TY - JOUR
T1 - Testing a neural coding hypothesis using surrogate data
AU - Hirata, Yoshito
AU - Katori, Yuichi
AU - Shimokawa, Hidetoshi
AU - Suzuki, Hideyuki
AU - Blenkinsop, Timothy A.
AU - Lang, Eric J.
AU - Aihara, Kazuyuki
N1 - Funding Information:
This research is partially supported by Grant-in-Aid for Scientific Research on Priority Areas – Higher-Order Brain Functions – (17022012), the Advanced and Innovational Research program in Life Sciences from MEXT of Japan, NIAAA (AA016566), and NINDS (NS037028).
PY - 2008/7/30
Y1 - 2008/7/30
N2 - Determining how a particular neuron, or population of neurons, encodes information in their spike trains is not a trivial problem, because multiple coding schemes exist and are not necessarily mutually exclusive. Coding schemes generally fall into one of two broad categories, which we refer to as rate and temporal coding. In rate coding schemes, information is encoded in the variations of the average firing rate of the spike train. In contrast, in temporal coding schemes, information is encoded in the specific timing of the individual spikes that comprise the train. Here, we describe a method for testing the presence of temporal encoding of information. Suppose that a set of original spike trains is given. First, surrogate spike trains are generated by randomizing each of the original spike trains subject to the following constraints: the local average firing rate is approximately preserved, while the overall average firing rate and the distribution of primary interspike intervals are perfectly preserved. These constraints ensure that any rate coding of information present in the original spike trains is preserved in the members of the surrogate population. The null-hypothesis is rejected when additional information is found to be present in the original spike trains, implying that temporal coding is present. The method is validated using artificial data, and then demonstrated using real neuronal data.
AB - Determining how a particular neuron, or population of neurons, encodes information in their spike trains is not a trivial problem, because multiple coding schemes exist and are not necessarily mutually exclusive. Coding schemes generally fall into one of two broad categories, which we refer to as rate and temporal coding. In rate coding schemes, information is encoded in the variations of the average firing rate of the spike train. In contrast, in temporal coding schemes, information is encoded in the specific timing of the individual spikes that comprise the train. Here, we describe a method for testing the presence of temporal encoding of information. Suppose that a set of original spike trains is given. First, surrogate spike trains are generated by randomizing each of the original spike trains subject to the following constraints: the local average firing rate is approximately preserved, while the overall average firing rate and the distribution of primary interspike intervals are perfectly preserved. These constraints ensure that any rate coding of information present in the original spike trains is preserved in the members of the surrogate population. The null-hypothesis is rejected when additional information is found to be present in the original spike trains, implying that temporal coding is present. The method is validated using artificial data, and then demonstrated using real neuronal data.
KW - Cerebellum
KW - Cricket
KW - Multielectrode
KW - Rate coding
KW - Simultaneous coding
KW - Spike trains
KW - Synchrony
KW - Temporal coding
UR - http://www.scopus.com/inward/record.url?scp=46249092236&partnerID=8YFLogxK
U2 - 10.1016/j.jneumeth.2008.05.004
DO - 10.1016/j.jneumeth.2008.05.004
M3 - Article
C2 - 18565591
AN - SCOPUS:46249092236
SN - 0165-0270
VL - 172
SP - 312
EP - 322
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
IS - 2
ER -