Default mode-visual network hypoconnectivity in an autism subtype with pronounced social visual engagement difficulties

Social visual engagement difficulties are hallmark early signs of autism (ASD) and are easily quantified using eye tracking methods. However, it is unclear how these difficulties are linked to atypical early functional brain organization in ASD. With resting state fMRI data in a large sample of ASD toddlers and other non-ASD comparison groups, we find ASD-related functional hypoconnnectivity between ‘social brain’ circuitry such as the default mode network (DMN) and visual and attention networks. An eye tracking-identified ASD subtype with pronounced early social visual engagement difficulties (GeoPref ASD) is characterized by marked DMN-occipito-temporal cortex (OTC) hypoconnectivity. Increased DMN-OTC hypoconnectivity is also related to increased severity of social-communication difficulties, but only in GeoPref ASD. Early and pronounced social-visual circuit hypoconnectivity is a key underlying neurobiological feature describing GeoPref ASD and may be critical for future social-communicative development and represent new treatment targets for early intervention in these individuals.

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Large-Scale Intrinsic Functional Brain Organization Emerges from Three Canonical Spatiotemporal Patterns

10.1101/2021.06.20.448984 ◽

2021 ◽

Author(s):

Taylor S Bolt ◽

Jason Nomi ◽

Danilo Bzdok ◽

Catie Chang ◽

B.T. Thomas Yeo ◽

...

Keyword(s):

Resting State ◽

Large Scale ◽

Low Frequency ◽

Resting State Fmri ◽

Spatiotemporal Patterns ◽

Brain Organization ◽

Functional Brain ◽

Temporal Properties ◽

Human Connectome Project ◽

Functional Brain Organization

The characterization of intrinsic functional brain organization has been approached from a multitude of analytic techniques and methods. We are still at a loss of a unifying conceptual framework for capturing common insights across this patchwork of empirical findings. By analyzing resting-state fMRI data from the Human Connectome Project using a large number of popular analytic techniques, we find that all results can be seamlessly reconciled by three fundamental low-frequency spatiotemporal patterns that we have identified via a novel time-varying complex pattern analysis. Overall, these three spatiotemporal patterns account for a wide variety of previously observed phenomena in the resting-state fMRI literature including the task-positive/task-negative anticorrelation, the global signal, the primary functional connectivity gradient and the network community structure of the functional connectome. The shared spatial and temporal properties of these three canonical patterns suggest that they arise from a single hemodynamic mechanism.

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A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum

10.1101/450452 ◽

2018 ◽

Cited By ~ 2

Author(s):

Benjamin A. Seitzman ◽

Caterina Gratton ◽

Scott Marek ◽

Ryan V. Raut ◽

Nico U.F. Dosenbach ◽

...

Keyword(s):

Resting State Fmri ◽

Brain Regions ◽

Brain Network ◽

Functional Network ◽

Network Organization ◽

Brain Organization ◽

Functional Brain ◽

Network Analyses ◽

Functional Brain Network ◽

Functional Brain Organization

AbstractAn important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011 and (2) 333 cortical surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets using several criteria, including agreement with existing literature and anatomical atlases. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.

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Large-Scale Intrinsic Functional Brain Organization Emerges from Three Canonical Spatiotemporal Patterns

10.21203/rs.3.rs-659082/v1 ◽

2021 ◽

Author(s):

Taylor Bolt ◽

Jason Nomi ◽

Danilo Bzdok ◽

Catie Chang ◽

B.T. Yeo ◽

...

Keyword(s):

Large Scale ◽

Functional Neuroimaging ◽

Time Lag ◽

Low Frequency ◽

Resting State Fmri ◽

Spatiotemporal Patterns ◽

Brain Organization ◽

Functional Brain ◽

Global Signal ◽

Functional Brain Organization

Abstract The past decade of functional neuroimaging research has seen the application of increasingly sophisticated advanced methods to characterize intrinsic functional brain organization. Accompanying these techniques are a patchwork of empirical findings highlighting novel properties of intrinsic functional brain organization. To date, there has been little attempt to understand whether there is an underlying unity across this patchwork of empirical findings. Our study conducted a systematic survey of popular analytic techniques and their output on a large sample of resting-state fMRI data. We found that the apparent complexity of intrinsic functional brain organization can be seamlessly reduced to three fundamental low-frequency spatiotemporal patterns. Our study demonstrates that a long list of previously observed phenomena, including functional connectivity gradients, the task-positive/task-negative pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern and the network structure of the functional connectome are simply manifestations of these three spatiotemporal patterns. An in-depth characterization of these three spatiotemporal patterns using a novel time-varying complex pattern analysis revealed that these three patterns may arise from a single hemodynamic mechanism.

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Age development of cortical rhythmics in the EEG depending on the formation of the child’s personal psychical characteristics

Medical alphabet ◽

10.33667/2078-5631-2019-1-8(383)-42-48 ◽

2019 ◽

Vol 1 (8) ◽

pp. 42-50

Author(s):

A. V. Budkevich ◽

L. B. Ivanov ◽

G. R. Novikova ◽

G. M. Dzhanumova

Keyword(s):

Alpha Rhythm ◽

Age Groups ◽

Healthy Children ◽

Brain Organization ◽

Age Related ◽

Mathematical Processing ◽

Functional Brain Organization ◽

Child's Brain ◽

Attention Function ◽

Apparently Healthy

According to the authors, rationing the age-related EEG parameters in children should be based on personal psychical characteristics. A comparative analysis of personal psychical characteristics and electroencephalographic data was carried out in 300 apparently healthy children aged 3-15 years. According to this principle, two subgroups of conditionally healthy children in each age group were singled out: 1) with an immature attention function and 2) with an increased anxious background that do not reach the pathological level. Registration and analysis of EEG was performed by the Neurokariograf computer complex (MBN, Moscow) using mathematical processing methods.The EEG interpretation was based on the principle of assessing the functional state of a child's brain using a three-component model according to: 1) wakefulness level and its dissociation, 2) severity of signs of the EEG neurotic pattern, 3) directionality of formation of traits of the system-functional brain organization (severity of signs functional hypofrontality).lt was found the presence of EEG signs was indicative of a lower level of wakefulness in children with an immature function of attention in all age groups, compared with the indicators of the average population of group and children with an increased background of anxiety. Children with an increased background of anxiety have a tendency to prevalence and excessive spatial synchronization of the alpha rhythm. ln healthy children, the fact of a decrease in wakefulness and the presence of signs of anxiety in the clinic and in EEG patterns indicates individual personalities and should not be considered as pathology.

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Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study

NeuroImage ◽

10.1016/j.neuroimage.2020.117581 ◽

2021 ◽

Vol 226 ◽

pp. 117581

Author(s):

Fengmei Fan ◽

Xuhong Liao ◽

Tianyuan Lei ◽

Tengda Zhao ◽

Mingrui Xia ◽

...

Keyword(s):

Default Mode Network ◽

Resting State ◽

Resting State Fmri ◽

Childhood And Adolescence ◽

Default Mode ◽

Fmri Study

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Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry

Communications Biology ◽

10.1038/s42003-021-02015-2 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Natasha Bertelsen ◽

◽

Isotta Landi ◽

Richard A. I. Bethlehem ◽

Jakob Seidlitz ◽

...

Keyword(s):

Repetitive Behavior ◽

Resting State Fmri ◽

Neural Circuitry ◽

Autism Spectrum ◽

Repetitive Behaviors ◽

Typically Developing ◽

Out Of Sample ◽

Genetic Mechanisms ◽

Social Communicative ◽

The Eu

AbstractSocial-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

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Visual engagement with urban street edges: insights using mobile eye-tracking

Journal of Urbanism International Research on Placemaking and Urban Sustainability ◽

10.1080/17549175.2018.1552884 ◽

2018 ◽

Vol 12 (3) ◽

pp. 259-278 ◽

Cited By ~ 5

Author(s):

James Simpson ◽

Megan Freeth ◽

Kimberley J. Simpson ◽

Kevin Thwaites

Keyword(s):

Eye Tracking ◽

Urban Street ◽

Visual Engagement ◽

Mobile Eye Tracking

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Comparison of EEG microstates with resting state fMRI and FDG-PET measures in the default mode network via simultaneously recorded trimodal (PET/MR/EEG) data

Human Brain Mapping ◽

10.1002/hbm.24429 ◽

2018 ◽

Cited By ~ 4

Author(s):

Ravichandran Rajkumar ◽

Ezequiel Farrher ◽

Jörg Mauler ◽

Praveen Sripad ◽

Cláudia Régio Brambilla ◽

...

Keyword(s):

Default Mode Network ◽

Resting State ◽

Fdg Pet ◽

Resting State Fmri ◽

Default Mode ◽

Eeg Data

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Neurophysiology (fMRI)

Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques ◽

10.1017/cjn.2015.173 ◽

2015 ◽

Vol 42 (S1) ◽

pp. S38-S38

Author(s):

ST Lang ◽

B Goodyear ◽

J Kelly ◽

P Federico

Keyword(s):

Cognitive Functioning ◽

Default Mode Network ◽

Resting State ◽

Attentional Control ◽

Brain Tumours ◽

Resting State Fmri ◽

Fmri Data ◽

Resting State Networks ◽

Default Mode ◽

Eloquent Cortex

Background: Resting state functional MRI (rs-fMRI) provides many advantages to task-based fMRI in neurosurgical populations, foremost of which is the lack of the need to perform a task. Many networks can be identified by rs-fMRI in a single period of scanning. Despite the advantages, there is a paucity of literature on rs-fMRI in neurosurgical populations. Methods: Eight patients with tumours near areas traditionally considered as eloquent cortex participated in a five minute rs-fMRI scan. Resting-state fMRI data underwent Independent Component Analysis (ICA) using the Multivariate Exploratory Linear Optimized Decomposition into Independent Components (MELODIC) toolbox in FSL. Resting state networks (RSNs) were identified on a visual basis. Results: Several RSNs, including language (N=7), sensorimotor (N=7), visual (N=7), default mode network (N=8) and frontoparietal attentional control (n=7) networks were readily identifiable using ICA of rs-fMRI data. Conclusion: These pilot data suggest that ICA applied to rs-fMRI data can be used to identify motor and language networks in patients with brain tumours. We have also shown that RSNs associated with cognitive functioning, including the default mode network and the frontoparietal attentional control network can be identified in individual subjects with brain tumours. While preliminary, this suggests that rs-fMRI may be used pre-operatively to localize areas of cortex important for higher order cognitive functioning.

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