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Which spike train distance is most suitable for distinguishing rate and temporal coding?
Eero Satuvuori1, Thomas Kreuz2
1Institute for Complex Systems, CNR, Sesto Fiorentino, Italy; Department of Physics and Astronomy, University of Florence, Sesto Fiorentino, Italy; MOVE Research Institute, Department of Human Movement Sciences, Vrije Universiteit Amsterdam, The Netherlands.
Journal of Neuroscience Methods
|February 21, 2018
Summary
This study evaluates spike train distances for neuronal coding, finding that spike-resolved measures are better for low rates, while time-resolved measures excel at normal rates. The best choice depends on the specific data rates analyzed.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Information Theory
Background:
- Neuronal coding assumes consistent neuron responses to repeated stimuli.
- Spike train distances (e.g., Victor-Purpura, van Rossum, RI-SPIKE) quantify response similarity.
- Existing methods include spike-resolved and time-resolved distance measures.
Purpose of the Study:
- To investigate how spike train distance sensitivity to temporal coding varies with firing rates.
- To assess the performance of different spike train distances at very low neuronal firing rates.
- To provide guidance on selecting appropriate spike train distance measures based on data characteristics.
Main Methods:
- Utilized independent steady-rate Poisson processes as surrogate spike trains.
- Analyzed the sensitivity of various spike train distances to temporal coding across different rates.
- Focused on the behavior of spike-resolved and time-resolved distances at low firing rates.
Main Results:
- Spike-resolved distances retain rate information, beneficial for very low rates but problematic at high rates.
- Time-resolved distances offer superior temporal coding detection at normal rates but yield artifacts at very low rates.
- The RI-SPIKE-distance uniquely isolates timing information.
Conclusions:
- The optimal spike train distance measure is rate-dependent.
- Spike-resolved distances are more suitable for very low firing rates.
- A summary table is provided to aid in selecting the most appropriate measure for diverse neuronal data analysis scenarios.
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