scholarly journals Structural and effective brain connectivity underlying biological motion detection

2018 ◽  
Vol 115 (51) ◽  
pp. E12034-E12042 ◽  
Author(s):  
Arseny A. Sokolov ◽  
Peter Zeidman ◽  
Michael Erb ◽  
Philippe Ryvlin ◽  
Karl J. Friston ◽  
...  
Keyword(s):  
Biological Motion ◽  
Effective Connectivity ◽  
Inferior Frontal Gyrus ◽  
Functional Integration ◽  
Temporal Cortex ◽  
Causal Modeling ◽  
High Angular Resolution ◽  
Wide Range ◽  
Crus I ◽  
The Right

The perception of actions underwrites a wide range of socio-cognitive functions. Previous neuroimaging and lesion studies identified several components of the brain network for visual biological motion (BM) processing, but interactions among these components and their relationship to behavior remain little understood. Here, using a recently developed integrative analysis of structural and effective connectivity derived from high angular resolution diffusion imaging (HARDI) and functional magnetic resonance imaging (fMRI), we assess the cerebro-cerebellar network for processing of camouflaged point-light BM. Dynamic causal modeling (DCM) informed by probabilistic tractography indicates that the right superior temporal sulcus (STS) serves as an integrator within the temporal module. However, the STS does not appear to be a “gatekeeper” in the functional integration of the occipito-temporal and frontal regions: The fusiform gyrus (FFG) and middle temporal cortex (MTC) are also connected to the right inferior frontal gyrus (IFG) and insula, indicating multiple parallel pathways. BM-specific loops of effective connectivity are seen between the left lateral cerebellar lobule Crus I and right STS, as well as between the left Crus I and right insula. The prevalence of a structural pathway between the FFG and STS is associated with better BM detection. Moreover, a canonical variate analysis shows that the visual sensitivity to BM is best predicted by BM-specific effective connectivity from the FFG to STS and from the IFG, insula, and STS to the early visual cortex. Overall, the study characterizes the architecture of the cerebro-cerebellar network for BM processing and offers prospects for assessing the social brain.

Fronto-thalamic dysconnectivity and cognitive control in schizophrenia

2016 ◽  
Vol 33 (S1) ◽  
pp. S34-S34
Author(s):  
G. Wagner ◽  
F. De la Cruz ◽  
D. Güllmar ◽  
C.C. Schultz ◽  
K. Koch ◽  
...  
Keyword(s):  
Cognitive Control ◽  
Diffusion Tensor ◽  
Effective Connectivity ◽  
Causal Modeling ◽  
Anterior Cingulate ◽  
System Level ◽  
Healthy Controls ◽  
Bold Signal ◽  
Wide Range ◽  
The Right

IntroductionSeveral lines of evidence suggest that cognitive deficits represent a core feature of schizophrenia.ObjectivesThe concept of “cognitive dysmetria” has been introduced to characterize disintegration at the system level of frontal-thalamic-cerebellar circuitry which has been regarded as a key network for a wide range of neuropsychological symptoms in schizophrenia.AimsThe present multimodal study aimed at investigating effective and structural connectivity of the frontal-thalamic circuitry in schizophrenia.MethodsUnivariate fMRI data analysis and effective connectivity analysis using dynamic causal modeling (DCM) were combined to examine cognitive control processes in 40 patients with schizophrenia and 40 matched healthy controls. BOLD signal and parameters of effective connectivity were related to parameters of corresponding white matter integrity assessed with diffusion tensor imaging (DTI).ResultsIn the DTI analysis, significantly decreased fractional anisotropy (FA) was detected in patients in the right anterior limb of the internal capsule (ALIC), the right thalamus and the right corpus callosum. During Stroop task performance patients demonstrated significantly lower activation relative to healthy controls in a predominantly right lateralized frontal-thalamic-cerebellar network. An abnormal effective connectivity was observed in the right lateralized connections between thalamus, anterior cingulate and dorsolateral prefrontal cortex. FA in the right ALIC was significantly correlated with the fronto-thalamic BOLD signal, effective connectivity and cognitive performance in patients.ConclusionsPresent data provide evidence for the notion of a structural and functional defect in the prefrontal-thalamic-cerebellar circuitry, which seems to be the basis of the cognitive control deficits in schizophrenia.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Altered effective connectivity in migraine patients during emotional stimuli: a multi-frequency magnetoencephalography study

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Jing Ren ◽  
Qun Yao ◽  
Minjie Tian ◽  
Feng Li ◽  
Yueqiu Chen ◽  
...  
Keyword(s):  
Brain Activity ◽  
Effective Connectivity ◽  
Temporal Cortex ◽  
Primary Headache ◽  
Clustering Coefficient ◽  
Frequency Range ◽  
Emotional Stimuli ◽  
Emotional Modulation ◽  
Gamma Frequency ◽  
Wide Range

Abstract Background Migraine is a common and disabling primary headache, which is associated with a wide range of psychiatric comorbidities. However, the mechanisms of emotion processing in migraine are not fully understood yet. The present study aimed to investigate the neural network during neutral, positive, and negative emotional stimuli in the migraine patients. Methods A total of 24 migraine patients and 24 age- and sex-matching healthy controls were enrolled in this study. Neuromagnetic brain activity was recorded using a whole-head magnetoencephalography (MEG) system upon exposure to human facial expression stimuli. MEG data were analyzed in multi-frequency ranges from 1 to 100 Hz. Results The migraine patients exhibited a significant enhancement in the effective connectivity from the prefrontal lobe to the temporal cortex during the negative emotional stimuli in the gamma frequency (30–90 Hz). Graph theory analysis revealed that the migraine patients had an increased degree and clustering coefficient of connectivity in the delta frequency range (1–4 Hz) upon exposure to positive emotional stimuli and an increased degree of connectivity in the delta frequency range (1–4 Hz) upon exposure to negative emotional stimuli. Clinical correlation analysis showed that the history, attack frequency, duration, and neuropsychological scales of the migraine patients had a negative correlation with the network parameters in certain frequency ranges. Conclusions The results suggested that the individuals with migraine showed deviant effective connectivity in viewing the human facial expressions in multi-frequencies. The prefrontal-temporal pathway might be related to the altered negative emotional modulation in migraine. These findings suggested that migraine might be characterized by more universal altered cerebral processing of negative stimuli. Since the significant result in this study was frequency-specific, more independent replicative studies are needed to confirm these results, and to elucidate the neurocircuitry underlying the association between migraine and emotional conditions.

scholarly journals Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jake Gockley ◽  
Kelsey S. Montgomery ◽  
William L. Poehlman ◽  
Jesse C. Wiley ◽  
Yue Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Prefrontal Cortex ◽  
Association Study ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
European Ancestry ◽  
Common Genetic Variants ◽  
Wide Range

Abstract Background Alzheimer’s disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions. Methods A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene’s surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues. Results Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR < 5%: N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR < 0.05): APOC1, EED, CD2AP, CEACAM19, CLPTM1, MTCH2, TREM2, and KNOP1. Conclusions We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.

scholarly journals Fronto-thalamic structural and effective connectivity and delusions in schizophrenia: a combined DTI/DCM study

2020 ◽  
pp. 1-11
Author(s):  
Gábor Csukly ◽  
Ádám Szabó ◽  
Patrícia Polgár ◽  
Kinga Farkas ◽  
Gyula Gyebnár ◽  
...  
Keyword(s):  
Coupling Strength ◽  
Effective Connectivity ◽  
Structural Connectivity ◽  
Network Connectivity ◽  
Causal Modeling ◽  
Anterior Cingulate ◽  
Network Activity ◽  
Subcortical Structures ◽  
Left Thalamus ◽  
The Right

Abstract Background Schizophrenia (SZ) is a complex disorder characterized by a range of behavioral and cognitive symptoms as well as structural and functional alterations in multiple cortical and subcortical structures. SZ is associated with reduced functional network connectivity involving core regions such as the anterior cingulate cortex (ACC) and the thalamus. However, little is known whether effective coupling, the directed influence of one structure over the other, is altered during rest in the ACC–thalamus network. Methods We collected resting-state fMRI and diffusion-weighted MRI data from 18 patients and 20 healthy controls. We analyzed fronto-thalamic effective connectivity using dynamic causal modeling for cross-spectral densities in a network consisting of the ACC and the left and right medio-dorsal thalamic regions. We studied structural connectivity using fractional anisotropy (FA). Results We found decreased coupling strength from the right thalamus to the ACC and from the right thalamus to the left thalamus, as well as increased inhibitory intrinsic connectivity in the right thalamus in patients relative to controls. ACC-to-left thalamus coupling strength correlated with the Positive and Negative Syndrome Scale (PANSS) total positive syndrome score and with delusion score. Whole-brain structural analysis revealed several tracts with reduced FA in patients, with a maximum decrease in white matter tracts containing fronto-thalamic and cingulo-thalamic fibers. Conclusions We found altered effective and structural connectivity within the ACC–thalamus network in SZ. Our results indicate that ACC–thalamus network activity at rest is characterized by reduced thalamus-to-ACC coupling. We suggest that positive symptoms may arise as a consequence of compensatory measures to imbalanced fronto-thalamic coupling.

scholarly journals Regression dynamic causal modeling for resting-state fMRI

2020 ◽  
Author(s):  
Stefan Frässle ◽  
Samuel J. Harrison ◽  
Jakob Heinzle ◽  
Brett A. Clementz ◽  
Carol A. Tamminga ◽  
...  
Keyword(s):  
Resting State ◽  
Brain Connectivity ◽  
Effective Connectivity ◽  
Brain Networks ◽  
Resting State Fmri ◽  
Causal Modeling ◽  
Computationally Efficient ◽  
Dynamic Causal Modeling ◽  
Whole Brain ◽  
Wide Range

Abstract“Resting-state” functional magnetic resonance imaging (rs-fMRI) is widely used to study brain connectivity. So far, researchers have been restricted to measures of functional connectivity that are computationally efficient but undirected, or to effective connectivity estimates that are directed but limited to small networks.Here, we show that a method recently developed for task-fMRI – regression dynamic causal modeling (rDCM) – extends to rs-fMRI and offers both directional estimates and scalability to whole-brain networks. First, simulations demonstrate that rDCM faithfully recovers parameter values over a wide range of signal-to-noise ratios and repetition times. Second, we test construct validity of rDCM in relation to an established model of effective connectivity, spectral DCM. Using rs-fMRI data from nearly 200 healthy participants, rDCM produces biologically plausible results consistent with estimates by spectral DCM. Importantly, rDCM is computationally highly efficient, reconstructing whole-brain networks (>200 areas) within minutes on standard hardware. This opens promising new avenues for connectomics.

scholarly journals Barking up the right tree: Univariate and multivariate fMRI analyses of homonym comprehension

2019 ◽  
Author(s):  
Paul Hoffman ◽  
Andres Tamm
Keyword(s):  
Semantic Processing ◽  
Control Function ◽  
Semantic Representation ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Unrelated Word ◽  
Test Case ◽  
Neuroimaging Data ◽  
The Right

AbstractHomonyms are a critical test case for investigating how the brain resolves ambiguity in language and, more generally, how context influences semantic processing. Previous neuroimaging studies have associated processing of homonyms with greater engagement of regions involved in executive control of semantic processing. However, the precise role of these areas and the involvement of semantic representational regions in homonym comprehension remain elusive. We addressed this by combining univariate and multivariate fMRI analyses of homonym processing. We tested whether multi-voxel activation patterns could discriminate between presentations of the same homonym in different contexts (e.g., bark following tree vs. bark following dog). The ventral anterior temporal lobe, implicated in semantic representation but not previously in homonym comprehension, showed this meaning-specific coding, despite not showing increased mean activation for homonyms. Within inferior frontal gyrus (IFG), a key site for semantic control, there was a dissociation between pars orbitalis, which also showed meaning-specific coding, and pars triangularis, which discriminated more generally between semantically related and unrelated word pairs. IFG effects were goal-dependent, only occurring when the task required semantic decisions, in line with a top-down control function. Finally, posterior middle temporal cortex showed a hybrid pattern of responses, supporting the idea that it acts as an interface between semantic representations and the control system. The study provides new evidence for context-dependent coding in the semantic system and clarifies the role of control regions in processing ambiguity. It also highlights the importance of combining univariate and multivariate neuroimaging data to fully elucidate the role of a brain region in semantic cognition.

scholarly journals Developmental Increase in Top–Down and Bottom–Up Processing in a Phonological Task: An Effective Connectivity, fMRI Study

2009 ◽  
Vol 21 (6) ◽  
pp. 1135-1145 ◽  
Author(s):  
Tali Bitan ◽  
Jimmy Cheon ◽  
Dong Lu ◽  
Douglas D. Burman ◽  
James R. Booth
Keyword(s):  
Language Processing ◽  
Effective Connectivity ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Control Process ◽  
Brain Regions ◽  
Top Down ◽  
Bottom Up ◽  
Age Related ◽  
Task Irrelevant

We examined age-related changes in the interactions among brain regions in children performing rhyming judgments on visually presented words. The difficulty of the task was manipulated by including a conflict between task-relevant (phonological) information and task-irrelevant (orthographic) information. The conflicting conditions included pairs of words that rhyme despite having different spelling patterns (jazz–has), or words that do not rhyme despite having similar spelling patterns (pint–mint). These were contrasted with nonconflicting pairs that have similar orthography and phonology (dime–lime) or different orthography and phonology (press–list). Using fMRI, we examined effective connectivity among five left hemisphere regions of interest: fusiform gyrus (FG), inferior frontal gyrus (IFG), intraparietal sulcus (IPS), lateral temporal cortex (LTC), and medial frontal gyrus (MeFG). Age-related increases were observed in the influence of the IFG and FG on the LTC, but only in conflicting conditions. These results reflect a developmental increase in the convergence of bottom–up and top–down information on the LTC. In older children, top–down control process may selectively enhance the sensitivity of the LTC to bottom–up information from the FG. This may be evident especially in situations that require selective enhancement of task-relevant versus task-irrelevant information. Altogether these results provide a direct evidence for a developmental increase in top–down control processes in language processing. The developmental increase in bottom–up processing may be secondary to the enhancement of top–down processes.

scholarly journals Functional connectivity of the right inferior frontal gyrus and orbitofrontal cortex in depression

2020 ◽  
Vol 15 (1) ◽  
pp. 75-86 ◽  
Author(s):  
Edmund T Rolls ◽  
Wei Cheng ◽  
Jingnan Du ◽  
Dongtao Wei ◽  
Jiang Qiu ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Orbitofrontal Cortex ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Cingulate Cortex ◽  
Posterior Cingulate Cortex ◽  
Angular Gyrus ◽  
Parahippocampal Gyrus ◽  
The Right ◽  
And Behavior

Abstract The orbitofrontal cortex extends into the laterally adjacent inferior frontal gyrus. We analyzed how voxel-level functional connectivity of the inferior frontal gyrus and orbitofrontal cortex is related to depression in 282 people with major depressive disorder (125 were unmedicated) and 254 controls, using FDR correction P &lt; 0.05 for pairs of voxels. In the unmedicated group, higher functional connectivity was found of the right inferior frontal gyrus with voxels in the lateral and medial orbitofrontal cortex, cingulate cortex, temporal lobe, angular gyrus, precuneus, hippocampus and frontal gyri. In medicated patients, these functional connectivities were lower and toward those in controls. Functional connectivities between the lateral orbitofrontal cortex and the precuneus, posterior cingulate cortex, inferior frontal gyrus, ventromedial prefrontal cortex and the angular and middle frontal gyri were higher in unmedicated patients, and closer to controls in medicated patients. Medial orbitofrontal cortex voxels had lower functional connectivity with temporal cortex areas, the parahippocampal gyrus and fusiform gyrus, and medication did not result in these being closer to controls. These findings are consistent with the hypothesis that the orbitofrontal cortex is involved in depression, and can influence mood and behavior via the right inferior frontal gyrus, which projects to premotor cortical areas.

scholarly journals The Neural Bases of Drawing. A Meta-analysis and a Systematic Literature Review of Neurofunctional Studies in Healthy Individuals

2021 ◽  
Author(s):  
Simona Raimo ◽  
Gabriella Santangelo ◽  
Luigi Trojano
Keyword(s):  
Semantic Processing ◽  
Parietal Lobe ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Inferior Frontal Gyrus ◽  
Temporal Cortex ◽  
Extrastriate Cortex ◽  
Healthy Individuals ◽  
Inferior Parietal Lobe ◽  
Wide Range

AbstractDrawing is a multi-component process requiring a wide range of cognitive abilities. Several studies on patients with focal brain lesions and functional neuroimaging studies on healthy individuals demonstrated that drawing is associated with a wide brain network. However, the neural structures specifically related to drawing remain to be better comprehended. We conducted a systematic review complemented by a meta-analytic approach to identify the core neural underpinnings related to drawing in healthy individuals. In analysing the selected studies, we took into account the type of the control task employed (i.e. motor or non-motor) and the type of drawn stimulus (i.e. geometric, figurative, or nonsense). The results showed that a fronto-parietal network, particularly on the left side of the brain, was involved in drawing when compared with other motor activities. Drawing figurative images additionally activated the inferior frontal gyrus and the inferior temporal cortex, brain areas involved in selection of semantic features of objects and in visual semantic processing. Moreover, copying more than drawing from memory was associated with the activation of extrastriate cortex (BA 18, 19). The activation likelihood estimation coordinate-based meta-analysis revealed a core neural network specifically associated with drawing which included the premotor area (BA 6) and the inferior parietal lobe (BA 40) bilaterally, and the left precuneus (BA 7).These results showed that a fronto-parietal network is specifically involved in drawing and suggested that a crucial role is played by the (left) inferior parietal lobe, consistent with classical literature on constructional apraxia.

scholarly journals Effective Connectivity Analysis of Brain Activated Regions during Distracted Driving

2021 ◽  
Vol 11 (6) ◽  
pp. 690
Author(s):  
Mi-Hyun Choi ◽  
Jin-Ju Jung ◽  
Je-Hyeop Lee ◽  
Ye-Jin Kim ◽  
Kyu-Beom Kim ◽  
...  
Keyword(s):  
Left Hemisphere ◽  
Secondary Task ◽  
Right Hemisphere ◽  
Effective Connectivity ◽  
Movement Control ◽  
Driving Performance ◽  
Causal Modeling ◽  
Precentral Gyrus ◽  
Connectivity Analysis ◽  
The Right

This study aims to use functional magnetic resonance imaging (fMRI) to assess the effective connectivity between the regions of the brain activated when driving and performing a secondary task (addition task). The subjects used an MR-compatible driving simulator ㅊ to manipulate the driving wheel with both hands and control the pedals (accelerator and brake) with their right foot as if they were driving in an actual environment. Effective connectivity analysis was performed for three regions of the right and the left hemispheres with the highest z-scores, and six of the regions of the entire brain (right and left hemisphere) activated during driving by dynamic causal modeling (DCM). In the right hemisphere, a motor control pathway related to movement control for driving performance was discovered; in the left hemisphere, the pathways in the regions related to movement control for driving performance, starting with the region associated with the secondary task, were discovered. In the whole brain, connectivity was discovered in each of the right and left hemispheres. The motor network of declarative memory, which is the connectivity of the right thalamus, left lingual gyrus, and right precentral gyrus, was worth noting. These results seem meaningful, as they demonstrate the connectivity associated with the control of voluntary movement related to memory from human experience, although limited to driving tasks.

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