Given previous reports of strong interactions between vision and somatic senses, we investigated whether vision of the body modulates pain perception. Participants looked into a mirror aligned with their body midline at either the reflection of their own left hand (creating the illusion that they were looking directly at their own right hand) or the reflection of a neutral object. We induced pain using an infrared laser and recorded nociceptive laser-evoked potentials (LEPs). We also collected subjective ratings of pain intensity and unpleasantness. Vision of the body produced clear analgesic effects on both subjective ratings of pain and the N2/P2 complex of LEPs. Similar results were found during direct vision of the hand, without the mirror. Furthermore, these effects were specific to vision of one's own hand and were absent when viewing another person's hand. These results demonstrate a novel analgesic effect of non-informative vision of the body.

SUMMARY Spontaneous fMRI fluctuations are organized in large-scale spatiotemporal structures, or resting-state networks (RSN). However, it is unknown how task performance affects RSN dynamics. We use MEG to measure slow (~0.1 Hz) coherent fluctuations of band-limited power (BLP), a robust correlate of RSN, during rest and movie observation and compare them to fMRI-RSN. BLP correlation, especially in α band, dropped in multiple RSN during movie although overall topography was maintained. Variability of power correlation increased in visual occipital cortex, and transient decrements corresponded to scenes perceived as “event boundaries.” Additionally, stronger task-dependent interactions developed between vision and language networks in θ and β bands, and default and language networks in γ band. The topography of fMRI connectivity and relative changes induced by the movie were well matched to MEG. We conclude that resting-state and task network interactions are clearly different in the frequency domain despite maintenance of underlying network topography.

Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DAN→VIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing "idling" activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a "prior" for attention selection.functional connectivity | directional connectivity | resting-state networks | attention networks | task-evoked activity T he function of the brain has been traditionally studied in response to controlled stimuli at the level of single neurons, cortical circuits, or systems, and spontaneous activity has been modeled as stochastic noise, with its variability randomly affecting the threshold of postsynaptic firing (hence, the forward transmission of information through cortical circuits) (1). However, in the last two decades, it has become apparent that spontaneous activity is far from random but organized in space and time at the level of micro-and macrocircuitries (2) as well as at the level of large-scale distributed neuroanatomical systems (3). The large-scale organization of spontaneous activity has been most effectively studied by computing the temporal correlation of the blood oxygenation level-dependent (BOLD) signal (or functional connectivity) measured at rest with functional magnetic resonance imaging (fMRI) in the absence of any task or stimulus. The whole cerebral cortex has been subdivided in a relatively small number of networks formed by regions that show correlated activity over long periods of time [resting-state networks (RSNs)] (4, 5). The relatively small number of R...

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. In cases where functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assess similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by means of temporal correlation. Using natural vision data, we reveal regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This novel framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models.

Our behavior entails a flexible and context-sensitive interplay between brain areas to integrate information according to goal-directed requirements. However, the neural mechanisms governing the entrainment of functionally specialized brain areas remain poorly understood. In particular, the question arises whether observed changes in the regional activity for different cognitive conditions are explained by modifications of the inputs to the brain or its connectivity? We observe that transitions of fMRI activity between areas convey information about the tasks performed by 19 subjects, watching a movie versus a black screen (rest). We use a model-based framework that explains this spatiotemporal functional connectivity pattern by the local variability for 66 cortical regions and the network effective connectivity between them. We find that, among the estimated model parameters, movie viewing affects to a larger extent the local activity, which we interpret as extrinsic changes related to the increased stimulus load. However, detailed changes in the effective connectivity preserve a balance in the propagating activity and select specific pathways such that high-level brain regions integrate visual and auditory information, in particular boosting the communication between the two brain hemispheres. These findings speak to a dynamic coordination underlying the functional integration in the brain.