The interplay between long- and short-range temporal correlations shapes cortex dynamics across vigilance states

Increasing evidence suggests that cortical dynamics during wake exhibits long-range temporal correlations suitable to integrate inputs over extended periods of time to increase the signal-to-noise ratio in decision-making and working memory tasks. Accordingly, sleep has been suggested as a state characterized by a breakdown of long-range correlations; detailed measurements of neuronal timescales that support this view, however, have so far been lacking. Here we show that the long timescales measured at the individual neuron level in freely-behaving rats during the awake state are abrogated during non-REM (NREM) sleep. We provide evidence for the existence of two distinct states in terms of timescale dynamics in cortex: one which is characterized by long timescales which dominate during wake and REM sleep, and a second one characterized by the absence of long-range temporal correlations which characterizes NREM sleep. We observe that both timescale regimes can co-exist and, in combination, lead to an apparent gradual decline of long timescales during extended wake which is restored after sleep. Our results provide a missing link between the observed long timescales in individual neuron fluctuations during wake and the reported absence of long-term correlations during deep sleep in EEG and fMRI studies. They furthermore suggest a network-level function of sleep, to reorganize cortical networks towards states governed by slow cortex dynamics to ensure optimal function for the time awake

Attention in the Brain Under Conditions of Sub-Optimal Alertness: Neurobiological Effects and Individual Differences

Sleep deprivation (SD) is a prevalent problem in modern society, and one that can have serious adverse consequences for health and safety. Critically, even short periods of SD can lead to relatively large decrements in attention, which may in turn cause an individual to neglect important environmental stimuli. In this thesis, I report the results of three experiments designed to investigate the neural bases of attentional declines under conditions of sleep loss and mental fatigue. In two experiments using arterial spin labeled fMRI, a technique that enables the quantification of absolute levels of cerebral blood flow (CBF), it was found that CBF patterns in the resting brain differed significantly based on arousal levels (Study #1) and prior cognitive workload (Study #2). These findings are a departure from prior neuroimaging studies, which have typically taken neural activity during non-task periods as static and inseparable baseline. In a test of sustained attention, performance declines were observed both following SD (Study #1) and when performing the task for an extended period of time while well-rested (Study #2). These decrements were primarily mediated by hypoactivation in a fronto-parietal attentional circuit. Furthermore, resting baseline levels of cerebral blood flow in the thalamus and prefrontal cortex before the start of the task were predictive of interindividual differences in subsequent performance decline (Study #2). In Study #3, an experiment using standard BOLD fMRI, it was found that performance declines in a test of selective attention following SD were accompanied by reduced functional connectivity between top-down control areas and regions of ventral visual cortex, as well as reductions in activation to targets in object-selective areas. Taken together, these results further our understanding of the neural basis of attention under conditions when this system is taxed beyond its normal limits

A randomized, double-blind, placebo-controlled trial of blue wavelength light exposure on sleep and recovery of brain structure, function, and cognition following mild traumatic brain injury.

Sleep and circadian rhythms are among the most powerful but least understood contributors to cognitive performance and brain health. Here we capitalize on the circadian resetting effect of blue-wavelength light to phase shift the sleep patterns of adult patients (aged 18-48 years) recovering from mild traumatic brain injury (mTBI), with the aim of facilitating recovery of brain structure, connectivity, and cognitive performance. During a randomized, double-blind, placebo-controlled trial of 32 adults with a recent mTBI, we compared 6-weeks of daily 30-min pulses of blue light (peak lambda = 469 nm) each morning versus amber placebo light (peak lambda= 578 nm) on neurocognitive and neuroimaging outcomes, including gray matter volume (GMV), resting-state functional connectivity, directed connectivity using Granger causality, and white matter integrity using diffusion tensor imaging (DTI). Relative to placebo, morning blue light led to phase-advanced sleep timing, reduced daytime sleepiness, and improved executive functioning, and was associated with increased volume of the posterior thalamus (i.e., pulvinar), greater thalamo-cortical functional connectivity, and increased axonal integrity of these pathways. These findings provide insight into the contributions of the circadian and sleep systems in brain repair and lay the groundwork for interventions targeting the retinohypothalamic system to facilitate injury recovery.Open access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Functional connectivity of the ageing brain

This thesis investigated the impact of advancing age on modifying the functional connectivity (FC) of both typical cortical resting-state networks and subcortical structures in the human brain. Furthermore, it explored how any differences in FC may be associated with changes in sleep quality, also thought to be affected by age, and how such interactions may contribute to typical cognitive disruption associated with older age. The results suggest that older age is associated with the heterogeneous, spatially specific re-organisation of resting-state networks (RSNs), as well as indicating gender-specific spatial re-organisation. Investigation of thalamic FC revealed that older adults exhibited greater thalamo-sensory and thalamo-hippocampal FC, which was related to cognitive performance on RT and memory tasks, respectively. Investigation into participant’s sleep patterns provided evidence that sleep quality was more variable amongst the older participants. Furthermore, older adults that slept the longest each night were found to exhibit patterns of thalamic FC which were associated with better cognitive performance, than seen in older shorter sleepers. These results provide preliminary evidence that sleep may be associated with more ‘preferable’ patterns of FC in older adults which may be beneficial for cognitive function

Altered insular functional connectivity correlates to impaired vigilant attention after sleep deprivation: A resting-state functional magnetic resonance imaging study

ObjectivesThis study used resting-state functional magnetic resonance imaging (rs-fMRI) scans to assess the dominant effects of 36 h total sleep deprivation (TSD) on vigilant attention and changes in the resting-state network.Materials and methodsTwenty-two healthy college students were enrolled in this study. Participants underwent two rs-fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. We used psychomotor vigilance tasks (PVT) to measure vigilant attention. The region-of-interest to region-of-interest correlation was employed to analyze the relationship within the salience network (SN) and between other networks after 36 h of TSD. Furthermore, Pearson’s correlation analysis investigated the relationship between altered insular functional connectivity and PVT performance.ResultsAfter 36 h of TSD, participants showed significantly decreased vigilant attention. Additionally, TSD induced decreased functional connectivity between the visual and parietal regions, whereas, a significant increase was observed between the anterior cingulate cortex and insula. Moreover, changes in functional connectivity in the anterior cingulate cortex and insula showed a significant positive correlation with the response time to PVT.ConclusionOur results suggest that 36 h of TSD impaired vigilant visual attention, resulting in slower reaction times. The decrease in visual-parietal functional connectivity may be related to the decrease in the reception of information in the brain. Enhanced functional connectivity of the anterior cingulate cortex with the insula revealed that the brain network compensation occurs mainly in executive function

Identifying Network Correlates of Memory Consolidation

Neuronal spiking activity carries information about our experiences in the waking world but exactly how the brain can quickly and efficiently encode sensory information into a useful neural code and then subsequently consolidate that information into memory remains a mystery. While neuronal networks are known to play a vital role in these processes, detangling the properties of network activity from the complex spiking dynamics observed is a formidable challenge, requiring collaborations across scientific disciplines. In this work, I outline my contributions in computational modeling and data analysis toward understanding how network dynamics facilitate memory consolidation. For experimental perspective, I investigate hippocampal recordings of mice that are subjected to contextual fear conditioning and subsequently undergo sleep-dependent fear memory consolidation. First, I outline the development of a functional connectivity algorithm which rapidly and robustly assesses network structure based on neuronal spike timing. I show that the relative stability of these functional networks can be used to identify global network dynamics, revealing that an increase in functional network stability correlates with successful fear memory consolidation in vivo. Using an attractor-based model to simulate memory encoding and consolidation, I go on to show that dynamics associated with a second-order phase transition, at a critical point in phase-space, are necessary for recruiting additional neurons into network dynamics associated with memory consolidation. I show that successful consolidation subsequently shifts dynamics away from a critical point and towards sub-critical dynamics. Investigations of in vivo spiking dynamics likewise revealed that hippocampal dynamics during non-rapid-eye-movement (NREM) sleep show features of being near a critical point and that fear memory consolidation leads to a shift in dynamics. Finally, I investigate the role of NREM sleep in facilitating memory consolidation using a conductance-based model of neuronal activity that can easily switch between modes of activity loosely representing waking and NREM sleep. Analysis of model simulations revealed that oscillations associated with NREM sleep promote a phase-based coding of information; neurons with high firing rates during periods of wake lead spiking activity during NREM oscillations. I show that when phase-coding is active in both simulations and in vivo, synaptic plasticity selectively strengthens the input to neurons firing late in the oscillation while simultaneously reducing input to neurons firing early in the oscillation. The effect is a net homogenization of firing rates observed in multiple other studies, and subsequently leads to recruitment of new neurons into a memory engram and information transfer from fast firing neurons to slow firing neurons. Taken together, my work outlines important, newly-discovered features of neuronal network dynamics related to memory encoding and consolidation: networks near criticality promote recruitment of additional neurons into stable firing patterns through NREM-associated oscillations and subsequently consolidates information into memories through phase-based coding.PHDBiophysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162991/1/qmskill_1.pd

How sleep deprivation degrades task performance: combining experimental analysis with simulations of adenosinergic effects of basal ganglia and cortical circuits

Thesis (Ph.D.)--Boston UniversityHumans configure themselves into "neural machines" to perform optimally on distinct tasks, and they excel at maintaining such configurations for brief episodes. The neural configuration needed for peak performance, however, is subject to perturbations on multiple time scales. This thesis reports new empirical analyses and computational modeling to advance understanding of the variations in reaction time (RT) on simple RT tasks that are associated with the duration of the preceding inter-stimulus interval (order of seconds); the time-on-task duration (order of minutes); and sleep deprivation duration (order of hours to days). Responses from the psychomotor vigilance task (PVT), including anticipations (false alarms), normal RTs, and very long RTs (lapses in attention), were analyzed to discover the effects of: the 1 - 9 second inter-stimulus interval (ISI); the 10-minute task session; up to 50 hours of sleep deprivation (SD); and wake-promoting agents, caffeine and modafinil. Normal RTs and lapses in attention were negatively correlated with ISI length, whereas anticipations were positively correlated. Anticipations, normal RTs, and lapses increased as time-on-task increased, and during SD. Both caffeine and modafinil reduced lapses and anticipations during SD and decreased RT variability. A simple neural network model incorporating both a time-dependent inhibitory process and a time-dependent excitatory process was developed. The model robustly simulated the ISI effect on behavior. The SD effects were reproducible with two parameter adjustments. Informed modeling of drug effects required greater neurobiological detail. In the basal ganglia (BG), adenosine accumulation during SD has two notable effects: it antagonizes dopamine to reduce BG responsiveness to incoming cortical signals, and it reduces cholinergic transmission to parietal and prefrontal cortices, thus reducing attention to visual signals. A detailed computational model of interactions between BG and cortex during PVT was developed to simulate effects of adenosine and their amelioration by caffeine. The model simulates drug, ISI and SD effects on anticipations, RTs, and lapses. This model can be used to describe the effects of SD over a wide range of tasks requiring planned and reactive movements, and can predict and model effects of pharmacological agents acting on the adenosinergic, cholinergic and dopaminergic systems

DEVELOPMENT OF NEUROPHYSIOLOGICAL APPROACHES FOR MONITORING AND INTERVENING MENTAL FATIGUE

Ph.DDOCTOR OF PHILOSOPH

How Does the Body Affect the Mind? Role of Cardiorespiratory Coherence in the Spectrum of Emotions

The brain is considered to be the primary generator and regulator of emotions; however, afferent signals originating throughout the body are detected by the autonomic nervous system (ANS) and brainstem, and, in turn, can modulate emotional processes. During stress and negative emotional states, levels of cardiorespiratory coherence (CRC) decrease, and a shift occurs toward sympathetic dominance. In contrast, CRC levels increase during more positive emotional states, and a shift occurs toward parasympathetic dominance. Te dynamic changes in CRC that accompany different emotions can provide insights into how the activity of the limbic system and afferent feedback manifest as emotions. The authors propose that the brainstem and CRC are involved in important feedback mechanisms that modulate emotions and higher cortical areas. That mechanism may be one of many mechanisms that underlie the physiological and neurological changes that are experienced during pranayama and meditation and may support the use of those techniques to treat various mood disorders and reduce stress