Emily S. Finn

The paper shows that reinterpretation of ambiguous social scenes is linked to representational shifts in association cortex, not changes in gaze.

The paper compares neural responses to objective and subjective socialness in an fMRI study, finding that subjective ratings better predict activity in visuo-social brain regions.

The paper investigates how neural representations of narrative elements change with reinterpretation of the same story, identifying dissociable brain regions involved in different narrative levels.

The paper characterizes individual and group-level thresholds for social perception using parameterizable stimuli and finds unique, stable tuning curves linked to socio-affective traits.

This study uses naturalistic movie-watching fMRI to predict cognitive scores and sex through a deep neural network framework, showing improved performance over resting-state FC.

The paper shows that negative affect homogenizes and positive affect diversifies social memory consolidation during post-encoding rest.

The paper shows that neural representations of concrete concepts are reliable across stories and unique to individuals, while abstract concepts show more variability.

This study decodes self-relevance and valence of spontaneous thought from fMRI signals using personal narratives and resting-state data.

The paper examines individual differences in neural event segmentation during movie watching and finds that boundary locations vary with segmentation speed and movie content, influencing memory and appraisal.

The paper investigates the neural correlates of conscious social perception using fMRI and observer reports, finding that social perception is subjective and influenced by internalizing traits.

The paper uses natural language processing to analyze how brain states respond to movie narratives, finding the default network is most involved in semantic integration.

This study links fluctuations in narrative engagement to brain coactivation patterns and shows that neural signatures of engagement predict later memory recall.

The paper shows that movie-watching provides more accurate predictions of behavioral traits than resting-state functional connectivity.

This study replicates Smith et al.'s (2015) findings on functional connectivity and subject measures using HCP datasets, showing a dominant primary mode in both smaller and larger datasets.

This study shows that a validated functional connectivity model predicts attention changes across time and under different sedation states.

This paper introduces a Bayesian multilevel framework for inter-subject correlation analysis in naturalistic scanning data, improving inference efficiency and reproducibility.

This study uses sub-millimeter fMRI to show that individual fingers have multiple mirrored representations in the motor cortex based on movement types, bridging invasive and non-invasive motor organization research.

The paper uses high-resolution fMRI to show layer-specific activity in human dlPFC during working memory task epochs, with superficial layers active during delay and deeper layers during response.

This study uses connectome-based predictive modeling on fMRI data to identify functional brain networks that predict social ability measures in autism spectrum disorder.

This study shows that trait paranoia modulates neural and behavioral responses to an ambiguous social narrative through differential brain synchrony and language processing.

This paper compares functional connectivity variability during movies and rest, finding movies enhance individual differences detection.