Rava Azeredo da Silveira

Random Compressed Coding with Neurons

The paper shows that irregular neural responses can achieve efficient coding without fine-tuning, using a random synaptic network model and monkey motor cortex data.

Universal statistics of hippocampal place fields across species and dimensionalities

The paper shows a simple mathematical model explains the statistical properties of hippocampal place fields across species and environments.

Joint visual-vestibular computation of head direction and reflexive eye movement

The paper shows that head direction in mice is driven by both visual and vestibular signals, with visual signals dominating at low speeds and affecting navigational behavior.

Fixational eye movements as active sensation for high visual acuity

This paper investigates how fixational eye movements (FEM) affect visual acuity by modeling retinal coding and comparing it to human performance in a visual acuity task.

Jointly efficient encoding and decoding in neural populations

This paper introduces a framework combining encoding and decoding in neural populations using variational autoencoders, showing that models with broad tuning curves achieve accurate stimulus reconstruction and generalization.

Human Inference in Changing Environments with TemporalStructure

This study investigates how humans adapt their inference processes to temporal structure in stimuli, showing suboptimal behavior that can be modeled by sampling-based inference.