The effect of deep brain structure modeling on transcranial direct current stimulation-induced electric fields: An in-silico study.

To study transcranial direct current stimulation (tDCS) and its effect on the brain, it could be useful to predict the distribution of the electric field induced in the brain with given tDCS parameters. As a solution, simulation with realistic computational models using magnetic resonance images (MRIs) have been widely used in the fields. With the recent advance of deep learning-based segmentation techniques of the brain, questions have been raised about if tDCS-induced electric field is affected by the deep brain structures. This study aimed to investigate the effect of the deep brain structure modeling on the induced electric field. To this end, we generated models with and without the deep brain structures by using an open MRI dataset comprising tDCS parameters, electric field simulation results and in-vivo intracranial recordings in the deep brain structures. We investigated the difference between the simulation results of the two models with a statistical analysis. Our results indicated that tDCS-induced electric fields and current flow in the brain are significantly different when the deep brain structures are considered.

Effect of Non-invasive Spinal Stimulation on Self-sustained Firing Motoneuron Model: In-Silico Study Using Human Body Model.

Transcutaneous spinal electrical stimulation (tSCS) is a non-invasive neuromodulation approach using a low intensity direct current. Recent developments in the technique have opened the possibility that tSCS can help restore motor function after spinal cord injury (SCI). However, the exact mechanism of action tSCS has on the spinal circuits is still unknown. Due to the complexity of experimental synthesis in a human model to delineate the mechanisms, models that link the stimulation paradigm and circuit behaviors are advantageous. Thus, this study aims to simulate the underlying changes in motor circuit firing rates in response to external stimuli induced by tSCS. Serial stimulations combining a high-fidelity finite element model with the human torso and spinal cord with a lumped motor neuron model is constructed. The parameters for both components of the model were derived from previous studies. We focused our analysis on a lumped motor neuron model that describes sustained firing behavior of the motor neuron driven primarily by persistent inward current (PIC), a signature behavior of the motor neuron after SCI. Modulation of the PIC behaviors was achieved by stimulating voltage-dependent calcium and sodium channels in the dendrite using a tSCS-induced electric field (E-field) expressed at different a spatial locations of the motor neuron in the gray matter. The PIC behaviors of spinal motor neurons in the left ventral horn were suppressed, while for the most part invariant in the right ventral horn. These initial simulations will provide a steppingstone for future examinations that incorporate additional neuronal models of inhibitory and excitatory interneurons to access the circuit-level effect of spinal stimulation.

Possible Effect of Binaural Beat Combined With Autonomous Sensory Meridian Response for Inducing Sleep.

Sleep is important to maintain physical and cognitive functions in everyday life. However, the prevalence of sleep disorders is on the rise. One existing solution to this problem is to induce sleep using an auditory stimulus. When we listen to acoustic beats of two tones in each ear simultaneously, a binaural beat is generated which induces brain signals at a specific desired frequency. However, this auditory stimulus is uncomfortable for users to listen to induce sleep. To overcome this difficulty, we can exploit the feelings of calmness and relaxation that are induced by the perceptual phenomenon of autonomous sensory meridian response (ASMR). In this study, we proposed a novel auditory stimulus for inducing sleep. Specifically, we used a 6 Hz binaural beat corresponding to the center of the theta band (4-8 Hz), which is the frequency at which brain activity is entrained during non-rapid eye movement (NREM) in sleep stage 1. In addition, the "ASMR triggers" that cause ASMR were presented from natural sound as the sensory stimuli. In session 1, we combined two auditory stimuli (the 6 Hz binaural beat and ASMR triggers) at three-decibel ratios to find the optimal combination ratio. As a result, we determined that the combination of a 30:60 dB ratio of binaural beat to ASMR trigger is most effective for inducing theta power and psychological stability. In session 2, the effects of these combined stimuli (CS) were compared with an only binaural beat, only the ASMR trigger, or a sham condition. The combination stimulus retained the advantages of the binaural beat and resolved its shortcomings with the ASMR triggers, including psychological self-reports. Our findings indicate that the proposed auditory stimulus could induce the brain signals required for sleep, while simultaneously keeping the user in a psychologically comfortable state. This technology provides an important opportunity to develop a novel method for increasing the quality of sleep.