Adrienne L. Fairhall

The paper shows that reliable motor sequences can maintain timing stability while allowing flexible neuronal participation in zebra finch songs.

The paper shows that neural activity across multiple brain regions reflects Bayesian belief updating during a multi-dimensional inference task in monkeys.

This study shows that the primate hippocampus segments experience into discrete events through abrupt population activity shifts, reflecting abstract task structure rather than specific sensory features.

The paper uses correlative light and electron microscopy to identify synaptic motifs in larval zebrafish that support visual motion processing.

The paper develops a meta-learning approach to discover plasticity rules that organize and maintain sequence-generating neural dynamics in the presence of noise and perturbations.

The paper shows that the mouse olfactory bulb tracks breathing rhythms and self-location, providing contextual information for olfactory processing.

The paper shows that songbirds can recover from large-scale neuronal perturbation through unsupervised homeostatic mechanisms, with songs reverting to normal through saltatory recovery.

This study shows that a learned motor behavior can recover after chronic disruption of inhibitory circuits, with neuronal activity permanently altered but song recovery possible without relying on learning circuits.

This paper introduces Non-Stationary Dynamic Mode Decomposition (NS-DMD) to analyze time-varying spatiotemporal data, demonstrating its application to neural recordings from a non-human primate.

The paper introduces a model inspired by songbird brains that uses low-dimensional input fluctuations to correct timing errors in motor sequences, verified in zebra finch songs.

The paper shows that inhibitory neuron tuning in cortical networks emerges from synaptic heterogeneity and homeostatic regulation, not individual-level properties.

This study shows dopamine neurons in singing birds evaluate natural fluctuations in song performance without external perturbations.

This paper shows that generalized linear models can capture gain scaling and multi-timescale adaptation in neurons by incorporating spike history and fractional differentiation of stimulus variance.

EMC2 tracks calcium dynamics in neurons of behaving animals, showing daily turnover in mouse visual cortex and identifying three neuron ensembles in Hydra.

This study investigates how olfactory and visual cues are integrated in mosquitoes, showing CO2 modulates visual responses and revealing asymmetrical, time-dependent neural coupling between these senses.

The paper demonstrates how rapid excitability changes in spiking neural networks can enable fast and flexible sequence replay, mimicking cognitive flexibility mechanisms in the hippocampus.

The paper develops a method to track neuronal activity in deformable organisms by correcting motion and aligning neurons using fiducials and point-set registration.