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Effect of interacting second- and third-order stimulus-dependent correlations on population-coding asymmetries
Lisandro Montangie1, Fernando Montani1
1Instituto de Física de Líquidos y Sistemas Biológicos (IFLYSIB), Universidad Nacional de La Plata, CONICET CCT-La Plata, Calle 59-789, La Plata 1900, Argentina.
Physical Review. E
|November 15, 2016
Summary
Neuronal spike correlations are common. Analyzing higher-order correlations reveals how neuronal populations interact, going beyond simple pairwise analysis to understand information processing in the brain.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Information Theory
Background:
- Spike correlations are prevalent in neural activity.
- Pairwise correlation analysis captures some population activity features but is insufficient for complex dynamics.
- Understanding neural population coding requires analyzing higher-order interactions.
Purpose of the Study:
- To extend information-theoretic frameworks for analyzing neural population activity.
- To investigate the contribution of higher-order correlations to information transmission.
- To explore the interplay between pairwise and higher-than-pairwise interactions.
Main Methods:
- Series expansion of mutual information for short timescales.
- Decomposition of information into firing rate and correlational components.
- Analysis of second- and higher-order neuronal correlations.
Main Results:
- A mixed stimulus-dependent correlation term was identified.
- This term influences the interplay between pairwise and higher-than-pairwise interactions.
- Higher-order correlations can lead to redundancy or synergy in information transmission.
Conclusions:
- Pairwise correlation analysis alone is insufficient to explain population dynamics.
- Higher-order correlations play a crucial role in neural information processing.
- The identified mixed correlation term offers new insights into neural coding mechanisms.
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