Targeting Personalized Brain States Reflecting Strong and Weak Corticospinal Tract Output in Real-time

University of Texas at Austin21 enrolled

Overview

Transcranial magnetic stimulation (TMS) interventions could feasibly strengthen residual corticospinal tract (CST) connections and enhance recovery of paretic hand function after stroke. To maximize the therapeutic effects of such interventions, they must be delivered during poststroke brain activity patterns during which TMS best activates the residual corticospinal tract and enhances neural transmission within it (i.e., brain state-dependent TMS). In this study, the investigators will test the feasibility of real-time, personalized brain state-dependent TMS in neurotypical adults. Participants will visit the laboratory for one day of testing. Upon arrival, participants will provide their informed consent; afterwards, they will complete eligibility screening. The investigators will then place recording electrodes on the scalp using a swim-type cap and on the left first dorsal interosseous, abductor pollicis brevis, and extensor digitorum communis muscles. After determining the location at which TMS best elicits muscle twitches in the left first dorsal interosseous, the investigators will determine the lowest possible intensity at which TMS elicits muscle twitches at least half of the time in this muscle. Then, the investigators will deliver 6 blocks of 100 single TMS pulses while the participant rests quietly with their eyes open; stimulation will be delivered at an intensity that is 20% greater than the lowest possible intensity at which TMS elicits muscle twitches at least half of the time. Afterwards, the investigators will use the muscle and brain activity recordings acquired during these 6 blocks to build a personalized mathematical model that identifies which patterns of brain activity correspond to the largest TMS-evoked muscle twitches. The investigators will then use this model to detect the occurrence of these brain activity patterns in real-time; when these patterns are detected, single TMS pulses will be delivered. Afterwards, all recording electrodes will be removed, participation will be complete, and participants will leave the laboratory. The investigators will recruit a total of 16 neurotypical adults for this study.

Study Type

INTERVENTIONAL

Allocation

Purpose

BASIC_SCIENCE

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Right-hand dominance * Willingness to participate * Ability to provide informed consent Exclusion Criteria: * History of major neurological, orthopedic, psychiatric, or cardiovascular disease * Presence of contraindications to transcranial magnetic stimulation (TMS) or peripheral nerve stimulation (PNS), including: * history of adverse reactions to TMS or PNS * history of stroke or head injury * metal in head, eyes, neck, chest/trunk, or arms, including but not limited to shrapnel, * surgical clips, fragments from metalworking, fragments from welding * implanted devices * history of frequent and severe headaches or migraines * immediate family history of seizure or epilepsy * personal history of seizure or epilepsy * current, suspected, or planned pregnancy * current or recent (within the last 3 months) use of medications acting on the central nervous system, including but not limited to: antipsychotic drugs, antidepressants, benzodiazepines, prescription stimulants

Outcomes

Primary Outcomes

Motor-evoked Potential (MEP) Amplitudes

Peak-to-peak MEP amplitudes elicited by single transcranial magnetic stimulation (TMS) pulses delivered during personalized strong and weak CST states will be measured from the left first dorsal interosseous muscle. At the individual participant level, all MEP amplitudes will be normalized to the mean MEP amplitude observed in that participant. Mean normalized MEP amplitudes will be compared across CST states.

Time frame: single session

Secondary Outcomes

State-targeting Accuracy

An offline version of the real-time EEG analysis algorithm will be used to determine the brain state (i.e., strong or weak CST states, or neither) immediately preceding delivery of each single TMS pulse. The proportion of trials during which the online and offline versions of the real-time EEG analysis algorithm produce the same brain state prediction will be calculated per participant and used as a state-targeting accuracy metric. State-targeting accuracy metrics will be compared to the theoretical chance level (0.5).