Tjeerd W. Boonstra

Effects of sleep deprivation on neural functioning: an integrative review

Abstract.Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of sleep deprivation on brain activity include reduced cortical responsiveness to incoming stimuli, reflecting reduced attention. On a microscopic level, sleep deprivation is associated with increased levels of adenosine, a neuromodulator that has a general inhibitory effect on neural activity. The inhibition of cholinergic nuclei appears particularly relevant, as the associated decrease in cortical acetylcholine seems to cause effects of sleep deprivation on macroscopic brain activity. In general, however, the relationships between the neural effects of sleep deprivation across observation scales are poorly understood and uncovering these relationships should be a primary target in future research.

Multivariate time-frequency analysis of electromagnetic brain activity during bimanual motor learning.

Although the relationship between brain activity and motor performance is reasonably well established, the manner in which this relationship changes with motor learning remains incompletely understood. This paper presents a study of cortical modulations of event-related beta activity when participants learned to perform a complex bimanual motor task: 151 channel MEG data were acquired from nine healthy adults whilst learning a bimanual 3:5 polyrhythm. Sources of MEG activity were determined by means of synthetic aperture magnetometry that yielded locations and time courses of beta activities. The relationship between changes in performance and corresponding changes in event-related power were assessed using partial least squares. Behavioral data revealed that participants successfully learned to perform the 3:5 polyrhythm and that performance improvement was mainly achieved through the proper timing of the finger producing the slow rhythm. We found event-related modulation of beta power in the contralateral motor cortex that was inversely related to force output. The degree of beta modulation increased during the experiment - although the force level remained constant - and was positively correlated with motor performance, in particular for the motor cortex contralateral to the slow hand. These electrophysiological findings support the view that activity in motor cortex co-varies closely with behavioral changes over the course of learning.

Neural mechanisms of intermuscular coherence: implications for the rectification of surface electromyography.

Oscillatory activity plays a crucial role in corticospinal control of muscle synergies and is widely investigated using corticospinal and intermuscular synchronization. However, the neurophysiological mechanisms that translate these rhythmic patterns into surface electromyography (EMG) are not well understood. This is underscored by the ongoing debate on the rectification of surface EMG before spectral analysis. Whereas empirical studies commonly rectify surface EMG, computational approaches have argued against it. In the present study, we employ a computational model to investigate the role of the motor unit action potential (MAUP) on the translation of oscillatory activity. That is, diverse MUAP shapes may distort the transfer of common input into surface EMG. We test this in a computational model consisting of two motor unit pools receiving common input and compare it to empirical results of intermuscular coherence between bilateral leg muscles. The shape of the MUAP was parametrically varied, and power and coherence spectra were investigated with and without rectification. The model shows that the effect of EMG rectification depends on the uniformity of MUAP shapes. When output spikes of different motor units are convolved with identical MUAPs, oscillatory input is evident in both rectified and nonrectified EMG. In contrast, a heterogeneous MAUP distribution distorts common input and oscillatory components are only manifest as periodic amplitude modulations, i.e., in rectified EMG. The experimental data showed that intermuscular coherence was mainly discernable in rectified EMG, hence providing empirical support for a heterogeneous distribution of MUAPs. These findings implicate that the shape of MUAPs is an essential parameter to reconcile experimental and computational approaches.

We Feel: Mapping Emotion on Twitter

Research data on predisposition to mental health problems, and the fluctuations and regulation of emotions, thoughts, and behaviors are traditionally collected through surveys, which cannot provide a real-time insight into the emotional state of individuals or communities. Large datasets such as World Health Organization (WHO) statistics are collected less than once per year, whereas social network platforms, such as Twitter, offer the opportunity for real-time analysis of expressed mood. Such patterns are valuable to the mental health research community, to help understand the periods and locations of greatest demand and unmet need. We describe the “We Feel” system for analyzing global and regional variations in emotional expression, and report the results of validation against known patterns of variation in mood.

Multi-frequency phase locking in human somatosensory cortex

2.73 \times 10^{9}

Low-Alcohol Doses Reduce Common 10- to 15-Hz Input to Bilateral Leg Muscles During Quiet Standing

emotional tweets were collected over a 12-week period, and automatically annotated for emotion, geographic location, and gender. Principal component analysis (PCA) of the data illustrated a dominant in-phase pattern across all emotions, modulated by antiphase patterns for “positive” and “negative” emotions. The first three principal components accounted for over 90% of the variation in the data. PCA was also used to remove the dominant diurnal and weekly variations allowing identification of significant events within the data, with z-scores showing expression of emotions over 80 standard deviations from the mean. We also correlate emotional expression with WHO data at a national level and although no correlations were observed for the burden of depression, the burden of anxiety and suicide rates appeared to correlate with expression of particular emotions.

Corticomuscular and bilateral EMG coherence reflect distinct aspects of neural synchronization.

Cortical population responses to sensory input arise from the interaction between external stimuli and the intrinsic dynamics of the densely interconnected neuronal population. Although there is a large body of knowledge regarding single neuron responses to periodic stimuli, responses at the scale of cortical populations are incompletely understood. The characteristics of large-scale neuronal activity during periodic stimulation speak directly to the mechanisms underlying collective neuronal activity. Their accurate elucidation is hence a vital prelude to constructing and evaluating large-scale computational and biophysical models of the brain. Electroencephalographic data was recorded from eight human subjects while periodic vibrotactile stimuli were applied to the fingertip. Time-frequency decomposition was performed on the multi-channel data in order to investigate relative changes in the power and phase distributions at stimulus-related frequencies. We observed phase locked oscillatory activity at multiple stimulus-specific frequencies, in particular at ratios of 1:1, 2:1 and 2:3 to the stimulus frequency. These phase locked components were found to be modulated differently across the range of stimulus frequencies, with oscillatory responses most robustly sustained around 30 Hz. In contrast, no robust frequency-locked responses were apparent in the power changes. These results demonstrate n:m phase synchronization between cortical oscillations in the somatosensory system and an external periodic signal. We argue that neuronal populations evidence a collective nonlinear response to periodic sensory input. The existence of n:m phase synchronization demonstrates the contribution of intrinsic cortical dynamics to stimulus encoding and provides a novel phenomenological criteria for the validation of large-scale models of the brain.

Bilateral motor unit synchronization of leg muscles during a simple dynamic balance task

The effects of low doses of alcohol on neural synchronization in muscular activity were investigated in ten participants during quiet standing with eyes open or closed. We focused on changes in common input to bilateral motor unit pools as evident in surface electromyographic (EMG) recordings of lower leg extensor and flexor muscles. The extensor muscles exhibited bilateral synchronization in two distinct frequency bands (i.e., 0-5 and 10-15 Hz), whereas synchronization between flexor muscles was minimal. As expected, alcohol ingestion affected postural sway, yielding increased sway at higher blood-alcohol levels. Whereas vision affected bilateral synchronization only at 0-5 Hz, alcohol ingestion resulted in a progressive decrease of synchronization at 10-15 Hz between the EMG activities of the extensor muscles. The decrease in common bilateral input is most likely related to reduced reticulospinal activity with alcohol ingestion.

Amplitude and phase dynamics associated with acoustically paced finger tapping

Using electroencephalography (EEG) and electromyography (EMG), corticomuscular and bilateral motor unit synchronization have been found in different frequency bands and under different task conditions. These different types of long-range synchrony are hypothesized to originate from distinct mechanisms. We tested this by comparing time-resolved EEG-EMG and EMG-EMG coherence in a bilateral precision-grip task. Bilateral EMG activity was synchronized between 7 and 13Hz for about 1s when force output from both hands changed from an increasing to a stable force production. In contrast, EEG-EMG coherence was statistically significant between 15 and 30Hz during stable force production. The disparities in their time-frequency profiles accord with the existence of distinct underlying processes for corticomuscular and bilateral motor unit synchronization. In addition, the absence of synchronization between cortical activity and common spinal input at 10Hz renders a cortical source unlikely.

Critical fluctuations in cortical models near instability.

To handle the rich repertoire of behavioural goals, the CNS has to control the many degrees of freedom of the musculoskeletal system in a flexible manner. This problem can be drastically simplified if muscle synergies serve as the to‐be‐controlled building blocks of motor performance, instead of the individual degrees of freedom. Muscle synergies have been identified as coherent activation patterns of a group of muscles in space or time, but the neural mechanisms underlying their formation remain largely unknown. Here we evaluated the hypothesis that synergies are reflected in common input to different contributing muscles, and investigated modulations in motor unit (MU) synchronization of homologous muscles during a rhythmic balance task. If common input is related to muscle synergies, the resultant MU synchronization should not be static but task dependent and, in the present context, vary in time. Coherence between surface electromyographic signals of bilateral leg muscles revealed MU synchronization in two distinct frequency bands. MU synchronization was not constant but modulated within a movement cycle, and its time course resembled the activation patterns of the muscles. These results are congruent with a linkage between MU synchronization and muscle synergies, and suggest that MU synchronization provides an expedient method for studying synergy‐related neural mechanisms.