AIMC Topic: Neurosciences

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Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience.

Nature neuroscience
The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitig...

A new era in cognitive neuroscience: the tidal wave of artificial intelligence (AI).

BMC neuroscience
Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promise for significant breakthroughs in our ability to probe the intrinsic mechanisms of the brain. The recent unprecedented development of robust AI model...

What have we learned about artificial intelligence from studying the brain?

Biological cybernetics
Neuroscience and artificial intelligence (AI) share a long, intertwined history. It has been argued that discoveries in neuroscience were (and continue to be) instrumental in driving the development of new AI technology. Scrutinizing these historical...

The hardware is the software.

Neuron
Human brains and bodies are not hardware running software: the hardware is the software. We reason that because the physics of artificial intelligence hardware and of human biological "hardware" is distinct, neuromorphic engineers need to be selectiv...

Neural networks need real-world behavior.

The Behavioral and brain sciences
Bowers et al. propose to use controlled behavioral experiments when evaluating deep neural networks as models of biological vision. We agree with the sentiment and draw parallels to the notion that "neuroscience needs behavior." As a promising path f...

Grounding neuroscience in behavioral changes using artificial neural networks.

Current opinion in neurobiology
Connecting neural activity to function is a common aim in neuroscience. How to define and conceptualize function, however, can vary. Here I focus on grounding this goal in the specific question of how a given change in behavior is produced by a chang...

Reconstructing computational system dynamics from neural data with recurrent neural networks.

Nature reviews. Neuroscience
Computational models in neuroscience usually take the form of systems of differential equations. The behaviour of such systems is the subject of dynamical systems theory. Dynamical systems theory provides a powerful mathematical toolbox for analysing...

Computational and systems neuroscience: The next 20 years.

PLoS biology
Over the past 20 years, neuroscience has been propelled forward by theory-driven experimentation. We consider the future outlook for the field in the age of big neural data and powerful artificial intelligence models.