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Neurosciences

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Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research.

Neural networks : the official journal of the International Neural Network Society
Neuroscience and artificial intelligence (AI) share a long history of collaboration. Advances in neuroscience, alongside huge leaps in computer processing power over the last few decades, have given rise to a new generation of in silico neural networ...

Forms of explanation and understanding for neuroscience and artificial intelligence.

Journal of neurophysiology
Much of the controversy evoked by the use of deep neural networks as models of biological neural systems amount to debates over what constitutes scientific progress in neuroscience. To discuss what constitutes scientific progress, one must have a goa...

Yulong Li.

Neuron
In an interview with Neuron, Yulong Li discusses optical tool development and next steps to interrogate the whole brain. He further shares the importance of interdisciplinarity; how new tools for neural imaging, perturbation, and artificial intellige...

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Behavioural brain research
Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data owne...

Natural Language Processing Applications in the Clinical Neurosciences: A Machine Learning Augmented Systematic Review.

Acta neurochirurgica. Supplement
Natural language processing (NLP), a domain of artificial intelligence (AI) that models human language, has been used in medicine to automate diagnostics, detect adverse events, support decision making and predict clinical outcomes. However, applicat...

Machine Intelligence in Clinical Neuroscience: Taming the Unchained Prometheus.

Acta neurochirurgica. Supplement
The democratization of machine learning (ML) through availability of open-source learning libraries, the availability of datasets in the "big data" era, increasing computing power even on mobile devices, and online training resources have both led to...

Superposition mechanism as a neural basis for understanding others.

Scientific reports
Social cognition has received much attention in fields such as neuroscience, psychology, cognitive science, and philosophy. Theory-theory (TT) and simulation theory (ST) provide the dominant theoretical frameworks for research on social cognition. Ho...

A whole brain probabilistic generative model: Toward realizing cognitive architectures for developmental robots.

Neural networks : the official journal of the International Neural Network Society
Building a human-like integrative artificial cognitive system, that is, an artificial general intelligence (AGI), is the holy grail of the artificial intelligence (AI) field. Furthermore, a computational model that enables an artificial system to ach...

Linking Brain Structure, Activity, and Cognitive Function through Computation.

eNeuro
Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generati...

Addressing neuroethics issues in practice: Lessons learnt by tech companies in AI ethics.

Neuron
Neurotechnologies raise ethical concerns overlapping with those of other technologies, like artificial intelligence (AI). We discuss how to leverage the experience and lessons learnt by tech companies addressing AI ethics issues to accelerate going f...