| http://dbpedia.org/ontology/abstract
|
The dynamical systems approach to neurosci … The dynamical systems approach to neuroscience is a branch of mathematical biology that utilizes nonlinear dynamics to understand and model the nervous system and its functions. In a dynamical system, all possible states are expressed by a phase space. Such systems can experience bifurcation (a qualitative change in behavior) as a function of its bifurcation parameters and often exhibit chaos. Dynamical neuroscience describes the non-linear dynamics at many levels of the brain from single neural cells to cognitive processes, sleep states and the behavior of neurons in large-scale neuronal simulation. Neurons have been modeled as nonlinear systems for decades now, but dynamical systems emerge in numerous other ways in the nervous system. From chemistry, chemical species models like the Gray–Scott model exhibit rich, chaotic dynamics. Dynamic interactions between extracellular fluid pathways reshapes our view of intraneural communication. Information theory draws on thermodynamics in the development of which can involve nonlinear systems, especially with regards to the brain.ems, especially with regards to the brain.
|
| http://dbpedia.org/ontology/wikiPageID
|
28289092
|
| http://dbpedia.org/ontology/wikiPageLength
|
18690
|
| http://dbpedia.org/ontology/wikiPageRevisionID
|
1108564604
|
| http://dbpedia.org/ontology/wikiPageWikiLink
|
http://dbpedia.org/resource/Neural_oscillation +
, http://dbpedia.org/resource/Phase_space +
, http://dbpedia.org/resource/Alan_Hodgkin +
, http://dbpedia.org/resource/Action_potential +
, http://dbpedia.org/resource/Sleep +
, http://dbpedia.org/resource/Excitability +
, http://dbpedia.org/resource/FitzHugh%E2%80%93Nagumo_model +
, http://dbpedia.org/resource/Infodynamics +
, http://dbpedia.org/resource/Network_topology +
, http://dbpedia.org/resource/Glial_cell +
, http://dbpedia.org/resource/Nonlinearity +
, http://dbpedia.org/resource/Andrew_Huxley +
, http://dbpedia.org/resource/Cell_%28biology%29 +
, http://dbpedia.org/resource/Category:Neuroscience +
, http://dbpedia.org/resource/Adenosine_triphosphate +
, http://dbpedia.org/resource/Aldous_Huxley +
, http://dbpedia.org/resource/Nonlinear +
, http://dbpedia.org/resource/Synapse +
, http://dbpedia.org/resource/Biophysics +
, http://dbpedia.org/resource/Artificial_neural_network +
, http://dbpedia.org/resource/Information_theory +
, http://dbpedia.org/resource/Central_pattern_generator +
, http://dbpedia.org/resource/Mathematical_biology +
, http://dbpedia.org/resource/Lyapunov_function +
, http://dbpedia.org/resource/Hodgkin%E2%80%93Huxley_model +
, http://dbpedia.org/resource/Thermodynamics +
, http://dbpedia.org/resource/Neuroscience +
, http://dbpedia.org/resource/Membrane_potential +
, http://dbpedia.org/resource/Artificial_intelligence +
, http://dbpedia.org/resource/Nervous_system +
, http://dbpedia.org/resource/Computational_neuroscience +
, http://dbpedia.org/resource/Organelle +
, http://dbpedia.org/resource/Randomness +
, http://dbpedia.org/resource/Oculomotor_control +
, http://dbpedia.org/resource/Gap_junction +
, http://dbpedia.org/resource/Theoretical_neuroscience +
, http://dbpedia.org/resource/Squid_giant_axon +
, http://dbpedia.org/resource/Neurotransmitter +
, http://dbpedia.org/resource/Cognition +
, http://dbpedia.org/resource/Morris%E2%80%93Lecar_model +
, http://dbpedia.org/resource/Homeostasis +
, http://dbpedia.org/resource/Integrate-and-fire +
, http://dbpedia.org/resource/Ion_channel +
, http://dbpedia.org/resource/Nonlinear_dynamics +
, http://dbpedia.org/resource/G-protein +
, http://dbpedia.org/resource/Dynamical_systems +
, http://dbpedia.org/resource/Wikt:bifurcation +
, http://dbpedia.org/resource/Biological_neuron_model +
, http://dbpedia.org/resource/Category:Mathematical_and_theoretical_biology +
, http://dbpedia.org/resource/Category:Dynamical_systems +
|
| http://dbpedia.org/property/date
|
September 2022
|
| http://dbpedia.org/property/reason
|
incidence is normally used only in the singular form, perhaps instances or incidents was intended
|
| http://dbpedia.org/property/wikiPageUsesTemplate
|
http://dbpedia.org/resource/Template:Neuroscience +
, http://dbpedia.org/resource/Template:Orphan +
, http://dbpedia.org/resource/Template:Reflist +
, http://dbpedia.org/resource/Template:Main +
, http://dbpedia.org/resource/Template:Verify_spelling +
, http://dbpedia.org/resource/Template:See_also +
|
| http://purl.org/dc/terms/subject
|
http://dbpedia.org/resource/Category:Dynamical_systems +
, http://dbpedia.org/resource/Category:Mathematical_and_theoretical_biology +
, http://dbpedia.org/resource/Category:Neuroscience +
|
| http://www.w3.org/ns/prov#wasDerivedFrom
|
http://en.wikipedia.org/wiki/Dynamical_neuroscience?oldid=1108564604&ns=0 +
|
| http://xmlns.com/foaf/0.1/isPrimaryTopicOf
|
http://en.wikipedia.org/wiki/Dynamical_neuroscience +
|
| owl:sameAs |
http://www.wikidata.org/entity/Q42417126 +
, http://dbpedia.org/resource/Dynamical_neuroscience +
, https://global.dbpedia.org/id/3vfjn +
|
| rdfs:comment |
The dynamical systems approach to neurosci … The dynamical systems approach to neuroscience is a branch of mathematical biology that utilizes nonlinear dynamics to understand and model the nervous system and its functions. In a dynamical system, all possible states are expressed by a phase space. Such systems can experience bifurcation (a qualitative change in behavior) as a function of its bifurcation parameters and often exhibit chaos. Dynamical neuroscience describes the non-linear dynamics at many levels of the brain from single neural cells to cognitive processes, sleep states and the behavior of neurons in large-scale neuronal simulation.eurons in large-scale neuronal simulation.
|
| rdfs:label |
Dynamical neuroscience
|
| rdfs:seeAlso |
http://dbpedia.org/resource/Cell_excitability +
|
