語系:
繁體中文
English
說明(常見問題)
圖資館首頁
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Estimating functional connectivity a...
~
Pastore, Vito Paolo.
Estimating functional connectivity and topology in large-scale neuronal assembliesstatistical and computational methods /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Estimating functional connectivity and topology in large-scale neuronal assembliesby Vito Paolo Pastore.
其他題名:
statistical and computational methods /
作者:
Pastore, Vito Paolo.
出版者:
Cham :Springer International Publishing :2021.
面頁冊數:
xv, 87 p. :ill., digital ;24 cm.
Contained By:
Springer Nature eBook
標題:
Neural networks (Neurobiology)Mathematical models.
電子資源:
https://doi.org/10.1007/978-3-030-59042-0
ISBN:
9783030590420$q(electronic bk.)
Estimating functional connectivity and topology in large-scale neuronal assembliesstatistical and computational methods /
Pastore, Vito Paolo.
Estimating functional connectivity and topology in large-scale neuronal assemblies
statistical and computational methods /[electronic resource] :by Vito Paolo Pastore. - Cham :Springer International Publishing :2021. - xv, 87 p. :ill., digital ;24 cm. - Springer theses,2190-5053. - Springer theses..
Introduction -- Materials and Methods -- Results -- Conclusion.
This book describes a set of novel statistical algorithms designed to infer functional connectivity of large-scale neural assemblies. The algorithms are developed with the aim of maximizing computational accuracy and efficiency, while faithfully reconstructing both the inhibitory and excitatory functional links. The book reports on statistical methods to compute the most significant functional connectivity graph, and shows how to use graph theory to extract the topological features of the computed network. A particular feature is that the methods used and extended at the purpose of this work are reported in a fairly completed, yet concise manner, together with the necessary mathematical fundamentals and explanations to understand their application. Furthermore, all these methods have been embedded in the user-friendly open source software named SpiCoDyn, which is also introduced here. All in all, this book provides researchers and graduate students in bioengineering, neurophysiology and computer science, with a set of simplified and reduced models for studying functional connectivity in in silico biological neuronal networks, thus overcoming the complexity of brain circuits.
ISBN: 9783030590420$q(electronic bk.)
Standard No.: 10.1007/978-3-030-59042-0doiSubjects--Topical Terms:
273715
Neural networks (Neurobiology)
--Mathematical models.
LC Class. No.: QP363.3 / .P37 2021
Dewey Class. No.: 612.82
Estimating functional connectivity and topology in large-scale neuronal assembliesstatistical and computational methods /
LDR
:02344nmm a2200337 a 4500
001
595895
003
DE-He213
005
20201106125318.0
006
m d
007
cr nn 008maaau
008
211013s2021 sz s 0 eng d
020
$a
9783030590420$q(electronic bk.)
020
$a
9783030590413$q(paper)
024
7
$a
10.1007/978-3-030-59042-0
$2
doi
035
$a
978-3-030-59042-0
040
$a
GP
$c
GP
$e
rda
041
0
$a
eng
050
4
$a
QP363.3
$b
.P37 2021
072
7
$a
MQW
$2
bicssc
072
7
$a
TEC059000
$2
bisacsh
072
7
$a
MQW
$2
thema
082
0 4
$a
612.82
$2
23
090
$a
QP363.3
$b
.P293 2021
100
1
$a
Pastore, Vito Paolo.
$3
888435
245
1 0
$a
Estimating functional connectivity and topology in large-scale neuronal assemblies
$h
[electronic resource] :
$b
statistical and computational methods /
$c
by Vito Paolo Pastore.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2021.
300
$a
xv, 87 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Springer theses,
$x
2190-5053
505
0
$a
Introduction -- Materials and Methods -- Results -- Conclusion.
520
$a
This book describes a set of novel statistical algorithms designed to infer functional connectivity of large-scale neural assemblies. The algorithms are developed with the aim of maximizing computational accuracy and efficiency, while faithfully reconstructing both the inhibitory and excitatory functional links. The book reports on statistical methods to compute the most significant functional connectivity graph, and shows how to use graph theory to extract the topological features of the computed network. A particular feature is that the methods used and extended at the purpose of this work are reported in a fairly completed, yet concise manner, together with the necessary mathematical fundamentals and explanations to understand their application. Furthermore, all these methods have been embedded in the user-friendly open source software named SpiCoDyn, which is also introduced here. All in all, this book provides researchers and graduate students in bioengineering, neurophysiology and computer science, with a set of simplified and reduced models for studying functional connectivity in in silico biological neuronal networks, thus overcoming the complexity of brain circuits.
650
0
$a
Neural networks (Neurobiology)
$x
Mathematical models.
$3
273715
650
0
$a
Biomedical engineering.
$3
190330
650
0
$a
Electrophysiology.
$3
189030
650
0
$a
Neural networks (Computer science)
$3
181982
650
0
$a
Graph theory.
$3
181880
650
1 4
$a
Biomedical Engineering and Bioengineering.
$3
826326
650
2 4
$a
Complexity.
$3
274400
650
2 4
$a
Coding and Information Theory.
$3
273763
650
2 4
$a
Graph Theory.
$3
522732
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer Nature eBook
830
0
$a
Springer theses.
$3
557607
856
4 0
$u
https://doi.org/10.1007/978-3-030-59042-0
950
$a
Engineering (SpringerNature-11647)
筆 0 讀者評論
全部
電子館藏
館藏
1 筆 • 頁數 1 •
1
條碼號
館藏地
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
000000194583
電子館藏
1圖書
電子書
EB QP363.3 .P293 2021 2021
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
多媒體檔案
https://doi.org/10.1007/978-3-030-59042-0
評論
新增評論
分享你的心得
Export
取書館別
處理中
...
變更密碼
登入