STDP forms associations between memory traces in networks of spiking
neurons
C. Pokorny, M. J. Ison, A. Rao, R. Legenstein, C. Papadimitriou, and
W. Maass
Abstract:
Memory traces and associations between them are fundamental for cognitive brain
function. Neuron recordings suggest that distributed assemblies of neurons in
the brain serve as memory traces for spatial information, real-world items,
and concepts. However, there is conflicting evidence regarding neural codes
for associated memory traces. Some studies suggest the emergence of overlaps
between assemblies during an association, while others suggest that the
assemblies themselves remain largely unchanged and new assemblies emerge as
neural codes for associated memory items. Here we study the emergence of
neural codes for associated memory items in a generic computational model of
recurrent networks of spiking neurons with a data-constrained rule for
spike-timing- dependent plasticity. The model depends critically on two
parameters, which control the excitability of neurons and the scale of
initial synaptic weights. By modifying these two parameters, the model can
reproduce both experimental data from the human brain on the fast formation
of associations through emergent overlaps between assemblies, and rodent data
where new neurons are recruited to encode the associated memories. Hence, our
findings suggest that the brain can use both of these two neural codes for
associations, and dynamically switch between them during consolidation.
Reference: C. Pokorny, M. J. Ison, A. Rao, R. Legenstein,
C. Papadimitriou, and W. Maass.
STDP forms associations between memory traces in networks of spiking
neurons.
Cerebral Cortex, 30(3):952-968, 2020.