Persistent binding at dopamine transporters determines sustained psychostimulant effects.

Psychostimulants interacting with the dopamine transporter (DAT) can be used illicitly or for the treatment of specific neuropsychiatric disorders. However, they can also produce severe and persistent adverse events. Often, their pharmacological properties in vitro do not fully correlate to their pharmacological profile in vivo. Here, we investigated the pharmacological effects of enantiomers of pyrovalerone, α-pyrrolidinovalerophenone, and 3,4-methylenedioxypyrovalerone as compared to the traditional psychostimulants cocaine and methylphenidate, using a variety of in vitro, computational, and in vivo approaches. We found that in vitro drug-binding kinetics at DAT correlate with the time-course of in vivo psychostimulant action in mice. In particular, a slow dissociation (i.e., slow koff) of S-enantiomers of pyrovalerone analogs from DAT predicts their more persistent in vivo effects when compared to cocaine and methylphenidate. Overall, our findings highlight the critical importance of drug-binding kinetics at DAT for determining the in vivo profile of effects produced by psychostimulant drugs.

Decoding speech from spike-based neural population recordings in secondary auditory cortex of non-human primates.

Direct electronic communication with sensory areas of the neocortex is a challenging ambition for brain-computer interfaces. Here, we report the first successful neural decoding of English words with high intelligibility from intracortical spike-based neural population activity recorded from the secondary auditory cortex of macaques. We acquired 96-channel full-broadband population recordings using intracortical microelectrode arrays in the rostral and caudal parabelt regions of the superior temporal gyrus (STG). We leveraged a new neural processing toolkit to investigate the choice of decoding algorithm, neural preprocessing, audio representation, channel count, and array location on neural decoding performance. The presented spike-based machine learning neural decoding approach may further be useful in informing future encoding strategies to deliver direct auditory percepts to the brain as specific patterns of microstimulation.