FILM: A Dataset of Flexible-Electrode Intracortical Recordings for Longitudinal Motor Decoding

Reliable long-term use of intracortical brain–computer interfaces (iBCIs) depends on sustained recording quality and decoding performance across days. Flexible intracortical electrodes support chronic recordings, but the long-term stability of motor decoding from these signals remains insufficiently characterized. To address this gap, we introduce FILM (Flexible-Electrode Intracortical Recordings for Longitudinal Motor Decoding), a longitudinal dataset for evaluating motor decoding from chronic flexible-electrode recordings. FILM pairs neural features derived from 512-channel recordings with synchronized two-dimensional cursor kinematics from two non-human primates performing Center-Out and Random Target reaching tasks. FILM comprises 178 sessions organized into three subject–task subsets spanning up to 277 days. Using FILM, we characterize longitudinal behavioral and neural changes, evaluate within-day and cross-day decoding performance, and assess target-day recalibration. Mean velocity profiles for each movement direction show substantial similarity across days, while movement speed, trial duration, neural activity, and estimated velocity tuning vary. Within-day decoding performance remains generally high, whereas cross-day decoding performance without recalibration tends to decline as the interval between training and testing days increases. Recalibration with limited target-day data improves cross-day decoding. Compared with matched recalibration without historical weights, incorporating these weights improves mean performance at the smallest calibration budget, with gains diminishing as more target-day data become available. Retrospective analyses further associate larger source–target weight mismatch with smaller or negative gains. FILM provides a resource for studying longitudinal neural distribution shifts and data-efficient adaptation in chronic iBCIs.