Humanized Foxp2 accelerates learning by enhancing transitions from declarative to procedural performance.

The acquisition of language and speech is uniquely human, but how genetic changes might have adapted the nervous system to this capacity is not well understood. Two human-specific amino acid substitutions in the transcription factor forkhead box P2 (FOXP2) are outstanding mechanistic candidates, as they could have been positively selected during human evolution and as FOXP2 is the sole gene to date firmly linked to speech and language development. When these two substitutions are introduced into the endogenous Foxp2 gene of mice (Foxp2(hum)), cortico-basal ganglia circuits are specifically affected. Here we demonstrate marked effects of this humanization of Foxp2 on learning and striatal neuroplasticity. Foxp2(hum/hum) mice learn stimulus-response associations faster than their WT littermates in situations in which declarative (i.e., place-based) and procedural (i.e., response-based) forms of learning could compete during transitions toward proceduralization of action sequences. Striatal districts known to be differently related to these two modes of learning are affected differently in the Foxp2(hum/hum) mice, as judged by measures of dopamine levels, gene expression patterns, and synaptic plasticity, including an NMDA receptor-dependent form of long-term depression. These findings raise the possibility that the humanized Foxp2 phenotype reflects a different tuning of corticostriatal systems involved in declarative and procedural learning, a capacity potentially contributing to adapting the human brain for speech and language acquisition.

Convulsive seizure detection using a wrist-worn electrodermal activity and accelerometry biosensor.

The special requirements for a seizure detector suitable for everyday use in terms of cost, comfort, and social acceptance call for alternatives to electroencephalography (EEG)-based methods. Therefore, we developed an algorithm for automatic detection of generalized tonic-clonic (GTC) seizures based on sympathetically mediated electrodermal activity (EDA) and accelerometry measured using a novel wrist-worn biosensor. The problem of GTC seizure detection was posed as a supervised learning task in which the goal was to classify 10-s epochs as a seizure or nonseizure event based on 19 extracted features from EDA and accelerometry recordings using a Support Vector Machine. Performance was evaluated using a double cross-validation method. The new seizure detection algorithm was tested on >4,213 h of recordings from 80 patients and detected 15 (94%) of 16 of the GTC seizures from seven patients with 130 false alarms (0.74 per 24 h). This algorithm can potentially provide a convulsive seizure alarm system for caregivers and objective quantification of seizure frequency.

Continuous monitoring of electrodermal activity during epileptic seizures using a wearable sensor.

We present a novel method for monitoring sympathetic nervous system activity during epileptic seizures using a wearable sensor measuring electrodermal activity (EDA). The wearable sensor enables long-term, continuous EDA recordings from patients. Preliminary results from our pilot study suggest that epileptic seizures induce a surge in EDA. These changes are greater in generalized tonic-clonic seizures and reflect a massive sympathetic discharge. This paper offers a new approach for investigating the relationship between epileptic seizures and autonomic alterations.