Tinnitus- and Task-Related Differences in Resting-State Networks

We investigated tinnitus-related differences in functional networks in adults with tinnitus by means of a functional connectivity study. Previously it was found that various networks show differences in connectivity in patients with tinnitus compared to controls. How this relates to patients' ongoing tinnitus and whether the ecological sensory environment modulates connectivity remains unknown. Twenty healthy controls and twenty patients suffering from chronic tinnitus were enrolled in this study. Except for the presence of tinnitus in the patient group, all subjects were selected to have normal or near-normal hearing. fMRI data were obtained in two different functional states. In one set of runs, subjects freely viewed emotionally salient movie fragments ("fixed-state") while in the other they were not performing any task ("resting-state"). After data pre-processing, Principal Component Analysis was performed to obtain 25 components for all datasets. These were fed into an Independent Component Analysis (ICA), concatenating the data across both groups and both datasets, to obtain group-level networks of neural origin, each consisting of spatial maps with their respective time-courses. Subject-specific maps and their time-course were obtained by back-projection (Dual Regression). For each of the components a mixed-effects linear model was composed with factors group (tinnitus vs. controls), task (fixed-state vs. resting state) and their interaction. The neural components comprised the visual, sensorimotor, auditory, and limbic systems, the default mode, dorsal attention, executive-control, and frontoparietal networks, and the cerebellum. Most notably, the default mode network (DMN) was less extensive and shows significantly less connectivity in tinnitus patients than in controls. This group difference existed in both paradigms. At the same time, the DMN was stronger during resting-state than during fixed-state in the controls but not the patients. We attribute this pattern to the unremitting engaging effect of the tinnitus percept.</p

Functional segmentation of the hippocampus in the healthy human brain and in Alzheimer's disease (vol 66, pg 28, 2013)

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Estimating interactions of functional brain connectivity by Hidden Markov models

The brain activity reflected by functional magnetic resonance imaging (fMRI) is temporally organized as a combination of sensory inputs from environment and its own spontaneous activity. However, temporal patterns of brain activity in a large number of subjects remain unclear. We propose a regularized hidden Markov model (HMM) to estimate dynamic functional connectivity among distributed brain regions and discover repeating connectivity patterns from resting-state functional connectivity across a group of subjects. We found that functional brain connectivity are hierarchically organized and exhibit three repeated patterns across subjects with attention deficit hyperactivity disorder (ADHD). We have examined the temporal characteristics of functional connectivity by its occupancy. And we validated our method by comparing the classification performance with state-of-the-art methods using the same dataset. Experimental results show that our method can improve the classification performance compared to other functional connectivity modelling methods