Collaboration With Other Disciplines
Neuroinformatics is formed at the intersections of the following fields:
- neuroscience
- computer science
- biology
- experimental psychology
- medicine
- engineering
- physical sciences
- mathematics
- chemistry
Biology is concerned with molecular data (from genes to cell specific expression); medicine and anatomy with the structure of synapses and systems level anatomy; engineering – electrophysiology (from single channels to scalp surface EEG), brain imaging; computer science – databases, software tools, mathematical sciences – models, chemistry – neurotransmitters, etc. Neuroscience uses all aforementioned experimental and theoretical studies to learn about the brain through its various levels. Medical and biological specialists help to identify the unique cell types, and their elements and anatomical connections. Functions of complex organic molecules and structures, including a myriad of biochemical, molecular, and genetic mechanisms which regulate and control brain function, are determined by specialists in chemistry and cell biology. Brain imaging determines structural and functional information during mental and behavioral activity. Specialists in biophysics and physiology study physical processes within neural cells neuronal networks. The data from these fields of research is analyzed and arranged in databases and neural models in order to integrate various elements into a sophisticated system; this is the point where neuroinformatics meets other disciplines.
Neuroscience provides the following types of data and information on which neuroinformatics operates:
- Molecular and cellular data (ion channel, action potential, genetics, cytology of neurons, protein pathways),
- Data from organs and systems (visual cortex, perception, audition, sensory system, pain, taste, motor system, spinal cord),
- Cognitive data (language, emotion, motor learning, sexual behavior, decision making, social neuroscience),
- Developmental information (neuronal differentiation, cell survival, synaptic formation, motor differentiation, injury and regeneration, axon guidance, growth factors),
- Information about diseases and aging (autonomic nervous system, depression, anxiety, Parkinson's disease, addiction, memory loss),
- Neural engineering data (brain-computer interface), and
- Computational neuroscience data (computational models of various neuronal systems, from membrane currents, proteins to learning and memory).
Neuroinformatics uses databases, the Internet, and visualization in the storage and analysis of the mentioned neuroscience data.
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