Performance on cognitive tasks during learning is used to measure knowledge, yet it remains controversial since such testing is susceptible to contextual factors. To what extent does performance during learning depend on the testing context, rather than underlying knowledge? We trained mice, rats and ferrets on a range of tasks to examine how testing context impacts the acquisition of knowledge versus its expression. We interleaved reinforced trials with probe trials in which we omitted reinforcement. Across tasks, each animal species performed remarkably better in probe trials during learning and inter-animal variability was strikingly reduced. Reinforcement feedback is thus critical for learning-related behavioral improvements but, paradoxically masks the expression of underlying knowledge. We capture these results with a network model in which learning occurs during reinforced trials while context modulates only the read-out parameters. Probing learning by omitting reinforcement thus uncovers latent knowledge and identifies context- not "smartness"- as the major source of individual variability.

Social interactions powerfully impact the brain and the body, but high-resolution descriptions of these important physical interactions and their neural correlates are lacking. Currently, most studies rely on labor-intensive methods such as manual annotation. Scalable and objective tracking methods are required to understand the neural circuits underlying social behavior. Here we describe a hardware/software system and analysis pipeline that combines 3D videography, deep learning, physical modeling, and GPU-accelerated robust optimization, with automatic analysis of neuronal receptive fields recorded in interacting mice. Our system ("3DDD Social Mouse Tracker") is capable of fully automatic multi-animal tracking with minimal errors (including in complete darkness) during complex, spontaneous social encounters, together with simultaneous electrophysiological recordings. We capture posture dynamics of multiple unmarked mice with high spatiotemporal precision (~2 mm, 60 frames/s). A statistical model that relates 3D behavior and neural activity reveals multiplexed 'social receptive fields' of neurons in barrel cortex. Our approach could be broadly useful for neurobehavioral studies of multiple animals interacting in complex low-light environments.

Behavioural engagement can enhance sensory perception. However, the neuronal mechanisms by which behavioural states affect stimulus perception remain poorly understood. Here we record from single units in auditory cortex of rats performing a self-initiated go/no-go auditory task. Self-initiation transforms cortical tuning curves and bidirectionally modulates stimulus-evoked activity patterns and improves auditory detection and recognition. Trial self-initiation decreases the rate of spontaneous activity in the majority of recorded cells. Optogenetic disruption of cortical activity before and during tone presentation shows that these changes in evoked and spontaneous activity are important for sound perception. Thus, behavioural engagement can prepare cortical circuits for sensory processing by dynamically changing sound representation and by controlling the pattern of spontaneous activity.

A common single-nucleotide polymorphism (SNP) in the human brain-derived neurotrophic factor (BDNF) gene results in a Val66Met substitution in the BDNF prodomain region. This SNP is associated with alterations in memory and with enhanced risk to develop depression and anxiety disorders in humans. Here we show that the isolated BDNF prodomain is detected in the hippocampus and that it can be secreted from neurons in an activity-dependent manner. Using nuclear magnetic resonance spectroscopy and circular dichroism, we find that the prodomain is intrinsically disordered, and the Val66Met substitution induces structural changes. Surprisingly, application of Met66 (but not Val66) BDNF prodomain induces acute growth cone retraction and a decrease in Rac activity in hippocampal neurons. Expression of p75(NTR) and differential engagement of the Met66 prodomain to the SorCS2 receptor are required for this effect. These results identify the Met66 prodomain as a new active ligand, which modulates neuronal morphology.