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xcor function of  (MathWorks Inc)


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    MathWorks Inc xcor function of
    ( A ): Example of an individual stimulus/pupillary signal cross-correlation using <t>the</t> <t>Matlab</t> <t>xcor</t> function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.
    Xcor Function Of, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/xcor+function+of/pmc11036301-173-6-9
    Average 90 stars, based on 1 article reviews
    xcor function of - by Bioz Stars, 2026-08
    90/100 stars

    Images

    1) Product Images from "Method to Quickly Map Multifocal Pupillary Response Fields (mPRF) Using Frequency Tagging"

    Article Title: Method to Quickly Map Multifocal Pupillary Response Fields (mPRF) Using Frequency Tagging

    Journal: Vision

    doi: 10.3390/vision8020017

    ( A ): Example of an individual stimulus/pupillary signal cross-correlation using the Matlab xcor function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.
    Figure Legend Snippet: ( A ): Example of an individual stimulus/pupillary signal cross-correlation using the Matlab xcor function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.

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    ( A ): Example of an individual stimulus/pupillary signal cross-correlation using <t>the</t> <t>Matlab</t> <t>xcor</t> function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.
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    Image Search Results


    ( A ): Example of an individual stimulus/pupillary signal cross-correlation using the Matlab xcor function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.

    Journal: Vision

    Article Title: Method to Quickly Map Multifocal Pupillary Response Fields (mPRF) Using Frequency Tagging

    doi: 10.3390/vision8020017

    Figure Lengend Snippet: ( A ): Example of an individual stimulus/pupillary signal cross-correlation using the Matlab xcor function. ( B ): Histogram of phase lags for all participants. Bottom left: right eye; bottom middle: left eye. ( C ): Correlation between cross-correlation lags of the right and left eyes of all participants. Red lines show the linear regression (r = 083, p < 0.0001) together with 95% confidence intervals. Note that because pupillary signals are down-sampled to 60 Hz, the time resolution of lags is only 16.666 ms such that phase lags from different participants overlap. The high correlation shown here indicate that similar lags are observed for the right and left eyes of each participant.

    Article Snippet: The temporal lags (computed with the xcor function of Matlab for each run) are around 500 ms (range 420–540 ms, ) and are comparable to the maximum constriction latencies reported for the PLR, ranging between 500 and 600 ms [ , , ].

    Techniques: