Large-scale Cortical Networks Research Articles

Disruption of large-scale electrophysiological networks in stroke patients with visuospatial neglect.

Stroke frequently produces attentional dysfunctions including symptoms of hemispatial neglect, which is characterized by a breakdown of awareness for the contralesional hemispace. Recent studies with functional MRI (fMRI) suggest that hemineglect patients display abnormal intra- and interhemispheric functional connectivity. However, since stroke is a vascular disorder and fMRI signals remain sensitive to nonneuronal (i.e., vascular) coupling, more direct demonstrations of neural network dysfunction in hemispatial neglect are warranted. Here, we utilize electroencephalogram (EEG) source imaging to uncover differences in resting-state network organization between patients with right hemispheric stroke (N = 15) and age-matched, healthy controls (N = 27), and determine the relationship between hemineglect symptoms and brain network organization. We estimated intra- and interregional differences in cortical communication by calculating the spectral power and amplitude envelope correlations of narrow-band EEG oscillations. We first observed focal frequency-slowing within the right posterior cortical regions, reflected in relative delta/theta power increases and alpha/beta/gamma decreases. Secondly, nodes within the right temporal and parietal cortex consistently displayed anomalous intra- and interhemispheric coupling, stronger in delta and gamma bands, and weaker in theta, alpha, and beta bands. Finally, a significant association was observed between the severity of left-hemispace search deficits (e.g., cancellation test omissions) and reduced functional connectivity within the alpha and beta bands. In sum, our novel results validate the hypothesis of large-scale cortical network disruption following stroke and reinforce the proposal that abnormal brain oscillations may be intimately involved in the pathophysiology of visuospatial neglect.

Cortical traveling waves reflect state-dependent hierarchical sequencing of local regions in the human connectome network

Recent human studies using electrocorticography have demonstrated that alpha and theta band oscillations form traveling waves on the cortical surface. According to neural synchronization theories, the cortical traveling waves may group local cortical regions and sequence them by phase synchronization; however these contributions have not yet been assessed. This study aimed to evaluate the functional contributions of traveling waves using connectome-based network modeling. In the simulation, we observed stable traveling waves on the entire cortical surface wherein the topographical pattern of these phases was substantially correlated with the empirically obtained resting-state networks, and local radial waves also appeared within the size of the empirical networks (< 50 mm). Importantly, individual regions in the entire network were instantaneously sequenced by their internal frequencies, and regions with higher intrinsic frequency were seen in the earlier phases of the traveling waves. Based on the communication-through-coherence theory, this phase configuration produced a hierarchical organization of each region by unidirectional communication between the arbitrarily paired regions. In conclusion, cortical traveling waves reflect the intrinsic frequency-dependent hierarchical sequencing of local regions, global traveling waves sequence the set of large-scale cortical networks, and local traveling waves sequence local regions within individual cortical networks.

Chapter 24 - Frontotemporal dementia: A unique window on the functional role of the temporal lobes

Frontotemporal dementia (FTD) is an umbrella term covering a plethora of progressive changes in executive functions, motor abilities, behavior, and/or language. Different clinical syndromes have been described in relation to localized atrophy, informing on the functional networks that underlie these specific cognitive, emotional, and behavioral processes. These functional declines are linked with the underlying neurodegeneration of frontal and/or temporal lobes due to diverse molecular pathologies. Initially, the accumulation of misfolded proteins targets specifically susceptible cell assemblies, leading to relatively focal neurodegeneration that later spreads throughout large-scale cortical networks. Here, we discuss the most recent clinical, neuropathological, imaging, and genetics findings in FTD-spectrum syndromes affecting the temporal lobe. We focus on the semantic variant of primary progressive aphasia and its mirror image, the right temporal variant of FTD. Incipient focal atrophy of the left anterior temporal lobe (ATL) manifests with predominant naming, word comprehension, reading, and object semantic deficits, while cases of predominantly right ATL atrophy present with impairments of socioemotional, nonverbal semantic, and person-specific knowledge. Overall, the observations in FTD allow for crucial clinical-anatomic inferences, shedding light on the role of the temporal lobes in both cognition and complex behaviors. The concerted activity of both ATLs is critical to ensure that percepts are translated into concepts, yet important hemispheric differences should be acknowledged. On one hand, the left ATL attributes meaning to linguistic, external stimuli, thus supporting goal-oriented, action-related behaviors (e.g., integrating sounds and letters into words). On the other hand, the right ATL assigns meaning to emotional, visceral stimuli, thus guiding socially relevant behaviors (e.g., integrating body sensations into feelings of familiarity).

Attention network modulation via tRNS correlates with attention gain.

Transcranial random noise stimulation (tRNS) can enhance vision in the healthy and diseased brain. Yet, the impact of multi-day tRNS on large-scale cortical networks is still unknown. We investigated the impact of tRNS coupled with behavioral training on resting-state functional connectivity and attention. We trained human subjects for 4 consecutive days on two attention tasks, while receiving tRNS over the intraparietal sulci, the middle temporal areas, or Sham stimulation. We measured resting-state functional connectivity of nodes of the dorsal and ventral attention network (DVAN) before and after training. We found a strong behavioral improvement and increased connectivity within the DVAN after parietal stimulation only. Crucially, behavioral improvement positively correlated with connectivity measures. We conclude changes in connectivity are a marker for the enduring effect of tRNS upon behavior. Our results suggest that tRNS has strong potential to augment cognitive capacity in healthy individuals and promote recovery in the neurological population.

An altered balance of integrated and segregated brain activity is a marker of cognitive deficits following sleep deprivation.

Sleep deprivation (SD) leads to impairments in cognitive function. Here, we tested the hypothesis that cognitive changes in the sleep-deprived brain can be explained by information processing within and between large-scale cortical networks. We acquired functional magnetic resonance imaging (fMRI) scans of 20 healthy volunteers during attention and executive tasks following a regular night of sleep, a night of SD, and a recovery nap containing nonrapid eye movement (NREM) sleep. Overall, SD was associated with increased cortex-wide functional integration, driven by a rise of integration within cortical networks. The ratio of within versus between network integration in the cortex increased further in the recovery nap, suggesting that prolonged wakefulness drives the cortex towards a state resembling sleep. This balance of integration and segregation in the sleep-deprived state was tightly associated with deficits in cognitive performance. This was a distinct and better marker of cognitive impairment than conventional indicators of homeostatic sleep pressure, as well as the pronounced thalamocortical connectivity changes that occurs towards falling asleep. Importantly, restoration of the balance between segregation and integration of cortical activity was also related to performance recovery after the nap, demonstrating a bidirectional effect. These results demonstrate that intra- and interindividual differences in cortical network integration and segregation during task performance may play a critical role in vulnerability to cognitive impairment in the sleep-deprived state.

A tale of two gradients: differences between the left and right hemispheres predict semantic cognition

Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.

Mental Visualization in the Cerebellum: Rapid Non-motor Learning at Sub-Lobular and Causal Network Levels.

It is generally understood that the main role of the cerebellum is in movement planning and coordination, but neuroimaging has led to striking findings of its involvement in many aspects of cognitive processing. Mental visualization is such a cognitive process, extensively involved in learning and memory, artistic and inventive creativity, etc. Here, our aim was to conduct a multidimensional study of cerebellar involvement in the non-motor cognitive tasks. First, we used fMRI to investigate whether the cognitive task of visualization from an immediate memory of complex spatial structures (line drawings) engages the cerebellum, and identified a cerebellar network of both strongly activated and suppressed regions. Second, the task-specificity of these regions was examined by comparative analysis with the task of perceptual exploration and memorization of the drawings to be later visualized from memory. BOLD response patterns over the iterations of each task differed significantly; unexpectedly, the suppression grew markedly stronger in visualization. Third, to gain insights in the organization of these regions into cerebellar networks, we determined the directed inter-regional causal influences using Granger Causal Connectivity analysis. Additionally, the causal interactions of the cerebellar networks with a large-scale cortical network, the Default Mode Network (DMN), were studied. Fourth, we investigated rapid cognitive learning in the cerebellum at the level of short-term BOLD response evolution within each region of interest, and at the higher level of network reorganization. Our paradigm of interleaved sequences of iteration between two tasks combined with some innovative analyses were instrumental in addressing these questions. In particular, rapid forms of non-motor learning that strongly drive cerebellar plasticity through mental visualization were uncovered and characterized at both sub-lobular and network levels. Collectively, these findings provide novel and expansive insights into high-order cognitive functions in the cerebellum, and its macroscale functional neuroanatomy. They represent a basis for a framework of rapid cerebellar reorganization driven by non-motor learning, with implications for the enhancement of cognitive abilities such as learning and memory.

Bridging large-scale cortical networks: Integrative and function-specific hubs in the thalamus

SummaryThe thalamus is critical for the brain's integrative hub functions; however, the localization and characterization of the different thalamic hubs remain unclear. Using a voxel-level network measure called functional connectivity overlap ratio (FCOR), we examined the thalamus' association with large-scale resting-state networks (RSNs) to elucidate its connector hub roles. Connections to the core-neurocognitive networks were localized in the anterior and medial parts, such as the anteroventral and mediodorsal nuclei areas. Regions functionally connected to the sensorimotor network were distinctively located around the lateral pulvinar nucleus but to a limited extent. Prominent connector hubs include the anteroventral, ventral lateral, and mediodorsal nuclei with functional connections to multiple RSNs. These findings suggest that the thalamus, with extensive connections to most of the RSNs, is well placed as a critical integrative functional hub and could play an important role for functional integration facilitating brain functions associated with primary processing and higher cognition.

Atypicalities in the developmental trajectory of cortico-striatal functional connectivity in autism spectrum disorder.

Autism spectrum disorder has long been conceptualized as a disorder of "atypical development of functional brain connectivity (which refers to correlations in activity levels of distant brain regions)." However, most of the research has focused on the connectivity between cortical regions, and much remains unknown about the developmental changes of functional connectivity between subcortical and cortical areas in autism spectrum disorder. We used the technique of resting-state functional magnetic resonance imaging to explore the developmental characteristics of intrinsic functional connectivity (functional brain connectivity when people are asked not to do anything) between subcortical and cortical regions in individuals with and without autism spectrum disorder aged 6-30 years. We focused on one important subcortical structure called striatum, which has roles in motor, cognitive, and affective processes. We found that cortico-striatal intrinsic functional connectivities showed opposite developmental trajectories in autism spectrum disorder and typically developing individuals, with connectivity increasing with age in autism spectrum disorder and decreasing or constant in typically developing individuals. We also found significant negative behavioral correlations between those atypical cortico-striatal intrinsic functional connectivities and autistic symptoms, such as social-communication deficits, and restricted/repetitive behaviors and interests. Taken together, this work highlights that the atypical development of cortico-subcortical functional connectivity might be largely involved in the neuropathological mechanisms of autism spectrum disorder.

VTA and Anterior Hippocampus Target Dissociable Neocortical Networks for Post-Novelty Enhancements.

The detection of novelty indicates changes in the environment and the need to update existing representations. In response to novelty, interactions across the VTA-hippocampal circuit support experience-dependent plasticity in the hippocampus. While theories have broadly suggested plasticity-related changes are also instantiated in the cortex, research has also shown evidence for functional heterogeneity in cortical networks. It therefore remains unclear how the hippocampal-VTA circuit engages cortical networks, and whether novelty targets specific cortical regions or diffuse, large-scale cortical networks. To adjudicate the role of the VTA and hippocampus in cortical network plasticity, we used fMRI to compare resting-state functional coupling before and following exposure to novel scene images in human subjects of both sexes. Functional coupling between right anterior hippocampus and VTA was enhanced following novelty exposure. However, we also found evidence for a double dissociation, with anterior hippocampus and VTA showing distinct patterns of post-novelty functional coupling enhancements, targeting task-relevant regions versus large-scale networks, respectively. Further, significant correlations between these networks and the novelty-related plasticity in the anterior hippocampal-VTA functional network suggest that the central hippocampal-VTA network may facilitate the interactions with the cortex. These findings support an extended model of novelty-induced plasticity, in which novelty elicits plasticity-related changes in both local and global cortical networks.SIGNIFICANCE STATEMENT Novelty detection is critical for adaptive behavior, signaling the need to update existing representations. By engaging the bidirectional hippocampal-VTA circuit, novelty has been shown to induce plasticity-related changes in the hippocampus. However, it remains an open question how novelty targets such plasticity-related changes in cortical networks. We show that anterior hippocampus and VTA target cortical networks at different spatial scales, with respective enhancements in post-novelty functional coupling with a task-relevant cortical region and a large-scale memory network. The results presented here support an extended model of novelty-related plasticity, in which engaging the anterior hippocampal-VTA circuit through novelty exposure propagates cortical plasticity through hippocampal and VTA functional pathways at distinct scales, targeting specific or diffuse cortical networks.

Spatiospectral brain networks reflective of improvisational experience

Musical improvisers are trained to categorize certain musical structures into functional classes, which is thought to facilitate improvisation. Using a novel auditory oddball paradigm (Goldman et al., 2020) which enables us to disassociate a deviant (i.e. musical chord inversion) from a consistent functional class, we recorded scalp EEG from a group of musicians who spanned a range of improvisational and classically trained experience. Using a spatiospectral based inter and intra network connectivity analysis, we found that improvisers showed a variety of differences in connectivity within and between large-scale cortical networks compared to classically trained musicians, as a function of deviant type. Inter-network connectivity in the alpha band, for a time window leading up to the behavioural response, was strongly linked to improvisation experience, with the default mode network acting as a hub. Spatiospectral networks post response were substantially different between improvisers and classically trained musicians, with greater inter-network connectivity (specific to the alpha and beta bands) seen in improvisers whereas those with more classical training had largely reduced inter-network activity (mostly in the gamma band). More generally, we interpret our findings in the context of network-level correlates of expectation violation as a function of subject expertise, and we discuss how these may generalize to other and more ecologically valid scenarios.

Dynamic Network Analysis Demonstrates the Formation of Stable Functional Networks During Rule Learning.

Variations in the functional connectivity of large-scale cortical brain networks may explain individual differences in learning ability. We used a dynamic network analysis of fMRI data to identify changes in functional brain networks that are associated with context-dependent rule learning. During fMRI scanning, naïve subjects performed a cognitive task designed to test their ability to learn context-dependent rules. Notably, subjects were given minimal instructions about the task prior to scanning. We identified several key network characteristics associated with fast and accurate rule learning. First, consistent with the formation of stable functional networks, a dynamic community detection analysis revealed regionally specific reductions in flexible switching between different functional communities in successful learners. Second, successful rule learners showed decreased centrality of ventral attention regions and increased assortative mixing of cognitive control regions as the rules were learned. Finally, successful subjects showed greater decoupling of default and attention communities throughout the entire task, whereas ventral attention and cognitive control regions became more connected during learning. Overall, the results support a framework by which a stable ventral attention community and more flexible cognitive control community support sustained attention and the formation of rule representations in successful learners.

Circuit mechanisms for the chemical modulation of cortex-wide network interactions and behavioral variability.

Influential theories postulate distinct roles of catecholamines and acetylcholine in cognition and behavior. However, previous physiological work reported similar effects of these neuromodulators on the response properties (specifically, the gain) of individual cortical neurons. Here, we show a double dissociation between the effects of catecholamines and acetylcholine at the level of large-scale interactions between cortical areas in humans. A pharmacological boost of catecholamine levels increased cortex-wide interactions during a visual task, but not rest. An acetylcholine boost decreased interactions during rest, but not task. Cortical circuit modeling explained this dissociation by differential changes in two circuit properties: the local excitation-inhibition balance (more strongly increased by catecholamines) and intracortical transmission (more strongly reduced by acetylcholine). The inferred catecholaminergic mechanism also predicted noisier decision-making, which we confirmed for both perceptual and value-based choice behavior. Our work highlights specific circuit mechanisms for shaping cortical network interactions and behavioral variability by key neuromodulatory systems.

Group-level cortical functional connectivity patterns using fNIRS: assessing the effect of bilingualism in young infants.

.Significance: Early monolingual versus bilingual experience induces adaptations in the development of linguistic and cognitive processes, and it modulates functional activation patterns during the first months of life. Resting-state functional connectivity (RSFC) is a convenient approach to study the functional organization of the infant brain. RSFC can be measured in infants during natural sleep, and it allows to simultaneously investigate various functional systems. Adaptations have been observed in RSFC due to a lifelong bilingual experience. Investigating whether bilingualism-induced adaptations in RSFC begin to emerge early in development has important implications for our understanding of how the infant brain’s organization can be shaped by early environmental factors.Aims: We attempt to describe RSFC using functional near-infrared spectroscopy (fNIRS) and to examine whether it adapts to early monolingual versus bilingual environments. We also present an fNIRS data preprocessing and analysis pipeline that can be used to reliably characterize RSFC in development and to reduce false positives and flawed results interpretations.Methods: We measured spontaneous hemodynamic brain activity in a large cohort () of 4-month-old monolingual and bilingual infants using fNIRS. We implemented group-level approaches based on independent component analysis to examine RSFC, while providing proper control for physiological confounds and multiple comparisons.Results: At the group level, we describe the functional organization of the 4-month-old infant brain in large-scale cortical networks. Unbiased group-level comparisons revealed no differences in RSFC between monolingual and bilingual infants at this age.Conclusions: High-quality fNIRS data provide a means to reliably describe RSFC patterns in the infant brain. The proposed group-level RSFC analyses allow to assess differences in RSFC across experimental conditions. An effect of early bilingual experience in RSFC was not observed, suggesting that adaptations might only emerge during explicit linguistic tasks, or at a later point in development.

Association between metabolic syndrome and resting-state functional brain connectivity

The objective of this study is to examine whether metabolic syndrome (MetS), the clustering of 3 or more cardiovascular risk factors, disrupts the resting-state functional connectivity (FC) of the large-scale cortical brain networks. Resting-state functional magnetic resonance imaging data were collected from seventy-eight middle-aged and older adults living with and without MetS (27 MetS; 51 non-MetS). FC maps were derived from the time series of intrinsic activity in the large-scale brain networks by correlating the spatially averaged time series with all brain voxels using a whole-brain seed-based FC approach. Participants with MetS showed hyperconnectivity across the core brain regions with evidence of loss of modularity when compared with non-MetS individuals. Furthermore, patterns of higher between-network MetS-related effects were observed across most of the seed regions in both right and left hemispheres. These findings indicate that MetS is associated with altered intrinsic communication across core neural networks and disrupted between-network connections across the brain due to the co-occurring vascular risk factors in MetS.

Real time and delayed effects of subcortical low intensity focused ultrasound

Deep brain nuclei are integral components of large-scale circuits mediating important cognitive and sensorimotor functions. However, because they fall outside the domain of conventional non-invasive neuromodulatory techniques, their study has been primarily based on neuropsychological models, limiting the ability to fully characterize their role and to develop interventions in cases where they are damaged. To address this gap, we used the emerging technology of non-invasive low-intensity focused ultrasound (LIFU) to directly modulate left lateralized basal ganglia structures in healthy volunteers. During sonication, we observed local and distal decreases in blood oxygenation level dependent (BOLD) signal in the targeted left globus pallidus (GP) and in large-scale cortical networks. We also observed a generalized decrease in relative perfusion throughout the cerebrum following sonication. These results show, for the first time using functional MRI data, the ability to modulate deep-brain nuclei using LIFU while measuring its local and global consequences, opening the door for future applications of subcortical LIFU.

Intraoperative Brain Mapping by Cortico-Cortical Evoked Potential.

To preserve postoperative brain function, it is important for neurosurgeons to fully understand the brain's structure, vasculature, and function. Intraoperative high-frequency electrical stimulation during awake craniotomy is the gold standard for mapping the function of the cortices and white matter; however, this method can only map the “focal” functions and cannot monitor large-scale cortical networks in real-time. Recently, an in vivo electrophysiological method using cortico-cortical evoked potentials (CCEPs) induced by single-pulse electrical cortical stimulation has been developed in an extraoperative setting. By using the CCEP connectivity pattern intraoperatively, mapping and real-time monitoring of the dorsal language pathway is available. This intraoperative CCEP method also allows for mapping of the frontal aslant tract, another language pathway, and detection of connectivity between the primary and supplementary motor areas in the frontal lobe network. Intraoperative CCEP mapping has also demonstrated connectivity between the frontal and temporal lobes, likely via the ventral language pathway. Establishing intraoperative electrophysiological monitoring is clinically useful for preserving brain function, even under general anesthesia. This CCEP technique demonstrates potential clinical applications for mapping and monitoring large-scale cortical networks.

Infrared neural stimulation with 7T fMRI: A rapid in vivo method for mapping cortical connections of primate amygdala

We have previously shown that INS-fMRI is a rapid method for mapping mesoscale brain networks in the macaque monkey brain. Focal stimulation of single cortical sites led to the activation of connected cortical locations, resulting in a global connectivity map. Here, we have extended this method for mapping brainwide networks following stimulation of single subcortical sites. As a testbed, we focused on the basal nucleus of the amygdala in the macaque monkey. We describe methods to target basal nucleus locations with submillimeter precision, pulse train stimulation methods, and statistical tests for assessing non-random nature of activations. Using these methods, we report that stimulation of precisely targeted loci in the basal nucleus produced sparse and specific activations in the brain. Activations were observed in the insular and sensory association cortices as well as activations in the cingulate cortex, consistent with known anatomical connections. What is new here is that the activations were focal and, in some cases, exhibited shifting topography with millimeter shifts in stimulation site. The precision of the method enables networks mapped from different nearby sites in the basal nucleus to be distinguished. While further investigation is needed to improve the sensitivity of this method, our analyses do support the reproducibility and non-random nature of some of the activations. We suggest that INS-fMRI is a promising method for mapping large-scale cortical and subcortical networks at high spatial resolution.

Nucleus Accumbens Stimulation Modulates Inhibitory Control by Right Prefrontal Cortex Activation in Obsessive-Compulsive Disorder.

Inhibitory control is considered a compromised cognitive function in obsessive-compulsive (OCD) patients and likely linked to corticostriatal circuitry disturbances. Here, 9 refractory OCD patients treated with deep brain stimulation (DBS) were evaluated to address the dynamic modulations of large-scale cortical network activity involved in inhibitory control after nucleus accumbens (NAc) stimulation and their relationship with cortical thickness. A comparison of DBS "On/Off" states showed that patients committed fewer errors and exhibited increased intraindividual reaction time variability, resulting in improved goal maintenance abilities and proactive inhibitory control. Visual P3 event-related potentials showed increased amplitudes during Go/NoGo performance. Go and NoGo responses increased cortical activation mainly over the right inferior frontal gyrus and medial frontal gyrus, respectively. Moreover, increased cortical activation in these areas was equally associated with a higher cortical thickness within the prefrontal cortex. These results highlight the critical role of NAc DBS for preferentially modulating the neuronal activity underlying sustained speed responses and inhibitory control in OCD patients and show that it is triggered by reorganizing brain functions to the right prefrontal regions, which may depend on the underlying cortical thinning. Our findings provide updated structural and functional evidence that supports critical dopaminergic-mediated frontal-striatal network interactions in OCD.

Cortical gradients of functional connectivity are robust to state-dependent changes following sleep deprivation

Sleep deprivation leads to significant impairments in cognitive performance and changes to the interactions between large scale cortical networks, yet the hierarchical organization of cortical activity across states is still being explored. We used functional magnetic resonance imaging to assess activations and connectivity during cognitive tasks in 20 healthy young adults, during three states: (i) following a normal night of sleep, (ii) following 24hr of total sleep deprivation, and (iii) after a morning recovery nap. Situating cortical activity during cognitive tasks along hierarchical organizing gradients based upon similarity of functional connectivity patterns, we found that regional variations in task-activations were captured by an axis differentiating areas involved in executive control from default mode regions and paralimbic cortex. After global signal regression, the range of functional differentiation along this axis at baseline was significantly related to decline in working memory performance (2-back task) following sleep deprivation, as well as the extent of recovery in performance following a nap. The relative positions of cortical regions within gradients did not significantly change across states, except for a lesser differentiation of the visual system and increased coupling of the posterior cingulate cortex with executive control areas after sleep deprivation. This was despite a widespread increase in the magnitude of functional connectivity across the cortex following sleep deprivation. Cortical gradients of functional differentiation thus appear relatively insensitive to state-dependent changes following sleep deprivation and recovery, suggesting that there are no large-scale changes in cortical functional organization across vigilance states. Certain features of particular gradient axes may be informative for the extent of decline in performance on more complex tasks following sleep deprivation, and could be beneficial over traditional voxel- or parcel-based approaches in identifying realtionships between state-dependent brain activity and behavior.