Introduction of Systems Neuroscience
Systems neuroscience refers to a subdiscipline of systems biology and neuroscience that aims to understand the structure and function of neural circuits and systems. Systems neuroscience research normally focuses on nerve cell behavior with the formation of neural pathways, neural circuits, and larger brain networks. At this analysis level, there are a series of studies showing the influence of different neural circuits and sensory information on the perception of the external world. With multiple molecular and cellular approaches, brain structure and function can be well understood, and advanced mental functions such as language, memory, and self-awareness are studied.
The animal models can be used in systems neuroscience research to provide more precise results for advanced cognitive functions study. The research data can be extended to human brain function to a certain extent. Furthermore, the computational models make it possible to repair or argue broken neural circuits in diseased or disrupted states.
Clinical Systems Neuroscience
Clinical systems neuroscience is the intersection between clinical medicine and neuroscience, it concerns malfunctions resulting from disease of the neural systems. In the past few decades, the remarkable development of informatics, computer science, and information technology largely promotes the measurement and analysis of brain activity and greatly contributed to the development of clinical systems neuroscience. Compared with the pathophysiology understanding of neuropsychiatric disorders, clinical systems neuroscience provides a clinical tool supporting diagnosis as well as treatment.
Fig.1 Clinical systems neuroscience.
Research Methods for Systems Neuroscience
- Positron emission tomography (PET) scan
- Functional magnetic resonance imaging (fMRI)
- Single-photon emission tomography (SPECT)
- Near-infrared spectroscopy (NIRS)
- Electroencephalography (EEG)
- Magnetoencephalography (MEG)
- Transcranial magnetic stimulation (TMS)
- Deep brain stimulation (DBS)
- Animal models
- Computational models
Fig.2 Three representative images indicating different information obtained with MRI from a healthy volunteer.
Current Topics in Systems Neuroscience
In recent years, the intellectual thrust of systems neuroscience is neural coding and dynamics study. Neural coding refers to information representation in the electrical and biochemical signals in neurons and the patterns of synaptic connections, that is, short-term memory and long-term memory. Neural dynamics refers to patterns of nerve cell electrical and chemical activity for information to create, manipulate, and storage.
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