Categorization, the grouping of similar objects, actions, or events, is fundamental to adaptive behavior. Traditionally, neuroscience assumes it begins with feature detection following to, as a final stage, assigning representations stored in memory. We review converging evidence from neuroanatomy, electrophysiology, brain imaging and cognitive science to suggest a different view: Categorization is not the end stage of perception but occurs throughout signal processing, from the very beginning. It is a core computational strategy of the brain, implemented through predictive feedback signals that organize feedforward processing. Implications for theory, future research, and neuropsychiatric disorders are discussed.

The hypothalamus plays an important role in the regulation of the bodys metabolic state and behaviors related to survival. Despite its importance however, many questions exist regarding the intrinsic and extrinsic connections of the hypothalamus in humans, especially its relationship with the cortex. As a heterogeneous structure, it is possible that the hypothalamus is composed of different subregions, which have their own distinct relationships with the cortex. Previous work on functional connectivity in the human hypothalamus have either treated it as a unitary structure or relied on methodological approaches that are limited in modeling its intrinsic functional architecture. Here, we used resting state data from ultrahigh field 7 Tesla fMRI and a data driven analytical approach to identify functional subregions of the human hypothalamus. Our approach identified four functional hypothalamic subregions based on intrinsic functional connectivity, which in turn showed distinct patterns of functional connectivity with cortex. Overall, all hypothalamic subregions showed stronger connectivity with a cortical network, Cortical Network 1 composed primarily of frontal, midline, and limbic cortical areas and weaker connectivity with a second cortical network composed largely of posterior sensorimotor regions, Cortical Network 2. Of the hypothalamic subregions, the anterior hypothalamus showed the strongest connection to Cortical Network 1, while a more ventral subregion containing the anterior hypothalamus extending to the tuberal region showed the weakest connectivity. The findings support the use of ultrahigh field, high resolution imaging in providing a more incisive investigation of the human hypothalamus that respects its complex internal structure and extrinsic functional architecture.

This paper uses a generative neural network architecture combining unsupervised (generative) and supervised (discriminative) models with a model comparison strategy to evaluate assumptions about the mappings between brain states and behavior. Most modeling in cognitive neuroscience publications assume a one-to-one brain-behavior relationship that is linear, but never test these assumptions or the consequences of violating them. We systematically varied these assumptions using simulations of four ground-truth brain-behavior mappings that involve progressively more complex relationships, ranging from one-to-one linear mappings to many-to-one nonlinear mappings. We then applied our Variational AutoEncoder-Classifier framework to the simulations to show how it accurately captured diverse brain-behavior mappings,provided evidence regarding which assumptions are supported by the data, and illustrated the problems that arise when assumptions are violated. This integrated approach offers a reliable foundation for cognitive neuroscience to effectively model complex neural and behavioral processes, allowing more justified conclusions about the nature of brain-behavior mappings.

In psychology and neuroscience, scientific questions are often framed in terms of mental activity (e.g., cognition, emotion, and perception); however, the brain is an organ with a particular function that only it can fulfill. Converging evidence suggests that this function is allostasis: the predictive regulation of competing demands from internal bodily systems. We review evidence for a distributed allostatic system that organizes whole-brain signaling, scaffolds psychological phenomena, and places bodily regulation at the core of brain structure. We also demonstrate, with an example from Alzheimer's disease, how an "allostasis-first" perspective might transform hypothesis generation in the context of neurological health and disease. In sum, the common conception that the brain is primarily for thinking, or other cognitive processes, is potentially misleading, and neuroscience may benefit from a theoretical structure that centers on basic questions of how the brain coordinates and efficiently regulates the body.

A recently published paper by van Heijst, Kret and Ploeger (2024) attempts to reconcile tworesearch traditions in the science of emotion — basic emotion theory and the theory of constructedemotion — by suggesting that the former explains emotions as bioregulatory states of the bodywhereas the latter explains feelings that arise from those state changes. This bifurcation of emotioninto objective physiological states and subjective feeling involves three misleading simplificationsthat fundamentally misrepresent the theory of constructed emotion. Our commentary identifiesthese misleading simplifications and the resulting factual errors, empirical oversights, andevolutionary oversimplifications. We then discuss why such errors will continue to arise untilscientists realize that the two theories are intrinsically irreconcilable. They rest on incommensurateassumptions and require different methods of evaluation. Only by directly considering thesedifferences will these research silos in the science of emotion finally dissolve, speeding theaccumulation of trustworthy scientific knowledge about emotion that is usable in the real world.

In the science of emotion, it is widely assumed that folk emotion categories form a biological and psychological typology, and studies are routinely designed and analyzed to identify emotion-specific patterns. This approach shapes the observations that studies report, ultimately reinforcing the assumption that guided the investigation. Here, we reanalyzed data from one such typologically-guided study that reported mappings between individual brain patterns and group-averaged ratings of 34 emotion categories. Our reanalysis was guided by an alternative view of emotion categories as populations of variable, situated instances, and which predicts a priori that there will be significant variation in brain patterns within a category across instances. Correspondingly, our analysis made minimal assumptions about the structure of the variance present in the data. As predicted, we did not observe the original mappings and instead observed significant variation across individuals. These findings demonstrate how starting assumptions can ultimately impact scientific conclusions and suggest that a hypothesis must be supported using multiple analytic methods before it is taken seriously.

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.

The brain continuously anticipates the body’s energetic needs and prepares to meet them before they arise—a process called allostasis. To support allostasis, the brain continually models the body’s sensory state, a process known as interoception. Here we replicate and extend a large-scale system that supports allostasis and interoception in the human brain using ultrahigh precision 7 Tesla functional magnetic resonance imaging ( n = 90), improving precision in subgenual and pregenual anterior cingulate topography and expanding brainstem nuclei mapping. Our functional connectivity analyses provide corroborating evidence for more than 96% of the anatomical connections documented in nonhuman animal tract-tracing studies. This system also includes regions of dense intrinsic connectivity throughout the system, some of which were identified previously as part of the backbone of neural communication across the brain. These results reinforce the existing evidence for a whole-brain system that supports the modeling and regulation of the body’s internal milieu.

When investigating the brain, bodily, or behavioral correlates of emotional experience, researchers often present participants with stimuli that are assumed to reliably and exclusively evoke an instance of one, and only one, emotion category across participants (e.g., a fear stimulus, a joy stimulus, and so on). These assumptions are driven by a typological view. Here, we tested the extent to which they are met. Across three studies (total N = 453), participants reported their experiences as they viewed silent video clips or static images that were curated from published studies and from online search engines. Two different response formats were used. Overall, the proportion of stimulus-evoked emotion experiences that met even lenient benchmarks for validity and reliability for labeling a stimulus as pertaining to a single emotion category label was exceedingly low. Furthermore, participants frequently used more than one label for a given instance. The findings suggest that typological assumptions, and the nomothetic approach they align with, rely on assumptions that are rarely, if ever, met in stimulus-evoked paradigms. Correspondingly, the use of group-averaged normative ratings masks tremendous variation that is potentially meaningful. An overreliance on these norms may lead to conclusions that emotions are organized as discrete categories, yet these theory-laden conclusions may have limited generalizability regarding the emotional experiences of individual people during these tasks. Rather, emotional experiences evoked by visual stimuli are multifaceted (i.e., involve multiple labels per instance) and vary tremendously across individuals. Future work may benefit from multifaceted measurement of emotion and idiographic, data-driven modeling approaches. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

A recently published article by van Heijst et al. attempted to reconcile two research approaches in the science of emotion-basic emotion theory and the theory of constructed emotion-by suggesting that the former explains emotions as bioregulatory states of the body whereas the latter explains feelings that arise from those state changes. This bifurcation of emotion into objective physical states and subjective feelings involves three misleading simplifications that fundamentally misrepresent the theory of constructed emotion and prevent progress in the science of emotion. In this article we identify these misleading simplifications and the resulting factual errors, empirical oversights, and evolutionary oversimplifications. We then discuss why such errors will continue to arise until scientists realize that the two theories are intrinsically irreconcilable. They rest on incommensurate assumptions and require different methods of evaluation. Only by directly considering these differences will these research silos in the science of emotion finally dissolve, speeding the accumulation of trustworthy scientific knowledge about emotion that is usable in the real world.

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.

This paper suggests cultivating and modeling individual variation in research on affect and emotion, emphasizing the importance of studying real-world contexts to reveal their individualized nature. We propose a new standard for study design using more flexible and context-aware methods that emphasize modeling of high-dimensional signal arrays within individuals and then inductively learning generalizations rather than presuming their existence. We compare laboratory and real-life settings for the study of affect and emotion and highlight opportunities for studying individual variation structured by context. We discuss current challenges and future directions therein and emphasize the need for interdisciplinary and international collaboration and leveraging new technologies.