Work

LatenZy : nonparametric, binning-free estimation of latencies from neural spiking data

Year: 2025

Type: article

Abstract: We present latenZy and latenZy2, two nonparametric, binning-free methods for precise latency estimation from neural spiking data. Unlike traditional approaches, our tools avoid arbitrary parameters, enhancing reproducibility and comparability. Validated on real electrophysiological datasets, these methods outperform conventional techniques by providing less variable estimates and more accurately capturing known physiological timing effects. Crucially, statistical tests based on latenZy estimates require fewer neurons to detect significant latency differences, boosting efficiency in neural population analyses.

Source: Journal of Neurophysiology

DOI: 10.1152/jn.00332.2025

Authors: Robin Haak, J. Alexander Heimel

Institutions: Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences

Language: English

Topic: Neural dynamics and brain function

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: hybrid

Funder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Award: How innocuous stimuli are learned to be ignored