Analysis of slow (theta) oscillations as a potential temporal reference frame for information coding in sensory cortices
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Analysis of slow (theta) oscillations as a potential temporal reference frame for information coding in sensory cortices. / Kayser, Christoph; Ince, Robin A A; Panzeri, Stefano.
In: PLOS COMPUT BIOL, Vol. 8, No. 10, 2012, p. e1002717.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Analysis of slow (theta) oscillations as a potential temporal reference frame for information coding in sensory cortices
AU - Kayser, Christoph
AU - Ince, Robin A A
AU - Panzeri, Stefano
PY - 2012
Y1 - 2012
N2 - While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
AB - While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
KW - Action Potentials
KW - Animals
KW - Auditory Cortex/physiology
KW - Computational Biology
KW - Macaca mulatta
KW - Models, Neurological
KW - Signal Processing, Computer-Assisted
KW - Theta Rhythm/physiology
KW - Time Factors
KW - Visual Cortex/physiology
U2 - 10.1371/journal.pcbi.1002717
DO - 10.1371/journal.pcbi.1002717
M3 - SCORING: Journal article
C2 - 23071429
VL - 8
SP - e1002717
JO - PLOS COMPUT BIOL
JF - PLOS COMPUT BIOL
SN - 1553-734X
IS - 10
ER -