Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks.

Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks.

Signal neutrality, scalar property, and collapsing boundaries as consequences of a learned multi-timescale strategy.

We postulate that three fundamental elements underlie a decision making process: perception of time passing, information processing in multiple timescales and reward maximisation. We build a simple reinforcement learning agent upon these principles that we train on a random dot-like task. Our results, similar to the experimental data, demonstrate three emerging signatures.

SpaRCe: Improved Learning of Reservoir Computing Systems Through Sparse Representations.

"Sparse" neural networks, in which relatively few neurons or connections are active, are common in both machine learning and neuroscience. While, in machine learning, "sparsity" is related to a penalty term that leads to some connecting weights becoming small or zero, in biological brains, sparsity is often created when high spiking thresholds prevent neuronal activity. Here, we introduce sparsity into a reservoir computing network via neuron-specific learnable thresholds of activity, allowing neurons with low thresholds to contribute to decision-making but suppressing information from neurons with high thresholds.

Estimating the impact of COVID-19 pandemic on services provided by Italian Neuromuscular Centers: an Italian Association of Myology survey of the acute phase.

Introduction: Since February 2020, the outbreak of COVID-19 in Italy has forced the health care system to undergo profound rearrangements in its services and facilities, especially in the worst-hit areas in Northern Italy. In this setting, inpatient and outpatient services had to rethink and reorganize their activities to meet the needs of patients during the "lockdown". The Italian Association of Myology developed a survey to estimate the impact of these changes on patients affected by neuromuscular disorders and on specialized neuromuscular centers during the acute phase of COVID-19 pandemic.