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Neurosciences

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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...

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...

Internal world models in humans, animals, and AI.

Neuron
How do brains-biological or artificial-respond and adapt to an ever-changing environment? In a recent meeting, experts from various fields of neuroscience and artificial intelligence met to discuss internal world models in brains and machines, arguin...

Neuroethics and AI ethics: a proposal for collaboration.

BMC neuroscience
The scientific relationship between neuroscience and artificial intelligence is generally acknowledged, and the role that their long history of collaboration has played in advancing both fields is often emphasized. Beyond the important scientific ins...

Implications of the novel EU AI Act for neurotechnologies.

Neuron
The EU AI Act, the first comprehensive regulation of AI, came into effect in August. Here, we provide an overview of the provisions that apply to the field of neurotechnology with respect to research and development and neuroscience practice and disc...

Neuromorphic engineering: Artificial brains for artificial intelligence.

Annals of the New York Academy of Sciences
Neuromorphic engineering is a research discipline that tries to bridge the gaps between neuroscience and engineering, cognition and algorithms, and natural and artificial intelligence. Neuromorphic engineering promises revolutionary breakthroughs tha...

Neuroscientific insights about computer vision models: a concise review.

Biological cybernetics
The development of biologically-inspired computational models has been the focus of study ever since the artificial neuron was introduced by McCulloch and Pitts in 1943. However, a scrutiny of literature reveals that most attempts to replicate the hi...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...