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The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brain's global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brain's response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research., Competing Interests: The authors have declared that no competing interests exist.

Objective: The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been hampered by the large artifact that the TMS generates in the EEG. Using TMS with EEG necessitates a sophisticated artifact-resistant EEG system that can acquire reliable signals in the crucial several tens of milliseconds immediately following the TMS pulse. Here, we demonstrate the use of a novel artifact removal algorithm together with a 24-bit EEG system to achieve similar recordings as those obtained with the dedicated TMS-compatible EEG system., Methods: This setup was used to compare TMS-evoked responses between a group of healthy controls and a group of patients with schizophrenia, a condition in which effective neural connectivity is thought to be compromised., Results: We observe differences in TMS-evoked responses between the two groups, similar to those recently reported in a study that used a dedicated TMS-compatible EEG system., Conclusions: The standard 24-bit EEG system combined with an artifact removal algorithm produces results similar to the dedicated TMS-compatible system., Significance: This paves the way for more researchers and clinicians to use TMS-evoked responses for research and diagnosis of a wide spectrum of disorders.

Transcranial Magnetic Stimulation (TMS) is rapidly gaining acceptance as a non-invasive probe into brain functionality. We utilize TMS to study the connectivity of a simple motor network in patients of schizophrenia (N=19), and in healthy control subjects (N=9). TMS was used in an externally paced finger tapping task, perturbing the internal network oscillations invoked by the finger motion as it keeps pace with a metronome. TMS perturbations were synchronized to the metronome and applied to the network at the level of the primary motor cortex (M1). Contrary to initial expectations, TMS did not affect the sensorimotor synchronization of subjects with schizophrenia or their tapping accuracy. TMS did cause extreme deviations in the finger's trajectory, and altered the timing perceptions of subjects with schizophrenia. Additionally, it invoked high-level deficiencies related to attention and volition in the form of lapses, implying that the connectivity between modules in the brain that underlie motor control, sensorimotor synchronization, timing perception and awareness of action, can be disrupted by TMS in subjects with schizophrenia, but not in healthy subjects. The ability to disrupt high level network functions with perturbations to the lower level of M1 supports models describing deficits in connectivity of distributed networks in the brains of schizophrenia patients. It also demonstrates the use of TMS to probe connectivity between components of such networks.

We study the interplay between motor programs and their timing in the brain by using precise pulses of transcranial magnetic stimulation (TMS) applied to the primary motor cortex. The movement of the finger performing a tapping task is periodically perturbed in synchronization with a metronome. TMS perturbation can profoundly affect both the finger trajectory and its kinematics, but the tapping accuracy itself is surprisingly not affected. The motion of the finger during the TMS perturbation can be categorized into two abnormal behaviors that subjects were unaware of: a doubling of the frequency of the tap and a stalling of the finger for half the period. More stalls occurred as the tapping frequency increased. In addition, an enhancement of the velocity of the finger on its way up was observed. We conclude that the timing process involved in controlling the tapping movement is separate from the motor processes in charge of execution of the motor commands. We speculate that the TMS is causing a release of the motor plan ahead of time into activation mode. The observed doubles and stalls are then the result of an indirect interaction in the brain, making use of an existing motor plan to correct the preactivation and obtain the temporal goal of keeping the beat.