Bio-realistic neural network implementation on loihi 2 with izhikevich neurons

Name: Bio-realistic neural network implementation on loihi 2 with izhikevich neurons
Author: Akturk, Ismail, Sengor, N. S., Isler, Y. S., Cagdas, S., Uludag, Recep Bugra

İsim	Bio-realistic neural network implementation on loihi 2 with izhikevich neurons
Yazar	Akturk, Ismail, Sengor, N. S., Isler, Y. S., Cagdas, S., Uludag, Recep Bugra
Basım Tarihi:	2024-06-18
Basım Yeri	- IOP Publishing
Konu	Energy efficiency, Basal ganglia circuit, Izhikevich neuron, Loihi 2, Neuromorphic processor
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2634-4386
Kayıt Numarası	305524d9-0d78-4132-ac1c-accc4f198d52
Lokasyon	Computer Science
Tarih	2024-06-18
Notlar	Intel's Neuromorphic Research Community (INRC) ; ITU Scientific Research Projects Office
Örnek Metin	Neuromorphic systems are designed to emulate the principles of biological information processing, with the goals of improving computational efficiency and reducing energy usage. A critical aspect of these systems is the fidelity of neuron models and neural networks to their biological counterparts. In this study, we implemented the Izhikevich neuron model on Intel's Loihi 2 neuromorphic processor. The Izhikevich neuron model offers a more biologically accurate alternative to the simpler leaky-integrate and fire model, which is natively supported by Loihi 2. We compared these two models within a basic two-layer network, examining their energy consumption, processing speeds, and memory usage. Furthermore, to demonstrate Loihi 2's ability to realize complex neural structures, we implemented a basal ganglia circuit to perform a Go/No-Go decision-making task. Our findings demonstrate the practicality of customizing neuron models on Loihi 2, thereby paving the way for constructing spiking neural networks that better replicate biological neural networks and have the potential to simulate complex cognitive processes.
DOI	10.1088/2634-4386/ad5584
Cilt	4

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Bio-realistic neural network implementation on loihi 2 with izhikevich neurons

Yazar Akturk, Ismail, Sengor, N. S., Isler, Y. S., Cagdas, S., Uludag, Recep Bugra

Basım Tarihi 2024-06-18

Basım Yeri - IOP Publishing

Konu Energy efficiency, Basal ganglia circuit, Izhikevich neuron, Loihi 2, Neuromorphic processor

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2634-4386

Kayıt Numarası 305524d9-0d78-4132-ac1c-accc4f198d52

Lokasyon Computer Science

Tarih 2024-06-18

Notlar Intel's Neuromorphic Research Community (INRC) ; ITU Scientific Research Projects Office

Örnek Metin Neuromorphic systems are designed to emulate the principles of biological information processing, with the goals of improving computational efficiency and reducing energy usage. A critical aspect of these systems is the fidelity of neuron models and neural networks to their biological counterparts. In this study, we implemented the Izhikevich neuron model on Intel's Loihi 2 neuromorphic processor. The Izhikevich neuron model offers a more biologically accurate alternative to the simpler leaky-integrate and fire model, which is natively supported by Loihi 2. We compared these two models within a basic two-layer network, examining their energy consumption, processing speeds, and memory usage. Furthermore, to demonstrate Loihi 2's ability to realize complex neural structures, we implemented a basal ganglia circuit to perform a Go/No-Go decision-making task. Our findings demonstrate the practicality of customizing neuron models on Loihi 2, thereby paving the way for constructing spiking neural networks that better replicate biological neural networks and have the potential to simulate complex cognitive processes.

DOI 10.1088/2634-4386/ad5584

Cilt 4