Biology subjects

Yonelinas, A. P.

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

5 recordsLinked to original sources

bioRxiv2025

Model-based EEG phenotyping uncovers distinct neurocomputational mechanisms underlying learning impairments across psychopathologies

BackgroundMajor depressive disorder (MDD), bipolar disorder (BP), and schizophrenia (SCZ) involve learning impairments with poorly understood mechanisms. Understanding both the similarities and differences in these mechanisms is important to guide the development of new, targeted interventions. Methods255 participants diagnosed with MDD (n=54), BP (n=47), SCZ (n=67) or without any diagnoses (CTRL; n=87) performed an associative learning task. Computational modeling quantified the mechanistic interplay between working memory (WM) and reinforcement learning (RL). The latent RL and WM signatures in the EEG dynamics showed shared and distinct neurocognitive mechanisms underlying learning. ResultsAll clinical groups showed learning impairments at the behavioral level. Model-based EEG analyses linked these impairments to distinct patterns in the dynamic interplay between latent RL and WM mechanisms, contrasting with the typical patterns observed in CTRL. SCZ was characterized by reduced neural markers of WM, weakening the cooperative influence of WM onto RL (reduced WM recruitment), and reduced integration of negative feedback. Conversely, MDD was characterized by reduced reciprocal influence of RL onto WM, reducing the tendency to upregulate WM contribution with reward history (impaired WM management). Finally, BP was characterized by deficits in both WM and RL recruitment, along with higher WM decay. ConclusionsBehavioral learning impairments that appear similar across clinical groups can be linked to distinct neurocognitive mechanisms via integrative neurocomputational modeling. Our approach provides insights into the interplay of underlying learning mechanisms and how they manifest differently across psychopathologies. CitationThis manuscript is a preprint version of the later manuscript accepted for publication in Biological Psychiatry: Global Open Science. The content may differ from the final published version following peer review and editorial revisions. Ging-Jehli, N.R., Rac-Lubashevsky, R., Bera, K., Roberts, A., Loder, A., Boudewyn, M.A., Carter, C.S., Erickson, M., Gold, J., Luck, S.J., Ragland, J.D., Yonelinas, A.P., MacDonald III, A.W., Barch, D.M., & Frank, M.J. (2025). Model-based EEG phenotyping uncovers distinct neurocomputational mechanisms underlying learning impairments across psychopathologies. Preprint at bioRxiv.

pathology↗

bioRxiv2021

Relationships between individual differences in dual process and electrophysiological signatures of familiarity and recollection during retrieval

Our everyday memories can vary in terms of accuracy and phenomenology. According to one theoretical account, these differences hinge on whether the memories contain information about both an item itself as well as associated details (remember) versus those that are devoid of these associated contextual details (familiar). This distinction has been supported by computational modeling of behavior, studies in patients, and neuroimaging work including differences both in electrophysiological and functional magnetic resonance imaging. At present, however, little evidence has emerged to suggest that neurophysiological measures track individual differences in estimates of recollection and familiarity. Here, we conducted electrophysiological recordings of brain activity during a recognition memory task designed to differentiate between behavioral indices of recollection and familiarity. Non-parametric cluster-based permutation analyses revealed associations between electrophysiological signatures of familiarity and recollection with their respective behavioral estimates. These results support the idea that recollection and familiarity are distinct phenomena and is the first, to our knowledge, to identify distinct electrophysiological signatures that track individual differences in these processes.

neuroscience↗

bioRxiv2018

The role of the fornix in human navigational learning

Studies in rodents have demonstrated that transecting the white matter pathway linking the hippocampus and anterior thalamic nuclei - the fornix - impairs flexible navigational learning in the Morris Water Maze (MWM), as well as similar spatial learning tasks. While diffusion MRI studies in humans have linked fornix microstructure to scene discrimination and memory, its role in human navigation is currently unknown. We used high-angular resolution diffusion MRI to ask whether inter-individual differences in fornix microstructure would be associated with spatial learning in a virtual MWM task. To increase sensitivity to individual learning across trials, we adopted a novel curve fitting approach to estimate a single index of learning rate. We found a significant correlation between learning rate and the microstructure (mean diffusivity) of the fornix, but not that of a control tract linking occipital and anterior temporal cortices (the inferior longitudinal fasciculus, ILF). Further, this correlation remained significant when controlling for hippocampal volume. These findings extend previous animal studies by demonstrating the functional relevance of the fornix for human navigational learning, and highlight the importance of a distributed neuroanatomical network, underpinned by key white matter pathways, such as the fornix, in complex spatial behaviour.

neuroscience↗

bioRxiv2018

Dissociable medial temporal pathways for encoding emotional item and context information

Emotional experiences are typically remembered with a greater sense of recollection than neutral experiences, but memory benefits for emotional items do not typically extend to their source contexts. Item and source memory have been attributed to different subregions of the medial temporal lobes (MTL), but it is unclear how emotional item recollection fits into existing models of MTL function and, in particular, what is the role of the hippocampus. To address these issues, we used high-resolution functional magnetic resonance imaging (fMRI) to examine MTL contributions to successful emotional item and context encoding. The results showed that emotional items were recollected more often than neutral items. Whereas amygdala and perirhinal cortex (PRC) activity supported the recollection advantage for emotional items, hippocampal and parahippocampal cortex activity predicted subsequent source memory for both types of items, reflecting a double dissociation between anterior and posterior MTL regions. In addition, amygdala activity during encoding modulated the relationships of PRC activity and hippocampal activity to subsequent item recollection and source memory, respectively. Specifically, whereas PRC activity best predicted subsequent item recollection when amygdala activity was relatively low, hippocampal activity best predicted source memory when amygdala activity was relatively high. We interpret these findings in terms of complementary compared to synergistic amygdala-MTL interactions. The results suggest that emotion-related enhancements in item recollection are supported by an amygdala-PRC pathway, which is separable from the hippocampal pathway that binds items to their source context.

neuroscience↗

bioRxiv2017

CA1 And CA3 Differentially Support Spontaneous Retrieval Of Episodic Contexts Within Human Hippocampal Subfields

The hippocampus plays a critical role in spatial and episodic memory. Mechanistic models predict that hippocampal subfields have computational specializations that differentially support memory. However, there is little empirical evidence suggesting differences between the subfields, particularly in humans. To clarify how hippocampal subfields support human spatial and episodic memory, we developed a virtual reality paradigm where participants passively navigated through houses (spatial contexts) across a series of videos (episodic contexts). We then used multivariate analyses of high-resolution fMRI data to identify neural representations of contextual information during recollection. Multi-voxel pattern similarity analyses revealed that CA1 represented objects that shared an episodic context as more similar than those from different episodic contexts. CA23DG showed the opposite pattern, differentiating between objects encountered in the same episodic context. The complementary characteristics of these subfields explain how we can parse our experiences into cohesive episodes while retaining the specific details that support vivid recollection.

neuroscience↗