In this episode, Matt sits down with Gaurav Vankataraman (Trisk Bio) to talk about how human memory is physically realized. Click here to download episode 146 of Elucidations.
Where do your memories live? In the brain, right? They’re, like, imprinted there somehow? We often think of memories as analogous with recordings, like when you do an audio recording and the air vibrations get translated into an electrical signal which reorients the magnetic particles on some tape. But is that really how it works? Is the brain some tape waiting to get recorded to, or a hard drive waiting to get data written to it? We don’t exactly have definitive answers to those questions, but in this episode, our distinguished guest discusses a line of research into whether memories could be stored outside the brain, in RNA. He then notes that there is also a lot of RNA in the human brain itself, which means that a similar mechanism for storing memories could exist there as well.
This research, as it turns out, originated in some rather astonishing scientific work from the 1950s involving planarian flatworms. Planarian flatworms have the extraordinary ability to regenerate: if you cut one in half, each of the two halves can actually grow back into a new worm. At that time, there was some preliminary evidence to suggest that if a planarian flatworm learned something, and you cut it in half, when the half that didn’t have a brain grew back, it still retained what the original worm had learned. What the what? It could remember something even though it had a brand new brain? Those initial studies went through a period of being discredited, but in recent years a number of researchers have been exploring new, more rigorous evidence that something of this nature could be going on. Perhaps the flatworms could actually be storing some of their memories in their RNA or DNA, and perhaps RNA has the ability to preserve some of that information both in and outside of the brain.
In this episode, our guest argues that the RNA in the brain not responsible for making proteins (called non-coding RNA) has a specific type of mathematical structure that is particularly well-suited for transmitting information both fast and accurately. Not only that, but entities with that kind of structure transmit information more accurately the faster they transmit it. So the fact that RNA in the brain is structurally arranged in the way it is actually makes it a viable candidate for being sort of like the brain’s “software” for storing and manipulating memories.
I was absolutely hooked on what Gaurav Venkataraman had to say from the moment we started recording. Give it a listen and see if you feel the same way!
Further Resources
If you’d like to do a deep research dive into what we talked about in this episode, let’s begin by highlighting Gaurav Venkataraman’s big research paper in this area, written in collaboration with Eric Miska and David Jordan:
Processive and distributive non-equilibrium networks discriminate in alternate limits
Next, he discussed the following Phillip Agre paper on mental representations:
Two articles on synaptic memory:
Reinstatement of long-term memory following erasure of its behavioral and synaptic expression in Aplysia
Memory. Engram cells retain memory under retrograde amnesia
Kerry Ressler’s work:
Parental olfactory experience influences behavior and neural structure in subsequent generations
A review article by Eric Miska:
A review article on paradigm shifts in where we think memories are stored:
The Demise of the Synapse As the Locus of Memory: A Looming Paradigm Shift?
Book chapter on the social science research that revived this work:
On memory in bacteria:
Behavioral diversity in microbes and low-dimensional phenotypic spaces
Implementing a finite state machine in a single cell:
A unicellular walker controlled by a microtubule-based finite-state machine
Four articles on single-cell learning:
Self-organized computation in the far-from-equilibrium cell
A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote
Cellular Cognition: Sequential Logic in a Giant Protist
Reconsidering the evidence for learning in single cells
On RNA memory:
On natural universal computation:
Single-cell learning in neurons, driving behavior:
Biochemical computation underlying behavioral decision-making
Neural network-style pattern recognition with molecues:
Pattern recognition in the nucleation kinetics of non-equilibrium self-assembly
Evidence of memory localized to a single cell in a neuron:
Memory trace and timing mechanism localized to cerebellar Purkinje cells
Happy reading!
Matt Teichman