Alex T. Piet

The paper presents a database of spiking activity in the mouse visual system during an image change detection task, revealing task-specific coding patterns across brain regions.

The paper identifies topographic organization in locus coeruleus norepinephrine neurons, linking their morphology, gene expression, and activity to specific brain regions and learning-related behaviors.

The paper uses population network models and public datasets to analyze how cortical circuits adapt to stimulus novelty, finding weaker connections and shifts in neural population dynamics.

This study develops a process model to explain how rats adjust waiting times based on confidence and environmental factors, finding their behavior aligns with optimal strategies when travel times are considered.

The paper examines how different behavioral strategies in mice affect neural activity in the Vip-Sst disinhibitory circuit during a visual change detection task.

The paper identifies diverse functional neuron types in the visual cortex that process novel and familiar stimuli in mice.

This paper shows that mixing diverse activation functions in CNNs improves image classification performance, suggesting a computational role for diverse cell types in biological circuits.

This paper introduces emergent property inference (EPI), a method using deep learning to solve inverse problems in theoretical neuroscience by learning parameter distributions consistent with computational properties.

This study shows that the superior colliculus (SC) plays a key role in non-spatial cognitive processes in rats, challenging the view that cognition relies primarily on prefrontal cortex.

This study investigates how rats represent provisional decisions in dynamic environments, finding that Frontal Orienting Fields (FOF) encode evidence with temporal gain modulation and rapidly update during changes of mind.

This study shows that lateral orbitofrontal cortex (lOFC) promotes learning of risky biases but not spatial biases in rats during decision-making tasks.

This study applies Prospect Theory to rats, showing they exhibit probability distortion and diminishing sensitivity similar to humans, suggesting shared neural mechanisms.

This study shows rats can optimally accumulate and discount evidence in dynamic environments by adjusting their timescales based on environmental statistics and noise.