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Local and global functional connectivity of the human medial temporal lobe including the amygdala

Dynamic causal modeling (DCM) is a method for analyzing functional magnetic resonance imaging (fMRI) and other functional neuroimaging data that provides information about directionality of connectivity between brain regions. A review of the neuropsychiatric fMRI DCM literature suggests that there may be a historical trend to under-report self-connectivity (within brain regions) compared to between brain region connectivity findings. These findings are an integral part of the neurologic model represented by DCM and serve an important neurobiological function in regulating excitatory and inhibitory activity between regions. We reviewed the literature on the topic as well as the past 13 years of available neuropsychiatric DCM literature to find an increasing (but still, perhaps, and inadequate) trend in reporting these results. The focus of this review is fMRI as the majority of published DCM studies utilized fMRI and the interpretation of the self-connectivity findings may vary across imaging methodologies. About 25% of articles published between 2007 and 2019 made any mention of self-connectivity findings. We recommend increased attention toward the inclusion and interpretation of self-connectivity findings in DCM analyses in the neuropsychiatric literature, particularly in forthcoming effective connectivity studies of substance use disorders.

Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development.

Recent work with noninvasive human brain imaging has started to investigate the effects of 3,4-methylenedioxymethamphetamine (MDMA) on large-scale patterns of brain activity. MDMA, a potent monoamine-releaser with particularly pronounced serotonin- releasing properties, has unique subjective effects that include: marked positive mood, pleasant/unusual bodily sensations and pro-social, empathic feelings. However, the neurobiological basis for these effects is not properly understood, and the present analysis sought to address this knowledge gap. To do this, we administered MDMA-HCl (100 mg p.o.) and, separately, placebo (ascorbic acid) in a randomized, double-blind, repeated-measures design with twenty-five healthy volunteers undergoing fMRI scanning. We then employed a measure of global resting-state functional brain connectivity and follow-up seed-to-voxel analysis to the fMRI data we acquired. Results revealed decreased right insula/salience network functional connectivity under MDMA. Furthermore, these decreases in right insula/salience network connectivity correlated with baseline trait anxiety and acute experiences of altered bodily sensations under MDMA. The present findings highlight insular disintegration (ie, compromised salience network membership) as a neurobiological signature of the MDMA experience, and relate this brain effect to trait anxiety and acutely altered bodily sensations–both of which are known to be associated with insular functioning.

The ability to quantify synaptic function at the level of cortical microcircuits from non-invasive data would be enormously useful in the study of neuronal processing in humans and the pathophysiology that attends many neuropsychiatric disorders. Here, we provide proof of principle that one can estimate inter-and intra-laminar interactions among specific neuronal populations using induced gamma responses in the visual cortex of human subjects – using dynamic causal modelling based upon the canonical microcircuit (CMC; a simplistic model of a cortical column). Using variability in induced (spectral) responses over a large cohort of normal subjects, we find that the predominant determinants of gamma responses rest on recurrent and intrinsic connections between superficial pyramidal cells and inhibitory interneurons. Furthermore, variations in beta responses were mediated by inter-subject differences in the intrinsic connections between deep pyramidal cells and inhibitory interneurons. Interestingly, we also show that increasing the self-inhibition of superficial pyramidal cells suppresses the amplitude of gamma activity, while increasing its peak frequency. This systematic and nonlinear relationship was only disclosed by modelling the causes of induced responses. Crucially, we were able to validate this form of neurophysiological phenotyping by showing a selective effect of the GABA re-uptake inhibitor tiagabine on the rate constants of inhibitory interneurons. Remarkably, we were able to recover the pharmacodynamics of this effect over the course of several hours on a per subject basis. These findings speak to the possibility of measuring population specific synaptic function – and its response to pharmacological intervention – to provide subject-specific biomarkers of mesoscopic neuronal processes using non-invasive data. Finally, our results demonstrate that, using the CMC as a proxy, the synaptic mechanisms that underlie the gain control of neuronal message passing within and between different levels of cortical hierarchies may now be amenable to quantitative study using non-invasive (MEG) procedures.

Few long-term studies report late outcomes after severe traumatic brain injury. New rehabilitation techniques are needed for this heterogenous patient group. We present a dance intervention six and half years after an extreme severe TBI including excessive diffuse axonal injury, which disconnects the brain networks. Given the fact, that efficient brain function depends on the integrated operation of large-scale brain networks like default mode network (DMN), we created an intervention with multisensory and multimodal approach and goal-directed behavior. The intervention lasted four months including weekly one-hour dance lessons with the help of a physiotherapist and dance teacher. The measures included functional independence measure (FIM), repeated electroencephalogram (EEG) analysis of three subnets of DMN and clinical evaluations and observations. The results showed clear improvement after the intervention, and FIM stayed in elevated level during several years after the intervention. We present suggestion for further studies using larger patient groups.

The cortical distribution of amyloid-β plaques in Alzheimer’s disease strikingly resembles frontal-parietal intrinsic functional connectivity networks. Using a novel method to trace the distribution of amyloid-β plaques within single patients, Myers et al. reveal a marked negative effect on intrinsic connectivity in several networks that have not typically been investigated., There is striking overlap between the spatial distribution of amyloid-β pathology in patients with Alzheimer’s disease and the spatial distribution of high intrinsic functional connectivity in healthy persons. This overlap suggests a mechanistic link between amyloid-β and intrinsic connectivity, and indeed there is evidence in patients for the detrimental effects of amyloid-β plaque accumulation on intrinsic connectivity in areas of high connectivity in heteromodal hubs, and particularly in the default mode network. However, the observed spatial extent of amyloid-β exceeds these tightly circumscribed areas, suggesting that previous studies may have underestimated the negative impact of amyloid-β on intrinsic connectivity. We hypothesized that the known positive baseline correlation between patterns of amyloid-β and intrinsic connectivity may mask the larger extent of the negative effects of amyloid-β on connectivity. Crucially, a test of this hypothesis requires the within-patient comparison of intrinsic connectivity and amyloid-β distributions. Here we compared spatial patterns of amyloid-β-plaques (measured by Pittsburgh compound B positron emission tomography) and intrinsic functional connectivity (measured by resting-state functional magnetic resonance imaging) in patients with prodromal Alzheimer’s disease via spatial correlations in intrinsic networks covering fronto-parietal heteromodal cortices. At the global network level, we found that amyloid-β and intrinsic connectivity patterns were positively correlated in the default mode and several fronto-parietal attention networks, confirming that amyloid-β aggregates in areas of high intrinsic connectivity on a within-network basis. Further, we saw an internetwork gradient of the magnitude of correlation that depended on network plaque-load. After accounting for this globally positive correlation, local amyloid-β-plaque concentration in regions of high connectivity co-varied negatively with intrinsic connectivity, indicating that amyloid-β pathology adversely reduces connectivity anywhere in an affected network as a function of local amyloid-β-plaque concentration. The local negative association between amyloid-β and intrinsic connectivity was much more pronounced than conventional group comparisons of intrinsic connectivity would suggest. Our findings indicate that the negative impact of amyloid-β on intrinsic connectivity in heteromodal networks is underestimated by conventional analyses. Moreover, our results provide first within-patient evidence for correspondent patterns of amyloid-β and intrinsic connectivity, with the distribution of amyloid-β pathology following functional connectivity gradients within and across intrinsic networks.

While the literature on aberrant long-distance connectivity in autism spectrum disorder (ASD) has grown fast over the past decade, little is known about local connectivity. We used regional homogeneity and local density approaches at different spatial scales to examine local connectivity in 29 children and adolescents with ASD and 29 matched typically developing participants, using resting state functional magnetic resonance imaging data. Across a total of 12 analysis pipelines, the gross pattern of between-group findings was overall stable, with local overconnectivity in the ASD group in occipital and posterior temporal regions and underconnectivity in middle/posterior cingulate, and medial prefrontal regions. This general pattern was confirmed in secondary analyses for low-motion subsamples (n = 20 per group), in which time series segments with >0.25 mm head motion were censored, as well as in an analysis including global signal regression. Local overconnectivity in visual regions appears consistent with preference for local over global visual processing previously reported in ASD, whereas cingulate and medial frontal underconnectivity may relate to aberrant function within the default mode network.

Our study provides a new and comprehensive look at how migraine affects brain structure, how these changes in structure are related to functional brain networks, and how coping and disease severity influence both structure and functional networks. Specifically, we demonstrate concomitant functional and structural brain changes related to pain catastrophizing and disease severity in migraine patients., Cover Figure Migraine patients (Pts) show widespread structural and functional brain changes that are associated with symptoms and increased pain catastrophizing A, Migraine patients showed (i) increased gray matter volume (GMV) in the left (L) hippocampus and (ii) decreased cortical thickness in the L anterior midcingulate cortex (aMCC) compared to healthy control subjects. B, Pain catastrophizing correlated with GMV reductions in the (i) L primary somatosensory cortex (S1) and (ii) L medial prefrontal cortex (mPFC), and cortical thinning in the (iii) L dorsolateral prefrontal cortex (DLPFC) and middle temporal gyrus (MTG) in migraine patients. C, GMV reductions correlated with (i) disease duration (ii), attack frequency, and (iii) migraine pain intensity in patients. D, Whole-brain overlay maps for migraine patients and healthy controls for the (i) L PCC, (ii) L aINS, and (iii) aMCC seed regions rendered onto inflated brains. Red represents resting-state functional connectivity for healthy controls and green represents the same maps in migraine patients. Yellow represents areas showing overlap in functional connectivity in controls and migraineurs. Images are thresholded at T = 4.5 (cluster extent = 25) for visualization purposes. The schematic illustrates the relationship between disease severity measures and pain catastrophizing and disruptions in functional connectivity between the default mode network (DMN), central executive network (CEN), and salience network (SN) in migraine patients. In patients, pain catastrophizing correlated with increased coupling between DMN and CEN nodes (PCC-DLPFC), whereas disease duration and migraine pain intensity correlated with SN-DMN network decoupling (aINS/aMCC-mPFC), and increased SN-CEN (aMCC-aINS) network coupling, respectively. To investigate the neuroanatomical and functional brain changes in migraine patients relative to healthy controls, we used a combined analytical approach including voxel- and surface-based morphometry along with resting-state functional connectivity to determine whether areas showing structural alterations in patients also showed abnormal functional connectivity. Additionally, we wanted to assess whether these structural and functional changes were associated with group differences in pain catastrophizing and migraine-related disease variables in patients. We acquired T1-weighted anatomical and functional magnetic resonance imaging scans during rest in human subjects with a diagnosis of migraine and healthy controls. Structural analyses revealed greater left hippocampal gray matter volume and reduced cortical thickness in the left anterior midcingulate in patients compared with controls. We also observed negative associations between pain catastrophizing and migraine disease variables and gray matter in areas implicated in processing the sensory, affective, and cognitive aspects of pain in patients. Functional connectivity analyses showed that migraine patients displayed disrupted connectivity between default mode, salience, cognitive, visuospatial, and sensorimotor networks, which was associated with group differences in pain catastrophizing and migraine-related disease variables in patients. Together, our findings show widespread morphological and functional brain abnormalities in migraineurs in affective, cognitive, visual, and pain-related brain areas, which are associated with increased pain catastrophizing, disease chronicity, and severity of symptoms, suggesting that these structural and functional changes may be a consequence of repeated, long-term nociceptive signaling leading to increased pain sensitivity, mood disturbances, and maladaptive coping strategies to deal with unrelenting pain.