Abstract
To examine the network-level organizing principles by which the brain achieves its real-time encoding of episodic information, we have developed a 96-channel array to simultaneously record the activity patterns of as many as 260 individual neurons in the mouse hippocampus during various startling episodes. We find that the mnemonic startling episodes triggered firing changes in a set of CA1 neurons in both startle-type and environment-dependent manners. Pattern classification methods reveal that these firing changes form distinct ensemble representations in a low-dimensional encoding subspace. Application of a sliding window technique further enabled us to reliably capture not only the temporal dynamics of real-time network encoding but also postevent processing of newly formed ensemble traces. Our analyses revealed that the network-encoding power is derived from a set of functional coding units, termed neural cliques, in the CA1 network. The individual neurons within neural cliques exhibit "collective cospiking" dynamics that allow the neural clique to overcome the response variability of its members and to achieve real-time encoding robustness. Conversion of activation patterns of these coding unit assemblies into a set of real-time digital codes permits concise and universal representation and categorization of discrete behavioral episodes across different individual brains.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 6125-6130 |
| Number of pages | 6 |
| Journal | Proceedings of the National Academy of Sciences of the United States of America |
| Volume | 102 |
| Issue number | 17 |
| DOIs | |
| State | Published - Apr 26 2005 |
Fingerprint
Keywords
- Cell assembly
- Episodic memory
- Neural clique
- Neural code
- Startle
ASJC Scopus subject areas
- General
Cite this
Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus. / Lin, Longnian; Osan, Remus; Shoham, Shy; Jin, Wenjun; Zuo, Wenqi; Tsien, Joe Z.
In: Proceedings of the National Academy of Sciences of the United States of America, Vol. 102, No. 17, 26.04.2005, p. 6125-6130.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus
AU - Lin, Longnian
AU - Osan, Remus
AU - Shoham, Shy
AU - Jin, Wenjun
AU - Zuo, Wenqi
AU - Tsien, Joe Z.
PY - 2005/4/26
Y1 - 2005/4/26
N2 - To examine the network-level organizing principles by which the brain achieves its real-time encoding of episodic information, we have developed a 96-channel array to simultaneously record the activity patterns of as many as 260 individual neurons in the mouse hippocampus during various startling episodes. We find that the mnemonic startling episodes triggered firing changes in a set of CA1 neurons in both startle-type and environment-dependent manners. Pattern classification methods reveal that these firing changes form distinct ensemble representations in a low-dimensional encoding subspace. Application of a sliding window technique further enabled us to reliably capture not only the temporal dynamics of real-time network encoding but also postevent processing of newly formed ensemble traces. Our analyses revealed that the network-encoding power is derived from a set of functional coding units, termed neural cliques, in the CA1 network. The individual neurons within neural cliques exhibit "collective cospiking" dynamics that allow the neural clique to overcome the response variability of its members and to achieve real-time encoding robustness. Conversion of activation patterns of these coding unit assemblies into a set of real-time digital codes permits concise and universal representation and categorization of discrete behavioral episodes across different individual brains.
AB - To examine the network-level organizing principles by which the brain achieves its real-time encoding of episodic information, we have developed a 96-channel array to simultaneously record the activity patterns of as many as 260 individual neurons in the mouse hippocampus during various startling episodes. We find that the mnemonic startling episodes triggered firing changes in a set of CA1 neurons in both startle-type and environment-dependent manners. Pattern classification methods reveal that these firing changes form distinct ensemble representations in a low-dimensional encoding subspace. Application of a sliding window technique further enabled us to reliably capture not only the temporal dynamics of real-time network encoding but also postevent processing of newly formed ensemble traces. Our analyses revealed that the network-encoding power is derived from a set of functional coding units, termed neural cliques, in the CA1 network. The individual neurons within neural cliques exhibit "collective cospiking" dynamics that allow the neural clique to overcome the response variability of its members and to achieve real-time encoding robustness. Conversion of activation patterns of these coding unit assemblies into a set of real-time digital codes permits concise and universal representation and categorization of discrete behavioral episodes across different individual brains.
KW - Cell assembly
KW - Episodic memory
KW - Neural clique
KW - Neural code
KW - Startle
UR - http://www.scopus.com/inward/record.url?scp=17844400311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=17844400311&partnerID=8YFLogxK
U2 - 10.1073/pnas.0408233102
DO - 10.1073/pnas.0408233102
M3 - Article
C2 - 15833817
AN - SCOPUS:17844400311
VL - 102
SP - 6125
EP - 6130
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 17
ER -