Impact statement: Ultra-high field neuroimaging dissects the ventral medial geniculate 17 body (vMGB) of the primary auditory pathway from other MGB subregions and reveals that 18 vMGB top-down modulation is relevant for speech recognition. Abstract 23Sensory thalami are central sensory pathway stations for information processing. Their role for human 24 cognition and perception, however, remains unclear. Recent evidence suggests an involvement of the 25 sensory thalami in speech recognition. In particular, the auditory thalamus (medial geniculate body, MGB) 26 response is modulated by speech recognition tasks and the amount of this task-dependent modulation is 27 associated with speech recognition abilities. Here we tested the specific hypothesis that this behaviorally 28 relevant modulation is present in the MGB subsection that corresponds to the primary auditory pathway 29 (i.e., the ventral MGB [vMGB]). We used ultra-high field 7T fMRI to identify the vMGB, and found a 30 significant positive correlation between the amount of task-dependent modulation and the speech 31 recognition performance across participants within left vMGB, but not within the other MGB subsections. 32These results imply that modulation of thalamic driving input to the auditory cortex facilitates speech 33 recognition. 34

NKCC1 is the primary transporter mediating chloride uptake in immature principal neurons, but its role in the development of in vivo network dynamics and cognitive abilities remains unknown. Here, we address the function of NKCC1 in developing mice using electrophysiological, optical, and behavioral approaches. We report that NKCC1 deletion from telencephalic glutamatergic neurons decreases in vitro excitatory actions of γ-aminobutyric acid (GABA) and impairs neuronal synchrony in neonatal hippocampal brain slices. In vivo, it has a minor impact on correlated spontaneous activity in the hippocampus and does not affect network activity in the intact visual cortex. Moreover, long-term effects of the developmental NKCC1 deletion on synaptic maturation, network dynamics, and behavioral performance are subtle. Our data reveal a neural network function of NKCC1 in hippocampal glutamatergic neurons in vivo, but challenge the hypothesis that NKCC1 is essential for major aspects of hippocampal development.

This paper summarizes our recent attempts to integrate action and perception within a single optimization framework. We start with a statistical formulation of Helmholtz's ideas about neural energy to furnish a model of perceptual inference and learning that can explain a remarkable range of neurobiological facts. Using constructs from statistical physics it can be shown that the problems of inferring the causes of our sensory inputs and learning regularities in the sensorium can be resolved using exactly the same principles. Furthermore, inference and learning can proceed in a biologically plausible fashion. The ensuing scheme rests on Empirical Bayes and hierarchical models of how sensory information is generated. The use of hierarchical models enables the brain to construct prior expectations in a dynamic and context-sensitive fashion. This scheme provides a principled way to understand many aspects of the brain's organization and responses. We will demonstrate the brain-like dynamics that this scheme entails by using models of birdsongs that are based on chaotic attractors with autonomous dynamics. This provides a nice example of how non-linear dynamics can be exploited by the brain to represent and predict dynamics in the environment.