Tag: memory

Representational Drift

Neurons that represented the smell of an apple in May and those that represented the same smell in June were as different from each other as those that represent the smells of apples and grass at any one time. Representational drift occurs in a variety of brain regions besides the piriform cortex. Its existence is clear; everything else is a mystery. How can animals possibly make any lasting sense of the world if their neural responses to that world are constantly in flux? If such flux is common, “there must be mechanisms in the brain that are undiscovered and even unimagined that allow it to keep up.”

Concept Refactoring

If you’ve ever maintained a Wiki, you’ve probably noticed that there is a lot of refactoring involved. Ideas are written down in one place, then rewritten, moved, titles changed, links redirected, pages split and merged.

Hypertext wants to be refactored. This is a feature of hypertext, not a bug. Through constant refactoring, knowledge in a hypertext network evolves to find the right packets for a given domain, where 1 packet = 1 idea. What if we introduced the minimum amount of structure for working with text? Something simple for people, simple for computers, and meaningful for both? That is my goal in experimenting with this new markup language, Subtext. Not formatting, but a kind of minimal markup for making notes legible so software can help you refactor them. “CSV for thought”.

I’ve found the same to be true for blogs with their tags, and better links over time.

Engram

Almost all neuroscientists base their search—for the physical basis of memory (the engram)—on the assumption that temporal-pairing causes learning. They are dedicated to this assumption—even though, as Rescorla pointed out 50 years ago, experimental attempts to define temporal-pairing have always failed. This failure is as striking now as it was 50 years ago. Anything that gets neuroscientists to abandon the idea that temporal-pairing is a useful scientific concept is a step toward discovering the physical basis of memory. Each neuron contains billions of (almost) incomprehensibly-tiny molecular machines. Molecular biologists have developed an astonishing array of techniques for visualizing/manipulating the actions of these little machines. These techniques will allow molecular biologists to follow the machines inside this huge neuron to the engram—to the tiny machine that encodes the experience-gleaned facts so that these learned/remembered facts can inform later behavior.

2021-11-19: This feels like a really big deal:

Biology feels different right now. New broadly enabling technologies and tools are driving forward progress in nearly every specific field at a rapid pace. The large scale adoption and application of a powerful set of common tools has created a virtuous cycle of further technology refinement and engineering. The rate of iteration is increasing, and previously intractable problems are now within reach. While RNA-seq and MPRAs are both valuable approaches, they come with some limitations. Fundamentally, each measurement represents a single static slice of a dynamic process which is only inferred by attempting to piece together the slices. The quality of the reconstruction is limited by sampling density. What if we could measure these systems continually as they occurred in a way that didn’t require destructive sampling? Here, the fundamental idea is that “DNA is the natural medium for biological information storage, and is easily ‘read’ through sequencing.” This forms the basis for this new technology: ENGRAM (ENhancer-driven Genomic Recording of transcriptional Activity in Multiplex). The workflow of this technique is very similar to that of the MPRA introduced above, but with an important twist. Instead of destroying the cell and sequencing a ratio of barcodes, the transcription event is recorded by the insertion of a barcode into a locus of DNA in the cell via prime editing. They went further and showed that they could effectively multiplex this technique by reading out all 3 signals in response to stimulants in a single population of cells. Even more, they showed a proof-of-concept for reading out the order in which events occurred.

Attention & memory

attention and working memory share the same neural mechanisms. Importantly, their work also reveals how neural representations of memories are transformed as they direct behavior.

“When we act on sensory inputs we call it ‘attention. But there’s a similar mechanism that can act on the thoughts we hold in mind.”

RNA Memory

Eventually, the worms recoiled to the light alone. Then something interesting happened when he cut the worms in half. The head of one half of the worm grew a tail and, understandably, retained the memory of its training. Surprisingly, however, the tail, which grew a head and a brain, also retained the memory of its training. If a headless worm can regrow a memory, then where is the memory stored, McConnell wondered. And, if a memory can regenerate, could he transfer it? They had transferred a memory, vaguely but surely, from one animal to another, and they had strong evidence that RNA was the memory-transferring agent. Glanzman now believes that synapses are necessary for the activation of a memory, but that the memory is encoded in the nucleus of the neuron through epigenetic changes.

Earlier research had shown that these epigenetic changes can be inherited. Perhaps phobias are epigenetic?

Memories can be passed down to later generations through genetic switches that allow offspring to inherit the experience of their ancestors.

Chickadee memory

Mountain chickadees remember the location of 80K seeds

Despite weighing less than 15g, mountain chickadees are able to survive harsh winters complete with subzero temperatures, howling winds and heavy snowfall. How do they do it? By spending the fall hiding as many as 80K individual seeds, which they then retrieve — by memory — during the winter. Their astounding ability to keep track of that many locations puts their memory among the most impressive in the animal kingdom.

330 TB memory

Combining these technologies, we were able to read and write data in our laboratory system at a linear density of 818K bits per inch. (For historical reasons, tape engineers around the world measure data density in inches.) In combination with the 246200 tracks per inch that the new technology can handle, our prototype unit achieved an areal density of 201 gigabits per square inch. Assuming that one cartridge can hold 1140 meters of tape—a reasonable assumption, based on the reduced thickness of the new tape media we used—this areal density corresponds to a cartridge capacity of a whopping 330 TB. That means that a single tape cartridge could record as much data as a wheelbarrow full of hard drives.

RRAM

Resistive random access memory (RRAM), could be a better kind of nonvolatile memory. Nonvolatile memory is the basis for flash memory in thumb drives, but flash technology has reached its size and performance limits. For several years, the industry has been hunting for a replacement. RRAM could surpass flash in many key respects: It is potentially faster and less energy-intensive. It also could pack 1TB into a postage stamp. But RRAM has yet to be broadly commercialized because of technical hurdles.