  Noninvasive brain stimulation and neuroimaging have revolutionized human
neuroscience, with a multitude of applications including diagnostic subtyping,
treatment optimization, and relapse prediction. It is therefore particularly
relevant to identify robust and clinically valuable brain biomarkers linking
symptoms to their underlying neural mechanisms. Brain biomarkers must be
reproducible (i.e., have internal reliability) across similar experiments
within a laboratory and be generalizable (i.e., have external reliability)
across experimental setups, laboratories, brain regions, and disease states.
However, reliability (internal and external) is not alone sufficient;
biomarkers also must have validity. Validity describes closeness to a true
measure of the underlying neural signal or disease state. We propose that these
two metrics, reliability and validity, should be evaluated and optimized before
any biomarker is used to inform treatment decisions. Here, we discuss these
metrics with respect to causal brain connectivity biomarkers from coupling
transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We
discuss controversies around TMS-EEG stemming from the multiple large
off-target components (noise) and relatively weak genuine brain responses
(signal), as is unfortunately often the case with human neuroscience. We review
the current state of TMS-EEG recordings, which consist of a mix of reliable
noise and unreliable signal. We describe methods for evaluating TMS-EEG
biomarkers, including how to assess internal and external reliability across
facilities, cognitive states, brain networks, and disorders, and how to
validate these biomarkers using invasive neural recordings or treatment
response. We provide recommendations to increase reliability and validity,
discuss lessons learned, and suggest future directions for the field.
