The Functional Language Network

2017 ◽  
Author(s):  
Angela D. Friederici ◽  
Noam Chomsky
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Oscillatory Activity ◽  
Neural Basis ◽  
Functional Neural Network ◽  
Ventral Pathway ◽  
Open Issue ◽  
Language Network

How information content is encoded and decoded in the sending and receiving brain areas is still an open issue. A possible though speculative view is that encoding and decoding requires similarity at the neuronal level in the encoding and decoding regions. This chapter discusses the functional neural network of language. It first describes the language network at the neurotransmitter level and then discusses the available data at the level of functional connectivity and oscillatory activity. Section 1 looks at the neural basis of information transfer, namely at the neurotransmitters which are crucially involved in the transmission of information from one neuron to the next. Section 2 uses functional connectivity analyses to provide information about how different brain regions work together. They allow us to make statements about which regions work together, and moreover, about the direction of the information flow between these. Section 3 models the language circuit as a a dynamic temporo-frontal network with initial input-driven information processed bottom-up from the auditory cortex to the frontal cortex along the ventral pathway, with semantic information reaching the anterior inferior frontal gyrus, and syntactic information reaching the posterior inferior frontal gyrus.

The Structural Language Network

2017 ◽  
Author(s):  
Angela D. Friederici ◽  
Noam Chomsky
Keyword(s):  
White Matter ◽  
Language Processing ◽  
Sentence Processing ◽  
Information Transfer ◽  
Right Hemisphere ◽  
Brain Regions ◽  
Neural Basis ◽  
Fiber Tracts ◽  
White Matter Fiber Tracts ◽  
The Right

An adequate description of the neural basis of language processing must consider the entire network both with respect to its structural white matter connections and the functional connectivities between the different brain regions as the information has to be sent between different language-related regions distributed across the temporal and frontal cortex. This chapter discusses the white matter fiber bundles that connect the language-relevant regions. The chapter is broken into three sections. In the first, we look at the white matter fiber tracts connecting the language-relevant regions in the frontal and temporal cortices; in the second, the ventral and dorsal pathways in the right hemisphere that connect temporal and frontal regions; and finally in the third, the two syntax-relevant and (at least) one semantic-relevant neuroanatomically-defined networks that sentence processing is based on. From this discussion, it becomes clear that online language processing requires information transfer via the long-range white matter fiber pathways that connect the language-relevant brain regions within each hemisphere and between hemispheres.

scholarly journals Routing information flow by separate neural synchrony frequencies allows for “functionally labeled lines” in higher primate cortex

2019 ◽  
Vol 116 (25) ◽  
pp. 12506-12515 ◽  
Author(s):  
Mohammad Bagher Khamechian ◽  
Vladislav Kozyrev ◽  
Stefan Treue ◽  
Moein Esghaei ◽  
Mohammad Reza Daliri
Keyword(s):  
Information Flow ◽  
Information Transfer ◽  
Sensory Information ◽  
Spike Timing ◽  
Oscillatory Activity ◽  
Attention Task ◽  
Cortical Areas ◽  
High Gamma ◽  
Ventral Pathway ◽  
Visual Cortical

Efficient transfer of sensory information to higher (motor or associative) areas in primate visual cortical areas is crucial for transforming sensory input into behavioral actions. Dynamically increasing the level of coordination between single neurons has been suggested as an important contributor to this efficiency. We propose that differences between the functional coordination in different visual pathways might be used to unambiguously identify the source of input to the higher areas, ensuring a proper routing of the information flow. Here we determined the level of coordination between neurons in area MT in macaque visual cortex in a visual attention task via the strength of synchronization between the neurons’ spike timing relative to the phase of oscillatory activities in local field potentials. In contrast to reports on the ventral visual pathway, we observed the synchrony of spikes only in the range of high gamma (180 to 220 Hz), rather than gamma (40 to 70 Hz) (as reported previously) to predict the animal’s reaction speed. This supports a mechanistic role of the phase of high-gamma oscillatory activity in dynamically modulating the efficiency of neuronal information transfer. In addition, for inputs to higher cortical areas converging from the dorsal and ventral pathway, the distinct frequency bands of these inputs can be leveraged to preserve the identity of the input source. In this way source-specific oscillatory activity in primate cortex can serve to establish and maintain “functionally labeled lines” for dynamically adjusting cortical information transfer and multiplexing converging sensory signals.

scholarly journals Functional connectivity predictors of acute depression treatment outcome

2019 ◽  
Vol 31 (12) ◽  
pp. 1831-1835 ◽  
Author(s):  
David C. Steffens ◽  
Lihong Wang ◽  
Godfrey D. Pearlson
Keyword(s):  
Functional Connectivity ◽  
Rating Scale ◽  
Inferior Frontal Gyrus ◽  
Late Life ◽  
Multivariate Regression Analysis ◽  
Brain Regions ◽  
Frontal Eye Field ◽  
Late Life Depression ◽  
Madrs Score ◽  
Sensorimotor Network

ABSTRACTFew studies have examined functional connectivity (FC) patterns using functional magnetic resonance imaging (fMRI) to predict outcomes in late-life depression. We hypothesized that FC within and between frontal and limbic regions would be associated with 12-week depression outcome in older depressed adults. Seventy-one subjects with major depression were enrolled in the study. A study geriatric psychiatrist performed a clinical interview and completed a Montgomery-Åsberg Depression Rating Scale (MADRS). All study participants were free of medication at baseline and had a brain fMRI scan. Using a regions of interest (ROI) atlas (including 164 ROIs), we conducted ROI-to-ROI resting-state FC analyses for each participant. In terms of treatment participants were offered sertraline initially, although in this naturalistic study, other medications were also prescribed. Subjects were evaluated every 2 weeks up to 12 weeks by the study psychiatrist, who followed a flexible, clinically based medication dosing schedule. Multivariate regression analysis was used to examine correlation between change of MADRS score over 12 weeks and baseline FC between brain regions, controlling for age, gender, mean head motion, and baseline MADRS. We found greater FC between the left inferior frontal gyrus pars triangularis and the left frontal eye field and FC of these two regions with a number of brain regions related to reward, salience, and sensorimortor function were correlated with change in MADRS score over 12 weeks. Our results highlight the important role of between inner speech-reward, attention-salience, and attention-sensorimotor network synchronization in predicting acute treatment response in late-life depression.

scholarly journals Altered Intra- and Interregional Synchronization in Resting-State Cerebral Networks Associated with Chronic Tinnitus

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yu-Chen Chen ◽  
Jian Zhang ◽  
Xiao-Wei Li ◽  
Wenqing Xia ◽  
Xu Feng ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Brain Activity ◽  
Inferior Frontal Gyrus ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Chronic Tinnitus ◽  
Healthy Controls ◽  
Tinnitus Distress ◽  
The Right

Objective. Subjective tinnitus is hypothesized to arise from aberrant neural activity; however, its neural bases are poorly understood. To identify aberrant neural networks involved in chronic tinnitus, we compared the resting-state functional magnetic resonance imaging (fMRI) patterns of tinnitus patients and healthy controls.Materials and Methods. Resting-state fMRI measurements were obtained from a group of chronic tinnitus patients (n=29) with normal hearing and well-matched healthy controls (n=30). Regional homogeneity (ReHo) analysis and functional connectivity analysis were used to identify abnormal brain activity; these abnormalities were compared to tinnitus distress.Results. Relative to healthy controls, tinnitus patients had significant greater ReHo values in several brain regions including the bilateral anterior insula (AI), left inferior frontal gyrus, and right supramarginal gyrus. Furthermore, the left AI showed enhanced functional connectivity with the left middle frontal gyrus (MFG), while the right AI had enhanced functional connectivity with the right MFG; these measures were positively correlated with Tinnitus Handicap Questionnaires (r=0.459,P=0.012andr=0.479,P=0.009, resp.).Conclusions. Chronic tinnitus patients showed abnormal intra- and interregional synchronization in several resting-state cerebral networks; these abnormalities were correlated with clinical tinnitus distress. These results suggest that tinnitus distress is exacerbated by attention networks that focus on internally generated phantom sounds.

scholarly journals Linear Input as a Fundamental Motif of Brain Connectivity Organization

2019 ◽  
Author(s):  
Jonathan F. O’Rawe ◽  
Hoi-Chung Leung
Keyword(s):  
Functional Connectivity ◽  
Information Transfer ◽  
Brain Connectivity ◽  
Brain Regions ◽  
Fundamental Aspect ◽  
Biased Sampling ◽  
Whole Brain ◽  
3 Dimensional ◽  
Face Area ◽  
Learning Techniques

AbstractDescribing the pattern of region-to-region functional connectivity is an important step towards understanding information transfer and transformation between brain regions. Although fMRI data are limited in spatial resolution, recent advances in technology afford more precise mapping. Here, we extended previous methods, connective field mapping, to 3 dimensions to provide a more concise estimate of the organization and potential information transformation from one region to another. We first replicated previous work with the 3 dimensional model by showing that the topology of functional connectivity between early visual regions maintained along their eccentricity axis or the anterior-posterior dimension. We then examined higher order visual regions (e,g, fusiform face area) and showed that their pattern of connectivity, the convergence and biased sampling, seem to contribute to some of their core receptive field properties. We further demonstrated that linearity of input is a fundamental aspect of functional connectivity of the whole brain, with higher linearity between regions within a network than across networks; that is, high connective linearity was evident between early visual areas, and between prefrontal areas, but less evident between them. By decomposing the whole brain linearity matrix with manifold learning techniques, we found that the principle mode of the linearity maps onto decompositions in both functional connectivity and genetic expression reported in previous studies. The current work provides evidence supporting that linearity of input is likely a fundamental motif of functional connectivity between regions for information processing across the brain, with high linearity preserving the integrity of information from one region to another within a network.

scholarly journals Heterogeneity of EEG resting-state brain networks in absolute pitch

2020 ◽  
Author(s):  
Marielle Greber ◽  
Carina Klein ◽  
Simon Leipold ◽  
Silvano Sele ◽  
Lutz Jäncke
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Resting State ◽  
Large Scale ◽  
Absolute Pitch ◽  
Brain Regions ◽  
Brain Network ◽  
Higher Order ◽  
Neural Basis ◽  
Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

Task-positive Functional Connectivity of the Default Mode Network Transcends Task Domain

2015 ◽  
Vol 27 (12) ◽  
pp. 2369-2381 ◽  
Author(s):  
Amanda Elton ◽  
Wei Gao
Keyword(s):  
Functional Connectivity ◽  
Task Performance ◽  
Default Mode Network ◽  
Inferior Frontal Gyrus ◽  
Brain Regions ◽  
Positive Functional ◽  
Default Mode ◽  
Goal Directed Behavior ◽  
Increased Activity

The default mode network (DMN) was first recognized as a set of brain regions demonstrating consistently greater activity during rest than during a multitude of tasks. Originally, this network was believed to interfere with goal-directed behavior based on its decreased activity during many such tasks. More recently, however, the role of the DMN during goal-directed behavior was established for internally oriented tasks, in which the DMN demonstrated increased activity. However, the well-documented hub position and information-bridging potential of midline DMN regions indicate that there is more to uncover regarding its functional contributions to goal-directed tasks, which may be based on its functional interactions rather than its level of activation. An investigation of task-related changes in DMN functional connectivity during a series of both internal and external tasks would provide the requisite investigation for examining the role of the DMN during goal-directed task performance. In this study, 20 participants underwent fMRI while performing six tasks spanning diverse internal and external domains in addition to a resting-state scan. We hypothesized that the DMN would demonstrate “task-positive” (i.e., positively contributing to task performance) changes in functional connectivity relative to rest regardless of the direction of task-related changes in activity. Indeed, our results demonstrate significant increases in DMN connectivity with task-promoting regions (e.g., anterior insula, inferior frontal gyrus, middle frontal gyrus) across all six tasks. Furthermore, canonical correlation analyses indicated that the observed task-related connectivity changes were significantly associated with individual differences in task performance. Our results indicate that the DMN may not only support a “default” mode but may play a greater role in both internal and external tasks through flexible coupling with task-relevant brain regions.

scholarly journals Parietal and hippocampal hyper-connectivity is associated with low math achievement in adolescence

2021 ◽  
Author(s):  
Roberto A. Abreu-Mendoza ◽  
Melanie Pincus ◽  
Yaira Chamorro ◽  
Dietsje Jolles ◽  
Esmeralda Matute ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Math Achievement ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Math Performance ◽  
Resting State Functional Connectivity ◽  
Neural Basis ◽  
Math Ability ◽  
Control Seed

Mathematical cognition requires coordinated activity across multiple brain regions, leading to the emergence of resting-state functional connectivity as a method for studying the neural basis of differences in mathematical achievement. Hyper-connectivity of the intraparietal sulcus (IPS), a key locus of mathematical and numerical processing, has been associated with poor mathematical skills in childhood, whereas greater connectivity has been related to better performance in adulthood. No studies to date have considered its role in adolescence. Further, hippocampal connectivity can predict mathematical learning, yet no studies have considered its contributions to contemporaneous measures of math achievement. Here, we used seed-based resting-state fMRI analyses to examine IPS and hippocampal intrinsic functional connectivity relations to math achievement in a group of 31 adolescents (mean age=16.42 years, range 15-17), whose math performance spanned the 1% to 99% percentile. After controlling for IQ, IPS connectivity was negatively related to math achievement, akin to findings in children. However, the specific temporooccipital regions, were more akin to the posterior loci implicated in adults. Hippocampal connectivity with frontal regions was also negatively correlated with concurrent math measures, which contrasts with results from learning studies. Finally, hyper-connectivity was not a global feature of low math performance, as connectivity of Heschl’s gyrus, a control seed not involved in math cognition, was not modulated by math performance. Together, our results point to adolescence as a transitional stage in which patterns found in childhood and adulthood can be observed; most notably, hyper-connectivity continues to be related to low math ability in this period.

scholarly journals Maladaptive Self-Focused Attention and Default Mode Network Connectivity: A Transdiagnostic Investigation Across Social Anxiety and Body Dysmorphic Disorders

2021 ◽  
Author(s):  
Angela Fang ◽  
Bengi Baran ◽  
Clare C Beatty ◽  
Jennifer Mosley ◽  
Jamie D Feusner ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Social Anxiety ◽  
Default Mode Network ◽  
Brain Regions ◽  
Posterior Cingulate Cortex ◽  
Focused Attention ◽  
Neural Basis ◽  
Default Mode ◽  
Body Dysmorphic Disorders ◽  
Primary Body

Abstract Maladaptive self-focused attention (SFA) is a bias toward internal thoughts, feelings, and physical states. Despite its role as a core maintaining factor of symptoms in cognitive theories of social anxiety and body dysmorphic disorders, studies have not examined its neural basis. In this study, we hypothesized that maladaptive SFA would be associated with hyperconnectivity in the default mode network (DMN) in self-focused patients with these disorders. Thirty patients with primary social anxiety disorder or primary body dysmorphic disorder, and 28 healthy individuals were eligible and scanned. Eligibility was determined by scoring greater than 1SD or below 1SD of the Public Self-Consciousness Scale normative mean, respectively, for each group. Seed-to-voxel functional connectivity was computed using a DMN posterior cingulate cortex (PCC) seed. There was no evidence of increased DMN functional connectivity in patients compared to controls. Patients (regardless of diagnosis) showed reduced functional connectivity of the PCC with several brain regions, including the bilateral superior parietal lobule (SPL), compared to controls, which was inversely correlated with maladaptive SFA but not associated with social anxiety, body dysmorphic, or depression severity, or rumination. Abnormal PCC-SPL connectivity may represent a transdiagnostic neural marker of SFA that reflects difficulty shifting between internal versus external attention.

scholarly journals Network Dynamics Theory of Human Intelligence

2016 ◽  
Author(s):  
Aki Nikolaidis ◽  
Aron K. Barbey
Keyword(s):  
Functional Connectivity ◽  
Scientific Discovery ◽  
Brain Networks ◽  
Network Dynamics ◽  
Brain Regions ◽  
Biological Characteristics ◽  
Human Intelligence ◽  
Neural Basis ◽  
Developmental Neuroscience ◽  
Insight Into

AbstractScientific discovery and insight into the biological foundations of human intelligence have advanced considerably with progress in neuroimaging. Neuroimaging methods allow for not only an exploration of what biological characteristics underlie intelligence and creativity, but also a detailed assessment of how these biological characteristics emerge through child and adolescent development. In the past 10 years, functional connectivity, a metric of coherence in activation across brain regions, has been used extensively to probe cognitive function; however more recently neuroscientists have begun to investigate the dynamics of these functional connectivity patterns, revealing important insight into these networks as a result. In the present article, we expand current theories on the neural basis of human intelligence by developing a framework that integrates both how short-term dynamic fluctuations in brain networks and long-term development of brain networks over time contribute to intelligence and creativity. Applying this framework, we propose testable hypotheses regarding the neural and developmental correlates of intelligence. We review important topics in both network neuroscience and developmental neuroscience, and we consolidate these insights into a Network Dynamics Theory of human intelligence.

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