Search bioRxiv⌕ Search

Biology subjects

Lightning, A.

Publications and source records attributed to Lightning, A..

2 recordsLinked to original sources

Persistent Light-Induced Reduction of Neuronal Excitability: Implications for Non-Optogenetic control of Brain Actvity

Visible light is widely used in neuroscience, yet its direct effects on neuronal activity in the absence of optogenetic manipulation remain incompletely understood. Here, we investigated whether light stimulation can induce sustained changes in neuronal excitability. Using ex vivo electrophysiological recordings, we show that repeated pulses of blue light (5 s, 430-495 nm, 19 mW) produce a robust and persistent reduction in evoked firing activity in cortical neurons from both male and female mice, with an average decrease of [~]60% relative to baseline. This inhibitory effect persisted for more than 20 minutes following stimulation and was associated with changes in both passive membrane properties and active ion channel conductance. In human cortical neurons, responses were more heterogeneous. While a subset of neurons exhibited similar inhibitory effects, others showed increased excitability, with this response occurring more frequently in neurons from female patients, suggesting a potential sex-dependent effect. In addition, a transient depolarizing response to light was observed in a minority of human neurons but not in mice. These findings indicate that visible light, independently of exogenous opsins, can induce long-lasting modulation of neuronal activity without evidence of acute cytotoxicity under the conditions tested. This raises the possibility that visible light may provide a previously underappreciated, opsin-independent mechanism for modulating neuronal activity, with potential relevance for disorders characterized by neuronal hyperexcitability. We outline a framework for future investigations, including validation in human systems, in vivo studies, optimization of stimulation parameters, and assessment of therapeutic potential in pathological models.

neuroscience↗

Enhancing Statistical Power While Maintaining Small Sample Sizes in Behavioral Neuroscience Experiments Evaluating Success Rates

Studies with low statistical power reduce the probability of detecting true effects and often lead to overestimated effect sizes, undermining the reproducibility of scientific results. While several free statistical software tools are available for calculating statistical power, they often do not account for the specialized aspects of experimental designs in behavioral studies that evaluate success rates. To address this gap, we developed "SuccessRatePower" a free and user-friendly power calculator based on Monte Carlo simulations that takes into account the particular parameters of these experimental designs. Using "SuccessRatePower", we demonstrated that statistical power can be increased by modifying the experimental protocol in three ways: 1) reducing the probability of succeeding by chance (chance level), 2) increasing the number of trials used to calculate subject success rates, and, in some circumstance, 3) employing statistical analyses suited for discrete values. These adjustments enable even studies with small sample sizes to achieve high statistical power. Finally, we performed an associative behavioral task in mice, confirming the simulated statistical advantages of reducing chance levels and increasing the number of trials in such studies

neuroscience↗