Limits...
Multiple spike time patterns occur at bifurcation points of membrane potential dynamics.

Toups JV, Fellous JM, Thomas PJ, Sejnowski TJ, Tiesinga PH - PLoS Comput. Biol. (2012)

Bottom Line: The response of a neuron to repeated somatic fluctuating current injections in vitro can elicit a reliable and precisely timed sequence of action potentials.However, at specific values called bifurcation points, large shifts in the spike times were obtained in response to small changes in the stimulus, resulting in multiple spike patterns that were revealed using an unsupervised classification method.Furthermore, the spike times shifted earlier with increasing offset.

View Article: PubMed Central - PubMed

Affiliation: Computational Neurophysics Laboratory, Department of Physics & Astronomy, University of North Carolina, Chapel Hill, NC, USA.

ABSTRACT
The response of a neuron to repeated somatic fluctuating current injections in vitro can elicit a reliable and precisely timed sequence of action potentials. The set of responses obtained across trials can also be interpreted as the response of an ensemble of similar neurons receiving the same input, with the precise spike times representing synchronous volleys that would be effective in driving postsynaptic neurons. To study the reproducibility of the output spike times for different conditions that might occur in vivo, we somatically injected aperiodic current waveforms into cortical neurons in vitro and systematically varied the amplitude and DC offset of the fluctuations. As the amplitude of the fluctuations was increased, reliability increased and the spike times remained stable over a wide range of values. However, at specific values called bifurcation points, large shifts in the spike times were obtained in response to small changes in the stimulus, resulting in multiple spike patterns that were revealed using an unsupervised classification method. Increasing the DC offset, which mimicked an overall increase in network background activity, also revealed bifurcation points and increased the reliability. Furthermore, the spike times shifted earlier with increasing offset. Although the reliability was reduced at bifurcation points, a theoretical analysis showed that the information about the stimulus time course was increased because each of the spike time patterns contained different information about the input.

Show MeSH

Related in: MedlinePlus

Information about the time course of the stimulus waveform is increased at bifurcation points because of the presence of multiple spike patterns.Data from an example model neuron as described in Figure 5. (A) Rastergram for a short time segment across 100 trials for a (bottom) low-noise and (top) medium-noise model neuron. The noise level refers to the magnitude of a white noise current that varied from trial-to-trial relative to the amplitude of the repeated fluctuating current waveform (shown as a thin solid line on top of each rastergram). For low noise, the neuron spiked only at six events, whereas for medium noise there were additional events. (B) We calculated the reliability and jitter for each event for the entire stimulus duration (1100 ms). The open circles represent the low-noise, and the asterisks represent the medium-noise result. The gray-filled region schematically represents the combination of jitter and reliability for which a putative postsynaptic neuron would generate a spike. (C) The spike-triggered average obtained across the entire stimulus period for (solid line) the medium-noise neuron and (dotted line) the low-noise neuron. (D) The stimulus waveform reconstructed using the low-noise (dotted line) and medium-noise (solid line) spike trains was compared to the actual stimulus waveform (gray solid line). We used an event-based reconstruction, where each extracted event contributed equally to the reconstruction regardless of reliability and jitter, as long as the reliability exceeded 5%. The three curves are offset from each other for clarity.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3475656&req=5

pcbi-1002615-g006: Information about the time course of the stimulus waveform is increased at bifurcation points because of the presence of multiple spike patterns.Data from an example model neuron as described in Figure 5. (A) Rastergram for a short time segment across 100 trials for a (bottom) low-noise and (top) medium-noise model neuron. The noise level refers to the magnitude of a white noise current that varied from trial-to-trial relative to the amplitude of the repeated fluctuating current waveform (shown as a thin solid line on top of each rastergram). For low noise, the neuron spiked only at six events, whereas for medium noise there were additional events. (B) We calculated the reliability and jitter for each event for the entire stimulus duration (1100 ms). The open circles represent the low-noise, and the asterisks represent the medium-noise result. The gray-filled region schematically represents the combination of jitter and reliability for which a putative postsynaptic neuron would generate a spike. (C) The spike-triggered average obtained across the entire stimulus period for (solid line) the medium-noise neuron and (dotted line) the low-noise neuron. (D) The stimulus waveform reconstructed using the low-noise (dotted line) and medium-noise (solid line) spike trains was compared to the actual stimulus waveform (gray solid line). We used an event-based reconstruction, where each extracted event contributed equally to the reconstruction regardless of reliability and jitter, as long as the reliability exceeded 5%. The three curves are offset from each other for clarity.

Mentions: We investigated the ability of an ensemble to reconstruct an input waveform in different noise regimes. In order to focus on stimulus reconstruction via ensemble event detection, we drove the Wang-Buzsaki model neuron with a frequency-modulated (FM) waveform. The FM waveform is simpler than a general Gaussian process, in that comprises a series of distinct upswings of equal amplitude, but at variable intervals and slopes. We compared the response at a bifurcation point under two circumstances: low noise and medium noise. In this way we could compare responses at the same amplitude with a similar, but not identical, spike rate. For the low-noise case in Figure 6A, there were six events during the time interval displayed (bottom, the ticks representing the spikes coalesced into gray vertical lines), but for the medium-noise case there were additional events with a reduced reliability and precision (top). We applied the event-based analysis to the entire simulation time interval (1100 ms) and determined for each event the reliability and precision (Figure 6B). We also determined the spike-triggered average (STA) of the stimulus for both cases (Figure 6C). Using all detected events with a reliability exceeding 5% and the measured STA, we reconstructed the stimulus waveform (Figure 6D). The ensemble of medium-noise spike trains, with their multiple spike patterns, yielded a better reconstruction (middle) than the low-noise case (top) from a single spike pattern.


Multiple spike time patterns occur at bifurcation points of membrane potential dynamics.

Toups JV, Fellous JM, Thomas PJ, Sejnowski TJ, Tiesinga PH - PLoS Comput. Biol. (2012)

Information about the time course of the stimulus waveform is increased at bifurcation points because of the presence of multiple spike patterns.Data from an example model neuron as described in Figure 5. (A) Rastergram for a short time segment across 100 trials for a (bottom) low-noise and (top) medium-noise model neuron. The noise level refers to the magnitude of a white noise current that varied from trial-to-trial relative to the amplitude of the repeated fluctuating current waveform (shown as a thin solid line on top of each rastergram). For low noise, the neuron spiked only at six events, whereas for medium noise there were additional events. (B) We calculated the reliability and jitter for each event for the entire stimulus duration (1100 ms). The open circles represent the low-noise, and the asterisks represent the medium-noise result. The gray-filled region schematically represents the combination of jitter and reliability for which a putative postsynaptic neuron would generate a spike. (C) The spike-triggered average obtained across the entire stimulus period for (solid line) the medium-noise neuron and (dotted line) the low-noise neuron. (D) The stimulus waveform reconstructed using the low-noise (dotted line) and medium-noise (solid line) spike trains was compared to the actual stimulus waveform (gray solid line). We used an event-based reconstruction, where each extracted event contributed equally to the reconstruction regardless of reliability and jitter, as long as the reliability exceeded 5%. The three curves are offset from each other for clarity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475656&req=5

pcbi-1002615-g006: Information about the time course of the stimulus waveform is increased at bifurcation points because of the presence of multiple spike patterns.Data from an example model neuron as described in Figure 5. (A) Rastergram for a short time segment across 100 trials for a (bottom) low-noise and (top) medium-noise model neuron. The noise level refers to the magnitude of a white noise current that varied from trial-to-trial relative to the amplitude of the repeated fluctuating current waveform (shown as a thin solid line on top of each rastergram). For low noise, the neuron spiked only at six events, whereas for medium noise there were additional events. (B) We calculated the reliability and jitter for each event for the entire stimulus duration (1100 ms). The open circles represent the low-noise, and the asterisks represent the medium-noise result. The gray-filled region schematically represents the combination of jitter and reliability for which a putative postsynaptic neuron would generate a spike. (C) The spike-triggered average obtained across the entire stimulus period for (solid line) the medium-noise neuron and (dotted line) the low-noise neuron. (D) The stimulus waveform reconstructed using the low-noise (dotted line) and medium-noise (solid line) spike trains was compared to the actual stimulus waveform (gray solid line). We used an event-based reconstruction, where each extracted event contributed equally to the reconstruction regardless of reliability and jitter, as long as the reliability exceeded 5%. The three curves are offset from each other for clarity.
Mentions: We investigated the ability of an ensemble to reconstruct an input waveform in different noise regimes. In order to focus on stimulus reconstruction via ensemble event detection, we drove the Wang-Buzsaki model neuron with a frequency-modulated (FM) waveform. The FM waveform is simpler than a general Gaussian process, in that comprises a series of distinct upswings of equal amplitude, but at variable intervals and slopes. We compared the response at a bifurcation point under two circumstances: low noise and medium noise. In this way we could compare responses at the same amplitude with a similar, but not identical, spike rate. For the low-noise case in Figure 6A, there were six events during the time interval displayed (bottom, the ticks representing the spikes coalesced into gray vertical lines), but for the medium-noise case there were additional events with a reduced reliability and precision (top). We applied the event-based analysis to the entire simulation time interval (1100 ms) and determined for each event the reliability and precision (Figure 6B). We also determined the spike-triggered average (STA) of the stimulus for both cases (Figure 6C). Using all detected events with a reliability exceeding 5% and the measured STA, we reconstructed the stimulus waveform (Figure 6D). The ensemble of medium-noise spike trains, with their multiple spike patterns, yielded a better reconstruction (middle) than the low-noise case (top) from a single spike pattern.

Bottom Line: The response of a neuron to repeated somatic fluctuating current injections in vitro can elicit a reliable and precisely timed sequence of action potentials.However, at specific values called bifurcation points, large shifts in the spike times were obtained in response to small changes in the stimulus, resulting in multiple spike patterns that were revealed using an unsupervised classification method.Furthermore, the spike times shifted earlier with increasing offset.

View Article: PubMed Central - PubMed

Affiliation: Computational Neurophysics Laboratory, Department of Physics & Astronomy, University of North Carolina, Chapel Hill, NC, USA.

ABSTRACT
The response of a neuron to repeated somatic fluctuating current injections in vitro can elicit a reliable and precisely timed sequence of action potentials. The set of responses obtained across trials can also be interpreted as the response of an ensemble of similar neurons receiving the same input, with the precise spike times representing synchronous volleys that would be effective in driving postsynaptic neurons. To study the reproducibility of the output spike times for different conditions that might occur in vivo, we somatically injected aperiodic current waveforms into cortical neurons in vitro and systematically varied the amplitude and DC offset of the fluctuations. As the amplitude of the fluctuations was increased, reliability increased and the spike times remained stable over a wide range of values. However, at specific values called bifurcation points, large shifts in the spike times were obtained in response to small changes in the stimulus, resulting in multiple spike patterns that were revealed using an unsupervised classification method. Increasing the DC offset, which mimicked an overall increase in network background activity, also revealed bifurcation points and increased the reliability. Furthermore, the spike times shifted earlier with increasing offset. Although the reliability was reduced at bifurcation points, a theoretical analysis showed that the information about the stimulus time course was increased because each of the spike time patterns contained different information about the input.

Show MeSH
Related in: MedlinePlus