Computational modeling and analysis of mouse neural population data finds that the excitation/inhibition imbalance theory of brain disorders is too limited to account for key changes in neural activity statistics.
Output neurons in the mushroom body of the fruit fly brain encode the positive or negative survival value of stimuli, enabling insects to choose adaptive approach and avoidance behaviors through associative learning.
Resting-state MEG-activity and MRS-GABA/Glx measurements reveal that there is a significant shift in excitability during the course of schizophrenia, involving hyperexcitability during the onset and a reduction at chronic stages.
Rostromedial tegmental neurons encode motivational valence and opponent responses across a wide range of affective stimulus modalities, while also driving dopamine inhibition and conditioned place aversion to aversive stimuli.
Neural populations may depend on balanced recurrent connectivity to produce an efficient stimulus representation while also maintaining an accurate stimulus encoding despite the variability introduced by adapting neural responses.