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Auditory hallucinations are a debilitating symptom of schizophrenia. Effective treatment is limited because the underlying neural mechanisms remain unknown. Our study investigates how local and long-range functional connectivity is associated with auditory perceptual disturbances (APD) in schizophrenia. APD was assessed using the Auditory Perceptual Trait and State Scale. Resting state fMRI data were collected for N=99 patients with schizophrenia. Local functional connectivity was estimated using regional homogeneity (ReHo) analysis; long-range connectivity was estimated using resting state functional connectivity (rsFC) analysis. Mediation analyses tested whether local (ReHo) connectivity significantly mediated associations between long-distance rsFC and APD. Severity of APD was significantly associated with reduced ReHo in left and right putamen, left temporoparietal junction (TPJ), and right hippocampus-pallidum. Higher APD was also associated with reduced rsFC between the right putamen and the contralateral putamen and auditory cortex. Local and long-distance connectivity measures together explained 40.3% of variance in APD (P < 0.001), with the strongest predictor being the left TPJ ReHo (P < 0.001). Additionally, TPJ ReHo significantly mediated the relationship between right putamen - left putamen rsFC and APD (Sobel test, P = 0.001). Our findings suggest that both local and long-range functional connectivity deficits contribute to APD, emphasizing the role of striatum and auditory cortex. Considering the translational impact of these circuit-based findings within the context of prior clinical trials to treat auditory hallucinations, we propose a model in which correction of both local and long-distance functional connectivity deficits may be necessary to treat auditory hallucinations. [ABSTRACT FROM AUTHOR]

Recent work has identified disruption of several brain networks involving limbic and cortical regions that contribute to the generation of diverse symptoms of major depressive disorder (MDD). Of particular interest are the networks anchored on the right anterior insula, which binds the cortical and limbic regions to enable key functions that integrate bottom-up and top-down information in emotional and cognitive processing. Emotional appraisal has been linked to a presumed hierarchy of processing, from sensory percepts to affective states. But it is unclear whether the network level dysfunction seen in depression relates to a breakdown of this presumed hierarchical processing system from sensory to higher cognitive regions, mediated by core limbic regions (e.g. insula). In 16 patients with current MDD, and 16 healthy controls, we investigated differences in directional influences between anterior insula and the rest of the brain using resting-state functional magnetic resonance imaging (fMRI) and Granger-causal analysis (GCA), using anterior insula as a seed region. Results showed a failure of reciprocal influence between insula and higher frontal regions (dorsomedial prefrontal cortex) in addition to a weakening of influences from sensory regions (pulvinar and visual cortex) to the insula. This suggests dysfunction of both sensory and putative self-processing regulatory loops centered around the insula in MDD. For the first time, we demonstrate a network-level processing defect extending from sensory to frontal regions through insula in depression. Within limitations of inferences drawn from GCA of resting fMRI, we offer a novel framework to advance targeted network modulation approaches to treat depression. [ABSTRACT FROM AUTHOR]

In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. [ABSTRACT FROM AUTHOR]

Abstract: Background: Restless legs syndrome (RLS) is a primary sensory disorder with a secondary motor component (e.g., urge to move), and the thalamus is known to play a central role in RLS. The purpose of our study was to explore the intrinsic changes in the thalamocortical circuit in RLS patients using a resting-state functional magnetic resonance imaging (fMRI) paradigm. Methods: Resting-state fMRIs were obtained in the morning from 25 idiopathic RLS patients who were not using RLS medications and 25 controls. Resting-state connectivity was analyzed by a seed-based method using Analysis of Functional NeuroImages (AFNI) software with the bilateral thalami (ventroposterolateral nucleus [VPLN]). The connectivity characteristics of RLS patients were compared to those of the controls. Results: We found that RLS patients showed reduced thalamic connectivity with the right parahippocampal gyrus, right precuneus, right precentral gyrus, and bilateral lingual gyri; however, the right superior temporal gyrus, bilateral middle temporal gyrus, and right medial frontal gyrus showed enhanced connectivity with the thalamus. RLS severity was negatively correlated with connectivity between the thalamus and right parahippocampal gyrus (r =−0.414; P =.040). Conclusions: Our results suggest that the characteristics of the connectivity changes may reflect the pathways involved in producing RLS symptoms and indicate that RLS patients may have deficits in controlling and managing sensory information, which supports the act of viewing RLS as a disorder disrupting somatosensory processing. [Copyright &y& Elsevier]

Background: Functional magnetic resonance imaging (fMRI) has great potential for measuring mechanisms of functional changes in Alzheimer’s disease (AD) and mild cognitive impairment, but task fMRI studies have produced conflicting results, partly due to failure to account for underlying morphological changes and to variations in patients’ ability to perform the tasks. Resting fMRI has potential for assessing brain function independently from a task, but greater understanding of how networks of resting functional connectivity relate to the functioning of the brain is needed. We combined resting fMRI and task fMRI to examine the correspondence between these methods in individuals with cognitive impairment. Methods: Eighty elderly (25 control subjects, 25 mild cognitive impairment, 30 AD) underwent a combined multimodal magnetic resonance imaging protocol including task fMRI and resting fMRI. Task fMRI data were acquired during the execution of a memory paradigm designed to account for differences in task performance. Structural and physiological confounds were modeled for both fMRI modalities. Results: Successful recognition was associated with increased task fMRI activation in lateral prefrontal regions in AD relative to control subjects; this overlapped with increased resting fMRI functional connectivity in the same regions. Conclusions: Our results show that task fMRI and resting fMRI are sensitive markers of residual ability over the known changes in brain morphology and cognition occurring in AD and suggest that resting fMRI has a potential to measure the effect of new treatments. [Copyright &y& Elsevier]

Abstract: The default-mode network (DMN) has become a well accepted concept in cognitive and clinical neuroscience over the last decade, and perusal of the recent literature attests to a stimulating research field of cognitive and diagnostic applications (for example, (Andrews-Hanna et al., 2010; Koch et al., 2010; Sheline et al., 2009a; Sheline et al., 2009b; Uddin et al., 2008; Uddin et al., 2009; Weng et al., 2009; Yan et al., 2009)). However, a formal definition of what exactly constitutes a functional brain network is difficult to come by. In recent contributions, some researchers argue that the DMN is best understood as multiple interacting subsystems (Buckner et al., 2008) and have explored modular components of the DMN that have different functional specialization and could to some extent be identified separately (Fox et al., 2005; Uddin et al., 2009). Such conception of modularity seems to imply an opposite construct of a ‘unified whole’, but it is difficult to locate proponents of the idea of a DMN who are supplying constraints that can be brought to bear on data in rigorous tests. Our aim in this paper is to present a principled way of deriving a single covariance pattern as the neural substrate of the DMN, test to what extent its behavior tracks the coupling strength between critical seed regions, and investigate to what extent our stricter concept of a network is consistent with the already established findings about the DMN in the literature. We show that our approach leads to a functional covariance pattern whose pattern scores are a good proxy for the integrity of the connections between a medioprefrontal, posterior cingulate and parietal seed regions. Our derived DMN network thus has potential for diagnostic applications that are simpler to perform than computation of pairwise correlational strengths or seed maps. [Copyright &y& Elsevier]

Introduction Rapidly propagating frontal lobe seizures that are difficult to lateralize may do so after corpus callosotomy. We performed callosotomy using laser interstitial thermal therapy (LITT) in three patients who were undergoing stereoelectroencephalography (SEEG) and examined both the electrocorticogram electrophysiology and neuroimaging connectivity measures. Methods SEEG electrodes were placed three patients with suspected underlying laterization. All three patients underwent anterior corpus callosotomy using stereotactic laser interstitial ablation with electrodes in place (e.g. Fig. 1). Resting fMRI, diffusion tractography were obtained one week before electrode implantation and one week after. In addition, the resting electrocorticogram and corticocortical evoked potential mapping were performed before and after the callosotomy procedure using the same electrodes that were rigidly held in place with skull bolts, resulting in minimal electrode migration after callosotomy. Results All patients had marked lateralization of both interictal activity (Fig. 3) as well as seizure onset (Fig. 4). Alterations in interhemispheric connectivity was reliably demonstrated using DTI and resting fMRI. This was paralleled by a similar changes in resting electrocorticography and corticocortical evoked potentials over areas with projections to the area of the callosum that was lesioned. Both intrahemispheric connectivity as well as interhemispheric connectivity beyond the callosotomy were relatively maintained as reflected by electrocorticographic- and MRI-based measures. Conclusions Callosotomy using LITT may be used in conjunction with SEEG to accurately identify ictal onset in cases where seizure lateralization is difficult. Our results further confirm the correspondence of MRI- and electrophysiological-based connectivity measures by showing that alterations of function connectivity occur using both methods after surgical disconnection. [ABSTRACT FROM AUTHOR]