Plasticity of DNA methylation, functional brain connectivity and efficiency in cognitive remediation for schizophrenia.

Cognitive remediation (CR) is predicated on principles of neuroplasticity, but the actual molecular and neurocircuitry changes underlying cognitive change in individuals with impaired neuroplastic processes is poorly understood. The present study examined epigenetic-neurocircuitry-behavioral outcome measures in schizophrenia, before and after participating in a CR program that targeted higher-order cognitive functions. Outcome measures included DNA methylation of genes central to synaptic plasticity (CpG sites of Reelin promoter and BDNF promoter) from buccal swabs, resting-state functional brain connectivity and topological network efficiency, and global scores of a cognitive battery from 35 inpatients in a rehabilitative ward (18 CR, 17 non-CR) with similar premorbid IQ to 15 healthy controls. Baseline group differences between healthy controls and schizophrenia, group-by-time effects of CR in schizophrenia, and associations between the outcome measures were tested. Baseline functional connectivity abnormalities within the frontal, fronto-temporal and fronto-parietal regions, and trending decreases in global efficiency, but not DNA methylation, were found in schizophrenia; the frontal and fronto-temporal connectivity, and global efficiency correlated with global cognitive performance across all individuals. Notably, CR resulted in differential changes in Reelin promoter CpG methylation levels, altered within-frontal and fronto-temporal functional connectivity, increasing global efficiency and improving cognitive performance in schizophrenia, when compared to non-CR. In the CR inpatients, positive associations between the micro to macro measures: Reelin methylation changes, higher global efficiency and improving global cognitive performance were found. Present findings provide a neurobiological insight into potential CR-led epigenetics-neurocircuitry modifications driving cognitive plasticity.

Neural correlates of retrieval-based enhancement of autobiographical memory in older adults.

Lifelog photo review is considered to enhance the recall of personal events. While a sizable body of research has explored the neural basis of autobiographical memory (AM), there is limited neural evidence on the retrieval-based enhancement effect on event memory among older adults in the real-world environment. This study examined the neural processes of AM as was modulated by retrieval practice through lifelog photo review in older adults. In the experiment, blood-oxygen-level dependent response during subjects' recall of recent events was recorded, where events were cued by photos that may or may not have been exposed to a priori retrieval practice (training). Subjects remembered more episodic details under the trained relative to non-trained condition. Importantly, the neural correlates of AM was exhibited by (1) dissociable cortical areas related to recollection and familiarity, and (2) a positive correlation between the amount of recollected episodic details and cortical activation within several lateral temporal and parietal regions. Further analysis of the brain activation pattern at a few regions of interest within the core remember network showed a training_condition × event_detail interaction effect, suggesting that the boosting effect of retrieval practice depended on the level of recollected event details.

Regularized Spatial Filtering Method (R-SFM) for detection of Attention Deficit Hyperactivity Disorder (ADHD) from resting-state functional Magnetic Resonance Imaging (rs-fMRI).

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental problem in children. Resting state functional magnetic resonance imaging (rs-fMRI) provides an important tool in understanding the aberrant functional mechanisms in ADHD patients and assist in clinical diagnosis. Recently, spatio-temporal decomposition via spatial filtering (Fukunaga-Koontz transform, ICA) have gained attention in the analysis of fMRI time-series data. Their ability to decompose the blood oxygen level dependent (BOLD) rs-fMRI time series data into discriminative spatial and temporal components have resulted in better classification accuracy and the ability to isolate the important brain circuits responsible for the observed differences in brain activity. However, they are prone to errors in the estimation of covariance matrices due to the significant presence of atypical samples in the ADHD dataset. In this paper, we present a regularization framework to obtain a robust estimation of the covariance matrices such that the effect of atypical samples is reduced. The resulting approach called as regularized spatial filtering method (R-SFM) further uses Mahalanobis whitening to lower the effect of two-way correlations while preserving the spatial arrangement of the data in the feature extraction process. R-SFM was evaluated on the benchmark ADHD200 dataset and not only obtained a 6% improvement in classification accuracy, but also a 66.66% decrease in standard deviation over the previously developed SFM approach. Also R-SFM produces higher specificity which results in lower misclassification of ADHD, thereby reducing the risk of misdiagnosis. These results clearly show that R- SFM provides an accurate and reliable tool for detection of ADHD from BOLD rs-fMRI time series data.

Identification of lateralized compensatory neural activities within the social brain due to autism spectrum disorder in adolescent males.

Socio-behavioral impairments are important characteristics of autism spectrum disorders (ASD) and MRI-based studies are pursued to identify a neurobiological basis behind these conditions. This paper presents an MRI-based study undertaken to (i) identify the differences in brain activities due to ASD, (ii) verify whether such differences exist within the 'social brain' circuit which is hypothesized to be responsible for social functions, and (iii) uncover potential compensatory mechanisms within the identified differences in brain activities. In this study, a whole-brain voxel-wise analysis is performed using resting-state fMRI data from 598 adolescent males, that is openly available from the ABIDE consortium. A new method is developed, which can (i) extract the discriminative brain activities, that provide high separability between the blood oxygenation time-series signals from ASD and neurotypical populations, (ii) select the activities that are relevant to ASD by evaluating the correlation between the separability and traditional severity scores, and (iii) map the spatial pattern of regions responsible for generating the discriminative activities. The results show that the most discriminative brain activities occur within a subset of the social brain that is involved with affective aspects of social processing, thereby supporting the idea of the social brain and also its fractionalization in ASD. Further, it has also been found that the diminished activities in the posterior cingulate area are potentially compensated by enhanced activities in the ventromedial prefrontal and anterior temporal areas within the social brain. Hemispherical lateralization is also observed on such compensatory activities.

Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

This paper presents a new approach for detecting major differences in brain activities between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the resting state fMRI. Further the method also extracts discriminative features for an accurate diagnosis of ASD. The proposed approach determines a spatial filter that projects the covariance matrices of the Blood Oxygen Level Dependent (BOLD) time-series signals from both the ASD patients and neurotypical subjects in orthogonal directions such that they are highly separable. The inverse of this filter also provides a spatial pattern map within the brain that highlights those regions responsible for the distinguishable activities between the ASD patients and neurotypical subjects. For a better classification, highly discriminative log-variance features providing the maximum separation between the two classes are extracted from the projected BOLD time-series data. A detailed study has been carried out using the publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) consortium for the different gender and age-groups. The study results indicate that for all the above categories, the regional differences in resting state activities are more commonly found in the right hemisphere compared to the left hemisphere of the brain. Among males, a clear shift in activities to the prefrontal cortex is observed for ASD patients while other parts of the brain show diminished activities compared to neurotypical subjects. Among females, such a clear shift is not evident; however, several regions, especially in the posterior and medial portions of the brain show diminished activities due to ASD. Finally, the classification performance obtained using the log-variance features is found to be better when compared to earlier studies in the literature.