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Hutchings, F.

Publications and source records attributed to Hutchings, F..

2 recordsLinked to original sources

Characterization of light penetration through brain tissue, for optogenetic stimulation

The recent development of optogenetic tools, to manipulate neuronal activity using light, provides opportunities for novel brain-machine interface (BMI) control systems for treating neurological conditions. An issue of critical importance, therefore, is how well light penetrates through brain tissue. We took two different approaches to estimate light penetration through rodent brain tissue. The first employed so-called "nucleated patches" from cells expressing the light-activated membrane channel, channelrhodopsin (ChR2). By recording light-activated currents, we used these nucleated patches as extremely sensitive, microscopic, biological light-meters, to measure light penetration through 300-700{micro}m thick slices of rodent neocortical tissue. The nucleated patch method indicates that the effective illumination drops off with increasing tissue thickness, corresponding to a space constant of 317{micro}m (95% confidence interval between 248-441{micro}m). We compared this with measurements taken from directly visualizing the illumination of brain tissue, orthogonal to the direction of the light. This yielded a contour map of reduced illumination with distance, which along the direction of light delivery, had a space constant,{tau} 453{micro}m. This yields a lower extinction coefficient, {micro}e (the reciprocal of{tau} , [~]3mm-1) than previous estimates, implying better light penetration from LED sources than these earlier studies suggest.

neuroscience↗

Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients

In patients with drug resistant focal epilepsy, targeted weak stimulation of the affected brain regions has been proposed as an alternative to surgery. However, the effectiveness of stimulation as a treatment presents great variation from patient to patient. In this study, brain activity is simulated for a period of one day using a network of Wilson-Cowan oscillators coupled according to diffusion imaging based structural connectivity. We use this computational model to examine the potential long-term effects of stimulation on brain connectivity. Our findings indicate that the overall simulated effect of stimulation is heavily dependent on the excitability of the stimulated regions. Additionally, stimulation seems to lead to long-term effects in the connectivity of secondary (non-stimulated) regions in epileptic patients. These effects are correlated with a worse surgery outcome in some patients, which suggests that long-term simulations could be used as a tool to determine suitability for surgery/stimulation.

neuroscience↗