scholarly journals Hierarchical Heterogeneity Across Human Cortex Shapes Large-Scale Neural Dynamics

2018 ◽  
Author(s):  
Murat Demirtaş ◽  
Joshua B. Burt ◽  
Markus Helmer ◽  
Jie Lisa Ji ◽  
Brendan D. Adkinson ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Spectral Power ◽  
Resting State Functional Connectivity ◽  
Human Cortex ◽  
Cortical Organization ◽  
Long Range Interactions ◽  
Neuroimaging Data ◽  
Local Properties ◽  
Local Circuits

SummaryThe large-scale organization of dynamical neural activity across cortex emerges through long-range interactions among local circuits. We hypothesized that large-scale dynamics are also shaped by heterogeneity of intrinsic local properties across cortical areas. One key axis along which microcircuit properties are specialized relates to hierarchical levels of cortical organization. We developed a large-scale dynamical circuit model of human cortex that incorporates heterogeneity of local synaptic strengths, following a hierarchical axis inferred from MRI-derived T1w/T2w mapping, and fit the model using multimodal neuroimaging data. We found that incorporating hierarchical heterogeneity substantially improves the model fit to fMRI-measured resting-state functional connectivity and captures sensory-association organization of multiple fMRI features. The model predicts hierarchically organized high-frequency spectral power, which we tested with resting-state magnetoencephalography. These findings suggest circuit-level mechanisms linking spatiotemporal levels of analysis and highlight the importance of local properties and their hierarchical specialization on the large-scale organization of human cortical dynamics.

scholarly journals Attention network modulation via tRNS correlates with attention gain

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Federica Contò ◽  
Grace Edwards ◽  
Sarah Tyler ◽  
Danielle Parrott ◽  
Emily Grossman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Random Noise ◽  
Cognitive Capacity ◽  
Resting State Functional Connectivity ◽  
Attention Network ◽  
Transcranial Random Noise Stimulation ◽  
The Impact ◽  
Behavioral Improvement

Transcranial random noise stimulation (tRNS) can enhance vision in the healthy and diseased brain. Yet, the impact of multi-day tRNS on large-scale cortical networks is still unknown. We investigated the impact of tRNS coupled with behavioral training on resting-state functional connectivity and attention. We trained human subjects for 4 consecutive days on two attention tasks, while receiving tRNS over the intraparietal sulci, the middle temporal areas, or Sham stimulation. We measured resting-state functional connectivity of nodes of the dorsal and ventral attention network (DVAN) before and after training. We found a strong behavioral improvement and increased connectivity within the DVAN after parietal stimulation only. Crucially, behavioral improvement positively correlated with connectivity measures. We conclude changes in connectivity are a marker for the enduring effect of tRNS upon behavior. Our results suggest that tRNS has strong potential to augment cognitive capacity in healthy individuals and promote recovery in the neurological population.

scholarly journals Sex-specific differences in resting-state functional connectivity of large-scale networks in postconcussion syndrome

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Reema Shafi ◽  
Adrian P. Crawley ◽  
Maria Carmela Tartaglia ◽  
Charles H. Tator ◽  
Robin E. Green ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Regions ◽  
Healthy Controls ◽  
Postconcussion Syndrome ◽  
Resting State Functional Connectivity ◽  
Post Injury ◽  
Network Nodes ◽  
Specific Impact

AbstractConcussions are associated with a range of cognitive, neuropsychological and behavioral sequelae that, at times, persist beyond typical recovery times and are referred to as postconcussion syndrome (PCS). There is growing support that concussion can disrupt network-based connectivity post-injury. To date, a significant knowledge gap remains regarding the sex-specific impact of concussion on resting state functional connectivity (rs-FC). The aims of this study were to (1) investigate the injury-based rs-FC differences across three large-scale neural networks and (2) explore the sex-specific impact of injury on network-based connectivity. MRI data was collected from a sample of 80 concussed participants who fulfilled the criteria for postconcussion syndrome and 31 control participants who did not have any history of concussion. Connectivity maps between network nodes and brain regions were used to assess connectivity using the Functional Connectivity (CONN) toolbox. Network based statistics showed that concussed participants were significantly different from healthy controls across both salience and fronto-parietal network nodes. More specifically, distinct subnetwork components were identified in the concussed sample, with hyperconnected frontal nodes and hypoconnected posterior nodes across both the salience and fronto-parietal networks, when compared to the healthy controls. Node-to-region analyses showed sex-specific differences across association cortices, however, driven by distinct networks. Sex-specific network-based alterations in rs-FC post concussion need to be examined to better understand the underlying mechanisms and associations to clinical outcomes.

scholarly journals Reproducing macaque lateral grasping and oculomotor networks using resting state functional connectivity and diffusion tractography

2020 ◽  
Vol 225 (8) ◽  
pp. 2533-2551 ◽  
Author(s):  
Henrietta Howells ◽  
Luciano Simone ◽  
Elena Borra ◽  
Luca Fornia ◽  
Gabriella Cerri ◽  
...  
Keyword(s):  
Motor Control ◽  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Ex Vivo ◽  
Lower Sensitivity ◽  
Connectivity Analysis ◽  
Resting State Functional Connectivity ◽  
Native Space ◽  
Functional Connectivity Analysis

Abstract Cortico-cortical networks involved in motor control have been well defined in the macaque using a range of invasive techniques. The advent of neuroimaging has enabled non-invasive study of these large-scale functionally specialized networks in the human brain; however, assessing its accuracy in reproducing genuine anatomy is more challenging. We set out to assess the similarities and differences between connections of macaque motor control networks defined using axonal tracing and those reproduced using structural and functional connectivity techniques. We processed a cohort of macaques scanned in vivo that were made available by the open access PRIME-DE resource, to evaluate connectivity using diffusion imaging tractography and resting state functional connectivity (rs-FC). Sectors of the lateral grasping and exploratory oculomotor networks were defined anatomically on structural images, and connections were reproduced using different structural and functional approaches (probabilistic and deterministic whole-brain and seed-based tractography; group template and native space functional connectivity analysis). The results showed that parieto-frontal connections were best reproduced using both structural and functional connectivity techniques. Tractography showed lower sensitivity but better specificity in reproducing connections identified by tracer data. Functional connectivity analysis performed in native space had higher sensitivity but lower specificity and was better at identifying connections between intrasulcal ROIs than group-level analysis. Connections of AIP were most consistently reproduced, although those connected with prefrontal sectors were not identified. We finally compared diffusion MR modelling with histology based on an injection in AIP and speculate on anatomical bases for the observed false negatives. Our results highlight the utility of precise ex vivo techniques to support the accuracy of neuroimaging in reproducing connections, which is relevant also for human studies.

Aberrant Functional and Effective Connectivity of the Frontostriatal Network in Unilateral Acute Tinnitus Patients with Hearing Loss

2021 ◽  
Author(s):  
Gang-Ping Zhou ◽  
Yu-Chen Chen ◽  
Wang-Wei Li ◽  
Heng-Le Wei ◽  
Yu-Sheng Yu ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Resting State ◽  
Large Scale ◽  
Early Stage ◽  
Effective Connectivity ◽  
Causality Analysis ◽  
Resting State Functional Connectivity ◽  
Midcingulate Cortex ◽  
Tinnitus Distress ◽  
Acute Tinnitus

Abstract Purpose: The present study combined resting-state functional connectivity (FC) and Granger causality analysis (GCA) to explore frontostriatal network dysfunction in unilateral acute tinnitus (AT) patients with hearing loss. Methods: The participants included 42 AT patients and 43 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging (fMRI) scans. Based on the seed regions in the frontostriatal network, FC and GCA were conducted between the AT patients and HC subjects. Correlation analyses were used to examine correlations among altered FC values, GCA values, and clinical features in AT patients. Results: Compared with HCs, AT patients showed a general reduction in FC between the seed regions in the frontostriatal network and nonauditory areas, including the frontal cortices, midcingulate cortex (MCC) , supramarginal gyrus (SMG), and postcentral gyrus (PoCG) . Using the GCA algorithm, we detected abnormal effective connectivity (EC) in the inferior occipital gyrus (IOG), MCC, Cerebelum_Crus1, and PoCG. Furthermore, correlations between disrupted FC/EC and clinical characteristics, especially tinnitus distress-related characteristics, were found in AT patients. Conclusions: Our work demonstrated abnormal FC and EC between the frontostriatal network and several nonauditory regions in AT patients with hearing loss, suggesting that multiple large-scale network dysfunctions and interactions are involved in the perception of tinnitus. These findings not only enhance the current understanding of the frontostriatal network in tinnitus but also serve as a reminder of the importance of focusing on tinnitus at an early stage.

scholarly journals Heritability analysis with repeat measurements and its application to resting-state functional connectivity

2017 ◽  
Vol 114 (21) ◽  
pp. 5521-5526 ◽  
Author(s):  
Tian Ge ◽  
Avram J. Holmes ◽  
Randy L. Buckner ◽  
Jordan W. Smoller ◽  
Mert R. Sabuncu
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Resting State Fmri ◽  
Transient Effects ◽  
Resting State Functional Connectivity ◽  
Linear Mixed Effects ◽  
Heritability Analysis ◽  
Test Retest Reliability ◽  
Different Levels

Heritability, defined as the proportion of phenotypic variation attributable to genetic variation, provides important information about the genetic basis of a trait. Existing heritability analysis methods do not discriminate between stable effects (e.g., due to the subject’s unique environment) and transient effects, such as measurement error. This can lead to misleading assessments, particularly when comparing the heritability of traits that exhibit different levels of reliability. Here, we present a linear mixed effects model to conduct heritability analyses that explicitly accounts for intrasubject fluctuations (e.g., due to measurement noise or biological transients) using repeat measurements. We apply the proposed strategy to the analysis of resting-state fMRI measurements—a prototypic data modality that exhibits variable levels of test–retest reliability across space. Our results reveal that the stable components of functional connectivity within and across well-established large-scale brain networks can be considerably heritable. Furthermore, we demonstrate that dissociating intra- and intersubject variation can reveal genetic influence on a phenotype that is not fully captured by conventional heritability analyses.

scholarly journals Rorschach Nomological Network and Resting-State Large Scale Brain Networks

2016 ◽  
Vol 37 (1) ◽  
pp. 74-92 ◽  
Author(s):  
Stefania Cristofanelli ◽  
Claudia Pignolo ◽  
Laura Ferro ◽  
Agata Ando’ ◽  
Alessandro Zennaro
Keyword(s):  
Research Design ◽  
Resting State ◽  
Personality Assessment ◽  
Large Scale ◽  
Resting State Functional Connectivity ◽  
Psychological Traits ◽  
New Research ◽  
Perceptual Styles ◽  
Rorschach Variables ◽  
Neuroimaging Techniques

Abstract. Despite advances in neuroscience, the field of personality assessment has not yet taken full advantage of the progress in neuroimaging techniques. Functional Magnetic Resonance Imaging (fMRI) is one of the most widely used neuroimaging techniques and allows the detection of brain processes and their anatomically detailed correspondences. In the last fifteen years, few studies have developed research designs using the Rorschach test in fMRI settings, analyzing the relationship between Rorschach variables and brain neural circuits. Although their findings were promising, some methodological issues related to fMRI research design have been outlined. Recently, personality neuroscience is emerging as a new field of research that attempts to deepen and refine neurobiological and psychological theories of personality using fMRI in resting state conditions. Recent studies report that resting state networks show a direct relationship with psychological traits. The aim of the present article is to propose a new research design that employs resting-state functional connectivity analyses to explore the brain’s functional architecture in relation to psychological constructs of Rorschach variables related to perceptual styles and personality traits.

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