LEADER 05758nam 22006735 450 001 9910298292503321 005 20200704073002.0 010 $a1-4939-1969-5 024 7 $a10.1007/978-1-4939-1969-7 035 $a(CKB)3710000000280929 035 $a(EBL)1968365 035 $a(OCoLC)895661059 035 $a(SSID)ssj0001385803 035 $a(PQKBManifestationID)11895239 035 $a(PQKBTitleCode)TC0001385803 035 $a(PQKBWorkID)11341298 035 $a(PQKB)10645478 035 $a(DE-He213)978-1-4939-1969-7 035 $a(MiAaPQ)EBC1968365 035 $a(PPN)183097858 035 $a(EXLCZ)993710000000280929 100 $a20141113d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aAnalysis and Modeling of Coordinated Multi-neuronal Activity$b[electronic resource] /$fedited by Masami Tatsuno 205 $a1st ed. 2015. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Springer,$d2015. 215 $a1 online resource (353 p.) 225 1 $aSpringer Series in Computational Neuroscience,$x2197-1900 ;$v12 300 $aDescription based upon print version of record. 311 $a1-4939-1968-7 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aPart I.  Method of Multi-Electrode Recording -- Chapter 1. Techniques for Large-Scale Multiunit Recording -- Chapter 2. Silicon Probe Techniques for Large-scale Multiunit Recording -- Part II. Coordinated Neural Activity in Rodent Hippocampus and Associated Areas -- Chapter 3. Overview of Neural Activity in the Awake and Sleeping Hippocampus -- Chapter 4. Associative Reactivation of Place-Reward Information in the Hippocampal-Ventral Striatal Circuitry -- Chapter 5. Hippocampal Sequences and the Cognitive Map -- Chapter 6. Reorganization of Hippocampal Place-Selective Patterns During Goal-Directed Learning and Their Reactivation During Sleep -- Chapter 7. Causal Relationship Between SPW-Rs and Spatial Learning and Memory -- Part III. Cortical Neural Activity and Interaction with the Hippocampus -- Chapter 8. Packets of Sequential Neural Activity in Sensory Cortex -- Chapter 9. Coordinated Sequence Replays Between the Visual Cortex and Hippocampus -- Chapter 10. Memory Consolidation, Replay, and Cortico-Hippocampal Interactions -- Part IV. Memory Reactivation in Humans -- Chapter 11. Memory Reactivation in Humans (Imaging Studies) -- Part V. Computational Modeling of Coordinated Neural Activity -- Chapter 12. Models and Theoretical Frameworks for Hippocampal and Entorhinal Cortex Function in Memory and Navigation -- Chapter 13.  Information Encoding and Reconstruction by Phase Coding of Spikes -- Chapter 14. Reinforcement Learning and Hippocampal Dynamics -- Chapter 15. Off-line Replay and Hippocampal-Neocortical Interaction. 330 $aSince information in the brain is processed by the exchange of spikes among neurons, a study of such group dynamics is extremely important in understanding hippocampus dependent memory. These spike patterns and local field potentials (LFPs) have been analyzed by various statistical methods. These studies have led to important findings of memory information processing. For example, memory-trace replay, a reactivation of behaviorally induced neural patterns during subsequent sleep, has been suggested to play an important role in memory consolidation. It has also been suggested that a ripple/sharp wave event (one of the characteristics of LFPs in the hippocampus) and spiking activity in the cortex have a specific relationship that may facilitate the consolidation of hippocampal dependent memory from the hippocampus to the cortex. The book will provide a state-of-the-art finding of memory information processing through the analysis of multi-neuronal data. The first half of the book is devoted to this analysis aspect. Understanding memory information representation and its consolidation, however, cannot be achieved only by analyzing the data. It is extremely important to construct a computational model to seek an underlying mathematical principle. In other words, an entire picture of hippocampus dependent memory system would be elucidated through close collaboration among experiments, data analysis, and computational modeling. Not only does computational modeling benefit the data analysis of multi-electrode recordings, but it also provides useful insight for future experiments and analyses. The second half of the book will be devoted to the computational modeling of hippocampus-dependent memory. 410 0$aSpringer Series in Computational Neuroscience,$x2197-1900 ;$v12 606 $aNeurosciences 606 $aNeurobiology 606 $aNeural networks (Computer science)  606 $aNeurosciences$3https://scigraph.springernature.com/ontologies/product-market-codes/B18006 606 $aNeurobiology$3https://scigraph.springernature.com/ontologies/product-market-codes/L25066 606 $aMathematical Models of Cognitive Processes and Neural Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/M13100 615 0$aNeurosciences. 615 0$aNeurobiology. 615 0$aNeural networks (Computer science) . 615 14$aNeurosciences. 615 24$aNeurobiology. 615 24$aMathematical Models of Cognitive Processes and Neural Networks. 676 $a153 702 $aTatsuno$b Masami$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298292503321 996 $aAnalysis and Modeling of Coordinated Multi-neuronal Activity$92502134 997 $aUNINA