Neuroscience is the collection of scientific disciplines dedicated to studying the nervous system, particularly the brain, in its structural, functional, evolutionary, and pathological aspects. Its aim is to unravel the biological mechanisms underlying cognitive, emotional, and behavioral phenomena. Neuroscience distinguishes itself from cognitive science through its experimental and biological focus, using molecular to computational approaches and relying on advanced imaging and modeling techniques.
Use cases and examples
Neuroscience is applied in basic research to decipher neural circuits, as well as in clinical applications such as diagnosing and treating neurodegenerative diseases (Alzheimer's, Parkinson's), behavioral neurology, and psychiatry. It also plays a role in the development of neural prostheses, optimization of brain-machine interfaces, and enhancement of artificial intelligence algorithms inspired by brain function.
Main software tools, libraries, frameworks
Key tools include data analysis software like MATLAB, Python (with libraries such as MNE, Nilearn, Brainstorm), brain imaging platforms like FreeSurfer or SPM, and neural simulation environments like NEURON or NEST. Deep learning frameworks such as TensorFlow or PyTorch are also used for modeling biological and artificial neural networks.
Recent developments, evolutions, and trends
Recent trends involve the extensive integration of artificial intelligence for brain data analysis, the rise of multimodal computational neuroscience, and the emergence of neuroethics in response to issues surrounding brain manipulation. Brain-machine interfaces are becoming more efficient, and connectomics (mapping neural connections) is opening up new opportunities in health and AI.