Transcranial magnetic stimulation and magnetoencephalography are feasible alternatives to invasive methods in optimizing responsive neurostimulation device placement.

Responsive neurostimulation (RNS) is a treatment option for patients with refractory epilepsy when surgical resection is not possible due to overlap of the irritative zone and eloquent cortex. Presurgical evaluations for RNS placement typically rely on invasive methods. This study investigated the potential of transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG) to provide key presurgical information non-invasively. We hypothesized that these non-invasive methods may assist in optimizing RNS placement by providing useful information for seizure localization by MEG and eloquent cortex mapping by TMS. A retrospective chart review identified nine patients who underwent RNS placement (mean age = 20.4 years [SD = 5.6], two-thirds were female). Characterization of the irritative zone using MEG was successful in eight of nine patients. Non-invasive mapping of relevant eloquent cortex was attempted in all patients. TMS was successful in eight of nine patients, and MEG was successful in two of six patients. Importantly, patients mapped with non-invasive modalities experienced an average seizure reduction of 77 % at their most recent clinic visit, compared to 75 % seizure reduction in those with invasive evaluations, indicating appropriate RNS placement. These data demonstrate that TMS and MEG can provide key information for RNS and may be feasible alternatives to invasive methods for assisting in decision making regarding RNS placement. Non-invasive methods for determining RNS placement have a high rate of success when data from multiple non-invasive modalities converge and can inform more accurate placement of intracranial electrodes prior to RNS placement or mitigate their need.

Efficiently Quantifying Egocentric Social Network Cannabis Use: Initial Psychometric Validation of the Brief Cannabis Social Density Assessment.

OBJECTIVE: Social environment is a key determinant of substance use, but cannabis-related social network analysis is not common, in part due to the assessment burden of comprehensive egocentric social network analysis. METHOD: The current pre-registered secondary analysis assessed the psychometric properties (i.e., convergent, criterion-related, incremental validity) of the Brief Cannabis Social Density Assessment (B-CaSDA) in a cross-sectional sample of adults who use cannabis (N = 310) using a survey-based design. The B-CaSDA assesses the quantity and frequency of cannabis use for the respondent's four closest (non-parent) relationships. RESULTS: Cannabis use severity was elevated for each additional person who used cannabis at all or daily in the individual's social network. B-CaSDA indices (i.e., frequency, quantity, total score) were positively correlated with cannabis consumption, cannabis use severity indicators, and established risk factors for harmful cannabis use. B-CaSDA indices also discriminated between those above and below a clinical cutoff on the Cannabis Use Disorder Identification Test - Revised (CUDIT-R). Finally, in omnibus models that included common risk factors for cannabis use severity, the B-CaSDA quantity index contributed additional variance when predicting CUDIT-R total score, and B-CaSDA frequency contributed additional variance in predicting the CUDIT-R quantity-frequency subscale. CONCLUSIONS: The results suggest that the B-CaSDA has the potential to expand social network research on cannabis use and misuse by increasing its assessment feasibility in diverse designs.