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Sub-Millisecond Firing Synchrony of Closely Neighboring Pyramidal Neurons in Hippocampal CA1 of Rats During Delayed Non-Matching to Sample Task.

Takahashi S, Sakurai Y - Front Neural Circuits (2009)

Bottom Line: The synchrony generally co-occurred with the firing rate modulation in relation to both internal (retention and comparison) and external (stimulus input and motor output) events during the task.However, the synchrony occasionally occurred in relation to stimulus inputs even when rate modulation was clearly absent, suggesting that the synchrony is not simply accompanied with firing rate modulation and that the synchrony and the rate modulation might code similar information independently.We therefore conclude that the sub-millisecond firing synchrony in the hippocampus is an effective carrier for propagating information - as represented by the firing rate modulations - to downstream neurons.

View Article: PubMed Central - PubMed

Affiliation: Khoyama Center for Neuroscience, Faculty of Computer Science and Engineering, Kyoto Sangyo University Kyoto, Japan.

ABSTRACT
Firing synchrony among neurons is thought to play functional roles in several brain regions. In theoretical analyses, firing synchrony among neurons within sub-millisecond precision is feasible to convey information. However, little is known about the occurrence and the functional significance of the sub-millisecond synchrony among closely neighboring neurons in the brain of behaving animals because of a technical issue: spikes simultaneously generated from closely neighboring neurons are overlapped in the extracellular space and are not easily separated. As described herein, using a unique spike sorting technique based on independent component analysis together with extracellular 12-channel multi-electrodes (dodecatrodes), we separated such overlapping spikes and investigated the firing synchrony among closely neighboring pyramidal neurons in the hippocampal CA1 of rats during a delayed non-matching to sample task. Results showed that closely neighboring pyramidal neurons in the hippocampal CA1 can co-fire with sub-millisecond precision. The synchrony generally co-occurred with the firing rate modulation in relation to both internal (retention and comparison) and external (stimulus input and motor output) events during the task. However, the synchrony occasionally occurred in relation to stimulus inputs even when rate modulation was clearly absent, suggesting that the synchrony is not simply accompanied with firing rate modulation and that the synchrony and the rate modulation might code similar information independently. We therefore conclude that the sub-millisecond firing synchrony in the hippocampus is an effective carrier for propagating information - as represented by the firing rate modulations - to downstream neurons.

No MeSH data available.


Related in: MedlinePlus

SSSs related to stimulus inputs are associated with firing rate modulations. Comparison of SSSs and rate modulations between high tone and low tone trials was selected in this example. Each subfigure averages all correct trials of a session. Results of U-tests of 5 s of tone presentation in the preceding trial, 5 s of delay, and 2 s of tone presentation in the next trial are shown. Additional details are described in Section ‘Materials and Methods’. (A) Firing rates of neuron 7 in high tone (red) and low tone (blue) trials. (B,C) Raster plots of spikes of neuron 7 in high tone (red) and low tone (blue) trials. (D) P-values of neuron 7 for a difference between rates in high tone and low tone trials. The dotted red line represents the level of significance, α (=2; P = 0.01). The significant period (P < 0.01) is enclosed in the green shaded box. (E)–(I) and (N) are shown in the same manner as in (A)–(D). (E) Firing rates of neuron 8. (F,G) Raster plots of neuron 8. (H) P-values of neuron 8. (I) Rates of the SSS between neurons 7 and 8. (J–M) In copies of raster plots from (B), (C), (F), and (G) (black dots), SSSs are shown as green dots. (N) P-value of the SSS between neurons 7 and 8. The significant firing rates of neurons 7 and 8 are associated with SSS.
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Figure 5: SSSs related to stimulus inputs are associated with firing rate modulations. Comparison of SSSs and rate modulations between high tone and low tone trials was selected in this example. Each subfigure averages all correct trials of a session. Results of U-tests of 5 s of tone presentation in the preceding trial, 5 s of delay, and 2 s of tone presentation in the next trial are shown. Additional details are described in Section ‘Materials and Methods’. (A) Firing rates of neuron 7 in high tone (red) and low tone (blue) trials. (B,C) Raster plots of spikes of neuron 7 in high tone (red) and low tone (blue) trials. (D) P-values of neuron 7 for a difference between rates in high tone and low tone trials. The dotted red line represents the level of significance, α (=2; P = 0.01). The significant period (P < 0.01) is enclosed in the green shaded box. (E)–(I) and (N) are shown in the same manner as in (A)–(D). (E) Firing rates of neuron 8. (F,G) Raster plots of neuron 8. (H) P-values of neuron 8. (I) Rates of the SSS between neurons 7 and 8. (J–M) In copies of raster plots from (B), (C), (F), and (G) (black dots), SSSs are shown as green dots. (N) P-value of the SSS between neurons 7 and 8. The significant firing rates of neurons 7 and 8 are associated with SSS.

Mentions: To confirm whether SSSs can code information as well as rate modulations, we analyzed the association between the firing rate of SSS of a group of neurons (or spikes of participating neurons) and behavioral events during a task. We defined that the firing rate of SSS as a frequency of spikes co-fired from two or more neurons within precision of less than 1 ms. Unitary event analysis (UEA) (Riehle et al., 1997) is a good tool that enables us to investigate such dynamic synchronies. However, because it has a limitation related to firing rates (Roy et al., 2000), neurons in our datasets whose firing rates cannot exceed the limitation cannot be analyzed using UEA. For that reason, we modified UEA using a conventional non-parametric statistical test: the Mann–Whitney U–test. Each firing rate of SSS of a group of neurons (e.g. Figure 5I) and of spike of the participating neurons (e.g. Figures 5D,H) was computed by sliding a boxcar window of 1 s in 1 ms steps over the behavioral events (stimulus inputs, retention of a stimulus, motor outputs and comparison of stimuli). To determine whether the spikes of a neuron or SSSs among the considered neurons are associated with behavioral events, the statistically significant difference in the firing rate of spikes of an individual neuron or SSSs of a group of neurons between the sets of behavioral events (stimulus inputs and retention of a stimulus: high/low tone; motor outputs: go/no-go responses; comparison of stimuli: correct/erroneous match trials) was tested using a two-tailed Mann–Whitney U-test for each boxcar window of 1 s in 1 ms steps. For SSSs, to eliminate the expected rate of firing coincidence, we subtracted the product of individual firing rates of participating neurons from the firing rate of SSS of a group of neurons based on the hypothesis of independent firing (Aertsen et al., 1989; Riehle et al., 1997). To verify the hypothesis, we performed a simple simulation in which two Poisson spike trains for 10 s whose firing rates are set at 0.1, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 Hz were constructed and analyzed. The correlation coefficient and linear regression coefficient between the product of individual firing rates of two Poisson spike trains and the firing rates of the SSS between them were 0.97 and 1.0, respectively, under the simulation (Figure 2C), validating this hypothesis.


Sub-Millisecond Firing Synchrony of Closely Neighboring Pyramidal Neurons in Hippocampal CA1 of Rats During Delayed Non-Matching to Sample Task.

Takahashi S, Sakurai Y - Front Neural Circuits (2009)

SSSs related to stimulus inputs are associated with firing rate modulations. Comparison of SSSs and rate modulations between high tone and low tone trials was selected in this example. Each subfigure averages all correct trials of a session. Results of U-tests of 5 s of tone presentation in the preceding trial, 5 s of delay, and 2 s of tone presentation in the next trial are shown. Additional details are described in Section ‘Materials and Methods’. (A) Firing rates of neuron 7 in high tone (red) and low tone (blue) trials. (B,C) Raster plots of spikes of neuron 7 in high tone (red) and low tone (blue) trials. (D) P-values of neuron 7 for a difference between rates in high tone and low tone trials. The dotted red line represents the level of significance, α (=2; P = 0.01). The significant period (P < 0.01) is enclosed in the green shaded box. (E)–(I) and (N) are shown in the same manner as in (A)–(D). (E) Firing rates of neuron 8. (F,G) Raster plots of neuron 8. (H) P-values of neuron 8. (I) Rates of the SSS between neurons 7 and 8. (J–M) In copies of raster plots from (B), (C), (F), and (G) (black dots), SSSs are shown as green dots. (N) P-value of the SSS between neurons 7 and 8. The significant firing rates of neurons 7 and 8 are associated with SSS.
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Related In: Results  -  Collection

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Show All Figures
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Figure 5: SSSs related to stimulus inputs are associated with firing rate modulations. Comparison of SSSs and rate modulations between high tone and low tone trials was selected in this example. Each subfigure averages all correct trials of a session. Results of U-tests of 5 s of tone presentation in the preceding trial, 5 s of delay, and 2 s of tone presentation in the next trial are shown. Additional details are described in Section ‘Materials and Methods’. (A) Firing rates of neuron 7 in high tone (red) and low tone (blue) trials. (B,C) Raster plots of spikes of neuron 7 in high tone (red) and low tone (blue) trials. (D) P-values of neuron 7 for a difference between rates in high tone and low tone trials. The dotted red line represents the level of significance, α (=2; P = 0.01). The significant period (P < 0.01) is enclosed in the green shaded box. (E)–(I) and (N) are shown in the same manner as in (A)–(D). (E) Firing rates of neuron 8. (F,G) Raster plots of neuron 8. (H) P-values of neuron 8. (I) Rates of the SSS between neurons 7 and 8. (J–M) In copies of raster plots from (B), (C), (F), and (G) (black dots), SSSs are shown as green dots. (N) P-value of the SSS between neurons 7 and 8. The significant firing rates of neurons 7 and 8 are associated with SSS.
Mentions: To confirm whether SSSs can code information as well as rate modulations, we analyzed the association between the firing rate of SSS of a group of neurons (or spikes of participating neurons) and behavioral events during a task. We defined that the firing rate of SSS as a frequency of spikes co-fired from two or more neurons within precision of less than 1 ms. Unitary event analysis (UEA) (Riehle et al., 1997) is a good tool that enables us to investigate such dynamic synchronies. However, because it has a limitation related to firing rates (Roy et al., 2000), neurons in our datasets whose firing rates cannot exceed the limitation cannot be analyzed using UEA. For that reason, we modified UEA using a conventional non-parametric statistical test: the Mann–Whitney U–test. Each firing rate of SSS of a group of neurons (e.g. Figure 5I) and of spike of the participating neurons (e.g. Figures 5D,H) was computed by sliding a boxcar window of 1 s in 1 ms steps over the behavioral events (stimulus inputs, retention of a stimulus, motor outputs and comparison of stimuli). To determine whether the spikes of a neuron or SSSs among the considered neurons are associated with behavioral events, the statistically significant difference in the firing rate of spikes of an individual neuron or SSSs of a group of neurons between the sets of behavioral events (stimulus inputs and retention of a stimulus: high/low tone; motor outputs: go/no-go responses; comparison of stimuli: correct/erroneous match trials) was tested using a two-tailed Mann–Whitney U-test for each boxcar window of 1 s in 1 ms steps. For SSSs, to eliminate the expected rate of firing coincidence, we subtracted the product of individual firing rates of participating neurons from the firing rate of SSS of a group of neurons based on the hypothesis of independent firing (Aertsen et al., 1989; Riehle et al., 1997). To verify the hypothesis, we performed a simple simulation in which two Poisson spike trains for 10 s whose firing rates are set at 0.1, 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, and 10 Hz were constructed and analyzed. The correlation coefficient and linear regression coefficient between the product of individual firing rates of two Poisson spike trains and the firing rates of the SSS between them were 0.97 and 1.0, respectively, under the simulation (Figure 2C), validating this hypothesis.

Bottom Line: The synchrony generally co-occurred with the firing rate modulation in relation to both internal (retention and comparison) and external (stimulus input and motor output) events during the task.However, the synchrony occasionally occurred in relation to stimulus inputs even when rate modulation was clearly absent, suggesting that the synchrony is not simply accompanied with firing rate modulation and that the synchrony and the rate modulation might code similar information independently.We therefore conclude that the sub-millisecond firing synchrony in the hippocampus is an effective carrier for propagating information - as represented by the firing rate modulations - to downstream neurons.

View Article: PubMed Central - PubMed

Affiliation: Khoyama Center for Neuroscience, Faculty of Computer Science and Engineering, Kyoto Sangyo University Kyoto, Japan.

ABSTRACT
Firing synchrony among neurons is thought to play functional roles in several brain regions. In theoretical analyses, firing synchrony among neurons within sub-millisecond precision is feasible to convey information. However, little is known about the occurrence and the functional significance of the sub-millisecond synchrony among closely neighboring neurons in the brain of behaving animals because of a technical issue: spikes simultaneously generated from closely neighboring neurons are overlapped in the extracellular space and are not easily separated. As described herein, using a unique spike sorting technique based on independent component analysis together with extracellular 12-channel multi-electrodes (dodecatrodes), we separated such overlapping spikes and investigated the firing synchrony among closely neighboring pyramidal neurons in the hippocampal CA1 of rats during a delayed non-matching to sample task. Results showed that closely neighboring pyramidal neurons in the hippocampal CA1 can co-fire with sub-millisecond precision. The synchrony generally co-occurred with the firing rate modulation in relation to both internal (retention and comparison) and external (stimulus input and motor output) events during the task. However, the synchrony occasionally occurred in relation to stimulus inputs even when rate modulation was clearly absent, suggesting that the synchrony is not simply accompanied with firing rate modulation and that the synchrony and the rate modulation might code similar information independently. We therefore conclude that the sub-millisecond firing synchrony in the hippocampus is an effective carrier for propagating information - as represented by the firing rate modulations - to downstream neurons.

No MeSH data available.


Related in: MedlinePlus