03993nam 2201021z- 450 9910346856603321202102113-03897-665-2(CKB)4920000000095101(oapen)https://directory.doabooks.org/handle/20.500.12854/50225(oapen)doab50225(EXLCZ)99492000000009510120202102d2019 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierInformation Theory in NeuroscienceMDPI - Multidisciplinary Digital Publishing Institute20191 online resource (280 p.)3-03897-664-4 As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code-that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.brain networkcategorical perceptionchannel capacitycomplex networksconnectomeconsciousnessdecodingdiscrete Markov chainsdiscriminationeigenvector centralityentorhinal cortexfeedforward networksfree-energy principlefunctional connectomeGibbs measuresgoodnessgraph theoretical analysisgraph theoryhigher-order correlationshippocampusindependent component analysisinfomax principleinformation entropy productioninformation theoryintegrated informationintegrated information theoryinternal model hypothesisIsing modellatchingmaximum entropymaximum entropy principleminimum information partitionmismatched decodingmutual informationmutual information decompositionnavigationnetwork eigen-entropyneural codeneural codingneural information propagationneural networkneural population codingneurosciencenoise correlationsordernessperceived similarityperceptual magnetPotts modelprincipal component analysispulse-gatingQueyranne's algorithmrecursionredundancyrepresentationspike train statisticsspike-time precisionsubmodularitysynergyunconscious inferencePiasini Eugenioauth1292375Panzeri StefanoauthBOOK9910346856603321Information Theory in Neuroscience3022229UNINA