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Statistical Inter-stimulus Interval Window Estimation for Transient Neuromodulation via Paired Mechanical and Brain Stimulation.

ABSTRACT: For achieving motor recovery in individuals with sensorimotor deficits, augmented activation of the appropriate sensorimotor system, and facilitated induction of neural plasticity are essential. An emerging procedure that combines peripheral nerve stimulation and its associative stimulation with central brain stimulation is known to enhance the excitability of the motor cortex. In order to effectively apply this paired stimulation technique, timing between central and peripheral stimuli must be individually adjusted. There is a small range of effective timings between two stimuli, or the inter-stimulus interval window (ISI-W). Properties of ISI-W from neuromodulation in response to mechanical stimulation (Mstim) of muscles have been understudied because of the absence of a versatile and reliable mechanical stimulator. This paper adopted a combination of transcranial magnetic stimulation (TMS) and Mstim by using a high-precision robotic mechanical stimulator. A pneumatically operated robotic tendon tapping device was applied. A low-friction linear cylinder achieved high stimulation precision in time and low electromagnetic artifacts in physiological measurements. This paper describes a procedure to effectively estimate an individual ISI-W from the transiently enhanced motor evoked potential (MEP) with a reduced number of paired Mstim and sub-threshold TMS trials by applying statistical sampling and regression technique. This paper applied a total of four parametric and non-parametric statistical regression methods for ISI-W estimation. The developed procedure helps to reduce time for individually adjusting effective ISI, reducing physical burden on the subject.

SUBMITTER: Kim E

PROVIDER: S-EPMC7010981 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Sensory gating (SG) is a neurophysiological phenomenon whereby the response to the second stimulus in a repetitive pair is attenuated. This filtering of irrelevant or redundant information is thought to preserve neural resources for more behaviorally-relevant stimuli and thereby reflect the functional inhibition of sensory input. Developing a SG paradigm in which optimal suppression of sensory input is achieved requires investigators to consider numerous parameters such as stimulus intensity, time between stimulus pairs, and the inter-stimulus interval (ISI) within each pair. While these factors have been well defined for the interrogation of auditory gating, the precise parameters for eliciting optimal gating in the somatosensory domain are far less understood. To address this, we investigated the impact of varying the ISI within each identical pair of stimuli on gating using magnetoencephalography (MEG). Specifically, 25 healthy young adults underwent paired-pulse electrical stimulation of the median nerve with increasing ISIs between 100 and 1000 ms (in 100 ms increments). Importantly, for correspondence with previous studies of somatosensory gating, both time-domain and oscillatory neural responses to somatosensory stimulation were evaluated. Our results indicated that gating of somatosensory input was optimal (i.e., best suppression) for trials with an ISI of 200-220 ms, as evidenced by the smallest gating ratios and through statistical modeling estimations of optimal suppression. Importantly, this was true irrespective of whether oscillatory or evoked neural activity was used to calculate SG. Interestingly, oscillatory metrics of gating calculated using peak gamma (30-75 Hz) power and frequency revealed more robust gating (i.e., smaller ratios) than those calculated using time-domain neural responses, suggesting that high frequency oscillations may provide a more sensitive measure of SG. These findings have important implications for the development of optimal protocols and analysis pipelines to interrogate SG and inhibitory processing with a higher degree of sensitivity and accuracy.

Dataset Information

Statistical Inter-stimulus Interval Window Estimation for Transient Neuromodulation via Paired Mechanical and Brain Stimulation.

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