brain regions. However, it remains largely unknown how the small-world topology and modular organization of human brain networks emerge and develop. Using longitudinal MRI data of 28 healthy pediatric subjects, collected at their ages of 1 month, 1 year, and 2 years, we analyzed development patterns of brain anatomical networks derived from morphological correlations of brain regional volumes. The results show that the brain network of 1-month-olds has the characteristically economic small-world topology and nonrandom modular organization. The network's cost efficiency increases with the brain development to 1 year and 2 years, so does the modularity, providing supportive evidence for the hypothesis that the small-world topology and the modular organization of brain networks are established during early brain development to support rapid synchronization and information transfer with minimal rewiring cost, as well as to balance between local processing and global integration of information. Copyright © 2010. Published by Elsevier Inc.

Supervised dictionary learning for inferring concurrent brain networks.

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Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

What makes your brain suggestible? Hypnotizability is associated with differential brain activity during attention outside hypnosis.

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Cojan, Yann; Piguet, Camille; Vuilleumier, Patrik

2015-08-15

Theoretical models of hypnosis have emphasized the importance of attentional processes in accounting for hypnotic phenomena but their exact nature and brain substrates remain unresolved. Individuals vary in their susceptibility to hypnosis, a variability often attributed to differences in attentional functioning such as greater ability to filter irrelevant information and inhibit prepotent responses. However, behavioral studies of attentional performance outside the hypnotic state have provided conflicting results. We used fMRI to investigate the recruitment of attentional networks during a modified flanker task in High and Low hypnotizable participants. The task was performed in a normal (no hypnotized) state. While behavioral performance did not reliably differ between groups, components of the fronto-parietal executive network implicated in monitoring (anterior cingulate cortex; ACC), adjustment (lateral prefrontal cortex; latPFC), and implementation of attentional control (intraparietal sulcus; IPS) were differently activated depending on the hypnotizability of the subjects: the right inferior frontal gyrus (rIFG) was more recruited, whereas IPS and ACC were less recruited by High susceptible individuals compared to Low. Our results demonstrate that susceptibility to hypnosis is associated with particular executive control capabilities allowing efficient attentional focusing, and point to specific neural substrates in right prefrontal cortex. We demonstrated that outside hypnosis, low hypnotizable subjects recruited more parietal cortex and anterior cingulate regions during selective attention conditions suggesting a better detection and implementation of conflict. However, outside hypnosis the right inferior frontal gyrus (rIFG) was more recruited by highly hypnotizable subjects during selective attention conditions suggesting a better control of conflict. Furthermore, in highly hypnotizable subjects this region was more connected to the default mode network

Brain mechanisms associated with internally directed attention and self-generated thought.

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Benedek, Mathias; Jauk, Emanuel; Beaty, Roger E; Fink, Andreas; Koschutnig, Karl; Neubauer, Aljoscha C

2016-03-10

Internal cognition like imagination and prospection require sustained internally directed attention and involve self-generated thought. This fMRI study aimed to disentangle the brain mechanisms associated with attention-specific and task-specific processes during internally directed cognition. The direction of attention was manipulated by either keeping a relevant stimulus visible throughout the task, or by masking it, so that the task had to be performed "in the mind's eye". The level of self-directed thought was additionally varied between a convergent and a divergent thinking task. Internally directed attention was associated with increased activation in the right anterior inferior parietal lobe (aIPL), bilateral lingual gyrus and the cuneus, as well as with extended deactivations of superior parietal and occipital regions representing parts of the dorsal attention network. The right aIPL further showed increased connectivity with occipital regions suggesting an active top-down mechanism for shielding ongoing internal processes from potentially distracting sensory stimulation in terms of perceptual decoupling. Activation of the default network was not related to internally directed attention per se, but rather to a higher level of self-generated thought. The findings hence shed further light on the roles of inferior and superior parietal cortex for internally directed cognition.

Modality-specificity of Selective Attention Networks.

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Stewart, Hannah J; Amitay, Sygal

2015-01-01

To establish the modality specificity and generality of selective attention networks. Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled "general attention." The third component was labeled "auditory attention," as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as "spatial orienting" and "spatial conflict," respectively-they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task-all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location). These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific.

THE IMPACT OF POVERTY ON THE DEVELOPMENT OF BRAIN NETWORKS

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Sebastian J Lipina

2012-08-01

Full Text Available Although the study of brain development in non-human animals is an old one, recent imaging methods have allowed non-invasive studies of the grey and white matter of the human brain over the lifespan. Classic animal studies show clearly that impoverished environments reduce cortical grey matter in relation to complex environments and cognitive and imaging studies in humans suggest which networks may be most influenced by poverty. Studies have been clear in showing the plasticity of many brain systems, but whether sensitivity to learning differs over the lifespan and for which networks is still unclear. A major task for current research is a successful integration of these methods to understand how development and learning shape the neural networks underlying achievements in literacy, numeracy, and attention. This paper seeks to foster further integration by reviewing the currents state of knowledge relating brain changes to behavior and indicating possible future directions.

Brain systems underlying attentional control and emotional distraction during working memory encoding.

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Ziaei, Maryam; Peira, Nathalie; Persson, Jonas

2014-02-15

Goal-directed behavior requires that cognitive operations can be protected from emotional distraction induced by task-irrelevant emotional stimuli. The brain processes involved in attending to relevant information while filtering out irrelevant information are still largely unknown. To investigate the neural and behavioral underpinnings of attending to task-relevant emotional stimuli while ignoring irrelevant stimuli, we used fMRI to assess brain responses during attentional instructed encoding within an emotional working memory (WM) paradigm. We showed that instructed attention to emotion during WM encoding resulted in enhanced performance, by means of increased memory performance and reduced reaction time, compared to passive viewing. A similar performance benefit was also demonstrated for recognition memory performance, although for positive pictures only. Functional MRI data revealed a network of regions involved in directed attention to emotional information for both positive and negative pictures that included medial and lateral prefrontal cortices, fusiform gyrus, insula, the parahippocampal gyrus, and the amygdala. Moreover, we demonstrate that regions in the striatum, and regions associated with the default-mode network were differentially activated for emotional distraction compared to neutral distraction. Activation in a sub-set of these regions was related to individual differences in WM and recognition memory performance, thus likely contributing to performing the task at an optimal level. The present results provide initial insights into the behavioral and neural consequences of instructed attention and emotional distraction during WM encoding. © 2013.

Yoga lessons for consciousness research: a paralimbic network balancing brain resource allocation

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Hans C Lou

2011-12-01

Full Text Available Consciousness has been proposed to play a key role in shaping flexible learning and as such is thought to confer an evolutionary advantage. Attention and awareness are the perhaps most important underlying processes, yet their precise relationship is presently unclear. Both of these processes must, however, serve the evolutionary imperatives of survival and procreation. They are thus intimately bound by reward and emotion to help to prioritize efficient brain resource allocation in order to predict and optimize behaviour. Here we show how this process is served by a paralimbic network consisting primarily of regions located on the midline of the human brain. Using many different techniques, experiments have demonstrated that this network is effective and specific for self-awareness and contributes to the sense of unity of consciousness by acting as a common neural path for a wide variety of conscious experiences. Interestingly, haemodynamic activity in the network decreases with focusing on external stimuli, which has led to the idea of a default mode network. This network is one of many networks that wax and vane as resources are allocated to accommodate the different cyclical needs of the organism primarily related the fundamental pleasures afforded by evolution: food, sex and conspecifics. Here we hypothesize, however, that the paralimbic network serves a crucial role in balancing and regulating brain resource allocation, and discuss how it can be thought of as a link between current theories of so-called default mode, resting state networks and global workspace. We show how major developmental disorders of self-awareness and self-control can arise from problems in the paralimbic network as demonstrated here by the example of Asperger syndrome. We conclude that attention, awareness and emotion are integrated by a paralimbic network that helps to efficiently allocate brain resources to optimize behaviour and help survival.

Cognition, emotion, and attention.

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Müller-Oehring, Eva M; Schulte, Tilman

2014-01-01

Deficits of attention, emotion, and cognition occur in individuals with alcohol abuse and addiction. This review elucidates the concepts of attention, emotion, and cognition and references research on the underlying neural networks and their compromise in alcohol use disorder. Neuroimaging research on adolescents with family history of alcoholism contributes to the understanding of pre-existing brain structural conditions and characterization of cognition and attention processes in high-risk individuals. Attention and cognition interact with other brain functions, including perceptual selection, salience, emotion, reward, and memory, through interconnected neural networks. Recent research reports compromised microstructural and functional network connectivity in alcoholism, which can have an effect on the dynamic tuning between brain systems, e.g., the frontally based executive control system, the limbic emotion system, and the midbrain-striatal reward system, thereby impeding cognitive flexibility and behavioral adaptation to changing environments. Finally, we introduce concepts of functional compensation, the capacity to generate attentional resources for performance enhancement, and brain structure recovery with abstinence. An understanding of the neural mechanisms of attention, emotion, and cognition will likely provide the basis for better treatment strategies for developing skills that enhance alcoholism therapy adherence and quality of life, and reduce the propensity for relapse. © 2014 Elsevier B.V. All rights reserved.

Notational usage modulates attention networks in binumerates

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Atesh eKoul

2014-05-01

Full Text Available Multicultural environments require learning multiple number notations wherein some are encountered more frequently than others. This leads to differences in exposure and consequently differences in usage between notations. We find that differential notational usage imposes a significant neurocognitive load on number processing. Despite simultaneous acquisition, forty-two adult binumerate populations, familiar with two positional writing systems namely Hindu Nagari digits and Hindu Arabic digits, reported significantly lower preference and usage for Nagari as compared to Arabic. Twenty-four participants showed significantly increased reaction times and reduced accuracy while performing magnitude comparison tasks in Nagari with respect to Arabic. Functional magnetic resonance imaging revealed that processing Nagari elicited significantly greater activity in number processing and attention networks. A direct subtraction of networks for Nagari and Arabic notations revealed a neural circuit comprising of bilateral intra-parietal sulcus, inferior and mid frontal gyri, fusiform gyrus and the anterior cingulate cortex (FDR p<0.005. Additionally, whole brain correlation analysis showed that activity in the left inferior parietal region was modulated by task performance in Nagari. We attribute the increased activation in Ng to increased task difficulty due to infrequent exposure and usage. Our results reiterate the role of the left intra-parietal sulcus in modulating performance in numeric tasks and highlight that of the attention network for monitoring symbolic notation mode in binumerates.

Modality-specificity of selective attention networks

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Hannah Jamieson Stewart

2015-11-01

Full Text Available Objective: To establish the modality specificity and generality of selective attention networks. Method: Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT, the Test of Everyday Attention (TEA, and the Test of Attention in Listening (TAiL. These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. Results: The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled ‘general attention’. The third component was labeled ‘auditory attention’, as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as ‘spatial orienting’ and ‘spatial conflict’, respectively – they were comprised of orienting and conflict resolution measures from the vANT, aANT and TAiL attend-location task – all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location. Conclusions: These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific.

Attention supports verbal short-term memory via competition between dorsal and ventral attention networks.

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Majerus, Steve; Attout, Lucie; D'Argembeau, Arnaud; Degueldre, Christian; Fias, Wim; Maquet, Pierre; Martinez Perez, Trecy; Stawarczyk, David; Salmon, Eric; Van der Linden, Martial; Phillips, Christophe; Balteau, Evelyne

2012-05-01

Interactions between the neural correlates of short-term memory (STM) and attention have been actively studied in the visual STM domain but much less in the verbal STM domain. Here we show that the same attention mechanisms that have been shown to shape the neural networks of visual STM also shape those of verbal STM. Based on previous research in visual STM, we contrasted the involvement of a dorsal attention network centered on the intraparietal sulcus supporting task-related attention and a ventral attention network centered on the temporoparietal junction supporting stimulus-related attention. We observed that, with increasing STM load, the dorsal attention network was activated while the ventral attention network was deactivated, especially during early maintenance. Importantly, activation in the ventral attention network increased in response to task-irrelevant stimuli briefly presented during the maintenance phase of the STM trials but only during low-load STM conditions, which were associated with the lowest levels of activity in the dorsal attention network during encoding and early maintenance. By demonstrating a trade-off between task-related and stimulus-related attention networks during verbal STM, this study highlights the dynamics of attentional processes involved in verbal STM.

Brain networks underlying mental imagery of auditory and visual information.

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Zvyagintsev, Mikhail; Clemens, Benjamin; Chechko, Natalya; Mathiak, Krystyna A; Sack, Alexander T; Mathiak, Klaus

2013-05-01

Mental imagery is a complex cognitive process that resembles the experience of perceiving an object when this object is not physically present to the senses. It has been shown that, depending on the sensory nature of the object, mental imagery also involves correspondent sensory neural mechanisms. However, it remains unclear which areas of the brain subserve supramodal imagery processes that are independent of the object modality, and which brain areas are involved in modality-specific imagery processes. Here, we conducted a functional magnetic resonance imaging study to reveal supramodal and modality-specific networks of mental imagery for auditory and visual information. A common supramodal brain network independent of imagery modality, two separate modality-specific networks for imagery of auditory and visual information, and a common deactivation network were identified. The supramodal network included brain areas related to attention, memory retrieval, motor preparation and semantic processing, as well as areas considered to be part of the default-mode network and multisensory integration areas. The modality-specific networks comprised brain areas involved in processing of respective modality-specific sensory information. Interestingly, we found that imagery of auditory information led to a relative deactivation within the modality-specific areas for visual imagery, and vice versa. In addition, mental imagery of both auditory and visual information widely suppressed the activity of primary sensory and motor areas, for example deactivation network. These findings have important implications for understanding the mechanisms that are involved in generation of mental imagery. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Asymmetrical brain activity induced by voluntary spatial attention depends on the visual hemifield: a functional near-infrared spectroscopy study.

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Harasawa, Masamitsu; Shioiri, Satoshi

2011-04-01

The effect of the visual hemifield to which spatial attention was oriented on the activities of the posterior parietal and occipital visual cortices was examined using functional near-infrared spectroscopy in order to investigate the neural substrates of voluntary visuospatial attention. Our brain imaging data support the theory put forth in a previous psychophysical study, namely, the attentional resources for the left and right visual hemifields are distinct. Increasing the attentional load asymmetrically increased the brain activity. Increase in attentional load produced a greater increase in brain activity in the case of the left visual hemifield than in the case of the right visual hemifield. This asymmetry was observed in all the examined brain areas, including the right and left occipital and parietal cortices. These results suggest the existence of asymmetrical inhibitory interactions between the hemispheres and the presence of an extensive inhibitory network. Copyright © 2011 Elsevier Inc. All rights reserved.

Brain Network Modelling

DEFF Research Database (Denmark)

Andersen, Kasper Winther

Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

A longitudinal study of structural brain network changes with normal aging

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Kai eWu

2013-04-01

Full Text Available The aim of this study was to investigate age-related changes in the topological organization of structural brain networks by applying a longitudinal design over 6 years. Structural brain networks were derived from measurements of regional gray matter volume and were constructed in age-specific groups from baseline and follow-up scans. The structural brain networks showed economical small-world properties, providing high global and local efficiency for parallel information processing at low connection costs. In the analysis of the global network properties, the local and global efficiency of the baseline scan were significantly lower compared to the follow-up scan. Moreover, the annual rate of changes in local and global efficiency showed a positive and negative quadratic correlation with the baseline age, respectively; both curvilinear correlations peaked at approximately the age of 50. In the analysis of the regional nodal properties, significant negative correlations between the annual rate of changes in nodal strength and the baseline age were found in the brain regions primarily involved in the visual and motor/ control systems, whereas significant positive quadratic correlations were found in the brain regions predominately associated with the default-mode, attention, and memory systems. The results of the longitudinal study are consistent with the findings of our previous cross-sectional study: the structural brain networks develop into a fast distribution from young to middle age (approximately 50 years old and eventually became a fast localization in the old age. Our findings elucidate the network topology of structural brain networks and its longitudinal changes, thus enhancing the understanding of the underlying physiology of normal aging in the human brain.

Origin of hyperbolicity in brain-to-brain coordination networks

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Tadić, Bosiljka; Andjelković, Miroslav; Šuvakov, Milovan

2018-02-01

Hyperbolicity or negative curvature of complex networks is the intrinsic geometric proximity of nodes in the graph metric space, which implies an improved network function. Here, we investigate hidden combinatorial geometries in brain-to-brain coordination networks arising through social communications. The networks originate from correlations among EEG signals previously recorded during spoken communications comprising of 14 individuals with 24 speaker-listener pairs. We find that the corresponding networks are delta-hyperbolic with delta_max=1 and the graph diameter D=3 in each brain. While the emergent hyperbolicity in the two-brain networks satisfies delta_max/D/2 neuronal correlation patterns ranging from weak coordination to super-brain structure. These topology features are in qualitative agreement with the listener’s self-reported ratings of own experience and quality of the speaker, suggesting that studies of the cross-brain connector networks can reveal new insight into the neural mechanisms underlying human social behavior.

FROM BRAIN DRAIN TO BRAIN NETWORKING

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Irina BONCEA

2015-06-01

Full Text Available Scientific networking is the most accessible way a country can turn the brain drain into brain gain. Diaspora’s members offer valuable information, advice or financial support from the destination country, without being necessary to return. This article aims to investigate Romania’s potential of turning brain drain into brain networking, using evidence from the medical sector. The main factors influencing the collaboration with the country of origin are investigated. The conclusions suggest that Romania could benefit from the diaspora option, through an active implication at institutional level and the implementation of a strategy in this area.

Modifications in resting state functional anticorrelation between default mode network and dorsal attention network: comparison among young adults, healthy elders and mild cognitive impairment patients.

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Esposito, Roberto; Cieri, Filippo; Chiacchiaretta, Piero; Cera, Nicoletta; Lauriola, Mariella; Di Giannantonio, Massimo; Tartaro, Armando; Ferretti, Antonio

2018-02-01

Resting state brain activity incorporates different components, including the Default Mode Network and the Dorsal Attention Network, also known as task-negative network and task-positive network respectively. These two networks typically show an anticorrelated activity during both spontaneous oscillations and task execution. However modifications of this anticorrelated activity pattern with age and pathology are still unclear. The present study aimed to investigate differences in resting state Default Mode Network-Dorsal Attention Network functional anticorrelation among young adults, healthy elders and Mild Cognitive Impairment patients. We retrospectively enrolled in this study 27 healthy young adults (age range: 25-35 y.o.; mean age: 28,5), 26 healthy elders (age range: 61-72 y.o.; mean age: 65,1) and 17 MCI patients (age range 64-87 y.o.; mean age: 73,6). Mild Cognitive Impairment patients were selected following Petersen criteria. All participants underwent neuropsychological evaluation and resting state functional Magnetic Resonance Imaging. Spontaneous anticorrelated activity between Default Mode Network and Dorsal Attention Network was observed in each group. This anticorrelation was significantly decreased with age in most Default Mode Network-Dorsal Attention Network connections (p Default Mode Network and the right inferior parietal sulcus node of the Dorsal Attention Network was significantly decreased when comparing Mild Cognitive Impairment with normal elders (p Default Mode Network and Dorsal Attention Network is part of the normal aging process and that Mild Cognitive Impairment status is associated with more evident inter-networks functional connectivity changes.

Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

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Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

2016-01-01

Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

OpenAIRE

Zagoruyko, Sergey; Komodakis, Nikos

2016-01-01

Attention plays a critical role in human visual experience. Furthermore, it has recently been demonstrated that attention can also play an important role in the context of applying artificial neural networks to a variety of tasks from fields such as computer vision and NLP. In this work we show that, by properly defining attention for convolutional neural networks, we can actually use this type of information in order to significantly improve the performance of a student CNN network by forcin...

Structural networks involved in attention and executive functions in multiple sclerosis

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Sara Llufriu

2017-01-01

Full Text Available Attention and executive deficits are disabling symptoms in multiple sclerosis (MS that have been related to disconnection mechanisms. We aimed to investigate changes in structural connectivity in MS and their association with attention and executive performance applying an improved framework that combines high order probabilistic tractography and anatomical exclusion criteria postprocessing. We compared graph theory metrics of structural networks and fractional anisotropy (FA of white matter (WM connections or edges between 72 MS subjects and 38 healthy volunteers (HV and assessed their correlation with cognition. Patients displayed decreased network transitivity, global efficiency and increased path length compared with HV (p < 0.05, corrected. Also, nodal strength was decreased in 26 of 84 gray matter regions. The distribution of nodes with stronger connections or hubs of the network was similar among groups except for the right pallidum and left insula, which became hubs in patients. MS subjects presented reduced edge FA widespread in the network, while FA was increased in 24 connections (p < 0.05, corrected. Decreased integrity of frontoparietal networks, deep gray nuclei and insula correlated with worse attention and executive performance (r between 0.38 and 0.55, p < 0.05, corrected. Contrarily, higher strength in the right transverse temporal cortex and increased FA of several connections (mainly from cingulate, frontal and occipital cortices were associated with worse functioning (r between −0.40 and −0.47, p < 0.05 corrected. In conclusion, structural brain connectivity is disturbed in MS due to widespread impairment of WM connections and gray matter structures. The increased edge connectivity suggests the presence of reorganization mechanisms at the structural level. Importantly, attention and executive performance relates to frontoparietal networks, deep gray nuclei and insula. These results support the relevance of

Modulation of attention network activation under antidepressant agents in healthy subjects.

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Graf, Heiko; Abler, Birgit; Hartmann, Antonie; Metzger, Coraline D; Walter, Martin

2013-07-01

While antidepressants are supposed to exert similar effects on mood and drive via various mechanisms of action, diverging effects are observed regarding side-effects and accordingly on neural correlates of motivation, emotion, reward and salient stimuli processing as a function of the drugs impact on neurotransmission. In the context of erotic stimulation, a unidirectional modulation of attentional functioning despite opposite effects on sexual arousal has been suggested for the selective serotonin reuptake-inhibitor (SSRI) paroxetine and the selective dopamine and noradrenaline reuptake-inhibitor (SDNRI) bupropion. To further elucidate the effects of antidepressant-related alterations of neural attention networks, we investigated 18 healthy males under subchronic administration (7 d) of paroxetine (20 mg), bupropion (150 mg) and placebo within a randomized placebo-controlled cross-over double-blind functional magnetic resonance imaging (fMRI) design during an established preceding attention task. Neuropsychological effects beyond the fMRI-paradigm were assessed by measuring alertness and divided attention. Comparing preceding attention periods of salient vs. neutral pictures, we revealed congruent effects of both drugs vs. placebo within the anterior midcingulate cortex, dorsolateral prefrontal cortex, anterior prefrontal cortex, superior temporal gyrus, anterior insula and the thalamus. Relatively decreased activation in this network was paralleled by slower reaction times in the divided attention task in both verum conditions compared to placebo. Our results suggest similar effects of antidepressant treatments on behavioural and neural attentional functioning by diverging neurochemical pathways. Concurrent alterations of brain regions within a fronto-parietal and cingulo-opercular attention network for top-down control could point to basic neural mechanisms of antidepressant action irrespective of receptor profiles.

Aberrant Modulation of Brain Oscillatory Activity and Attentional Impairment in Attention-Deficit/Hyperactivity Disorder.

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Lenartowicz, Agatha; Mazaheri, Ali; Jensen, Ole; Loo, Sandra K

2018-01-01

Electroencephalography and magnetoencephalography are noninvasive neuroimaging techniques that have been used extensively to study various resting-state and cognitive processes in the brain. The purpose of this review is to highlight a number of recent studies that have investigated the alpha band (8-12 Hz) oscillatory activity present in magnetoencephalography and electroencephalography, to provide new insights into the maladaptive network activity underlying attentional impairments in attention-deficit/hyperactivity disorder (ADHD). Studies reviewed demonstrate that event-related decrease in alpha is attenuated during visual selective attention, primarily in ADHD inattentive type, and is often significantly associated with accuracy and reaction time during task performance. Furthermore, aberrant modulation of alpha activity has been reported across development and may have abnormal or atypical lateralization patterns in ADHD. Modulations in the alpha band thus represent a robust, relatively unexplored putative biomarker of attentional impairment and a strong prospect for future studies aimed at examining underlying neural mechanisms and treatment response among individuals with ADHD. Potential limitations of its use as a diagnostic biomarker and directions for future research are discussed. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Assessing the heritability of attentional networks

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Fossella John A

2001-09-01

Full Text Available Abstract Background Current efforts to study the genetics of higher functions have been lacking appropriate phenotypes to describe cognition. One of the problems is that many cognitive concepts for which there is a single word (e.g. attention have been shown to be related to several anatomical networks. Recently we have developed an Attention Network Test (ANT that provides a separate measure for each of three anatomically defined attention networks. In this small scale study, we ran 26 pairs of MZ and DZ twins in an effort to determine if any of these networks show sufficient evidence of heritability to warrant further exploration of their genetic basis. Results The efficiency of the executive attention network, that mediates stimulus and response conflict, shows sufficient heritability to warrant further study. Alerting and overall reaction time show some evidence for heritability and in our study the orienting network shows no evidence of heritability. Conclusions These results suggest that genetic variation contributes to normal individual differences in higher order executive attention involving dopamine rich frontal areas including the anterior cingulate. At least the executive portion of the ANT may serve as a valid endophenotype for larger twin studies and subsequent molecular genetic analysis in normal subject populations.

Network Theory and Effects of Transcranial Brain Stimulation Methods on the Brain Networks

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Sema Demirci

2014-12-01

Full Text Available In recent years, there has been a shift from classic localizational approaches to new approaches where the brain is considered as a complex system. Therefore, there has been an increase in the number of studies involving collaborations with other areas of neurology in order to develop methods to understand the complex systems. One of the new approaches is graphic theory that has principles based on mathematics and physics. According to this theory, the functional-anatomical connections of the brain are defined as a network. Moreover, transcranial brain stimulation techniques are amongst the recent research and treatment methods that have been commonly used in recent years. Changes that occur as a result of applying brain stimulation techniques on physiological and pathological networks help better understand the normal and abnormal functions of the brain, especially when combined with techniques such as neuroimaging and electroencephalography. This review aims to provide an overview of the applications of graphic theory and related parameters, studies conducted on brain functions in neurology and neuroscience, and applications of brain stimulation systems in the changing treatment of brain network models and treatment of pathological networks defined on the basis of this theory.

A biased competition account of attention and memory in Alzheimer's disease.

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Finke, Kathrin; Myers, Nicholas; Bublak, Peter; Sorg, Christian

2013-10-19

The common view of Alzheimer's disease (AD) is that of an age-related memory disorder, i.e. declarative memory deficits are the first signs of the disease and associated with progressive brain changes in the medial temporal lobes and the default mode network. However, two findings challenge this view. First, new model-based tools of attention research have revealed that impaired selective attention accompanies memory deficits from early pre-dementia AD stages on. Second, very early distributed lesions of lateral parietal networks may cause these attention deficits by disrupting brain mechanisms underlying attentional biased competition. We suggest that memory and attention impairments might indicate disturbances of a common underlying neurocognitive mechanism. We propose a unifying account of impaired neural interactions within and across brain networks involved in attention and memory inspired by the biased competition principle. We specify this account at two levels of analysis: at the computational level, the selective competition of representations during both perception and memory is biased by AD-induced lesions; at the large-scale brain level, integration within and across intrinsic brain networks, which overlap in parietal and temporal lobes, is disrupted. This account integrates a large amount of previously unrelated findings of changed behaviour and brain networks and favours a brain mechanism-centred view on AD.

Memory networks supporting retrieval effort and retrieval success under conditions of full and divided attention.

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Skinner, Erin I; Fernandes, Myra A; Grady, Cheryl L

2009-01-01

We used a multivariate analysis technique, partial least squares (PLS), to identify distributed patterns of brain activity associated with retrieval effort and retrieval success. Participants performed a recognition memory task under full attention (FA) or two different divided attention (DA) conditions during retrieval. Behaviorally, recognition was disrupted when a word, but not digit-based distracting task, was performed concurrently with retrieval. PLS was used to identify patterns of brain activation that together covaried with the three memory conditions and which were functionally connected with activity in the right hippocampus to produce successful memory performance. Results indicate that activity in the right dorsolateral frontal cortex increases during conditions of DA at retrieval, and that successful memory performance in the DA-digit condition is associated with activation of the same network of brain regions functionally connected to the right hippocampus, as under FA, which increases with increasing memory performance. Finally, DA conditions that disrupt successful memory performance (DA-word) interfere with recruitment of both retrieval-effort and retrieval-success networks.

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

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Richiardi, Jonas; Altmann, Andre; Milazzo, Anna-Clare; Chang, Catie; Chakravarty, M Mallar; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Bromberg, Uli; Büchel, Christian; Conrod, Patricia; Fauth-Bühler, Mira; Flor, Herta; Frouin, Vincent; Gallinat, Jürgen; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Lemaître, Hervé; Mann, Karl F; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomáš; Pausova, Zdenka; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Spanagel, Rainer; Ströhle, Andreas; Schumann, Gunter; Hawrylycz, Mike; Poline, Jean-Baptiste; Greicius, Michael D

2015-06-12

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function. Copyright © 2015, American Association for the Advancement of Science.

Dynamic reconfiguration of human brain functional networks through neurofeedback.

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Haller, Sven; Kopel, Rotem; Jhooti, Permi; Haas, Tanja; Scharnowski, Frank; Lovblad, Karl-Olof; Scheffler, Klaus; Van De Ville, Dimitri

2013-11-01

Recent fMRI studies demonstrated that functional connectivity is altered following cognitive tasks (e.g., learning) or due to various neurological disorders. We tested whether real-time fMRI-based neurofeedback can be a tool to voluntarily reconfigure brain network interactions. To disentangle learning-related from regulation-related effects, we first trained participants to voluntarily regulate activity in the auditory cortex (training phase) and subsequently asked participants to exert learned voluntary self-regulation in the absence of feedback (transfer phase without learning). Using independent component analysis (ICA), we found network reconfigurations (increases in functional network connectivity) during the neurofeedback training phase between the auditory target region and (1) the auditory pathway; (2) visual regions related to visual feedback processing; (3) insula related to introspection and self-regulation and (4) working memory and high-level visual attention areas related to cognitive effort. Interestingly, the auditory target region was identified as the hub of the reconfigured functional networks without a-priori assumptions. During the transfer phase, we again found specific functional connectivity reconfiguration between auditory and attention network confirming the specific effect of self-regulation on functional connectivity. Functional connectivity to working memory related networks was no longer altered consistent with the absent demand on working memory. We demonstrate that neurofeedback learning is mediated by widespread changes in functional connectivity. In contrast, applying learned self-regulation involves more limited and specific network changes in an auditory setup intended as a model for tinnitus. Hence, neurofeedback training might be used to promote recovery from neurological disorders that are linked to abnormal patterns of brain connectivity. Copyright © 2013 Elsevier Inc. All rights reserved.

Brain anatomical network and intelligence.

Directory of Open Access Journals (Sweden)

Yonghui Li

2009-05-01

Full Text Available Intuitively, higher intelligence might be assumed to correspond to more efficient information transfer in the brain, but no direct evidence has been reported from the perspective of brain networks. In this study, we performed extensive analyses to test the hypothesis that individual differences in intelligence are associated with brain structural organization, and in particular that higher scores on intelligence tests are related to greater global efficiency of the brain anatomical network. We constructed binary and weighted brain anatomical networks in each of 79 healthy young adults utilizing diffusion tensor tractography and calculated topological properties of the networks using a graph theoretical method. Based on their IQ test scores, all subjects were divided into general and high intelligence groups and significantly higher global efficiencies were found in the networks of the latter group. Moreover, we showed significant correlations between IQ scores and network properties across all subjects while controlling for age and gender. Specifically, higher intelligence scores corresponded to a shorter characteristic path length and a higher global efficiency of the networks, indicating a more efficient parallel information transfer in the brain. The results were consistently observed not only in the binary but also in the weighted networks, which together provide convergent evidence for our hypothesis. Our findings suggest that the efficiency of brain structural organization may be an important biological basis for intelligence.

Deep hierarchical attention network for video description

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Li, Shuohao; Tang, Min; Zhang, Jun

2018-03-01

Pairing video to natural language description remains a challenge in computer vision and machine translation. Inspired by image description, which uses an encoder-decoder model for reducing visual scene into a single sentence, we propose a deep hierarchical attention network for video description. The proposed model uses convolutional neural network (CNN) and bidirectional LSTM network as encoders while a hierarchical attention network is used as the decoder. Compared to encoder-decoder models used in video description, the bidirectional LSTM network can capture the temporal structure among video frames. Moreover, the hierarchical attention network has an advantage over single-layer attention network on global context modeling. To make a fair comparison with other methods, we evaluate the proposed architecture with different types of CNN structures and decoders. Experimental results on the standard datasets show that our model has a more superior performance than the state-of-the-art techniques.

Brain anatomical networks in world class gymnasts: a DTI tractography study.

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Wang, Bin; Fan, Yuanyuan; Lu, Min; Li, Shumei; Song, Zheng; Peng, Xiaoling; Zhang, Ruibin; Lin, Qixiang; He, Yong; Wang, Jun; Huang, Ruiwang

2013-01-15

The excellent motor skills of world class gymnasts amaze everyone. People marvel at the way they precisely control their movements and wonder how the brain structure and function of these elite athletes differ from those of non-athletes. In this study, we acquired diffusion images from thirteen world class gymnasts and fourteen matched controls, constructed their anatomical networks, and calculated the topological properties of each network based on graph theory. From a connectivity-based analysis, we found that most of the edges with increased connection density in the champions were linked to brain regions that are located in the sensorimotor, attentional, and default-mode systems. From graph-based metrics, we detected significantly greater global and local efficiency but shorter characteristic path length in the anatomical networks of the champions compared with the controls. Moreover, in the champions we found a significantly higher nodal degree and greater regional efficiency in several brain regions that correspond to motor and attention functions. These included the left precentral gyrus, left postcentral gyrus, right anterior cingulate gyrus and temporal lobes. In addition, we revealed an increase in the mean fractional anisotropy of the corticospinal tract in the champions, possibly in response to long-term gymnastic training. Our study indicates that neuroanatomical adaptations and plastic changes occur in gymnasts' brain anatomical networks either in response to long-term intensive gymnastic training or as an innate predisposition or both. Our findings may help to explain gymnastic skills at the highest levels of performance and aid in understanding the neural mechanisms that distinguish expert gymnasts from novices. Copyright © 2012 Elsevier Inc. All rights reserved.

Antiretroviral treatment is associated with increased attentional load-dependent brain activation in HIV patients.

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Chang, L; Yakupov, R; Nakama, H; Stokes, B; Ernst, T

2008-06-01

The purpose of this paper was to determine whether antiretroviral medications, especially the nucleoside analogue reverse transcriptase inhibitors, lead to altered brain activation due to their potential neurotoxic effects in patients with human immunodeficiency virus (HIV) infection. Forty-two right-handed men were enrolled in three groups: seronegative controls (SN, n = 18), HIV subjects treated with antiretroviral medications (HIV+ARV, n = 12), or not treated with antiretroviral medications (HIV+NARV, n = 12). Each subject performed a set of visual attention tasks with increasing difficulty or load (tracking two, three or four balls) during functional magnetic resonance imaging. HIV subjects, both groups combined, showed greater load-dependent increases in brain activation in the right frontal regions compared to SN (p-corrected = 0.006). HIV+ARV additionally showed greater load-dependent increases in activation compared to SN in bilateral superior frontal regions (p-corrected = 0.032) and a lower percent accuracy on the performance of the most difficult task (tracking four balls). Region of interest analyses further demonstrated that SN showed load-dependent decreases (with repeated trials despite increasing difficulty), while HIV subjects showed load-dependent increases in activation with the more difficult tasks, especially those on ARVs. These findings suggest that chronic ARV treatments may lead to greater requirement of the attentional network reserve and hence less efficient usage of the network and less practice effects in these HIV patients. As the brain has a limited reserve capacity, exhausting the reserve capacity in HIV+ARV would lead to declined performance with more difficult tasks that require more attention.

Alterations in Normal Aging Revealed by Cortical Brain Network Constructed Using IBASPM.

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Li, Wan; Yang, Chunlan; Shi, Feng; Wang, Qun; Wu, Shuicai; Lu, Wangsheng; Li, Shaowu; Nie, Yingnan; Zhang, Xin

2018-04-16

Normal aging has been linked with the decline of cognitive functions, such as memory and executive skills. One of the prominent approaches to investigate the age-related alterations in the brain is by examining the cortical brain connectome. IBASPM is a toolkit to realize individual atlas-based volume measurement. Hence, this study seeks to determine what further alterations can be revealed by cortical brain networks formed by IBASPM-extracted regional gray matter volumes. We found the reduced strength of connections between the superior temporal pole and middle temporal pole in the right hemisphere, global hubs as the left fusiform gyrus and right Rolandic operculum in the young and aging groups, respectively, and significantly reduced inter-module connection of one module in the aging group. These new findings are consistent with the phenomenon of normal aging mentioned in previous studies and suggest that brain network built with the IBASPM could provide supplementary information to some extent. The individualization of morphometric features extraction deserved to be given more attention in future cortical brain network research.

Personal and Impersonal Stimuli Differentially Engage Brain Networks during Moral Reasoning

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Xue, Shao-Wei; Wang, Yan; Tang, Yi-Yuan

2013-01-01

Moral decision making has recently attracted considerable attention as a core feature of all human endeavors. Previous functional magnetic resonance imaging studies about moral judgment have identified brain areas associated with cognitive or emotional engagement. Here, we applied graph theory-based network analysis of event-related potentials…

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

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Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Multilayer Brain Networks

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Vaiana, Michael; Muldoon, Sarah Feldt

2018-01-01

The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

Magnetoencephalographic alpha band connectivity reveals differential default mode network interactions during focused attention and open monitoring meditation

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Marzetti, Laura; Di Lanzo, Claudia; Zappasodi, Filippo; Chella, Federico; Raffone, Antonino; Pizzella, Vittorio

2014-01-01

According to several conceptualizations of meditation, the interplay between brain systems associated to self-related processing, attention and executive control is crucial for meditative states and related traits. We used magnetoencephalography (MEG) to investigate such interplay in a highly selected group of “virtuoso” meditators (Theravada Buddhist monks), with long-term training in the two main meditation styles: focused attention (FA) and open monitoring (OM) meditation. Specifically, we investigated the differences between FA meditation, OM meditation and resting state in the coupling between the posterior cingulate cortex, core node of the Default Mode Network (DMN) implicated in mind wandering and self-related processing, and the whole brain, with a recently developed phase coherence approach. Our findings showed a state dependent coupling of posterior cingulate cortex (PCC) to nodes of the DMN and of the executive control brain network in the alpha frequency band (8–12 Hz), related to different attentional and cognitive control processes in FA and OM meditation, consistently with the putative role of alpha band synchronization in the functional mechanisms for attention and consciousness. The coupling of PCC with left medial prefrontal cortex (lmPFC) and superior frontal gyrus characterized the contrast between the two meditation styles in a way that correlated with meditation expertise. These correlations may be related to a higher mindful observing ability and a reduced identification with ongoing mental activity in more expert meditators. Notably, different styles of meditation and different meditation expertise appeared to modulate the dynamic balance between fronto-parietal (FP) and DMN networks. Our results support the idea that the interplay between the DMN and the FP network in the alpha band is crucial for the transition from resting state to different meditative states. PMID:25360102

Functional MRI studies of the neural mechanisms of human brain attentional networks

International Nuclear Information System (INIS)

Hao Jing; Li Kuncheng; Chen Qi; Wang Yan; Peng Xiaozhe; Zhou Xiaolin

2005-01-01

Objective: To identify the neural mechanisms of the anterior attention network (AAN) and posterior attention network (PAN) , investigate the possible interaction between them with event-related functional MRI(ER-fMRI). Methods: Eight right-handed healthy volunteers participated in the experiment designed with inhibition of return in visual orienting and Stroop color-word interference effect. The fMRI data were collected on Siemens 1.5 T Sonata MRI systems and analyzed by AFNI to generate the activation map. Results: The data sets from 6 of 8 subjects were used in the study. The functional localizations of the Stroop and IOR, which manifest the function of the AAN and PAN respectively, were consistent with previous imaging researches. On cued locations, left inferior parietal lobule (IPL), area MT/V5, right dorsolateral prefrontal cortex (DLPFC) and left anterior cingulated cortex (ACC) were significantly activated. On uncued locations, right superior parietal lobule (SPL) and bilateral area MT/V5 were significantly activated. Conclusion: The AAN exerts control over the PAN, while its function can be in turn modulated by the PAN. There are interaction between the AAN and PAN. In addition, it is also proved that ER-fMRI is a feasible method to revise preexisting cognitive model and theory. (authors)

The brain's silent messenger: using selective attention to decode human thought for brain-based communication.

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Naci, Lorina; Cusack, Rhodri; Jia, Vivian Z; Owen, Adrian M

2013-05-29

The interpretation of human thought from brain activity, without recourse to speech or action, is one of the most provoking and challenging frontiers of modern neuroscience. In particular, patients who are fully conscious and awake, yet, due to brain damage, are unable to show any behavioral responsivity, expose the limits of the neuromuscular system and the necessity for alternate forms of communication. Although it is well established that selective attention can significantly enhance the neural representation of attended sounds, it remains, thus far, untested as a response modality for brain-based communication. We asked whether its effect could be reliably used to decode answers to binary (yes/no) questions. Fifteen healthy volunteers answered questions (e.g., "Do you have brothers or sisters?") in the fMRI scanner, by selectively attending to the appropriate word ("yes" or "no"). Ninety percent of the answers were decoded correctly based on activity changes within the attention network. The majority of volunteers conveyed their answers with less than 3 min of scanning, suggesting that this technique is suited for communication in a reasonable amount of time. Formal comparison with the current best-established fMRI technique for binary communication revealed improved individual success rates and scanning times required to detect responses. This novel fMRI technique is intuitive, easy to use in untrained participants, and reliably robust within brief scanning times. Possible applications include communication with behaviorally nonresponsive patients.

Pro-cognitive drug effects modulate functional brain network organization

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Giessing, Carsten; Thiel, Christiane M.

2012-01-01

Previous studies document that cholinergic and noradrenergic drugs improve attention, memory and cognitive control in healthy subjects and patients with neuropsychiatric disorders. In humans neural mechanisms of cholinergic and noradrenergic modulation have mainly been analyzed by investigating drug-induced changes of task-related neural activity measured with functional magnetic resonance imaging (fMRI). Endogenous neural activity has often been neglected. Further, although drugs affect the coupling between neurons, only a few human studies have explicitly addressed how drugs modulate the functional connectome, i.e., the functional neural interactions within the brain. These studies have mainly focused on synchronization or correlation of brain activations. Recently, there are some drug studies using graph theory and other new mathematical approaches to model the brain as a complex network of interconnected processing nodes. Using such measures it is possible to detect not only focal, but also subtle, widely distributed drug effects on functional network topology. Most important, graph theoretical measures also quantify whether drug-induced changes in topology or network organization facilitate or hinder information processing. Several studies could show that functional brain integration is highly correlated with behavioral performance suggesting that cholinergic and noradrenergic drugs which improve measures of cognitive performance should increase functional network integration. The purpose of this paper is to show that graph theory provides a mathematical tool to develop theory-driven biomarkers of pro-cognitive drug effects, and also to discuss how these approaches can contribute to the understanding of the role of cholinergic and noradrenergic modulation in the human brain. Finally we discuss the “global workspace” theory as a theoretical framework of pro-cognitive drug effects and argue that pro-cognitive effects of cholinergic and noradrenergic drugs

Reward processing in the value-driven attention network: reward signals tracking cue identity and location.

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Anderson, Brian A

2017-03-01

Through associative reward learning, arbitrary cues acquire the ability to automatically capture visual attention. Previous studies have examined the neural correlates of value-driven attentional orienting, revealing elevated activity within a network of brain regions encompassing the visual corticostriatal loop [caudate tail, lateral occipital complex (LOC) and early visual cortex] and intraparietal sulcus (IPS). Such attentional priority signals raise a broader question concerning how visual signals are combined with reward signals during learning to create a representation that is sensitive to the confluence of the two. This study examines reward signals during the cued reward training phase commonly used to generate value-driven attentional biases. High, compared with low, reward feedback preferentially activated the value-driven attention network, in addition to regions typically implicated in reward processing. Further examination of these reward signals within the visual system revealed information about the identity of the preceding cue in the caudate tail and LOC, and information about the location of the preceding cue in IPS, while early visual cortex represented both location and identity. The results reveal teaching signals within the value-driven attention network during associative reward learning, and further suggest functional specialization within different regions of this network during the acquisition of an integrated representation of stimulus value. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Improvement of postoperative cognitive dysfunction and attention network function of patients with ischemic cerebrovascular disease via dexmedetomidine.

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Zhang, Jingchao; Wang, Guoliang; Zhang, Fangxiang; Zhao, Qian

2018-03-01

The protective effect of dexmedetomidine on cognitive dysfunction and decreased attention network function of patients with ischemic cerebrovascular disease after stenting was investigated. Fifty-eight patients with ischemic cerebrovascular disease undergoing stenting in Guizhou Provincial People's Hospital were selected and randomly divided into control group (n=29) and dexmedetomidine group (n=29). The dexmedetomidine group was treated with dexmedetomidine before induced anesthesia, while the control group was given the same dose of normal saline; and the normal volunteers of the same age were selected as the normal group (n=29). At 3 days after operation, the levels of serum S100B and nerve growth factor (NGF) in each group were detected using the enzyme-linked immunosorbent assay, and the level of brain-derived neurotrophic factor (BDNF) was detected via western blotting. Montreal cognitive assessment (MoCA) and attention network test (ANT) were performed. Moreover, the cognitive function and attention network function, and the effects of dexmedetomidine on cognitive function and attention network function were evaluated. The concentrations of serum S100B and NGF in dexmedetomidine group was lower than those in control group (Pfunction scores, attention scores, delayed memory scores, targeted network efficiency and executive control network efficiency in dexmedetomidine group were obviously higher than those in control group (Pcognitive function and attention network function of patients with ischemic cerebrovascular disease have a certain degree of damage, and the preoperative administration of dexmedetomidine can effectively improve the patient's cognitive dysfunction and attention network function after operation.

Shapley ratings in brain networks

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Rolf Kötter

2007-11-01

Full Text Available Recent applications of network theory to brain networks as well as the expanding empirical databases of brain architecture spawn an interest in novel techniques for analyzing connectivity patterns in the brain. Treating individual brain structures as nodes in a directed graph model permits the application of graph theoretical concepts to the analysis of these structures within their large-scale connectivity networks. In this paper, we explore the application of concepts from graph and game theory toward this end. Specifically, we utilize the Shapley value principle, which assigns a rank to players in a coalition based upon their individual contributions to the collective profit of that coalition, to assess the contributions of individual brain structures to the graph derived from the global connectivity network. We report Shapley values for variations of a prefrontal network, as well as for a visual cortical network, which had both been extensively investigated previously. This analysis highlights particular nodes as strong or weak contributors to global connectivity. To understand the nature of their contribution, we compare the Shapley values obtained from these networks and appropriate controls to other previously described nodal measures of structural connectivity. We find a strong correlation between Shapley values and both betweenness centrality and connection density. Moreover, a stepwise multiple linear regression analysis indicates that approximately 79% of the variance in Shapley values obtained from random networks can be explained by betweenness centrality alone. Finally, we investigate the effects of local lesions on the Shapley ratings, showing that the present networks have an immense structural resistance to degradation. We discuss our results highlighting the use of such measures for characterizing the organization and functional role of brain networks.

Shared visual attention and memory systems in the Drosophila brain.

Directory of Open Access Journals (Sweden)

Bruno van Swinderen

Full Text Available BACKGROUND: Selective attention and memory seem to be related in human experience. This appears to be the case as well in simple model organisms such as the fly Drosophila melanogaster. Mutations affecting olfactory and visual memory formation in Drosophila, such as in dunce and rutabaga, also affect short-term visual processes relevant to selective attention. In particular, increased optomotor responsiveness appears to be predictive of visual attention defects in these mutants. METHODOLOGY/PRINCIPAL FINDINGS: To further explore the possible overlap between memory and visual attention systems in the fly brain, we screened a panel of 36 olfactory long term memory (LTM mutants for visual attention-like defects using an optomotor maze paradigm. Three of these mutants yielded high dunce-like optomotor responsiveness. We characterized these three strains by examining their visual distraction in the maze, their visual learning capabilities, and their brain activity responses to visual novelty. We found that one of these mutants, D0067, was almost completely identical to dunce(1 for all measures, while another, D0264, was more like wild type. Exploiting the fact that the LTM mutants are also Gal4 enhancer traps, we explored the sufficiency for the cells subserved by these elements to rescue dunce attention defects and found overlap at the level of the mushroom bodies. Finally, we demonstrate that control of synaptic function in these Gal4 expressing cells specifically modulates a 20-30 Hz local field potential associated with attention-like effects in the fly brain. CONCLUSIONS/SIGNIFICANCE: Our study uncovers genetic and neuroanatomical systems in the fly brain affecting both visual attention and odor memory phenotypes. A common component to these systems appears to be the mushroom bodies, brain structures which have been traditionally associated with odor learning but which we propose might be also involved in generating oscillatory brain activity

Integration and segregation of large-scale brain networks during short-term task automatization.

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Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Brain networks that track musical structure.

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Janata, Petr

2005-12-01

As the functional neuroimaging literature grows, it becomes increasingly apparent that music and musical activities engage diverse regions of the brain. In this paper I discuss two studies to illustrate that exactly which brain areas are observed to be responsive to musical stimuli and tasks depends on the tasks and the methods used to describe the tasks and the stimuli. In one study, subjects listened to polyphonic music and were asked to either orient their attention selectively to individual instruments or in a divided or holistic manner across multiple instruments. The network of brain areas that was recruited changed subtly with changes in the task instructions. The focus of the second study was to identify brain regions that follow the pattern of movement of a continuous melody through the tonal space defined by the major and minor keys of Western tonal music. Such an area was identified in the rostral medial prefrontal cortex. This observation is discussed in the context of other neuroimaging studies that implicate this region in inwardly directed mental states involving decisions about the self, autobiographical memory, the cognitive regulation of emotion, affective responses to musical stimuli, and familiarity judgments about musical stimuli. Together with observations that these regions are among the last to atrophy in Alzheimer disease, and that these patients appear to remain responsive to autobiographically salient musical stimuli, very early evidence is emerging from the literature for the hypothesis that the rostral medial prefrontal cortex is a node that is important for binding music with memories within a broader music-responsive network.

Nicotine increases brain functional network efficiency.

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Wylie, Korey P; Rojas, Donald C; Tanabe, Jody; Martin, Laura F; Tregellas, Jason R

2012-10-15

Despite the use of cholinergic therapies in Alzheimer's disease and the development of cholinergic strategies for schizophrenia, relatively little is known about how the system modulates the connectivity and structure of large-scale brain networks. To better understand how nicotinic cholinergic systems alter these networks, this study examined the effects of nicotine on measures of whole-brain network communication efficiency. Resting state fMRI was acquired from fifteen healthy subjects before and after the application of nicotine or placebo transdermal patches in a single blind, crossover design. Data, which were previously examined for default network activity, were analyzed with network topology techniques to measure changes in the communication efficiency of whole-brain networks. Nicotine significantly increased local efficiency, a parameter that estimates the network's tolerance to local errors in communication. Nicotine also significantly enhanced the regional efficiency of limbic and paralimbic areas of the brain, areas which are especially altered in diseases such as Alzheimer's disease and schizophrenia. These changes in network topology may be one mechanism by which cholinergic therapies improve brain function. Published by Elsevier Inc.

Impairment of attention networks in patients with untreated hyperthyroidism.

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Yuan, Lili; Tian, Yanghua; Zhang, Fangfang; Dai, Fang; Luo, Li; Fan, Jin; Wang, Kai

2014-06-27

Attention disorders are common symptoms in patients with untreated hyperthyroidism. Nevertheless, it is unknown whether they represent a global attention deficit or selective impairment of attention networks. Thirty-seven patients with hyperthyroidism were recruited and underwent the Attention Network Test (ANT), which provided measures of three independent attention networks (alerting, orienting and executive control), before being treated with methimazole. This study demonstrated that patients with untreated hyperthyroidism had significant deficits in the alerting and executive control networks. Interestingly, a significant positive association was also found between T4 level and the value of the executive network in patients with hyperthyroidism. These results suggest that the patients with hyperthyroidism may not just exist a specific impairment of attention networks, and there was some relationship between the level of T4, not T3 or TSH, and the value of the executive control network in patients with hyperthyroidism. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Understanding emotion with brain networks.

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Pessoa, Luiz

2018-02-01

Emotional processing appears to be interlocked with perception, cognition, motivation, and action. These interactions are supported by the brain's large-scale non-modular anatomical and functional architectures. An important component of this organization involves characterizing the brain in terms of networks. Two aspects of brain networks are discussed: brain networks should be considered as inherently overlapping (not disjoint) and dynamic (not static). Recent work on multivariate pattern analysis shows that affective dimensions can be detected in the activity of distributed neural systems that span cortical and subcortical regions. More broadly, the paper considers how we should think of causation in complex systems like the brain, so as to inform the relationship between emotion and other mental aspects, such as cognition.

Brain Activity Associated With Attention Deficits Following Chemotherapy for Childhood Acute Lymphoblastic Leukemia.

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Fellah, Slim; Cheung, Yin T; Scoggins, Matthew A; Zou, Ping; Sabin, Noah D; Pui, Ching-Hon; Robison, Leslie L; Hudson, Melissa M; Ogg, Robert J; Krull, Kevin R

2018-05-21

The impact of contemporary chemotherapy treatment for childhood acute lymphoblastic leukemia on central nervous system activity is not fully appreciated. Neurocognitive testing and functional magnetic resonance imaging (fMRI) were obtained in 165 survivors five or more years postdiagnosis (average age = 14.4 years, 7.7 years from diagnosis, 51.5% males). Chemotherapy exposure was measured as serum concentration of methotrexate following high-dose intravenous injection. Neurocognitive testing included measures of attention and executive function. fMRI was obtained during completion of two tasks, the continuous performance task (CPT) and the attention network task (ANT). Image analysis was performed using Statistical Parametric Mapping software, with contrasts targeting sustained attention, alerting, orienting, and conflict. All statistical tests were two-sided. Compared with population norms, survivors demonstrated impairment on number-letter switching (P < .001, a measure of cognitive flexibility), which was associated with treatment intensity (P = .048). Task performance during fMRI was associated with neurocognitive dysfunction across multiple tasks. Regional brain activation was lower in survivors diagnosed at younger ages for the CPT (bilateral parietal and temporal lobes) and the ANT (left parietal and right hippocampus). With higher serum methotrexate exposure, CPT activation decreased in the right temporal and bilateral frontal and parietal lobes, but ANT alerting activation increased in the ventral frontal, insula, caudate, and anterior cingulate. Brain activation during attention and executive function tasks was associated with serum methotrexate exposure and age at diagnosis. These findings provide evidence for compromised and compensatory changes in regional brain function that may help clarify the neural substrates of cognitive deficits in acute lymphoblastic leukemia survivors.

Spinal Cord Injury Disrupts Resting-State Networks in the Human Brain.

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Hawasli, Ammar H; Rutlin, Jerrel; Roland, Jarod L; Murphy, Rory K J; Song, Sheng-Kwei; Leuthardt, Eric C; Shimony, Joshua S; Ray, Wilson Z

2018-03-15

Despite 253,000 spinal cord injury (SCI) patients in the United States, little is known about how SCI affects brain networks. Spinal MRI provides only structural information with no insight into functional connectivity. Resting-state functional MRI (RS-fMRI) quantifies network connectivity through the identification of resting-state networks (RSNs) and allows detection of functionally relevant changes during disease. Given the robust network of spinal cord afferents to the brain, we hypothesized that SCI produces meaningful changes in brain RSNs. RS-fMRIs and functional assessments were performed on 10 SCI subjects. Blood oxygen-dependent RS-fMRI sequences were acquired. Seed-based correlation mapping was performed using five RSNs: default-mode (DMN), dorsal-attention (DAN), salience (SAL), control (CON), and somatomotor (SMN). RSNs were compared with normal control subjects using false-discovery rate-corrected two way t tests. SCI reduced brain network connectivity within the SAL, SMN, and DMN and disrupted anti-correlated connectivity between CON and SMN. When divided into separate cohorts, complete but not incomplete SCI disrupted connectivity within SAL, DAN, SMN and DMN and between CON and SMN. Finally, connectivity changed over time after SCI: the primary motor cortex decreased connectivity with the primary somatosensory cortex, the visual cortex decreased connectivity with the primary motor cortex, and the visual cortex decreased connectivity with the sensory parietal cortex. These unique findings demonstrate the functional network plasticity that occurs in the brain as a result of injury to the spinal cord. Connectivity changes after SCI may serve as biomarkers to predict functional recovery following an SCI and guide future therapy.

Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

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Wang, Xun-Heng; Li, Lihua

2015-01-01

Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

Altered temporal features of intrinsic connectivity networks in boys with combined type of attention deficit hyperactivity disorder

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Wang, Xun-Heng, E-mail: xhwang@hdu.edu.cn [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China); School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096 (China); Li, Lihua [College of Life Information Science and Instrument Engineering, Hangzhou Dianzi University, Hangzhou 310018 (China)

2015-05-15

Highlights: • Temporal patterns within ICNs provide new way to investigate ADHD brains. • ADHD exhibits enhanced temporal activities within and between ICNs. • Network-wise ALFF influences functional connectivity between ICNs. • Univariate patterns within ICNs are correlated to behavior scores. - Abstract: Purpose: Investigating the altered temporal features within and between intrinsic connectivity networks (ICNs) for boys with attention-deficit/hyperactivity disorder (ADHD); and analyzing the relationships between altered temporal features within ICNs and behavior scores. Materials and methods: A cohort of boys with combined type of ADHD and a cohort of age-matched healthy boys were recruited from ADHD-200 Consortium. All resting-state fMRI datasets were preprocessed and normalized into standard brain space. Using general linear regression, 20 ICNs were taken as spatial templates to analyze the time-courses of ICNs for each subject. Amplitude of low frequency fluctuations (ALFFs) were computed as univariate temporal features within ICNs. Pearson correlation coefficients and node strengths were computed as bivariate temporal features between ICNs. Additional correlation analysis was performed between temporal features of ICNs and behavior scores. Results: ADHD exhibited more activated network-wise ALFF than normal controls in attention and default mode-related network. Enhanced functional connectivities between ICNs were found in ADHD. The network-wise ALFF within ICNs might influence the functional connectivity between ICNs. The temporal pattern within posterior default mode network (pDMN) was positively correlated to inattentive scores. The subcortical network, fusiform-related DMN and attention-related networks were negatively correlated to Intelligence Quotient (IQ) scores. Conclusion: The temporal low frequency oscillations of ICNs in boys with ADHD were more activated than normal controls during resting state; the temporal features within ICNs could

Acupuncture, the limbic system, and the anticorrelated networks of the brain.

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Hui, Kathleen K S; Marina, Ovidiu; Liu, Jing; Rosen, Bruce R; Kwong, Kenneth K

2010-10-28

The study of the mechanism of acupuncture action was revolutionized by the use of functional magnetic resonance imaging (fMRI). Over the past decade, our fMRI studies of healthy subjects have contributed substantially to elucidating the central effect of acupuncture on the human brain. These studies have shown that acupuncture stimulation, when associated with sensations comprising deqi, evokes deactivation of a limbic-paralimbic-neocortical network, which encompasses the limbic system, as well as activation of somatosensory brain regions. These networks closely match the default mode network and the anti-correlated task-positive network described in the literature. We have also shown that the effect of acupuncture on the brain is integrated at multiple levels, down to the brainstem and cerebellum. Our studies support the hypothesis that the effect of acupuncture on the brain goes beyond the effect of attention on the default mode network or the somatosensory stimulation of acupuncture needling. The amygdala and hypothalamus, in particular, show decreased activation during acupuncture stimulation that is not commonly associated with default mode network activity. At the same time, our research shows that acupuncture stimulation needs to be done carefully, limiting stimulation when the resulting sensations are very strong or when sharp pain is elicited. When acupuncture induced sharp pain, our studies show that the deactivation was attenuated or reversed in direction. Our results suggest that acupuncture mobilizes the functionally anti-correlated networks of the brain to mediate its actions, and that the effect is dependent on the psychophysical response. In this work we also discuss multiple avenues of future research, including the role of neurotransmitters, the effect of different acupuncture techniques, and the potential clinical application of our research findings to disease states including chronic pain, major depression, schizophrenia, autism, and Alzheimer

ORIENTING OF ATTENTION: THEN AND NOW1

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Posner, Michael I.

2014-01-01

It is nearly 35 years since I gave the 7th Sir Frederick Bartlett lecture at Oxford University. This was published as a paper entitled Orienting of Attention in the Quarterly Journal (1980, 32: 3–25). The topic was then primarily in Psychology, but now equally often in Neuroscience. This paper summarizes the background of the reaction time methods used in the original paper and findings that emerged later on the sensory consequences of orienting, mainly in the visual system. It then discusses the brain network which is the source of the sensory amplification and other brain networks that are involved in attention. Next, it reviews studies of the development of attentional networks in early life. Finally, it indicates how the new tools available to explore the human brain can lead to further progress. PMID:25176352

Internal and external attention and the default mode network.

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Scheibner, Hannah J; Bogler, Carsten; Gleich, Tobias; Haynes, John-Dylan; Bermpohl, Felix

2017-03-01

Focused attention meditations have been shown to improve psychological health and wellbeing and are nowadays an integral part of many psychotherapies. While research on the neural correlates of focused attention meditation is increasing, findings vary on whether meditations are associated with high or low activity in the default mode network (DMN). To clarify the relationship between focused attention meditation and the activity in DMN regions, it may be helpful to distinguish internal and external attention as well as different phases within one meditation: During focused attention meditation, the practitioner switches between mindful attention, mind-wandering and refocusing. Here, we employed a thought-probe paradigm to study the neural correlates of these different phases. Twenty healthy, meditation naïve participants were introduced to external (mindfulness of sound) and internal (mindfulness of breathing) attention meditation and then practiced the meditation at home for four consecutive days. They then performed the same focused attention meditations during fMRI scanning, in four runs alternating between internal and external attention. At pseudorandom intervals, participants were asked whether they had just been focused on the task (mindful attention) or had been distracted (mind-wandering). During mindful attention, brain regions typically associated with the DMN, such as the medial prefrontal cortex, posterior cingulate cortex and left temporoparietal junction showed significantly less neural activation compared to mind-wandering phases. Reduced activity of the DMN was found during both external and internal attention, with stronger deactivation in the posterior cingulate cortex during internal attention compared to external attention. Moreover, refocusing after mind-wandering was associated with activity in the left inferior frontal gyrus. Our results support the theory that mindful attention is associated with reduced DMN activity compared to mind

Developing a Novel Eye Tracking Paradigm to Assess Mild Traumatic Brain Injury: A Feasibility Study of the Bethesda Eye and Attention Measure (BEAM)

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2012-10-01

alerting, executive, and gap networks (Fan, et al., 2008; Fan, et al., 2005; Fan, et al., 2002; Fan & Posner, 2004; Fernandez- Duque & Posner, 2001... Duque , D., & Posner, M. I. (2001). Brain imaging of attentional networks in normal and pathological states. Journal of Clinical and Experimental

Modulation of attentional networks by food-related disinhibition.

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Hege, Maike A; Stingl, Krunoslav T; Veit, Ralf; Preissl, Hubert

2017-07-01

The risk of weight gain is especially related to disinhibition, which indicates the responsiveness to external food stimuli with associated disruptions in eating control. We adapted a food-related version of the attention network task and used functional magnetic resonance imaging to study the effects of disinhibition on attentional networks in 19 normal-weight participants. High disinhibition scores were associated with a rapid reorienting response to food pictures after invalid cueing and with an enhanced alerting effect of a warning cue signalizing the upcoming appearance of a food picture. Imaging data revealed activation of a right-lateralized ventral attention network during reorienting. The faster the reorienting and the higher the disinhibition score, the less activation of this network was observed. The alerting contrast showed activation in visual, temporo-parietal and anterior sites. These modulations of attentional networks by food-related disinhibition might be related to an attentional bias to energy dense and palatable food and increased intake of food in disinhibited individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

Defining nodes in complex brain networks

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Matthew Lawrence Stanley

2013-11-01

Full Text Available Network science holds great promise for expanding our understanding of the human brain in health, disease, development, and aging. Network analyses are quickly becoming the method of choice for analyzing functional MRI data. However, many technical issues have yet to be confronted in order to optimize results. One particular issue that remains controversial in functional brain network analyses is the definition of a network node. In functional brain networks a node represents some predefined collection of brain tissue, and an edge measures the functional connectivity between pairs of nodes. The characteristics of a node, chosen by the researcher, vary considerably in the literature. This manuscript reviews the current state of the art based on published manuscripts and highlights the strengths and weaknesses of three main methods for defining nodes. Voxel-wise networks are constructed by assigning a node to each, equally sized brain area (voxel. The fMRI time-series recorded from each voxel is then used to create the functional network. Anatomical methods utilize atlases to define the nodes based on brain structure. The fMRI time-series from all voxels within the anatomical area are averaged and subsequently used to generate the network. Functional activation methods rely on data from traditional fMRI activation studies, often from databases, to identify network nodes. Such methods identify the peaks or centers of mass from activation maps to determine the location of the nodes. Small (~10-20 millimeter diameter spheres located at the coordinates of the activation foci are then applied to the data being used in the network analysis. The fMRI time-series from all voxels in the sphere are then averaged, and the resultant time series is used to generate the network. We attempt to clarify the discussion and move the study of complex brain networks forward. While the correct method to be used remains an open, possibly unsolvable question that

Caffeine Modulates Attention Network Function

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Brunye, Tad T.; Mahoney, Caroline R.; Lieberman, Harris R.; Taylor, Holly A.

2010-01-01

The present work investigated the effects of caffeine (0 mg, 100 mg, 200 mg, 400 mg) on a flanker task designed to test Posner's three visual attention network functions: alerting, orienting, and executive control [Posner, M. I. (2004). "Cognitive neuroscience of attention". New York, NY: Guilford Press]. In a placebo-controlled, double-blind…

Source space analysis of event-related dynamic reorganization of brain networks.

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Ioannides, Andreas A; Dimitriadis, Stavros I; Saridis, George A; Voultsidou, Marotesa; Poghosyan, Vahe; Liu, Lichan; Laskaris, Nikolaos A

2012-01-01

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

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Wu, Kai; Taki, Yasuyuki; Sato, Kazunori; Hashizume, Hiroshi; Sassa, Yuko; Takeuchi, Hikaru; Thyreau, Benjamin; He, Yong; Evans, Alan C; Li, Xiaobo; Kawashima, Ryuta; Fukuda, Hiroshi

2013-01-01

Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI) was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

Topological organization of functional brain networks in healthy children: differences in relation to age, sex, and intelligence.

Directory of Open Access Journals (Sweden)

Kai Wu

Full Text Available Recent studies have demonstrated developmental changes of functional brain networks derived from functional connectivity using graph theoretical analysis, which has been rapidly translated to studies of brain network organization. However, little is known about sex- and IQ-related differences in the topological organization of functional brain networks during development. In this study, resting-state fMRI (rs-fMRI was used to map the functional brain networks in 51 healthy children. We then investigated the effects of age, sex, and IQ on economic small-world properties and regional nodal properties of the functional brain networks. At a global level of whole networks, we found significant age-related increases in the small-worldness and local efficiency, significant higher values of the global efficiency in boys compared with girls, and no significant IQ-related difference. Age-related increases in the regional nodal properties were found predominately in the frontal brain regions, whereas the parietal, temporal, and occipital brain regions showed age-related decreases. Significant sex-related differences in the regional nodal properties were found in various brain regions, primarily related to the default mode, language, and vision systems. Positive correlations between IQ and the regional nodal properties were found in several brain regions related to the attention system, whereas negative correlations were found in various brain regions primarily involved in the default mode, emotion, and language systems. Together, our findings of the network topology of the functional brain networks in healthy children and its relationship with age, sex, and IQ bring new insights into the understanding of brain maturation and cognitive development during childhood and adolescence.

The developing brain in a multitasking world.

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Rothbart, Mary K; Posner, Michael I

2015-03-01

To understand the problem of multitasking, it is necessary to examine the brain's attention networks that underlie the ability to switch attention between stimuli and tasks and to maintain a single focus among distractors. In this paper we discuss the development of brain networks related to the functions of achieving the alert state, orienting to sensory events, and developing self-control. These brain networks are common to everyone, but their efficiency varies among individuals and reflects both genes and experience. Training can alter brain networks. We consider two forms of training: (1) practice in tasks that involve particular networks, and (2) changes in brain state through such practices as meditation that may influence many networks. Playing action video games and multitasking are themselves methods of training the brain that can lead to improved performance but also to overdependence on media activity. We consider both of these outcomes and ideas about how to resist overdependence on media. Overall, our paper seeks to inform the reader about what has been learned about attention that can influence multitasking over the course of development.

Neural, electrophysiological and anatomical basis of brain-network variability and its characteristic changes in mental disorders.

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Zhang, Jie; Cheng, Wei; Liu, Zhaowen; Zhang, Kai; Lei, Xu; Yao, Ye; Becker, Benjamin; Liu, Yicen; Kendrick, Keith M; Lu, Guangming; Feng, Jianfeng

2016-08-01

ratio of intra- to inter-community structural connectivity. Application of the mesoscale variability measure to multicentre datasets of three mental disorders and matched controls involving 1180 subjects reveals that those regions demonstrating extreme, i.e. highest/lowest variability in controls are most liable to change in mental disorders. Specifically, we draw attention to the identification of diametrically opposing patterns of variability changes between schizophrenia and attention deficit hyperactivity disorder/autism. Regions of the default-mode network demonstrate lower variability in patients with schizophrenia, but high variability in patients with autism/attention deficit hyperactivity disorder, compared with respective controls. In contrast, subcortical regions, especially the thalamus, show higher variability in schizophrenia patients, but lower variability in patients with attention deficit hyperactivity disorder. The changes in variability of these regions are also closely related to symptom scores. Our work provides insights into the dynamic organization of the resting brain and how it changes in brain disorders. The nodal variability measure may also be potentially useful as a predictor for learning and neural rehabilitation. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Specialization in the default mode: Task-induced brain deactivations dissociate between visual working memory and attention.

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Mayer, Jutta S; Roebroeck, Alard; Maurer, Konrad; Linden, David E J

2010-01-01

The idea of an organized mode of brain function that is present as default state and suspended during goal-directed behaviors has recently gained much interest in the study of human brain function. The default mode hypothesis is based on the repeated observation that certain brain areas show task-induced deactivations across a wide range of cognitive tasks. In this event-related functional resonance imaging study we tested the default mode hypothesis by comparing common and selective patterns of BOLD deactivation in response to the demands on visual attention and working memory (WM) that were independently modulated within one task. The results revealed task-induced deactivations within regions of the default mode network (DMN) with a segregation of areas that were additively deactivated by an increase in the demands on both attention and WM, and areas that were selectively deactivated by either high attentional demand or WM load. Attention-selective deactivations appeared in the left ventrolateral and medial prefrontal cortex and the left lateral temporal cortex. Conversely, WM-selective deactivations were found predominantly in the right hemisphere including the medial-parietal, the lateral temporo-parietal, and the medial prefrontal cortex. Moreover, during WM encoding deactivated regions showed task-specific functional connectivity. These findings demonstrate that task-induced deactivations within parts of the DMN depend on the specific characteristics of the attention and WM components of the task. The DMN can thus be subdivided into a set of brain regions that deactivate indiscriminately in response to cognitive demand ("the core DMN") and a part whose deactivation depends on the specific task. 2009 Wiley-Liss, Inc.

BrainNet Viewer: a network visualization tool for human brain connectomics.

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Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

BrainNet Viewer: a network visualization tool for human brain connectomics.

Directory of Open Access Journals (Sweden)

Mingrui Xia

Full Text Available The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI, we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/.

Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli

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Field, Brent A.; Buck, Cara L.; McClure, Samuel M.; Nystrom, Leigh E.; Kahneman, Daniel; Cohen, Jonathan D.

2015-01-01

Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value. PMID:26158468

Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli.

Directory of Open Access Journals (Sweden)

Brent A Field

Full Text Available Studies of subjective well-being have conventionally relied upon self-report, which directs subjects' attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure by using functional magnetic resonance imaging (fMRI to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly the activity of brain mechanisms thought to represent hedonic value.

Attention Networks and Consciousness

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Michael ePosner

2012-03-01

Full Text Available The term consciousness is an important one in the vernacular of the western literature in many fields. It is no wonder that scientists have assumed that consciousness will be found as a component of the human brain and that we will come to understand its neural basis. However, there is rather little in common between consciousness as the neurologist would use it to diagnose the vegetative state, how the feminist would use it to support raising male consciousness of the economic plight of women and as the philosopher would use it when defining the really hard question of the subjective state of awareness induced by sensory qualities. When faced with this kind of problem it is usual to subdivide the term into more manageable perhaps partly operational definitions. Three meanings that capture aspects of consciousness are: (1 the neurology of the state of mind allowing coherent orientation to time and place (2 the selection of sensory or memorial information for awareness and (3 the voluntary control over overt responses. In each of these cases the mechanisms of consciousness overlap with one or more of the attentional networks that have been studied with the methods of cognitive neuroscience. In this paper we explore t

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

International Nuclear Information System (INIS)

Zhou Changsong; Zemanova, Lucia; Zamora-Lopez, Gorka; Hilgetag, Claus C; Kurths, Juergen

2007-01-01

The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

Energy Technology Data Exchange (ETDEWEB)

Zhou Changsong [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zemanova, Lucia [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zamora-Lopez, Gorka [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Hilgetag, Claus C [Jacobs University Bremen, Campus Ring 6, Rm 116, D-28759 Bremen (Germany); Kurths, Juergen [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany)

2007-06-15

The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.

Effects of motivation on reward and attentional networks: an fMRI study.

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Ivanov, Iliyan; Liu, Xun; Clerkin, Suzanne; Schulz, Kurt; Friston, Karl; Newcorn, Jeffrey H; Fan, Jin

2012-11-01

Existing evidence suggests that reward and attentional networks function in concert and that activation in one system influences the other in a reciprocal fashion; however, the nature of these influences remains poorly understood. We therefore developed a three-component task to assess the interaction effects of reward anticipation and conflict resolution on the behavioral performance and the activation of brain reward and attentional systems. Sixteen healthy adult volunteers aged 21-45 years were scanned with functional magnetic resonance imaging (fMRI) while performing the task. A two-way repeated measures analysis of variance (ANOVA) with cue (reward vs. non-reward) and target (congruent vs. incongruent) as within-subjects factors was used to test for main and interaction effects. Neural responses to anticipation, conflict, and reward outcomes were tested. Behaviorally there were main effects of both reward cue and target congruency on reaction time. Neuroimaging results showed that reward anticipation and expected reward outcomes activated components of the attentional networks, including the inferior parietal and occipital cortices, whereas surprising non-rewards activated the frontoinsular cortex bilaterally and deactivated the ventral striatum. In turn, conflict activated a broad network associated with cognitive control and motor functions. Interaction effects showed decreased activity in the thalamus, anterior cingulated gyrus, and middle frontal gyrus bilaterally when difficult conflict trials (e.g., incongruent targets) were preceded by reward cues; in contrast, the ventral striatum and orbitofrontal cortex showed greater activation during congruent targets preceded by reward cues. These results suggest that reward anticipation is associated with lower activation in attentional networks, possibly due to increased processing efficiency, whereas more difficult, conflict trials are associated with lower activity in regions of the reward system, possibly

Selective attentional deficit in essential tremor: Evidence from the attention network test.

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Pauletti, Caterina; Mannarelli, Daniela; De Lucia, Maria Caterina; Locuratolo, Nicoletta; Currà, Antonio; Missori, Paolo; Marinelli, Lucio; Fattapposta, Francesco

2015-11-01

The traditional view of essential tremor (ET) as a monosymptomatic and benign disorder has been reconsidered after patients with ET have been shown to experience cognitive deficits that are also related to attention. The Attention Network Test (ANT) is a rapid, widely used test to measure the efficiency of three attentional networks, i.e. alerting, orienting and executive, by evaluating reaction times (RTs) in response to visual stimuli. The aim of this study was to investigate attentional functioning in ET patients by means of the ANT. 21 non-demented patients with ET and 21 age- and sex-matched healthy controls performed the ANT. RT was significantly longer in ET patients than in controls (p attention in ET patients, probably owing to a dysfunction in the cerebello-thalamo-cortical loop. These selective attentional deficits are not related to clinical motor symptoms, contributing to shed further light on the clinical picture of ET. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cingulate, Frontal and Parietal Cortical Dysfunction in Attention-Deficit/Hyperactivity Disorder

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Bush, George

2011-01-01

Functional and structural neuroimaging have identified abnormalities of the brain that are likely to contribute to the neuropathophysiology of attention-deficit/hyperactivity disorder (ADHD). In particular, hypofunction of the brain regions comprising the cingulo-frontal-parietal (CFP) cognitive-attention network have been consistently observed across studies. These are major components of neural systems that are relevant to ADHD, including cognitive/attention networks, motor systems and reward/feedback-based processing systems. Moreover, these areas interact with other brain circuits that have been implicated in ADHD, such as the “default mode” resting state network. ADHD imaging data related to CFP network dysfunction will be selectively highlighted here to help facilitate its integration with the other information presented in this special issue. Together, these reviews will help shed light on the neurobiology of ADHD. PMID:21489409

Construction of Individual Morphological Brain Networks with Multiple Morphometric Features

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Chunlan Yang

2017-04-01

Full Text Available In recent years, researchers have increased attentions to the morphological brain network, which is generally constructed by measuring the mathematical correlation across regions using a certain morphometric feature, such as regional cortical thickness and voxel intensity. However, cerebral structure can be characterized by various factors, such as regional volume, surface area, and curvature. Moreover, most of the morphological brain networks are population-based, which has limitations in the investigations of individual difference and clinical applications. Hence, we have extended previous studies by proposing a novel method for realizing the construction of an individual-based morphological brain network through a combination of multiple morphometric features. In particular, interregional connections are estimated using our newly introduced feature vectors, namely, the Pearson correlation coefficient of the concatenation of seven morphometric features. Experiments were performed on a healthy cohort of 55 subjects (24 males aged from 20 to 29 and 31 females aged from 20 to 28 each scanned twice, and reproducibility was evaluated through test–retest reliability. The robustness of morphometric features was measured firstly to select the more reproducible features to form the connectomes. Then the topological properties were analyzed and compared with previous reports of different modalities. Small-worldness was observed in all the subjects at the range of the entire network sparsity (20–40%, and configurations were comparable with previous findings at the sparsity of 23%. The spatial distributions of the hub were found to be significantly influenced by the individual variances, and the hubs obtained by averaging across subjects and sparsities showed correspondence with previous reports. The intraclass coefficient of graphic properties (clustering coefficient = 0.83, characteristic path length = 0.81, betweenness centrality = 0.78 indicates

Network dynamics with BrainX(3): a large-scale simulation of the human brain network with real-time interaction.

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Arsiwalla, Xerxes D; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F M J

2015-01-01

BrainX(3) is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX(3) in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX(3) can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

Science.gov (United States)

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martinez, Enrique; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas. PMID:25759649

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

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Xerxes D. Arsiwalla

2015-02-01

Full Text Available BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimulations to observe reverberating network activity, simulate lesion dynamics or implement network analysis functions from a library of graph theoretic measures. BrainX3 can thus be used as a novel immersive platform for real-time exploration and analysis of dynamical activity patterns in brain networks, both at rest or in a task-related state, for discovery of signaling pathways associated to brain function and/or dysfunction and as a tool for virtual neurosurgery. Our results demonstrate these functionalities and shed insight on the dynamics of the resting-state attractor. Specifically, we found that a noisy network seems to favor a low firing attractor state. We also found that the dynamics of a noisy network is less resilient to lesions. Our simulations on TMS perturbations show that even though TMS inhibits most of the network, it also sparsely excites a few regions. This is presumably, due to anti-correlations in the dynamics and suggests that even a lesioned network can show sparsely distributed increased activity compared to healthy resting-state, over specific brain areas.

Potential language and attentional networks revealed through factor analysis of rCBF data measured with SPECT

DEFF Research Database (Denmark)

McLaughlin, T; Steinberg, B; Christensen, B

1992-01-01

's area (left hemisphere), when subjects listened to narrative speech, compared to white noise (baseline). No significant rCBF differences were detected with this test during dichotic stimulation vs. white noise. A more sophisticated statistical method (factor analysis) disclosed patterns of functionally...... brain networks involved in (I) auditory/linguistic, (II) attentional, and (III) visual imaging activity....

Dysfunctional whole brain networks in mild cognitive impairment patients: an fMRI study

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Liu, Zhenyu; Bai, Lijun; Dai, Ruwei; Zhong, Chongguang; Xue, Ting; You, Youbo; Tian, Jie

2012-03-01

Mild cognitive impairment (MCI) was recognized as the prodromal stage of Alzheimer's disease (AD). Recent researches have shown that cognitive and memory decline in AD patients is coupled with losses of small-world attributes. However, few studies pay attention to the characteristics of the whole brain networks in MCI patients. In the present study, we investigated the topological properties of the whole brain networks utilizing graph theoretical approaches in 16 MCI patients, compared with 18 age-matched healthy subjects as a control. Both MCI patients and normal controls showed small-world architectures, with large clustering coefficients and short characteristic path lengths. We detected significantly longer characteristic path length in MCI patients compared with normal controls at the low sparsity. The longer characteristic path lengths in MCI indicated disrupted information processing among distant brain regions. Compared with normal controls, MCI patients showed decreased nodal centrality in the brain areas of the angular gyrus, heschl gyrus, hippocampus and superior parietal gyrus, while increased nodal centrality in the calcarine, inferior occipital gyrus and superior frontal gyrus. These changes in nodal centrality suggested a widespread rewiring in MCI patients, which may be an integrated reflection of reorganization of the brain networks accompanied with the cognitive decline. Our findings may be helpful for further understanding the pathological mechanisms of MCI.

Dopamine Transporters in Striatum Correlate with Deactivation in the Default Mode Network during Visuospatial Attention

International Nuclear Information System (INIS)

Tomasi, D.; Fowler, J.; Tomasi, D.; Volkow, N.D.; Wang, R.L.; Telang, F.; Wang, Chang L.; Ernst, T.; Fowler, J.S.

2009-01-01

Dopamine and dopamine transporters (DAT, which regulate extracellular dopamine in the brain) are implicated in the modulation of attention but their specific roles are not well understood. Here we hypothesized that dopamine modulates attention by facilitation of brain deactivation in the default mode network (DMN). Thus, higher striatal DAT levels, which would result in an enhanced clearance of dopamine and hence weaker dopamine signals, would be associated to lower deactivation in the DMN during an attention task. For this purpose we assessed the relationship between DAT in striatum (measured with positron emission tomography and [ 11 C]cocaine used as DAT radiotracer) and brain activation and deactivation during a parametric visual attention task (measured with blood oxygenation level dependent functional magnetic resonance imaging) in healthy controls. We show that DAT availability in caudate and putamen had a negative correlation with deactivation in ventral parietal regions of the DMN (precuneus, BA 7) and a positive correlation with deactivation in a small region in the ventral anterior cingulate gyrus (BA 24/32). With increasing attentional load, DAT in caudate showed a negative correlation with load-related deactivation increases in precuneus. These findings provide evidence that dopamine transporters modulate neural activity in the DMN and anterior cingulate gyrus during visuospatial attention. Our findings suggest that dopamine modulates attention in part by regulating neuronal activity in posterior parietal cortex including precuneus (region involved in alertness) and cingulate gyrus (region deactivated in proportion to emotional interference). These findings suggest that the beneficial effects of stimulant medications (increase dopamine by blocking DAT) in inattention reflect in part their ability to facilitate the deactivation of the DMN.

BrainNetVis: analysis and visualization of brain functional networks.

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Tsiaras, Vassilis; Andreou, Dimitris; Tollis, Ioannis G

2009-01-01

BrainNetVis is an application, written in Java, that displays and analyzes synchronization networks from brain signals. The program implements a number of network indices and visualization techniques. We demonstrate its use through a case study of left hand and foot motor imagery. The data sets were provided by the Berlin BCI group. Using this program we managed to find differences between the average left hand and foot synchronization networks by comparing them with the average idle state synchronization network.

Source Space Analysis of Event-Related Dynamic Reorganization of Brain Networks

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Andreas A. Ioannides

2012-01-01

Full Text Available How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

IS ATTENTION AN APPROPRIATE CONCEPT FOR EXPLAINING BRAIN PROCESSES

NARCIS (Netherlands)

DALENOORT, GJ

In interpreting measurements of brain processes it is necessary to make the model used explicit. A concept such as attention cannot be used in the description of brain activities without a model of the relation of mental and neural processes.

Information processing speed and attention in multiple sclerosis: Reconsidering the Attention Network Test (ANT).

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Roth, Alexandra K; Denney, Douglas R; Lynch, Sharon G

2015-01-01

The Attention Network Test (ANT) assesses attention in terms of discrepancies between response times to items that differ in the burden they place on some facet of attention. However, simple arithmetic difference scores commonly used to capture these discrepancies fail to provide adequate control for information processing speed, leading to distorted findings when patient and control groups differ markedly in the speed with which they process and respond to stimulus information. This study examined attention networks in patients with multiple sclerosis (MS) using simple difference scores, proportional scores, and residualized scores that control for processing speed through statistical regression. Patients with relapsing-remitting (N = 20) or secondary progressive (N = 20) MS and healthy controls (N = 40) of similar age, education, and gender completed the ANT. Substantial differences between patients and controls were found on all measures of processing speed. Patients exhibited difficulties in the executive control network, but only when difference scores were considered. When deficits in information processing speed were adequately controlled using proportional or residualized score, deficits in the alerting network emerged. The effect sizes for these deficits were notably smaller than those for overall information processing speed and were also limited to patients with secondary progressive MS. Deficits in processing speed are more prominent in MS than those involving attention, and when the former are properly accounted for, differences in the latter are confined to the alerting network.

ATTENTIONAL NETWORKS AND SELECTIVE VISUAL SYSTEM

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ALEJANDRO CASTILLO MORENO

2006-05-01

Full Text Available In this paper we checked the principal researches and theories to explain the attention system functioning.We are going to start reviewing along time about the concept of attention, from filter theories andresources distributor theories, to the current theories in which attention is conceived as a control system.From this last point of view, we will emphasize on the attentional networks theory of Posner, thatproposes different systems to explain diverse aspects of attention, but they are related to each other. Atlast in this paper, we will mention experimental results that have been important to characterize theselective attentional mechanisms of the human visual system, using the attentional spotlight model forthis aim.

Network-dependent modulation of brain activity during sleep.

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Watanabe, Takamitsu; Kan, Shigeyuki; Koike, Takahiko; Misaki, Masaya; Konishi, Seiki; Miyauchi, Satoru; Miyahsita, Yasushi; Masuda, Naoki

2014-09-01

Brain activity dynamically changes even during sleep. A line of neuroimaging studies has reported changes in functional connectivity and regional activity across different sleep stages such as slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep. However, it remains unclear whether and how the large-scale network activity of human brains changes within a given sleep stage. Here, we investigated modulation of network activity within sleep stages by applying the pairwise maximum entropy model to brain activity obtained by functional magnetic resonance imaging from sleeping healthy subjects. We found that the brain activity of individual brain regions and functional interactions between pairs of regions significantly increased in the default-mode network during SWS and decreased during REM sleep. In contrast, the network activity of the fronto-parietal and sensory-motor networks showed the opposite pattern. Furthermore, in the three networks, the amount of the activity changes throughout REM sleep was negatively correlated with that throughout SWS. The present findings suggest that the brain activity is dynamically modulated even in a sleep stage and that the pattern of modulation depends on the type of the large-scale brain networks. Copyright © 2014 Elsevier Inc. All rights reserved.

Developmental process emerges from extended brain-body-behavior networks

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Byrge, Lisa; Sporns, Olaf; Smith, Linda B.

2014-01-01

Studies of brain connectivity have focused on two modes of networks: structural networks describing neuroanatomy and the intrinsic and evoked dependencies of functional networks at rest and during tasks. Each mode constrains and shapes the other across multiple time scales, and each also shows age-related changes. Here we argue that understanding how brains change across development requires understanding the interplay between behavior and brain networks: changing bodies and activities modify the statistics of inputs to the brain; these changing inputs mold brain networks; these networks, in turn, promote further change in behavior and input. PMID:24862251

Dynamic reorganization of human resting-state networks during visuospatial attention.

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Spadone, Sara; Della Penna, Stefania; Sestieri, Carlo; Betti, Viviana; Tosoni, Annalisa; Perrucci, Mauro Gianni; Romani, Gian Luca; Corbetta, Maurizio

2015-06-30

Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing "idling" activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a "prior" for attention selection.

Gender differences associated with orienting attentional networks in healthy subjects

Institute of Scientific and Technical Information of China (English)

LIU Gang; HU Pan-pan; FAN Jin; WANG Kai

2013-01-01

Background Selective attention is considered one of the main components of cognitive functioning.A number of studies have demonstrated gender differences in cognition.This study aimed to investigate the gender differences in selective attention in healthy subjects.Methods The present experiment examined the gender differences associated with the efficiency of three attentional networks:alerting,orienting,and executive control attention in 73 healthy subjects (38 males).All participants performed a modified version of the Attention Network Test (ANT).Results Females had higher orienting scores than males (t=2.172,P ＜0.05).Specifically,females were faster at covert orienting of attention to a spatially cued location.There were no gender differences between males and females in alerting (t=0.813,P ＞0.05) and executive control (t=0.945,P ＞0.05) attention networks.Conclusions There was a significant gender difference between males and females associated with the orienting network.Enhanced orienting attention in females may function to motivate females to direct their attention to a spatially cued location.

Hemispheric asymmetry of electroencephalography-based functional brain networks.

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Jalili, Mahdi

2014-11-12

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Disruption of functional networks in dyslexia: A whole-brain, data-driven analysis of connectivity

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Finn, Emily S.; Shen, Xilin; Holahan, John M.; Scheinost, Dustin; Lacadie, Cheryl; Papademetris, Xenophon; Shaywitz, Sally E.; Shaywitz, Bennett A.; Constable, R. Todd

2013-01-01

Background Functional connectivity analyses of fMRI data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which may result in mixing distinct activation timecourses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia. Methods Whole-brain connectivity was assessed in children (n = 75; 43 NI, 32 DYS) and adult (n = 104; 64 NI, 40 DYS) readers. Results Compared to NI readers, DYS readers showed divergent connectivity within the visual pathway and between visual association areas and prefrontal attention areas; increased right-hemisphere connectivity; reduced connectivity in the visual word-form area (part of the left fusiform gyrus specialized for printed words); and persistent connectivity to anterior language regions around the inferior frontal gyrus. Conclusions Together, findings suggest that NI readers are better able to integrate visual information and modulate their attention to visual stimuli, allowing them to recognize words based on their visual properties, while DYS readers recruit altered reading circuits and rely on laborious phonology-based “sounding out” strategies into adulthood. These results deepen our understanding of the neural basis of dyslexia and highlight the importance of synchrony between diverse brain regions for successful reading. PMID:24124929

Cortical networks involved in visual awareness independent of visual attention

OpenAIRE

Webb, Taylor W.; Igelström, Kajsa M.; Schurger, Aaron; Graziano, Michael S. A.

2016-01-01

Do specific areas of the brain participate in subjective visual experience? We measured brain activity in humans using fMRI. Participants were aware of a visual stimulus in one condition and unaware of it in another condition. The two conditions were balanced for their effect on visual attention. Specific brain areas were more active in the aware than in the unaware condition, suggesting they were involved in subjective awareness independent of attention. The largest cluster of activity was f...

Mechanism of Cerebralcare Granule® for Improving Cognitive Function in Resting-State Brain Functional Networks of Sub-healthy Subjects

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Jing Li

2017-07-01

Full Text Available Cerebralcare Granule® (CG, a Chinese herbal medicine, has been used to ameliorate cognitive impairment induced by ischemia or mental disorders. The ability of CG to improve health status and cognitive function has drawn researchers' attention, but the relevant brain circuits that underlie the ameliorative effects of CG remain unclear. The present study aimed to explore the underlying neurobiological mechanisms of CG in ameliorating cognitive function in sub-healthy subjects using resting-state functional magnetic resonance imaging (fMRI. Thirty sub-healthy participants were instructed to take one 2.5-g package of CG three times a day for 3 months. Clinical cognitive functions were assessed with the Chinese Revised Wechsler Adult Intelligence Scale (WAIS-RC and Wechsler Memory Scale (WMS, and fMRI scans were performed at baseline and the end of intervention. Functional brain network data were analyzed by conventional network metrics (CNM and frequent subgraph mining (FSM. Then 21 other sub-healthy participants were enrolled as a blank control group of cognitive functional. We found that administrating CG can improve the full scale of intelligence quotient (FIQ and Memory Quotient (MQ scores. At the same time, following CG treatment, in CG group, the topological properties of functional brain networks were altered in various frontal, temporal, occipital cortex regions, and several subcortical brain regions, including essential components of the executive attention network, the salience network, and the sensory-motor network. The nodes involved in the FSM results were largely consistent with the CNM findings, and the changes in nodal metrics correlated with improved cognitive function. These findings indicate that CG can improve sub-healthy subjects' cognitive function through altering brain functional networks. These results provide a foundation for future studies of the potential physiological mechanism of CG.

Spatiotemporal overlap between brain activation related to saccade preparation and attentional orienting.

NARCIS (Netherlands)

van der Lubbe, Robert Henricus Johannes; Neggers, Sebastiaan F.W.; Verleger, Rolf; Kenemans, J. Leon

2006-01-01

Recent brain imaging studies provided evidence that the brain areas involved with attentional orienting and the preparation of saccades largely overlap, which may indicate that focusing attention at a specific location can be considered as an unexecuted saccade towards that location (i.e. the

Anxiety type modulates immediate versus delayed engagement of attention-related brain regions.

Science.gov (United States)

Spielberg, Jeffrey M; De Leon, Angeline A; Bredemeier, Keith; Heller, Wendy; Engels, Anna S; Warren, Stacie L; Crocker, Laura D; Sutton, Bradley P; Miller, Gregory A

2013-09-01

Background Habituation of the fear response, critical for the treatment of anxiety, is inconsistently observed during exposure to threatening stimuli. One potential explanation for this inconsistency is differential attentional engagement with negatively valenced stimuli as a function of anxiety type. Methods The present study tested this hypothesis by examining patterns of neural habituation associated with anxious arousal, characterized by panic symptoms and immediate engagement with negatively valenced stimuli, versus anxious apprehension, characterized by engagement in worry to distract from negatively valenced stimuli. Results As predicted, the two anxiety types evidenced distinct patterns of attentional engagement. Anxious arousal was associated with immediate activation in attention-related brain regions that habituated over time, whereas anxious apprehension was associated with delayed activation in attention-related brain regions that occurred only after habituation in a worry-related brain region. Conclusions Results further elucidate mechanisms involved in attention to negatively valenced stimuli and indicate that anxiety is a heterogeneous construct with regard to attention to such stimuli.

Timing of the brain events underlying access to consciousness during the attentional blink.

Science.gov (United States)

Sergent, Claire; Baillet, Sylvain; Dehaene, Stanislas

2005-10-01

In the phenomenon of attentional blink, identical visual stimuli are sometimes fully perceived and sometimes not detected at all. This phenomenon thus provides an optimal situation to study the fate of stimuli not consciously perceived and the differences between conscious and nonconscious processing. We correlated behavioral visibility ratings and recordings of event-related potentials to study the temporal dynamics of access to consciousness. Intact early potentials (P1 and N1) were evoked by unseen words, suggesting that these brain events are not the primary correlates of conscious perception. However, we observed a rapid divergence around 270 ms, after which several brain events were evoked solely by seen words. Thus, we suggest that the transition toward access to consciousness relates to the optional triggering of a late wave of activation that spreads through a distributed network of cortical association areas.

Pain: a distributed brain information network?

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Hiroaki Mano

2015-01-01

Full Text Available Understanding how pain is processed in the brain has been an enduring puzzle, because there doesn't appear to be a single "pain cortex" that directly codes the subjective perception of pain. An emerging concept is that, instead, pain might emerge from the coordinated activity of an integrated brain network. In support of this view, Woo and colleagues present evidence that distinct brain networks support the subjective changes in pain that result from nociceptive input and self-directed cognitive modulation. This evidence for the sensitivity of distinct neural subsystems to different aspects of pain opens up the way to more formal computational network theories of pain.

The social brain network and autism.

Science.gov (United States)

Misra, Vivek

2014-04-01

Available research data in Autism suggests the role of a network of brain areas, often known as the 'social brain'. Recent studies highlight the role of genetic mutations as underlying patho-mechanism in Autism. This mini review, discusses the basic concepts behind social brain networks, theory of mind and genetic factors associated with Autism. It critically evaluates and explores the relationship between the behavioral outcomes and genetic factors providing a conceptual framework for understanding of autism.

Abnormal Ventral and Dorsal Attention Network Activity During Single and Dual Target Detection in Schizophrenia

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Amy M. Jimenez

2016-03-01

Full Text Available Early visual perception and attention are impaired in schizophrenia, and these deficits can be observed on target detection tasks. These tasks activate distinct ventral and dorsal brain networks which support stimulus-driven and goal-directed attention, respectively. We used single and dual target rapid serial visual presentation (RSVP tasks during fMRI with an ROI approach to examine regions within these networks associated with target detection and the attentional blink (AB in 21 schizophrenia outpatients and 25 healthy controls. In both tasks, letters were targets and numbers were distractors. For the dual target task, the second target (T2 was presented at 3 different lags after the first target (T1 (lag1=100ms, lag3=300ms, lag7=700ms. For both single and dual target tasks, patients identified fewer targets than controls. For the dual target task, both groups showed the expected AB effect with poorer performance at lag 3 than at lags 1 or 7, and there was no group by lag interaction. During the single target task, patients showed abnormally increased deactivation of the temporo-parietal junction (TPJ, a key region of the ventral network. When attention demands were increased during the dual target task, patients showed overactivation of the posterior intraparietal cortex, a key dorsal network region, along with failure to deactivate TPJ. Results suggest inefficient and faulty suppression of salience-oriented processing regions, resulting in increased sensitivity to stimuli in general, and difficulty distinguishing targets from non-targets.

Development in attention functions and social processing: Evidence from the Attention Network Test.

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Federico, Francesca; Marotta, Andrea; Martella, Diana; Casagrande, Maria

2017-06-01

According to the attention network approach, attention is best understood in terms of three functionally and neuroanatomically distinct networks - alerting, orienting, and executive attention. Recent findings showed that social information influences the efficiency of these networks in adults. Using some social and non-social variants of the Attentional Network Test (ANT), this study was aimed to evaluate the development of the three attention networks in childhood, also assessing the development of the ability to manage social or non-social conflicting information. Sixty-six children (three groups of 6, 8, and 10 years of age) performed three variants of the original ANT, using fish, schematic, or real faces looking to the left or right as target and flanker stimuli. Results showed an improvement from 6 to 8 and 10 years of age in reaction time (RT) and accuracy, together with an improvement of executive control and a decrement in alerting. These developmental changes were not unique to social stimuli, and no differences were observed between social and no-social variants of the ANT. However, independently from the age of the children, a real face positively affected the executive control (as indexed by RTs) as compared to both a schematic face and a fish. Findings of this study suggest that attentional networks are still developing from 6 to 10 years of age and underline the importance of face information in modulating the efficiency of executive control. Statement of contribution What is already known? Younger children made more errors and slower reaction times (RTs) than older children, in line with the majority of the past selective attention studies. Younger children showed both greater conflict and alerting effect than older children. The prediction that younger children would display larger interference effects than older children was supported. What does this study add? Extending the findings observed in adults and children, independently from their age

An overview of attention deficits after paediatric traumatic brain injury.

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Ginstfeldt, Tim; Emanuelson, Ingrid

2010-01-01

Attention could be categorized into sustained, selective, shifting, divided and attention span. The primary objective was to evaluate the type of attention deficits that occurs after paediatric traumatic brain injury. Keywords were used such as 'attention', 'child', 'traumatic', 'brain' and 'injury' on MEDLINE articles published in 1991-2009. Articles found through MEDLINE were manually cross-referenced. Out of the examined categorizes, divided and sustained attention seem to be the most vulnerably, frequently displaying deficits in the children with TBI. Attention span seemed to be the most resistant and the shifting and selective categories falling somewhere in between. Most of the recovery is expected within the first year post-injury, even if some individuals continue to improve for years, and deficits often persist into adulthood. The attention domains are not affected to the same extent by TBI and this should be taken into consideration when evaluating a child. The commonly used tests also seem to differ in how sensitive they are in detecting deficits. The definition of attention domains and TBI would benefit to be stricter and agreed upon, to further facilitate research and rehabilitation programmes.

Large-Scale Brain Network Coupling Predicts Total Sleep Deprivation Effects on Cognitive Capacity.

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Yu Lei

Full Text Available Interactions between large-scale brain networks have received most attention in the study of cognitive dysfunction of human brain. In this paper, we aimed to test the hypothesis that the coupling strength of large-scale brain networks will reflect the pressure for sleep and will predict cognitive performance, referred to as sleep pressure index (SPI. Fourteen healthy subjects underwent this within-subject functional magnetic resonance imaging (fMRI study during rested wakefulness (RW and after 36 h of total sleep deprivation (TSD. Self-reported scores of sleepiness were higher for TSD than for RW. A subsequent working memory (WM task showed that WM performance was lower after 36 h of TSD. Moreover, SPI was developed based on the coupling strength of salience network (SN and default mode network (DMN. Significant increase of SPI was observed after 36 h of TSD, suggesting stronger pressure for sleep. In addition, SPI was significantly correlated with both the visual analogue scale score of sleepiness and the WM performance. These results showed that alterations in SN-DMN coupling might be critical in cognitive alterations that underlie the lapse after TSD. Further studies may validate the SPI as a potential clinical biomarker to assess the impact of sleep deprivation.

Approach of Complex Networks for the Determination of Brain Death

Institute of Scientific and Technical Information of China (English)

SUN Wei-Gang; CAO Jian-Ting; WANG Ru-Bin

2011-01-01

In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our Sndings might provide valuable insights on the determination of brain death.%@@ In clinical practice, brain death is the irreversible end of all brain activity.Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination.Brain functional networks constructed by correlation analysis axe derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated.Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state.Our findings might provide valuable insights on the determination of brain death.

Attention, predictions and expectations, and their violation: attentional control in the human brain

OpenAIRE

Vossel, Simone; Geng, Joy J.; Friston, Karl J.

2014-01-01

In the complex scenes of everyday life, our brains must select from among many competing inputs for perceptual synthesis—so that only the most relevant are fully processed and irrelevant (distracting) information is suppressed. At the same time, we must remain responsive to salient events outside our current focus of attention—and balancing these two processing modes is a fundamental task our brain constantly needs to solve.This Research Topic examines how attentional control is guided by sen...

Gaze-independent brain-computer interfaces based on covert attention and feature attention

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Treder, M. S.; Schmidt, N. M.; Blankertz, B.

2011-10-01

There is evidence that conventional visual brain-computer interfaces (BCIs) based on event-related potentials cannot be operated efficiently when eye movements are not allowed. To overcome this limitation, the aim of this study was to develop a visual speller that does not require eye movements. Three different variants of a two-stage visual speller based on covert spatial attention and non-spatial feature attention (i.e. attention to colour and form) were tested in an online experiment with 13 healthy participants. All participants achieved highly accurate BCI control. They could select one out of thirty symbols (chance level 3.3%) with mean accuracies of 88%-97% for the different spellers. The best results were obtained for a speller that was operated using non-spatial feature attention only. These results show that, using feature attention, it is possible to realize high-accuracy, fast-paced visual spellers that have a large vocabulary and are independent of eye gaze.

Brain networks of the imaginative mind: Dynamic functional connectivity of default and cognitive control networks relates to openness to experience.

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Beaty, Roger E; Chen, Qunlin; Christensen, Alexander P; Qiu, Jiang; Silvia, Paul J; Schacter, Daniel L

2018-02-01

Imagination and creative cognition are often associated with the brain's default network (DN). Recent evidence has also linked cognitive control systems to performance on tasks involving imagination and creativity, with a growing number of studies reporting functional interactions between cognitive control and DN regions. We sought to extend the emerging literature on brain dynamics supporting imagination by examining individual differences in large-scale network connectivity in relation to Openness to Experience, a personality trait typified by imagination and creativity. To this end, we obtained personality and resting-state fMRI data from two large samples of participants recruited from the United States and China, and we examined contributions of Openness to temporal shifts in default and cognitive control network interactions using multivariate structural equation modeling and dynamic functional network connectivity analysis. In Study 1, we found that Openness was related to the proportion of scan time (i.e., "dwell time") that participants spent in a brain state characterized by positive correlations among the default, executive, salience, and dorsal attention networks. Study 2 replicated and extended the effect of Openness on dwell time in a correlated brain state comparable to the state found in Study 1, and further demonstrated the robustness of this effect in latent variable models including fluid intelligence and other major personality factors. The findings suggest that Openness to Experience is associated with increased functional connectivity between default and cognitive control systems, a connectivity profile that may account for the enhanced imaginative and creative abilities of people high in Openness to Experience. © 2017 Wiley Periodicals, Inc.

Brain network disturbance related to posttraumatic stress and traumatic brain injury in veterans.

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Spielberg, Jeffrey M; McGlinchey, Regina E; Milberg, William P; Salat, David H

2015-08-01

Understanding the neural causes and consequences of posttraumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) is a high research priority, given the high rates of associated disability and suicide. Despite remarkable progress in elucidating the brain mechanisms of PTSD and mTBI, a comprehensive understanding of these conditions at the level of brain networks has yet to be achieved. The present study sought to identify functional brain networks and topological properties (measures of network organization and function) related to current PTSD severity and mTBI. Graph theoretic tools were used to analyze resting-state functional magnetic resonance imaging data from 208 veterans of Operation Enduring Freedom, Operation Iraqi Freedom, and Operation New Dawn, all of whom had experienced a traumatic event qualifying for PTSD criterion A. Analyses identified brain networks and topological network properties linked to current PTSD symptom severity, mTBI, and the interaction between PTSD and mTBI. Two brain networks were identified in which weaker connectivity was linked to higher PTSD re-experiencing symptoms, one of which was present only in veterans with comorbid mTBI. Re-experiencing was also linked to worse functional segregation (necessary for specialized processing) and diminished influence of key regions on the network, including the hippocampus. Findings of this study demonstrate that PTSD re-experiencing symptoms are linked to weakened connectivity in a network involved in providing contextual information. A similar relationship was found in a separate network typically engaged in the gating of working memory, but only in veterans with mTBI. Published by Elsevier Inc.

Attentional neural networks impairment in healthy aging

NARCIS (Netherlands)

Vazquez-Marrufo, Manuel; Luisa Benitez, Maria; Rodriguez-Gomez, Guillermo; Galvao-Carmona, Alejandro; Fernandez-Del Olmo, Aaron; Vaquero-Casares, Encarnacion

2011-01-01

Introduction. Diverse evidences have shown that the process of natural aging causes a decline in different cognitive functions, including among them the attentional process. Aim. To determine how the healthy aging affects to the different attentional networks. Subjects and methods. Two groups: young

Higher Physical Activity is Associated with Increased Attentional Network Connectivity in the Healthy Elderly

Directory of Open Access Journals (Sweden)

Geon Ha Kim

2016-08-01

Full Text Available The purpose of this study was to demonstrate the potential alterations in structural network properties related to physical activity (PA in healthy elderly. We recruited 76 elderly individuals with normal cognition from Samsung Medical Center in Seoul, Korea. All participants underwent the Cambridge Neuropsychological Test Automated Battery and 3.0T brain magnetic resonance imaging (MRI. Participants were subdivided into quartiles according to the International Physical Activity Questionnaire scores, which represents the amount of PA. Through graph theory based analyses, we compared global and local network topologies according to PA quartile. The higher PA group demonstrated better performance in speed processing compared to the lower PA group. Regional nodal strength also significantly increased in the higher PA group, which involved the bilateral middle frontal, bilateral inferior parietal, right medial orbitofrontal, right superior and middle temporal gyri. These results were further replicated when the highest and the lowest quartile groups were compared in terms of regional nodal strengths and local efficiency. Our findings that the regional nodal strengths associated with the attentional network were increased in the higher PA group suggest the preventive effects of PA on age-related cognitive decline, especially in attention.

A network of genes, genetic disorders, and brain areas.

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Satoru Hayasaka

Full Text Available The network-based approach has been used to describe the relationship among genes and various phenotypes, producing a network describing complex biological relationships. Such networks can be constructed by aggregating previously reported associations in the literature from various databases. In this work, we applied the network-based approach to investigate how different brain areas are associated to genetic disorders and genes. In particular, a tripartite network with genes, genetic diseases, and brain areas was constructed based on the associations among them reported in the literature through text mining. In the resulting network, a disproportionately large number of gene-disease and disease-brain associations were attributed to a small subset of genes, diseases, and brain areas. Furthermore, a small number of brain areas were found to be associated with a large number of the same genes and diseases. These core brain regions encompassed the areas identified by the previous genome-wide association studies, and suggest potential areas of focus in the future imaging genetics research. The approach outlined in this work demonstrates the utility of the network-based approach in studying genetic effects on the brain.

Cortical Network Dynamics of Perceptual Decision-Making in the Human Brain

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Markus eSiegel

2011-02-01

Full Text Available Goal-directed behavior requires the flexible transformation of sensory evidence about our environment into motor actions. Studies of perceptual decision-making have shown that this transformation is distributed across several widely separated brain regions. Yet, little is known about how decision-making emerges from the dynamic interactions among these regions. Here, we review a series of studies, in which we characterized the cortical network interactions underlying a perceptual decision process in the human brain. We used magnetoencephalography (MEG to measure the large-scale cortical population dynamics underlying each of the sub-processes involved in this decision: the encoding of sensory evidence and action plan, the mapping between the two, and the attentional selection of task-relevant evidence. We found that these sub-processes are mediated by neuronal oscillations within specific frequency ranges. Localized gamma-band oscillations in sensory and motor cortices reflect the encoding of the sensory evidence and motor plan. Large-scale oscillations across widespread cortical networks mediate the integrative processes connecting these local networks: Gamma- and beta-band oscillations across frontal, parietal and sensory cortices serve the selection of relevant sensory evidence and its flexible mapping onto action plans. In sum, our results suggest that perceptual decisions are mediated by oscillatory interactions within overlapping local and large-scale cortical networks.

Emotion Regulation and Complex Brain Networks: Association Between Expressive Suppression and Efficiency in the Fronto-Parietal Network and Default-Mode Network

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Junhao Pan

2018-03-01

Full Text Available Emotion regulation (ER refers to the “implementation of a conscious or non-conscious goal to start, stop or otherwise modulate the trajectory of an emotion” (Etkin et al., 2015. Whereas multiple brain areas have been found to be involved in ER, relatively little is known about whether and how ER is associated with the global functioning of brain networks. Recent advances in brain connectivity research using graph-theory based analysis have shown that the brain can be organized into complex networks composed of functionally or structurally connected brain areas. Global efficiency is one graphic metric indicating the efficiency of information exchange among brain areas and is utilized to measure global functioning of brain networks. The present study examined the relationship between trait measures of ER (expressive suppression (ES and cognitive reappraisal (CR and global efficiency in resting-state functional brain networks (the whole brain network and ten predefined networks using structural equation modeling (SEM. The results showed that ES was reliably associated with efficiency in the fronto-parietal network and default-mode network. The finding advances the understanding of neural substrates of ER, revealing the relationship between ES and efficient organization of brain networks.

Development of Attention Networks and Their Interactions in Childhood

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Pozuelos, Joan P.; Paz-Alonso, Pedro M.; Castillo, Alejandro; Fuentes, Luis J.; Rueda, M. Rosario

2014-01-01

In the present study, we investigated developmental trajectories of alerting, orienting, and executive attention networks and their interactions over childhood. Two cross-sectional experiments were conducted with different samples of 6-to 12-year-old children using modified versions of the attention network task (ANT). In Experiment 1 (N = 106),…

Spectral properties of the temporal evolution of brain network structure.

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Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Brain network clustering with information flow motifs

NARCIS (Netherlands)

Märtens, M.; Meier, J.M.; Hillebrand, Arjan; Tewarie, Prejaas; Van Mieghem, P.F.A.

2017-01-01

Recent work has revealed frequency-dependent global patterns of information flow by a network analysis of magnetoencephalography data of the human brain. However, it is unknown which properties on a small subgraph-scale of those functional brain networks are dominant at different frequencies bands.

[Attention system functions and their relationship with self-reported health in patients with brain damage due to tumor].

Science.gov (United States)

Egorov, V N; Razumnikova, O M; Perfil'ev, A M; Stupak, V V

2015-01-01

To compare parameters of attention in healthy people and patients with neoplasms in different regions of the cerebral cortex and to evaluate quality of life (QoL) indices with regard to impairment of different attention systems. Twenty patients with oncological lesions of the brain (mean age 56.5±8.8 years) who did not undergo surgery were studied. Tumor localization was confirmed using contrast-enhanced computed tomography, the tumor type was histologically verified. A control group included 18 healthy people matched for age, sex and education level. To determine attention system functions, we developed a computed version of the Attention Network Test. Error rate and reaction time for correct responses to the target stimulus, displayed along with neutral, congruent and incongruent signals, were the indicators of the efficacy of selective processes. QoL indices were assessed using SF-36 health survey questionnaire. The readiness to respond to incoming stimuli was mostly impaired in patients with brain tumors. Efficacy of executive attention, assessed as the increase in the number of errors in selection of visual stimuli, was decreased while temporary parameters of the functions of this system were not changed in patients compared to controls. The SF-36 total score was stable in patients with marked reduction in scores on the Role and Emotional Functioning scales. The most severe health impairment measured on the SF-36 scales of role/social emotional functioning and viability was recorded in patients with the lesions of frontal cortical areas compared to temporal/parietal areas. The relationship between SF-36 Health self-rating and attention systems was found. This finding puts the question of the importance of attention characteristics and QoL for survival prognosis of patients with brain tumors.

State-related functional integration and functional segregation brain networks in schizophrenia.

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Yu, Qingbao; Sui, Jing; Kiehl, Kent A; Pearlson, Godfrey; Calhoun, Vince D

2013-11-01

Altered topological properties of brain connectivity networks have emerged as important features of schizophrenia. The aim of this study was to investigate how the state-related modulations to graph measures of functional integration and functional segregation brain networks are disrupted in schizophrenia. Firstly, resting state and auditory oddball discrimination (AOD) fMRI data of healthy controls (HCs) and schizophrenia patients (SZs) were decomposed into spatially independent components (ICs) by group independent component analysis (ICA). Then, weighted positive and negative functional integration (inter-component networks) and functional segregation (intra-component networks) brain networks were built in each subject. Subsequently, connectivity strength, clustering coefficient, and global efficiency of all brain networks were statistically compared between groups (HCs and SZs) in each state and between states (rest and AOD) within group. We found that graph measures of negative functional integration brain network and several positive functional segregation brain networks were altered in schizophrenia during AOD task. The metrics of positive functional integration brain network and one positive functional segregation brain network were higher during the resting state than during the AOD task only in HCs. These findings imply that state-related characteristics of both functional integration and functional segregation brain networks are impaired in schizophrenia which provides new insight into the altered brain performance in this brain disorder. © 2013.

Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

Science.gov (United States)

Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

2018-04-01

Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

Functional evolution of new and expanded attention networks in humans.

Science.gov (United States)

Patel, Gaurav H; Yang, Danica; Jamerson, Emery C; Snyder, Lawrence H; Corbetta, Maurizio; Ferrera, Vincent P

2015-07-28

Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks.

Enhanced Network Efficiency of Functional Brain Networks in Primary Insomnia Patients

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Xiaofen Ma

2018-02-01

Full Text Available Accumulating evidence from neuroimaging studies suggests that primary insomnia (PI affects interregional neural coordination of multiple interacting functional brain networks. However, a complete understanding of the whole-brain network organization from a system-level perspective in PI is still lacking. To this end, we investigated in topological organization changes in brain functional networks in PI. 36 PI patients and 38 age-, sex-, and education-matched healthy controls were recruited. All participants underwent a series of neuropsychological assessments and resting-state functional magnetic resonance imaging scans. Individual whole-brain functional network were constructed and analyzed using graph theory-based network approaches. There were no significant differences with respect to age, sex, or education between groups (P > 0.05. Graph-based analyses revealed that participants with PI had a significantly higher total number of edges (P = 0.022, global efficiency (P = 0.014, and normalized global efficiency (P = 0.002, and a significantly lower normalized local efficiency (P = 0.042 compared with controls. Locally, several prefrontal and parietal regions, the superior temporal gyrus, and the thalamus exhibited higher nodal efficiency in participants with PI (P < 0.05, false discovery rate corrected. In addition, most of these regions showed increased functional connectivity in PI patients (P < 0.05, corrected. Finally, altered network efficiency was correlated with neuropsychological variables of the Epworth Sleepiness Scale and Insomnia Severity Index in patients with PI. PI is associated with abnormal organization of large-scale functional brain networks, which may account for memory and emotional dysfunction in people with PI. These findings provide novel implications for neural substrates associated with PI.

Evaluation of the attention network test using vibrotactile stimulations.

Science.gov (United States)

Salzer, Yael; Oron-Gilad, Tal; Henik, Avishai

2015-06-01

We report a vibrotactile version of the attention network test (ANT)-the tactile ANT (T-ANT). It has been questioned whether attentional components are modality specific or not. The T-ANT explores alertness, orienting, cognitive control, and their relationships, similar to its visual counterpart, in the tactile modality. The unique features of the T-ANT are in utilizing stimuli on a single plane-the torso-and replacing the original imperative flanker task with a tactile Simon task. Subjects wore a waist belt mounted with two vibrotactile stimulators situated on the back and positioned to the right and left of the spinal column. They responded by pressing keys with their right or left hand in reaction to the type of vibrotactile stimulation (pulsed/continuous signal). On a single trial, an alerting tone was followed by a short tactile (informative/noninformative) peripheral cue and an imperative tactile Simon task target. The T-ANT was compared with a variant of the ANT in which the flanker task was replaced with a visual Simon task. Experimental data showed effects of orienting over control only when the peripheral cues were informative. In contrast to the visual task, interactions between alertness and control or alertness and orienting were not found in the tactile task. A possible rationale for these results is discussed. The T-ANT allows examination of attentional processes among patients with tactile attentional deficits and patients with eyesight deficits who cannot take part in visual tasks. Technological advancement would enable implementation of the T-ANT in brain-imaging studies.

Lower cognitive reserve in the aging human immunodeficiency virus-infected brain.

Science.gov (United States)

Chang, Linda; Holt, John L; Yakupov, Renat; Jiang, Caroline S; Ernst, Thomas

2013-04-01

More HIV-infected individuals are living longer; however, how their brain function is affected by aging is not well understood. One hundred twenty-two men (56 seronegative control [SN] subjects, 37 HIV subjects with normal cognition [HIV+NC], 29 with HIV-associated neurocognitive disorder [HAND]) performed neuropsychological tests and had acceptable functional magnetic resonance imaging scans at 3 Tesla during tasks with increasing attentional load. With older age, SN and HIV+NC subjects showed increased activation in the left posterior (reserve, "bottom-up") attention network for low attentional-load tasks, and further increased activation in the left posterior and anterior ("top-down") attention network on intermediate (HIV+NC only) and high attentional-load tasks. HAND subjects had only age-dependent decreases in activation. Age-dependent changes in brain activation differed between the 3 groups, primarily in the left frontal regions (despite similar brain atrophy). HIV and aging act synergistically or interactively to exacerbate brain activation abnormalities in different brain regions, suggestive of a neuroadaptive mechanism in the attention network to compensate for declined neural efficiency. While the SN and HIV+NC subjects compensated for their declining attention with age by using reserve and "top-down" attentional networks, older HAND subjects were unable to compensate which resulted in cognitive decline. Copyright © 2013 Elsevier Inc. All rights reserved.

The Efficiency of a Small-World Functional Brain Network

Institute of Scientific and Technical Information of China (English)

ZHAO Qing-Bai; ZHANG Xiao-Fei; SUI Dan-Ni; ZHOU Zhi-Jin; CHEN Qi-Cai; TANG Yi-Yuan

2012-01-01

We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task.Functional brain networks are constructed by multichannel eventrelated potential data,in which the electrodes are the nodes and the functional connectivities between them are the edges.The results show that the correlation between small-world measures and reaction time is task-specific,such that in global imagery,there is a positive correlation between the clustering coefficient and reaction time,while in local imagery the average path length is positively correlated with the reaction time.This suggests that the efficiency of a functional brain network is task-dependent.%We investigate whether the small-world topology of a functional brain network means high information processing efficiency by calculating the correlation between the small-world measures of a functional brain network and behavioral reaction during an imagery task. Functional brain networks are constructed by multichannel event-related potential data, in which the electrodes are the nodes and the functional connectivities between them are the edges. The results show that the correlation between small-world measures and reaction time is task-specific, such that in global imagery, there is a positive correlation between the clustering coefficient and reaction time, while in local imagery the average path length is positively correlated with the reaction time. This suggests that the efficiency of a functional brain network is task-dependent.

Complex brain networks: From topological communities to clustered

Indian Academy of Sciences (India)

Complex brain networks: From topological communities to clustered dynamics ... Recent research has revealed a rich and complicated network topology in the cortical connectivity of mammalian brains. ... Pramana – Journal of Physics | News.

The Persistence of Experience: Prior Attentional and Emotional State Affects Network Functioning in a Target Detection Task.

Science.gov (United States)

Stern, Emily R; Muratore, Alexandra F; Taylor, Stephan F; Abelson, James L; Hof, Patrick R; Goodman, Wayne K

2015-09-01

Efficient, adaptive behavior relies on the ability to flexibly move between internally focused (IF) and externally focused (EF) attentional states. Despite evidence that IF cognitive processes such as event imagination comprise a significant amount of awake cognition, the consequences of internal absorption on the subsequent recruitment of brain networks during EF tasks are unknown. The present functional magnetic resonance imaging (fMRI) study employed a novel attentional state switching task. Subjects imagined positive and negative events (IF task) or performed a working memory task (EF task) before switching to a target detection (TD) task also requiring attention to external information, allowing for the investigation of neural functioning during external attention based on prior attentional state. There was a robust increase of activity in frontal, parietal, and temporal regions during TD when subjects were previously performing the EF compared with IF task, an effect that was most pronounced following negative IF. Additionally, dorsolateral prefrontal cortex was less negatively coupled with ventromedial prefrontal and posterior cingulate cortices during TD following IF compared with EF. These findings reveal the striking consequences for brain activity following immersion in an IF attentional state, which have strong implications for psychiatric disorders characterized by excessive internal focus. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Hierarchical nonlinear dynamics of human attention.

Science.gov (United States)

Rabinovich, Mikhail I; Tristan, Irma; Varona, Pablo

2015-08-01

Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cognitive Control Network Contributions to Memory-Guided Visual Attention.

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Rosen, Maya L; Stern, Chantal E; Michalka, Samantha W; Devaney, Kathryn J; Somers, David C

2016-05-01

Visual attentional capacity is severely limited, but humans excel in familiar visual contexts, in part because long-term memories guide efficient deployment of attention. To investigate the neural substrates that support memory-guided visual attention, we performed a set of functional MRI experiments that contrast long-term, memory-guided visuospatial attention with stimulus-guided visuospatial attention in a change detection task. Whereas the dorsal attention network was activated for both forms of attention, the cognitive control network(CCN) was preferentially activated during memory-guided attention. Three posterior nodes in the CCN, posterior precuneus, posterior callosal sulcus/mid-cingulate, and lateral intraparietal sulcus exhibited the greatest specificity for memory-guided attention. These 3 regions exhibit functional connectivity at rest, and we propose that they form a subnetwork within the broader CCN. Based on the task activation patterns, we conclude that the nodes of this subnetwork are preferentially recruited for long-term memory guidance of visuospatial attention. Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Resolving structural variability in network models and the brain.

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Florian Klimm

2014-03-01

Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

Task vs. rest-different network configurations between the coactivation and the resting-state brain networks.

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Di, Xin; Gohel, Suril; Kim, Eun H; Biswal, Bharat B

2013-01-01

There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest.

Brain Network Analysis from High-Resolution EEG Signals

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de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

EEG Brain Wave Activity at Rest and during Evoked Attention in Children with Attention-Deficit/Hyperactivity Disorder and Effects of Methylphenidate.

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Thomas, Bianca Lee; Viljoen, Margaretha

2016-01-01

The aim of this study was to assess baseline EEG brain wave activity in children with attention-deficit/hyperactivity disorder (ADHD) and to examine the effects of evoked attention and methylphenidate on this activity. Children with ADHD (n = 19) were tested while they were stimulant free and during a period in which they were on stimulant (methylphenidate) medication. Control subjects (n = 18) were tested once. EEG brain wave activity was tested both at baseline and during focussed attention. Attention was evoked and EEG brain wave activity was determined by means of the BioGraph Infiniti biofeedback apparatus. The main finding of this study was that control subjects and stimulant-free children with ADHD exhibited the expected reactivity in high alpha-wave activity (11-12 Hz) from baseline to focussed attention; however, methylphenidate appeared to abolish this reactivity. Methylphenidate attenuates the normal cortical response to a cognitive challenge. © 2016 S. Karger AG, Basel.

Brain network dysregulation, emotion, and complaints after mild traumatic brain injury.

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van der Horn, Harm J; Liemburg, Edith J; Scheenen, Myrthe E; de Koning, Myrthe E; Marsman, Jan-Bernard C; Spikman, Jacoba M; van der Naalt, Joukje

2016-04-01

To assess the role of brain networks in emotion regulation and post-traumatic complaints in the sub-acute phase after non-complicated mild traumatic brain injury (mTBI). Fifty-four patients with mTBI (34 with and 20 without complaints) and 20 healthy controls (group-matched for age, sex, education, and handedness) were included. Resting-state fMRI was performed at four weeks post-injury. Static and dynamic functional connectivity were studied within and between the default mode, executive (frontoparietal and bilateral frontal network), and salience network. The hospital anxiety and depression scale (HADS) was used to measure anxiety (HADS-A) and depression (HADS-D). Regarding within-network functional connectivity, none of the selected brain networks were different between groups. Regarding between-network interactions, patients with complaints exhibited lower functional connectivity between the bilateral frontal and salience network compared to patients without complaints. In the total patient group, higher HADS-D scores were related to lower functional connectivity between the bilateral frontal network and both the right frontoparietal and salience network, and to higher connectivity between the right frontoparietal and salience network. Furthermore, whereas higher HADS-D scores were associated with lower connectivity within the parietal midline areas of the bilateral frontal network, higher HADS-A scores were related to lower connectivity within medial prefrontal areas of the bilateral frontal network. Functional interactions of the executive and salience networks were related to emotion regulation and complaints after mTBI, with a key role for the bilateral frontal network. These findings may have implications for future studies on the effect of psychological interventions. © 2016 Wiley Periodicals, Inc.

Spontaneous brain network activity: Analysis of its temporal complexity

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Mangor Pedersen

2017-06-01

Full Text Available The brain operates in a complex way. The temporal complexity underlying macroscopic and spontaneous brain network activity is still to be understood. In this study, we explored the brain’s complexity by combining functional connectivity, graph theory, and entropy analyses in 25 healthy people using task-free functional magnetic resonance imaging. We calculated the pairwise instantaneous phase synchrony between 8,192 brain nodes for a total of 200 time points. This resulted in graphs for which time series of clustering coefficients (the “cliquiness” of a node and participation coefficients (the between-module connectivity of a node were estimated. For these two network metrics, sample entropy was calculated. The procedure produced a number of results: (1 Entropy is higher for the participation coefficient than for the clustering coefficient. (2 The average clustering coefficient is negatively related to its associated entropy, whereas the average participation coefficient is positively related to its associated entropy. (3 The level of entropy is network-specific to the participation coefficient, but not to the clustering coefficient. High entropy for the participation coefficient was observed in the default-mode, visual, and motor networks. These results were further validated using an independent replication dataset. Our work confirms that brain networks are temporally complex. Entropy is a good candidate metric to explore temporal network alterations in diseases with paroxysmal brain disruptions, including schizophrenia and epilepsy. In recent years, connectomics has provided significant insights into the topological complexity of brain networks. However, the temporal complexity of brain networks still remains somewhat poorly understood. In this study we used entropy analysis to demonstrate that the properties of network segregation (the clustering coefficient and integration (the participation coefficient are temporally complex

Macroscopic networks in the human brain: mapping connectivity in healthy and damaged brains

NARCIS (Netherlands)

Nijhuis, E.H.J.

2013-01-01

The human brain contains a network of interconnected neurons. Recent advances in functional and structural in-vivo magnetic resonance neuroimaging (MRI) techniques have provided opportunities to model the networks of the human brain on a macroscopic scale. This dissertation investigates the

Complex brain networks: From topological communities to clustered ...

Indian Academy of Sciences (India)

functional connectivity of the human brain has shown that both types of brain networks share .... the areas and also of the whole network, the Pearson correlation coefficient r and ..... Several areas important for intercommunity communication.

Validation of network communicability metrics for the analysis of brain structural networks.

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Jennifer Andreotti

Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Sensitivity analysis of human brain structural network construction

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Kuang Wei

2017-12-01

Full Text Available Network neuroscience leverages diffusion-weighted magnetic resonance imaging and tractography to quantify structural connectivity of the human brain. However, scientists and practitioners lack a clear understanding of the effects of varying tractography parameters on the constructed structural networks. With diffusion images from the Human Connectome Project (HCP, we characterize how structural networks are impacted by the spatial resolution of brain atlases, total number of tractography streamlines, and grey matter dilation with various graph metrics. We demonstrate how injudicious combinations of highly refined brain parcellations and low numbers of streamlines may inadvertently lead to disconnected network models with isolated nodes. Furthermore, we provide solutions to significantly reduce the likelihood of generating disconnected networks. In addition, for different tractography parameters, we investigate the distributions of values taken by various graph metrics across the population of HCP subjects. Analyzing the ranks of individual subjects within the graph metric distributions, we find that the ranks of individuals are affected differently by atlas scale changes. Our work serves as a guideline for researchers to optimize the selection of tractography parameters and illustrates how biological characteristics of the brain derived in network neuroscience studies can be affected by the choice of atlas parcellation schemes. Diffusion tractography has been proven to be a promising noninvasive technique to study the network properties of the human brain. However, how various tractography and network construction parameters affect network properties has not been studied using a large cohort of high-quality data. We utilize data provided by the Human Connectome Project to characterize the changes to network properties induced by varying the brain parcellation atlas scales, the number of reconstructed tractography tracks, and the degree of grey

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

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Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

Directory of Open Access Journals (Sweden)

Xia Liang

Full Text Available Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation, global signal presence (regressed or not and frequency band selection [slow-5 (0.01-0.027 Hz versus slow-4 (0.027-0.073 Hz] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR. The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics

Attention in spina bifida myelomeningocele: Relations with brain volume and integrity

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Paulina A. Kulesz

2015-01-01

Full Text Available This study investigated the relations of tectal volume and superior parietal cortex, as well as alterations in tectocortical white matter connectivity, with the orienting and executive control attention networks in individuals with spina bifida myelomeningocele (SBM. Probabilistic diffusion tractography and quantification of tectal and superior parietal cortical volume were performed on 74 individuals aged 8–29 with SBM and a history of hydrocephalus. Behavioral assessments measured posterior (covert orienting and anterior (conflict resolution, attentional control attention network functions. Reduced tectal volume was associated with slower covert orienting; reduced superior parietal cortical volume was associated with slower conflict resolution; and increased axial diffusivity and radial diffusivity along both frontal and parietal tectocortical pathways were associated with reduced attentional control. Results suggest that components of both the orienting and executive control attention networks are impaired in SBM. Neuroanatomical disruption to the orienting network appears more robust and a direct consequence of characteristic midbrain dysmorphology; whereas, executive control difficulties may emerge from parietal cortical anomalies and reduced frontal and parietal cortical–subcortical white matter pathways susceptible to the pathophysiological effects of congenital hydrocephalus.

Hierarchical organization of brain functional networks during visual tasks.

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Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

2011-09-01

The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

Altered causal connectivity of resting state brain networks in amnesic MCI.

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Peipeng Liang

Full Text Available Most neuroimaging studies of resting state networks in amnesic mild cognitive impairment (aMCI have concentrated on functional connectivity (FC based on instantaneous correlation in a single network. The purpose of the current study was to investigate effective connectivity in aMCI patients based on Granger causality of four important networks at resting state derived from functional magnetic resonance imaging data--default mode network (DMN, hippocampal cortical memory network (HCMN, dorsal attention network (DAN and fronto-parietal control network (FPCN. Structural and functional MRI data were collected from 16 aMCI patients and 16 age, gender-matched healthy controls. Correlation-purged Granger causality analysis was used, taking gray matter atrophy as covariates, to compare the group difference between aMCI patients and healthy controls. We found that the causal connectivity between networks in aMCI patients was significantly altered with both increases and decreases in the aMCI group as compared to healthy controls. Some alterations were significantly correlated with the disease severity as measured by mini-mental state examination (MMSE, and California verbal learning test (CVLT scores. When the whole-brain signal averaged over the entire brain was used as a nuisance co-variate, the within-group maps were significantly altered while the between-group difference maps did not. These results suggest that the alterations in causal influences may be one of the possible underlying substrates of cognitive impairments in aMCI. The present study extends and complements previous FC studies and demonstrates the coexistence of causal disconnection and compensation in aMCI patients, and thus might provide insights into biological mechanism of the disease.

Approach of Complex Networks for the Determination of Brain Death

International Nuclear Information System (INIS)

Sun Wei-Gang; Cao Jian-Ting; Wang Ru-Bin

2011-01-01

In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death. (cross-disciplinary physics and related areas of science and technology)

Educating the Human Brain. Human Brain Development Series

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Posner, Michael I.; Rothbart, Mary K.

2006-01-01

"Educating the Human Brain" is the product of a quarter century of research. This book provides an empirical account of the early development of attention and self regulation in infants and young children. It examines the brain areas involved in regulatory networks, their connectivity, and how their development is influenced by genes and…

Extrinsic and Intrinsic Brain Network Connectivity Maintains Cognition across the Lifespan Despite Accelerated Decay of Regional Brain Activation.

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Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Razi, Adeel; Geerligs, Linda; Ham, Timothy E; Rowe, James B

2016-03-16

The maintenance of wellbeing across the lifespan depends on the preservation of cognitive function. We propose that successful cognitive aging is determined by interactions both within and between large-scale functional brain networks. Such connectivity can be estimated from task-free functional magnetic resonance imaging (fMRI), also known as resting-state fMRI (rs-fMRI). However, common correlational methods are confounded by age-related changes in the neurovascular signaling. To estimate network interactions at the neuronal rather than vascular level, we used generative models that specified both the neural interactions and a flexible neurovascular forward model. The networks' parameters were optimized to explain the spectral dynamics of rs-fMRI data in 602 healthy human adults from population-based cohorts who were approximately uniformly distributed between 18 and 88 years (www.cam-can.com). We assessed directed connectivity within and between three key large-scale networks: the salience network, dorsal attention network, and default mode network. We found that age influences connectivity both within and between these networks, over and above the effects on neurovascular coupling. Canonical correlation analysis revealed that the relationship between network connectivity and cognitive function was age-dependent: cognitive performance relied on neural dynamics more strongly in older adults. These effects were driven partly by reduced stability of neural activity within all networks, as expressed by an accelerated decay of neural information. Our findings suggest that the balance of excitatory connectivity between networks, and the stability of intrinsic neural representations within networks, changes with age. The cognitive function of older adults becomes increasingly dependent on these factors. Maintaining cognitive function is critical to successful aging. To study the neural basis of cognitive function across the lifespan, we studied a large population

Attention-deficit hyperactivity disorder (ADHD) and tuberous sclerosis complex.

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D'Agati, Elisa; Moavero, Romina; Cerminara, Caterina; Curatolo, Paolo

2009-10-01

The neurobiological basis of attention-deficit hyperactivity disorder (ADHD) in tuberous sclerosis complex is still largely unknown. Cortical tubers may disrupt several brain networks that control different types of attention. Frontal lobe dysfunction due to seizures or epileptiform electroencephalographic discharges may perturb the development of brain systems that underpin attentional and hyperactive functions during a critical early stage of brain maturation. Comorbidity of attention-deficit hyperactivity disorder (ADHD) with mental retardation and autism spectrum disorders is frequent in children with tuberous sclerosis. Attention-deficit hyperactivity disorder (ADHD) may also reflect a direct effect of the abnormal genetic program. Treatment of children with tuberous sclerosis complex with combined symptoms of attention-deficit hyperactivity disorder (ADHD) and epilepsy may represent a challenge for clinicians, because antiepileptic therapy and drugs used to treat attention-deficit hyperactivity disorder (ADHD) may aggravate the clinical picture of each other.

A permutation testing framework to compare groups of brain networks.

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Simpson, Sean L; Lyday, Robert G; Hayasaka, Satoru; Marsh, Anthony P; Laurienti, Paul J

2013-01-01

Brain network analyses have moved to the forefront of neuroimaging research over the last decade. However, methods for statistically comparing groups of networks have lagged behind. These comparisons have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different mental states and disease conditions. Current comparison approaches generally either rely on a summary metric or on mass-univariate nodal or edge-based comparisons that ignore the inherent topological properties of the network, yielding little power and failing to make network level comparisons. Gleaning deeper insights into normal and abnormal changes in complex brain function demands methods that take advantage of the wealth of data present in an entire brain network. Here we propose a permutation testing framework that allows comparing groups of networks while incorporating topological features inherent in each individual network. We validate our approach using simulated data with known group differences. We then apply the method to functional brain networks derived from fMRI data.

Task vs. rest—different network configurations between the coactivation and the resting-state brain networks

Science.gov (United States)

Di, Xin; Gohel, Suril; Kim, Eun H.; Biswal, Bharat B.

2013-01-01

There is a growing interest in studies of human brain networks using resting-state functional magnetic resonance imaging (fMRI). However, it is unclear whether and how brain networks measured during the resting-state exhibit comparable properties to brain networks during task performance. In the present study, we investigated meta-analytic coactivation patterns among brain regions based upon published neuroimaging studies, and compared the coactivation network configurations with those in the resting-state network. The strength of resting-state functional connectivity between two regions were strongly correlated with the coactivation strength. However, the coactivation network showed greater global efficiency, smaller mean clustering coefficient, and lower modularity compared with the resting-state network, which suggest a more efficient global information transmission and between system integrations during task performing. Hub shifts were also observed within the thalamus and the left inferior temporal cortex. The thalamus and the left inferior temporal cortex exhibited higher and lower degrees, respectively in the coactivation network compared with the resting-state network. These results shed light regarding the reconfiguration of the brain networks between task and resting-state conditions, and highlight the role of the thalamus in change of network configurations in task vs. rest. PMID:24062654

Multimodal mapping of the brain's functional connectivity and the adult outcome of attention deficit hyperactivity disorder.

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Sudre, Gustavo; Szekely, Eszter; Sharp, Wendy; Kasparek, Steven; Shaw, Philip

2017-10-31

We have a limited understanding of why many children with attention deficit hyperactivity disorder do not outgrow the disorder by adulthood. Around 20-30% retain the full syndrome as young adults, and about 50% show partial, rather than complete, remission. Here, to delineate the neurobiology of this variable outcome, we ask if the persistence of childhood symptoms into adulthood impacts on the brain's functional connectivity. We studied 205 participants followed clinically since childhood. In early adulthood, participants underwent magnetoencephalography (MEG) to measure neuronal activity directly and functional MRI (fMRI) to measure hemodynamic activity during a task-free period (the "resting state"). We found that symptoms of inattention persisting into adulthood were associated with disrupted patterns of typical functional connectivity in both MEG and fMRI. Specifically, those with persistent inattention lost the typical balance of connections within the default mode network (DMN; prominent during introspective thought) and connections between this network and those supporting attention and cognitive control. By contrast, adults whose childhood inattentive symptoms had resolved did not differ significantly from their never-affected peers, both hemodynamically and electrophysiologically. The anomalies in functional connectivity tied to clinically significant inattention centered on midline regions of the DMN in both MEG and fMRI, boosting confidence in a possible pathophysiological role. The findings suggest that the clinical course of this common childhood onset disorder impacts the functional connectivity of the adult brain. Published under the PNAS license.

Role of physical and mental training in brain network configuration.

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Foster, Philip P

2015-01-01

It is hypothesized that the topology of brain networks is constructed by connecting nodes which may be continuously remodeled by appropriate training. Efficiency of physical and/or mental training on the brain relies on the flexibility of networks' architecture molded by local remodeling of proteins and synapses of excitatory neurons producing transformations in network topology. Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of "energy cost-driven small-world network disorder" with dysfunction of high-energy cost wiring as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement, presumably via reconfiguration of brain networks into greater small-worldness, appears essential in learning, memory, and executive functions. A macroscopic cartography of creation-removal of synaptic connections in a macro-network, and at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF). The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical, or combined-mental-physical trainings? Physical practice seems to be

Attentional Networks and Biological Motion

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Chandramouli Chandrasekaran

2010-03-01

Full Text Available Our ability to see meaningful actions when presented with pointlight traces of human movement is commonly referred to as the perception of biological motion. While traditionalexplanations have emphasized the spontaneous and automatic nature of this ability, morerecent findings suggest that attention may play a larger role than is typically assumed. Intwo studies we show that the speed and accuracy of responding to point-light stimuli is highly correlated with the ability to control selective attention. In our first experiment we measured thresholds for determining the walking direction of a masked point-light figure, and performance on a range of attention-related tasks in the same set of observers. Mask-density thresholds for the direction discrimination task varied quite considerably from observer to observer and this variation was highly correlated with performance on both Stroop and flanker interference tasks. Other components of attention, such as orienting, alerting and visual search efficiency, showed no such relationship. In a second experiment, we examined the relationship between the ability to determine the orientation of unmasked point-light actions and Stroop interference, again finding a strong correlation. Our results are consistent with previous research suggesting that biological motion processing may requite attention, and specifically implicate networks of attention related to executive control and selection.

An algebraic topological method for multimodal brain networks comparison

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Tiago eSimas

2015-07-01

Full Text Available Understanding brain connectivity is one of the most important issues in neuroscience. Nonetheless, connectivity data can reflect either functional relationships of brain activities or anatomical connections between brain areas. Although both representations should be related, this relationship is not straightforward. We have devised a powerful method that allows different operations between networks that share the same set of nodes, by embedding them in a common metric space, enforcing transitivity to the graph topology. Here, we apply this method to construct an aggregated network from a set of functional graphs, each one from a different subject. Once this aggregated functional network is constructed, we use again our method to compare it with the structural connectivity to identify particular brain regions that differ in both modalities (anatomical and functional. Remarkably, these brain regions include functional areas that form part of the classical resting state networks. We conclude that our method -based on the comparison of the aggregated functional network- reveals some emerging features that could not be observed when the comparison is performed with the classical averaged functional network.

Complex modular structure of large-scale brain networks

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Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

2009-06-01

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

From genes to brain development to phenotypic behavior: "dorsal-stream vulnerability" in relation to spatial cognition, attention, and planning of actions in Williams syndrome (WS) and other developmental disorders.

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Atkinson, Janette; Braddick, Oliver

2011-01-01

Visual information is believed to be processed through two distinct, yet interacting cortical streams. The ventral stream performs the computations needed for recognition of objects and faces ("what" and "who"?) and the dorsal stream the computations for registering spatial relationships and for controlling visually guided actions ("where" and "how"?). We initially proposed a model of spatial deficits in Williams syndrome (WS) in which visual abilities subserved by the ventral stream, such as face recognition, are relatively well developed (although not necessarily in exactly the same way as in typical development), whereas dorsal-stream functions, such as visuospatial actions, are markedly impaired. Since these initial findings in WS, deficits of motion coherence sensitivity, a dorsal-stream function has been found in other genetic disorders such as Fragile X and autism, and as a consequence of perinatal events (in hemiplegia, perinatal brain anomalies following very premature birth), leading to the proposal of a general "dorsal-stream vulnerability" in many different conditions of abnormal human development. In addition, dorsal-stream systems provide information used in tasks of visuospatial memory and locomotor planning, and these systems are closely coupled to networks for attentional control. We and several other research groups have previously shown deficits of frontal and parietal lobe function in WS individuals for specific attention tasks [e.g., Atkinson, J., Braddick, O., Anker, S., Curran, W., & Andrew, R. (2003). Neurobiological models of visuospatial cognition in children with Williams Syndrome: Measures of dorsal-stream and frontal function. Developmental Neuropsychology, 23(1/2), 141-174.]. We have used the Test of Everyday Attention for Children (TEA-Ch) which aims to attempt to separate components of attention with distinct brain networks (selective attention, sustained attention, and attention control-executive function) testing a group of older

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

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Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with

Covert orienting in the split brain: Right hemisphere specialization for object-based attention.

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Kingstone, Alan

2015-12-18

The present paper takes as its starting point Phil Bryden's long-standing interest in human attention and the role it can play in laterality effects. Past split-brain research has suggested that object-based attention is lateralized to the left hemisphere [e.g., Egly, R., Rafal, R. D., Driver, J., & Starreveld, Y. (1994). Covert orienting in the split brain reveals hemispheric specialization for object-based attention. Psychological Science, 5(6), 380-382]. The task used to isolate object-based attention in that previous work, however, has been found wanting [Vecera, S. P. (1994). Grouped locations and object-based attention: Comment on Egly, Driver, and Rafal (1994). Journal of Experimental Psychology: General, 123(3), 316-320]; and indeed, subsequent research with healthy participants using a different task has suggested that object-based attention is lateralized to the opposite right hemisphere (RH) [Valsangkar-Smyth, M. A., Donovan, C. L., Sinnett, S., Dawson, M. R., & Kingstone, A. (2004). Hemispheric performance in object-based attention. Psychonomic Bulletin & Review, 11(1), 84-91]. The present study tested the same split-brain as Egly, Rafal, et al. (1994) but used the object-based attention task introduced by Valsangkar-Smyth et al. (2004). The results confirm that object-based attention is lateralized to the RH. They also suggest that subcortical interhemispheric competition may occur and be dominated by the RH.

Role of physical and mental training in brain network configuration

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Philip P. Foster

2015-06-01

Full Text Available Continuous remodeling of proteins of excitatory neurons is fine-tuning the scaling and strength of excitatory synapses up or down via regulation of intra-cellular metabolic and regulatory networks of the genome-transcriptome-proteome interface. Alzheimer's disease is a model of energy cost-driven small-world network disorder as the network global efficiency is impaired by the deposition of an informed agent, the amyloid-β, selectively targeting high-degree nodes. In schizophrenia, the interconnectivity and density of rich-club networks are significantly reduced. Training-induced homeostatic synaptogenesis-enhancement produces a reconfiguration of brain networks into greater small-worldness. Creation of synaptic connections in a macro-network, and, at the intra-cellular scale, micro-networks regulate the physiological mechanisms for the preferential attachment of synapses. The strongest molecular relationship of exercise and functional connectivity was identified for brain-derived neurotrophic factor (BDNF. The allele variant, rs7294919, also shows a powerful relationship with the hippocampal volume. How the brain achieves this unique quest of reconfiguration remains a puzzle. What are the underlying mechanisms of synaptogenesis promoting communications brain ↔ muscle and brain ↔ brain in such trainings? What is the respective role of independent mental, physical or combined-mental-physical trainings? Physical practice seems to be playing an instrumental role in the cognitive enhancement (brain ↔ muscle com.. However, mental training, meditation or virtual reality (films, games require only minimal motor activity and cardio-respiratory stimulation. Therefore, other potential paths (brain ↔ brain com. molding brain networks are nonetheless essential. Patients with motor neuron disease/injury (e.g. amyotrophic lateral sclerosis, traumatism also achieve successful cognitive enhancement albeit they may only elicit mental practice

Brain networks and their origins. Comment on “Understanding brain networks and brain organization” by Luiz Pessoa

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Cisek, Paul

2014-09-01

Nearly every textbook on psychology or neuroscience contains theories of function described with box and arrow diagrams. Sometimes, the boxes stand for purely theoretical constructs, such as attention or working memory, and sometimes they also correspond to specific brain regions or systems, such as parietal or prefrontal cortex, and the arrows between them to known anatomical pathways. It is common for scientists (present company included) to summarize their theories in this way and to think of the brain as a set of interacting modules with clearly distinguishable functions.

Emotion and attention: event-related brain potential studies.

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Schupp, Harald T; Flaisch, Tobias; Stockburger, Jessica; Junghöfer, Markus

2006-01-01

Emotional pictures guide selective visual attention. A series of event-related brain potential (ERP) studies is reviewed demonstrating the consistent and robust modulation of specific ERP components by emotional images. Specifically, pictures depicting natural pleasant and unpleasant scenes are associated with an increased early posterior negativity, late positive potential, and sustained positive slow wave compared with neutral contents. These modulations are considered to index different stages of stimulus processing including perceptual encoding, stimulus representation in working memory, and elaborate stimulus evaluation. Furthermore, the review includes a discussion of studies exploring the interaction of motivated attention with passive and active forms of attentional control. Recent research is reviewed exploring the selective processing of emotional cues as a function of stimulus novelty, emotional prime pictures, learned stimulus significance, and in the context of explicit attention tasks. It is concluded that ERP measures are useful to assess the emotion-attention interface at the level of distinct processing stages. Results are discussed within the context of two-stage models of stimulus perception brought out by studies of attention, orienting, and learning.

Negative Affect, Decision Making, and Attentional Networks.

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Ortega, Ana Raquel; Ramírez, Encarnación; Colmenero, José María; García-Viedma, Ma Del Rosario

2017-02-01

This study focuses on whether risk avoidance in decision making depends on negative affect or it is specific to anxious individuals. The Balloon Analogue Risk Task was used to obtain an objective measure in a risk situation with anxious, depressive, and control individuals. The role of attentional networks was also studied using the Attentional Network Test-Interaction (ANT-I) task with neutral stimuli. A significant difference was observed between anxious and depressive individuals in assumed risk in decision making. We found no differences between anxious and normal individuals in the alert, orientation, and congruency effects obtained in the ANT-I task. The results showed that there was no significant relationship between the risk avoidance and the indexes of alertness, orienting, and control. Future research shall determine whether emotionally relevant stimulation leads to attentional control deficit or whether differences between anxious and no anxious individuals are due to the type of strategy followed in choice tasks.

Aging-related changes in the default mode network and its anti-correlated networks: a resting-state fMRI study.

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Wu, Jing-Tao; Wu, Hui-Zhen; Yan, Chao-Gan; Chen, Wen-Xin; Zhang, Hong-Ying; He, Yong; Yang, Hai-Shan

2011-10-17

Intrinsic brain activity in a resting state incorporates components of the task negative network called default mode network (DMN) and task-positive networks called attentional networks. In the present study, the reciprocal neuronal networks in the elder group were compared with the young group to investigate the differences of the intrinsic brain activity using a method of temporal correlation analysis based on seed regions of posterior cingulate cortex (PCC) and ventromedial prefrontal cortex (vmPFC). We found significant decreased positive correlations and negative correlations with the seeds of PCC and vmPFC in the old group. The decreased coactivations in the DMN network components and their negative networks in the old group may reflect age-related alterations in various brain functions such as attention, motor control and inhibition modulation in cognitive processing. These alterations in the resting state anti-correlative networks could provide neuronal substrates for the aging brain. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Altered resting state brain networks in Parkinson's disease.

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Martin Göttlich

Full Text Available Parkinson's disease (PD is a neurodegenerative disorder affecting dopaminergic neurons in the substantia nigra leading to dysfunctional cortico-striato-thalamic-cortical loops. In addition to the characteristic motor symptoms, PD patients often show cognitive impairments, affective changes and other non-motor symptoms, suggesting system-wide effects on brain function. Here, we used functional magnetic resonance imaging and graph-theory based analysis methods to investigate altered whole-brain intrinsic functional connectivity in PD patients (n = 37 compared to healthy controls (n = 20. Global network properties indicated less efficient processing in PD. Analysis of brain network modules pointed to increased connectivity within the sensorimotor network, but decreased interaction of the visual network with other brain modules. We found lower connectivity mainly between the cuneus and the ventral caudate, medial orbitofrontal cortex and the temporal lobe. To identify regions of altered connectivity, we mapped the degree of intrinsic functional connectivity both on ROI- and on voxel-level across the brain. Compared to healthy controls, PD patients showed lower connectedness in the medial and middle orbitofrontal cortex. The degree of connectivity was also decreased in the occipital lobe (cuneus and calcarine, but increased in the superior parietal cortex, posterior cingulate gyrus, supramarginal gyrus and supplementary motor area. Our results on global network and module properties indicated that PD manifests as a disconnection syndrome. This was most apparent in the visual network module. The higher connectedness within the sensorimotor module in PD patients may be related to compensation mechanism in order to overcome the functional deficit of the striato-cortical motor loops or to loss of mutual inhibition between brain networks. Abnormal connectivity in the visual network may be related to adaptation and compensation processes as a consequence

The development of brain network architecture

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Wierenga, Lara M.; van den Heuvel, Martijn P.; van Dijk, Sarai; Rijks, Yvonne; de Reus, Marcel A.; Durston, Sarah

2016-01-01

Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes

A covert attention P300-based brain-computer interface: Geospell.

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Aloise, Fabio; Aricò, Pietro; Schettini, Francesca; Riccio, Angela; Salinari, Serenella; Mattia, Donatella; Babiloni, Fabio; Cincotti, Febo

2012-01-01

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities. This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.

Myndplay: Measuring Attention Regulation with Single Dry Electrode Brain Computer Interface

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van der Wal, C.N.; Irrmischer, M.; Guo, Y.; Friston, K.; Faisal, A.; Hill, S.; Peng, H.

2015-01-01

Future applications for the detection of attention can be helped by the development and validation of single electrode brain computer interfaces that are small and user-friendly. The two objectives of this study were: to (1) understand the correlates of attention regulation as detected with the

[Formula: see text]Working memory and attention in pediatric brain tumor patients treated with and without radiation therapy.

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Raghubar, Kimberly P; Mahone, E Mark; Yeates, Keith Owen; Cecil, Kim M; Makola, Monwabisi; Ris, M Douglas

2017-08-01

Children are at risk for cognitive difficulties following the diagnosis and treatment of a brain tumor. Longitudinal studies have consistently demonstrated declines on measures of intellectual functioning, and recently it has been proposed that specific neurocognitive processes underlie these changes, including working memory, processing speed, and attention. However, a fine-grained examination of the affected neurocognitive processes is required to inform intervention efforts. Radiation therapy (RT) impacts white matter integrity, likely affecting those cognitive processes supported by distributed neural networks. This study examined working memory and attention in children during the early delayed stages of recovery following surgical resection and RT. The participants included 27 children diagnosed with pediatric brain tumor, treated with (n = 12) or without (n = 15) RT, who completed experimental and standardized measures of working memory and attention (n-back and digit span tasks). Children treated with radiation performed less well than those who did not receive radiation on the n-back measure, though performance at the 0-back level was considerably poorer than would be expected for both groups, perhaps suggesting difficulties with more basic processes such as vigilance. Along these lines, marginal differences were noted on digit span forward. The findings are discussed with respect to models of attention and working memory, and the interplay between the two.

Development of large-scale functional brain networks in children.

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Kaustubh Supekar

2009-07-01

Full Text Available The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y and 22 young-adults (ages 19-22 y. Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Development of large-scale functional brain networks in children.

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Supekar, Kaustubh; Musen, Mark; Menon, Vinod

2009-07-01

The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism.

Cerebral networks of sustained attention and working memory: a functional magnetic resonance imaging study based on the Continuous Performance Test.

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Bartés-Serrallonga, M; Adan, A; Solé-Casals, J; Caldú, X; Falcón, C; Pérez-Pàmies, M; Bargalló, N; Serra-Grabulosa, J M

2014-04-01

One of the most used paradigms in the study of attention is the Continuous Performance Test (CPT). The identical pairs version (CPT-IP) has been widely used to evaluate attention deficits in developmental, neurological and psychiatric disorders. However, the specific locations and the relative distribution of brain activation in networks identified with functional imaging, varies significantly with differences in task design. To design a task to evaluate sustained attention using functional magnetic resonance imaging (fMRI), and thus to provide data for research concerned with the role of these functions. Forty right-handed, healthy students (50% women; age range: 18-25 years) were recruited. A CPT-IP implemented as a block design was used to assess sustained attention during the fMRI session. The behavioural results from the CPT-IP task showed a good performance in all subjects, higher than 80% of hits. fMRI results showed that the used CPT-IP task activates a network of frontal, parietal and occipital areas, and that these are related to executive and attentional functions. In relation to the use of the CPT to study of attention and working memory, this task provides normative data in healthy adults, and it could be useful to evaluate disorders which have attentional and working memory deficits.

Small-world human brain networks: Perspectives and challenges.

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Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

2017-06-01

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Speech networks at rest and in action: interactions between functional brain networks controlling speech production

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Fuertinger, Stefan

2015-01-01

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. PMID:25673742

Mapping human whole-brain structural networks with diffusion MRI.

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Patric Hagmann

Full Text Available Understanding the large-scale structural network formed by neurons is a major challenge in system neuroscience. A detailed connectivity map covering the entire brain would therefore be of great value. Based on diffusion MRI, we propose an efficient methodology to generate large, comprehensive and individual white matter connectional datasets of the living or dead, human or animal brain. This non-invasive tool enables us to study the basic and potentially complex network properties of the entire brain. For two human subjects we find that their individual brain networks have an exponential node degree distribution and that their global organization is in the form of a small world.

Top-down and bottom-up attention-to-memory: mapping functional connectivity in two distinct networks that underlie cued and uncued recognition memory.

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Burianová, Hana; Ciaramelli, Elisa; Grady, Cheryl L; Moscovitch, Morris

2012-11-15

The objective of this study was to examine the functional connectivity of brain regions active during cued and uncued recognition memory to test the idea that distinct networks would underlie these memory processes, as predicted by the attention-to-memory (AtoM) hypothesis. The AtoM hypothesis suggests that dorsal parietal cortex (DPC) allocates effortful top-down attention to memory retrieval during cued retrieval, whereas ventral parietal cortex (VPC) mediates spontaneous bottom-up capture of attention by memory during uncued retrieval. To identify networks associated with these two processes, we conducted a functional connectivity analysis of a left DPC and a left VPC region, both identified by a previous analysis of task-related regional activations. We hypothesized that the two parietal regions would be functionally connected with distinct neural networks, reflecting their engagement in the differential mnemonic processes. We found two spatially dissociated networks that overlapped only in the precuneus. During cued trials, DPC was functionally connected with dorsal attention areas, including the superior parietal lobules, right precuneus, and premotor cortex, as well as relevant memory areas, such as the left hippocampus and the middle frontal gyri. During uncued trials, VPC was functionally connected with ventral attention areas, including the supramarginal gyrus, cuneus, and right fusiform gyrus, as well as the parahippocampal gyrus. In addition, activity in the DPC network was associated with faster response times for cued retrieval. This is the first study to show a dissociation of the functional connectivity of posterior parietal regions during episodic memory retrieval, characterized by a top-down AtoM network involving DPC and a bottom-up AtoM network involving VPC. Copyright © 2012 Elsevier Inc. All rights reserved.

Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

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Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

2018-04-01

Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

Scalable Brain Network Construction on White Matter Fibers.

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Chung, Moo K; Adluru, Nagesh; Dalton, Kim M; Alexander, Andrew L; Davidson, Richard J

2011-02-12

DTI offers a unique opportunity to characterize the structural connectivity of the human brain non-invasively by tracing white matter fiber tracts. Whole brain tractography studies routinely generate up to half million tracts per brain, which serves as edges in an extremely large 3D graph with up to half million edges. Currently there is no agreed-upon method for constructing the brain structural network graphs out of large number of white matter tracts. In this paper, we present a scalable iterative framework called the ε-neighbor method for building a network graph and apply it to testing abnormal connectivity in autism.

Oscillatory brain correlates of live joint attention: a dual-EEG study

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Fanny eLachat

2012-06-01

Full Text Available Joint attention consists in following another’s gaze onto an environmental object, which leads to the alignment of both subjects' attention onto this object. It is a fundamental mechanism of non-verbal communication, and it is essential for dynamic, online, interindividual synchronization during interactions. We aimed at investigating the oscillatory brain correlates of joint attention in a face-to-face paradigm where dyads of participants dynamically oriented their attention toward objects during joint and no-joint attention periods respectively. We also manipulated task instruction: in socially-driven instructions, the participants had to follow explicitly their partner’s gaze, while in color-driven instructions, the objects to be looked at were designated at by their color so that no explicit gaze following was required. We focused on oscillatory activities in the 10 Hz frequency range, where parieto-occipital alpha and the centro-parietal mu rhythms have been described, as these rhythms have been associated with attention and social coordination processes respectively. We tested the hypothesis of a modulation of these oscillatory activities by joint attention. We used dual EEG to record simultaneously the brain activities of the participant dyads during our live, face-to-face joint attention paradigm. We showed that joint attention periods – as compared to the no-joint attention periods – were associated with a decrease of signal power between 11 and 13 Hz over a large set of left centro-parieto-occipital electrodes, encompassing the scalp regions where alpha and mu rhythms have been described. This 11-13 Hz signal power decrease was observed independently of the task instruction: it was similar when joint versus no-joint attention situations were socially-driven and when they were color-driven. These results are interpreted in terms of the processes of attention mirroring, social coordination, and mutual attentiveness associated

Brain connectivity study of joint attention using frequency-domain optical imaging technique

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Chaudhary, Ujwal; Zhu, Banghe; Godavarty, Anuradha

2010-02-01

Autism is a socio-communication brain development disorder. It is marked by degeneration in the ability to respond to joint attention skill task, from as early as 12 to 18 months of age. This trait is used to distinguish autistic from nonautistic populations. In this study, diffuse optical imaging is being used to study brain connectivity for the first time in response to joint attention experience in normal adults. The prefrontal region of the brain was non-invasively imaged using a frequency-domain based optical imager. The imaging studies were performed on 11 normal right-handed adults and optical measurements were acquired in response to joint-attention based video clips. While the intensity-based optical data provides information about the hemodynamic response of the underlying neural process, the time-dependent phase-based optical data has the potential to explicate the directional information on the activation of the brain. Thus brain connectivity studies are performed by computing covariance/correlations between spatial units using this frequency-domain based optical measurements. The preliminary results indicate that the extent of synchrony and directional variation in the pattern of activation varies in the left and right frontal cortex. The results have significant implication for research in neural pathways associated with autism that can be mapped using diffuse optical imaging tools in the future.

Complex network analysis of resting-state fMRI of the brain.

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Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman

2016-08-01

Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.

The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

Science.gov (United States)

Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

2018-06-01

Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

Two cognitive and neural systems for endogenous and exogenous spatial attention.

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Chica, Ana B; Bartolomeo, Paolo; Lupiáñez, Juan

2013-01-15

Orienting of spatial attention is a family of phylogenetically old mechanisms developed to select information for further processing. Information can be selected via top-down or endogenous mechanisms, depending on the goals of the observers or on the task at hand. Moreover, salient and potentially dangerous events also attract spatial attention via bottom-up or exogenous mechanisms, allowing a rapid and efficient reaction to unexpected but important events. Fronto-parietal brain networks have been demonstrated to play an important role in supporting spatial attentional orienting, although there is no consensus on whether there is a single attentional system supporting both endogenous and exogenous attention, or two anatomical and functionally different attentional systems. In the present paper we review behavioral evidence emphasizing the differential characteristics of both systems, as well as their possible interactions for the control of the final orienting response. Behavioral studies reporting qualitative differences between the effects of both systems as well as double dissociations of the effects of endogenous and exogenous attention on information processing, suggest that they constitute two independent attentional systems, rather than a single one. Recent models of attentional orienting in humans have put forward the hypothesis of a dorsal fronto-parietal network for orienting spatial attention, and a more ventral fronto-parietal network for detecting unexpected but behaviorally relevant events. Non-invasive neurostimulation techniques, as well as neuropsychological data, suggest that endogenous and exogenous attention are implemented in overlapping, although partially segregated, brain circuits. Although more research is needed in order to refine our anatomical and functional knowledge of the brain circuits underlying spatial attention, we conclude that endogenous and exogenous spatial orienting constitute two independent attentional systems, with

Rounding of abrupt phase transitions in brain networks

International Nuclear Information System (INIS)

Martín, Paula Villa; Moretti, Paolo; Muñoz, Miguel A

2015-01-01

The observation of critical-like behavior in cortical networks represents a major step forward in elucidating how the brain manages information. Understanding the origin and functionality of critical-like dynamics, as well as its robustness, is a major challenge in contemporary neuroscience. Here, we present an extensive numerical study of a family of simple dynamical models, which describe activity propagation in brain networks through the integration of different neighboring spiking potentials, mimicking basic neural interactions. The requirement of signal integration may lead to discontinuous phase transitions in networks that are well described by the mean-field approximation, thus preventing the emergence of critical points in such systems. Brain networks, however, are finite dimensional and exhibit a heterogeneous hierarchical structure that cannot be encoded in mean-field models. Here we propose that, as a consequence of the presence of such a heterogeneous substrate with its concomitant structural disorder, critical-like features may emerge even in the presence of integration. These conclusions may prove significant in explaining the observation of traits of critical behavior in large-scale measurements of brain activity. (paper)

Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

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Simonyan, Kristina; Fuertinger, Stefan

2015-04-01

Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

Divided attention and driving. The effects of aging and brain injury

OpenAIRE

Withaar, Frederiec Kunna

2000-01-01

In this thesis, divided attention was investigated in four groups of subjects: closed head injury (CHI) patients, young control and healthy older subjects, and older subjects with cognitive impairments. It was studied how diffuse brain injury and normal and abnormal aging affect cognitive processes involved in divided attention tasks. Furthermore, it was investigated how deficits in divided attention relate to performance of instrumental activities of daily living (IADL), with an emphasis on ...

Brain and Social Networks: Fundamental Building Blocks of Human Experience.

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Falk, Emily B; Bassett, Danielle S

2017-09-01

How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Deciding where to attend: Large-scale network mechanisms underlying attention and intention revealed by graph-theoretic analysis.

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Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R

2017-08-15

The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.

EEG classification of emotions using emotion-specific brain functional network.

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Gonuguntla, V; Shafiq, G; Wang, Y; Veluvolu, K C

2015-08-01

The brain functional network perspective forms the basis to relate mechanisms of brain functions. This work analyzes the network mechanisms related to human emotion based on synchronization measure - phase-locking value in EEG to formulate the emotion specific brain functional network. Based on network dissimilarities between emotion and rest tasks, most reactive channel pairs and the reactive band corresponding to emotions are identified. With the identified most reactive pairs, the subject-specific functional network is formed. The identified subject-specific and emotion-specific dynamic network pattern show significant synchrony variation in line with the experiment protocol. The same network pattern are then employed for classification of emotions. With the study conducted on the 4 subjects, an average classification accuracy of 62 % was obtained with the proposed technique.

An ANOVA approach for statistical comparisons of brain networks.

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Fraiman, Daniel; Fraiman, Ricardo

2018-03-16

The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.

Meta-connectomics: human brain network and connectivity meta-analyses.

Science.gov (United States)

Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

Brain network characterization of high-risk preterm-born school-age children

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Elda Fischi-Gomez

2016-01-01

Full Text Available Higher risk for long-term cognitive and behavioral impairments is one of the hallmarks of extreme prematurity (EP and pregnancy-associated fetal adverse conditions such as intrauterine growth restriction (IUGR. While neurodevelopmental delay and abnormal brain function occur in the absence of overt brain lesions, these conditions have been recently associated with changes in microstructural brain development. Recent imaging studies indicate changes in brain connectivity, in particular involving the white matter fibers belonging to the cortico-basal ganglia-thalamic loop. Furthermore, EP and IUGR have been related to altered brain network architecture in childhood, with reduced network global capacity, global efficiency and average nodal strength. In this study, we used a connectome analysis to characterize the structural brain networks of these children, with a special focus on their topological organization. On one hand, we confirm the reduced averaged network node degree and strength due to EP and IUGR. On the other, the decomposition of the brain networks in an optimal set of clusters remained substantially different among groups, talking in favor of a different network community structure. However, and despite the different community structure, the brain networks of these high-risk school-age children maintained the typical small-world, rich-club and modularity characteristics in all cases. Thus, our results suggest that brain reorganizes after EP and IUGR, prioritizing a tight modular structure, to maintain the small-world, rich-club and modularity characteristics. By themselves, both extreme prematurity and IUGR bear a similar risk for neurocognitive and behavioral impairment, and the here defined modular network alterations confirm similar structural changes both by IUGR and EP at school age compared to control. Interestingly, the combination of both conditions (IUGR + EP does not result in a worse outcome. In such cases, the alteration

Episodic memory in aspects of large-scale brain networks

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Jeong, Woorim; Chung, Chun Kee; Kim, June Sic

2015-01-01

Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL) structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network (DMN). Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network (RSN). Altered patterns of functional connectivity (FC) among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment. PMID:26321939

Episodic memory in aspects of large-scale brain networks

Directory of Open Access Journals (Sweden)

Woorim eJeong

2015-08-01

Full Text Available Understanding human episodic memory in aspects of large-scale brain networks has become one of the central themes in neuroscience over the last decade. Traditionally, episodic memory was regarded as mostly relying on medial temporal lobe (MTL structures. However, recent studies have suggested involvement of more widely distributed cortical network and the importance of its interactive roles in the memory process. Both direct and indirect neuro-modulations of the memory network have been tried in experimental treatments of memory disorders. In this review, we focus on the functional organization of the MTL and other neocortical areas in episodic memory. Task-related neuroimaging studies together with lesion studies suggested that specific sub-regions of the MTL are responsible for specific components of memory. However, recent studies have emphasized that connectivity within MTL structures and even their network dynamics with other cortical areas are essential in the memory process. Resting-state functional network studies also have revealed that memory function is subserved by not only the MTL system but also a distributed network, particularly the default-mode network. Furthermore, researchers have begun to investigate memory networks throughout the entire brain not restricted to the specific resting-state network. Altered patterns of functional connectivity among distributed brain regions were observed in patients with memory impairments. Recently, studies have shown that brain stimulation may impact memory through modulating functional networks, carrying future implications of a novel interventional therapy for memory impairment.

Selective impairment of attention networks during propofol anesthesia after gynecological surgery in middle-aged women.

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Chen, Chen; Xu, Guang-hong; Li, Yuan-hai; Tang, Wei-xiang; Wang, Kai

2016-04-15

Postoperative cognitive dysfunction is a common complication of anesthesia and surgery. Attention networks are essential components of cognitive function and are subject to impairment after anesthesia and surgery. It is not known whether such impairment represents a global attention deficit or relates to a specific attention network. We used an Attention Network Task (ANT) to examine the efficiency of the alerting, orienting, and executive control attention networks in middle-aged women (40-60 years) undergoing gynecologic surgery. A matched group of medical inpatients were recruited as a control. Fifty female patients undergoing gynecologic surgery (observation group) and 50 female medical inpatients (control group) participated in this study. Preoperatively patients were administered a mini-mental state examination as a screening method. The preoperative efficiencies of three attention networks in an attention network test were compared to the 1st and 5th post-operative days. The control group did not have any significant attention network impairments. On the 1st postoperative day, significant impairment was shown in the alerting (p=0.003 vs. control group, p=0.015 vs. baseline), orienting (pAttention networks of middle-aged women show a varying degree of significant impairment and differing levels of recovery after surgery and propofol anesthetic. Copyright © 2016 Elsevier B.V. All rights reserved.

A review of structural and functional brain networks: small world and atlas.

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Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Moore, Philip; Zheng, Jiaxiang

2015-03-01

Brain networks can be divided into two categories: structural and functional networks. Many studies of neuroscience have reported that the complex brain networks are characterized by small-world or scale-free properties. The identification of nodes is the key factor in studying the properties of networks on the macro-, micro- or mesoscale in both structural and functional networks. In the study of brain networks, nodes are always determined by atlases. Therefore, the selection of atlases is critical, and appropriate atlases are helpful to combine the analyses of structural and functional networks. Currently, some problems still exist in the establishment or usage of atlases, which are often caused by the segmentation or the parcellation of the brain. We suggest that quantification of brain networks might be affected by the selection of atlases to a large extent. In the process of building atlases, the influences of single subjects and groups should be balanced. In this article, we focused on the effects of atlases on the analysis of brain networks and the improved divisions based on the tractography or connectivity in the parcellation of atlases.

Identifying modular relations in complex brain networks

DEFF Research Database (Denmark)

Andersen, Kasper Winther; Mørup, Morten; Siebner, Hartwig

2012-01-01

We evaluate the infinite relational model (IRM) against two simpler alternative nonparametric Bayesian models for identifying structures in multi subject brain networks. The models are evaluated for their ability to predict new data and infer reproducible structures. Prediction and reproducibility...... and obtains comparable reproducibility and predictability. For resting state functional magnetic resonance imaging data from 30 healthy controls the IRM model is also superior to the two simpler alternatives, suggesting that brain networks indeed exhibit universal complex relational structure...

Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep.

Science.gov (United States)

Tagliazucchi, Enzo; von Wegner, Frederic; Morzelewski, Astrid; Brodbeck, Verena; Jahnke, Kolja; Laufs, Helmut

2013-09-17

The integration of segregated brain functional modules is a prerequisite for conscious awareness during wakeful rest. Here, we test the hypothesis that temporal integration, measured as long-term memory in the history of neural activity, is another important quality underlying conscious awareness. For this aim, we study the temporal memory of blood oxygen level-dependent signals across the human nonrapid eye movement sleep cycle. Results reveal that this property gradually decreases from wakefulness to deep nonrapid eye movement sleep and that such decreases affect areas identified with default mode and attention networks. Although blood oxygen level-dependent spontaneous fluctuations exhibit nontrivial spatial organization, even during deep sleep, they also display a decreased temporal complexity in specific brain regions. Conversely, this result suggests that long-range temporal dependence might be an attribute of the spontaneous conscious mentation performed during wakeful rest.

Development of the brain's functional network architecture.

Science.gov (United States)

Vogel, Alecia C; Power, Jonathan D; Petersen, Steven E; Schlaggar, Bradley L

2010-12-01

A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.

Human brain networks function in connectome-specific harmonic waves.

Science.gov (United States)

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Structural covariance networks in the mouse brain.

Science.gov (United States)

Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro

2016-04-01

The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural correlates of executive attention in adults born very preterm

Directory of Open Access Journals (Sweden)

Marcel Daamen

2015-01-01

Full Text Available Very preterm birth is associated with an increased prevalence of attention problems and may especially impair executive attention, i.e., top-down control of attentional selection in situations where distracting information interferes with the processing of task-relevant stimuli. While there are initial findings linking structural brain alterations in preterm-born individuals with attention problems, the functional basis of these problems are not well understood. The present study used an fMRI adaptation of the Attentional Network Test to examine the neural correlates of executive attention in a large sample of N = 86 adults born very preterm and/or with very low birth weight (VP/VLBW, and N = 100 term-born controls. Executive attention was measured by comparing task behavior and brain activations associated with the processing of incongruent vs. congruent arrow flanker stimuli. Consistent with subtle impairments of executive attention, the VP/VLBW group showed lower accuracy and a tendency for increased response times during the processing of incongruent stimuli. Both groups showed similar activation patters, especially within expected fronto-cingulo-parietal areas, but no significant between-group differences. Our results argue for a maintained attention-relevant network organization in high-functioning preterm born adults in spite of subtle deficits in executive attention. Gestational age and neonatal treatment variables showed associations with task behavior, and brain activation in the dorsal ACC and lateral occipital areas, suggesting that the degree of prematurity (and related neonatal complications has subtle modulatory influences on executive attention processing.

Information dynamics of brain-heart physiological networks during sleep

Science.gov (United States)

Faes, L.; Nollo, G.; Jurysta, F.; Marinazzo, D.

2014-10-01

This study proposes an integrated approach, framed in the emerging fields of network physiology and information dynamics, for the quantitative analysis of brain-heart interaction networks during sleep. With this approach, the time series of cardiac vagal autonomic activity and brain wave activities measured respectively as the normalized high frequency component of heart rate variability and the EEG power in the δ, θ, α, σ, and β bands, are considered as realizations of the stochastic processes describing the dynamics of the heart system and of different brain sub-systems. Entropy-based measures are exploited to quantify the predictive information carried by each (sub)system, and to dissect this information into a part actively stored in the system and a part transferred to it from the other connected systems. The application of this approach to polysomnographic recordings of ten healthy subjects led us to identify a structured network of sleep brain-brain and brain-heart interactions, with the node described by the β EEG power acting as a hub which conveys the largest amount of information flowing between the heart and brain nodes. This network was found to be sustained mostly by the transitions across different sleep stages, as the information transfer was weaker during specific stages than during the whole night, and vanished progressively when moving from light sleep to deep sleep and to REM sleep.

The overlapping community structure of structural brain network in young healthy individuals.

Directory of Open Access Journals (Sweden)

Kai Wu

2011-05-01

Full Text Available Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities overlap and share many edges and nodes. Uncovering the overlapping community structure of complex networks remains largely unknown in human brain networks. Here, using regional gray matter volume, we investigated the structural brain network among 90 brain regions (according to a predefined anatomical atlas in 462 young, healthy individuals. Overlapped nodes between communities were defined by assuming that nodes (brain regions can belong to more than one community. We demonstrated that 90 brain regions were organized into 5 overlapping communities associated with several well-known brain systems, such as the auditory/language, visuospatial, emotion, decision-making, social, control of action, memory/learning, and visual systems. The overlapped nodes were mostly involved in an inferior-posterior pattern and were primarily related to auditory and visual perception. The overlapped nodes were mainly attributed to brain regions with higher node degrees and nodal efficiency and played a pivotal role in the flow of information through the structural brain network. Our results revealed fuzzy boundaries between communities by identifying overlapped nodes and provided new insights into the understanding of the relationship between the structure and function of the human brain. This study provides the first report of the overlapping community structure of the structural network of the human brain.

Mutated Genes in Schizophrenia Map to Brain Networks

Science.gov (United States)

... Matters NIH Research Matters August 12, 2013 Mutated Genes in Schizophrenia Map to Brain Networks Schizophrenia networks ... have a high number of spontaneous mutations in genes that form a network in the front region ...

Big words, halved brains and small worlds: complex brain networks of figurative language comprehension.

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Arzouan, Yossi; Solomon, Sorin; Faust, Miriam; Goldstein, Abraham

2011-04-27

Language comprehension is a complex task that involves a wide network of brain regions. We used topological measures to qualify and quantify the functional connectivity of the networks used under various comprehension conditions. To that aim we developed a technique to represent functional networks based on EEG recordings, taking advantage of their excellent time resolution in order to capture the fast processes that occur during language comprehension. Networks were created by searching for a specific causal relation between areas, the negative feedback loop, which is ubiquitous in many systems. This method is a simple way to construct directed graphs using event-related activity, which can then be analyzed topologically. Brain activity was recorded while subjects read expressions of various types and indicated whether they found them meaningful. Slightly different functional networks were obtained for event-related activity evoked by each expression type. The differences reflect the special contribution of specific regions in each condition and the balance of hemispheric activity involved in comprehending different types of expressions and are consistent with the literature in the field. Our results indicate that representing event-related brain activity as a network using a simple temporal relation, such as the negative feedback loop, to indicate directional connectivity is a viable option for investigation which also derives new information about aspects not reflected in the classical methods for investigating brain activity.

Cognition Is Related to Resting-State Small-World Network Topology: An Magnetoencephalographic Study

NARCIS (Netherlands)

Douw, L.; Schoonheim, M.M.; Landi, D.; van der Meer, M.L.; Geurts, J.J.G.; Reijneveld, J.C.; Klein, M.; Stam, C.J.

2011-01-01

Brain networks and cognition have recently begun to attract attention: studies suggest that more efficiently wired resting-state brain networks are indeed correlated with better cognitive performance. "Small-world" brain networks combine local segregation with global integration, hereby subserving

Finding influential nodes for integration in brain networks using optimal percolation theory.

Science.gov (United States)

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Childhood maltreatment is associated with a sex-dependent functional reorganization of a brain inhibitory control network.

Science.gov (United States)

Elton, Amanda; Tripathi, Shanti P; Mletzko, Tanja; Young, Jonathan; Cisler, Josh M; James, G Andrew; Kilts, Clinton D

2014-04-01

Childhood adversity represents a major risk factor for drug addiction and other mental disorders. However, the specific mechanisms by which childhood adversity impacts human brain organization to confer greater vulnerability for negative outcomes in adulthood is largely unknown. As an impaired process in drug addiction, inhibitory control of behavior was investigated as a target of childhood maltreatment (abuse and neglect). Forty adults without Axis-I psychiatric disorders (21 females) completed a Childhood Trauma Questionnaire (CTQ) and underwent functional MRI (fMRI) while performing a stop-signal task. A group independent component analysis identified a putative brain inhibitory control network. Graph theoretical analyses and structural equation modeling investigated the impact of childhood maltreatment on the functional organization of this neural processing network. Graph theory outcomes revealed sex differences in the relationship between network functional connectivity and inhibitory control which were dependent on the severity of childhood maltreatment exposure. A network effective connectivity analysis indicated that a maltreatment dose-related negative modulation of dorsal anterior cingulate (dACC) activity by the left inferior frontal cortex (IFC) predicted better response inhibition and lesser attention deficit hyperactivity disorder (ADHD) symptoms in females, but poorer response inhibition and greater ADHD symptoms in males. Less inhibition of the right IFC by dACC in males with higher CTQ scores improved inhibitory control ability. The childhood maltreatment-related reorganization of a brain inhibitory control network provides sex-dependent mechanisms by which childhood adversity may confer greater risk for drug use and related disorders and by which adaptive brain responses protect individuals from this risk factor. Copyright © 2013 Wiley Periodicals, Inc.

Mind wandering away from pain dynamically engages antinociceptive and default mode brain networks.

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Kucyi, Aaron; Salomons, Tim V; Davis, Karen D

2013-11-12

Human minds often wander away from their immediate sensory environment. It remains unknown whether such mind wandering is unsystematic or whether it lawfully relates to an individual's tendency to attend to salient stimuli such as pain and their associated brain structure/function. Studies of pain-cognition interactions typically examine explicit manipulation of attention rather than spontaneous mind wandering. Here we sought to better represent natural fluctuations in pain in daily life, so we assessed behavioral and neural aspects of spontaneous disengagement of attention from pain. We found that an individual's tendency to attend to pain related to the disruptive effect of pain on his or her cognitive task performance. Next, we linked behavioral findings to neural networks with strikingly convergent evidence from functional magnetic resonance imaging during pain coupled with thought probes of mind wandering, dynamic resting state activity fluctuations, and diffusion MRI. We found that (i) pain-induced default mode network (DMN) deactivations were attenuated during mind wandering away from pain; (ii) functional connectivity fluctuations between the DMN and periaqueductal gray (PAG) dynamically tracked spontaneous attention away from pain; and (iii) across individuals, stronger PAG-DMN structural connectivity and more dynamic resting state PAG-DMN functional connectivity were associated with the tendency to mind wander away from pain. These data demonstrate that individual tendencies to mind wander away from pain, in the absence of explicit manipulation, are subserved by functional and structural connectivity within and between default mode and antinociceptive descending modulation networks.

Emotion and attention : Event-related brain potential studies

OpenAIRE

Schupp, Harald Thomas; Flaisch, Tobias; Stockburger, Jessica; Junghöfer, Markus

2006-01-01

Emotional pictures guide selective visual attention. A series of event-related brain potential (ERP) studies is reviewed demonstrating the consistent and robust modulation of specific ERP components by emotional images. Specifically, pictures depicting natural pleasant and unpleasant scenes are associated with an increased early posterior negativity, late positive potential, and sustained positive slow wave compared with neutral contents. These modulations are considered to index different st...

Association between structural brain network efficiency and intelligence increases during adolescence

NARCIS (Netherlands)

Koenis, Marinka M G; Brouwer, Rachel M; Swagerman, Suzanne C; van Soelen, Inge L C; Boomsma, Dorret I; Hulshoff Pol, Hilleke E

2018-01-01

Adolescence represents an important period during which considerable changes in the brain take place, including increases in integrity of white matter bundles, and increasing efficiency of the structural brain network. A more efficient structural brain network has been associated with higher

Towards Developmental Connectomics of the Human Brain

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Miao eCao

2016-03-01

Full Text Available Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and

Toward Developmental Connectomics of the Human Brain.

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Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental

Toward Developmental Connectomics of the Human Brain

Science.gov (United States)

Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental

Development of Human Brain Structural Networks Through Infancy and Childhood

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Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J.; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

2015-01-01

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. PMID:24335033

Association of structural global brain network properties with intelligence in normal aging.

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Florian U Fischer

Full Text Available Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60-85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience.

Association of Structural Global Brain Network Properties with Intelligence in Normal Aging

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Fischer, Florian U.; Wolf, Dominik; Scheurich, Armin; Fellgiebel, Andreas

2014-01-01

Higher general intelligence attenuates age-associated cognitive decline and the risk of dementia. Thus, intelligence has been associated with cognitive reserve or resilience in normal aging. Neurophysiologically, intelligence is considered as a complex capacity that is dependent on a global cognitive network rather than isolated brain areas. An association of structural as well as functional brain network characteristics with intelligence has already been reported in young adults. We investigated the relationship between global structural brain network properties, general intelligence and age in a group of 43 cognitively healthy elderly, age 60–85 years. Individuals were assessed cross-sectionally using Wechsler Adult Intelligence Scale-Revised (WAIS-R) and diffusion-tensor imaging. Structural brain networks were reconstructed individually using deterministic tractography, global network properties (global efficiency, mean shortest path length, and clustering coefficient) were determined by graph theory and correlated to intelligence scores within both age groups. Network properties were significantly correlated to age, whereas no significant correlation to WAIS-R was observed. However, in a subgroup of 15 individuals aged 75 and above, the network properties were significantly correlated to WAIS-R. Our findings suggest that general intelligence and global properties of structural brain networks may not be generally associated in cognitively healthy elderly. However, we provide first evidence of an association between global structural brain network properties and general intelligence in advanced elderly. Intelligence might be affected by age-associated network deterioration only if a certain threshold of structural degeneration is exceeded. Thus, age-associated brain structural changes seem to be partially compensated by the network and the range of this compensation might be a surrogate of cognitive reserve or brain resilience. PMID:24465994

Frontal Parietal Control Network Regulates the Anti-Correlated Default and Dorsal Attention Networks

OpenAIRE

Gao, Wei; Lin, Weili

2011-01-01

Recent reports demonstrate the anti-correlated behaviors between the default and the dorsal attention (DA) networks. We aimed to investigate the roles of the frontal parietal control (FPC) network in regulating the two anti-correlated networks through three experimental conditions, including resting, continuous self-paced/attended sequential finger tapping (FT), and natural movie watching (MW), respectively. The two goal-directed tasks were chosen to engage either one of the two competing net...

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.

Science.gov (United States)

Murakami, Masaya; Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-04-08

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks

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Masaya Murakami

2018-04-01

Full Text Available Virtualization of wireless sensor networks (WSN is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions and nodes (i.e., neurons. We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

Riemannian multi-manifold modeling and clustering in brain networks

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Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

Pre-attentive modulation of brain responses to tones in coloured-hearing synesthetes

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Jäncke Lutz

2012-12-01

Full Text Available Abstract Background Coloured-hearing (CH synesthesia is a perceptual phenomenon in which an acoustic stimulus (the inducer initiates a concurrent colour perception (the concurrent. Individuals with CH synesthesia "see" colours when hearing tones, words, or music; this specific phenomenon suggesting a close relationship between auditory and visual representations. To date, it is still unknown whether the perception of colours is associated with a modulation of brain functions in the inducing brain area, namely in the auditory-related cortex and associated brain areas. In addition, there is an on-going debate as to whether attention to the inducer is necessarily required for eliciting a visual concurrent, or whether the latter can emerge in a pre-attentive fashion. Results By using the EEG technique in the context of a pre-attentive mismatch negativity (MMN paradigm, we show that the binding of tones and colours in CH synesthetes is associated with increased MMN amplitudes in response to deviant tones supposed to induce novel concurrent colour perceptions. Most notably, the increased MMN amplitudes we revealed in the CH synesthetes were associated with stronger intracerebral current densities originating from the auditory cortex, parietal cortex, and ventral visual areas. Conclusions The automatic binding of tones and colours in CH synesthetes is accompanied by an early pre-attentive process recruiting the auditory cortex, inferior and superior parietal lobules, as well as ventral occipital areas.

Whole brain and brain regional coexpression network interactions associated with predisposition to alcohol consumption.

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Lauren A Vanderlinden

Full Text Available To identify brain transcriptional networks that may predispose an animal to consume alcohol, we used weighted gene coexpression network analysis (WGCNA. Candidate coexpression modules are those with an eigengene expression level that correlates significantly with the level of alcohol consumption across a panel of BXD recombinant inbred mouse strains, and that share a genomic region that regulates the module transcript expression levels (mQTL with a genomic region that regulates alcohol consumption (bQTL. To address a controversy regarding utility of gene expression profiles from whole brain, vs specific brain regions, as indicators of the relationship of gene expression to phenotype, we compared candidate coexpression modules from whole brain gene expression data (gathered with Affymetrix 430 v2 arrays in the Colorado laboratories and from gene expression data from 6 brain regions (nucleus accumbens (NA; prefrontal cortex (PFC; ventral tegmental area (VTA; striatum (ST; hippocampus (HP; cerebellum (CB available from GeneNetwork. The candidate modules were used to construct candidate eigengene networks across brain regions, resulting in three "meta-modules", composed of candidate modules from two or more brain regions (NA, PFC, ST, VTA and whole brain. To mitigate the potential influence of chromosomal location of transcripts and cis-eQTLs in linkage disequilibrium, we calculated a semi-partial correlation of the transcripts in the meta-modules with alcohol consumption conditional on the transcripts' cis-eQTLs. The function of transcripts that retained the correlation with the phenotype after correction for the strong genetic influence, implicates processes of protein metabolism in the ER and Golgi as influencing susceptibility to variation in alcohol consumption. Integration of these data with human GWAS provides further information on the function of polymorphisms associated with alcohol-related traits.

Functional disconnection of frontal cortex and visual cortex in attention-deficit/hyperactivity disorder.

NARCIS (Netherlands)

Mazaheri, A.; Coffey-Corina, S.; Mangun, G.R.; Bekker, E.M.; Berry, A.S.; Corbett, B.A.

2010-01-01

BACKGROUND: Current pathophysiologic models of attention-deficit/hyperactivity disorder (ADHD) suggest that impaired functional connectivity within brain attention networks may contribute to the disorder. In this electroencephalographic (EEG) study, we analyzed cross-frequency amplitude correlations

Attention to pain! A neurocognitive perspective on attentional modulation of pain in neuroimaging studies.

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Torta, D M; Legrain, V; Mouraux, A; Valentini, E

2017-04-01

Several studies have used neuroimaging techniques to investigate brain correlates of the attentional modulation of pain. Although these studies have advanced the knowledge in the field, important confounding factors such as imprecise theoretical definitions of attention, incomplete operationalization of the construct under exam, and limitations of techniques relying on measuring regional changes in cerebral blood flow have hampered the potential relevance of the conclusions. Here, we first provide an overview of the major theories of attention and of attention in the study of pain to bridge theory and experimental results. We conclude that load and motivational/affective theories are particularly relevant to study the attentional modulation of pain and should be carefully integrated in functional neuroimaging studies. Then, we summarize previous findings and discuss the possible neural correlates of the attentional modulation of pain. We discuss whether classical functional neuroimaging techniques are suitable to measure the effect of a fluctuating process like attention, and in which circumstances functional neuroimaging can be reliably used to measure the attentional modulation of pain. Finally, we argue that the analysis of brain networks and spontaneous oscillations may be a crucial future development in the study of attentional modulation of pain, and why the interplay between attention and pain, as examined so far, may rely on neural mechanisms shared with other sensory modalities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Network Dynamics with BrainX3: A Large-Scale Simulation of the Human Brain Network with Real-Time Interaction

OpenAIRE

Xerxes D. Arsiwalla; Riccardo eZucca; Alberto eBetella; Enrique eMartinez; David eDalmazzo; Pedro eOmedas; Gustavo eDeco; Gustavo eDeco; Paul F.M.J. Verschure; Paul F.M.J. Verschure

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Network dynamics with BrainX3: a large-scale simulation of the human brain network with real-time interaction

OpenAIRE

Arsiwalla, Xerxes D.; Zucca, Riccardo; Betella, Alberto; Martínez, Enrique, 1961-; Dalmazzo, David; Omedas, Pedro; Deco, Gustavo; Verschure, Paul F. M. J.

2015-01-01

BrainX3 is a large-scale simulation of human brain activity with real-time interaction, rendered in 3D in a virtual reality environment, which combines computational power with human intuition for the exploration and analysis of complex dynamical networks. We ground this simulation on structural connectivity obtained from diffusion spectrum imaging data and model it on neuronal population dynamics. Users can interact with BrainX3 in real-time by perturbing brain regions with transient stimula...

Brain network alterations and vulnerability to simulated neurodegeneration in breast cancer.

Science.gov (United States)

Kesler, Shelli R; Watson, Christa L; Blayney, Douglas W

2015-08-01

Breast cancer and its treatments are associated with mild cognitive impairment and brain changes that could indicate an altered or accelerated brain aging process. We applied diffusion tensor imaging and graph theory to measure white matter organization and connectivity in 34 breast cancer survivors compared with 36 matched healthy female controls. We also investigated how brain networks (connectomes) in each group responded to simulated neurodegeneration based on network attack analysis. Compared with controls, the breast cancer group demonstrated significantly lower fractional anisotropy, altered small-world connectome properties, lower brain network tolerance to systematic region (node), and connection (edge) attacks and significant cognitive impairment. Lower tolerance to network attack was associated with cognitive impairment in the breast cancer group. These findings provide further evidence of diffuse white matter pathology after breast cancer and extend the literature in this area with unique data demonstrating increased vulnerability of the post-breast cancer brain network to future neurodegenerative processes. Copyright © 2015 Elsevier Inc. All rights reserved.

How motivation and reward learning modulate selective attention.

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Bourgeois, A; Chelazzi, L; Vuilleumier, P

2016-01-01

Motivational stimuli such as rewards elicit adaptive responses and influence various cognitive functions. Notably, increasing evidence suggests that stimuli with particular motivational values can strongly shape perception and attention. These effects resemble both selective top-down and stimulus-driven attentional orienting, as they depend on internal states but arise without conscious will, yet they seem to reflect attentional systems that are functionally and anatomically distinct from those classically associated with frontoparietal cortical networks in the brain. Recent research in human and nonhuman primates has begun to reveal how reward can bias attentional selection, and where within the cognitive system the signals providing attentional priority are generated. This review aims at describing the different mechanisms sustaining motivational attention, their impact on different behavioral tasks, and current knowledge concerning the neural networks governing the integration of motivational influences on attentional behavior. © 2016 Elsevier B.V. All rights reserved.

Incorporating modern neuroscience findings to improve brain-computer interfaces: tracking auditory attention.

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Wronkiewicz, Mark; Larson, Eric; Lee, Adrian Kc

2016-10-01

Brain-computer interface (BCI) technology allows users to generate actions based solely on their brain signals. However, current non-invasive BCIs generally classify brain activity recorded from surface electroencephalography (EEG) electrodes, which can hinder the application of findings from modern neuroscience research. In this study, we use source imaging-a neuroimaging technique that projects EEG signals onto the surface of the brain-in a BCI classification framework. This allowed us to incorporate prior research from functional neuroimaging to target activity from a cortical region involved in auditory attention. Classifiers trained to detect attention switches performed better with source imaging projections than with EEG sensor signals. Within source imaging, including subject-specific anatomical MRI information (instead of using a generic head model) further improved classification performance. This source-based strategy also reduced accuracy variability across three dimensionality reduction techniques-a major design choice in most BCIs. Our work shows that source imaging provides clear quantitative and qualitative advantages to BCIs and highlights the value of incorporating modern neuroscience knowledge and methods into BCI systems.

Measuring the performance of attention networks with the Dalhousie Computerized Attention Battery (DalCAB: Methodology and reliability in healthy adults

Directory of Open Access Journals (Sweden)

Stephanie Anne Holland Jones

2016-06-01

Full Text Available Attention is an important, multifaceted cognitive domain that has been linked to three distinct, yet interacting, networks: alerting, orienting, and executive control. The measurement of attention and deficits of attention within these networks is critical to the assessment of many neurological and psychiatric conditions in both research and clinical settings. The Dalhousie Computerized Attention Battery (DalCAB was created to assess attentional functions related to the three attention networks using a range of tasks including: simple reaction time, go/no-go, choice reaction time, dual task, flanker, item and location working memory and visual search. The current study provides preliminary normative data, test-retest reliability (intraclass correlations and practice effects in DalCAB performance 24-hours after baseline for healthy young adults (n = 96, 18-31 years. Performance on the DalCAB tasks demonstrated Good to Excellent test-retest reliability for mean reaction time, while accuracy and difference measures (e.g., switch costs, interference effects and working memory load effects were most reliable for tasks that require more extensive cognitive processing (e.g., choice reaction time, flanker, dual task, and conjunction search. Practice effects were common and pronounced at the 24-hour interval. In addition, performance related to specific within-task parameters of the DalCAB sub-tests provides preliminary support for future formal assessment of the convergent validity of our interpretation of the DalCAB as a potential clinical and research assessment tool for measuring aspects of attention related to the alerting, orienting and executive control networks.Keywords: computerized assessment; attention; orienting; alerting; executive function

The minimum spanning tree : An unbiased method for brain network analysis

NARCIS (Netherlands)

Tewarie, P.; van Dellen, E.; Hillebrand, A.; Stam, C. J.

2015-01-01

The brain is increasingly studied with graph theoretical approaches, which can be used to characterize network topology. However, studies on brain networks have reported contradictory findings, and do not easily converge to a clear concept of the structural and functional network organization of the

Intrinsic and task-evoked network architectures of the human brain

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Cole, Michael W.; Bassett, Danielle S.; Power, Jonathan D.; Braver, Todd S.; Petersen, Steven E.

2014-01-01

Summary Many functional network properties of the human brain have been identified during rest and task states, yet it remains unclear how the two relate. We identified a whole-brain network architecture present across dozens of task states that was highly similar to the resting-state network architecture. The most frequent functional connectivity strengths across tasks closely matched the strengths observed at rest, suggesting this is an “intrinsic”, standard architecture of functional brain organization. Further, a set of small but consistent changes common across tasks suggests the existence of a task-general network architecture distinguishing task states from rest. These results indicate the brain’s functional network architecture during task performance is shaped primarily by an intrinsic network architecture that is also present during rest, and secondarily by evoked task-general and task-specific network changes. This establishes a strong relationship between resting-state functional connectivity and task-evoked functional connectivity – areas of neuroscientific inquiry typically considered separately. PMID:24991964

Hierarchical modularity in human brain functional networks

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David Meunier

2009-10-01

Full Text Available The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or “modules-within-modules” decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions.

The application of graph theoretical analysis to complex networks in the brain.

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Reijneveld, Jaap C; Ponten, Sophie C; Berendse, Henk W; Stam, Cornelis J

2007-11-01

Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.

Development of human brain structural networks through infancy and childhood.

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Huang, Hao; Shu, Ni; Mishra, Virendra; Jeon, Tina; Chalak, Lina; Wang, Zhiyue J; Rollins, Nancy; Gong, Gaolang; Cheng, Hua; Peng, Yun; Dong, Qi; He, Yong

2015-05-01

During human brain development through infancy and childhood, microstructural and macrostructural changes take place to reshape the brain's structural networks and better adapt them to sophisticated functional and cognitive requirements. However, structural topological configuration of the human brain during this specific development period is not well understood. In this study, diffusion magnetic resonance image (dMRI) of 25 neonates, 13 toddlers, and 25 preadolescents were acquired to characterize network dynamics at these 3 landmark cross-sectional ages during early childhood. dMRI tractography was used to construct human brain structural networks, and the underlying topological properties were quantified by graph-theory approaches. Modular organization and small-world attributes are evident at birth with several important topological metrics increasing monotonically during development. Most significant increases of regional nodes occur in the posterior cingulate cortex, which plays a pivotal role in the functional default mode network. Positive correlations exist between nodal efficiencies and fractional anisotropy of the white matter traced from these nodes, while correlation slopes vary among the brain regions. These results reveal substantial topological reorganization of human brain structural networks through infancy and childhood, which is likely to be the outcome of both heterogeneous strengthening of the major white matter tracts and pruning of other axonal fibers. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Fetal brain extracellular matrix boosts neuronal network formation in 3D bioengineered model of cortical brain tissue.

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Sood, Disha; Chwalek, Karolina; Stuntz, Emily; Pouli, Dimitra; Du, Chuang; Tang-Schomer, Min; Georgakoudi, Irene; Black, Lauren D; Kaplan, David L

2016-01-01

The extracellular matrix (ECM) constituting up to 20% of the organ volume is a significant component of the brain due to its instructive role in the compartmentalization of functional microdomains in every brain structure. The composition, quantity and structure of ECM changes dramatically during the development of an organism greatly contributing to the remarkably sophisticated architecture and function of the brain. Since fetal brain is highly plastic, we hypothesize that the fetal brain ECM may contain cues promoting neural growth and differentiation, highly desired in regenerative medicine. Thus, we studied the effect of brain-derived fetal and adult ECM complemented with matricellular proteins on cortical neurons using in vitro 3D bioengineered model of cortical brain tissue. The tested parameters included neuronal network density, cell viability, calcium signaling and electrophysiology. Both, adult and fetal brain ECM as well as matricellular proteins significantly improved neural network formation as compared to single component, collagen I matrix. Additionally, the brain ECM improved cell viability and lowered glutamate release. The fetal brain ECM induced superior neural network formation, calcium signaling and spontaneous spiking activity over adult brain ECM. This study highlights the difference in the neuroinductive properties of fetal and adult brain ECM and suggests that delineating the basis for this divergence may have implications for regenerative medicine.

Shared vs. specific brain activation changes in dyslexia after training of phonology, attention, or reading.

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Heim, Stefan; Pape-Neumann, Julia; van Ermingen-Marbach, Muna; Brinkhaus, Moti; Grande, Marion

2015-07-01

Whereas the neurobiological basis of developmental dyslexia has received substantial attention, only little is known about the processes in the brain during remediation. This holds in particular in light of recent findings on cognitive subtypes of dyslexia which suggest interactions between individual profiles, training methods, and also the task in the scanner. Therefore, we trained three groups of German dyslexic primary school children in the domains of phonology, attention, or visual word recognition. We compared neurofunctional changes after 4 weeks of training in these groups to those in untrained normal readers in a reading task and in a task of visual attention. The overall reading improvement in the dyslexic children was comparable over groups. It was accompanied by substantial increase of the activation level in the visual word form area (VWFA) during a reading task inside the scanner. Moreover, there were activation increases that were unique for each training group in the reading task. In contrast, when children performed the visual attention task, shared training effects were found in the left inferior frontal sulcus and gyrus, which varied in amplitude between the groups. Overall, the data reveal that different remediation programmes matched to individual profiles of dyslexia may improve reading ability and commonly affect the VWFA in dyslexia as a shared part of otherwise distinct networks.

Disentangling the Attention Network Test: Behavioral, Event Related Potentials and neural source analyses.

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Alejandro eGalvao-Carmona

2014-10-01

Full Text Available Background. The study of the attentional system remains a challenge for current neuroscience. The Attention Network Test (ANT was designed to study simultaneously three different attentional networks (alerting, orienting and executive based in subtraction of different experimental conditions. However, some studies recommend caution with these calculations due to the interactions between the attentional networks. In particular, it is highly relevant that several interpretations about attentional impairment have arisen from these calculations in diverse pathologies. Event Related Potentials (ERPs and neural source analysis can be applied to disentangle the relationships between these attentional networks not specifically shown by behavioural measures. Results. This study shows that there is a basic level of alerting (tonic alerting in the no cue condition, represented by a slow negative trend in the ERP trace prior to the onset of the target stimuli. A progressive increase in the CNV amplitude related to the amount of information provided by the cue conditions is also shown. Neural source analysis reveals specific modulations of the CNV related to a task-related expectancy presented in the no cue condition; a late modulation triggered by the central cue condition and probably representing a generic motor preparation; and an early and late modulation for spatial cue condition suggesting specific motor and sensory preactivation. Finally, the first component in the information processing of the target stimuli modulated by the interaction between orienting network and the executive system can be represented by N1. Conclusions. The ANT is useful as a paradigm to study specific attentional mechanisms and their interactions. However, calculation of network effects is based in subtractions with non-comparable experimental conditions, as evidenced by the present data, which can induce misinterpretations in the study of the attentional capacity in human

Local Immediate versus Long-Range Delayed Changes in Functional Connectivity Following rTMS on the Visual Attention Network.

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Battelli, Lorella; Grossman, Emily D; Plow, Ela B

The interhemispheric competition hypothesis attributes the distribution of selective attention to a balance of mutual inhibition between homotopic, interhemispheric connections in parietal cortex (Kinsbourne 1977; Battelli et al., 2009). In support of this hypothesis, repetitive inhibitory TMS over right parietal cortex in healthy individuals rapidly induces interhemispheric imbalance in cortical activity that spreads beyond the site of stimulation (Plow et al., 2014). Behaviorally, the impacts of inhibitory rTMS may be long delayed from the onset of stimulation, as much as 30 minutes (Agosta et al., 2014; Hubl et al., 2008). In this study, we examine the temporal dynamics of inhibitory rTMS on cortical network integrity that supports sustained visual attention. Healthy individuals received 15 min of 1 Hz offline, inhibitory rTMS (or sham) over left parietal cortex, and then immediately engaged in a bilateral visual tracking task while we recorded brain activity with fMRI. We computed functional connectivity (FC) between three nodes of the attention network engaged by visual tracking: the intraparietal sulcus (IPS), frontal eye fields (FEF) and human MT+ (hMT+). FC immediately and significantly decreased between the stimulation site (left IPS) and all other regions, then recovered to normal levels within 30 minutes. rTMS increased FC between left and right FEF at approximately 36 min following stimulation, and between sites in the unstimulated hemisphere approximately 48 min after stimulation. These findings demonstrate large-scale changes in cortical organization following inhibitory rTMS. The immediate impact of rTMS on connectivity to the stimulation site dovetails with the putative role of interhemispheric balance for bilateral visual sustained attention. The delayed, compensatory increases in functional connectivity have implications for models of dynamic reorganization in networks supporting spatial and nonspatial selective attention, and

Time Course of Brain Network Reconfiguration Supporting Inhibitory Control.

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Popov, Tzvetan; Westner, Britta U; Silton, Rebecca L; Sass, Sarah M; Spielberg, Jeffrey M; Rockstroh, Brigitte; Heller, Wendy; Miller, Gregory A

2018-05-02

Hemodynamic research has recently clarified key nodes and links in brain networks implementing inhibitory control. Although fMRI methods are optimized for identifying the structure of brain networks, the relatively slow temporal course of fMRI limits the ability to characterize network operation. The latter is crucial for developing a mechanistic understanding of how brain networks shift dynamically to support inhibitory control. To address this critical gap, we applied spectrally resolved Granger causality (GC) and random forest machine learning tools to human EEG data in two large samples of adults (test sample n = 96, replication sample n = 237, total N = 333, both sexes) who performed a color-word Stroop task. Time-frequency analysis confirmed that recruitment of inhibitory control accompanied by slower behavioral responses was related to changes in theta and alpha/beta power. GC analyses revealed directionally asymmetric exchanges within frontal and between frontal and parietal brain areas: top-down influence of superior frontal gyrus (SFG) over both dorsal ACC (dACC) and inferior frontal gyrus (IFG), dACC control over middle frontal gyrus (MFG), and frontal-parietal exchanges (IFG, precuneus, MFG). Predictive analytics confirmed a combination of behavioral and brain-derived variables as the best set of predictors of inhibitory control demands, with SFG theta bearing higher classification importance than dACC theta and posterior beta tracking the onset of behavioral response. The present results provide mechanistic insight into the biological implementation of a psychological phenomenon: inhibitory control is implemented by dynamic routing processes during which the target response is upregulated via theta-mediated effective connectivity within key PFC nodes and via beta-mediated motor preparation. SIGNIFICANCE STATEMENT Hemodynamic neuroimaging research has recently clarified regional structures in brain networks supporting inhibitory control. However, due to

The development of brain network architecture.

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Wierenga, Lara M; van den Heuvel, Martijn P; van Dijk, Sarai; Rijks, Yvonne; de Reus, Marcel A; Durston, Sarah

2016-02-01

Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes in network topology and regional developmental patterns during childhood and adolescence. We acquired two sets of Diffusion Weighted Imaging-scans and anatomical T1-weighted scans. The first dataset included 85 typically developing individuals (53 males; 32 females), aged between 7 and 23 years and was acquired on a Philips Achieva 1.5 Tesla scanner. A second dataset (N = 38) was acquired on a different (but identical) 1.5 T scanner and was used for independent replication of our results. We reconstructed whole brain networks using tractography. We operationalized fiber tract development as changes in mean diffusivity and radial diffusivity with age. Most fibers showed maturational changes in mean and radial diffusivity values throughout childhood and adolescence, likely reflecting increasing white matter integrity. The largest age-related changes were observed in association fibers within and between the frontal and parietal lobes. Furthermore, there was a simultaneous age-related decrease in average path length (P maturational model where connections between unimodal regions strengthen in childhood, followed by connections from these unimodal regions to association regions, while adolescence is characterized by the strengthening of connections between association regions within the frontal and parietal cortex. Hum Brain Mapp 37:717-729, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A study of brain networks associated with swallowing using graph-theoretical approaches.

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Bo Luan

Full Text Available Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, [Formula: see text] years of age. To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.

Handedness- and Brain Size-Related Efficiency Differences in Small-World Brain Networks: A Resting-State Functional Magnetic Resonance Imaging Study

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Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

2015-01-01

The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical...

New Perspectives on Spontaneous Brain Activity: Dynamic Networks and Energy Matter.

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Tozzi, Arturo; Zare, Marzieh; Benasich, April A

2016-01-01

Spontaneous brain activity has received increasing attention as demonstrated by the exponential rise in the number of published article on this topic over the last 30 years. Such "intrinsic" brain activity, generated in the absence of an explicit task, is frequently associated with resting-state or default-mode networks (DMN)s. The focus on characterizing spontaneous brain activity promises to shed new light on questions concerning the structural and functional architecture of the brain and how they are related to "mind". However, many critical questions have yet to be addressed. In this review, we focus on a scarcely explored area, specifically the energetic requirements and constraints of spontaneous activity, taking into account both thermodynamical and informational perspectives. We argue that the "classical" definitions of spontaneous activity do not take into account an important feature, that is, the critical thermodynamic energetic differences between spontaneous and evoked brain activity. Spontaneous brain activity is associated with slower oscillations compared with evoked, task-related activity, hence it exhibits lower levels of enthalpy and "free-energy" (i.e., the energy that can be converted to do work), thus supporting noteworthy thermodynamic energetic differences between spontaneous and evoked brain activity. Increased spike frequency during evoked activity has a significant metabolic cost, consequently, brain functions traditionally associated with spontaneous activity, such as mind wandering, require less energy that other nervous activities. We also review recent empirical observations in neuroscience, in order to capture how spontaneous brain dynamics and mental function can be embedded in a non-linear dynamical framework, which considers nervous activity in terms of phase spaces, particle trajectories, random walks, attractors and/or paths at the edge of the chaos. This takes us from the thermodynamic free-energy, to the realm of "variational

Is the ADHD brain wired differently? A review on structural and functional connectivity in attention deficit hyperactivity disorder.

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Konrad, Kerstin; Eickhoff, Simon B

2010-06-01

In recent years, a change in perspective in etiological models of attention deficit hyperactivity disorder (ADHD) has occurred in concordance with emerging concepts in other neuropsychiatric disorders such as schizophrenia and autism. These models shift the focus of the assumed pathology from regional brain abnormalities to dysfunction in distributed network organization. In the current contribution, we report findings from functional connectivity studies during resting and task states, as well as from studies on structural connectivity using diffusion tensor imaging, in subjects with ADHD. Although major methodological limitations in analyzing connectivity measures derived from noninvasive in vivo neuroimaging still exist, there is convergent evidence for white matter pathology and disrupted anatomical connectivity in ADHD. In addition, dysfunctional connectivity during rest and during cognitive tasks has been demonstrated. However, the causality between disturbed white matter architecture and cortical dysfunction remains to be evaluated. Both genetic and environmental factors might contribute to disruptions in interactions between different brain regions. Stimulant medication not only modulates regionally specific activation strength but also normalizes dysfunctional connectivity, pointing to a predominant network dysfunction in ADHD. By combining a longitudinal approach with a systems perspective in ADHD in the future, it might be possible to identify at which stage during development disruptions in neural networks emerge and to delineate possible new endophenotypes of ADHD. (c) 2010 Wiley-Liss, Inc.

Selective attention to affective value alters how the brain processes olfactory stimuli.

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Rolls, Edmund T; Grabenhorst, Fabian; Margot, Christian; da Silva, Maria A A P; Velazco, Maria Ines

2008-10-01

How does selective attention to affect influence sensory processing? In a functional magnetic resonance imaging investigation, when subjects were instructed to remember and rate the pleasantness of a jasmine odor, activations were greater in the medial orbito-frontal and pregenual cingulate cortex than when subjects were instructed to remember and rate the intensity of the odor. When the subjects were instructed to remember and rate the intensity, activations were greater in the inferior frontal gyrus. These top-down effects occurred not only during odor delivery but started in a preparation period after the instruction before odor delivery, and continued after termination of the odor in a short-term memory period. Thus, depending on the context in which odors are presented and whether affect is relevant, the brain prepares itself, responds to, and remembers an odor differently. These findings show that when attention is paid to affective value, the brain systems engaged to prepare for, represent, and remember a sensory stimulus are different from those engaged when attention is directed to the physical properties of a stimulus such as its intensity. This differential biasing of brain regions engaged in processing a sensory stimulus depending on whether the cognitive demand is for affect-related versus more sensory-related processing may be an important aspect of cognition and attention. This has many implications for understanding the effects not only of olfactory but also of other sensory stimuli.

From behavior to neural dynamics: An integrated theory of attention

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Buschman, Timothy J.; Kastner, Sabine

2015-01-01

The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention. PMID:26447577

Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

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Kabbara, A; Eid, H; El Falou, W; Khalil, M; Wendling, F; Hassan, M

2018-04-01

Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients' functional brain networks and their cognitive scores. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

Measuring the Performance of Attention Networks with the Dalhousie Computerized Attention Battery (DalCAB): Methodology and Reliability in Healthy Adults.

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Jones, Stephanie A H; Butler, Beverly C; Kintzel, Franziska; Johnson, Anne; Klein, Raymond M; Eskes, Gail A

2016-01-01

Attention is an important, multifaceted cognitive domain that has been linked to three distinct, yet interacting, networks: alerting, orienting, and executive control. The measurement of attention and deficits of attention within these networks is critical to the assessment of many neurological and psychiatric conditions in both research and clinical settings. The Dalhousie Computerized Attention Battery (DalCAB) was created to assess attentional functions related to the three attention networks using a range of tasks including: simple reaction time, go/no-go, choice reaction time, dual task, flanker, item and location working memory, and visual search. The current study provides preliminary normative data, test-retest reliability (intraclass correlations) and practice effects in DalCAB performance 24-h after baseline for healthy young adults (n = 96, 18-31 years). Performance on the DalCAB tasks demonstrated Good to Very Good test-retest reliability for mean reaction time, while accuracy and difference measures (e.g., switch costs, interference effects, and working memory load effects) were most reliable for tasks that require more extensive cognitive processing (e.g., choice reaction time, flanker, dual task, and conjunction search). Practice effects were common and pronounced at the 24-h interval. In addition, performance related to specific within-task parameters of the DalCAB sub-tests provides preliminary support for future formal assessment of the convergent validity of our interpretation of the DalCAB as a potential clinical and research assessment tool for measuring aspects of attention related to the alerting, orienting, and executive control networks.

Functional brain networks in schizophrenia: a review

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Vince D Calhoun

2009-08-01

Full Text Available Functional magnetic resonance imaging (fMRI has become a major technique for studying cognitive function and its disruption in mental illness, including schizophrenia. The major proportion of imaging studies focused primarily upon identifying regions which hemodynamic response amplitudes covary with particular stimuli and differentiate between patient and control groups. In addition to such amplitude based comparisons, one can estimate temporal correlations and compute maps of functional connectivity between regions which include the variance associated with event related responses as well as intrinsic fluctuations of hemodynamic activity. Functional connectivity maps can be computed by correlating all voxels with a seed region when a spatial prior is available. An alternative are multivariate decompositions such as independent component analysis (ICA which extract multiple components, each of which is a spatially distinct map of voxels with a common time course. Recent work has shown that these networks are pervasive in relaxed resting and during task performance and hence provide robust measures of intact and disturbed brain activity. This in turn bears the prospect of yielding biomarkers for schizophrenia, which can be described both in terms of disrupted local processing as well as altered global connectivity between large scale networks. In this review we will summarize functional connectivity measures with a focus upon work with ICA and discuss the meaning of intrinsic fluctuations. In addition, examples of how brain networks have been used for classification of disease will be shown. We present work with functional network connectivity, an approach that enables the evaluation of the interplay between multiple networks and how they are affected in disease. We conclude by discussing new variants of ICA for extracting maximally group discriminative networks from data. In summary, it is clear that identification of brain networks and their

Low-dimensional morphospace of topological motifs in human fMRI brain networks

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Sarah E. Morgan

2018-06-01

Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.

Association of familial risk for schizophrenia with thalamic and medial prefrontal functional connectivity during attentional control.

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Antonucci, Linda A; Taurisano, Paolo; Fazio, Leonardo; Gelao, Barbara; Romano, Raffaella; Quarto, Tiziana; Porcelli, Annamaria; Mancini, Marina; Di Giorgio, Annabella; Caforio, Grazia; Pergola, Giulio; Popolizio, Teresa; Bertolino, Alessandro; Blasi, Giuseppe

2016-05-01

Anomalies in behavioral correlates of attentional processing and related brain activity are crucial correlates of schizophrenia and associated with familial risk for this brain disorder. However, it is not clear how brain functional connectivity during attentional processes is key for schizophrenia and linked with trait vs. state related variables. To address this issue, we investigated patterns of functional connections during attentional control in healthy siblings of patients with schizophrenia, who share with probands genetic features but not variables related to the state of the disorder. 356 controls, 55 patients with schizophrenia on stable treatment with antipsychotics and 40 healthy siblings of patients with this brain disorder underwent the Variable Attentional Control (VAC) task during fMRI. Independent Component Analysis (ICA) is allowed to identify independent components (IC) of BOLD signal recorded during task performance. Results indicated reduced connectivity strength in patients with schizophrenia as well as in their healthy siblings in left thalamus within an attentional control component and greater connectivity in right medial prefrontal cortex (PFC) within the so-called Default Mode Network (DMN) compared to healthy individuals. These results suggest a relationship between familial risk for schizophrenia and brain functional networks during attentional control, such that this biological phenotype may be considered a useful intermediate phenotype in order to link genes effects to aspects of the pathophysiology of this brain disorder. Copyright © 2016 Elsevier B.V. All rights reserved.