Development of top-down cortical propagations in youth

Hierarchical processing requires activity propagating between higher- and lower-order cortical areas. However, functional neuroimaging studies have chiefly quantified fluctuations within regions over time rather than propagations occurring over space. Here, we leverage advances in neuroimaging and computer vision to track cortical activity propagations in a large sample of youth (n = 388). We delineate cortical propagations that systematically ascend and descend a cortical hierarchy in all individuals in our developmental cohort, as well as in an independent dataset of densely sampled adults. Further, we demonstrate that top-down, descending hierarchical propagations become more prevalent with greater demands for cognitive control as well as with development in youth. These findings emphasize that hierarchical processing is reflected in the directionality of propagating cortical activity and suggest top-down propagations as a potential mechanism of neurocognitive maturation in youth.

Cortico-autonomic local arousals and heightened somatosensory arousability during NREMS of mice in neuropathic pain

Frequent nightly arousals typical for sleep disorders cause daytime fatigue and present health risks. As such arousals are often short, partial, or occur locally within the brain, reliable characterization in rodent models of sleep disorders and in human patients is challenging. We found that the EEG spectral composition of non-rapid eye movement sleep (NREMS) in healthy mice shows an infraslow (~50 s) interval over which microarousals appear preferentially. NREMS could hence be vulnerable to abnormal arousals on this time scale. Chronic pain is well-known to disrupt sleep. In the spared nerve injury (SNI) mouse model of chronic neuropathic pain, we found more numerous local cortical arousals accompanied by heart rate increases in hindlimb primary somatosensory, but not in prelimbic, cortices, although sleep macroarchitecture appeared unaltered. Closed-loop mechanovibrational stimulation further revealed higher sensory arousability. Chronic pain thus preserved conventional sleep measures but resulted in elevated spontaneous and evoked arousability. We develop a novel moment-to-moment probing of NREMS vulnerability and propose that chronic pain-induced sleep complaints arise from perturbed arousability.

Revisiting Functional Connectivity for Infraslow Scale-Free Brain Dynamics Using Complex Wavelets

The analysis of human brain functional networks is achieved by computing functional connectivity indices reflecting phase coupling and interactions between remote brain regions. In magneto- and electroencephalography, the most frequently used functional connectivity indices are constructed based on Fourier-based cross-spectral estimation applied to specific fast and band-limited oscillatory regimes. Recently, infraslow arrhythmic fluctuations (below the 1 Hz) were recognized as playing a leading role in spontaneous brain activity. The present work aims to propose to assess functional connectivity from fractal dynamics, thus extending the assessment of functional connectivity to the infraslow arrhythmic or scale-free temporal dynamics of M/EEG-quantified brain activity. Instead of being based on Fourier analysis, new Imaginary Coherence and weighted Phase Lag indices are constructed from complex-wavelet representations. Their performances are first assessed on synthetic data by means of Monte-Carlo simulations, and they are then compared favorably against the classical Fourier-based indices. These new assessments of functional connectivity indices are also applied to MEG data collected on 36 individuals both at rest and during the learning of a visual motion discrimination task. They demonstrate a higher statistical sensitivity, compared to their Fourier counterparts, in capturing significant and relevant functional interactions in the infraslow regime and modulations from rest to task. Notably, the consistent overall increase in functional connectivity assessed from fractal dynamics from rest to task correlated with a change in temporal dynamics as well as with improved performance in task completion, which suggests that the complex-wavelet weighted Phase Lag index is the sole index is able to capture brain plasticity in the infraslow scale-free regime.

Infraslow coordination of slow wave activity through altered neuronal synchrony

Slow wave activity (SWA; the EEG power between 0.5 and 4 Hz during non-rapid eye movement sleep [NREM]) is the best electrophysiological marker of sleep need; SWA dissipates across the night and increases following sleep deprivation. In addition to these well-documented homeostatic SWA trends, SWA exhibits extensive variability across shorter timescales (seconds to minutes) and between local cortical regions. The physiological underpinnings of SWA variability, however, remain poorly characterized. In male Sprague-Dawley rats, we observed that SWA exhibits pronounced infraslow fluctuations (~40- to 120-s periods) that are coordinated across disparate cortical locations. Peaks in SWA across infraslow cycles were associated with increased slope, amplitude, and duration of individual slow waves and a reduction in the total number of waves and proportion of multipeak waves. Using a freely available data set comprised of extracellular unit recordings during consolidated NREM episodes in male Long-Evans rats, we further show that infraslow SWA does not appear to arise as a consequence of firing rate modulation of putative excitatory or inhibitory neurons. Instead, infraslow SWA was associated with alterations in neuronal synchrony surrounding "On"/"Off" periods and changes in the number and duration of "Off" periods. Collectively, these data provide a mechanism by which SWA can be coordinated across disparate cortical locations and thereby connect local and global expression of this patterned neuronal activity. In doing so, infraslow SWA may contribute to the regulation of cortical circuits during sleep and thereby play a critical role in sleep function.

Cognitive and Physiologic Impacts of the Infraslow Oscillation

Brain states are traditionally recognized via sleep-wake cycles, but modern neuroscience is beginning to identify many sub-states within these larger arousal types. Multiple lines of converging evidence now point to the infraslow oscillation (ISO) as a mediator of brain sub-states, with impacts ranging from the creation of resting state networks (RSNs) in awake subjects to interruptions in neural activity during sleep. This review will explore first the basic characteristics of the ISO in human subjects before reviewing findings in sleep and in animals. Networks of consistently correlated brain regions known as RSNs seen in human functional neuroimaging studies oscillate together at infraslow frequencies. The infraslow rhythm subdivides nonREM in a manner that may correlate with plasticity. The mechanism of this oscillation may be found in the thalamus and may ultimately come from glial cells. Finally, I review the functional impacts of ISOs on brain phenomena ranging from higher frequency oscillations, to brain networks, to information representation and cognitive performance. ISOs represent a relatively understudied phenomenon with wide effects on the brain and behavior.

Seizure susceptibility and infraslow modulatory activity in the intracranial electroencephalogram

OBJECTIVE

Studies of infraslow amplitude modulations (<0.15 Hz) of band power time series suggest that these envelope correlations may form a basis for distant spatial coupling in the brain. In this study, we sought to determine how infraslow relationships are affected by antiepileptic drug (AED) taper, time of day, and seizure.

METHODS

We studied intracranial electroencephalographic (icEEG) data collected from 13 medically refractory adult epilepsy patients who underwent monitoring at Yale-New Haven Hospital. We estimated the magnitude-squared coherence (MSC) at <0.15 Hz of traditional EEG frequency band power time series for all electrode contact pairs to quantify infraslow envelope correlations between them. We studied, first, hour-long background icEEG epochs before and after AED taper to understand the effect of taper. Second, we analyzed the entire record for each patient to study the effect of time of day. Finally, for each patient, we reviewed the clinical record to find all seizures that were at least 6 hours removed from other seizures and analyzed infraslow envelope MSC before and after them.

RESULTS

Infraslow envelope MSC increased slightly, but significantly, after AED taper, and increased on average during the night and decreased during the day. It was also increased significantly in all frequency bands up to 3 hours preseizure and 1 hour postseizure as compared to background icEEG (61 seizures studied). These changes occurred for both daytime and nighttime seizures (28 daytime, 33 nighttime). Interestingly, there was significant spatial variability to these changes, with the seizure onset area peaking at 3 hours preseizure, then showing progressive desynchronization from 3 hours preseizure to 1 hour postseizure.

SIGNIFICANCE

Infraslow envelope analysis may be used to understand long-term changes over the course of icEEG monitoring, provide unique insight into interictal electrophysiological changes related to ictogenesis, and contribute to the development of novel seizure forecasting algorithms.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Low Activity Microstates During Sleep

Study Objectives:

To better understand the distinct activity patterns of the brain during sleep, we observed and investigated periods of diminished oscillatory and population spiking activity lasting for seconds during non-rapid eye movement (non-REM) sleep, which we call “LOW” activity sleep.

Methods:

We analyzed spiking and local field potential (LFP) activity of hippocampal CA1 region alongside neocortical electroencephalogram (EEG) and electromyogram (EMG) in 19 sessions from four male Long-Evans rats (260–360 g) during natural wake/sleep across the 24-hr cycle as well as data from other brain regions obtained from http://crcns.org.^1,2

Results:

LOW states lasted longer than OFF/DOWN states and were distinguished by a subset of “LOW-active” cells. LOW activity sleep was preceded and followed by increased sharp-wave ripple activity. We also observed decreased slow-wave activity and sleep spindles in the hippocampal LFP and neocortical EEG upon LOW onset, with a partial rebound immediately after LOW. LOW states demonstrated activity patterns consistent with sleep but frequently transitioned into microarousals and showed EMG and LFP differences from small-amplitude irregular activity during quiet waking. Their likelihood decreased within individual non-REM epochs yet increased over the course of sleep. By analyzing data from the entorhinal cortex of rats,¹ as well as the hippocampus, the medial prefrontal cortex, the postsubiculum, and the anterior thalamus of mice,² obtained from http://crcns.org, we confirmed that LOW states corresponded to markedly diminished activity simultaneously in all of these regions.

Conclusions:

We propose that LOW states are an important microstate within non-REM sleep that provide respite from high-activity sleep and may serve a restorative function.

Spontaneous Infraslow Fluctuations Modulate Hippocampal EPSP-PS Coupling

Extensive trial-to-trial variability is a hallmark of most behavioral, cognitive, and physiological processes. Spontaneous brain activity (SBA), a ubiquitous phenomenon that coordinates levels and patterns of neuronal activity throughout the brain, may contribute to this variability by dynamically altering neuronal excitability. In freely-behaving male rats, we observed extensive variability of the hippocampal evoked response across 28-min recording periods despite maintaining constant stimulation parameters of the medial perforant path. This variability was related to antecedent SBA: increases in low-frequency (0.5–9 Hz) and high-frequency (40.25–100 Hz) band-limited power (BLP) in the 4-s preceding stimulation were associated with decreased slope of the field EPSP (fEPSP) and increased population spike (PS) amplitude. These fluctuations in SBA and evoked response magnitude did not appear stochastic but rather exhibited coordinated activity across infraslow timescales (0.005–0.02 Hz). Specifically, infraslow fluctuations in high- and low-frequency BLP were antiphase with changes in fEPSP slope and in phase with changes in PS amplitude. With these divergent effects on the fEPSP and PS, infraslow SBA ultimately modulates EPSP-PS coupling and thereby enables hippocampal circuitry to generate heterogeneous outputs from identical inputs. Consequently, infraslow SBA appears well suited to dynamically alter sensory selection and information processing and highlights the fundamental role of endogenous neuronal activity for shaping the brain’s response to incoming stimuli.