Biology subjects

Tarnaud, T.

Publications and source records attributed to Tarnaud, T..

3 recordsLinked to original sources

bioRxiv2022

Non-linearities and Timescales in Temporal Interference Deep Brain Stimulation

In temporal interference (TI) stimulation, neuronal cells react to two interfering sinusoidal electric fields with a slightly different frequency. It was previously seen that for the same input intensity, the neurons do not react to a purely sinusoidal signal. This study aims to get a better understanding of the mechanism underlying TI neuromodulation, which is largely unknown. To this end, single-compartment models are used to simulate computationally the response of neurons to the sinusoidal and TI waveform. This study compares different neuron models to get insight into which models are able to reproduce the experimental observations. It was found that integrate- and-fire models do not entirely reflect the experimental behavior while the Hodgkin-Huxley and Frankenhaeuser-Huxley model do reflect this behavior. Changing the characteristics of the ion gates in the Frankenhaeuser-Huxley model alters the response to both the sinusoidal and TI signal, possibly reducing the firing threshold of the sinusoidal input below that of the TI input. The model results show that TI stimulation is not qualitatively impacted by nonlinearities in the current-voltage relation. In contrast, ion channels have a significant impact on the neuronal response. This paper makes advances both in terms of biophysical insight into the neuron as well as the insight in computational modelling of TI stimulation.

neuroscience↗

bioRxiv2021

Improved alpha-beta power reduction via combined Electrical and Ultrasonic stimulation in a Parkinsonian Cortex-Basal Ganglia-Thalamus Computational Model

ObjectiveTo investigate computationally the interaction of combined electrical and ultrasonic modulation of isolated neurons and of the Parkinsonian cortex-basal ganglia-thalamus loop. MethodsContinuous-wave or pulsed electrical and ultrasonic neuromodulation is applied to isolated Otsuka plateau-potential generating subthalamic nucleus (STN) and Pospischil regular, fast and low-threshold spiking cortical cells in a temporally-alternating or simultaneous manner. Similar combinations of electrical/ultrasonic waveforms are applied to a Parkinsonian biophysical cortex-basal ganglia-thalamus neuronal network. Ultrasound-neuron interaction is modelled respectively for isolated neurons and the neuronal network with the NICE and SONIC implementations of the bilayer sonophore underlying mechanism. Reduction in --{beta} spectral energy is used as a proxy to express improvement in Parkinsons disease by insonication and electrostimulation. ResultsSimultaneous electro-acoustic stimulation achieves a given level of neuronal activity at lower intensities compared to the separate stimulation modalities. Conversely, temporally alternating stimulation with 50 Hz electrical and ultrasound pulses is capable of eliciting 100 Hz STN firing rates. Furthermore, combination of ultrasound with hyperpolarizing currents can alter cortical cell relative spiking regimes. In the Parkinsonian neuronal network, high-frequency pulsed separated electrical and ultrasonic deep brain stimulation (DBS) reduce pathological -- {beta} power by entraining STN-neurons. In contrast, continuous-wave ultrasound reduces pathological oscillations by silencing the STN. Compared to the separated stimulation modalities, temporally simultaneous or alternating electro-acoustic stimulation can achieve higher reductions in -- {beta} power for the same contraints on electrical/ultrasonic intensity. ConclusionContinuous-wave and pulsed ultrasound reduce pathological oscillations by different mechanisms. Electroacoustic stimulation further improves -- {beta} power for given safety limits and is capable of altering cortical relative spiking regimes. Significancefocused ultrasound has the potential of becoming a non-invasive alternative of conventional DBS for the treatment of Parkinsons disease. Here, we elaborate on proposed benefits of combined electro-acoustic stimulation in terms of improved dynamic range, efficiency, resolution, and neuronal selectivity.

neuroscience↗

bioRxiv2020

Hodgkin and Huxley Opsin Model for Computationally Efficient Optogenetic Neurostimulation in Cells and Networks

Optogenetics has a lot of potential to become an effective neuromodulative therapy for clinical application. Selecting the correct opsin is crucial to have an optimal optogenetic tool. With computational modeling, the neuronal response to the current dynamics of an opsin can be extensively and systematically tested. Unlike electrical stimulation where the effect is directly defined by the applied field, the stimulation in optogenetics is indirect, depending on the selected opsins non-linear kinetics. With the continuous expansion of opsin possibilities, computational studies are difficult due to the need for an accurate model of the selected opsin first. To this end, we propose a Hodgkin-and-Huxley based model (22HH) as alternative to the conventional three and four state Markov models used for opsin modeling. Furthermore, we provide a fitting procedure, which allows for nearly automatic model fitting starting from a vast parameter space. With this procedure, we successfully fitted two distinctive opsins ChR2(H134R) and MerMAID. Both models are able to represent the experimental data with great accuracy and were obtained within an acceptable time frame. This is due to the absence of differential equations in the fitting procedure, with an enormous reduction in computational cost as result. The performance of the proposed model with a fit to ChR2(H134R) was tested, by comparing the neural response in a regular spiking neuron to the response obtained with the non-instantaneous, four state Markov model (4SB), derived by Williams et al. (2013) [1]. Finally, a computational speed gain was observed with the 22HH model in a regular spiking and sparse Pyramidal-Interneuron-Network-Gamma (sPING) network simulation with respect to the 4SB-model, due to the former having two differential equations less. Consequently, the proposed model allows for computationally efficient optogenetic neurostimulation and with the proposed fitting procedure will be valuable for further research in the field of optogenetics.

bioengineering↗