Primate somatosensory cortical neurons are entrained to both spontaneous and peripherally evoked spindle oscillations

Region-specific complexity of the intracranial EEG in the sleeping human brain

As the brain is a complex system with occurrence of self-similarity at different levels, a dedicated analysis of the complexity of brain signals is of interest to elucidate the functional role of various brain regions across the various stages of vigilance. We exploited intracranial electroencephalogram data from 38 cortical regions using the Higuchi fractal dimension (HFD) as measure to assess brain complexity, on a dataset of 1772 electrode locations. HFD values depended on sleep stage and topography. HFD increased with higher levels of vigilance, being highest during wakefulness in the frontal lobe. HFD did not change from wake to stage N2 in temporo-occipital regions. The transverse temporal gyrus was the only area in which the HFD did not differ between any two vigilance stages. Interestingly, HFD of wakefulness and stage R were different mainly in the precentral gyrus, possibly reflecting motor inhibition in stage R. The fusiform and parahippocampal gyri were the only areas showing no difference between wakefulness and N2. Stages R and N2 were similar only for the postcentral gyrus. Topographical analysis of brain complexity revealed that sleep stages are clearly differentiated in fronto-central brain regions, but that temporo-occipital regions sleep differently.

A 10.8 µW Neural Signal Recorder and Processor With Unsupervised Analog Classifier for Spike Sorting

Implantable brain machine interfaces for treatment of neurological disorders require on-chip, real-time signal processing of action potentials (spikes). In this work, we present the first spike sorting SoC with integrated neural recording front-end and analog unsupervised classifier. The event-driven, low power spike sorter features a novel hardware-optimized, K-means based algorithm that effectively eliminates duplicate clusters and is implemented using a novel clockless and ADC-less analog architecture. The 1.4 mm² chip is fabricated in a 180-nm CMOS SOI process. The analog front-end achieves a 3.3 μV_rms noise floor over the spike bandwidth (400 - 5000 Hz) and consumes 6.42 μW from a 1.5 V supply. The analog spike sorter consumes 4.35 μW and achieves 93.2% classification accuracy on a widely used synthetic test dataset. In addition, higher than 93% agreement between the chip classification result and that of a standard spike sorting software is observed using pre-recorded real neural signals. Simulations of the implemented spike sorter show robust performance under process-voltage-temperature variations.

Shared and unique features of mammalian sleep spindles - insights from new and old animal models

Sleep spindles are phasic events observed in mammalian non-rapid eye movement sleep. They are relevant today in the study of memory consolidation, sleep quality, mental health and ageing. We argue that our advanced understanding of their mechanisms has not exhausted the utility and need for animal model work. This is both because some topics, like cognitive ageing, have not yet been addressed sufficiently in comparative efforts and because the evolutionary history of this oscillation is still poorly understood. Comparisons across species often are either limited to referencing the classical cat and rodent models, or are over-inclusive, uncritically including reports of sleep spindles in rarely studied animals. In this review, we discuss the emergence of new (dog and sheep) models for sleep spindles and compare the strengths and shortcomings of new and old models based on the three validation criteria for animal models - face, predictive, and construct validity. We conclude that an emphasis on cognitive ageing might dictate the future of comparative sleep spindle studies, a development that is already becoming visible in studies on dogs. Moreover, reconstructing the evolutionary history of sleep spindles will require more stringent criteria for their identification, across more species. In particular, a stronger emphasis on construct and predictive validity can help verify if spindle-like events in other species are actual sleep spindles. Work in accordance with such stricter validation suggests that sleep spindles display more universally shared features, like defining frequency, than previously thought.

Communication from the cerebellum to the neocortex during sleep spindles

Surprisingly little is known about neural activity in the sleeping cerebellum. Using long-term wireless recording, we characterised dynamic cerebro-thalamo-cerebellar interactions during natural sleep in monkeys. Similar sleep cycles were evident in both M1 and cerebellum as cyclical fluctuations in firing rates as well as a reciprocal pattern of slow waves and sleep spindles. Directed connectivity from motor cortex to the cerebellum suggested a neocortical origin of slow waves. Surprisingly however, spindles were associated with a directional influence from the cerebellum to motor cortex, conducted via the thalamus. Furthermore, the relative phase of spindle-band oscillations in the neocortex and cerebellum varied systematically with their changing amplitudes. We used linear dynamical systems analysis to show that this behaviour could only be explained by a system of two coupled oscillators. These observations appear inconsistent with a single spindle generator within the thalamo-cortical system, and suggest instead a cerebellar contribution to neocortical sleep spindles. Since spindles are implicated in the off-line consolidation of procedural learning, we speculate that this may involve communication via cerebello-thalamo-neocortical pathways in sleep.

Investigating the effects of transcranial alternating current stimulation on primary somatosensory cortex

Near-threshold tactile stimuli perception and somatosensory temporal discrimination threshold (STDT) are encoded in the primary somatosensory cortex (S1) and largely depend on alpha and beta S1 rhythm. Transcranial alternating current stimulation (tACS) is a non-invasive neurophysiological technique that allows cortical rhythm modulation. We investigated the effects of tACS delivered over S1 at alpha, beta, and gamma frequencies on near-threshold tactile stimuli perception and STDT, as well as phase-dependent tACS effects on near-threshold tactile stimuli perception in healthy subjects. In separate sessions, we tested the effects of different tACS montages, and tACS at the individualised S1 μ-alpha frequency peak, on STDT and near-threshold tactile stimuli perception. We found that tACS applied over S1 at alpha, beta, and gamma frequencies did not modify STDT or near-threshold tactile stimuli perception. Moreover, we did not detect effects of tACS phase or montage. Finally, tACS did not modify near-threshold tactile stimuli perception and STDT even when delivered at the individualised μ-alpha frequency peak. Our study showed that tACS does not alter near-threshold tactile stimuli or STDT, possibly due to the inability of tACS to activate deep S1 layers. Future investigations may clarify tACS effects over S1 in patients with focal dystonia, whose pathophysiology implicates increased STDT.