The deer mouse (Peromyscus) has emerged as a model system for studying many aspects of biology, supported by extensive historical knowledge of its fascinating and varied natural history.
Leave-One-Trial-Out (LOTO) is a general, efficient and easily implementable approach for inferring trial-by-trial measures of computational model parameters in order to link these measures to neural mechanisms.
Direct in-vivo measurements in the human brain test validity of detailed computational models of trancranial electric stimulation and show that electric fields in the brain are weaker than currently assumed.
A new probabilistic model of connectivity reveals the structural and functional properties of the neural networks controlling locomotion in many individual tadpoles.
Model-based imaging shows that the rostrolateral prefrontal cortex supports dissimilarity-based heuristics that people may use when they are confronted with ambiguous scenarios.
Spontaneous theta oscillations and interneuron-specific phase preferences emerge spontaneously in a full-scale model of the isolated hippocampal CA1 subfield, corroborating and extending recent experimental findings.
A spiking network model that examines the transformation of odor information from olfactory bulb to piriform cortex demonstrates how intrinsic cortical circuitry preserves representations of odor identity across odorant concentrations.
A novel analysis of neural activity recorded in monkeys performing a “brain-machine interface” task reveals that a mismatch between motor effectors and the brains’ internal models of those effectors can explain a substantial portion of movement errors.
Influenza transmission among ferrets correlates strongly with transmission among humans, so the ferret model for influenza transmission is a valid tool for pandemic potential in humans.
