As mentioned in the previous post, this is the first installment of BrainStorm, a section of ideas I have under development, but don’t have the time to physically work on. This section will contain organically developed ideas, organized by project. Reader feedback is encouraged.
How can we identify the group of neurons that encode a particular thought?
I don’t want to simply see correlations of in activity of a few scattered neurons with a given thought, but identify the entire neuronal ensemble. Which neurons are active at a precise moment in a task? How are they wired together? Which are the drivers of activity?
Existing technology is inadequate to identify the entire neural ensemble that encodes a thought. Immediate early gene expression patterns have not been shown to be precisely correlated with brain activity, and have a temporal resolution on the order of minutes. Genetically encoded calcium sensors (GECIs) have the necessary temporal and spatial resolution, but their response is nearly as fleeting as a thought, making it impossible to simultaneously record from networks of thousands of possible participants with current microscopy techniques.
In BrainStorm 1, I will outline a technology, photoswitchable genetically-encoded calcium memory sensors, that can identify all the neurons in a large network that are active during user-specified, aribitrarly brief or long time periods. I will propose four potential strategies for construction of these sensors, and detail practical considerations for sensor design, screening and application.