Invited Symposium 2 - Putting the frontal lobe into focus: precision mapping of fine-scale functional organization of prefrontal cortex

Sunday, March 8, 2026, 10:00 am – 12:00 pm PDT, Salon EF

Chair: Caterina Gratton¹; ¹University of Illinois at Urbana-Champaign
Presenters: Caterina Gratton, Moataz Assem, Jinkang (Derrick) Xiang, Kevin Weiner

Prefrontal cortex has long been recognized as a core structure for diverse cognitive processes, including goal-directed ‘cognitive control’, as well as language, social cognition, and decision making. Disruptions to prefrontal cortex are implicated across a number of neurological and psychiatric disorders. Yet, despite its importance, identifying reliable organizational principles within prefrontal cortex has proven challenging. Some accounts propose that prefrontal cortex lacks systematic specialization and fine-scale topography, functioning instead as a flexible hub. However, prefrontal cortex is also a structure that has seen significant evolutionary expansion, has protracted development, and varies substantially even among healthy individuals. Thus, prior approaches that rely on group-averaged data may fail to capture important features in this heterogeneous region. This symposium will highlight emerging insights into prefrontal cortex garnered from ‘precision’ neuroimaging – approaches that focus on fine-scale spatial detail, garnered from repeated measurements across multiple contexts and individualized analytic frameworks. Presenters will showcase work using precision approaches to map resting-state networks, characterize fMRI responses across diverse task and stimulus sets, and delineate detailed anatomical features in humans, alongside complementary neuronal array recordings in nonhuman primates. Each of these studies identifies new patterns of fine-scale specialization and functional topography within the frontal lobe. Collectively, this symposium emphasizes the opportunity for precision neuroimaging to reveal new insights into this complex, but structured, brain region.

Presentations

Precision neuroimaging insights into the network architecture of prefrontal cortex

Caterina Gratton¹; ¹University of Illinois at Urbana-Champaign, USA

Complex cognitive processes are supported by large-scale brain networks: distributed sets of regions with coordinated functions. Group-level analyses have consistently highlighted a large frontoparietal network that lies along the lateral prefrontal cortex (LPFC), with connections to parietal, temporal, and subcortical regions, that is hypothesized to be central to cognitive control. However, while people share a core set of networks, there are substantial individual differences in their layout, particularly in prefrontal cortex. This highlights the need to move beyond group-level maps to focus on individual-level analysis of the frontal lobe – a process that can be facilitated by high sampling ‘precision’ fMRI methods. In this presentation, I will review principles of precision fMRI and its potential to transform our understanding of frontal lobe organization. In the LPFC, we find that group-level maps systematically over-estimate the size of the frontoparietal network and miss important features. The individual LPFC shows a dense interweaving of distinct network regions, validated by both resting-state and task fMRI. Despite individual variability, common motifs reappear across people in the LPFC, suggesting shared organizational rules. These findings underscore the power of precision fMRI to move beyond group-level maps, opening the door to a deeper understanding of the principles that link brain organization and complex cognition.

Category-biased patches encircle core domain-general regions in the human lateral prefrontal cortex

Moataz Assem¹; ¹University of Cambridge, UK

The fine-grained functional organization of the human lateral prefrontal cortex (PFC) remains poorly understood. Previous fMRI studies delineated focal domain-general, or multiple-demand (MD), PFC areas that co-activate during diverse cognitively demanding tasks. Recent precision fMRI studies have revealed interdigitating sensory-biased PFC patches adjacent to MD regions. Here I present evidence that this interdigitated arrangement extends to other functional specializations and may represent a fundamental organizational principle of the PFC. Across three datasets using high-resolution multimodal 3T and 7T MRI approaches of the Human Connectome Project, participants performed cognitive control tasks with visual stimuli spanning diverse categories including faces, places, tools, body parts, geometric shapes, letters and digits. Analyses were performed at the individual subject level. Contrasting each stimulus category against the others revealed focal interdigitated patches of activity adjacent to core MD regions, many representing previously undescribed functional biases in the PFC. Notably, in single subjects activations often fragment into small “dots” of peak activations, possibly reflecting millimeter-scale columnar units seen in invasive animal studies. These findings reveal a recurring motif in which domain-specific and domain-general circuits are interdigitated at a fine spatial scale. This organization likely supports flexible cognitive control by allowing task-relevant signals to feed directly into nearby MD regions, generating control signals tuned to current task demands. These findings also have implications for precision stimulation, multivariate fMRI, and building biologically inspired computational models.

Fine-grained, individual functional organization in primate prefrontal cortex: adaptive across single tasks, stable across many

Jinkang (Derrick) Xiang¹, Da Zhi^2,3, Maedbh King³, Megan Roussy¹, Benjamin Corrigan^1,4, Roberto Gulli⁵, Rogelio Luna⁶, Jörn Diedrichsen¹, Taylor Schmitz¹, Julio Martinez-Trujillo¹, Marieke Mur¹; ¹University of Western Ontario, Canada, ²Massachusetts General Hospital, USA, ³Harvard Medical School, USA, ⁴York University, Canada, ⁵Columbia University, USA, ⁶Universidad Autónoma de Chihuahua, Chihuahua City, Mexico

Primate prefrontal cortex is engaged in a wide range of cognitive tasks that tap into multiple higher-order cognitive functions. However, its functional organization remains poorly understood. Challenges arise due to the mixed selectivity of prefrontal neurons – they often respond to multiple task features, including stimuli, rules, rewards, behavioral context, and their interactions – rendering traditional stimulus mapping approaches unfruitful. It remains unclear whether similarly tuned prefrontal neurons organize into local clustered populations that form functional topographies, as seen in sensory cortices, and if so, whether such maps exhibit shared spatial motifs across tasks. Using monkey array recordings spanning three tasks, we show that prefrontal neural populations with similar selectivity organize into topographic maps at a fine-grained spatial scale. These maps are stable over time yet adaptive from one task to another, while still preserving some spatial motifs. Using human fMRI spanning 26 tasks, we show that there are functional boundaries separating segregated sub-regions of the prefrontal cortex, in addition to the functional gradients hypothesized in the literature. These boundaries are individually specific and generalize across task sets. Together, our results suggest a fine-grained and individually specific functional organization in prefrontal cortex. This organization appears adaptive from one task to the next, yet shows stable patterns across broader task sets. The shared spatial motifs may provide a scaffold for general task execution and functional specialization.

Cognitive, functional, network, and clinical insight from evolutionarily-new brain structures in PFC

Kevin Weiner¹; ¹University of California, Berkeley, USA

There is great interest in understanding the relationship among brain structure, brain function, and cognition - especially in portions of the brain that have expanded the most throughout evolution, such as prefrontal cortex (PFC). PFC also contains brain structures that are evolutionarily-new, some of which are human-specific. Critically, many of these structures disappear on group average templates. Thus, precision imaging and manual definitions of these structures in individual hemispheres is necessary to test the relationship of the morphology of these structures relative to individual differences in cognition, functional representations, and network properties. Such an approach is also ideal for clinical analyses in individual participants. The focus of this talk will be on recent results in lateral PFC, orbitofrontal cortex, and medial prefrontal cortex. Additionally, I will include some comparative analyses across species with mechanistic hypotheses that provide novel theoretical insights. Finally, I will describe new tools that use deep learning algorithms from these thousands of manually defined structures across studies to come closer to automatically identifying them. As the rate limiting step in these studies is the manual definition of these structures, these new, freely available tools aim to bridge the gap between precision imaging and large N studies, which we refer to as scalable precision imaging.