Long-range temporal correlations in scale-free neuromorphic networks.

Netw Neurosci

The MacDiarmid Institute for Advanced Materials and Nanotechnology, School of Physical and Chemical Sciences, Te Kura Matū, University of Canterbury, Christchurch, New Zealand.

Published: April 2020

Biological neuronal networks are the computing engines of the mammalian brain. These networks exhibit structural characteristics such as hierarchical architectures, small-world attributes, and scale-free topologies, providing the basis for the emergence of rich temporal characteristics such as scale-free dynamics and long-range temporal correlations. Devices that have both the topological and the temporal features of a neuronal network would be a significant step toward constructing a neuromorphic system that can emulate the computational ability and energy efficiency of the human brain. Here we use numerical simulations to show that percolating networks of nanoparticles exhibit structural properties that are reminiscent of biological neuronal networks, and then show experimentally that stimulation of percolating networks by an external voltage stimulus produces temporal dynamics that are self-similar, follow power-law scaling, and exhibit long-range temporal correlations. These results are expected to have important implications for the development of neuromorphic devices, especially for those based on the concept of reservoir computing.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286302PMC
http://dx.doi.org/10.1162/netn_a_00128DOI Listing

Publication Analysis

Top Keywords

long-range temporal
12
temporal correlations
12
biological neuronal
8
neuronal networks
8
exhibit structural
8
percolating networks
8
networks
6
temporal
5
correlations scale-free
4
scale-free neuromorphic
4

Similar Publications

The self-assembly of intrinsically disordered proteins (IDPs) into condensed phases and the formation of membrane-less organelles (MLOs) can be considered as the phenomenon of collective behavior. The conformational dynamics of IDPs are essential for their interactions and the formation of a condensed phase. From a physical perspective, collective behavior and the emergence of phase are associated with long-range correlations.

View Article and Find Full Text PDF

Prediction of future input explains lateral connectivity in primary visual cortex.

Curr Biol

January 2025

Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3PT, UK. Electronic address:

Neurons in primary visual cortex (V1) show a remarkable functional specificity in their pre- and postsynaptic partners. Recent work has revealed a variety of wiring biases describing how the short- and long-range connections of V1 neurons relate to their tuning properties. However, it is less clear whether these connectivity rules are based on some underlying principle of cortical organization.

View Article and Find Full Text PDF

In this work, we present a quantitative comparison of the cell division dynamics between populations of intact and regenerating root tips in the plant model system To achieve the required temporal resolution and to sustain it for the duration of the regeneration process, we adopted a live imaging system based on light-sheet fluorescence microscopy, previously developed in the laboratory. We offer a straightforward quantitative analysis of the temporal and spatial patterns of cell division events showing a statistically significant difference in the frequency of mitotic events and spatial separation of mitotic event clusters between intact and regenerating roots.

View Article and Find Full Text PDF

Enhanced Intrusion Detection for ICS Using MS1DCNN and Transformer to Tackle Data Imbalance.

Sensors (Basel)

December 2024

School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300132, China.

With the escalating threat posed by network intrusions, the development of efficient intrusion detection systems (IDSs) has become imperative. This study focuses on improving detection performance in programmable logic controller (PLC) network security while addressing challenges related to data imbalance and long-tail distributions. A dataset containing five types of attacks targeting programmable logic controllers (PLCs) in industrial control systems (ICS) was first constructed.

View Article and Find Full Text PDF

Background: In this work, we implement a data-driven approach using an aggregation of several analytical methods to study the characteristics of COVID-19 daily infection and death time series and identify correlations and characteristic trends that can be corroborated to the time evolution of this disease. The datasets cover twelve distinct countries across six continents, from January 22, 2020 till March 1, 2022. This time span is partitioned into three windows: (1) pre-vaccine, (2) post-vaccine and pre-omicron (BA.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!