Daniel Pacheco

This study investigates how the brain represents cues and contexts during fear learning and reversal, finding distinct neural strategies that predict fear renewal.

This study uses iEEG and RSA to show that human extinction learning involves context-specific neural representations in the amygdala and extinction network, with theta oscillations signaling safety and predicting fear or safety responses.

The paper investigates how working memory prioritization affects representational formats in visual and prefrontal cortex using intracranial EEG and deep neural networks.

This study uses a deep neural network and drift-diffusion model to show that perceptual and conceptual features are processed in parallel during perception, with selective attention altering their timing in different brain regions.

The paper shows that during retrieval of aversive memories, the hippocampus reactivates gamma activity patterns from encoding, which originate in the amygdala, suggesting a hippocampus-centered mechanism for memory retrieval.