Why Does the Cortex Have Such a Vast Storage Capacity?
The capacity of long-term memory seems to be extremely large, capable of storing information spanning almost a lifetime. Why does it have such a vast capacity? Why are some memories so enduring? What is the actual physical form of long-term memory? In the movie Inside Out, it is depicted as individu...
Gespeichert in:
Hauptverfasser: | , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | The capacity of long-term memory seems to be extremely large, capable of
storing information spanning almost a lifetime. Why does it have such a vast
capacity? Why are some memories so enduring? What is the actual physical form
of long-term memory? In the movie Inside Out, it is depicted as individual orbs
containing information. Is that really the case? Simply explaining this by
saying that the cortex has many neurons, numerous neural connections, and
complex electrochemical activity between them is not sufficient to answer these
fundamental questions. We need to uncover the theory hidden behind these
phenomena.In essence, a neural network is equivalent to a very large directed
graph, with a massive number of nodes and directed connections. This paper
posits that the physical form of long-term memory is a connected subgraph
within this complex directed graph. This subgraph is capable of linking
together the disparate fragments of the same event, spread across different
sensory cortices, to form associations. This provides a physical realization of
the engram theory. The robustness of the connected subgraph and the resources
it consumes can explain various memory behaviors.Based on anatomical, brain
imaging and electrophysiological evidence, this paper constructs a
probabilistic connectivity model and uses theorems from graph theory to prove
the ease of constructing connected subgraphs. Finally, it explains why the
potential capacity for memory is immense. |
---|---|
DOI: | 10.48550/arxiv.2411.01164 |