Brain Connectivity

Long-term neurological damage as a result of head trauma while playing sports is a major concern for football athletes today. Repetitive concussions have been linked to many neurological disorders. Recently, it has been reported that repetitive sub-concussive events can be a significant source of accrued damage. Since football athletes can experience hundreds of sub-concussive hits during a single season, it is of utmost importance to understand their effect on brain health in the short- and long-term. In this study, resting state functional magnetic resonance imaging (rs-fMRI) was used to study changes in the Default Mode Network (DMN) after repetitive sub-concussive mTBI. Twenty-two high school American football athletes, clinically asymptomatic, were scanned using rs-fMRI for a single season. Baseline scans were acquired before the start of the season, and follow-up scans were obtained during and after the season to track the potential changes in the DMN as a result of experience...

Amygdala hemodynamic responses to positive stimuli are attenuated in major depressive disorder (MDD) and normalize with remission. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) training with the goal of upregulating amygdala activity during recall of happy autobiographical memories (AMs) has been suggested, and recently explored, as a novel therapeutic approach that resulted in improvement in self-reported mood in depressed subjects. In this study, we assessed the possibility of sustained brain changes as well as the neuromodulatory effects of rtfMRI-nf training of the amygdala during recall of positive AMs in MDD and matched healthy subjects. MDD and healthy subjects went through one visit of rtfMRI-nf training. Subjects were assigned to receive active neurofeedback from the left amygdale (LA) or from a control region putatively not modulated by AM recall or emotion regulation, that is, the left horizontal segment of the intraparietal sulcus. To assess l...

Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitati...

This study employed functional magnetic resonance imaging (fMRI)-based dynamic causal modeling (DCM) to study the effective (directional) neuronal connectivity underlying inhibitory behavioral control. fMRI data were acquired from 15 healthy subjects while they performed a Go/NoGo task with two levels of NoGo difficulty (Easy and Hard NoGo conditions) in distinguishing spatial patterns of lines. Based on the previous inhibitory control literature and the present fMRI activation results, 10 brain regions were postulated as nodes in the effective connectivity model. Due to the large number of potential interconnections among these nodes, the number of models for final analysis was reduced to a manageable level for the whole group by conducting DCM Network Discovery, which is a recently developed option within the Statistical Parametric Mapping software package. Given the optimum network model, the DCM Network Discovery analysis found that the locations of the driving input into the mo...

Decoding the meaning of others' actions, a crucial step for social cognition, involves different neu-ral mechanisms. While the " mirror " and " mentalizing " systems have been associated with, respectively, the processing of biological actions versus more abstract information, their respective contribution to intention understanding is debated. Processing social interactions seems to recruit both neural systems, with a different weight depending on cues emphasizing either shared action goals or shared mental states. We have previously shown that observing cooperative and affective social interactions elicits stronger activity in key nodes of, respectively, the mirror (left posterior superior temporal sulcus (pSTS), superior parietal cortex (SPL), and ventral/dorsal premotor cortex (vPMC/dPMC)) and mentalizing (ventromedial prefrontal cortex (vmPFC)) systems. To unveil their causal organization, we investigated the effective connectivity underlying the observation of human social interactions expressing increasing cooperativity (involving left pSTS, SPL, and vPMC) versus affectivity (vmPFC) via dynamic causal modeling in 36 healthy human subjects. We found strong evidence for a model including the pSTS and vPMC as input nodes for the observed interactions. The extrinsic connectivity of this model undergoes oppositely valenced modulations, with cooperativity promoting positive modulations of connectivity between pSTS and both SPL (forward) and vPMC (mainly backward), and affectivity promoting reciprocal positive modulations of connectivity between pSTS and vmPFC (mainly backward). Alongside fMRI data, such divergent effective connectivity suggests that different dimensions underlying the processing of social interactions recruit distinct, although strongly interconnected, neural pathways associated with, respectively, the bottom–up visuomotor processing of motor intentions, and the top–down attri-bution of affective/mental states.

To study effective connectivity among sources in a densely voxelated (high-dimensional) cortical surface, we develop the source-space factor VAR model. The first step in our procedure is to estimate cortical activity from multichannel elec-troencephalograms (EEG) using anatomically constrained brain imaging methods. Following parcellation of the cortical surface into disjoint regions of interest (ROIs), latent factors within each ROI are computed using principal component analysis. These factors are ROI-specific low-rank approximations (or representations) which allow for efficient estimation of connectivity in the high-dimensional cortical source space. The second step is to model effective connectivity between ROIs by fitting a VAR model jointly on all the latent processes. Measures of cortical con-nectivity, in particular partial directed coherence, are formulated using the VAR parameters. We illustrate the proposed model to investigate connectivity and interactions between cortical ROIs during rest.

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks.

Generating movement rhythms is known to involve a network of distributed brain regions associated with motor planning, control, execution, and perception of timing for the repertoire of motor actions. What brain areas are bound in the network and how the network activity is modulated by rhythmic complexity have not been completely explored. To contribute to answering these questions, we designed a study in which nine healthy participants performed simple to complex rhythmic finger movement tasks while undergoing simultaneous functional magnetic resonance imaging and electroencephalography (fMRI-EEG) recordings of their brain activity during the tasks and rest. From fMRI blood oxygenation-level-dependent (BOLD) measurements, we found that the complexity of rhythms was associated with brain activations in the primary motor cortex (PMC), supplementary motor area (SMA), and cerebellum (Cb), and with network interactions from these cortical regions to the cerebellum. The spectral analysi...

Diffusion tensor imaging (DTI) and a longitudinal language learning approach were applied to investigate the relationship between the achieved second language (L2) proficiency during L2 learning and the reorganization of structural connectivity between core language areas. Language proficiency tests and DTI scans were obtained from German students before and after they completed an intensive 6-week course of the Dutch language. In the initial learning stage, with increasing L2 proficiency, the hemispheric dominance of the BA6-temporal pathway (mainly along the arcuate fasciculus) shifted from the left to the right hemisphere. With further increased proficiency, however, lateralization dominance was again found in the left BA6-temporal pathway. This result is consistent with reports in the literature that imply a stronger involvement of the right hemisphere in L2-processing especially for less proficient L2-speakers. This is the first time that a L2-proficiency-dependent laterality s...

The perception of facial affect engages a distributed cortical network. We used functional magnetic resonance imaging and dynamic causal modeling to characterize effective connectivity during explicit (conscious) categorization of affective stimuli in the human brain. Specifically, we examined the modulation of connectivity from posterior regions of the face-processing network to the lateral ventral prefrontal cortex (VPFC) during affective categorization and we tested for a potential role of the amygdala (AMG) in mediating this modulation. We found that explicit processing of facial affect led to prominent modulation (increase) in the effective connectivity from the inferior occipital gyrus (IOG) to the VPFC, while there was less evidence for modulation of the afferent connections from fusiform gyrus and AMG to VPFC. More specifically, the forward connection from IOG to the VPFC exhibited a selective increase under anger (as opposed to fear or sadness). Furthermore, Bayesian model comparison suggested that the modulation of afferent connections to the VPFC was mediated directly by facial affect, as opposed to an indirect modulation mediated by the AMG. Our results thus suggest that affective information is conveyed to the VPFC along multiple parallel pathways and that AMG activity is not sufficient to account for the gating of information transfer to the VPFC during explicit emotional processing.

The ultimate goal of brain connectivity research is to delineate a comprehensive set of anatomical neuronal connections in the brain, a structure defined as the connectome, and to understand how the dynamical activity of these interconnected neurons supports functions. Likewise, connectomics (or hodology) is the scientific study of this structural and functional organization. Three different types of brain connectivity are distinguished within the literature: functional connectivity, structural connectivity and effective connectivity. Combining multi-modal connectomes remains a challenge: the integration is even made more difficult by the fact that it is not always possible to find a direct correlation between functional, structural and effective connectivity. It must be remembered, however, that any type of neuronal dynamics is, by definition, constrained by the underlying cellular anatomy of the system. Thus, unifying these different concepts is one of the central problems in current brain connectivity research.

Perturbation of the developmental refinement of the corticospinal (CS) pathway leads to motor disorders. While non-primate developmental refinement is well documented, in primates invasive investigations of the developing CS pathway have been confined to neonatal and postnatal stages when refinement is relatively modest. Here, we investigated the developmental changes in the distribution of CS projection neurons in cynomolgus monkey (Macaca fascicularis). Injections of retrograde tracer at cervical levels of the spinal cord at embryonic day (E) 95 and E105 show that: (i) areal distribution of back-labeled neurons is more extensive than in the neonate and dense labeling is found in prefrontal, limbic, temporal, and occipital cortex; (ii) distributions of contralateral and ipsilateral projecting CS neurons are comparable in terms of location and numbers of labeled neurons, in contrast to the adult where the contralateral projection is an order of magnitude higher than the ipsilateral projection. Findings from one largely restricted injection suggest a hitherto unsuspected early innervation of the gray matter. In the fetus there was in addition dense labeling in the central nucleus of the amygdala, the hypothalamus, the subthalamic nucleus, and the adjacent region of the zona incerta, subcortical structures with only minor projections in the adult control.

Context: At present, no reliable predictors exist to distinguish future responders from non-responders to treatment during the first episode of psychosis (FEP). Among potential neuroimaging predictors of treatment response, gyrification represents an important marker of the integrity of normal cortical development that may characterise, already at illness onset, a subgroup of patients with particularly poor outcome.
Objective: We test the hypothesis that patients with FEP who do not respond to 12 weeks of antipsychotic treatment have, already at illness onset, significant gyrification defects.
Design: Case-control study with 12-weeks longitudinal follow-up to determine treatment response.
Participants: 126 subjects, including 80 patients presenting with FEP and 46 healthy controls. Patients were scanned at the outset and received various antipsychotic medications in a naturalistic clinical setting. They were followed up for 12-weeks and classified as Responders or Non-Responders if they reached criteria for symptom remission, evaluated with the Psychiatric and Personal History Schedule (PPHS).
Setting: Secondary psychiatric services in an inner city area (South London, United Kingdom).
Outcome: Cortical gyrification was assessed using local gyrification index (LGI) in a vertex-wise fashion across the entire cortical surface with correction for multiple testing using permutation analysis. Differences in LGI were assessed between Responders, Non-Responders, and healthy controls. The effect of diagnosis (affective vs. non-affective psychosis) on the LGI was also investigated in Responders and Non-Responders.
Results: Patients with FEP showed a significant reduction in gyrification (hypogyria) across multiple brain regions, compared to healthy controls. Interestingly, Non-Responders showed prominent hypogyria at bilateral insular, left frontal and right temporal regions when compared to Responders (all clusters significant at p<0.05). These effects were present for both affective and non-affective psychoses.
Conclusions: Gyrification appears to be a useful predictor of antipsychotic treatment response. Early neurodevelopmental aberrations may predict unfavourable prognosis in psychosis, irrespective of the existing diagnostic boundaries.

Alcohol-dependence is associated with cognitive and biological alterations, and also with interpersonal impairments. Although overwhelming in clinical settings and involved in relapse, these social impairments have received little attention from researchers. Particularly, brain alterations related to social exclusion have not been explored in alcohol-dependence. Our primary purpose was to determine the neural correlates of social exclusion feelings in this population. In all, 44 participants (22 abstinent alcohol-dependent patients and 22 paired controls) played a virtual game (&#x27;cyberball&#x27;) during fMRI recording. They were first included by other players, then excluded, and finally re-included. Brain areas involved in social exclusion were identified and the functional connectivity between these areas was explored using psycho-physiological interactions (PPI). Results showed that while both groups presented dorsal anterior cingulate cortex (dACC) activations during social ...

Abstract:
Background: Schizophrenia is characterised by both electrophysiological abnormalities and consistent changes in the structure of cortical grey matter. But the relationship between these two observations is largely unknown. Structural changes reported in schizophrenia include reduced grey matter volume, thickness and surface area in several cortical regions, but most frequently in the insula and anterior cingulate cortex. These two regions together constitute an intrinsic brain circuit known as the ‘Salience Network’, which has a key role in stimulus processing.  During stimulus processing tasks, evoked activity is noted using electroencephalography (EEG). Phase resetting of ongoing oscillations contributes to this evoked activity.
Methods: In this study, we investigated the relationship between the cortical thickness in the Salience Network (measured using MRI) and the degree of phase resetting observed during an oddball task (measured using EEG) in 18 patients with schizophrenia and 20 healthy controls. 
Results: In patients with schizophrenia the reduced thickness in the Salience Network was associated with the inefficient phase resetting of theta oscillations.
Conclusions: Our findings suggest that the grey matter reduction seen in the Salience Network in patients with schizophrenia has substantial functional consequences. In particular, the structural defect of the insula that is seen in schizophrenia is likely to be associated with less efficient recruitment of brain circuits for processing information. This implies a possible mechanism by which disruptions in the intrinsic Salience Network can result in a general disturbance in salience detection seen in schizophrenia.

Altered neuroplasticity is increasingly invoked as a mechanism underpinning dysconnectivity in schizophrenia. We used Dynamic Causal Modelling to compare connectivity during the magnetic auditory Mismatch Negativity (MMN), an index of error prediction, between schizophrenia patients and controls. Patients showed reduced intrinsic connectivity within the primary auditory cortex suggestive of impaired local neuronal adaptation and disrupted forward and backward extrinsic connectivity throughout the MMN network indicative of reduced higher order input in disambiguating activity in lower network nodes. Our study provides the first empirical description of the dysplastic changes underpinning dysconnectivity between primary sensory and higher order cortical areas in schizophrenia.

Failing to engage in joint attention is a strong marker of impaired social cognition associated with autism spectrum disorder (ASD). The goal of this study was to localize the source of impaired joint attention in individuals with ASD by examining both behavioral and fMRI data collected during various tasks involving eye gaze, directional cuing, and face processing. The tasks were designed to engage three brain networks associated with social cognition [face processing, theory of mind (TOM), and action understanding]. The behavioral results indicate that even high-functioning individuals with ASD perform less accurately and more slowly than neurotypical (NT) controls when processing eyes, but not when processing a directional cue (an arrow) that did not involve eyes. Behavioral differences between the NT and ASD groups were consistent with differences in the effective connectivity of FACE, TOM, and ACTION networks. An independent multiple-sample greedy equivalence search was used to examine these social brain networks and found that whereas NTs produced stable patterns of response across tasks designed to engage a given brain network, ASD participants did not. Moreover, ASD participants recruited all three networks in a manner highly dissimilar to that of NTs. These results extend a growing literature that describes disruptions in general brain connectivity in individuals with autism by targeting specific networks hypothesized to underlie the social cognitive impairments observed in these individuals.

The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the &quot;default-mode&quot; network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However no clear stipulation on the underlying mechanisms of the de-synchronization has yet to be provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFO) of the DMN sub-networks in populations of young normals, older subjects, acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order groupICA with 117 eyes-closed rs-fMRI sessions from volunteers in those population groups, isolating 3 robust components of the DMN among other resting state networks. The posterior component of the DMN presented noticeable differences. Measures of ALFF and fALFF of the network component demonstrated a decrease in resting st...