Paper Info
Title
Detection Of Stimuli Changes In Neural Eventograms Using The Line Of Synchronization Of Global Recurrence Plots
Abstract
Reliable detection of stimulus-driven states and their separation from internal state-driven spontaneous activity is an important step towards inferring temporal dynamics of neurons and its relation to the perception of external inputs. This is challenging, especially when no prior assumptions about the underlying model and data generating processes exist. To address this task, we applied efficient recurrence quantification analysis (RQA) based on global recurrence plots (RP) for accurate identification of the onset and offset of visual neuronal responses caused by distinct types of visual stimuli. In particular, these critical times are estimated by taking the first order difference of the line of synchronization extracted from the associated global RP. Our approach was evaluated using a real dataset of visually-driven neuronal responses and spontaneous activity (recorded by in vivo 2-photon calcium imaging). It accurately detects both the onset and offset time instants in the eventograms of pyramidal neurons in a completely model agnostic framework.
Year
DOI
Venue
2019
10.1109/icassp.2019.8683460
2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Keywords
Field
DocType
Recurrence quantification analysis, global recurrence plot, line of synchronization, neural eventograms, stimuli change detection
Synchronization,Pattern recognition,First order,Computer science,Calcium imaging,Artificial intelligence,Stimulus (physiology),Perception,Recurrence quantification analysis,Offset (computer science),Visual perception
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
George Tzagkarakis113917.94
G. Palagina200.68
I. Smirnakis300.34
Stelios M. Smirnakis4154.06
Maria Papadopouli552058.57