The enigma of infra-slow fluctuations in the human EEG

Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics

Higher brain functions require flexible integration of information across widely distributed brain regions depending on the task context. Resting-state functional magnetic resonance imaging (fMRI) has provided substantial insight into large-scale intrinsic brain network organisation, yet the principles of rapid context-dependent reconfiguration of that intrinsic network organisation are much less understood. A major challenge for task connectome mapping is the absence of a gold standard for deriving whole-brain task-modulated functional connectivity matrices. Here, we perform biophysically realistic simulations to control the ground-truth task-modulated functional connectivity over a wide range of experimental settings. We reveal the best-performing methods for different types of task designs and their fundamental limitations. Importantly, we demonstrate that rapid (100 ms) modulations of oscillatory neuronal synchronisation can be recovered from sluggish haemodynamic fluctuations even at typically low fMRI temporal resolution (2 s). Finally, we provide practical recommendations on task design and statistical analysis to foster task connectome mapping.

Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics

Higher brain functions require flexible integration of information across widely distributed brain regions depending on the task context. Resting-state functional magnetic resonance imaging (fMRI) has provided substantial insight into large-scale intrinsic brain network organisation, yet the principles of rapid context-dependent reconfiguration of that intrinsic network organisation are much less understood. A major challenge for task connectome mapping is the absence of a gold standard for deriving whole-brain task-modulated functional connectivity matrices. Here, we perform biophysically realistic simulations to control the ground-truth task-modulated functional connectivity over a wide range of experimental settings. We reveal the best-performing methods for different types of task designs and their fundamental limitations. Importantly, we demonstrate that rapid (100 ms) modulations of oscillatory neuronal synchronisation can be recovered from sluggish haemodynamic fluctuations even at typically low fMRI temporal resolution (2 s). Finally, we provide practical recommendations on task design and statistical analysis to foster task connectome mapping.

Brain states as wave-like motifs

There is ample evidence of wave-like activity in the brain at multiple scales and levels. This emerging literature supports the broader adoption of a wave perspective of brain activity. Specifically, a brain state can be described as a set of recurring, sequential patterns of propagating brain activity, namely a wave. We examine a collective body of experimental work investigating wave-like properties. Based on these works, we consider brain states as waves using a scale-agnostic framework across time and space. Emphasis is placed on the sequentiality and periodicity associated with brain activity. We conclude by discussing the implications, prospects, and experimental opportunities of this framework.

Contribution of chemical and electrical transmission to the low delta-like intrinsic retinal oscillation in mice: A role for daylight-activated neuromodulators

Basal electroretinogram (ERG) oscillations have shown predictive value for modifiable risk factors for type 2 diabetes. However, their origin remains unknown. Here, we seek to establish the pharmacological profile of the low delta-like (δ1) wave in the mouse because it shows light sensitivity in the form of a decreased peak frequency upon photopic exposure. Applying neuropharmacological drugs by intravitreal injection, we eliminated the δ1 wave using lidocaine or by blocking all chemical and electrical synapses. The δ1 wave was insensitive to the blockade of photoreceptor input, but was accelerated when all inhibitory or ionotropic inhibitory receptors in the retina were antagonized. The sole blockade of GABAA, GABAB, GABAC, and glycine receptors also accelerated the δ1 wave. In contrast, the gap junction blockade slowed the δ1 wave. Both GABAA receptors and gap junctions contribute to the light sensitivity of the δ1 wave. We further found that the day light-activated neuromodulators dopamine and nitric oxide donors mimicked the effect of photopic exposure on the δ1 wave. All drug effects were validated through light flash-evoked ERG responses. Our data indicate that the low δ-like intrinsic wave detected by the non-photic ERG arises from an inner retinal circuit regulated by inhibitory neurotransmission and nitric oxide/dopamine-sensitive gap junction-mediated communication.

Association of brain-autonomic activities and task accuracy under cognitive load: a pilot study using electroencephalogram, autonomic activity measurements, and arousal level estimated by machine learning

The total amount of mental activity applied to working memory at a given point in time is called cognitive load, which is an important factor in various activities in daily life. We have proposed new feature quantities that reflect the time-series changes in the power of typical frequency bands in electroencephalogram (EEG) for use in examining the relationship between brain activity and behavior under cognitive load. We also measured heart rate variability (HRV) and spontaneous skin conductance responses (SCR) to examine functional associations among brain activity, autonomic activity, and behavior under cognitive load. Additionally, we applied our machine learning model previously developed using EEG to the estimation of arousal level to interpret the brain-autonomic-behavior functional association under cognitive load. Experimental data from 12 healthy undergraduate students showed that participants with higher levels of infra-slow fluctuations of alpha power have more cognitive resources and thus can process information under cognitive load more efficiently. In addition, HRV reflecting parasympathetic activity correlated with task accuracy. The arousal level estimated using our machine learning model showed its robust relationship with EEG. Despite the limitation of the sample size, the results of this pilot study suggest that the information processing efficiency of the brain under cognitive load is reflected by time-series fluctuations in EEG, which are associated with an individual's task performance. These findings can contribute to the evaluation of the internal state of humans associated with cognitive load and the prediction of human behaviors in various situations under cognitive load.

Potential contributions of the intrinsic retinal oscillations recording using non-invasive electroretinogram to bioelectronics

Targeted electric signal use for disease diagnostics and treatment is emerging as a healthcare game-changer. Besides arrhythmias, treatment-resistant epilepsy and chronic pain, blindness, and perhaps soon vision loss, could be among the pathologies that benefit from bioelectronic medicine. The electroretinogram (ERG) technique has long demonstrated its role in diagnosing eye diseases and early stages of neurodegenerative diseases. Conspicuously, ERG applications are all based on light-induced responses. However, spontaneous, intrinsic activity also originates in retinal cells. It is a hallmark of degenerated retinas and its alterations accompany obesity and diabetes. To the extent that variables extracted from the resting activity of the retina measured by ERG allow the predictive diagnosis of risk factors for type 2 diabetes. Here, we provided a comparison of the baseline characteristics of intrinsic oscillatory activity recorded by ERGs in mice, rats, and humans, as well as in several rat strains, and explore whether zebrafish exhibit comparable activity. Their pattern was altered in neurodegenerative models including the cuprizone-induced demyelination model in mice as well as in the Royal College of Surgeons (RCS-/-) rats. We also discuss how the study of their properties may pave the way for future research directions and treatment approaches for retinopathies, among others.

Aging affects the phase coherence between spontaneous oscillations in brain oxygenation and neural activity

The risk of neurodegenerative disorders increases with age, due to reduced vascular nutrition and impaired neural function. However, the interactions between cardiovascular dynamics and neural activity, and how these interactions evolve in healthy aging, are not well understood. Here, the interactions are studied by assessment of the phase coherence between spontaneous oscillations in cerebral oxygenation measured by fNIRS, the electrical activity of the brain measured by EEG, and cardiovascular functions extracted from ECG and respiration effort, all simultaneously recorded. Signals measured at rest in 21 younger participants (31.1 ± 6.9 years) and 24 older participants (64.9 ± 6.9 years) were analysed by wavelet transform, wavelet phase coherence and ridge extraction for frequencies between 0.007 and 4 Hz. Coherence between the neural and oxygenation oscillations at ∼ 0.1 Hz is significantly reduced in the older adults in 46/176 fNIRS-EEG probe combinations. This reduction in coherence cannot be accounted for in terms of reduced power, thus indicating that neurovascular interactions change with age. The approach presented promises a noninvasive means of evaluating the efficiency of the neurovascular unit in aging and disease.