A closed-loop auditory stimulation approach selectively modulates alpha oscillations and sleep onset dynamics in humans.

Alpha oscillations play a vital role in managing the brain's resources, inhibiting neural activity as a function of their phase and amplitude, and are changed in many brain disorders. Developing minimally invasive tools to modulate alpha activity and identifying the parameters that determine its response to exogenous modulators is essential for the implementation of focussed interventions. We introduce Alpha Closed-Loop Auditory Stimulation (αCLAS) as an EEG-based method to modulate and investigate these brain rhythms in humans with specificity and selectivity, using targeted auditory stimulation. Across a series of independent experiments, we demonstrate that αCLAS alters alpha power, frequency, and connectivity in a phase, amplitude, and topography-dependent manner. Using single-pulse-αCLAS, we show that the effects of auditory stimuli on alpha oscillations can be explained within the theoretical framework of oscillator theory and a phase-reset mechanism. Finally, we demonstrate the functional relevance of our approach by showing that αCLAS can interfere with sleep onset dynamics in a phase-dependent manner.

A comparison of the effects of two cooking methods on arsenic species and nutrient elements in rice.

Rice is one of the major cereal crops in the world, contributing significantly towards the dietary energy and nutrition of more than half of the world's population. However, rice can also be a significant exposure route for inorganic arsenic (iAs). This risk is even greater if rice is cooked with iAs-contaminated water. Here, we quantified the effect of two cooking methods, excess water (EW) and parboiled and absorbed (PBA), on As species and essential nutrient elements (P, K, Mg, Fe, Zn, Mn, Cu, Se and Mo) in white, parboiled and brown rice cooked with As-safe (0.18 µg L-1) and As-spiked (10 and 50 µg L-1) tap water. Furthermore, we calculated the exposure risk using the margin of exposure (MOE) for both low (the UK) and high (Bangladesh) rice per capita consumption scenarios. The total micro and macronutrient content in cooked rice was measured using ICP-MS (Inductively Coupled Plasma Mass Spectrometry). An LC-ICP-MS (liquid chromatography-ICP-MS) method was used to quantify arsenic species. The results demonstrate that EW and PBA methods produced similar efficacy of iAs removal (54-58 %) for white and brown rice. However, the EW method was better at removing iAs from parboiled rice (∼50 %) than PBA (∼39 %). We found that cooked brown rice was superior to other rice types in many essential nutrient elements, and cooking methods significantly affected the loss of K, Fe, Cu and Mo. For both cooking methods, cooking with iAs-spiked water significantly increased iAs in all rice types: white > parboiled > brown. However, when using As-spiked water, the PBA method retained more iAs than EW. Our risk evaluations showed that cooking rice with 50 µg L-1 significantly raises the As-exposure of the Bangladesh population due to the high per capita rice consumption rate, reinforcing the importance of accessing As-safe water for cooking.

The neuron mixer and its impact on human brain dynamics.

A signal mixer facilitates rich computation, which has been the building block of modern telecommunication. This frequency mixing produces new signals at the sum and difference frequencies of input signals, enabling powerful operations such as heterodyning and multiplexing. Here, we report that a neuron is a signal mixer. We found through ex vivo and in vivo whole-cell measurements that neurons mix exogenous (controlled) and endogenous (spontaneous) subthreshold membrane potential oscillations, producing new oscillation frequencies, and that neural mixing originates in voltage-gated ion channels. Furthermore, we demonstrate that mixing is evident in human brain activity and is associated with cognitive functions. We found that the human electroencephalogram displays distinct clusters of local and inter-region mixing and that conversion of the salient posterior alpha-beta oscillations into gamma-band oscillations regulates visual attention. Signal mixing may enable individual neurons to sculpt the spectrum of neural circuit oscillations and utilize them for computational operations.