Intracranial high-γ connectivity distinguishes wakefulness from sleep.

Neural synchrony in the γ-band is considered a fundamental process in cortical computation and communication and it has also been proposed as a crucial correlate of consciousness. However, the latter claim remains inconclusive, mainly due to methodological limitations, such as the spectral constraints of scalp-level electroencephalographic recordings or volume-conduction confounds. Here, we circumvented these caveats by comparing γ-band connectivity between two global states of consciousness via intracranial electroencephalography (iEEG), which provides the most reliable measurements of high-frequency activity in the human brain. Non-REM Sleep recordings were compared to passive-wakefulness recordings of the same duration in three subjects with surgically implanted electrodes. Signals were analyzed through the weighted Phase Lag Index connectivity measure and relevant graph theory metrics. We found that connectivity in the high-γ range (90-120 Hz), as well as relevant graph theory properties, were higher during wakefulness than during sleep and discriminated between conditions better than any other canonical frequency band. Our results constitute the first report of iEEG differences between wakefulness and sleep in the high-γ range at both local and distant sites, highlighting the utility of this technique in the search for the neural correlates of global states of consciousness

Network Brain-Computer Interface (nBCI): An Alternative Approach for Cognitive Prosthetics

Brain computer interfaces (BCIs) have been applied to sensorimotor systems for many years. However, BCI technology has broad potential beyond sensorimotor systems. The emerging field of cognitive prosthetics, for example, promises to improve learning and memory for patients with cognitive impairment. Unfortunately, our understanding of the neural mechanisms underlying these cognitive processes remains limited in part due to the extensive individual variability in neural coding and circuit function. As a consequence, the development of methods to ascertain optimal control signals for cognitive decoding and restoration remains an active area of inquiry. To advance the field, robust tools are required to quantify time-varying and task-dependent brain states predictive of cognitive performance. Here, we suggest that network science is a natural language in which to formulate and apply such tools. In support of our argument, we offer a simple demonstration of the feasibility of a network approach to BCI control signals, which we refer to as network BCI (nBCI). Finally, in a single subject example, we show that nBCI can reliably predict online cognitive performance and is superior to certain common spectral approaches currently used in BCIs. Our review of the literature and preliminary findings support the notion that nBCI could provide a powerful approach for future applications in cognitive prosthetics

The entrainment of brain oscillations through transcranial alternating current stimulation (tACS) delivered at off-peak frequencies.

It has been demonstrated that endogenous brain oscillations can become entrained to rhythmic stimulation. Four studies were conducted to investigate the possibility of modulating endogenous frequency peaks, through entrainment, from stimulation delivered at off-peak frequencies. Study 1 utilised EEG recordings to establish whether off-peak stimulation within the alpha frequency range could successfully shift individual alpha peak frequencies in the direction of stimulation. Stimulation was delivered at 2Hz above and below the individual alpha peak frequency of each participant. EEG recordings taken immediately after stimulation found no significant modulation of individual alpha peak frequencies. In light of this, the subsequent studies assessed the effects of off-peak stimulation during the stimulation rather than immediately following it. These studies used a working memory task and were based on the theory that differences in theta and gamma frequency peaks causally effect working memory capacity. Studies 2 and 3 delivered tACS at off-peak theta frequencies (4Hz and 7Hz) and study 4 delivered tACS at off-peak gamma frequencies (40Hz and 70Hz) during a working memory task. This was done to ascertain whether such stimulation could alter working memory capacity, which would indicate that peak frequencies had been shifted. Studies 2 and 3 utilised two different electrode configurations (P4/Cz and P4/right supraorbital respectively). In study 3, working memory capacity was enhanced and impaired in the 4Hz and 7Hz conditions respectively. In studies 2 and 4, no significant changes in working memory capacity were found. The findings from study 3 indicate that off-peak entrainment can be used to shift frequency peaks in the direction of the stimulation frequency and that such shifts can have observable cognitive effects. The contrast between studies 2 and 3 highlights the importance of electrode placement in tACS studies