02582nas a2200145   4500008004100000245010600041210006900147520197600216100002702192700002302219700002402242700002302266700002202289856012502311       2025                        eng d00aBrain-computer interface (BCI)-based identification of congenital red-green color vision deficiencies0 aBraincomputer interface BCIbased identification of congenital re3 aWe demonstrate brain-computer interface (BCI)- based color vision (CV) assessment for the identification of congenital red-green CV deficiencies. Experiments were based on the identification of metamers—light sources with different spectral distributions perceived to be the same color. Metamers elicit steady-state visual evoked potentials (SSVEPs) of minimal size and are different for people with versus without CV deficiencies. Methods: Thirty-one participants (20 control (CTR), 11 color vision deficient (CVdef)) completed behaviorand BCI-based CV assessments. Experiments used a visual stimulus that alternated between a monochromatic light source (yellow; fixed luminance) and a dichromatic light source (red and green; varying luminances) at a fixed frequency. During behavior-based CV assessment, participants identified metamers by manually adjusting the dichromatic source’s settings until its color matched that of the monochromatic source. During BCI-based CV assessment, participants attended a sequence of stimuli (each with a different dichromatic source setting) while electroencephalography was recorded; metamers were defined as the dichromatic source settings that minimized SSVEP size. Results: The behavior- and BCI-identified metamers were identical within each group, but different across groups (i.e., CTR and CVdef and for people with protan- versus deutan-type CV deficiencies). Automatic identification of CVdef individuals (and type of deficiency) was demonstrated using a classification analysis (93% accuracy). Conclusion: Experiments validated BCI-based CV assessment for the identification of congenital red-green CV deficiencies. Significance: BCI-based CV assessment does not require behavioral responses and can be automated, making it suitable for people with cognitive/motor deficits. With further development, BCI-based CV assessment may enable automatic identification of many types of congenital and acquired CV deficiencies.1 aRueda-Parra, Sebastian1 aCaruso, Heather, A1 aNorton, Penelope, L1 aGemoets, Darren, E1 aNorton, James, JS  uhttps://www.neurotechcenter.org/publications/2025/brain-computer-interface-bci-based-identification-congenital-red-green01902nas a2200241   4500008004100000245011900041210006900160300000800229490000800237520107300245100002401318700001701342700002101359700002501380700001301405700002201418700002301440700002401463700002201487700002101509700001101530856011901541       2025                        eng d00aSoleus H-reflex size versus stimulation rate in the presence of background muscle activity: a methodological study0 aSoleus Hreflex size versus stimulation rate in the presence of b  a2150 v2433 aHoffmann reflex (HR) operant conditioning (HROC) is an important intervention for neurorehabilitation. Current HROC paradigms elicit HRs at low rates (~ 0.2 Hz), minimizing rate-dependent depression (RDD). We investigated the impact of higher stimulation rates on HR size. Fifteen healthy participants maintained low background soleus electromyographic activity (EMG) while standing. Soleus HR and M-wave recruitment curves were obtained at rates of 0.2, 1, and 2 Hz twice, from which Mmax and Hmax were calculated. Seventy-five HRs were collected for each rate at a target M-wave size (~ 10 to 20% of Mmax). HR depression was minimal at higher stimulation rates. The mean HR amplitude was reliable across the two repetitions and three rates, with high intraclass correlation coefficient (ICC) values. HROC could be performed consistently at rates up to 2 Hz with minimal HR depression. Faster rates enable more conditioning trials per session, reducing session duration and/or number, thereby potentially accelerating conditioning and reducing participant burden.1 aBrangaccio, Jodi, A1 aGupta, Disha1 aMojtabavi, Helia1 aHardesty, Russell, L1 aHill, NJ1 aCarp, Jonathan, S1 aGemoets, Darren, E1 aVaughan, Theresa, M1 aNorton, James, JS1 aPerez, Monica, A1 aothers  uhttps://www.neurotechcenter.org/publications/2025/soleus-h-reflex-size-versus-stimulation-rate-presence-background