NeuroImage
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In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of brain activity during a separate task. However, anatomical boundaries may be difficult to discern, and designing a task to interrogate desired brain regions of interest may be difficult, especially when subject compliance is in question, as in many patient studies. ⋯ Connectivity maps generated by rest-based seeds and task-based seeds were statistically equivalent; however, only 3 min of data were required to reach significance for rest-based seeds compared to an estimated 6 min for task-based seeds. Rest-based seeds also exhibited good inter-experimenter reproducibility. These findings suggest that seed regions based on inter-voxel cross-correlation of resting-state signals can be used as an alternative approach for connectivity analysis when task-related activity is not available or difficult to acquire, as in some patient studies.
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Normal aging is accompanied by various cognitive functional declines. Recent studies have revealed disruptions in the coordination of large-scale functional brain networks such as the default mode network in advanced aging. However, organizational alterations of the structural brain network at the system level in aging are still poorly understood. ⋯ More importantly, the aging brain network exhibited reduced intra-/inter-module connectivity in modules corresponding to the executive function and the default mode network of young adults, which might be associated with the decline of cognitive functions in aging. Finally, we observed age-associated alterations in the regional characterization in terms of their intra/inter-module connectivity. Our results indicate that aging is associated with an altered modular organization in the structural brain networks and provide new evidence for disrupted integrity in the large-scale brain networks that underlie cognition.
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Analyses of spontaneous hemodynamic fluctuations observed on functional magnetic resonance imaging (fMRI) have revealed the existence of temporal correlations in signal changes between widely separated brain regions during the resting state, termed "resting state functional connectivity." Recent studies have demonstrated that these correlations are also present in the hemodynamic signals measured by near infrared spectroscopy (NIRS). However, it is still uncertain whether frequency-specific characteristics exist in these signals. In the present study, we used multichannel NIRS to investigate the frequency dependency of functional connectivity between diverse regions in the cerebral cortex by decomposing fluctuations of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) signals into various frequency bands. ⋯ This approach demonstrated that functional connectivity based on the oxy-Hb signals between homologous cortical regions of the contralateral hemisphere (homologous connectivity) showed high coherence over a wide frequency range (0.009-0.1Hz), whereas connectivity between the prefrontal and occipital regions (fronto-posterior connectivity) showed high coherence only within a specific narrow frequency range (0.04-0.1Hz). Our findings suggest that homologous connectivity may reflect synchronization of neural activation over a wide frequency range through direct neuroanatomical connections, whereas fronto-posterior connectivity as revealed by high coherence only within a specific narrow frequency range corresponding to the time scale of typical hemodynamic response to a single event may reflect synchronization of transient neural activation among distant cortical regions. The present study demonstrated that NIRS provides a powerful tool to elucidate network properties of the cortex during resting state.