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Related Concept Videos

Action Potential01:14

Action Potential

Neurons communicate by firing action potentials—the electrochemical signal that is propagated along the axon. The signal results in the release of neurotransmitters at axon terminals, thereby transmitting information to the nervous system. An action potential is a specific "all-or-none" change in membrane potential that results in a rapid spike in voltage.
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Related Experiment Video

Updated: Jun 8, 2026

A Simple Stimulatory Device for Evoking Point-like Tactile Stimuli: A Searchlight for LFP to Spike Transitions
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A likelihood method for computing selection times in spiking and local field potential activity.

Arpan Banerjee1, Heather L Dean, Bijan Pesaran

  • 1New York University, Center for Neural Science, 4 Washington Place, New York, NY 10003, USA.

Journal of Neurophysiology
|October 2, 2010
PubMed
Summary

We developed a novel method to analyze neural signal timing on single trials. This approach, using accumulated log-likelihood ratio (AccLLR), accurately estimates selection times from both spiking and local field potential (LFP) activity.

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Analyzing the timing of neural responses is crucial for understanding neural processes and functional circuitry across brain regions.
  • Existing single-trial analysis methods for neural signal timing are limited in scope and application.
  • Accurate timing analysis is essential for testing detailed models of neural circuitry underlying behavior.

Purpose of the Study:

  • To develop a novel, general, and practical method for estimating the timing of information in neural activity on single trials.
  • To measure selection times, defined as when neural activity allows reliable discrimination between two hypotheses.
  • To ensure the method works with both spiking and local field potential (LFP) activity and across different recordings.

Main Methods:

  • Developed a novel method based on the accumulated log-likelihood ratio (AccLLR) to estimate selection times from single neural trials.
  • The AccLLR method quantifies the evidence distinguishing between two alternative hypotheses about neural activity.
  • Applied the AccLLR procedure to analyze spiking and LFP activity in the posterior parietal cortex during a memory-guided saccade task.

Main Results:

  • The developed AccLLR method successfully estimates selection times from single trials using both spiking and LFP data.
  • Demonstrated the method's utility in a monkey performing a memory-guided saccade task, analyzing neural activity in the posterior parietal cortex.
  • The AccLLR approach allows for comparisons between different neural recordings, enhancing its applicability.

Conclusions:

  • The AccLLR method provides a robust framework for analyzing signal timing in the nervous system on a single-trial basis.
  • This novel approach overcomes limitations of existing methods, offering broader scope and practical application.
  • The AccLLR method is proposed as a general tool for understanding the temporal dynamics of neural information processing.