Dissociable Roles of the Dorsolateral and Ventromedial Prefrontal Cortex in Human Categorization.
Matthew B BroschardBrandon M TurnerDaniel TranelJohn H FreemanPublished in: The Journal of neuroscience : the official journal of the Society for Neuroscience (2024)
Models of human categorization predict the prefrontal cortex (PFC) serves a central role in category learning. The dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC) have been implicated in categorization; however, it is unclear whether both are critical for categorization and whether they support unique functions. We administered three categorization tasks to patients with PFC lesions (mean age, 69.6 years; 5 men, 5 women) to examine how the prefrontal subregions contribute to categorization. These included a rule-based (RB) task that was solved via a unidimensional rule, an information integration (II) task that was solved by combining information from two stimulus dimensions, and a deterministic/probabilistic (DP) task with stimulus features that had varying amounts of category-predictive information. Compared with healthy comparison participants, both patient groups had impaired performance. Impairments in the dlPFC patients were largest during the RB task, whereas impairments in the vmPFC patients were largest during the DP task. A hierarchical model was fit to the participants' data to assess learning deficits in the patient groups. PFC damage was correlated with a regularization term that limited updates to attention after each trial. Our results suggest that the PFC, as a whole, is important for learning to orient attention to relevant stimulus information. The dlPFC may be especially important for rule-based learning, whereas the vmPFC may be important for focusing attention on deterministic (highly diagnostic) features and ignoring less predictive features. These results support overarching functions of the dlPFC in executive functioning and the vmPFC in value-based decision-making.
Keyphrases
- prefrontal cortex
- working memory
- end stage renal disease
- newly diagnosed
- endothelial cells
- ejection fraction
- health information
- clinical trial
- pregnant women
- healthcare
- electronic health record
- type diabetes
- insulin resistance
- polycystic ovary syndrome
- adipose tissue
- preterm infants
- patient reported outcomes
- deep learning
- metabolic syndrome
- skeletal muscle
- big data
- preterm birth
- pregnancy outcomes
- double blind