Restoration of the communication between brain circuitry is a crucial step in the recovery of brain damage induced by traumatic injuries or neurological insults. In this work we present a study of real-time unidirectional communication between a spiking neuronal network (SNN) implemented on digital platform and an in-vitro biological neuronal network (BNN), generating similar spontaneous patterns of activity both spatial and temporal. The communication between the networks was established using patterned optogenetic stimulation via a modified digital light projector (DLP) receiving real-time input dictated by the spiking neurons' state. Each stimulation consisted of a binary image composed of 8 × 8 squares, representing the state of 64 excitatory neurons. The spontaneous and evoked activity of the biological neuronal network was recorded using a multi-electrode array in conjunction with calcium imaging. The image was projected in a sub-portion of the cultured network covered by a subset of the all electrodes. The unidirectional information transmission (SNN to BNN) is estimated using the similarity matrix of the input stimuli and output firing. Information transmission was studied in relation to the distribution of stimulus frequency and stimulus intensity, both regulated by the spontaneous dynamics of the SNN, and to the entrainment of the biological networks. We demonstrate that high information transfer from SNN to BNN is possible and identify a set of conditions under which such transfer can occur, namely when the spiking network synchronizations drive the biological synchronizations (entrainment) and in a linear regime response to the stimuli. This research provides further evidence of possible application of miniaturized SNN in future neuro-prosthetic devices for local replacement of injured micro-circuitries capable to communicate within larger brain networks.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7200763PMC
http://dx.doi.org/10.1038/s41598-020-63934-4DOI Listing

Publication Analysis

Top Keywords

neuronal network
16
biological neuronal
12
patterned optogenetic
8
optogenetic stimulation
8
snn bnn
8
network
6
biological
5
snn
5
neuroprosthetic real-time
4
communication
4

Similar Publications

Amyotrophic lateral sclerosis (ALS) is a devastating, uniformly lethal degenerative disease of motor neurons, presenting with relentlessly progressive muscle atrophy and weakness. More than fifty genes carrying causative or disease-modifying variants have been identified since the 1990s, when the first ALS-associated variant in the gene SOD1 was discovered. The most commonly mutated ALS genes in the European populations include the C9orf72, SOD1, TARDBP and FUS.

View Article and Find Full Text PDF

Exploring spiking neural networks for deep reinforcement learning in robotic tasks.

Sci Rep

December 2024

Department of Electrical, Electronic, and Information Engineering "Guglielmo Marconi", Università di Bologna, 40126, Bologna, Italy.

Spiking Neural Networks (SNNs) stand as the third generation of Artificial Neural Networks (ANNs), mirroring the functionality of the mammalian brain more closely than their predecessors. Their computational units, spiking neurons, characterized by Ordinary Differential Equations (ODEs), allow for dynamic system representation, with spikes serving as the medium for asynchronous communication among neurons. Due to their inherent ability to capture input dynamics, SNNs hold great promise for deep networks in Reinforcement Learning (RL) tasks.

View Article and Find Full Text PDF

Multimodal Deep Learning Fusing Clinical and Radiomics Scores for Prediction of Early-Stage Lung Adenocarcinoma Lymph Node Metastasis.

Acad Radiol

December 2024

School of Public Health, Jiangxi Medical College, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.); Jiangxi Provincial Key Laboratory of Disease Prevention and Public Health, Nanchang University, Nanchang 330006, China (C.X., L.D., W.C., M.H.). Electronic address:

Rationale And Objectives: To develop and validate a multimodal deep learning (DL) model based on computed tomography (CT) images and clinical knowledge to predict lymph node metastasis (LNM) in early lung adenocarcinoma.

Materials And Methods: A total of 724 pathologically confirmed early invasive lung adenocarcinoma patients were retrospectively included from two centers. Clinical and CT semantic features of the patients were collected, and 3D radiomics features were extracted from nonenhanced CT images.

View Article and Find Full Text PDF

Nose-to-brain delivery of lithium via a sprayable in situ-forming hydrogel composed of chelating starch nanoparticles.

J Control Release

December 2024

Department of Chemical Engineering, McMaster University, 1280 Main Street, West Hamilton, ON L8S 4L8, Canada. Electronic address:

While bipolar disorder patients can benefit from lithium therapy, high levels of lithium in the serum can induce undesirable systemic side effects. Intranasal (IN) lithium delivery offers a potential solution to this challenge given its potential to facilitate improved lithium transport to brain when delivered to the olfactory mucosa. Herein, a sprayable, in situ forming nanoparticle network hydrogel (NNH) based on Schiff base interactions between chelator-functionalized oxidized starch nanoparticles (SNPs) and carboxymethyl chitosan (CMCh) is reported that can be deployed within the nasal cavity to release ultra-small penetrative SNPs over time.

View Article and Find Full Text PDF

Enhanced accuracy in first-spike coding using current-based adaptive LIF neuron.

Neural Netw

December 2024

Communications and Signal Processing Group, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, United Kingdom.

First spike timings are crucial for decision-making in spiking neural networks (SNNs). A recently introduced first-spike (FS) coding method demonstrates comparable accuracy to firing-rate (FR) coding in processing complex temporal information through supervised learning. However, its performance still falls behind advanced approaches.

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!