Large-scale Cortical Network Properties Predict Future Sound-to-Word Learning Success

The human brain possesses a remarkable capacity to interpret and recall novel sounds as spoken language. These linguistic abilities arise from complex processing spanning a widely distributed cortical network and are characterized by marked individual variation. Recently, graph theoretical analysis has facilitated the exploration of how such aspects of large-scale brain functional organization may underlie cognitive performance. Brain functional networks are known to possess small-world topologies characterized by efficient global and local information transfer, but whether these properties relate to language learning abilities remains unknown. Here we applied graph theory to construct large-scale cortical functional networks from cerebral hemodynamic (fMRI) responses acquired during an auditory pitch discrimination task and found that such network properties were associated with participants' future success in learning words of an artificial spoken language. Successful learners possessed networks with reduced local efficiency but increased global efficiency relative to less successful learners and had a more cost-efficient network organization. Regionally, successful and less successful learners exhibited differences in these network properties spanning bilateral prefrontal, parietal, and right temporal cortex, overlapping a core network of auditory language areas. These results suggest that efficient cortical network organization is associated with sound-to-word learning abilities among healthy, younger adults.

Download Full-text

The landscape of molecular chaperones across human tissues reveals a layered architecture of core and variable chaperones

Nature Communications ◽

10.1038/s41467-021-22369-9 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Netta Shemesh ◽

Juman Jubran ◽

Shiran Dror ◽

Eyal Simonovsky ◽

Omer Basha ◽

...

Keyword(s):

Large Scale ◽

De Novo ◽

Functional Organization ◽

Functional Networks ◽

Aging Brain ◽

Human Tissues ◽

Human Organ ◽

Tissue Specific ◽

Layered Architecture ◽

Development And Aging

AbstractThe sensitivity of the protein-folding environment to chaperone disruption can be highly tissue-specific. Yet, the organization of the chaperone system across physiological human tissues has received little attention. Through computational analyses of large-scale tissue transcriptomes, we unveil that the chaperone system is composed of core elements that are uniformly expressed across tissues, and variable elements that are differentially expressed to fit with tissue-specific requirements. We demonstrate via a proteomic analysis that the muscle-specific signature is functional and conserved. Core chaperones are significantly more abundant across tissues and more important for cell survival than variable chaperones. Together with variable chaperones, they form tissue-specific functional networks. Analysis of human organ development and aging brain transcriptomes reveals that these functional networks are established in development and decline with age. In this work, we expand the known functional organization of de novo versus stress-inducible eukaryotic chaperones into a layered core-variable architecture in multi-cellular organisms.

Download Full-text

Establishing the functional relevancy of white matter connections in the visual system and beyond

Brain Structure and Function ◽

10.1007/s00429-021-02423-4 ◽

2021 ◽

Author(s):

Mareike Grotheer ◽

Emily Kubota ◽

Kalanit Grill-Spector

Keyword(s):

White Matter ◽

Visual System ◽

Large Scale ◽

Functional Organization ◽

Temporal Cortex ◽

Fine Grained ◽

Brain Functions ◽

Functional Relationships ◽

Functional Regions ◽

The Brain

AbstractFor over a century, researchers have examined the functional relevancy of white matter bundles. Consequently, many large-scale bundles spanning several centimeters have been associated in their entirety with specific brain functions, such as language or attention. However, these coarse structural–functional relationships are at odds with modern understanding of the fine-grained functional organization of human cortex, such as the mosaic of category-selective regions in ventral temporal cortex. Here, we review a multimodal approach that combines fMRI to define functional regions of interest within individual’s brains with dMRI tractography to identify the white matter bundles of the same individual. Combining these data allows to determine which subsets of streamlines within a white matter bundle connect to specific functional regions in each individual. That is, this approach identifies the functionally defined white matter sub-bundles of the brain. We argue that this approach not only enhances the accuracy of interpreting the functional relevancy of white matter bundles, but also enables segmentation of these large-scale bundles into meaningful functional units, which can then be linked to behavior with enhanced precision. Importantly, this approach has the potential for making new discoveries of the fine-grained functional relevancy of white matter connections in the visual system and the brain more broadly, akin to the flurry of research that has identified functional regions in cortex.

Download Full-text

Mapping the human brain's cortical-subcortical functional network organization

10.1101/206292 ◽

2017 ◽

Cited By ~ 1

Author(s):

Jie Lisa Ji ◽

Marjolein Spronk ◽

Kaustubh Kulkarni ◽

Grega Repovs ◽

Alan Anticevic ◽

...

Keyword(s):

Large Scale ◽

Detection Algorithm ◽

Brain Regions ◽

Brain Network ◽

Cognitive Networks ◽

Functional Networks ◽

Network Organization ◽

Whole Brain ◽

Recent Estimate ◽

Local Circuits

Understanding complex systems such as the human brain requires characterization of the system's architecture across multiple levels of organization - from neurons, to local circuits, to brain regions, and ultimately large-scale brain networks. Here we focus on characterizing the human brain's large-scale network organization, as it provides an overall framework for the organization of all other levels. We developed a highly principled approach to identify cortical network communities at the level of functional systems, calibrating our community detection algorithm using extremely well-established sensory and motor systems as guides. Building on previous network partitions, we replicated and expanded upon well-known and recently-identified networks, including several higher-order cognitive networks such as a left-lateralized language network. We expanded these cortical networks to subcortex, revealing 358 highly-organized subcortical parcels that take part in forming whole-brain functional networks. Notably, the identified subcortical parcels are similar in number to a recent estimate of the number of cortical parcels (360). This whole-brain network atlas - released as an open resource for the neuroscience community - places all brain structures across both cortex and subcortex into a single large-scale functional framework, with the potential to facilitate a variety of studies investigating large-scale functional networks in health and disease.

Download Full-text

Inferring the heritability of large-scale functional networks with a multivariate ACE modeling approach

10.1101/437335 ◽

2018 ◽

Author(s):

Fernanda L. Ribeiro ◽

Felipe R. C. dos Santos ◽

João R. Sato ◽

Walter H. L. Pinaya ◽

Claudinei E. Biazoli

Keyword(s):

Large Scale ◽

Genetic Factors ◽

Functional Organization ◽

Identification Accuracy ◽

Functional Networks ◽

Intersubject Variability ◽

Functional Connectome ◽

Modeling Approach ◽

Heritability Estimation ◽

Large Scale Networks

AbstractRecent evidence suggests that the functional connectome is stable at different time scales and unique. These characteristics posit the functional connectome not only as an individual marker but also as a powerful discriminatory measure characterized by the high intersubject variability. Among distinct sources of intersubject variability, the long-term sources include functional patterns that emerge from genetic factors. Here, we sought to investigate the contribution of genetic factors to the variability of functional networks by determining the heritability of the connectivity strength in a multivariate fashion. First, we reproduced and extended the connectome fingerprinting analysis to the identification of twin pairs. Then, we estimated the heritability of functional networks by a multivariate ACE modeling approach with bootstrapping. We found that a visual (0.41) and the medial frontal (0.35) functional networks were the most heritable, while the subcortical-cerebellum (28.6%) and the medial frontal (21.1%) networks were the most accurate on twin pair identification. Taken together, our findings suggest that twin identification accuracy does not necessarily relate to the heritability of a given functional network, indicating that heritability estimation and connectome fingerprinting are both required to study the influence of genetic factors on the functional organization of human brain at the level of large-scale networks.

Download Full-text

Brainwide functional networks associated with anatomically- and functionally-defined hippocampal subfields using ultrahigh-resolution fMRI

Scientific Reports ◽

10.1038/s41598-021-90364-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Wei-Tang Chang ◽

Stephanie K. Langella ◽

Yichuan Tang ◽

Sahar Ahmad ◽

Han Zhang ◽

...

Keyword(s):

Resting State ◽

Functional Organization ◽

A Priori ◽

Longitudinal Axis ◽

Functional Networks ◽

Resting State Functional Connectivity ◽

Underlying Assumption ◽

Isotropic Resolution ◽

Hippocampal Subfields ◽

Fine Grained

AbstractThe hippocampus is critical for learning and memory and may be separated into anatomically-defined hippocampal subfields (aHPSFs). Hippocampal functional networks, particularly during resting state, are generally analyzed using aHPSFs as seed regions, with the underlying assumption that the function within a subfield is homogeneous, yet heterogeneous between subfields. However, several prior studies have observed similar resting-state functional connectivity (FC) profiles between aHPSFs. Alternatively, data-driven approaches investigate hippocampal functional organization without a priori assumptions. However, insufficient spatial resolution may result in a number of caveats concerning the reliability of the results. Hence, we developed a functional Magnetic Resonance Imaging (fMRI) sequence on a 7 T MR scanner achieving 0.94 mm isotropic resolution with a TR of 2 s and brain-wide coverage to (1) investigate the functional organization within hippocampus at rest, and (2) compare the brain-wide FC associated with fine-grained aHPSFs and functionally-defined hippocampal subfields (fHPSFs). This study showed that fHPSFs were arranged along the longitudinal axis that were not comparable to the lamellar structures of aHPSFs. For brain-wide FC, the fHPSFs rather than aHPSFs revealed that a number of fHPSFs connected specifically with some of the functional networks. Different functional networks also showed preferential connections with different portions of hippocampal subfields.

Download Full-text

Neuroimaging Findings in Adolescents and Young Adults with Anorexia Nervosa: A Systematic Review

Children ◽

10.3390/children8020137 ◽

2021 ◽

Vol 8 (2) ◽

pp. 137

Author(s):

Kalliopi Kappou ◽

Myrto Ntougia ◽

Aikaterini Kourtesi ◽

Eleni Panagouli ◽

Elpis Vlachopapadopoulou ◽

...

Keyword(s):

Systematic Review ◽

Young Adults ◽

Anorexia Nervosa ◽

Large Scale ◽

Temporal Cortex ◽

Adolescents And Young Adults ◽

Pubmed Central ◽

Executive Control Network ◽

Young Females ◽

Weight Restoration

Background: Anorexia nervosa (AN) is a serious, multifactorial mental disorder affecting predominantly young females. This systematic review examines neuroimaging findings in adolescents and young adults up to 24 years old, in order to explore alterations associated with disease pathophysiology. Methods: Eligible studies on structural and functional brain neuroimaging were sought systematically in PubMed, CENTRAL and EMBASE databases up to 5 October 2020. Results: Thirty-three studies were included, investigating a total of 587 patients with a current diagnosis of AN and 663 healthy controls (HC). Global and regional grey matter (GM) volume reduction as well as white matter (WM) microstructure alterations were detected. The mainly affected regions were the prefrontal, parietal and temporal cortex, hippocampus, amygdala, insula, thalamus and cerebellum as well as various WM tracts such as corona radiata and superior longitudinal fasciculus (SLF). Regarding functional imaging, alterations were pointed out in large-scale brain networks, such as default mode network (DMN), executive control network (ECN) and salience network (SN). Most findings appear to reverse after weight restoration. Specific limitations of neuroimaging studies in still developing individuals are also discussed. Conclusions: Structural and functional alterations are present in the early course of the disease, most of them being partially or totally reversible. Nonetheless, neuroimaging findings have been open to many biological interpretations. Thus, more studies are needed to clarify their clinical significance.

Download Full-text

Altered interplay among large-scale brain functional networks underpins multi-domain anosognosia in early-AD

Journal of the Neurological Sciences ◽

10.1016/j.jns.2021.118315 ◽

2021 ◽

Vol 429 ◽

pp. 118315

Author(s):

Jose Manuel Valera Bermejo ◽

Matteo De Marco ◽

Annalena Venneri

Keyword(s):

Large Scale ◽

Functional Networks ◽

Brain Functional Networks

Download Full-text

Age of Acquisition Norms for a Large Set of Object Names and Their Relation to Adult Estimates and Other Variables

The Quarterly Journal of Experimental Psychology Section A ◽

10.1080/027249897392017 ◽

1997 ◽

Vol 50 (3) ◽

pp. 528-559 ◽

Cited By ~ 356

Author(s):

Catriona M. Morrison ◽

Tameron D. Chappell ◽

Andrew W. Ellis

Keyword(s):

Word Learning ◽

Processing Speed ◽

Large Scale ◽

Lexical Processing ◽

Objective Measure ◽

Age Of Acquisition ◽

Large Set ◽

Name Agreement ◽

Object Familiarity ◽

The Relationship

Studies of lexical processing have relied heavily on adult ratings of word learning age or age of acquisition, which have been shown to be strongly predictive of processing speed. This study reports a set of objective norms derived in a large-scale study of British children's naming of 297 pictured objects (including 232 from the Snodgrass & Vanderwart, 1980, set). In addition, data were obtained on measures of rated age of acquisition, rated frequency, imageability, object familiarity, picture-name agreement, and name agreement. We discuss the relationship between the objective measure and adult ratings of word learning age. Objective measures should be used when available, but where not, our data suggest that adult ratings provide a reliable and valid measure of real word learning age.

Download Full-text