A new computational framework combines information-theoretic and network science principles to identify emergent phenomena in neural activity. The study investigates whether collective neural signatures like oscillations and avalanches have causal relevance or are mere epiphenomena. Results indicate that in-vivo neuronal oscillations show substantial emergent behavior at smaller prediction delays, while critical avalanches emerge at larger timescales. Simulations reveal that network structure and interneuronal time-delays facilitate the emergent signature of oscillations. The findings highlight network-level interactions between neuronal assemblies as the key driver of emergent population activity in the brain.
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