Trial-by-trial variability in perceptual performance on identical stimuli has been related to spontaneous fluctuations in ongoing activity of intrinsic functional connectivity networks (ICNs). In a paradigm requiring sustained vigilance for instance, we previously observed that higher prestimulus activity in a cingulo-insular-thalamic network facilitated subsequent perception. Here, we test our proposed interpretation that this network underpins maintenance of tonic alertness. We used simultaneous acquisition of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) in the absence of any paradigm to test an ensuing hypothesis, namely that spontaneous fluctuations in this ICNЈs activity (as measured by fMRI) should show a positive correlation with the electrical signatures of tonic alertness (as recorded by concurrent EEG). We found in human subjects (19 male, 7 female) that activity in a network comprising dorsal anterior cingulate cortex, anterior insula, anterior prefrontal cortex and thalamus is positively correlated with global field power (GFP) of upper alpha band (10 -12 Hz) oscillations, the most consistent electrical index of tonic alertness. Conversely, and in line with earlier findings, alpha band power was negatively correlated with activity in another ICN, the so-called dorsal attention network which is most prominently involved in selective spatial attention. We propose that the cingulo-insular-thalamic network serves maintaining tonic alertness through generalized expression of cortical alpha oscillations. Attention is mediated by activity in other systems, e.g., the dorsal attention network for space, selectively disrupts alertness-related suppression and hence manifests as local attenuation of alpha activity.

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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.

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 connectivity | brain networks | dynamics | graph theory | classification T he brain is highly active in a continuous manner, and much of neural activity is not directly locked to external events or stimuli. This continuous brain activity is spatiotemporally organized into a functional connectivity architecture that comprises several large-scale networks. Large-scale networks span different cerebral lobes and include subcortical structures (1). The regions comprised in such networks commonly coactivate together in response to task demands (2), but they also show correlated and spontaneous activity fluctuations when no changes occur in the external environment. The functional connectivity architecture ensuing from these activity cofluctuations largely persists across all mental states, including various tasks, resting wakefulness, and sleep, albeit showing some degree of modulation across these states (3, 4).Strength and spatial distributions of functional connectivity within this architecture are not, however, stationary across time. At the spatial level of large-scale networks, functional connectivity shows prominent changes over the range of seconds to minutes (5). These so-called in...

Recent studies have shown that ongoing activity fluctuations influence trial-by-trial perception of identical stimuli. Some brain systems seem to bias toward better perceptual performance and others toward worse. We tested whether these observations generalize to another as of yet unassessed sensory modality, audition, and a nonspatial but memory-dependent paradigm. In a sparse event-related functional magnetic resonance imaging design, we investigated detection of auditory near-threshold stimuli as a function of prestimulus baseline activity in early auditory cortex as well as several distributed networks that were defined on the basis of resting state functional connectivity. In accord with previous studies, hits were associated with higher prestimulus activity in related early sensory cortex as well as in a system comprising anterior insula, anterior cingulate, and thalamus, which other studies have related to processing salience and maintaining task set. In contrast to previous studies, however, higher prestimulus activity in the so-called dorsal attention system of frontal and parietal cortex biased toward misses, whereas higher activity in the so-called default mode network that includes posterior cingulate and precuneus biased toward hits. These results contradict a simple dichotomic view on the function of these two latter brain systems where higher ongoing activity in the dorsal attention network would facilitate perceptual performance, and higher activity in the default mode network would deteriorate perceptual performance. Instead, we show that the way in which ongoing activity fluctuations impact on perception depends on the specific sensory (i.e., nonspatial) and cognitive (i.e., mnemonic) context that is relevant.

Neural oscillations in the α-band (8-12Hz) 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 α-oscillations across distant cortical regions could regulate integration of information. Here, we investigated whether such long-range cross-region coupling in the α-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 α-band phase-synchrony. We adapted the phase-locking value (PLV) to assess fluctuations in synchrony that occur over time in ongoing activity. Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) were recorded during resting wakefulness in 26 human subjects. Fluctuations in global synchrony in the upper α-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 α 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 α-band synchrony is well-suited to support these functions. Complementing our previous findings that related α-oscillation power to neural structures serving tonic control, the current findings link α phase-synchrony to neural structures underpinning phasic control of alertness and task requirements.

Spatial Independent Component Analysis (ICA) is an increasingly used data-driven method to analyze functional Magnetic Resonance Imaging (fMRI) data. To date, it has been used to extract sets of mutually correlated brain regions without prior information on the time course of these regions. Some of these sets of regions, interpreted as functional networks, have recently been used to provide markers of brain diseases and open the road to paradigm-free population comparisons. Such group studies raise the question of modeling subject variability within ICA: how can the patterns representative of a group be modeled and estimated via ICA for reliable inter-group comparisons? In this paper, we propose a hierarchical model for patterns in multi-subject fMRI datasets, akin to mixed-effect group models used in linear-model-based analysis. We introduce an estimation procedure, CanICA (Canonical ICA), based on i) probabilistic dimension reduction of the individual data, ii) canonical correlation analysis to identify a data subspace common to the group iii) ICA-based pattern extraction. In addition, we introduce a procedure based on cross-validation to quantify the stability of ICA patterns at the level of the group. We compare our method with state-of-the-art multi-subject fMRI ICA methods and show that the features extracted using our procedure are more reproducible at the group level on two datasets of 12 healthy controls: a resting-state and a functional localizer study.

Ongoing brain activity has been observed since the earliest neurophysiological recordings and is found over a wide range of temporal and spatial scales. It is characterized by remarkably large spontaneous modulations. Here, we review evidence for the functional role of these ongoing activity fluctuations and argue that they constitute an essential property of the neural architecture underlying cognition. The role of spontaneous activity fluctuations is probably best understood when considering both their spatiotemporal structure and their functional impact on cognition. We first briefly argue against a “segregationist” view on ongoing activity, both in time and space, which would selectively associate certain frequency bands or levels of spatial organization with specific functional roles. Instead, we emphasize the functional importance of the full range, from differentiation to integration, of intrinsic activity within a hierarchical spatiotemporal structure. We then highlight the flexibility and context-sensitivity of intrinsic functional connectivity that suggest its involvement in functionally relevant information processing. This role in information processing is pursued by reviewing how ongoing brain activity interacts with afferent and efferent information exchange of the brain with its environment. We focus on the relationship between the variability of ongoing and evoked brain activity, and review recent reports that tie ongoing brain activity fluctuations to variability in human perception and behavior. Finally, these observations are discussed within the framework of the free-energy principle which – applied to human brain function – provides a theoretical account for a non-random, coordinated interaction of ongoing and evoked activity in perception and behavior.