AUTHOR=Calvet Emmanuel , Reulet Bertrand , Rouat Jean 

TITLE=The connectivity degree controls the difficulty in reservoir design of random boolean networks

JOURNAL=Frontiers in Computational Neuroscience

VOLUME=18

YEAR=2024

URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2024.1348138

DOI=10.3389/fncom.2024.1348138

ISSN=1662-5188

ABSTRACT=<p>Reservoir Computing (RC) is a paradigm in artificial intelligence where a recurrent neural network (RNN) is used to process temporal data, leveraging the inherent dynamical properties of the reservoir to perform complex computations. In the realm of RC, the excitatory-inhibitory balance <italic>b</italic> has been shown to be pivotal for driving the dynamics and performance of Echo State Networks (ESN) and, more recently, Random Boolean Network (RBN). However, the relationship between <italic>b</italic> and other parameters of the network is still poorly understood. This article explores how the interplay of the balance <italic>b</italic>, the connectivity degree <italic>K</italic> (i.e., the number of synapses per neuron) and the size of the network (i.e., the number of neurons <italic>N</italic>) influences the dynamics and performance (memory and prediction) of an RBN reservoir. Our findings reveal that <italic>K</italic> and <italic>b</italic> are strongly tied in optimal reservoirs. Reservoirs with high <italic>K</italic> have two optimal balances, one for globally inhibitory networks (<italic>b</italic> &lt; 0), and the other one for excitatory networks (<italic>b</italic> &gt; 0). Both show asymmetric performances about a zero balance. In contrast, for moderate <italic>K</italic>, the optimal value being <italic>K</italic> = 4, best reservoirs are obtained when excitation and inhibition almost, but not exactly, balance each other. For almost all <italic>K</italic>, the influence of the size is such that increasing <italic>N</italic> leads to better performance, even with very large values of <italic>N</italic>. Our investigation provides clear directions to generate optimal reservoirs or reservoirs with constraints on size or connectivity.</p>