Kim, Daeyoung Park, Seongsik Jeong, Yeonjoo Kim, Jaewook Lee, Suyoun Kwak, Joon Young Jang, Hyun Jae Kim, Inho Kim, Jong-Kook Park, Jongkil 2025-09-22T03:00:52Z 2025-09-22T03:00:52Z 2025-09-16 2025-06 1534-4320 https://pubs.kist.re.kr/handle/201004/153208 A deep understanding of neuronal circuitry connectivity is essential to replicate biological functions effectively. Inferring neural connectivity considers the cross-correlation of spike timing. Neuromorphic systems utilize online learning algorithms that leverage the temporal correlations of spikes by utilizing spiking neural networks. This research demonstrates real-time, large-scale neural connectivity inference by implementing the presynaptic spike-driven spike-timing-dependent plasticity method on neuromorphic hardware. We validate the capability of the proposed method to perform advanced neuron connectivity inference using synthetic data generated from leaky integrate-and-fire neurons on a multi-scale. Additionally, we analyzed that the proposed method exhibits invariant high inference performance in sparse networks without burst firing, regardless of transmission delay. Finally, we demonstrate the feasibility of the proposed method in real-time neural connectivity inference in actual in vitro or in vivo contexts by conducting neural connectivity inference simulating in a way closely mirroring in vitro conditions through fluorescence imaging signal data. English Institute of Electrical and Electronics Engineers Real-Time Large-Scale Neural Connectivity Inference on Spiking Neuromorphic System Article 10.1109/TNSRE.2025.3583057 1 IEEE Transactions on Neural Systems and Rehabilitation Engineering, v.33, pp.2781 - 2792 IEEE Transactions on Neural Systems and Rehabilitation Engineering 33 2781 2792 Y scie scopus 001565433100005 2-s2.0-105010592738 Engineering, Biomedical Rehabilitation Engineering Rehabilitation Article TIMING-DEPENDENT PLASTICITY FUNCTIONAL CONNECTIVITY BRAIN DYNAMICS LOIHI Granger causality online learning spike-timing-dependent plasticity spiking neural networks Granger causality online learning spike-timing-dependent plasticity spiking neural networks