Effects of task type on spontaneous alternations of attentional states.

Mind wandering is a common occurrence that can have serious consequences, but estimating when mind wandering occurs is a challenging research question. Previous research has shown that during meditation, people may spontaneously alternate between task-oriented and mind-wandering states without awareness (Zukosky & Wang, 2021, Cognition, 212, Article 104689). However, under what conditions such alternations occur is not clear. The present study examined the effects of task type on spontaneous alternations between task focus and mind wandering. In addition to a meditation task, participants performed either a scene-categorization-based CPT or a visual detection task while attentional orientation was assessed via self-monitoring and intermittent probes. The three tasks differ in the extent of their reliance on continuous monitoring (less required in the detection than meditation and CPT tasks) and attentional orientation (oriented internally in meditation task and externally in CPT and detection tasks). To overcome prior methodological challenges, we applied a technique designed to detect spontaneous alternations between focused and mind-wandering states without awareness, based on how the proportion of "focused" responses/ratings to intermittent probes changes during a focus-to-mind-wandering interval (i.e., the period from one self-report of mind wandering to the subsequent self-report). Our results showed that the proportion of "focused" responses to intermittent probes remained constant with increasing interprobe interval during meditation (consistent with previous work), but declined significantly in the CPT and detection tasks. These findings support the hypothesis that spontaneous alternations of attentional states without self-awareness occur during tasks emphasizing internally but not externally oriented attention.

Oscillation-Based Connectivity Architecture Is Dominated by an Intrinsic Spatial Organization, Not Cognitive State or Frequency.

Functional connectivity of neural oscillations (oscillation-based FC) is thought to afford dynamic information exchange across task-relevant neural ensembles. Although oscillation-based FC is classically defined relative to a prestimulus baseline, giving rise to rapid, context-dependent changes in individual connections, studies of distributed spatial patterns show that oscillation-based FC is omnipresent, occurring even in the absence of explicit cognitive demands. Thus, the issue of whether oscillation-based FC is primarily shaped by cognitive state or is intrinsic in nature remains open. Accordingly, we sought to reconcile these observations by interrogating the ECoG recordings of 18 presurgical human patients (8 females) for state dependence of oscillation-based FC in five canonical frequency bands across an array of six task states. FC analysis of phase and amplitude coupling revealed a highly similar, largely state-invariant (i.e., intrinsic) spatial component across cognitive states. This spatial organization was shared across all frequency bands. Crucially, however, each band also exhibited temporally independent FC dynamics capable of supporting frequency-specific information exchange. In conclusion, the spatial organization of oscillation-based FC is largely stable over cognitive states (i.e., primarily intrinsic in nature) and shared across frequency bands. Together, our findings converge with previous observations of spatially invariant patterns of FC derived from extremely slow and aperiodic fluctuations in fMRI signals. Our observations indicate that "background" FC should be accounted for in conceptual frameworks of oscillation-based FC targeting task-related changes.SIGNIFICANCE STATEMENT A fundamental property of neural activity is that it is periodic, enabling functional connectivity (FC) between distant regions through coupling of their oscillations. According to task-based studies, such oscillation-based FC is rapid and malleable to meet cognitive task demands. Studying distributed FC patterns instead of FC in a few individual connections, we found that oscillation-based FC is largely stable across various cognitive states and shares a common layout across oscillation frequencies. This stable spatial organization of FC in fast oscillatory brain signals parallels the known stability of fMRI-based intrinsic FC architecture. Despite the observed spatial state and frequency invariance, FC of individual connections was temporally independent between frequency bands, suggesting a putative mechanism for malleable frequency-specific FC to support cognitive tasks.

Tangling with the Entangled Brain: Putting the Global Back into the Local.

Pessoa's precis "The Entangled Brain" is a call to action. The larger concepts resonate with existing complex systems frameworks in general and in neuroscience in particular, especially in the fields of connectomics and criticality (Cocchi, Gollo, Zalesky, & Breakspear, 2017; Bassett & Gazzaniga, 2011). What is provocative from our perspective is that despite recognizing the brain as a complex system, the experimental approaches adopted by our community largely fail to align with this recognition. In this commentary, we lay out the fundamental challenge Pessoa brings to the neuroscience community: to engage with the brain, conceptually and experimentally, as a complex whole.

Connectomics of human electrophysiology.

We present both a scientific overview and conceptual positions concerning the challenges and assets of electrophysiological measurements in the search for the nature and functions of the human connectome. We discuss how the field has been inspired by findings and approaches from functional magnetic resonance imaging (fMRI) and informed by a small number of significant multimodal empirical studies, which show that the canonical networks that are commonplace in fMRI are in fact rooted in electrophysiological processes. This review is also an opportunity to produce a brief, up-to-date critical survey of current data modalities and analytical methods available for deriving both static and dynamic connectomes from electrophysiology. We review hurdles that challenge the significance and impact of current electrophysiology connectome research. We then encourage the field to take a leap of faith and embrace the wealth of electrophysiological signals, despite their apparent, disconcerting complexity. Our position is that electrophysiology connectomics is poised to inform testable mechanistic models of information integration in hierarchical brain networks, constructed from observable oscillatory and aperiodic signal components and their polyrhythmic interactions.

Dynamic trajectories of connectome state transitions are heritable.

The brain's functional connectome is dynamic, constantly reconfiguring in an individual-specific manner. However, which characteristics of such reconfigurations are subject to genetic effects, and to what extent, is largely unknown. Here, we identified heritable dynamic features, quantified their heritability, and determined their association with cognitive phenotypes. In resting-state fMRI, we obtained multivariate features, each describing a temporal or spatial characteristic of connectome dynamics jointly over a set of connectome states. We found strong evidence for heritability of temporal features, particularly, Fractional Occupancy (FO) and Transition Probability (TP), representing the duration spent in each connectivity configuration and the frequency of shifting between configurations, respectively. These effects were robust against methodological choices of number of states and global signal regression. Genetic effects explained a substantial proportion of phenotypic variance of these features (h2=0.39, 95% CI= [.24,.54] for FO; h2=0.43, 95% CI=[.29,.57] for TP). Moreover, these temporal phenotypes were associated with cognitive performance. Contrarily, we found no robust evidence for heritability of spatial features of the dynamic states (i.e., states' Modularity and connectivity pattern). Genetic effects may therefore primarily contribute to how the connectome transitions across states, rather than the precise spatial instantiation of the states in individuals. In sum, genetic effects impact the dynamic trajectory of state transitions (captured by FO and TP), and such temporal features may act as endophenotypes for cognitive abilities.

The relationship between EEG and fMRI connectomes is reproducible across simultaneous EEG-fMRI studies from 1.5T to 7T.

Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation (fMRI) and neurophysiological recordings (EEG) are indirectly coupled. The electrophysiological and BOLD signal can map the underlying functional connectivity structure at the whole brain scale at different timescales. Previous work demonstrated a moderate but significant correlation between resting-state functional connectivity of both modalities, however there is a wide range of technical setups to measure simultaneous EEG-fMRI and the reliability of those measures between different setups remains unknown. This is true notably with respect to different magnetic field strengths (low and high field) and different spatial sampling of EEG (medium to high-density electrode coverage). Here, we investigated the reproducibility of the bimodal EEG-fMRI functional connectome in the most comprehensive resting-state simultaneous EEG-fMRI dataset compiled to date including a total of 72 subjects from four different imaging centers. Data was acquired from 1.5T, 3T and 7T scanners with simultaneously recorded EEG using 64 or 256 electrodes. We demonstrate that the whole-brain monomodal connectivity reproducibly correlates across different datasets and that a moderate crossmodal correlation between EEG and fMRI connectivity of r ≈ 0.3 can be reproducibly extracted in low- and high-field scanners. The crossmodal correlation was strongest in the EEG-ß frequency band but exists across all frequency bands. Both homotopic and within intrinsic connectivity network (ICN) connections contributed the most to the crossmodal relationship. This study confirms, using a considerably diverse range of recording setups, that simultaneous EEG-fMRI offers a consistent estimate of multimodal functional connectomes in healthy subjects that are dominantly linked through a functional core of ICNs across spanning across the different timescales measured by EEG and fMRI. This opens new avenues for estimating the dynamics of brain function and provides a better understanding of interactions between EEG and fMRI measures. This observed level of reproducibility also defines a baseline for the study of alterations of this coupling in pathological conditions and their role as potential clinical markers.

Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes.

Functional connectivity (FC), thought to provide a window into neural communication, has become a core focus in the study of brain function and cognition. However, there is no consensus on how to conceptualize large-scale FC in electrophysiology. Phase coupling (PhC), defined as coupling between the phases of two signals, reflects the synchronization of rhythmic oscillation cycles. Conversely, amplitude coupling (AmpC), defined as coupling between the envelopes of two signals, reflects correlation of activation amplitude. Despite quantifying different electrophysiological properties, the relationship between PhC and AmpC remains largely unknown. We assessed spatial and temporal correspondence between PhC and AmpC over 5 canonical frequency bands during a cue-based motor task using electrocorticography (ECoG) in 18 patients (8 females) undergoing presurgical monitoring. Significant correspondence between the spatial pattern of PhC and AmpC was detected during stimulus processing across all subjects and frequency bands (R â€‹≈ â€‹0.50 for theta, decreasing with increasing frequency). The cross-measure spatial correlation vanished almost entirely when accounting for the portion of FC equally present during pre- and post-stimulus intervals, suggesting that the spatial correlations reflect intrinsic FC independent of stimulus processing. Stimulus-related processing modulated both PhC and AmpC, however in a spatially independent manner. Examining the linear temporal correlation, we found no evidence for linear dependence between PhC and AmpC. Supporting the robustness of our findings, results extended to a verb generation task in a second ECoG dataset of 6 subjects. We conclude that PhC and AmpC reflect intrinsic FC similarly across space, but exhibit divergent stimulus-related FC changes over space and time.

Concurrent EEG- and fMRI-derived functional connectomes exhibit linked dynamics.

Long-range connectivity has become the most studied feature of human functional Magnetic Resonance Imaging (fMRI), yet the spatial and temporal relationship between its whole-brain dynamics and electrophysiological connectivity remains largely unknown. FMRI-derived functional connectivity exhibits spatial reconfigurations or time-varying dynamics at infraslow (<0.1Hz) speeds. Conversely, electrophysiological connectivity is based on cross-region coupling of fast oscillations (~1-100Hz). It is unclear whether such fast oscillation-based coupling varies at infraslow speeds, temporally coinciding with infraslow dynamics across the fMRI-based connectome. If so, does the association of fMRI-derived and electrophysiological dynamics spatially vary over the connectome across the functionally distinct electrophysiological oscillation bands? In two concurrent electroencephalography (EEG)-fMRI resting-state datasets, oscillation-based coherence in all canonical bands (delta through gamma) indeed reconfigured at infraslow speeds in tandem with fMRI-derived connectivity changes in corresponding region-pairs. Interestingly, irrespective of EEG frequency-band the cross-modal tie of connectivity dynamics comprised a large proportion of connections distributed across the entire connectome. However, there were frequency-specific differences in the relative strength of the cross-modal association. This association was strongest in visual to somatomotor connections for slower EEG-bands, and in connections involving the Default Mode Network for faster EEG-bands. Methodologically, the findings imply that neural connectivity dynamics can be reliably measured by fMRI despite heavy susceptibility to noise, and by EEG despite shortcomings of source reconstruction. Biologically, the findings provide evidence that contrast with known territories of oscillation power, oscillation coupling in all bands slowly reconfigures in a highly distributed manner across the whole-brain connectome.

Lesions to the Fronto-Parietal Network Impact Alpha-Band Phase Synchrony and Cognitive Control.

Long-range phase synchrony in the α-oscillation band (near 10 Hz) has been proposed to facilitate information integration across anatomically segregated regions. Which areas may top-down regulate such cross-regional integration is largely unknown. We previously found that the moment-to-moment strength of high-α band (10-12 Hz) phase synchrony co-varies with activity in a fronto-parietal (FP) network. This network is critical for adaptive cognitive control functions such as cognitive flexibility required during set-shifting. Using electroencephalography (EEG) in 23 patients with focal frontal lobe lesions (resected tumors), we tested the hypothesis that the FP network is necessary for modulation of high-α band phase synchrony. Global phase-synchrony was measured using an adaptation of the phase-locking value (PLV) in a sliding window procedure, which allowed for measurement of changes in EEG-based resting-state functional connectivity across time. As hypothesized, the temporal modulation (range and standard deviation) of high-α phase synchrony was reduced as a function of FP network lesion extent, mostly due to dorsolateral prefrontal cortex (dlPFC) lesions. Furthermore, patients with dlPFC lesions exhibited reduced cognitive flexibility as measured by the Trail-Making Test (set-shifting). Our findings provide evidence that the FP network is necessary for modulatory control of high-α band long-range phase synchrony, and linked to cognitive flexibility.

Overdominant Effect of a CHRNA4 Polymorphism on Cingulo-Opercular Network Activity and Cognitive Control.

The nicotinic system plays an important role in cognitive control and is implicated in several neuropsychiatric conditions. However, the contributions of genetic variability in this system to individuals' cognitive control abilities are poorly understood and the brain processes that mediate such genetic contributions remain largely unidentified. In this first large-scale neuroimaging genetics study of the human nicotinic receptor system (two cohorts, males and females, fMRI total N = 1586, behavioral total N = 3650), we investigated a common polymorphism of the high-affinity nicotinic receptor α4ß2 (rs1044396 on the CHRNA4 gene) previously implicated in behavioral and nicotine-related studies (albeit with inconsistent major/minor allele impacts). Based on our prior neuroimaging findings, we expected this polymorphism to affect neural activity in the cingulo-opercular (CO) network involved in core cognitive control processes including maintenance of alertness. Consistent across the cohorts, all cortical areas of the CO network showed higher activity in heterozygotes compared with both types of homozygotes during cognitive engagement. This inverted U-shaped relation reflects an overdominant effect; that is, allelic interaction (cumulative evidence p = 1.33 * 10-5). Furthermore, heterozygotes performed more accurately in behavioral tasks that primarily depend on sustained alertness. No effects were observed for haplotypes of the surrounding CHRNA4 region, supporting a true overdominant effect at rs1044396. As a possible mechanism, we observed that this polymorphism is an expression quantitative trait locus modulating CHRNA4 expression levels. This is the first report of overdominance in the nicotinic system. These findings connect CHRNA4 genotype, CO network activation, and sustained alertness, providing insights into how genetics shapes individuals' cognitive control abilities.SIGNIFICANCE STATEMENT The nicotinic acetylcholine system plays a central role in neuromodulatory regulation of cognitive control processes and is dysregulated in several neuropsychiatric disorders. Despite this functional importance, no large-scale neuroimaging genetics studies have targeted the contributions of genetic variability in this system to human brain activity. Here, we show the impact of a common polymorphism of the high-affinity nicotinic receptor α4ß2 that is consistent across brain activity and behavior in two large human cohorts. We report a hitherto unknown overdominant effect (allelic interaction) at this locus, where the heterozygotes show higher activity in the cingulo-opercular network underlying alertness maintenance and higher behavioral alertness performance than both homozygous groups. This gene-brain-behavior relationship informs about the biological basis of interindividual differences in cognitive control.

Ongoing dynamics in large-scale functional connectivity predict perception.

Most brain activity occurs in an ongoing manner not directly locked to external events or stimuli. Regional ongoing activity fluctuates in unison with some brain regions but not others, and the degree of long-range coupling is called functional connectivity, often measured with correlation. Strength and spatial distributions of functional connectivity dynamically change in an ongoing manner over seconds to minutes, even when the external environment is held constant. Direct evidence for any behavioral relevance of these continuous large-scale dynamics has been limited. Here, we investigated whether ongoing changes in baseline functional connectivity correlate with perception. In a continuous auditory detection task, participants perceived the target sound in roughly one-half of the trials. Very long (22-40 s) interstimulus intervals permitted investigation of baseline connectivity unaffected by preceding evoked responses. Using multivariate classification, we observed that functional connectivity before the target predicted whether it was heard or missed. Using graph theoretical measures, we characterized the difference in functional connectivity between states that lead to hits vs. misses. Before misses compared with hits and task-free rest, connectivity showed reduced modularity, a measure of integrity of modular network structure. This effect was strongest in the default mode and visual networks and caused by both reduced within-network connectivity and enhanced across-network connections before misses. The relation of behavior to prestimulus connectivity was dissociable from that of prestimulus activity amplitudes. In conclusion, moment to moment dynamic changes in baseline functional connectivity may shape subsequent behavioral performance. A highly modular network structure seems beneficial to perceptual efficiency.

Functional Characterization of the Cingulo-Opercular Network in the Maintenance of Tonic Alertness.

The complex processing architecture underlying attentional control requires delineation of the functional role of different control-related brain networks. A key component is the cingulo-opercular (CO) network composed of anterior insula/operculum, dorsal anterior cingulate cortex, and thalamus. Its function has been particularly difficult to characterize due to the network's pervasive activity and frequent co-activation with other control-related networks. We previously suggested this network to underlie intrinsically maintained tonic alertness. Here, we tested this hypothesis by separately manipulating the demand for selective attention and for tonic alertness in a two-factorial, continuous pitch discrimination paradigm. The 2 factors had independent behavioral effects. Functional imaging revealed that activity as well as functional connectivity in the CO network increased when the task required more tonic alertness. Conversely, heightened selective attention to pitch increased activity in the dorsal attention (DAT) network but not in the CO network. Across participants, performance accuracy showed dissociable correlation patterns with activity in the CO, DAT, and fronto-parietal (FP) control networks. These results support tonic alertness as a fundamental function of the CO network. They further the characterization of this function as the effortful process of maintaining cognitive faculties available for current processing requirements.

Rapid dynamics of electrophysiological connectome states are heritable.

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, are a prominent feature of brain activity with broad functional implications. While infra-slow (<0.1Hz) connectome dynamics have been extensively studied with fMRI, rapid dynamics highly relevant for cognition are poorly understood. Here, we asked whether rapid electrophysiological connectome dynamics constitute subject-specific brain traits and to what extent they are under genetic influence. Using source-localized EEG connectomes during resting-state (N=928, 473 females), we quantified heritability of multivariate (multi-state) features describing temporal or spatial characteristics of connectome dynamics. States switched rapidly every ~60-500ms. Temporal features were heritable, particularly, Fractional Occupancy (in theta, alpha, beta, and gamma bands) and Transition Probability (in theta, alpha, and gamma bands), representing the duration spent in each state and the frequency of state switches, respectively. Genetic effects explained a substantial proportion of phenotypic variance of these features: Fractional Occupancy in beta (44.3%) and gamma (39.8%) bands and Transition Probability in theta (38.4%), alpha (63.3%), beta (22.6%), and gamma (40%) bands. However, we found no evidence for heritability of spatial features, specifically states' Modularity and connectivity pattern. We conclude that genetic effects strongly shape individuals' connectome dynamics at rapid timescales, specifically states' overall occurrence and sequencing.

Cognitive abilities are associated with rapid dynamics of electrophysiological connectome states.

Time-varying changes in whole-brain connectivity patterns, or connectome state dynamics, hold significant implications for cognition. However, connectome dynamics at fast (> 1Hz) timescales highly relevant to cognition are poorly understood due to the dominance of inherently slow fMRI in connectome studies. Here, we investigated the behavioral significance of rapid electrophysiological connectome dynamics using source-localized EEG connectomes during resting-state (N=926, 473 females). We focused on dynamic connectome features pertinent to individual differences, specifically those with established heritability: Fractional Occupancy (i.e., the overall duration spent in each recurrent connectome state) in beta and gamma bands, and Transition Probability (i.e., the frequency of state switches) in theta, alpha, beta, and gamma bands. Canonical correlation analysis found a significant relationship between the heritable phenotypes of sub-second connectome dynamics and cognition. Specifically, principal components of Transition Probabilities in alpha (followed by theta and gamma bands) and a cognitive factor representing visuospatial processing (followed by verbal and auditory working memory) most notably contributed to the relationship. We conclude that the specific order in which rapid connectome states are sequenced shapes individuals' cognitive abilities and traits. Such sub-second connectome dynamics may inform about behavioral function and dysfunction and serve as endophenotypes for cognitive abilities.

A network correspondence toolbox for quantitative evaluation of novel neuroimaging results.

Decades of neuroscience research has shown that macroscale brain dynamics can be reliably decomposed into a subset of large-scale functional networks, but the specific spatial topographies of these networks and the names used to describe them can vary across studies. Such discordance has hampered interpretation and convergence of research findings across the field. To address this problem, we have developed the Network Correspondence Toolbox (NCT) to permit researchers to examine and report spatial correspondence between their novel neuroimaging results and sixteen widely used functional brain atlases, consistent with recommended reporting standards developed by the Organization for Human Brain Mapping. The atlases included in the toolbox show some topographical convergence for specific networks, such as those labeled as default or visual. Network naming varies across atlases, particularly for networks spanning frontoparietal association cortices. For this reason, quantitative comparison with multiple atlases is recommended to benchmark novel neuroimaging findings. We provide several exemplar demonstrations using the Human Connectome Project task fMRI results and UK Biobank independent component analysis maps to illustrate how researchers can use the NCT to report their own findings through quantitative evaluation against multiple published atlases. The NCT provides a convenient means for computing Dice coefficients with spin test permutations to determine the magnitude and statistical significance of correspondence among user-defined maps and existing atlas labels. The NCT also includes functionality to incorporate additional atlases in the future. The adoption of the NCT will make it easier for network neuroscience researchers to report their findings in a standardized manner, thus aiding reproducibility and facilitating comparisons between studies to produce interdisciplinary insights.

α-band phase synchrony is related to activity in the fronto-parietal adaptive control network.

Neural oscillations in the alpha band (8-12 Hz) are increasingly viewed as an active inhibitory mechanism that gates and controls sensory information processing as a function of cognitive relevance. Extending this view, phase synchronization of alpha oscillations across distant cortical regions could regulate integration of information. Here, we investigated whether such long-range cross-region coupling in the alpha band is intrinsically and selectively linked to activity in a distinct functionally specialized brain network. If so, this would provide new insight into the functional role of alpha band phase synchrony. We adapted the phase-locking value to assess fluctuations in synchrony that occur over time in ongoing activity. Concurrent EEG and functional magnetic resonance imaging (fMRI) were recorded during resting wakefulness in 26 human subjects. Fluctuations in global synchrony in the upper alpha band correlated positively with activity in several prefrontal and parietal regions (as measured by fMRI). fMRI intrinsic connectivity analysis confirmed that these regions correspond to the well known fronto-parietal (FP) network. Spectral correlations with this network's activity confirmed that no other frequency band showed equivalent results. This selective association supports an intrinsic relation between large-scale alpha phase synchrony and cognitive functions associated with the FP network. This network has been suggested to implement phasic aspects of top-down modulation such as initiation and change in moment-to-moment control. Mechanistically, long-range upper alpha band synchrony is well suited to support these functions. Complementing our previous findings that related alpha oscillation power to neural structures serving tonic control, the current findings link alpha phase synchrony to neural structures underpinning phasic control of alertness and task requirements.

Functional interactions between intrinsic brain activity and behavior.

The brain continuously maintains a remarkably high level of intrinsic activity. This activity is non-stationary and its dynamics reveal highly structured patterns across several spatial scales, from fine-grained functional architecture in sensory cortices to large-scale networks. The mechanistic function of this activity is only poorly understood. The central goal of the current review is to provide an integrated summary of recent studies on structure, dynamics and behavioral consequences of spontaneous brain activity. In light of these empirical observations we propose that the structure of ongoing activity and its itinerant nature can be understood as an indispensible memory system modeling the statistical structure of the world. We review the dynamic properties of ongoing activity, and how they are malleable over short to long temporal scales that permit adapting over a range of short- to long-term cognitive challenges. We conclude by reviewing how the functional significance of ongoing activity manifests in its impact on human action, perception, and higher cognitive function.

High density of nicotinic receptors in the cingulo-insular network.

The nicotinic system plays an important role in ordinary cognition, particularly in attention. The main nicotinic receptor in the human brain is the heteromeric α4ß2 neuronal nicotinic acetylcholine receptor (nAChR), which is distributed throughout the brain, with an especially high density in the thalamus and brainstem. Despite the important role of α4ß2 nAChRs in various physiological functions and pathological conditions, their distribution in the human cortex remains poorly characterized. We assessed the in vivo distribution of α4ß2 nAChRs in the human cortex in a group of seven non-smoking healthy subjects, using 2-[(18)F]F-A-85380 PET and a volume-of-interest-based analysis. We showed that cortical nAChR density was highest in the insular and anterior cingulate cortices. In functional magnetic resonance imaging studies, these two cortical regions and the thalamus have been shown to be highly correlated during the resting state and various tasks. Here, we also directly assessed nAChR density in this cingulo-insular network as defined in an independent dataset using resting-state functional connectivity, and compared it to other control-related networks, to the default mode network as well as to sensory and motor networks. Receptor density was significantly higher in the cingulo-insular network. This network has been suggested to maintain a variety of foundational capacities fundamental to cognitive function. The demonstration of a high nAChR density in the insular and anterior cingulate cortices reflects a particular neurochemical organization of the cingulo-insular network, and suggests an important role of the nicotinic receptors in its functions.

Controversies and progress on standardization of large-scale brain network nomenclature.

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macroscale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field toward standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including (1) network scale, resolution, and hierarchies; (2) interindividual variability of networks; (3) dynamics and nonstationarity of networks; (4) consideration of network affiliations of subcortical structures; and (5) consideration of multimodal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

Ongoing brain activity fluctuations directly account for intertrial and indirectly for intersubject variability in Stroop task performance.

Recent studies have established a relation between ongoing brain activity fluctuations and intertrial variability in evoked neural responses, perception, and motor performance. Here, we extended these investigations into the domain of cognitive control. Using functional neuroimaging and a sparse event-related design (with long and unpredictable intervals), we measured ongoing activity fluctuations and evoked responses in volunteers performing a Stroop task with color-word interference. Across trials, prestimulus activity of several regions predicted subsequent response speed and across subjects this effect scaled with the Stroop effect size, being significant only in subjects manifesting behavioral interference. These effects occurred only in task relevant as the dorsal anterior cingulate and dorsolateral prefrontal cortex as well as ventral visual areas sensitive to color and visual words. Crucially, in subjects showing a Stroop effect, reaction times were faster when prestimulus activity was higher in task-relevant (color) regions and slower when activity was higher in irrelevant (word form) regions. These findings suggest that intrinsic brain activity fluctuations modulate neural mechanisms underpinning selective voluntary attention and cognitive control. Rephrased in terms of predictive coding models, ongoing activity can hence be considered a proxy of the precision (gain) with which prediction error signals are transmitted upon sensory stimulation.