Search

Hand visibility affects motor control, perception, and attention, as visual information is integrated into an internal model of somatomotor control. Spontaneous brain activity, i.e., at rest, in the absence of an active task, is correlated among somatomotor regions that are jointly activated during motor tasks. Recent studies suggest that spontaneous activity patterns not only replay task activation patterns but also maintain a model of the body's and environment's statistical regularities (priors), which may be used to predict upcoming behavior. Here, we test whether spontaneous activity in the human somatomotor cortex as measured using fMRI is modulated by visual stimuli that display hands vs. non-hand stimuli and by the use/action they represent. A multivariate pattern analysis was performed to examine the similarity between spontaneous activity patterns and task-evoked patterns to the presentation of natural hands, robot hands, gloves, or control stimuli (food). In the left somatomotor cortex, we observed a stronger (multivoxel) spatial correlation between resting state activity and natural hand picture patterns compared to other stimuli. No task-rest similarity was found in the visual cortex. Spontaneous activity patterns in somatomotor brain regions code for the visual representation of human hands and their use., (© 2024. The Author(s).)

Recent evidence suggests that, in the absence of any task, spontaneous brain activity patterns and connectivity in the visual and motor cortex code for natural stimuli and actions, respectively. These "resting-state" activity patterns may underlie the maintenance and consolidation (replay) of information states coding for ecological stimuli and behaviors. In this study, we examine whether replay patterns occur in resting-state activity in association cortex grouped into high-order cognitive networks not directly processing sensory inputs or motor outputs. Fifteen participants (7 females) performed four hand movements during an fMRI study. Three movements were ecological. The fourth movement as control was less ecological. Before and after the task scans, we acquired resting-state fMRI scans. The analysis examined whether multivertex task activation patterns for the four movements computed at the cortical surface in different brain networks resembled spontaneous activity patterns measured at rest. For each movement, we computed a vector of r values indicating the strength of the similarity between the mean task activation pattern and frame-by-frame resting-state patterns. We computed a cumulative distribution function of r 2 values and used the 90th percentile cutoff value for comparison. In the dorsal attention network, resting-state patterns were more likely to match task patterns for the ecological movements than the control movement. In contrast, rest-task pattern correlation was more likely for less ecological movement in the ventral attention network. These findings show that spontaneous activity patterns in human attention networks code for hand movements. SIGNIFICANCE STATEMENT fMRI indirectly measures neural activity noninvasively. Resting-state (spontaneous) fMRI signals measured in the absence of any task resemble signals evoked by task performance both in topography and inter-regional (functional) connectivity. However, the function of spontaneous brain activity is unknown. We recently showed that spatial activity patterns evoked by visual and motor tasks in visual and motor cortex, respectively, occur at rest in the absence of any stimulus or response. Here we show that activity patterns related to hand movements replay at rest in frontoparietal regions of the human attention system. These findings show that spontaneous activity in the human cortex may mediate the maintenance and consolidation of information states coding for ecological stimuli and behaviors., (Copyright © 2023 the authors.)

Understanding the relationships between brain organization and behavior is a central goal of neuroscience. Traditional teaching emphasizes that the human cerebrum includes many distinct areas for which damage or dysfunction would lead to a unique and specific behavioral syndrome. This teaching implies that brain areas correspond to encapsulated modules that are specialized for specific cognitive operations. However, empirically, local damage from stroke more often produces one of a small number of clusters of deficits and disrupts brain-wide connectivity in a small number of predictable ways (relative to the vast complexity of behavior and brain connectivity). Behaviors that involve shared operations show correlated deficits following a stroke, consistent with a low-dimensional behavioral space. Because of the networked organization of the brain, local damage from a stroke can result in widespread functional abnormalities, matching the low dimensionality of behavioral deficit. In alignment with this, neurological disease, psychiatric disease, and altered brain states produce behavioral changes that are highly correlated across a range of behaviors. We discuss how known structural and functional network priors in addition to graph theoretical concepts such as modularity and entropy have provided inroads to understanding this more complex relationship between brain and behavior. This model for brain disease has important implications for normal brain-behavior relationships and the treatment of neurological and psychiatric diseases., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: The endogenous allocation of spatial attention to selected environmental stimuli is controlled by prefrontal (frontal eye fields [FEFs]) and parietal (superior parietal lobe [SPL] and intraparietal sulcus [IPS]) regions belonging to the dorsal attention network (DAN) with a subdivision in subsystems devoted to reorienting (or shifting) of attention between locations (SPL) or maintaining attention at contralateral versus ipsilateral locations (ventral IPS [vIPS]). Although previous studies suggested a leading role of prefrontal regions over parietal sites in orienting attention, the spectral signature of communication flow within the DAN for different attention processes is still debated. Methods: We used the directed transfer function (DTF) on magnetoencephalography (MEG) data to examine the causal interaction between prefrontal and parietal regions of the DAN when subjects shifted versus maintained attention to a stream of cued visual stimuli. Results: In the beta band, we found that shift versus stay cues induced stronger connectivity (DTF values) from right FEF to right SPL, in the early phase of reorienting. Conversely, when considering stay versus shift cues, an increase of DTF values and stronger directionality was observed between bilateral vIPS and from right vIPS to FEF. Similar analyses carried out in theta, alpha, and gamma showed no significant frontoparietal increases of DTF for shift versus stay cues, whereas the stay-related increase of DTF observed in beta between ventral parietal areas was preserved in the alpha band. Conclusions: These findings suggest that control processes in DAN regions (in particular between FEF and SPL) can be associated to a beta frequency channel during shift of attention. Impact statement In the present study, we compared the reorienting response to novel stimuli with respect to maintaining response. Results provided new insights into understanding the neural mechanisms of control attention processes by identifying the frequency-specific causal interactions between frontal and parietal regions belonging to the dorsal attention network supporting spatial reorienting response.

Brains at rest generate dynamical activity that is highly structured in space and time. We suggest that spontaneous activity, as in rest or dreaming, underlies top-down dynamics of generative models. During active tasks, generative models provide top-down predictive signals for perception, cognition, and action. When the brain is at rest and stimuli are weak or absent, top-down dynamics optimize the generative models for future interactions by maximizing the entropy of explanations and minimizing model complexity. Spontaneous fluctuations of correlated activity within and across brain regions may reflect transitions between 'generic priors' of the generative model: low dimensional latent variables and connectivity patterns of the most common perceptual, motor, cognitive, and interoceptive states. Even at rest, brains are proactive and predictive., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Beyond causing local ischemia and cell damage at the site of injury, stroke strongly affects long-range anatomical connections, perturbing the functional organization of brain networks. Several studies reported functional connectivity abnormalities parallelling both behavioral deficits and functional recovery across different cognitive domains. FC alterations suggest that long-range communication in the brain is altered after stroke. However, standard FC analyses cannot reveal the directionality and time scale of inter-areal information transfer. We used resting-state fMRI and covariance-based Granger causality analysis to quantify network-level information transfer and its alteration in stroke. Two main large-scale anomalies were observed in stroke patients. First, inter-hemispheric information transfer was significantly decreased with respect to healthy controls. Second, stroke caused inter-hemispheric asymmetries, as information transfer within the affected hemisphere and from the affected to the intact hemisphere was significantly reduced. Both anomalies were more prominent in resting-state networks related to attention and language, and they correlated with impaired performance in several behavioral domains. Overall, our findings support the hypothesis that stroke provokes asymmetries between the affected and spared hemisphere, with different functional consequences depending on which hemisphere is lesioned., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

The scale at which humans can handle complex social situations is massively increased compared to other animals. However, the neural substrates of this scaling remain poorly understood. In this review, we discuss how the expansion and rearrangement of the temporoparietal junction and posterior superior temporal sulcus (TPJ-pSTS) may have played a key role in the growth of human social abilities. Comparing the function and anatomy of the TPJ-pSTS in humans and macaques, which are thought to be separated by 25 million years of evolution, we find that the expansion of this region in humans has shifted the architecture of the dorsal and ventral processing streams. The TPJ-pSTS contains areas related to face-emotion processing, attention, theory of mind operations, and memory; its expansion has allowed for the elaboration and rearrangement of the cortical areas contained within, and potentially the introduction of new cortical areas. Based on the arrangement and the function of these areas in the human, we propose that the TPJ-pSTS is the basis of a third frontoparietal processing stream that underlies the increased social abilities in humans. We then describe a model of how the TPJ-pSTS areas interact as a hub that coordinates the activities of multiple brain networks in the exploration of the complex dynamic social scenes typical of the human social experience., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objective: To investigate whether different language deficits are distinguished by the relative strengths of their association with the functional connectivity (FC) at rest of the language network (LN) and cingulo-opercular network (CON) after aphasic stroke., Methods: In a group of patients with acute stroke and left-hemisphere damage, we identified 3 distinct, yet correlated, clusters of deficits including comprehension/lexical semantic, grapheme-phoneme knowledge, and verbal executive functions. We computed partial correlations in which the contributions of a behavioral cluster and network FC of no interest were statistically regressed out., Results: We observed a double dissociation such that impairment of grapheme-phoneme knowledge was more associated with lower FC of the LN within the left hemisphere than lower FC of the CON, whereas verbal executive deficits were more related to lower FC of the CON than the LN in the left hemisphere. Furthermore, the specific association between language deficits and FC was independent of the amount of structural damage to the LN and CON., Conclusion: These findings indicate that after a left-hemisphere lesion, the type of language impairment is related to the abnormal pattern of correlated activity in different networks. Accordingly, they extend the concept of a neuropsychological double dissociation from structural damage to functional network abnormalities. Finally, current results strongly argue in favor of the behavioral specificity of intrinsic brain activity after focal structural damage., (© 2018 American Academy of Neurology.)

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., (Copyright © 2018 Elsevier Inc. All rights reserved.)

The brain is a network that mediates information processing through a wide range of states. The extent of state diversity is a reflection of the entropy of the network. Here we measured the entropy of brain regions (nodes) in empirical and modeled functional networks reconstructed from resting state fMRI to address the connection of entropy at rest with the underlying structure measured through diffusion spectrum imaging. Using 18 empirical and 18 modeled stroke networks, we also investigated the effect that focal lesions have on node entropy and information diffusion. Overall, positive correlations between node entropy and structure were observed, especially between node entropy and node strength in both empirical and modeled data. Although lesions were restricted to one hemisphere in all stroke patients, entropy reduction was not only present in nodes from the damaged hemisphere, but also in nodes from the contralesioned hemisphere, an effect replicated in modeled stroke networks. Globally, information diffusion was also affected in empirical and modeled strokes compared with healthy controls. This is the first study showing that artificial lesions affect local and global network aspects in very similar ways compared with empirical strokes, shedding new light into the functional nature of stroke.

Studies of stroke have identified local reorganization in perilesional tissue. However, because the brain is highly networked, strokes also broadly alter the brain's global network organization. Here, we assess brain network structure longitudinally in adult stroke patients using resting state fMRI. The topology and boundaries of cortical regions remain grossly unchanged across recovery. In contrast, the modularity of brain systems i.e. the degree of integration within and segregation between networks, was significantly reduced sub-acutely (n = 107), but partially recovered by 3 months (n = 85), and 1 year (n = 67). Importantly, network recovery correlated with recovery from language, spatial memory, and attention deficits, but not motor or visual deficits. Finally, in-depth single subject analyses were conducted using tools for visualization of changes in brain networks over time. This exploration indicated that changes in modularity during successful recovery reflect specific alterations in the relationships between different networks. For example, in a patient with left temporo-parietal stroke and severe aphasia, sub-acute loss of modularity reflected loss of association between frontal and temporo-parietal regions bi-hemispherically across multiple modules. These long-distance connections then returned over time, paralleling aphasia recovery. This work establishes the potential importance of normalization of large-scale modular brain systems in stroke recovery., (Copyright © 2017. Published by Elsevier Ltd.)

Resting state functional MRI (R-fMRI) studies have shown that slow (<0.1Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention. The other system includes the default mode network (DMN) and the fronto-parietal control system (FPC), RSNs that instantiate episodic memory and executive control, respectively. Here, we test the hypothesis, based on the spectral specificity of electrophysiologic responses to perceptual vs. memory tasks (Klimesch, 1999; Pfurtscheller and Lopes da Silva, 1999), that these two large-scale neural systems also manifest frequency specificity in the resting state. We measured the spatial correspondence between electrocorticographic (ECoG) band-limited power (BLP) and R-fMRI correlation patterns in awake, resting, human subjects. Our results show that, while gamma BLP correspondence was common throughout the brain, theta (4-8Hz) BLP correspondence was stronger in the DMN and FPC, whereas alpha (8-12Hz) correspondence was stronger in the SMN and DAN. Thus, the human brain, at rest, exhibits frequency specific electrophysiology, respecting both the spectral structure of task responses and the hierarchical organization of RSNs., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1-2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits., (© The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Even though the eyes constantly change position, the location of a stimulus can be accurately represented by a population of neurons with retinotopic receptive fields modulated by eye position gain fields. Recent electrophysiological studies, however, indicate that eye position gain fields may serve an additional function since they have a non-uniform spatial distribution that increases the neural response to stimuli in the straight-ahead direction. We used functional magnetic resonance imaging and a wide-field stimulus display to determine whether gaze modulations in early human visual cortex enhance the blood-oxygenation-level dependent (BOLD) response to stimuli that are straight-ahead. Subjects viewed rotating polar angle wedge stimuli centered straight-ahead or vertically displaced by ± 20° eccentricity. Gaze position did not affect the topography of polar phase-angle maps, confirming that coding was retinotopic, but did affect the amplitude of the BOLD response, consistent with a gain field. In agreement with recent electrophysiological studies, BOLD responses in V1 and V2 to a wedge stimulus at a fixed retinal locus decreased when the wedge location in head-centered coordinates was farther from the straight-ahead direction. We conclude that stimulus-evoked BOLD signals are modulated by a systematic, non-uniform distribution of eye-position gain fields.

Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks.

A long-held view is that stroke causes many distinct neurological syndromes due to damage of specialized cortical and subcortical centers. However, it is unknown if a syndrome-based description is helpful in characterizing behavioral deficits across a large number of patients. We studied a large prospective sample of first-time stroke patients with heterogeneous lesions at 1-2 weeks post-stroke. We measured behavior over multiple domains and lesion anatomy with structural MRI and a probabilistic atlas of white matter pathways. Multivariate methods estimated the percentage of behavioral variance explained by structural damage. A few clusters of behavioral deficits spanning multiple functions explained neurological impairment. Stroke topography was predominantly subcortical, and disconnection of white matter tracts critically contributed to behavioral deficits and their correlation. The locus of damage explained more variance for motor and language than memory or attention deficits. Our findings highlight the need for better models of white matter damage on cognition., (Copyright © 2015 Elsevier Inc. All rights reserved.)

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.

The relationship between spontaneous brain activity and behaviour following focal injury is not well understood. Here, we report a large-scale study of resting state functional connectivity MRI and spatial neglect following stroke in a large (n=84) heterogeneous sample of first-ever stroke patients (within 1-2 weeks). Spatial neglect, which is typically more severe after right than left hemisphere injury, includes deficits of spatial attention and motor actions contralateral to the lesion, and low general attention due to impaired vigilance/arousal. Patients underwent structural and resting state functional MRI scans, and spatial neglect was measured using the Posner spatial cueing task, and Mesulam and Behavioural Inattention Test cancellation tests. A principal component analysis of the behavioural tests revealed a main factor accounting for 34% of variance that captured three correlated behavioural deficits: visual neglect of the contralesional visual field, visuomotor neglect of the contralesional field, and low overall performance. In an independent sample (21 healthy subjects), we defined 10 resting state networks consisting of 169 brain regions: visual-fovea and visual-periphery, sensory-motor, auditory, dorsal attention, ventral attention, language, fronto-parietal control, cingulo-opercular control, and default mode. We correlated the neglect factor score with the strength of resting state functional connectivity within and across the 10 resting state networks. All damaged brain voxels were removed from the functional connectivity:behaviour correlational analysis. We found that the correlated behavioural deficits summarized by the factor score were associated with correlated multi-network patterns of abnormal functional connectivity involving large swaths of cortex. Specifically, dorsal attention and sensory-motor networks showed: (i) reduced interhemispheric functional connectivity; (ii) reduced anti-correlation with fronto-parietal and default mode networks in the right hemisphere; and (iii) increased intrahemispheric connectivity with the basal ganglia. These patterns of functional connectivity:behaviour correlations were stronger in patients with right- as compared to left-hemisphere damage and were independent of lesion volume. Our findings identify large-scale changes in resting state network interactions that are a physiological signature of spatial neglect and may relate to its right hemisphere lateralization., (© The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: Recent findings associated with resting-state cortical networks have provided insight into the brain's organizational structure. In addition to their neuroscientific implications, the networks identified by resting-state functional magnetic resonance imaging (rs-fMRI) may prove useful for clinical brain mapping., Objective: To demonstrate that a data-driven approach to analyze resting-state networks (RSNs) is useful in identifying regions classically understood to be eloquent cortex as well as other functional networks., Methods: This study included 6 patients undergoing surgical treatment for intractable epilepsy and 7 patients undergoing tumor resection. rs-fMRI data were obtained before surgery and 7 canonical RSNs were identified by an artificial neural network algorithm. Of these 7, the motor and language networks were then compared with electrocortical stimulation (ECS) as the gold standard in the epilepsy patients. The sensitivity and specificity for identifying these eloquent sites were calculated at varying thresholds, which yielded receiver-operating characteristic (ROC) curves and their associated area under the curve (AUC). RSNs were plotted in the tumor patients to observe RSN distortions in altered anatomy., Results: The algorithm robustly identified all networks in all patients, including those with distorted anatomy. When all ECS-positive sites were considered for motor and language, rs-fMRI had AUCs of 0.80 and 0.64, respectively. When the ECS-positive sites were analyzed pairwise, rs-fMRI had AUCs of 0.89 and 0.76 for motor and language, respectively., Conclusion: A data-driven approach to rs-fMRI may be a new and efficient method for preoperative localization of numerous functional brain regions.

Objective: We examined whether depression and anxiety disorders in early childhood were associated with changes in resting state functional connectivity (RSFC) of the ventral attention network (VAN), and whether RSFC in the VAN was associated with alterations in attention specific to these disorders. Important clinical features of these illnesses, including changes in attention toward novel stimuli and changes in attention to stimuli of negative valence (threat/sad bias), indirectly implicate the VAN., Method: We collected resting state functional magnetic resonance imaging data in children aged 8 to 12 years. Data were volume censored to reduce artifact from submillimeter movement, resulting in analyzable data from 30 children with a history of depression and/or anxiety and 42 children with no psychiatric history. We compared pairwise RSFC among the following VAN regions: right ventro-lateral prefrontal cortex (VLPFC), right posterior superior temporal gyrus (pSTG), and right ventral supramarginal gyrus (vSMG). We also collected measures of threat bias and current clinical symptoms., Results: Children with a history of depression and/or anxiety had reduced RSFC among the regions of the VAN compared to children with no psychiatric history. The magnitude of VAN RSFC was correlated with measures of attention bias toward threat but not with current depressive, internalizing, or externalizing symptoms. No RSFC changes were detected between groups among homotopic left hemisphere regions., Conclusions: Disruption in the VAN may be an early feature of depression and anxiety disorders. VAN changes were associated with attention bias and clinical history but not with current symptoms of depression and anxiety., (Copyright © 2013 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Resting state functional magnetic resonance imaging (fMRI) has been used to study brain networks associated with both normal and pathological cognitive functions. The objective of this work is to reliably compute resting state network (RSN) topography in single participants. We trained a supervised classifier (multi-layer perceptron; MLP) to associate blood oxygen level dependent (BOLD) correlation maps corresponding to pre-defined seeds with specific RSN identities. Hard classification of maps obtained from a priori seeds was highly reliable across new participants. Interestingly, continuous estimates of RSN membership retained substantial residual error. This result is consistent with the view that RSNs are hierarchically organized, and therefore not fully separable into spatially independent components. After training on a priori seed-based maps, we propagated voxel-wise correlation maps through the MLP to produce estimates of RSN membership throughout the brain. The MLP generated RSN topography estimates in individuals consistent with previous studies, even in brain regions not represented in the training data. This method could be used in future studies to relate RSN topography to other measures of functional brain organization (e.g., task-evoked responses, stimulation mapping, and deficits associated with lesions) in individuals. The multi-layer perceptron was directly compared to two alternative voxel classification procedures, specifically, dual regression and linear discriminant analysis; the perceptron generated more spatially specific RSN maps than either alternative., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Resting state networks (RSNs) are sets of brain regions exhibiting temporally coherent activity fluctuations in the absence of imposed task structure. RSNs have been extensively studied with fMRI in the infra-slow frequency range (nominally <10(-1)Hz). The topography of fMRI RSNs reflects stationary temporal correlation over minutes. However, neuronal communication occurs on a much faster time scale, at frequencies nominally in the range of 10(0)-10(2)Hz. We examined phase-shifted interactions in the delta (2-3.5 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (13-30 Hz) frequency bands of resting-state source space MEG signals. These analyses were conducted between nodes of the dorsal attention network (DAN), one of the most robust RSNs, and between the DAN and other networks. Phase shifted interactions were mapped by the multivariate interaction measure (MIM), a measure of true interaction constructed from the maximization of imaginary coherency in the virtual channels comprised of voxel signals in source space. Non-zero-phase interactions occurred between homologous left and right hemisphere regions of the DAN in the delta and alpha frequency bands. Even stronger non-zero-phase interactions were detected between networks. Visual regions bilaterally showed phase-shifted interactions in the alpha band with regions of the DAN. Bilateral somatomotor regions interacted with DAN nodes in the beta band. These results demonstrate the existence of consistent, frequency specific phase-shifted interactions on a millisecond time scale between cortical regions within RSN as well as across RSNs., (Copyright © 2013 Elsevier Inc. All rights reserved.)

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., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

Although posterior parietal cortex (PPC) has been traditionally associated with spatial attention and sensorimotor functions, recent neuroimaging evidence has suggested the involvement of regions of left PCC (LPPC) in memory retrieval. Yet, the role of the parietal lobe in memory-related functions is still controversial. Here we investigated the causal involvement of different LPPC regions in episodic memory retrieval using repetitive transcranial magnetic stimulation (rTMS) during a task that provided both objective and subjective measures of item recognition and source memory. Stimulation sites were identified on the basis of a recent fMRI study showing the involvement of regions of the default mode network (DMN), such as the angular gyrus (AG) in the inferior parietal lobule (IPL), during search for relevant information in episodic memory, and regions of the dorsal attention network (DAN), such as the superior parietal lobule (SPL), during perceptual search. We predicted a selective disruption of memory performance following rTMS stimulation of the left AG relative to a sham condition or stimulation of the left SPL. We found a modest but significant decrease of sensitivity for item recognition when AG was directly compared to SPL, but not to sham stimulation. A stronger effect was however observed for the criterion of source memory judgments when comparing AG with both SPL and sham stimulation, suggesting that the rTMS over AG affects subjective aspects of source monitoring associated with the weighing of relevant retrieved information for source attribution., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Inferences about functional correspondences between functional networks of human and non-human primates largely rely on proximity and anatomical expansion models. However, it has been demonstrated that topologically correspondent areas in two species can have different functional properties, suggesting that anatomy-based approaches should be complemented with alternative methods to perform functional comparisons. We have recently shown that comparative analyses based on temporal correlations of sensory-driven fMRI responses can reveal functional correspondent areas in monkeys and humans without relying on spatial assumptions. Inter-species activity correlation (ISAC) analyses require the definition of seed areas in one species to reveal functional correspondences across the cortex of the same and other species. Here we propose an extension of the ISAC method that does not rely on any seed definition, hence a method void of any spatial assumption. Specifically, we apply independent component analysis (ICA) separately to monkey and human data to define species-specific networks of areas with coherent stimulus-related activity. Then, we use a hierarchical cluster analysis to identify ICA-based ISAC clusters of monkey and human networks with similar timecourses. We implemented this approach on fMRI data collected in monkeys and humans during movie watching, a condition that evokes widespread sensory-driven activity throughout large portions of the cortex. Using ICA-based ISAC, we detected seven monkey-human clusters. The timecourses of several clusters showed significant correspondences either with the motion energy in the movie or with eye-movement parameters. Five of the clusters spanned putative homologous functional networks in either primary or extrastriate visual regions, whereas two clusters included higher-level visual areas at topological locations that are not predicted by cortical surface expansion models. Overall, our ICA-based ISAC analysis complemented the findings of our previous seed-based investigations, and suggested that functional processes can be executed by brain networks in different species that are functionally but not necessarily anatomically correspondent. Overall, our method provides a novel approach to reveal evolution-driven functional changes in the primate brain with no spatial assumptions., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences., (Copyright © 2012 Elsevier Inc. All rights reserved.)

The brain is organized into a set of widely distributed networks. Therefore, although structural damage from stroke is focal, remote dysfunction can occur in regions connected to the area of lesion. Historically, neuroscience has focused on local processing due in part to the absence of tools to study the function of distributed networks. In this article we discuss how a more comprehensive understanding of the effects of stroke can be attained using resting state functional connectivity BOLD magnetic resonance imaging (resting state fcMRI). Resting state fcMRI has a number of advantages over task-evoked fMRI for studying brain network reorganization in response to stroke, including the ability to image subjects with a broad range of impairments and the ability to study multiple networks simultaneously. We describe our rationale for using resting state connectivity as a tool for investigating the neural substrates of stroke recovery in a heterogeneous population of stroke patients and discuss the main questions we hope to answer, in particular whether resting state fcMRI measures in the acute phase of stroke can predict subsequent recovery. Early results suggest that disruption of inter-hemispheric connectivity in the somatomotor network and the dorsal attention network is more strongly associated with behavioral impairment in those domains than is intra-hemispheric connectivity within either the lesioned or unaffected hemisphere. We also observe in the somatomotor network an interesting interaction between corticospinal tract damage and decreased inter-hemispheric connectivity that suggests that both processes combine to contribute to neuromotor impairment after stroke. A connectivity-based approach will provide greater insight into network reorganization in the acute and chronic phases after stroke and will contribute to improving prognostic ability and the development of therapeutic interventions., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Little is known about the brain-wide correlation of electrophysiological signals. We found that spontaneous oscillatory neuronal activity exhibited frequency-specific spatial correlation structure in the human brain. We developed an analysis approach that discounts spurious correlation of signal power caused by the limited spatial resolution of electrophysiological measures. We applied this approach to source estimates of spontaneous neuronal activity reconstructed from magnetoencephalography. Overall, correlation of power across cortical regions was strongest in the alpha to beta frequency range (8–32 Hz) and correlation patterns depended on the underlying oscillation frequency. Global hubs resided in the medial temporal lobe in the theta frequency range (4–6 Hz), in lateral parietal areas in the alpha to beta frequency range (8–23 Hz) and in sensorimotor areas for higher frequencies (32–45 Hz). Our data suggest that interactions in various large-scale cortical networks may be reflected in frequency-specific power envelope correlations.

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.

We have recently shown that interference with repetitive transcranial magnetic stimulation (rTMS) of right posterior intraparietal sulcus (IPS) cortex during the allocation of spatial attention leads to abnormal desynchronization of anticipatory (pretarget) electroencephalographic alpha rhythms (8-12 Hz) in occipital-parietal cortex and the detection of subsequently presented visual targets (Capotosto et al. 2009). Since lesion data suggest that lesions of the right frontoparietal cortices produce more severe and long-lasting deficits of visual spatial attention than lesions of the left hemisphere, here, we used the mentioned rTMS-electroencephalographic procedure to test if the control of anticipatory alpha rhythms by IPS is asymmetrically organized in the 2 hemispheres. Results showed that interference with either left or right IPS during covert spatial attention equally disrupted the normally lateralized anticipatory modulation of occipital visual cortex, with stronger alpha desynchronization contralaterally to the attended visual field. In contrast, only interference with right IPS induced a paradoxical pretarget synchronization of alpha rhythms and bilateral deficits of target identification. These results suggest that the control of spatial topography of anticipatory alpha rhythms in occipital-parietal cortex is shared between left and right IPS cortex, but that right IPS uniquely contributes to a bilateral prestimulus activation of occipital visual cortex.

Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis.

Correlations in spontaneous brain activity provide powerful access to large-scale organizational principles of the CNS. However, making inferences about cognitive processes requires a detailed understanding of the link between these couplings and the structural integrity of the CNS. We studied the impact of multiple sclerosis, which leads to the severe disintegration of the central white matter, on functional connectivity patterns in spontaneous cortical activity. Using a data driven approach based on the strength of a salient pattern of cognitive pathology, we identified distinct networks that exhibit increases in functional connectivity despite the presence of strong and diffuse reductions of the central white-matter integrity. The default mode network emerged as a core target of these connectivity modulations, showing enhanced functional coupling in bilateral inferior parietal cortex, posterior cingulate, and medial prefrontal cortex. These findings imply a complex and diverging relation of anatomical and functional connectivity in early multiple sclerosis and, thus, add an important observation for understanding how cognitive abilities and CNS integrity may be reflected in the intrinsic covariance of functional signals.

To study functional connectivity using magnetoencephalographic (MEG) data, the high-quality source-level reconstruction of brain activity constitutes a critical element. MEG resting-state networks (RSNs) have been documented by means of a dedicated processing pipeline: MEG recordings are decomposed by independent component analysis (ICA) into artifact and brain components (ICs); next, the channel maps associated with the latter ones are projected into the source space and the resulting voxel-wise weights are used to linearly combine the IC time courses. An extensive description of the proposed pipeline is provided here, along with an assessment of its performances with respect to alternative approaches. The following investigations were carried out: (1) ICA decomposition algorithm. Synthetic data are used to assess the sensitivity of the ICA results to the decomposition algorithm, by testing FastICA, INFOMAX, and SOBI. FastICA with deflation approach, a standard solution, provides the best decomposition. (2) Recombination of brain ICs versus subtraction of artifactual ICs (at the channel level). Both the recombination of the brain ICs in the sensor space and the classical procedure of subtracting the artifactual ICs from the recordings provide a suitable reconstruction, with a lower distortion using the latter approach. (3) Recombination of brain ICs after localization versus localization of artifact-corrected recordings. The brain IC recombination after source localization, as implemented in the proposed pipeline, provides a lower source-level signal distortion. (4) Detection of RSNs. The accuracy in source-level reconstruction by the proposed pipeline is confirmed by an improved specificity in the retrieval of RSNs from experimental data.

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli, respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes.

Covert attention is associated with prestimulus blood oxygenation level-dependent (BOLD) modulations in visual cortex. In some situations, this preparatory activity can predict how well human subjects will perceive upcoming visual objects. Preparatory activity may mediate this behavioral effect by affecting the stimulus-evoked response, but the relationship between preparatory and stimulus-evoked BOLD modulations is unclear. Here, we examine this relationship by comparing the effects of spatial attention on anticipatory and stimulus-evoked signals and by measuring the trial-to-trial correlation between prestimulus and poststimulus modulations. We find that in extrastriate visual cortex (V4), modulations related to spatial attention are relatively large, extend from prestimulus through the peak of the evoked response, and are slightly larger in the evoked response compared with the prestimulus response. In striate cortex (V1), the frontal eye fields (FEF), and the intraparietal sulcus (IPS), modulations related to spatial attention are relatively small, are confined primarily to the prestimulus period, and are slightly larger in preparatory versus stimulus-evoked activity. Importantly, across visual cortex, the attentional biases (activity for attended versus unattended locations) in preparatory and evoked activity are more positively correlated, trial-by-trial, than would be expected on the basis of activity measured in subjects at rest. We argue that this pattern of results suggests that the same mechanisms underlie preparatory and stimulus-evoked BOLD modulations related to spatial attention and that incoming sensory signals add to preexistent biases in preparatory activity to generate the stimulus-evoked response.

Target detection paradigms have been widely applied in the study of human cognitive functions, particularly those associated with arousal, attention, stimulus processing and memory. In EEG recordings, the detection of task-relevant stimuli elicits the P300 component, a transient response with latency around 300 ms. The P300 response has been shown to be affected by the amount of mental effort and learning, as well as habituation. Furthermore, trial-by-trial variability of the P300 component has been associated with inter-stimulus interval, target-to-target interval or target probability; however, understanding the mechanisms underlying this variability is still an open question. In order to investigate whether it could be related to the distinct cortical networks in which coherent intrinsic activity is organized, and to understand the contribution of those networks to target detection processes, we carried out a simultaneous EEG-fMRI study, collecting data from 13 healthy subjects during a visual oddball task. We identified five large-scale networks, that largely overlap with the dorsal attention, the ventral attention, the core, the visual and the sensory-motor networks. Since the P300 component has been consistently associated with target detection, we concentrated on the first two brain networks, the time-course of which showed a modulation with the P300 response as detected in simultaneous EEG recordings. A trial-by-trial EEG-fMRI correlation approach revealed that they are involved in target detection with different functional roles: the ventral attention network, dedicated to revealing salient stimuli, was transiently activated by the occurrence of targets; the dorsal attention network, usually engaged during voluntary orienting, reflected sustained activity, possibly related to search for targets.

Covertly attending to a location modulates the activity of visual areas even in the absence of visual stimulation. These effects are widespread, being found in the cortical representations of both attended and unattended portions of the visual field. It is not clear, however, whether preparatory modulations depend on subjects' expectation regarding the presence of additional nontarget stimuli in the visual field. Here, we asked subjects to endogenously direct attention to a peripheral location in the upper visual field, to identify the orientation of a low-contrast target stimulus, and we manipulated the number and behavioral relevance of other low-contrast nontarget stimuli in the visual field. Anticipatory (i.e., prestimulus) blood oxygenation level-dependent (BOLD) signal increments in visual cortex were strongest at the contralateral attended location, whereas signal decrements were strongest at the unattended mirror-opposite ipsilateral location/region of visual cortex. Importantly, these strong anticipatory decrements were not related to the presence/absence of nontarget low-contrast stimuli and did not correlate with either weaker target-evoked responses or worse performance. Second, the presence of other low-contrast stimuli in the visual field, even when potential targets, did not modify the anticipatory signal modulation either at target or nontarget locations. We conclude that the topography of spatial attention-related anticipatory BOLD signal modulation across visual cortex, specifically decrements at unattended locations, is mainly determined by processes at the cued location and not by the number or behavioral relevance of distant low-contrast nontarget stimuli elsewhere in the visual field.

Humans can use advance information to direct spatial attention before stimulus presentation and respond more accurately to stimuli at the attended location compared with unattended locations. Likewise, spatially directed attention is associated with anticipatory activity in the portion of visual cortex representing the attended location. It is unknown, however, whether and how anticipatory signals predict the locus of spatial attention and perception. Here, we show that prestimulus, preparatory activity is highly correlated across regions representing attended and unattended locations. Comparing activity representing attended versus unattended locations, rather than measuring activity for only one location, dramatically improves the accuracy with which preparatory signals predict the locus of attention, largely by removing this positive correlation common across locations. In V3A, moreover, only the difference in activity between attended and unattended locations predicts whether upcoming visual stimuli will be accurately perceived. These results suggest that the locus of attention is coded in visual cortex by an asymmetry of anticipatory activity between attended and unattended locations and that this asymmetry predicts the accuracy of perception. This coding strategy may bias activity in downstream brain regions to represent the stimulus at the attended location.

On the basis of task-related imaging studies in normal human subjects, it has been suggested that two attention systems exist in the human brain: a bilateral dorsal attention system involved in top-down orienting of attention and a right-lateralized ventral attention system involved in reorienting attention in response to salient sensory stimuli. An important question is whether this functional organization emerges only in response to external attentional demands or is represented more fundamentally in the internal dynamics of brain activity. To address this question, we examine correlations in spontaneous fluctuations of the functional MRI blood oxygen level-dependent signal in the absence of task, stimuli, or explicit attentional demands. We identify a bilateral dorsal attention system and a right-lateralized ventral attention system solely on the basis of spontaneous activity. Further, we observe regions in the prefrontal cortex correlated with both systems, a potential mechanism for mediating the functional interaction between systems. These findings demonstrate that the neuroanatomical substrates of human attention persist in the absence of external events, reflected in the correlation structure of spontaneous activity.

To examine the distribution of visual and oculomotor activity across the macaque brain, we performed functional magnetic resonance imaging (fMRI) on awake, behaving monkeys trained to perform visually guided saccades. Two subjects alternated between periods of making saccades and central fixations while blood oxygen level dependent (BOLD) images were collected [3 T, (1.5 mm)3 spatial resolution]. BOLD activations from each of four cerebral hemispheres were projected onto the subjects' cortical surfaces and aligned to a surface-based atlas for comparison across hemispheres and subjects. This surface-based analysis revealed patterns of visuo-oculomotor activity across much of the cerebral cortex, including activations in the posterior parietal cortex, superior temporal cortex and frontal lobe. For each cortical domain, we show the anatomical position and extent of visuo-oculomotor activity, including evidence that the dorsolateral frontal activation, which includes the frontal eye field (on the anterior bank of the arcuate sulcus), extends anteriorly into posterior principal sulcus (area 46) and posteriorly into part of dorsal premotor cortex (area 6). Our results also suggest that subcortical BOLD activity in the pulvinar thalamus may be lateralized during voluntary eye movements. These findings provide new neuroanatomical information as to the complex neural substrates that underlie even simple goal-directed behaviors.

This study contrasts visuospatial reorienting and response selection signals in the right temporo-parietal junction (TPJ) with functional magnetic resonance imaging. The overall goal was to investigate whether spatial orienting signals and motor signals interacted or were independent in TPJ. The right TPJ showed a greater response to targets at in-validly rather than validly cued locations, but no significant modulation from the effector used to respond. We suggest that TPJ may work as a modality-independent 'circuit breaker' for the dorsal fronto-parietal attention system, directing attention to salient events and enabling a variety of responses to those events.

The right postero-lateral cerebellum participates with the left frontal lobe in the selection and production of words. Using fMRI, we examined whether cerebellar activity switches hemispheres in parallel with recruitment of putative compensatory right homologous frontal regions in post-stroke aphasia. Re-examining the data of Blasi et al. [Blasi, V., Young, A. C., Tansy, A. P., Petersen, S. E., Snyder, A. Z., & Corbetta, M. (2002). Word retrieval learning modulates right frontal cortex in patients with left frontal damage. Neuron, 36(1), 159-170], we asked: (1) if activity in the right cerebellum was disrupted by a left frontal lesion, (2) if activity switched to the left cerebellum, and (3) if activity in the left cerebellum was modulated by learning, as was right frontal cortex. Fourteen age-matched controls and eight mildly aphasic stroke patients participated. Aphasic participants all had lesions due to unilateral left hemisphere stroke at or near Broca's area. Subjects silently performed a word stem completion task with either novel or repeated items. Activity in right cerebellum of aphasic individuals was minimal and was not modulated by learning, as for controls. However, we observed robust learning-related attenuation of the BOLD signal in the left postero-lateral cerebellum consistent with learning-related effects in right frontal cortex. These findings support the hypothesis that right frontal and left cerebellar circuits are likely to be functionally relevant to recovered/residual verbal function.

The syndrome of spatial neglect is typically associated with focal injury to the temporoparietal or ventral frontal cortex. This syndrome shows spontaneous partial recovery, but the neural basis of both spatial neglect and its recovery is largely unknown. We show that spatial attention deficits in neglect (rightward bias and reorienting) after right frontal damage correlate with abnormal activation of structurally intact dorsal and ventral parietal regions that mediate related attentional operations in the normal brain. Furthermore, recovery of these attention deficits correlates with the restoration and rebalancing of activity within these regions. These results support a model of recovery based on the re-weighting of activity within a distributed neuronal architecture, and they show that behavioral deficits depend not only on structural changes at the locus of injury, but also on physiological changes in distant but functionally related brain areas.

During performance of attention-demanding cognitive tasks, certain regions of the brain routinely increase activity, whereas others routinely decrease activity. In this study, we investigate the extent to which this task-related dichotomy is represented intrinsically in the resting human brain through examination of spontaneous fluctuations in the functional MRI blood oxygen level-dependent signal. We identify two diametrically opposed, widely distributed brain networks on the basis of both spontaneous correlations within each network and anticorrelations between networks. One network consists of regions routinely exhibiting task-related activations and the other of regions routinely exhibiting task-related deactivations. This intrinsic organization, featuring the presence of anticorrelated networks in the absence of overt task performance, provides a critical context in which to understand brain function. We suggest that both task-driven neuronal responses and behavior are reflections of this dynamic, ongoing, functional organization of the brain.

We studied the functional organization of human posterior parietal and frontal cortex using functional magnetic resonance imaging (fMRI) to map preparatory signals for attending, looking, and pointing to a peripheral visual location. The human frontal eye field and two separate regions in the intraparietal sulcus were similarly recruited in all conditions, suggesting an attentional role that generalizes across response effectors. However, the preparation of a pointing movement selectively activated a different group of regions, suggesting a stronger role in motor planning. These regions were lateralized to the left hemisphere, activated by preparation of movements of either hand, and included the inferior and superior parietal lobule, precuneus, and posterior superior temporal sulcus, plus the dorsal premotor and anterior cingulate cortex anteriorly. Surface-based registration of macaque cortical areas onto the map of fMRI responses suggests a relatively good spatial correspondence between human and macaque parietal areas. In contrast, large interspecies differences were noted in the topography of frontal areas.

The functional organization of somatosensory and motor cortex was investigated in an individual with a high cervical spinal cord injury, a 5-year absence of nearly all sensorymotor function at and below the shoulders, and rare recovery of some function in years 6-8 after intense and sustained rehabilitation therapies. We used functional magnetic resonance imaging to study brain activity to vibratory stimulation and voluntary movements of body parts above and below the lesion. No response to vibratory stimulation of the hand was observed in the primary somatosensory cortex (SI) hand area, which was conversely recruited during tongue movements that normally evoke responses only in the more lateral face area. This result suggests SI reorganization analogous to previously reported neuroplasticity changes after peripheral lesions in animals and humans. In striking contradistinction, vibratory stimulation of the foot evoked topographically appropriate responses in SI and second somatosensory cortex (SII). Motor cortex responses, tied to a visuomotor tracking task, displayed a near-typical topography, although they were more widespread in premotor regions. These findings suggest possible preservation of motor and some somatosensory cortical representations in the absence of overt movements or conscious sensations for several years after spinal cord injury and have implications for future rehabilitation and neural-repair therapies.