Changes in Early Cortical Visual Processing Predict Enhanced Reactivity in Deaf Individuals

Individuals with profound deafness rely critically on vision to interact with their environment. Improvement of visual performance as a consequence of auditory deprivation is assumed to result from cross-modal changes occurring in late stages of visual processing. Here we measured reaction times and event-related potentials (ERPs) in profoundly deaf adults and hearing controls during a speeded visual detection task, to assess to what extent the enhanced reactivity of deaf individuals could reflect plastic changes in the early cortical processing of the stimulus. We found that deaf subjects were faster than hearing controls at detecting the visual targets, regardless of their location in the visual field (peripheral or peri-foveal). This behavioural facilitation was associated with ERP changes starting from the first detectable response in the striate cortex (C1 component) at about 80 ms after stimulus onset, and in the P1 complex (100–150 ms). In addition, we found that P1 peak amplitudes predicted the response times in deaf subjects, whereas in hearing individuals visual reactivity and ERP amplitudes correlated only at later stages of processing. These findings show that long-term auditory deprivation can profoundly alter visual processing from the earliest cortical stages. Furthermore, our results provide the first evidence of a co-variation between modified brain activity (cortical plasticity) and behavioural enhancement in this sensory-deprived population

Resting-State Brain Organization Revealed by Functional Covariance Networks

BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale

Your Resting Brain CAREs about Your Risky Behavior

Research on the neural correlates of risk-related behaviors and personality traits has provided insight into mechanisms underlying both normal and pathological decision-making. Task-based neuroimaging studies implicate a distributed network of brain regions in risky decision-making. What remains to be understood are the interactions between these regions and their relation to individual differences in personality variables associated with real-world risk-taking.We employed resting state functional magnetic resonance imaging (R-fMRI) and resting state functional connectivity (RSFC) methods to investigate differences in the brain's intrinsic functional architecture associated with beliefs about the consequences of risky behavior. We obtained an individual measure of expected benefit from engaging in risky behavior, indicating a risk seeking or risk-averse personality, for each of 21 participants from whom we also collected a series of R-fMRI scans. The expected benefit scores were entered in statistical models assessing the RSFC of brain regions consistently implicated in both the evaluation of risk and reward, and cognitive control (i.e., orbitofrontal cortex, nucleus accumbens, lateral prefrontal cortex, dorsal anterior cingulate). We specifically focused on significant brain-behavior relationships that were stable across R-fMRI scans collected one year apart. Two stable expected benefit-RSFC relationships were observed: decreased expected benefit (increased risk-aversion) was associated with 1) stronger positive functional connectivity between right inferior frontal gyrus (IFG) and right insula, and 2) weaker negative functional connectivity between left nucleus accumbens and right parieto-occipital cortex.Task-based activation in the IFG and insula has been associated with risk-aversion, while activation in the nucleus accumbens and parietal cortex has been associated with both risk seeking and risk-averse tendencies. Our results suggest that individual differences in attitudes toward risk-taking are reflected in the brain's functional architecture and may have implications for engaging in real-world risky behaviors

Resting-State Functional Connectivity between Fronto-Parietal and Default Mode Networks in Obsessive-Compulsive Disorder

Background: Obsessive-compulsive disorder (OCD) is characterized by an excessive focus on upsetting or disturbing thoughts, feelings, and images that are internally-generated. Internally-focused thought processes are subserved by the ‘‘default mode network’ ’ (DMN), which has been found to be hyperactive in OCD during cognitive tasks. In healthy individuals, disengagement from internally-focused thought processes may rely on interactions between DMN and a frontoparietal network (FPN) associated with external attention and task execution. Altered connectivity between FPN and DMN may contribute to the dysfunctional behavior and brain activity found in OCD. Methods: The current study examined interactions between FPN and DMN during rest in 30 patients with OCD (17 unmedicated) and 32 control subjects (17 unmedicated). Timecourses from seven fronto-parietal seeds were correlated across the whole brain and compared between groups. Results: OCD patients exhibited altered connectivity between FPN seeds (primarily anterior insula) and several regions of DMN including posterior cingulate cortex, medial frontal cortex, posterior inferior parietal lobule, and parahippocampus. These differences were driven largely by a reduction of negative correlations among patients compared to controls. Patients also showed greater positive connectivity between FPN and regions outside DMN, including thalamus, lateral frontal cortex, and somatosensory/motor regions

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank

General intelligence is associated with working memory-related brain activity: new evidence from a large sample study

Psychometric intelligence is closely related to working memory capacity. Here we aim to determine the associations of neural activation patterns during the N-back working memory paradigm with psychometric intelligence and working memory performance. We solved the statistical problems of previous studies using (1) a large cohort of 1235 young adults and (2) robust voxel-by-voxel permutation-based statistics at the whole-brain level. Many of the significant correlations were we ak, and our findings were not consistent with those of previous studies. We observed that many of the significant correlations involved brain areas in the periphery or boundaries between the task-positive network (TPN) and task-negative network (TNN), suggesting that the expansion of the TPN or TNN is associated with greater cognitive ability. Lower activity in TPN and less task-induced deactivation (TID) in TNN were associated with greater cognitive ability. These findings indicate that subjects with greater cognitive ability have a lower brain response to task demand, consistent with the notion that TID in TNN reflects cognitive demand but partly inconsistent with the prevailing neural efficiency theory. One exception was the pre-supplementary motor area, which plays a key role in cognitive control and sequential processing. In this area, intelligent subjects demonstrated greater activity related to working memory, suggesting that the pre-supplementary motor area plays a unique role in the execution of working memory tasks in intelligent subjects