 17th
International Conference of the Society of Neuroscientists of Africa Marrakesh-Morocco April, 17-20, 2025 |
Symposium
26
Title: Recent advances at the interface of neuroscience and AI
(NeuroAI)
Organizer: Srikanth Ramaswamy (UK)
co-organizer: Jie Mei (Austria)
Biosciences Institute, Newcastle University Framlington Place, NE2 4HH Newcastle upon Tyne, United Kingdom
Altenberger Str. 66c/Science Park 4, 4040 Linz, Austria
email: srikanth.ramaswamy@newcastle.ac.uk & jie.mei@it-u.at
Abstract:
| Biological neural networks adapt
and learn in diverse behavioral contexts. Artificial neural networks
(ANNs) have leveraged principles from biology to solve complex
problems. However, despite their success in specific tasks, ANNs still
fall short of matching the flexibility and adaptability of biological
cognition. This symposium will highlight recent advances in
neuroscience that deepen our understanding of both biological and
artificial intelligence. Neuroscience-inspired artificial intelligence
(NeuroAI) has produced powerful tools for solving complex tasks.
Efforts such as the US BRAIN Initiative, the NSF National AI Research
Institutes, and the EU Human Brain Project are laying the neural and
cognitive foundations for future AI systems. This symposium will bring together researchers to synthesize an integrative view of how insights from biological intelligence can catalyze the development of next-generation AI. The symposium is designed for doctoral students, postdocs, early and mid-career researchers, industry experts, and clinicians. An international panel will present short talks on how neural networks regulate learning and higher-order cognition, fostering dialogue aimed at identifying common organizing principles shared between biological and artificial intelligence. A concluding panel discussion will explore how advances in brain research can inspire the next generation of AI. |
Speakers
| Number |
Speaker |
e-mail |
Title
of the communication |
| SP26_1 |
Maryeme Ouafoudi |
omaryeme@gmail.com | Evolving Learning
Rules on and for Neuromorphic Hardware |
| SP26_2 |
Sadiq ADEDAYO |
sadiq.adedayo@univie.ac.at | Causal Discovery
to link Neuronal Activities to Behaaviour |
| SP26_3 |
Jie Mei | jie.mei@it-u.at |
Improving the adaptive and continuous learning capabilities of artificial neural networks using multi-scale, neuromodulation-aware rules |
| SP26_4 |
Nina
Hubig |
nina.hubig@it-u.at |
Explainability
and Interpretability in the Neurosciences |