Philip A. Kragel

The paper shows that human ventromedial prefrontal cortex encodes affective space with grid-like coding, supporting predictive inference and flexible decision-making.

The paper identifies convergent and selective functional zones in the insula using fMRI data, revealing a hierarchical convergence architecture across pain, appetitive, aversive, and cognitive control domains.

The paper examines the neural correlates of social interaction perception and theory of mind using fMRI, finding overlapping and distinct brain regions involved in these processes.

The paper uses artificial neural networks to model fMRI data and shows that the pSTS encodes facial expressions more robustly than the amygdala, while both regions encode visual context.

The paper presents a large-scale multimodal fMRI dataset combining naturalistic stimuli with diverse cognitive tasks to enable comprehensive cognitive neuroscience research.

This study investigates how hippocampal-prefrontal circuits represent emotion knowledge through functional MRI and computational modeling of emotional experiences.

The paper uses artificial neural networks to model how the human amygdala processes sensory inputs and relates them to self-reported valence in naturalistic stimuli.

The paper shows a convolutional neural network based on the Drosophila visual system predicts defensive blinking and emotional responses to looming stimuli in humans.

This study uses 7-Tesla fMRI to show that the human periaqueductal grey (PAG) shows bilateral BOLD increases during a working memory task without threat, suggesting a broader role in brain-body communication.

The paper replicates and extends a brain system for allostasis and interoception using 7 Tesla fMRI, finding high agreement with animal tract-tracing studies.

This study identifies a human brain signature of pleasure using fMRI, showing it is sensitive to pleasant tastes and humor, and linked to opioid receptor activity.

The paper examines spatial patterns of PAG activity and physiological responses during social stress in humans using 7T imaging.

This study uses fMRI to show that the human superior colliculus shows increased BOLD signal during visual and somatosensory stimulation and aversive conditions, correlating with brain regions involved in sensory and interoceptive processing.

This study uses 7-Tesla fMRI to show layer-dependent activity in the human superior colliculus during a working memory task, linking it to visual processing, motor control, and executive function.

The paper investigates how neural representations of fear experience vary across different situational contexts and finds that most brain regions encode fear in a situation-dependent manner.

The paper develops fMRI connectivity models to predict intelligence and tests their genetic correlations with measured IQ, finding stronger heritability and genetic overlap compared to single brain regions.

The paper evaluates the effect size and test-retest reliability of the Neurologic Pain Signature (NPS) across multiple studies, finding large within-person effect sizes and reliable performance with sufficient trial numbers.

This study identifies the dorsal premammillary nucleus as a central node in the escape network by showing its role in controlling escape vigor from both innate and conditioned threats in mice and suggesting a similar pathway in humans.

The paper develops a classifier using fMRI data to distinguish sexual from non-sexual images with high accuracy and shows its generalizability across individuals.

This study investigates the spatial scale of acute pain representation using fMRI data from 289 participants, finding that distributed, multi-system models better capture pain intensity than single regions or networks.

The paper develops a convolutional neural network to decode images into emotion categories and shows that human visual cortex activity reflects these emotion representations.