R. Matthew Hutchison

Dynamic functional connectivity: promise, issues, and interpretations.

The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.

Resting-State Networks Show Dynamic Functional Connectivity in Awake Humans and Anesthetized Macaques

Characterization of large‐scale brain networks using blood‐oxygenation‐level‐dependent functional magnetic resonance imaging is typically based on the assumption of network stationarity across the duration of scan. Recent studies in humans have questioned this assumption by showing that within‐network functional connectivity fluctuates on the order of seconds to minutes. Time‐varying profiles of resting‐state networks (RSNs) may relate to spontaneously shifting, electrophysiological network states and are thus mechanistically of particular importance. However, because these studies acquired data from awake subjects, the fluctuating connectivity could reflect various forms of conscious brain processing such as passive mind wandering, active monitoring, memory formation, or changes in attention and arousal during image acquisition. Here, we characterize RSN dynamics of anesthetized macaques that control for these accounts, and compare them to awake human subjects. We find that functional connectivity among nodes comprising the “oculomotor (OCM) network” strongly fluctuated over time during awake as well as anaesthetized states. For time dependent analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations that were missed when assessed with longer time windows. Similarly, the analysis identified network nodes that transiently link to the OCM network and did not emerge in average RSN analysis. Furthermore, time‐dependent analysis reliably revealed transient states of large‐scale synchronization that spanned all seeds. The results illustrate that resting‐state functional connectivity is not static and that RSNs can exhibit nonstationary, spontaneous relationships irrespective of conscious, cognitive processing. The findings imply that mechanistically important network information can be missed when using average functional connectivity as the single network measure. Hum Brain Mapp 34:2154–2177, 2013.

Functional Networks in the Anesthetized Rat Brain Revealed by Independent Component Analysis of Resting-State fMRI

The rodent brain is organized into functional networks that can be studied through examination of synchronized low-frequency spontaneous fluctuations (LFFs) of the functional magnetic resonance imaging -blood-oxygen-level-dependent (BOLD) signal. In this study, resting networks of LFFs were estimated from the whole-brain BOLD signals using independent component analysis (ICA). ICA provides a hypothesis-free technique for determining the functional connectivity map that does not require a priori selection of a seed region. Twenty Long-Evans rats were anesthetized with isoflurane (1%, n = 10) or ketamine/xylazine (50/6 mg . kg(-1) . h(-1) ip, n = 10) and imaged for 5-10 min in a 9.4 T MR scanner without experimental stimulation or task requirement. Independent, synchronous LFFs of BOLD signals were found to exist in clustered, bilaterally symmetric regions of both cortical and subcortical structures, including primary and secondary somatosensory cortices, motor cortices, visual cortices, posterior and anterior cingulate cortices, hippocampi, caudate-putamen, and thalamic and hypothalamic nuclei. The somatosensory and motor cortices typically demonstrated both symmetric and asymmetric components with unique frequency profiles. Similar independent network components were found under isoflurane and ketamine/xylazine anesthesia. The report demonstrates, for the first time, 12 independent resting networks that are bilaterally synchronous in different cortical and subcortical areas of the rat brain.

Specific Contributions of Ventromedial, Anterior Cingulate, and Lateral Prefrontal Cortex for Attentional Selection and Stimulus Valuation

Functional clusters of neurons in the monkey prefrontal and anterior cingulate cortex are involved in guiding attention to the most valuable objects in a scene.

Resting-state networks in the macaque at 7 T ☆

Assessment of brain connectivity has revealed that the structure and dynamics of large-scale network organization are altered in multiple disease states suggesting their use as diagnostic or prognostic indicators. Further investigation into the underlying mechanisms, organization, and alteration of large-scale brain networks requires a homologous animal model that would allow neurophysiological recordings and experimental manipulations. The current study presents a comprehensive assessment of macaque resting-state networks based on evaluation of intrinsic low-frequency fluctuations of the blood oxygen-level-dependent signal using group independent component analysis. Networks were found underlying multiple levels of sensory, motor, and cognitive processing. The results demonstrate that macaques share remarkable homologous network organization with humans, thereby providing strong support for their use as an animal model in the study of normal and abnormal brain connectivity as well as aiding the interpretation of electrophysiological recordings within the context of large-scale brain networks.

Monkey in the middle: why non-human primates are needed to bridge the gap in resting-state investigations

Resting-state investigations based on the evaluation of intrinsic low-frequency fluctuations of the BOLD fMRI signal have been extensively utilized to map the structure and dynamics of large-scale functional network organization in humans. In addition to increasing our knowledge of normal brain connectivity, disruptions of the spontaneous hemodynamic fluctuations have been suggested as possible diagnostic indicators of neurological and psychiatric disease states. Though the non-invasive technique has been received with much acclamation, open questions remain regarding the origin, organization, phylogenesis, as well as the basis of disease-related alterations underlying the signal patterns. Experimental work utilizing animal models, including the use of neurophysiological recordings and pharmacological manipulations, therefore, represents a critical component in the understanding and successful application of resting-state analysis, as it affords a range of experimental manipulations not possible in human subjects. In this article, we review recent rodent and non-human primate studies and based on the examination of the homologous brain architecture propose the latter to be the best-suited model for exploring these unresolved resting-state concerns. Ongoing work examining the correspondence of functional and structural connectivity, state-dependency and the neuronal correlates of the hemodynamic oscillations are discussed. We then consider the potential experiments that will allow insight into different brain states and disease-related network disruptions that can extend the clinical applications of resting-state fMRI (RS-fMRI).

Functional connectivity of the frontal eye fields in humans and macaque monkeys investigated with resting-state fMRI.

Although the frontal eye field (FEF) has been identified in macaque monkeys and humans, practical constraints related to invasiveness and task demands have limited a direct cross-species comparison of its functional connectivity. In this study, we used resting-state functional MRI data collected from both awake humans and anesthetized macaque monkeys to examine and compare the functional connectivity of the FEF. A seed region analysis revealed consistent ipsilateral functional connections of the FEF with fronto-parietal cortical areas across both species. These included the intraparietal sulcus, dorsolateral prefrontal cortex, anterior cingulate cortex, and supplementary eye fields. The analysis also revealed greater lateralization of connectivity with the FEF in both hemispheres in humans than in monkeys. Cortical surface-based transformation of connectivity maps between species further corroborated the remarkably similar organization of the FEF functional connectivity. The results support an evolutionarily preserved fronto-parietal system and provide a bridge for linking data from monkey and human studies.

Identification of Optimal Structural Connectivity Using Functional Connectivity and Neural Modeling

The complex network dynamics that arise from the interaction of the brains structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure–function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure–function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously—elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding ‘feeder’ cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

Resting-State Connectivity Identifies Distinct Functional Networks in Macaque Cingulate Cortex

Subregions of the cingulate cortex represent prominent intersections in the structural networks of the primate brain. The relevance of the cingulate to the structure and dynamics of large-scale networks ultimately requires a link to functional connectivity. Here, we map fine-grained functional connectivity across the complete extent of the macaque (Macaca fascicularis) cingulate cortex and delineate subdivisions pertaining to distinct identifiable networks. In particular, we identified 4 primary networks representing the functional spectrum of the cingulate: somatomotor, attention-orienting, executive, and limbic. The cingulate nodes of these networks originated from separable subfields along the rostral-to-caudal axis and were characterized by positive and negative correlations of spontaneous blood oxygen level-dependent activity. These findings represent a critical component for understanding how the anterior and midcingulate cortices integrate and shape information processing during task performance. The connectivity patterns also suggest future electrophysiological targets that may reveal new functional representations including those involved in conflict monitoring.