Neurosalience #S4E7 with Evan Gordon - Deep Sampling of fMRI Data: This is the way
Jan 5, 2024
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Exploring deep sampling of fMRI data with Dr. Evan Gordon, uncovering unique connectivity patterns and effector-specific regions in the motor cortex. Delving into advancements in individual brain mapping and variances in neural networks. Discussing brain evolution, motor cortex expansion, and the ongoing need for detailed brain mapping.
Effector-specific regions in the motor cortex challenge traditional brain maps and reveal insights into whole-body movements.
High-quality data and appropriate prior knowledge are essential for uncovering unexpected brain connectivity findings.
Inter-effector regions in the motor cortex may have evolutionary significance in coordinating whole-body movements across species.
Deep dives
Discovery of Effector-Specific Regions Within the Motor Cortex
Researchers have made an intriguing discovery within the motor cortex, finding effector-specific regions between the familiar hand, foot, and face areas. This finding challenges the traditional Penfield homunculus map and opens up new understandings of motor organization in the brain. These inter-effector regions have unique connectivity patterns, exhibiting strong connections within the hemisphere and across hemispheres similar to the face area. Additionally, they exhibit distinctive connectivity with the medial prefrontal regions associated with error detection and top-level control. This discovery suggests that these inter-effector regions play a role in integrated whole-body movements and are linked to regions involved in goal setting and action planning.
Priors and the Importance of High-Quality Data
The discovery of the effector-specific regions within the motor cortex highlights the importance of having the right priors and high-quality data when studying brain connectivity. The researchers emphasize that good data quality allows for the recognition of unexpected findings, even if they challenge established knowledge or traditional teaching. The ability to trust and explore these novel connections is crucial in uncovering previously unseen aspects of brain organization. With precision-mapped data and better data quality, new discoveries and understandings can arise, even in well-studied brain areas like the motor cortex.
Implications for Evolution and Integrated Whole-Body Movements
The discovery of inter-effector regions and their strong connectivity with regions involved in integrated whole-body movements suggests a potential evolutionary significance. These regions may play a role in coordinating movements across multiple effector systems in a task-independent manner. The findings align with neurosurgical evidence showing regions responsive to any type of motor movement. This suggests that the inter-effector system may be evolutionarily older and more prevalent in organisms that require coordinated whole-body movements rather than fine control of isolated effectors. Further research may shed light on the unique functions and adaptations of these inter-effector regions.
Boundary-based parcellation approach for mapping cortical areas
The podcast discusses the boundary-based parcellation approach used for mapping cortical areas in the brain. This approach, inspired by invasive anatomical studies, focuses on detecting abrupt changes in different properties at the boundaries of cortical areas. It emphasizes that the boundary-based approach is conceptually closest to how areas are defined in invasive anatomy, making it a valuable method for mapping cortical areas in non-invasive studies. Examples of boundary-based parcellation approaches used by different researchers are mentioned, including the work of Alex Cohen, Tim Lauman, Matt Glasser, and Thomas Yo.
Understanding the subdivisions within cortical areas and their functional relevance
The podcast delves into the concept of subdivisions within cortical areas and their functional relevance. It highlights that cortical areas are not homogenous entities, but consist of topographic subdivisions with distinct functional properties. The example of the motor strip is given, where the classic cortical area BA4 is functionally subdivided despite lacking architectonic subdivisions. The significance of these functional subdivisions, particularly in relation to conditions like chronic pain and depression, is emphasized. The podcast also discusses the potential of F-MRI in precision mapping and its relevance to clinical treatments that require localization for optimal efficacy.
Today, we are excited to have Dr. Evan Gordon on the podcast. Evan is an assistant professor in the Neuroimaging Labs Research Center, based in the Mallinckrodt Institute of Radiology at the Washington University School of Medicine in St. Louis. Since joining the group and joining forces with what is known as the "midnight scan club," he has gone on a scientific tear, publishing several highly influential papers that make use of the unique high-fidelity data sets, containing up to 11 hours of resting state or task-activated fMRI data for each subject. This powerful approach in fMRI is known as "deep sampling." His findings include insights into unique individual connectivity patterns, the whole brain use of a novel parcellation approach using boundary maps, and most recently, discovery of effector-specific regions in motor cortex - a finding which is likely to replace in textbooks the classic Penfield maps of the homunculus.
This was a wonderful conversation where we explored the implementation, benefits, and potential of deep sampling of fMRI data! Evan is not only a creative and productive scientist, but a great conversationalist. We hope you enjoy it!
Episode producers:
Omer Faruk Gulban
Alfie Wearn
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