Collective dynamics of a coupled Hindmarsh–Rose neurons with locally active memristor

Kanagaraj, Sathiyadevi; Durairaj, Premraj; Sampath, Sivaperumal; Karthikeyan, Anitha; Rajagopal, Karthikeyan

doi:10.1016/j.biosystems.2023.105010

Cited by 4 publications

(2 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In thermoacoustics, bursts result from slow-fast oscillations in calm systems and turbulence in turbulent ones [29]. Models utilizing Hindmarsh-Rose neurons and memristive connections demonstrate neuron synchronization [30]. Memristive devices induce mixed-mode oscillations in coupled LCR oscillators [31] and a memristorbased Shimizu-Morioka system illustrates burst dynamics [32].…”

Section: Discussionmentioning

confidence: 99%

“…Thermoacoustic research reveals that burst behavior primarily results from the interaction of slow and fast oscillations in laminar and low-turbulence systems, while turbulence plays a predominant role in high-turbulence systems [29]. A model of an unstructured neural network, based on the Hindmarsh-Rose neuron and memristive connections, demonstrates synchronization among neurons with different connection types [30]. The formation of mixed-mode oscillations (MMOs) is observed in a system of three coupled non-autonomous LCR oscillators with shared nonlinearity, achieved using memristive devices [31].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Control of Network Bursting in a Model Spiking Network Supplied with Memristor—Implemented Plasticity

Stasenko,

Mikhaylov,

Kazantsev

2023

Mathematics

View full text Add to dashboard Cite

We consider an unstructured neuron network model composed of excitatory and inhibitory neurons. The synaptic connections are supplied with spike timing-dependent plasticity (STDP). We take the STDP model implemented using a memristor. In normal conditions, the network forms so-called bursting discharges typical of unstructured living networks in dissociated neuronal cultures. Incorporating a biologically inspired model, we demonstrate how memristive plasticity emulates spike timing-dependent plasticity, which is crucial for regulating synchronous brain activity. We have found that, when the memristor-based STDP for inhibitory connections is activated, the bursting dynamics are suppressed and the network turns to a random spiking mode. The dependence of bursting properties on the degree of the memristor-based STDP plasticity is analyzed. These findings hold implications for advancing invasive neurointerfaces and for the identification and management of epileptiform activity.

show abstract