A Dopamine-Laden meeting with Dr.Alison Adcock
Today I met with Dr.Alison Adcock, core faculty at CCN and the PI of “Motivated Memory Lab” . Here’s a sneak preview of what ” Motivated Memory Lab” focuses on:
“Research in the Adcock laboratory focuses on the neural systems that allow what we desire to influence what we remember, for better and for worse. We use functional Magnetic Resonance Imaging (FMRI) activation (increases in image brightness that reflect changes in the oxygen levels in the brain) to measure how changes in brain activity relate to both motivation and memory.”
I’ll be helping Dr.Adcock with the visualization of mesolimbic reward pathways and VTA circuits by improving the images seen below.
Ventral Tegmental Area responds frequently to NOVELTY and REWARD. The VTA, like the substantia nigra, is populated with dopaminergic neurons that are busy fertilizing cortical excitation areas.
We also talked about brain imaging applications( fsl, SPM, brain voyager, MRICron, AFNI) and their implications on understanding the brain. Certain imaging tools dictate certain representational approaches and obviously there’s a need for improving the readibility / accessibility of imagery.
Dr.Adcock Also introduced me to Dr.Keith Worsley’s work, who’s an expert on visualizing 3d statistical maps (3d data sets) :
Here’s an excerpt from Dr.Worsley’s website:
“the geometry in the title is not the geometry of lines and angles but the geometry of topology, shape and knots. For example, galaxies are not distributed randomly in the universe, but they tend to form clusters, or sometimes strings, or even sheets of high galaxy density. How can this be handled statistically? The Euler characteristic (EC) of the set of high density regions has been used to measure the topology of such shapes; it counts the number of connected components of the set, minus the number of `holes,’ plus the number of `hollows’. Despite its complex definition, the exact expectation of the EC can be found for some simple models, so that observed EC can be compared with expected EC to check the model. A similar problem arises in functional magnetic resonance imaging (fMRI), where the EC is used to detect local increases in brain activity due to an external stimulus. Recent work has extended these ideas to manifolds so that we can detect changes in brain shape via structure masking, surface extraction, and 3D deformation fields. Finally, we look at some curious random fields whose excursion sets are strings, and we show using the Siefert representation that these strings can be knotted.”
It’s fascinating to see “galaxies ” and the “brain” in the same paragraph.
I left Dr.Adcock’s office feeling rejuvenated and inspired (something must have happened up there in my dopaminergic pathways), pursuing 3d visualization of the brain as an architectural space is becoming more and more appealing for many reasons… For one, as Dr.Adcock said:
” We’re carrying these beautiful structures in our head that we’re totally unaware of …”
In a world where seeing is believing , visualizing the obvious beauty of brain structures might change the way we approach/understand/treat our bodies .
