Conor J Houghton

The paper demonstrates that next-generation neural mass models can reproduce sharpness-tuned speech tracking and acoustic edge extraction through thresholded phase-resetting.

The paper shows that non-random brain connectome wiring improves robustness and efficiency in sparse neural networks compared to random wiring.

The paper applies hierarchical Bayesian modeling to multi-region brain cell count data, showing improved inference over traditional methods in under-sampled datasets.

This study investigates the role of GlyT2-positive interneurons in cerebellar network dynamics and behaviour, finding they modulate the timing of population activity rather than sensorimotor representations.

This paper proposes a cerebellar model for state estimation that links neuronal dynamics with behavioral coordination, using the free energy principle to explain contextual behavior.

The paper investigates how auditory cortex populations code competing sounds using information theory, finding that a diverse labeled line code outperforms summed population codes and achieves near-noiseless information transmission.

The paper develops a scalar Poincare map to model burst generation in Xenopus tadpole locomotor circuits, showing how synaptic depression affects rhythm patterns.

The paper investigates whether cortical entrainment reflects hierarchical syntactic processing or grammatical category repetition by comparing EEG responses to different linguistic conditions.

The paper presents a single-compartment model of Purkinje cell electrodynamics that simulates complex spikes and their interactions with simple spikes.

This study investigates how microzones in the cerebellar C3 zone of cats are organized and function during a skilled forelimb reaching task, revealing action-based control of muscle synergies.

The paper proposes selecting the smoothing parameter in Kozachenko-Leonenko estimators by maximizing estimated unbiased mutual information, tested on fictive data.