Neurocomputer Nearest Matched Filter Classification Of Spatiotemporal Patterns

1987 ◽  
Author(s):  
Robert Hecht-Nielsen
Keyword(s):  
Matched Filter ◽  
Spatiotemporal Patterns

Nearest matched filter classification of spatiotemporal patterns

1987 ◽  
Vol 26 (10) ◽  
pp. 1892 ◽  
Author(s):  
Robert Hecht-Nielsen
Keyword(s):  
Matched Filter ◽  
Spatiotemporal Patterns

scholarly journals A Matched-Filter-Based Algorithm for Subcellular Classification of T-System in Cardiac Tissues

2019 ◽  
Vol 116 (8) ◽  
pp. 1386-1393
Author(s):  
Dylan F. Colli ◽  
S. Ryan Blood ◽  
Aparna C. Sankarankutty ◽  
Frank B. Sachse ◽  
Michael Frisk ◽  
...  
Keyword(s):  
Matched Filter ◽  
Cardiac Tissues ◽  
T System

scholarly journals Temporal accuracy of human cortico-cortical interactions

2016 ◽  
Vol 115 (4) ◽  
pp. 1810-1820 ◽  
Author(s):  
Idan Tal ◽  
Moshe Abeles
Keyword(s):  
Cognitive Processes ◽  
Template Matching ◽  
Cognitive Process ◽  
Point Processes ◽  
Time Window ◽  
Spatiotemporal Patterns ◽  
Timing Accuracy ◽  
Synthetic Aperture Magnetometry ◽  
Better Than

The precision in space and time of interactions among multiple cortical sites was evaluated by examining repeating precise spatiotemporal patterns of instances in which cortical currents showed brief amplitude undulations. The amplitudes of the cortical current dipoles were estimated by applying a variant of synthetic aperture magnetometry to magnetoencephalographic (MEG) recordings of subjects tapping to metric auditory rhythms of drum beats. Brief amplitude undulations were detected in the currents by template matching at a rate of 2–3 per second. Their timing was treated as point processes, and precise spatiotemporal patterns were searched for. By randomly teetering these point processes within a time window W, we estimated the accuracy of the timing of these brief amplitude undulations and compared the results with those obtained by applying the same analysis to traces composed of random numbers. The results demonstrated that the timing accuracy of patterns was better than 3 ms. Successful classification of two different cognitive processes based on these patterns suggests that at least some of the repeating patterns are specific to a cognitive process.

scholarly journals A Matched-filter Based Algorithm for Subcellular Classification of T-system in Cardiac Tissues

2018 ◽  
Author(s):  
Dylan F Colli ◽  
Ryan Blood ◽  
Aparna C Sankarankutty ◽  
Frank B Sachse ◽  
Michael Frisk ◽  
...  
Keyword(s):  
Matched Filter ◽  
Surface Membrane ◽  
System Structure ◽  
Isolated Cells ◽  
Transverse Tubular System ◽  
Cardiac Tissues ◽  
System Characterization ◽  
Filter Approach ◽  
T System

In mammalian ventricular cardiomyocytes, invaginations of the surface membrane form the transverse tubular system (T-system) which consists of transverse tubules (TTs) that align with sarcomeres and Z-lines as well as longitudinal tubules (LTs) that are present between Z-lines in some species. In many cardiac disease etiologies the T-system is perturbed, which is believed to promote spatially heterogeneous, dyssynchronous Ca2+ release and inefficient contraction. In general, T-system characterization approaches have been directed primarily at isolated cells and do not detect subcellular T-system heterogeneity. Here we present MatchedMyo, a matched-filter based algorithm for subcellular T-system characterization in isolated cardiomyocytes and millimeter-scale myocardial sections. The algorithm utilizes "filters" representative of TTs, LTs, and T-system absence. Application of the algorithm to cardiomyocytes isolated from rat disease models of myocardial infarction (MI), dilated cardiomyopathy induced via aortic banding (AB), and sham surgery confirmed and quantified heterogeneous T-system structure and remodeling. Cardiomyocytes from post-MI hearts exhibited increasing T-system disarray as proximity to the infarct increased. We found significant (p<0.05, Welch's t-test) increases in LT density within cardiomyocytes proximal to the infarct (12±3%, data reported as mean ± SD, n=3) vs. sham (4±2%, n=5), but not distal to the infarct (7±1%, n=3). The algorithm also detected decreases in TTs within 5° of the myocyte minor axis for isolated AB (36±9%, n=3) and MI cardiomyocytes located intermediate (37±4%, n=3) and proximal (34±4%, n=3) to the infarct vs. sham (57±12%, n=5). Application of bootstrapping to rabbit MI tissue revealed distal sections comprised 18.9±1.0% TTs while proximal sections comprised 10.1±0.8% TTs (p<0.05), a 46.6% decrease. The matched filter approach therefore provides a robust and scalable technique for T-system characterization from isolated cells through millimeter-scale myocardial sections.

Dynamic LVQ Models for Classification of Spatiotemporal Patterns

2016 ◽  
Author(s):  
Isaque Q. Monteiro ◽  
Guilherme A. Barreto ◽  
Patrícia V. Nascimento
Keyword(s):  
Spatiotemporal Patterns

scholarly journals Machine classification of spatiotemporal patterns: automated parameter search in a rebounding spiking network

2020 ◽  
Vol 14 (3) ◽  
pp. 267-280 ◽  
Author(s):  
Lawrence Oprea ◽  
Christopher C. Pack ◽  
Anmar Khadra
Keyword(s):  
Spatiotemporal Patterns ◽  
Spiking Network ◽  
Parameter Search
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