Spontaneous Brain Activity Predicts Task-Evoked Activity During Animate Versus Inanimate Touch.

The spontaneous activity of the brain is characterized by an elaborate temporal structure with scale-free properties as indexed by the power law exponent (PLE). We test the hypothesis that spontaneous brain activity modulates task-evoked activity during interactions with animate versus inanimate stimuli. For this purpose, we developed a paradigm requiring participants to actively touch either animate (real hand) or inanimate (mannequin hand) stimuli. Behaviorally, participants perceived the animate target as closer in space, temporally more synchronous with their own self, and more personally relevant, compared with the inanimate. Neuronally, we observed a modulation of task-evoked activity by animate versus inanimate interactions in posterior insula, in medial prefrontal cortex, comprising anterior cingulate cortex, and in medial superior frontal gyrus. Among these regions, an increased functional connectivity was shown between posterior insula and perigenual anterior cingulate cortex (PACC) during animate compared with inanimate interactions and during resting state. Importantly, PLE during spontaneous brain activity in PACC correlated positively with PACC task-evoked activity during animate versus inanimate stimuli. In conclusion, we demonstrate that brain spontaneous activity in PACC can be related to the distinction between animate and inanimate stimuli and thus might be specifically tuned to align our brain with its animate environment.

The impact of improved MEG-MRI co-registration on MEG connectivity analysis.

Co-registration between structural head images and functional MEG data is needed for anatomically-informed MEG data analysis. Despite the efforts to minimize the co-registration error, conventional landmark- and surface-based strategies for co-registering head and MEG device coordinates achieve an accuracy of typically 5-10 mm. Recent advances in instrumentation and technical solutions, such as the development of hybrid ultra-low-field (ULF) MRI-MEG devices or the use of 3D-printed individualized foam head-casts, promise unprecedented co-registration accuracy, i.e., 2 mm or better. In the present study, we assess through simulations the impact of such an improved co-registration on MEG connectivity analysis. We generated synthetic MEG recordings for pairs of connected cortical sources with variable locations. We then assessed the capability to reconstruct source-level connectivity from these recordings for 0-15-mm co-registration error, three levels of head modeling detail (one-, three- and four-compartment models), two source estimation techniques (linearly constrained minimum-variance beamforming and minimum-norm estimation MNE) and five separate connectivity metrics (imaginary coherency, phase-locking value, amplitude-envelope correlation, phase-slope index and frequency-domain Granger causality). We found that beamforming can better take advantage of an accurate co-registration than MNE. Specifically, when the co-registration error was smaller than 3 mm, the relative error in connectivity estimates was down to one-third of that observed with typical co-registration errors. MNE provided stable results for a wide range of co-registration errors, while the performance of beamforming rapidly degraded as the co-registration error increased. Furthermore, we found that even moderate co-registration errors (>6 mm, on average) essentially decrease the difference of four- and three- or one-compartment models. Hence, a precise co-registration is important if one wants to take full advantage of highly accurate head models for connectivity analysis. We conclude that an improved co-registration will be beneficial for reliable connectivity analysis and effective use of highly accurate head models in future MEG connectivity studies.

Alpha and alpha-beta phase synchronization mediate the recruitment of the visuospatial attention network through the Superior Longitudinal Fasciculus.

It is well known that attentional selection of relevant information relies on local synchronization of alpha band neuronal oscillations in visual cortices for inhibition of distracting inputs. Additionally, evidence for long-range coupling of neuronal oscillations between visual cortices and regions engaged in the anticipation of upcoming stimuli has been more recently provided. Nevertheless, on the one hand the relation between long-range functional coupling and anatomical connections is still to be assessed, and, on the other hand, the specific role of the alpha and beta frequency bands in the different processes underlying visuo-spatial attention still needs further clarification. We address these questions using measures of linear (frequency-specific) and nonlinear (cross-frequency) phase-synchronization in a cohort of 28 healthy subjects using magnetoencephalography. We show that alpha band phase-synchronization is modulated by the orienting of attention according to a parieto-occipital top-down mechanism reflecting behavior, and its hemispheric asymmetry is predicted by volume's asymmetry of specific tracts of the Superior-Longitudinal-Fasciculus. We also show that a network comprising parietal regions and the right putative Frontal-Eye-Field, but not the left, is recruited in the deployment of spatial attention through an alpha-beta cross-frequency coupling. Overall, we demonstrate that the visuospatial attention network features subsystems indexed by characteristic spectral fingerprints, playing different functional roles in the anticipation of upcoming stimuli and with diverse relation to fiber tracts.

Distinct modes of functional connectivity induced by movie-watching.

A fundamental question in systems neuroscience is how endogenous neuronal activity self-organizes during particular brain states. Recent neuroimaging studies have demonstrated systematic relationships between resting-state and task-induced functional connectivity (FC). In particular, continuous task studies, such as movie watching, speak to alterations in coupling among cortical regions and enhanced fluctuations in FC compared to the resting-state. This suggests that FC may reflect systematic and large-scale reorganization of functionally integrated responses while subjects are watching movies. In this study, we characterized fluctuations in FC during resting-state and movie-watching conditions. We found that the FC patterns induced systematically by movie-watching can be explained with a single principal component. These condition-specific FC fluctuations overlapped with inter-subject synchronization patterns in occipital and temporal brain regions. However, unlike inter-subject synchronization, condition-specific FC patterns were characterized by increased correlations within frontal brain regions and reduced correlations between frontal-parietal brain regions. We investigated these condition-specific functional variations as a shorter time scale, using time-resolved FC. The time-resolved FC showed condition-specificity over time; notably when subjects watched both the same and different movies. To explain self-organisation of global FC through the alterations in local dynamics, we used a large-scale computational model. We found that condition-specific reorganization of FC could be explained by local changes that engendered changes in FC among higher-order association regions, mainly in frontal and parietal cortices.

["ConnectToBrain" : Synergy project for therapeutic closed-loop stimulation of brain network disorders]. / "ConnectToBrain" : Synergy-Projekt zur Closed-loop-Stimulationstherapie von Netzwerkerkrankungen des Gehirns.

Therapeutic non-invasive transcranial brain stimulation with previous treatment protocols showed at best moderate effect sizes and large interindividual variability with a substantial proportion of non-responders. A currently intensively discussed approach to address these problems is individualized closed-loop stimulation. ConnectToBrain is a synergy project funded by the European Research Council to develop noninvasive closed-loop therapeutic stimulation of network disorders of the human brain.It consists of three main pillars: (1) development of a multichannel transcranial magnetic stimulation (mTMS) coil array that covers nearly all of the cerebral cortex and enables highly precise electronic control of location, direction, intensity and timing of the induced electrical fields, (2) development of real-time analysis of activity and connectivity in brain networks using electroencephalography (EEG) for instantaneous spatial and temporal control of stimulation (brain state-dependent, closed-loop stimulation) and adaptive optimization of treatment effects by machine learning and (3) translation of these neurotechnological innovations into physiological and clinical studies.

Disclosing large-scale directed functional connections in MEG with the multivariate phase slope index.

The phase slope index (PSI) is a method to disclose the direction of frequency-specific neural interactions from magnetoencephalographic (MEG) time series. A fundamental property of PSI is that of vanishing for linear mixing of independent neural sources. This property allows PSI to cope with the artificial instantaneous connectivity among MEG sensors or brain sources induced by the field spread. Nevertheless, PSI is limited by being a bivariate estimator of directionality as opposite to the multidimensional nature of brain activity as revealed by MEG. The purpose of this work is to provide a multivariate generalization of PSI. We termed this measure as the multivariate phase slope index (MPSI). In order to test the ability of MPSI in estimating the directionality, and to compare the MPSI results to those obtained by bivariate PSI approaches based on maximizing imaginary part of coherency and on canonical correlation analysis, we used extensive simulations. We proved that MPSI achieves the highest performance and that in a large number of simulated cases, the bivariate methods, as opposed to MPSI, do not detect a statistically significant directionality. Finally, we applied MPSI to assess seed-based directed functional connectivity in the alpha band from resting state MEG data of 61 subjects from the Human Connectome Project. The obtained results highlight a directed functional coupling in the alpha band between the primary visual cortex and several key regions of well-known resting state networks, e.g. dorsal attention network and fronto-parietal network.

Effective connectivity inferred from fMRI transition dynamics during movie viewing points to a balanced reconfiguration of cortical interactions.

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.

Functional connections between activated and deactivated brain regions mediate emotional interference during externally directed cognition.

Recent evidence shows that task-deactivations are functionally relevant for cognitive performance. Indeed, higher cognitive engagement has been associated with higher suppression of activity in task-deactivated brain regions - usually ascribed to the Default Mode Network (DMN). Moreover, a negative correlation between these regions and areas actively engaged by the task is associated with better performance. DMN regions show positive modulation during autobiographical, social, and emotional tasks. However, it is not clear how processing of emotional stimuli affects the interplay between the DMN and executive brain regions. We studied this interplay in an fMRI experiment using emotional negative stimuli as distractors. Activity modulations induced by the emotional interference of negative stimuli were found in frontal, parietal, and visual areas, and were associated with modulations of functional connectivity between these task-activated areas and DMN regions. A worse performance was predicted both by lower activity in the superior parietal cortex and higher connectivity between visual areas and frontal DMN regions. Connectivity between right inferior frontal gyrus and several DMN regions in the left hemisphere was related to the behavioral performance. This relation was weaker in the negative than in the neutral condition, likely suggesting less functional inhibitions of DMN regions during emotional processing. These results show that both executive and DMN regions are crucial for the emotional interference process and suggest that DMN connections are related to the interplay between externally-directed and internally-focused processes. Among DMN regions, superior frontal gyrus may be a key node in regulating the interference triggered by emotional stimuli.

Task and Regions Specific Top-Down Modulation of Alpha Rhythms in Parietal Cortex.

Alpha (8-12 Hz) power desynchronization is strongly associated to visual perception but has been observed in a large variety of tasks, indicating a general role in task anticipation. We previously reported in human observers that interference by repetitive transcranial magnetic stimulation (rTMS) of core regions of the dorsal attention network (DAN) disrupts both anticipatory alpha desynchronization and performance during a visuospatial attention (VSA) task. Here, we test the hypothesis that alpha desynchronization is task specific, and can be selectively modulated by interfering with activity in different higher-order parietal regions. We contrast the effects of rTMS on alpha rhythms and behavior on 2 different tasks: a VSA and a semantic decision task, by targeting the posterior intraparietal sulcus (pIPS), a core region of the DAN, or the angular gyrus (AG), a core region of the default mode network (DMN). We found that both performance and anticipatory alpha desynchronization were affected by stimulation of IPS only during VSA, and of AG only during semantic decisions. These findings indicate the existence of multiple dedicated parietal channels for the modulation of anticipatory alpha rhythms, which in turn reflect task-specific modulation of excitability in human parieto-occipital cortex.

Dynamic reorganization of human resting-state networks during visuospatial attention.

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.

Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.

When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity.

Intertrial Variability in the Premotor Cortex Accounts for Individual Differences in Peripersonal Space.

We live in a dynamic environment, constantly confronted with approaching objects that we may either avoid or be forced to address. A multisensory and sensorimotor interface, the peripersonal space (PPS), mediates every physical interaction between our body and the environment. Behavioral investigations show high variability in the extension of PPS across individuals, but there is a lack of evidence on the neural underpinnings of these large individual differences. Here, we used approaching auditory stimuli and fMRI to capture the individual boundary of PPS and examine its neural underpinnings. Precisely, we tested the hypothesis that intertrial variability (ITV) in brain regions coding PPS predicts individual differences of its boundary at the behavioral level. Selectively in the premotor cortex, we found that ITV, rather than trial-averaged amplitude, of BOLD responses to far rather than near dynamic stimuli predicts the individual extension of PPS. Our results provide the first empirical support for the relevance of ITV of brain responses for individual differences in human behavior. SIGNIFICANCE STATEMENT: Peripersonal space (PPS) is a multisensory and sensorimotor interface mediating every physical interaction between the body and the environment. A major characteristic of the boundary of PPS in humans is the extremely high variability of its location across individuals. We show that interindividual differences in the extension of the PPS are predicted by variability of BOLD responses in the premotor cortex to far stimuli approaching our body. Our results provide the first empirical support to the relevance of variability of evoked responses for human behavior and its variance across individuals.

Dynamics of EEG rhythms support distinct visual selection mechanisms in parietal cortex: a simultaneous transcranial magnetic stimulation and EEG study.

Using repetitive transcranial magnetic stimulation (rTMS), we have recently shown a functional anatomical distinction in human parietal cortex between regions involved in maintaining attention to a location [ventral intraparietal sulcus (vIPS)] and a region involved in shifting attention between locations [medial superior parietal lobule (mSPL)]. In particular, while rTMS interference over vIPS impaired target discrimination at contralateral attended locations, interference over mSPL affected performance following shifts of attention regardless of the visual field (Capotosto et al., 2013). Here, using rTMS interference in conjunction with EEG recordings of brain rhythms during the presentation of cues that indicate to either shift or maintain spatial attention, we tested whether this functional anatomical segregation involves different mechanisms of rhythm synchronization. The transient inactivation of vIPS reduced the amplitude of the expected parieto-occipital low-α (8-10 Hz) desynchronization contralateral to the cued location. Conversely, the transient inactivation of mSPL, compared with vIPS, reduced the high-α (10-12 Hz) desynchronization induced by shifting attention into both visual fields. Furthermore, rTMS induced a frequency-specific delay of task-related modulation of brain rhythms. Specifically, rTMS over vIPS or mSPL during maintenance (stay cues) or shifting (shift cues) of spatial attention, respectively, caused a delay of α parieto-occipital desynchronization. Moreover, rTMS over vIPS during stay cues caused a delay of δ (2-4 Hz) frontocentral synchronization. These findings further support the anatomo-functional subdivision of the dorsal attention network in subsystems devoted to shifting or maintaining covert visuospatial attention and indicate that these mechanisms operate in different frequency channels linking frontal to parieto-occipital visual regions.

Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

How local excitation-inhibition ratio impacts the whole brain dynamics.

The spontaneous activity of the brain shows different features at different scales. On one hand, neuroimaging studies show that long-range correlations are highly structured in spatiotemporal patterns, known as resting-state networks, on the other hand, neurophysiological reports show that short-range correlations between neighboring neurons are low, despite a large amount of shared presynaptic inputs. Different dynamical mechanisms of local decorrelation have been proposed, among which is feedback inhibition. Here, we investigated the effect of locally regulating the feedback inhibition on the global dynamics of a large-scale brain model, in which the long-range connections are given by diffusion imaging data of human subjects. We used simulations and analytical methods to show that locally constraining the feedback inhibition to compensate for the excess of long-range excitatory connectivity, to preserve the asynchronous state, crucially changes the characteristics of the emergent resting and evoked activity. First, it significantly improves the model's prediction of the empirical human functional connectivity. Second, relaxing this constraint leads to an unrealistic network evoked activity, with systematic coactivation of cortical areas which are components of the default-mode network, whereas regulation of feedback inhibition prevents this. Finally, information theoretic analysis shows that regulation of the local feedback inhibition increases both the entropy and the Fisher information of the network evoked responses. Hence, it enhances the information capacity and the discrimination accuracy of the global network. In conclusion, the local excitation-inhibition ratio impacts the structure of the spontaneous activity and the information transmission at the large-scale brain level.

Memory accumulation mechanisms in human cortex are independent of motor intentions.

Previous studies on perceptual decision-making have often emphasized a tight link between decisions and motor intentions. Human decisions, however, also depend on memories or experiences that are not closely tied to specific motor responses. Recent neuroimaging findings have suggested that, during episodic retrieval, parietal activity reflects the accumulation of evidence for memory decisions. It is currently unknown, however, whether these evidence accumulation signals are functionally linked to signals for motor intentions coded in frontoparietal regions and whether activity in the putative memory accumulator tracks the amount of evidence for only previous experience, as reflected in "old" reports, or for both old and new decisions, as reflected in the accuracy of memory judgments. Here, human participants used saccadic-eye and hand-pointing movements to report recognition judgments on pictures defined by different degrees of evidence for old or new decisions. A set of cortical regions, including the middle intraparietal sulcus, showed a monotonic variation of the fMRI BOLD signal that scaled with perceived memory strength (older > newer), compatible with an asymmetrical memory accumulator. Another set, including the hippocampus and the angular gyrus, showed a nonmonotonic response profile tracking memory accuracy (higher > lower evidence), compatible with a symmetrical accumulator. In contrast, eye and hand effector-specific regions in frontoparietal cortex tracked motor intentions but were not modulated by the amount of evidence for the effector outcome. We conclude that item recognition decisions are supported by a combination of symmetrical and asymmetrical accumulation signals largely segregated from motor intentions.

Brain activity modulation during the production of imperative and declarative pointing.

Pointing is a communicative gesture, commonly used for expressing two main intentions: imperative, to obtain a desired object/action from the other, or declarative, to share attention/interest about a referent with the other. Previous neuroimaging research on adults examined pointing almost exclusively as a reaching-like motor act rather than as a communicative gesture. Here, we used fMRI to record brain activity while 16 participants produced either imperative or declarative pointing gestures within a communicative context. A network of regions (the bilateral ventral premotor cortex, anterior midcingulate cortex, middle insula and the right preSMA) showed a preference for the production of declarative pointing as opposed to imperative pointing. The right preSMA also preferred declarative intention during pointing observation. Instead, independently from the intention, the right pMTG was more active during pointing observation than production. In the bilateral posterior parietal reach region we also observed a side (contra>ipsi) effect when the intention was imperative, regardless of the subject's role in the communication. Based on these results, we propose that pointing with declarative intention recruits a network of regions associated with will, motivation, emotional/affective expression and intersubjectivity, whereas pointing with imperative intention recruits regions associated with reaching. The proposal is consistent with the developmental hypothesis that declarative pointing reflects social cognitive abilities more than imperative pointing and establishes a stimulating link for future interdisciplinary research.

Interspecies activity correlations reveal functional correspondence between monkey and human brain areas.

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. For cases in which 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 assessed similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by temporal correlation. Using natural vision data, we revealed 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 framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models.

More gain less pain: balance control learning shifts the activation patterns of leg and neck muscles and increases muscular parsimony.

Athletes such as skaters or surfers maintain their balance on very unstable platforms. Remarkably, the most skilled athletes seem to execute these feats almost effortlessly. However, the dynamics that lead to the acquisition of a defined and efficient postural strategy are incompletely known. To understand the posture reorganization process due to learning and expertise, we trained twelve participants in a demanding balance/posture maintenance task for 4 months and measured their muscular activity before and after a (predictable) disturbance cued by an auditory signal. The balance training determined significant delays in the latency of participants' muscular activity: from largely anticipatory muscular activity (prior to training) to a mixed anticipatory-compensatory control strategy (after training). After training, the onset of activation was delayed for all muscles, and the sequence of activation systematically reflected the muscle position in the body from top to bottom: neck/upper body muscles were recruited first and in an anticipatory fashion, whereas leg muscles were recruited after the disturbance onset, producing compensatory adjustments. The resulting control strategy includes a mixture of anticipatory and compensatory postural adjustments, with a systematic sequence of muscular activation reflecting the different demands of neck and leg muscles. Our results suggest that subjects learned the precise timing of the disturbance onset and used this information to deploy postural adjustments just-in-time and to transfer at least part of the control of posture from anticipatory to less-demanding feedback-based strategies. In turn, this strategy shift increases the cost-efficiency of muscular activity, which is a key signature of skilled performance.

Individual variability in functional connectivity predicts performance of a perceptual task.

People differ in their ability to perform novel perceptual tasks, both during initial exposure and in the rate of improvement with practice. It is also known that regions of the brain recruited by particular tasks change their activity during learning. Here we investigate neural signals predictive of individual variability in performance. We used resting-state functional MRI to assess functional connectivity before training on a novel visual discrimination task. Subsequent task performance was related to functional connectivity measures within portions of visual cortex and between visual cortex and prefrontal association areas. Our results indicate that individual differences in performing novel perceptual tasks can be related to individual differences in spontaneous cortical activity.