Although neural activity often reflects the processing of external inputs, intrinsic fluctuations in activity have been observed throughout the brain. These may relate to patterns of self-generated thought that can occur while not performing goal-driven tasks. To understand the relationship between self-generated mental activity and intrinsic neural fluctuations, we developed the New York Cognition Questionnaire (NYC-Q) to assess the content and form of an individual's experiences during the acquisition of resting-state fMRI data. The data were collected as a part of the Nathan Kline Rockland Enhanced sample. We decomposed NYC-Q scores using exploratory factor analysis and found that self-reported thoughts clustered into distinct dimensions of content (future related, past related, positive, negative, and social) and form (words, images, and specificity). We used these components to perform an individual difference analysis exploring how differences in the types of self-generated thoughts relate to whole brain measures of intrinsic brain activity (fractional amplitude of low frequency fluctuations, regional homogeneity, and degree centrality). We found patterns of self-generated thoughts related to changes that were distributed across a wide range of cortical areas. For example, individuals who reported greater imagery exhibited greater low frequency fluctuations in a region of perigenual cingulate cortex, a region that is known to participate in the so-called default-mode network. We also found certain forms of thought were associated with other areas, such as primary visual cortex, the insula, and the cerebellum. For example, individuals who reported greater future thought exhibited less homogeneous neural fluctuations in a region of lateral occipital cortex, a result that is consistent with the claim that particular types of self-generated thought depend on processes that are decoupled from sensory processes. These data provide evidence that self-generated thought is a heterogeneous category of experience and that studying its content can be helpful in understanding brain dynamics.

Transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) has been shown to induce changes in motor performance and learning. Recent studies indicate that tDCS is capable of modulating widespread neural network properties within the brain. However the temporal evolution of online- and after-effects of tDCS on functional connectivity (FC) within and across the stimulated motor cortices (M1) still remain elusive. In the present study, two different tDCS setups were investigated: (i) unilateral M1 tDCS (anode over right M1, cathode over the contralateral supraorbital region) and (ii) bilateral M1 tDCS (anode over right M1, cathode over left M1). In a randomized single-blinded cross-over design, 12 healthy subjects underwent functional magnetic resonance imaging at rest before, during and after 20 min of either bi-, unilateral, or sham M1 tDCS. Seed-based FC analysis was used to investigate tDCS-induced changes across and within M1. We found that bilateral M1 tDCS induced (a) a decrease in interhemispheric FC during stimulation and (b) an increase in intracortical FC within right M1 after termination of the intervention. While unilateral M1 tDCS also resulted in similar effects during stimulation, no such changes could be observed after termination of tDCS. Our results provide evidence that depending on the electrode montage, tDCS acts upon a modulation of either intracortical and/or interhemispheric processing of M1.

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique capable of modulating cortical excitability and thereby influencing behavior and learning. Recent evidence suggests that bilateral tDCS over both primary sensorimotor cortices (SM1) yields more prominent effects on motor performance in both healthy subjects and chronic stroke patients than unilateral tDCS over SM1. To better characterize the underlying neural mechanisms of this effect, we aimed to explore changes in resting-state functional connectivity during both stimulation types. In a randomized single-blind crossover design, 12 healthy subjects underwent functional magnetic resonance imaging at rest before, during, and after 20 min of unilateral, bilateral, and sham tDCS stimulation over SM1. Eigenvector centrality mapping (ECM) was used to investigate tDCS-induced changes in functional connectivity patterns across the whole brain. Uni- and bilateral tDCS over SM1 resulted in functional connectivity changes in widespread brain areas compared with sham stimulation both during and after stimulation. Whereas bilateral tDCS predominantly modulated changes in primary and secondary motor as well as prefrontal regions, unilateral tDCS affected prefrontal, parietal, and cerebellar areas. No direct effect was seen under the stimulating electrode in the unilateral condition. The time course of changes in functional connectivity in the respective brain areas was nonlinear and temporally dispersed. These findings provide evidence toward a network-based understanding regarding the underpinnings of specific tDCS interventions.

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Cerebral small vessel disease, mainly characterized by white matter lesions and lacunes, has a high clinical impact as it leads to vascular dementia. Recent studies have shown that this disease impairs frontoparietal networks. Here, we apply resting-state magnetic resonance imaging and data-driven whole-brain imaging analysis methods (eigenvector centrality) to investigate changes of the functional connectome in early small vessel disease. We show reduced connectivity in frontoparietal networks, whereas connectivity increases in the cerebellum. These functional changes are closely related to white matter lesions and typical neuropsychological deficits associated with small vessel disease.

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Evidence from clinical studies shows that early cerebellar injury can cause abnormal development of the cerebral cortex in children. Characterization of normative development of the cerebellar and cerebello-cortical organization in early life is of great clinical importance. Here, we analyzed cerebellar, cerebello-cortical, and cortico-cortical functional networks using resting-state functional magnetic resonance imaging data of healthy infants (6 months, n = 21), children (4-10 years, n = 68), and adults (23-38 years, n = 25). We employed independent component analysis and identified 7 cerebellar functional networks in infants and 12 in children and adults. We revealed that the cerebellum was functionally connected with the sensorimotor cortex in infants but with the sensorimotor, executive control, and default mode systems of the cortex in children and adults. The functional connectivity strength in the cerebello-cortical functional networks of sensorimotor, executive control, and default mode systems was the strongest in middle childhood, but was weaker in adulthood. In contrast, the functional coherence of the cortico-cortical networks was stronger in adulthood. These findings suggest early synchronization of the cerebello-cortical networks in infancy, particularly in the early developing primary sensorimotor system. Conversely, age-related differences of cerebellar, cerebello-cortical, and cortico-cortical functional networks in childhood and adulthood suggest potential asynchrony of the cerebellar and cortical functional maturation.