# Neuronal mechanisms for sequential activation of memory items: dynamics and reliability

## TL;DR

This paper introduces a biologically inspired model explaining how neural parameters control the activation and transition of memory sequences, differentiating between regular and irregular patterns without changing connectivity.

## Contribution

The model demonstrates how modulation of biological parameters like gain, inhibition, depression, and noise can switch between sequence types, providing insights into neural sequence dynamics.

## Key findings

- Synaptic depression and noise drive sequence transitions.
- Neuronal gain controls switching between regular and irregular sequences.
- Model reproduces biologically plausible sequence activation patterns.

## Abstract

In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences. The switch between the two types of activation occurs through the modulation of biological parameters, without altering the connectivity matrix. Some of the parameters included in our model are neuronal gain, strength of inhibition, synaptic depression and noise. We investigate how these parameters enable the existence of sequences and influence the type of sequences observed. In particular we show that synaptic depression and noise drive the transitions from one memory item to the next and neuronal gain controls the switching between regular and irregular (random) activations.