Neurobiological theories posit that schizophrenia relates to disturbances in connectivity between brain regions. Resting-state functional magnetic resonance imaging is a powerful tool for examining functional connectivity and has revealed several canonical brain networks, including the default mode, dorsal attention, executive control, and salience networks. The purpose of this study was to examine changes in these networks in schizophrenia. 42 patients with schizophrenia and 61 healthy subjects completed a RS-fMRI scanning session. Seed-based region-of-interest correlation analysis was used to identify the default mode, dorsal attention, executive control, and salience networks. Compared to healthy subjects, individuals with schizophrenia demonstrated greater connectivity between the posterior cingulate cortex, a key hub of the default mode, and the left inferior gyrus, left middle frontal gyrus, and left middle temporal gyrus. Interestingly, these regions were more strongly connected to the executive control network in healthy control subjects. In contrast to the default mode, patients demonstrated less connectivity in the executive control and dorsal attention networks. No differences were observed in the salience network. The results indicate that resting-state networks are differentially affected in schizophrenia. The alterations are characterized by reduced segregation between the default mode and executive control networks in the prefrontal cortex and temporal lobe, and reduced connectivity in the dorsal attention and executive control networks. The changes suggest that the process of functional specialization is altered in schizophrenia. Further work is needed to determine if the alterations are related to disturbances in white matter connectivity, neurodevelopmental abnormalities, and genetic risk for schizophrenia.

Functional magnetic resonance imaging is widely used to detect and delineate regions of the brain that change their level of activation in response to specific stimuli and tasks. Simple activation maps depict only the average level of engagement of different regions within distributed systems. FMRI potentially can reveal additional information about the degree by which components of large-scale neural systems are functionally coupled together to achieve specific tasks. In order to better understand how brain regions contribute to functionally connected circuits, it is necessary to record activation maps either as a function of different conditions, at different times or in different subjects. Data obtained under different conditions may then be analyzed by a variety of techniques to infer correlations and couplings between nodes in networks. Several different multivariate statistical methods have been adapted and applied to analyze the variations within such data. An approach of particular interest that is suited to studies of connectivity within single subjects makes use of acquisitions of runs of MRI images obtained while the brain is in a so-called steady state, either at rest (i.e. without any specific stimulus or task) or in a condition of continuous activation. The interregional correlations between fluctuations of MRI signal potentially reveal functional connectivity. Recent studies have established that interregional correlations between different components of circuits in each of the visual, language, motor and working memory systems can be detected in the resting state. The correlations at baseline are changed during the performance of a continuous task. In this review the various methods available for assessing connectivity are described and evaluated.

Summary Our ability to multitask is severely limited: Task performance deteriorates when we attempt to undertake two or more tasks simultaneously. Remarkably, extensive training can greatly reduce such multitasking costs. While it is not known how training alters the brain to solve the multitasking problem, it likely involves the prefrontal cortex given this brain region’s purported role in limiting multitasking performance. Here we show that the reduction of multitasking interference with training is not achieved by diverting the flow of information processing away from the prefrontal cortex, or by segregating prefrontal cells into independent task-specific neuronal ensembles, but rather by increasing the speed of information processing in this brain region, thereby allowing multiple tasks to be processed in rapid succession. These results not only reveal how training leads to efficient multitasking, they also provide a mechanistic account of multitasking limitations, namely the poor speed of information processing in human prefrontal cortex.

Objective Delirium duration is predictive of long-term cognitive impairment (LTCI) in Intensive Care Unit (ICU) survivors. Hypothesizing that a neuroanatomical basis may exist for the relationship between delirium and LTCI, we conducted this exploratory investigation of the associations between delirium duration, brain volumes and LTCI. Design, Setting, and Patients A prospective cohort of medical and surgical ICU survivors with respiratory failure or shock. Measurements Quantitative high resolution 3-Tesla brain magnetic resonance imaging was used to calculate brain volumes at discharge and three-month follow-up. Delirium was evaluated using the Confusion Assessment Method for the ICU; cognitive outcomes were tested at three- and twelve-month follow-up. Linear regression was used to examine associations between delirium duration and brain volumes, and between brain volumes and cognitive outcomes. Results A total of 47 patients completed the MRI protocol. Patients with longer duration of delirium displayed greater brain atrophy as measured by a larger ventricle-to-brain ratio (VBR) at hospital discharge [0.76, 95% confidence intervals (CI) (0.10, 1.41); p=0.03] and at 3-month follow-up [0.62 (0.02, 1.21), p=0.05]. Longer duration of delirium was associated with smaller superior frontal lobe [−2.11 cm3 (−3.89, −0.32); p=0.03] and hippocampal volumes at discharge [−0.58 cm3 (−0.85, −0.31), p<0.001] – regions responsible for executive functioning and memory, respectively. Greater brain atrophy (higher VBR) at three months was associated with worse cognitive performances at twelve months [lower RBANS battery score −11.17 (−21.12, −1.22), p=0.04]. Smaller superior frontal lobes, thalamus, and cerebellar volumes at three months were associated with worse executive functioning and visual attention at twelve months. Conclusions These preliminary data show that longer duration of delirium is associated with smaller brain volumes up to three months after discharge, and that smaller brain volumes are associated with LTCI up to 12 months. We cannot, however, rule out that smaller preexisting brain volumes explain these findings.

Functional MRI based on blood oxygenation level-dependent (BOLD) contrast is well established as a neuroimaging technique for detecting neural activity in the cortex of the human brain. While detection and characterization of BOLD signals, as well as their electrophysiological and hemodynamic/metabolic origins, have been extensively studied in gray matter (GM), the detection and interpretation of BOLD signals in white matter (WM) remain controversial. We have previously observed that BOLD signals in a resting state reveal structure-specific anisotropic temporal correlations in WM and that external stimuli alter these correlations and permit visualization of task-specific fiber pathways, suggesting variations in WM BOLD signals are related to neural activity. In this study, we provide further strong evidence that BOLD signals in WM reflect neural activities both in a resting state and under functional loading. We demonstrate that BOLD signal waveforms in stimulus-relevant WM pathways are synchronous with the applied stimuli but with various degrees of time delay and that signals in WM pathways exhibit clear task specificity. Furthermore, resting-state signal fluctuations in WM tracts show significant correlations with specific parcellated GM volumes. These observations support the notion that neural activities are encoded in WM circuits similarly to cortical responses.

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We recently reported our findings of resting state functional connectivity in the human spinal cord: in a cohort of healthy volunteers we observed robust functional connectivity between left and right ventral (motor) horns and between left and right dorsal (sensory) horns (Barry et al., 2014). Building upon these results, we now quantify the within-subject reproducibility of bilateral motor and sensory networks (intraclass correlation coefficient = 0.54–0.56) and explore the impact of including frequencies up to 0.13 Hz. Our results suggest that frequencies above 0.08 Hz may enhance the detectability of these resting state networks, which would be beneficial for practical studies of spinal cord functional connectivity.

Objective Evidence is emerging that delirium duration is a predictor of long-term cognitive impairment (LTCI) in Intensive Care Unit (ICU) survivors. Relationships between (a) delirium duration and brain white matter integrity, and (b) between white matter integrity and LTCI are poorly understood and could be explored using Magnetic Resonance Imaging (MRI). Design, Setting, Patients A two-center, prospective cohort study incorporating delirium monitoring, neuroimaging and cognitive testing in ICU survivors. Measurements Delirium was evaluated with the Confusion Assessment Method for the ICU (CAM-ICU) and cognitive outcomes were tested at 3 and 12-month follow-up. Following the ICU stay, Fractional Anisotropy (FA), a measure of white matter integrity, was calculated quantitatively using Diffusion Tensor Imaging (DTI) with a 3-Tesla MRI scanner at hospital discharge and three-month follow-up. We examined associations between (a) delirium duration and FA and (b) between FA and cognitive outcomes using linear regression adjusted for age and sepsis. Results A total of 47 patients with median age of 50 years completed the DTI-MRI protocol. Greater duration of delirium (3 vs. 0 days) was associated with lower FA (i.e. reduced FA=white matter disruption) in the genu (−0.02; p = 0.04) and splenium (−0.01; p = 0.02) of the corpus callosum and anterior limb of the internal capsule (−0.02; p = 0.01) at hospital discharge. These associations persisted at 3 months for the genu (−0.02; p= 0.02) and splenium (−0.01; p= 0.004). Lower FA in the anterior limb of internal capsule at discharge (−10.35; p= 0.05) and in genu of corpus callosum at three months (−8.81; p = 0.006) was associated with worse cognitive scores at 3 and 12 months. Conclusions In this pilot investigation, delirium duration in the ICU was associated with white matter disruption at both discharge and 3 months. Similarly, white matter disruption was associated with worse cognitive scores up to 12 months later. This hypothesis-generating investigation may help design future studies to explore these complex relationships in greater depth.