Chapter title |
Spontaneous Neuronal Network Persistent Activity in the Neocortex: A(n) (Endo)phenotype of Brain (Patho)physiology
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Chapter number | 19 |
Book title |
GeNeDis 2016
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Published in |
Advances in experimental medicine and biology, January 2017
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DOI | 10.1007/978-3-319-56246-9_19 |
Pubmed ID | |
Book ISBNs |
978-3-31-956245-2, 978-3-31-956246-9
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Authors |
Pavlos Rigas, Leonidas J. Leontiadis, Panagiotis Tsakanikas, Irini Skaliora |
Abstract |
Abnormal synaptic homeostasis in the cerebral cortex represents a risk factor for both psychiatric and neurodegenerative disorders, from autism and schizophrenia to Alzheimer's disease. Neurons via synapses form recurrent networks that are intrinsically active in the form of oscillating activity, visible at increasingly macroscopic neurophysiological levels: from single cell recordings to the local field potentials (LFPs) to the clinically relevant electroencephalography (EEG). Understanding in animal models the defects at the level of neural circuits is important in order to link molecular and cellular phenotypes with behavioral phenotypes of neurodevelopmental and/or neurodegenerative brain disorders. In this study we introduce the novel idea that recurring persistent network activity (Up states) in the neocortex at the reduced level of the brain slice may be used as an endophenotype of brain disorders that will help us understand not only how local microcircuits of the cortex may be affected in brain diseases, but also when, since an important issue for the design of successful treatment strategies concerns the time window available for intervention. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 17% |
Researcher | 4 | 17% |
Student > Master | 4 | 17% |
Student > Bachelor | 2 | 9% |
Lecturer > Senior Lecturer | 1 | 4% |
Other | 3 | 13% |
Unknown | 5 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 5 | 22% |
Neuroscience | 3 | 13% |
Psychology | 3 | 13% |
Engineering | 2 | 9% |
Computer Science | 1 | 4% |
Other | 3 | 13% |
Unknown | 6 | 26% |