Biology subjects

Kragel, P. A.

Publications and source records attributed to Kragel, P. A..

At least 19 recordsLinked to original sources

bioRxiv2026

A representation of the visual environment in the human basolateral amygdala supports learning and choice

Animals continuously transform sensory inputs into representations that guide behavior. Although the amygdala is a brain structure critical for learning and choice, how natural sensory experience is represented within this circuit remains unknown. Here, we identify a representation of the visual environment in the human basolateral amygdala (BLA) that contains information relevant for learning and choice. Using image-computable encoding models trained on responses to naturalistic videos, we recover a continuous, low-dimensional representation of visual experience in the BLA. The representation generalizes across individuals and independent datasets and prospectively predicts BLA responses to novel visual stimuli generated through closed-loop image synthesis. Signals derived from the representation also informed reinforcement-learning models of human choice. Together, these findings show that the human BLA organizes complex visual experience into a structured representation that can support learning and flexible behavioral responses.

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bioRxiv2026

A grid-like basis for affective space in human ventromedial prefrontal cortex

Human emotional experiences vary widely in everyday life, yet they are systematically organized within a continuous affective space defined by valence and arousal. Although this circumplex organization has shaped decades of research, its neural implementation remains unclear. Here, we asked whether abstract emotion concepts are encoded using grid-like coordinate principles in the human brain. During fMRI, participants tracked trajectories through affective space conveyed through morphs of facial expressions and sequences of phrases. We found that ventromedial prefrontal cortex (vmPFC) encoded affective space with robust hexadirectional modulation characteristic of grid-like coding. This coordinate representation generalized across stimulus modalities, indicating abstraction beyond perceptual features. The grid-like signal reflected a stable metric organization of emotion concepts independent of overt behavior, whereas distance-related signals in vmPFC predicted trial-by-trial affective judgements. Together, these findings suggest that emotion knowledge is structured by a grid-like coordinate system in the human brain that can support predictive inference and flexible decision-making.

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bioRxiv2025

The representation of emotion knowledge in hippocampal-prefrontal systems

Emotional experiences involve more than bodily reactions and momentary feelings--they depend on knowledge about the world that spans contexts and time. Although it is well established that individuals conceptualize emotions using a low-dimensional space organized by valence and arousal, the neural mechanisms giving rise to this configuration remain unclear. Here, we examine whether hippocampal-prefrontal circuits--regions implicated in forming cognitive maps--also support the abstraction of emotional experiences. Using functional MRI data collected as participants viewed emotionally evocative film clips, we found that activity in hippocampal and prefrontal cortex predicted self-reported emotion across schematically distinct videos, consistent with a role in structural learning. Computational modeling of emotion transitions revealed that hippocampal responses to films and emotion self-reports could be predicted based on the statistical regularities of emotion transitions across different temporal scales. These findings demonstrate that hippocampal-prefrontal systems represent emotion concepts at multiple levels of abstraction, offering new insight into how the brain organizes emotion knowledge.

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bioRxiv2025

Convergent and selective representations of pain, appetitive processes, aversive processes, and cognitive control in the insula

Regions that respond to multiple types of information ("convergence zones") are crucial for the brain to generate coherent experiences and behaviors. The insular cortex, known for its functional diversity, has been hypothesized to be a key convergence hub, yet empirical evidence identifying how and where convergence occurs is incomplete. To address this gap, we analyzed functional convergence across four key task domains--somatic pain, non-somatic appetitive processes, aversive processes, and cognitive control--in a large-scale Bayesian mega-analysis of fMRI data (N=540, systematically sampled from 36 studies). Bayes Factor analyses identified both convergent zones responding to multiple domains and selective zones responding to single domains. Results revealed a hierarchical convergence architecture, with a multi-domain convergence zone in bilateral dorsal anterior insula surrounded by zones showing progressively increasing convergence. Functional decoding and coactivation analyses further support the insulas role as a convergence hub, while cytoarchitectonic and neurotransmitter profiling characterizes the potential neuroanatomical underpinnings subserving convergent and domain-selective function. Overall, our results demonstrate a structured functional topography in the insula that bridges specialized and convergent processing, providing a potential neural basis for how diverse information streams combine into unified subjective experiences.

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bioRxiv2024

Common and distinct neural correlates of social interaction perception and theory of mind

Social interaction perception and theory of mind (ToM) frequently co-occur, but their commonalities and distinctions at behavioral and neural levels remain unclear. Participants (N = 231) provided moment-by-moment ratings of four text and four audio narratives on social interactions and ToM engagement, which were reliable (split-half r = .98 and .92, respectively) but only modestly correlated (r = .32). In a second sample (N = 90), we analyzed the co-variation between social interaction and ToM ratings and fMRI activity during text and audio narratives. Social interaction and ToM activity maps generalized across modalities (spatial r = .83 and .57, respectively), both with significant, overlapping clusters in canonical mentalizing regions (FDR q < .01). ToM uniquely engaged the lateral occipitotemporal cortex, left anterior intraparietal sulcus, and right premotor cortex. These results suggest that perceiving social interactions automatically involves mentalizing, and ToM additionally engages brain regions for action understanding and executive functions.

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bioRxiv2024

Understanding human amygdala function with artificial neural networks

AbstractThe amygdala is a cluster of subcortical nuclei that receives diverse sensory inputs and projects to the cortex, midbrain and other subcortical structures. Numerous accounts of amygdalar contributions to social and emotional behavior have been offered, yet an overarching description of amygdala function remains elusive. Here we adopt a computationally explicit framework that aims to develop a model of amygdala function based on the types of sensory inputs it receives, rather than individual constructs such as threat, arousal, or valence. Characterizing human fMRI signal acquired as participants viewed a full-length film, we developed encoding models that predict both patterns of amygdala activity and self-reported valence evoked by naturalistic images. We use deep image synthesis to generate artificial stimuli that distinctly engage encoding models of amygdala subregions that systematically differ from one another in terms of their low-level visual properties. These findings characterize how the amygdala compresses high-dimensional sensory inputs into low-dimensional representations relevant for behavior.

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bioRxiv2024

A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, with 6 multifaceted cognitive tasks including 2 hours of naturalistic movie viewing. This datasets combination of ample sample size, extensive data per participant, more than 600 iso hours worth of data, and a wide range of experimental conditions -- including cognitive, affective, social, and somatic/interoceptive tasks -- positions it uniquely for probing important questions in cognitive neuroscience.

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bioRxiv2023

Visual looming is a primitive for human emotion

Looming objects afford threat of collision across the animal kingdom. Defensive responses to looming and neural computations for looming detection are strikingly conserved across species. In mammals, information about rapidly approaching threats is conveyed from the retina to the midbrain superior colliculus, where variables that indicate the position and velocity of approach are computed to enable defensive behavior. Although neuroscientific theories posit that midbrain representations contribute to emotion through connectivity with distributed brain systems, it remains unknown whether a computational system for looming detection can predict both defensive behavior and phenomenal experience in humans. Here, we show that a shallow convolutional neural network based on the Drosophila visual system predicts defensive blinking to looming objects in infants and superior colliculus responses to optical expansion in adults. Further, the responses of the convolutional network to a broad array of naturalistic video clips predict self-reported emotion largely on the basis of subjective arousal. Our findings illustrate how motor and experiential components of human emotion relate to species-general systems for survival in unpredictable environments.

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bioRxiv2023

Cortical and subcortical mapping of the allostatic-interoceptive system in the human brain: replication and extension with 7 Tesla fMRI

The brain continuously anticipates the energetic needs of the body and prepares to meet those needs before they arise, called allostasis. In support of allostasis, the brain continually models the sensory state of the body, called interoception. We replicated and extended a large-scale system supporting allostasis and interoception in the human brain using ultra-high precision 7 Tesla functional magnetic resonance imaging (fMRI) (N = 90), improving the precision of subgenual and pregenual anterior cingulate topography combined with extensive brainstem nuclei mapping. We observed over 90% of the anatomical connections published in tract-tracing studies in non-human animals. The system also included regions of dense intrinsic connectivity broadly throughout the system, some of which were identified previously as part of the backbone of neural communication across the brain. These results strengthen previous evidence for a whole-brain system supporting the modeling and regulation of the internal milieu of the body.

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bioRxiv2022

Distinct spatial patterns of neural and physiology-related activity in the human periaqueductal grey during anticipatory social stress.

Periaqueductal gray (PAG) columns mediate affective experience, physiological regulation, and survival-related behavior; yet, only 7T imaging can resolve these small structures in humans. In a social stress task, participants prepared a speech, and we observed (a) bilateral ventrolateral PAG activity, relative to baseline, and (b) distinct spatial patterns of correlation between PAG activity and physiological response (i.e., cardiac interbeat interval, reparation rate, and tonic electrodermal activity).

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bioRxiv2022

7-Tesla evidence for columnar and rostral--caudal organization of the human periaqueductal grey response in the absence of threat: a working memory study

The periaqueductal gray (PAG) is a small midbrain structure that surrounds the cerebral aqueduct, regulates brain-body communication, and is often studied for its role in "fight-or-flight" and "freezing" responses to threat. We used ultra-high field 7-Tesla fMRI to resolve the PAG in humans and distinguish it from the cerebral aqueduct, examining its in vivo function in humans during a working memory task (N = 87). Relative to baseline fixation, both mild and moderate task-elicited cognitive demands elicited bilateral BOLD increases in ventrolateral PAG (vlPAG), a region previously observed to show increased activity during anticipated painful threat in both non-human and human animals. The present task posed only the most minimal (if any) "threat". The mild-demand condition involved a task easier than remembering a phone number, elicited a heart rate decrease relative to baseline, yet nonetheless elicited a bilateral vlPAG response. Across PAG voxels, BOLD signal intensity correlated with changes in physiological reactivity (relative to baseline) and showed some evidence of spatial organization along the rostral-caudal axis. These findings suggest that the PAG may have a broader role in coordinating brain--body communication during a minimally to moderately demanding task, even in the absence of threat.

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bioRxiv2022

The role of human superior colliculus in affective experiences during visual and somatosensory stimulation

The superior colliculus is often studied for its role in visually guided behaviors, but research in non-human animals indicates it is a midbrain hub for processing sensory information from multiple domains, including interoception (which is associated with affect). We used ultra-high field 7-Tesla fMRI to extend this work to humans, modeling superior colliculus BOLD signal intensity during visual or somatosensory stimulation (N = 40 in each sensory modality), both under aversive and neutral affective intensity. As hypothesized, the superior colliculus showed increased BOLD signal intensity in the dorsal and ventral subregions during visual and somatosensory stimulation, respectively. The entire superior colliculus also showed increased BOLD signal intensity during aversive compared to neural conditions. The superior colliculus BOLD signal intensity also correlated with a preregistered set of brain regions involved in visual, somatosensory, and interoceptive processing.

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bioRxiv2022

Layer-dependent activity in the human superior colliculus during working memory

We examined the superior colliculus (SC) with ultra-high resolution 7-Tesla fMRI during an N-back working memory task. We observed both increased BOLD signal intensity and functional connectivity that followed a layer-dependent pattern predicted from anatomical connections between SC and other brain structures important for visual processing, motor control, and executive function. Our results highlight a role for the human SC in cognitive functions that usually associated with the cerebral cortex.

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bioRxiv2022

A mesocorticolimbic signature of pleasure in the human brain

Pleasure is a fundamental driver of human behavior, yet its neural basis remains largely unknown. Rodent studies highlight opioidergic neural circuits connecting the nucleus accumbens, ventral pallidum, insula, and orbitofrontal cortex as critical for the initiation and regulation of pleasure, and human neuroimaging studies exhibit some translational parity. However, whether activation observed across these regions reflects a common, generalizable code for pleasure driven by opioidergic mechanisms remains unclear. Here we use pattern recognition techniques to develop a human functional magnetic resonance imaging signature of mesocorticolimbic activity unique to states of pleasure. In independent validation tests, we find this signature has high sensitivity to pleasant tastes and positive affect evoked by humor. The signature is spatially coextensive with mu-opioid receptor gene expression, and its response is attenuated by the opioid antagonist naloxone. These findings provide evidence of a basis for pleasure derived from primary and secondary rewards in humans that is distributed across brain systems, and suggest that similar mechanisms underlie hedonic impact across mammalian species.

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bioRxiv2022

Neural predictors of subjective fear depend on the situation

ABSTRSCTThe extent to which neural representations of fear experience depend on or generalize across the situational context has remained unclear. We systematically manipulated variation within and across three distinct fearevocative situations including fear of heights, spiders, and social threats. Participants (n=21, 10 females and 11 males) viewed 20 second clips depicting spiders, heights, or social encounters, and rated fear after each video. Searchlight multivoxel pattern analysis (MVPA) was used to identify whether and which brain regions carry information that predicts fear experience, and the degree to which the fear-predictive neural codes in these areas depend upon or generalize across the situations. The overwhelming majority of brain regions carrying information about fear did so in a situation dependent manner. These findings suggest that local neural representations of fear experience are unlikely to involve a singular pattern, but rather a collection of multiple heterogeneous brain states

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bioRxiv2021

Dorsal premammillary projection to periaqueductal gray controls escape vigor from innate and conditioned threats

Escape from threats has paramount importance for survival. However, it is unknown if a single circuit controls escape from innate and conditioned threats. The hypothalamic dorsal premammillary nucleus (PMd) may control escape, as it is activated by escape-inducing threats and projects to the region most implicated in flight, the dorsolateral periaqueductal gray (dlPAG). We show that in mice cholecystokinin (cck)-expressing PMd cells are activated during escape, but not other defensive behaviors. PMd-cck ensemble activity can also predict future escape. Furthermore, PMd inhibition decreases escape speed from both innate and conditioned threats. Inhibition of the PMd-cck projection to the dlPAG also decreased escape speed. Lastly, human fMRI data show that a posterior hypothalamic-to-dlPAG pathway increased activity during exposure to aversive images, indicating that a similar pathway may possibly have a related role in humans. Our data identify the PMd as a central node of the escape network.

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bioRxiv2020

The Brain Activation-based Sexual Image Classifier (BASIC): A sensitive and specific fMRI activity pattern for sexual image perception

Sexual stimuli processing is a key element in the repertoire of human affective and motivational states. Previous neuroimaging studies of sexual stimulus processing have revealed a complicated mosaic of activated regions, leaving unresolved questions about their sensitivity and specificity to sexual stimuli per se, generalizability across individuals, and potential utility as neuromarkers for sexual stimulus processing. In this study, data on sexual, negative, non-sexual positive, and neutral images from Wehrum et al. (2013) (N = 100) were re-analyzed with multivariate Support Vector Machine models to create the Brain Activation-based Sexual Image Classifier (BASIC) model. This model was tested for sensitivity, specificity, and generalizability in cross-validation (N = 100) and an independent test cohort (N = 18; Kragel et al. 2019). The BASIC model showed highly accurate performance (94-100%) in classifying sexual versus neutral or nonsexual affective images in both datasets. Virtual lesions and test of individual large-scale networks (e.g., visual or attention networks) show that these individual networks are neither necessary nor sufficient to capture sexual stimulus processing. These findings suggest that brain responses to sexual stimuli constitute a category of mental event that is distinct from general affect and involves multiple brain networks. It is, however, largely conserved across individuals, permitting the development of neuromarkers for sexual processing in individual persons. Future studies could assess performance of BASIC to a broader array of affective/motivational stimuli and link brain responses with physiological and subjective measures of sexual arousal.

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bioRxiv2020

Evoked pain intensity representation is distributed across brain systems: A multistudy mega-analysis

Information is coded in the brain at different scales for different phenomena: locally, distributed across regions and networks, and globally. For pain, the scale of representation is controversial. Although generally believed to be an integrated cognitive and sensory phenomenon implicating diverse brain systems, quantitative characterizations of which regions and networks are sufficient to represent pain are lacking. In this meta-analysis (or mega-analysis) using data from 289 participants across 10 studies, we use model comparison combined with multivariate predictive models to investigate the spatial scale and location of acute pain representation. We compare models based on (a) a single most pain-predictive module, either previously identified elementary regions or a single best large-scale cortical resting-state network module; (b) selected cortical-subcortical systems related to evoked pain in prior literature ( multi-system models); and (c) a model spanning the full brain. We estimate the accuracy of pain intensity predictions using cross validation (7 studies) and subsequently validate in three independent holdout studies. All spatial scales convey information about pain intensity, but distributed, multi-system models better characterize pain representations than any individual region or network (e.g. multisystem models explain >20% more of individual subject pain ratings than the best elementary region). Full brain models showed no predictive advantage over multi-system models. These findings quantify the extent that representation of evoked pain experience is distributed across multiple cortical and subcortical systems, show that pain representation is not circumscribed by any elementary region or conical network, and provide a blueprint for identifying the spatial scale of information in other domains. Significance StatementWe define modular, multisystem and global views of brain function, use multivariate fMRI decoding to characterize pain representations at each level, and provide evidence for a multisystem representation of evoked pain. We further show that local views necessarily exclude important components of pain representation, while a global full brain representation is superfluous, even though both are viable frameworks for representing pain. These findings quantitatively juxtapose and reconcile divergent conclusions from evoked pain studies within a generalized neuroscientific framework, and provide a blueprint for investigating representational architecture for diverse brain processes.

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