Modes and models in disorders of consciousness science

The clinical assessment of non-communicative brain damaged patients is extremely difficult and there is a need for paraclinical diagnostic markers of the level of consciousness. In the last few years, progress within neuroimaging has led to a growing body of studies investigating vegetative state and minimally conscious state patients, which can be classified in two main approaches. Active neuroimaging paradigms search for a response to command without requiring a motor response. Passive neuroimaging paradigms investigate spontaneous brain activity and brain responses to external stimuli and aim at identifying neural correlates of consciousness. Other passive paradigms eschew neuroimaging in favour of behavioural markers which reliably distinguish conscious and unconscious conditions in healthy controls. In order to furnish accurate diagnostic criteria, a mechanistic explanation of how the brain gives rise to consciousness seems desirable. Mechanistic and theoretical approaches could also ultimately lead to a unification of passive and active paradigms in a coherent diagnostic approach. In this paper, we survey current passive and active paradigms available for diagnosis of residual consciousness in vegetative state and minimally conscious patients. We then review the current main theories of consciousness and see how they can apply in this context. Finally, we discuss some avenues for future research in this domai

Task-evoked functional connectivity does not explain functional connectivity differences between rest and task conditions

During complex tasks, patterns of functional connectivity differ from those in the resting state. However, what accounts for such differences remains unclear. Brain activity during a task reflects an unknown mixture of spontaneous and task-evoked activities. The difference in functional connectivity between a task state and the resting state may reflect not only task-evoked functional connectivity, but also changes in spontaneously emerging networks. Here, we characterized the differences in apparent functional connectivity between the resting state and when human subjects were watching a naturalistic movie. Such differences were marginally explained by the task-evoked functional connectivity involved in processing the movie content. Instead, they were mostly attributable to changes in spontaneous networks driven by ongoing activity during the task. The execution of the task reduced the correlations in ongoing activity among different cortical networks, especially between the visual and non-visual sensory or motor cortices. Our results suggest that task-evoked activity is not independent from spontaneous activity, and that engaging in a task may suppress spontaneous activity and its inter-regional correlation

Neuromagnetic activation and oscillatory dynamics of stimulus-locked processing during naturalistic viewing

Naturalistic stimuli such as watching a movie while in the scanner provide an ecologically valid paradigm that has the potential of extracting valuable information on how the brain processes complex stimuli in realistic visual and auditory contexts. Naturalistic viewing is also easier to conduct with challenging participant groups including patients and children. Given the high temporal resolution of MEG, in the present study, we demonstrate how a short movie clip can be used to map distinguishable activation and connectivity dynamics underlying the processing of specific classes of visual stimuli such as face and hand manipulations, as well as contrasting activation dynamics for auditory words and non-words. MEG data were collected from 22 healthy volunteers (6 females, 3 left handed, mean age – 27.7 ± 5.28 years) during the presentation of naturalistic audiovisual stimuli. The MEG data were split into trials with the onset of the stimuli belonging to classes of interest (words, non-words, faces, hand manipulations). Based on the components of the averaged sensor ERFs time-locked to the visual and auditory stimulus onset, four and three time-windows, respectively, were defined to explore brain activation dynamics. Pseudo-Z, defined as the ratio of the source-projected time-locked power to the projected noise power for each vertex, was computed and used as a proxy of time-locked brain activation. Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation. Based on peak pseudo-Z differences between the visual conditions, time-frequency resolved analyses were performed to assess beta band desynchronization in motor-related areas, and inter-trial phase synchronization between face processing areas. Our results provide the first evidence that activation and connectivity dynamics in canonical brain regions associated with the processing of particular classes of visual and auditory stimuli can be reliably mapped using MEG during presentation of naturalistic stimuli. Given the strength of MEG for brain mapping in temporal and frequency domains, the use of naturalistic stimuli may open new techniques in analyzing brain dynamics during ecologically valid sensation and perception

Influence of meditation on anti-correlated networks in the brain

Human experiences can be broadly divided into those that are external and related to interaction with the environment, and experiences that are internal and self-related. The cerebral cortex appears to be divided into two corresponding systems: an “extrinsic” system composed of brain areas that respond more to external stimuli and tasks and an “intrinsic” system composed of brain areas that respond less to external stimuli and tasks. These two broad brain systems seem to compete with each other, such that their activity levels over time is usually anti-correlated, even when subjects are “at rest” and not performing any task. This study used meditation as an experimental manipulation to test whether this competition (anti-correlation) can be modulated by cognitive strategy. Participants either fixated without meditation (fixation), or engaged in non-dual awareness (NDA) or focused attention (FA) meditations. We computed inter-area correlations (“functional connectivity”) between pairs of brain regions within each system, and between the entire extrinsic and intrinsic systems. Anti-correlation between extrinsic vs. intrinsic systems was stronger during FA meditation and weaker during NDA meditation in comparison to fixation (without mediation). However, correlation between areas within each system did not change across conditions. These results suggest that the anti-correlation found between extrinsic and intrinsic systems is not an immutable property of brain organization and that practicing different forms of meditation can modulate this gross functional organization in profoundly different ways

Linking fast and slow: the case for generative models

A pervasive challenge in neuroscience is testing whether neuronal connectivity changes over time due to specific causes, such as stimuli, events, or clinical interventions. Recent hardware innovations and falling data storage costs enable longer, more naturalistic neuronal recordings. The implicit opportunity for understanding the self-organised brain calls for new analysis methods that link temporal scales: from the order of milliseconds over which neuronal dynamics evolve, to the order of minutes, days or even years over which experimental observations unfold. This review article demonstrates how hierarchical generative models and Bayesian inference help to characterise neuronal activity across different time scales. Crucially, these methods go beyond describing statistical associations among observations and enable inference about underlying mechanisms. We offer an overview of fundamental concepts in state-space modeling and suggest a taxonomy for these methods. Additionally, we introduce key mathematical principles that underscore a separation of temporal scales, such as the slaving principle, and review Bayesian methods that are being used to test hypotheses about the brain with multi-scale data. We hope that this review will serve as a useful primer for experimental and computational neuroscientists on the state of the art and current directions of travel in the complex systems modelling literature.Comment: 20 pages, 5 figure

Functional Organization of the Brain at Rest and During Complex Tasks Using fMRI

How and why functional connectivity (FC), which captures the correlations among brain regions and/or networks, differs in various brain states has been incompletely understood. I review high-level background on this problem and how it relates to 1) the contributions of task-evoked activity, 2) white-matter fMRI, and 3) disease states in Chapter 1. In Chapter 2, based on the notion that brain activity during a task reflects an unknown mixture of spontaneous activity and task-evoked responses, we uncovered that the difference in FC between a task state (a naturalistic movie) and resting state only marginally (3-15%) reflects task-evoked connectivity. Instead, these changes may reflect changes in spontaneously emerging networks. In Chapter 3, we were able to show subtle task-related differences in the white matter using fMRI, which has only rarely been used to study functions in this tissue type. In doing so, we also demonstrated that white matter independent components were also hierarchically organized into axonal fiber bundles, challenging the conventional practice of taking white-matter signals as noise or artifacts. Finally, in Chapter 4, we examined the utility of combining FC with task-activation studies in uncovering changes in brain activity during preclinical Alzheimer\u27s Disease (mild cognitive impairment (MCI) and subjective cognitive decline (SCD) populations), based on data collected at the Indiana University School of Medicine. We found a reduction in neural task-based activations and resting-state FC that appeared to be directly related to diagnostic severity. Taken together, the work presented in this dissertation paves the way for a novel framework for understanding neural dynamics in health and disease

Changes in Cognitive State Alter Human Functional Brain Networks

The study of the brain as a whole system can be accomplished using network theory principles. Research has shown that human functional brain networks during a resting state exhibit small-world properties and high degree nodes, or hubs, localized to brain areas consistent with the default mode network. However, the study of brain networks across different tasks and or cognitive states has been inconclusive. Research in this field is important because the underpinnings of behavioral output are inherently dependent on whether or not brain networks are dynamic. This is the first comprehensive study to evaluate multiple network metrics at a voxel-wise resolution in the human brain at both the whole-brain and regional level under various conditions: resting state, visual stimulation, and multisensory (auditory and visual stimulation). Our results show that despite global network stability, functional brain networks exhibit considerable task-induced changes in connectivity, efficiency, and community structure at the regional level

Amygdalar Functional Connectivity Differences Associated With Reduced Pain Intensity in Pediatric Peripheral Neuropathic Pain

Background: There is evidence of altered corticolimbic circuitry in adults with chronic pain, but relatively little is known of functional brain mechanisms in adolescents with neuropathic pain (NeuP). Pediatric NeuP is etiologically and phenotypically different from NeuP in adults, highlighting the need for pediatric-focused research. The amygdala is a key limbic region with important roles in the emotional-affective dimension of pain and in pain modulation. Objective: To investigate amygdalar resting state functional connectivity (rsFC) in adolescents with NeuP. Methods This cross-sectional observational cohort study compared resting state functional MRI scans in adolescents aged 11–18 years with clinical features of chronic peripheral NeuP (n = 17), recruited from a tertiary clinic, relative to healthy adolescents (n = 17). We performed seed-to-voxel whole-brain rsFC analysis of the bilateral amygdalae. Next, we performed post hoc exploratory correlations with clinical variables to further explain rsFC differences. Results: Adolescents with NeuP had stronger negative rsFC between right amygdala and right dorsolateral prefrontal cortex (dlPFC) and stronger positive rsFC between right amygdala and left angular gyrus (AG), compared to controls (PFDR<0.025). Furthermore, lower pain intensity correlated with stronger negative amygdala-dlPFC rsFC in males (r = 0.67, P = 0.034, n = 10), and with stronger positive amygdala-AG rsFC in females (r = −0.90, P = 0.006, n = 7). These amygdalar rsFC differences may thus be pain inhibitory. Conclusions: Consistent with the considerable affective and cognitive factors reported in a larger cohort, there are rsFC differences in limbic pain modulatory circuits in adolescents with NeuP. Findings also highlight the need for assessing sex-dependent brain mechanisms in future studies, where possible

fMRI reveals reciprocal inhibition between social and physical cognitive domains

Two lines of evidence indicate that there exists a reciprocal inhibitory relationship between opposed brain networks. First, most attention-demanding cognitive tasks activate a stereotypical set of brain areas, known as the task-positive network and simultaneously deactivate a different set of brain regions, commonly referred to as the task negative or defaultmode network. Second, functional connectivity analyses show that these same opposed networks are anti-correlated in the resting state. Wehypothesize that these reciprocally inhibitory effects reflect two incompatible cognitive modes, each of which may be directed towards understanding the external world. Thus, engaging onemode activates one set of regions and suppresses activity in the other.Wetest this hypothesis by identifying two types of problem-solving task which, on the basis of prior work, have been consistently associated with the task positive and task negative regions: tasks requiring social cognition, i.e., reasoning about the mental states of other persons, and tasks requiring physical cognition, i.e., reasoning about the causal/mechanical properties of inanimate objects. Social and mechanical reasoning tasks were presented to neurologically normal participants during fMRI. Each task type was presented using both text and video clips. Regardless of presentation modality, we observed clear evidence of reciprocal suppression: social tasks deactivated regions associated with mechanical reasoning and mechanical tasks deactivated regions associated with social reasoning. These findings are not explained by self-referential processes, task engagement, mental simulation,mental time travel or external vs. internal attention, all factors previously hypothesized to explain default mode network activity. Analyses of resting state data revealed a close match between the regions our tasks identified as reciprocally inhibitory and regions of maximal anti-correlation in the resting state. These results indicate the reciprocal inhibition is not attributable to constraints inherent in the tasks, but is neural in origin. Hence, there is a physiological constraint on our ability to simultaneously engage two distinct cognitive modes. Furtherwork is needed tomore precisely characterize these opposing cognitive domains