Biology subjects

Zeithamova, D.

Publications and source records attributed to Zeithamova, D..

5 recordsLinked to original sources

bioRxiv2026

From cognitive abstraction to adaptive behavior: neural bases of concept learning in autistic adolescents

BACKGROUNDLearned knowledge does not consistently generalize to new contexts in autistic individuals, limiting potential for adapting to real-world demands. This challenge is hypothesized to stem from difficulties with forming abstract representations, potentially arising from perceptual processing that favors local details over the gestalt. We tested the prediction that generalization would be primarily based on exemplar-specific representations in autistic youth using computational modelling coupled with neuroimaging. METHODSSixty-four autistic adolescents without intellectual disability (69% males; ages 14-18 years) completed a category generalization task during functional magnetic resonance imaging at two time points. Computational models estimated abstract (prototype-based) and specific (exemplar-based) representations and underlying neural correlates. We further examined associations with adaptive functioning and moderation by autistic traits. RESULTSContrary to predictions, we observed a consistent prototype-dominant majority, a subgroup who generalized without consistent representational reliance, and a small minority who failed to acquire category structure. Prototypes were represented in bilateral ventromedial prefrontal cortex (VMPFC), inferior parietal lobule (IPL), right frontal pole, and right lateral occipital cortex, while exemplars were represented in bilateral cuneus. Better generalization predicted better real-world adaptive functioning. Moreover, greater prototype-related activation in left IPL predicted better adaptive functioning in participants with higher autistic traits. CONCLUSIONSThese findings challenge the prevailing view that concept learning in autism relies primarily on hyper-specific perceptual processing, identify meaningful variability in representational strategies, and reveal neural pathways through which abstract representation may support real-world adaptive behavior.

neuroscience↗

bioRxiv2025

Ventromedial prefrontal cortex supports prototype representations in healthy older adults

The ability to learn broad concepts from individual instances is relevant throughout our lifespans as new concepts enter the world, and we seek to acquire new skills and hobbies that can enrich our lives. While older age has been associated with declines in the ability to remember individual instances, less is known about how these declines impact concept learning and generalization or the neural systems that older adults recruit to support abstraction. In the present study, we used prototype-based category learning as a domain to test age differences in concept learning. Young and older adults completed a category-learning task while undergoing fMRI. We fit formal prototype and exemplar models to behavioral and brain data to index concept learning based on abstraction versus memory for individual category members. We found that the fit of both models to behavior was poorer in older adults, but older adults were more likely than young adults to be best fit by the prototype model and less likely to be best fit by the exemplar model. While only young adults showed significant prototype-tracking in the hippocampus, both young and older adults recruited the ventromedial prefrontal cortex (VMPFC) to support prototype-based generalization. Although evidence for age differences in prototype representations emerged in a whole-brain analysis, evidence for age differences were weak in the VMPFC and hippocampus. Thus, engagement of the VMPFC prototype-learning system may help maintain concept generalization in older adults.

neuroscience↗

bioRxiv2024

Age differences in functional connectivity track dedifferentiation of category representations

With advancing age, the distinctiveness of neural representations of information declines. While the finding of this so-called age-related neural dedifferentiation in category-selective neural regions is well-described, how neural dedifferentiation manifests at the level of large-scale functional networks is less understood. Furthermore, the relationship between age-related changes in network organization and dedifferentiation is unknown. Here, we investigated age-related neural dedifferentiation of category-selective regions as well as whole-brain functional networks. We additionally examined age differences in connectivity of category-selective regions to the rest of the brain. Younger and older adults viewed blocks of face and house stimuli while performing memory encoding and retrieval in the fMRI scanner. We found an age-related decline in neural distinctiveness for faces in the fusiform gyrus (FG) and for houses in the parahippocampal gyrus (PHG). Functional connectivity analyses revealed age-related dedifferentiation of global network structure as well as age differences in the connectivity profiles to category-selective regions. Together, our findings suggest that age-related neural dedifferentiation manifests both in regional categorical representations as well as in whole- brain functional networks. HighlightsO_LICategory representations are less distinctive, or dedifferentiated, in older adults C_LIO_LIFunctional networks are less segregated in older adults C_LIO_LIOlder adults reveal less connectivity between fusiform gyrus and visual cortices C_LI

neuroscience↗

bioRxiv2022

Evaluating methods for measuring background connectivity in slow event-related functional MRI designs

Resting-state functional MRI (fMRI) is widely used for measuring functional interactions between brain regions, significantly contributing to our understanding of large-scale brain networks and brain-behavior relationships. Furthermore, idiosyncratic patterns of resting-state connections can be leveraged to identify individuals and predict individual differences in clinical symptoms, cognitive abilities, and other individual factors. Idiosyncratic connectivity patters are thought to persist across task states, suggesting task-based fMRI can be similarly leveraged for individual differences analyses. Here, we tested the degree to which functional interactions occurring in the background of a task during slow event-related fMRI parallel or differ from those captured during resting-state fMRI. We compared two approaches for removing task- evoked activity from task-based fMRI: (1) applying a low-pass filter to remove task- related frequencies in the signal, or (2) extracting residuals from a general linear model (GLM) that accounts for task-evoked responses. We found that the organization of large-scale cortical networks and individuals idiosyncratic connectivity patterns are preserved during task-based fMRI. In contrast, individual differences in connection strength can vary more substantially between rest and task. Compared to low-pass filtering, background connectivity obtained from GLM residuals produced idiosyncratic connectivity patterns and individual differences in connection strength that more resembled rest. However, all background connectivity measures were highly similar when derived from the low-pass filtered signal or GLM residuals, indicating that both methods are suitable for measuring background connectivity. Together, our results highlight new avenues for the analysis of task-based fMRI datasets and the utility of each background connectivity method.

neuroscience↗

bioRxiv2020

Model-based fMRI reveals co-existing specific and generalized concept representations

There has been a long-standing debate about whether categories are represented by individual category members (exemplars) or by the central tendency abstracted from individual members (prototypes). Across neuroimaging studies, there has been neural evidence for either exemplar representations or prototype representations, but not both. In the present study, we asked whether it is possible for individuals to form multiple types of category representations within a single task. We designed a categorization task to promote both exemplar and prototype representations, and we tracked their formation across learning. We found evidence for co-existing prototype and exemplar representations in brain in regions that aligned with previous studies: prototypes in ventromedial prefrontal cortex and anterior hippocampus and exemplars in inferior frontal gyrus and lateral parietal cortex. These findings show that, under the right circumstances, individuals may form representations at multiple levels of specificity, potentially facilitating a broad range of future memory-based decisions.

neuroscience↗