
TL;DR
Emulator theory (ET) proposes that predictive neural models trained on neural dynamics and behavior can replicate biological brain functions and states, including consciousness, without detailed mechanistic explanations.
Contribution
The paper introduces emulator theory as a new paradigm for neuroscience, emphasizing prediction-based models over mechanistic details.
Findings
Emulators can generate indistinguishable behavior and cognitive states from biological systems.
ET offers a framework for understanding neural dynamics without explicit representations.
The theory suggests a shift towards prediction-based models in neuroscience research.
Abstract
A central goal in neuroscience is to provide explanations for how animal nervous systems can generate actions and cognitive states such as consciousness while artificial intelligence (AI) and machine learning (ML) seek to provide models that are increasingly better at prediction. Despite many decades of research we have made limited progress on providing neuroscience explanations yet there is an increased use of AI and ML methods in neuroscience for prediction of behavior and even cognitive states. Here we propose emulator theory (ET) and neural emulators as circuit- and scale-independent predictive models of biological brain activity and emulator theory (ET) as an alternative research paradigm in neuroscience. ET proposes that predictive models trained solely on neural dynamics and behaviors can generate functionally indistinguishable systems from their sources. That is, compared to…
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Taxonomy
TopicsNeural dynamics and brain function
