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magnitude-squared coherence function mscohere  (MathWorks Inc)


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    MathWorks Inc magnitude-squared coherence function mscohere
    Magnitude Squared Coherence Function Mscohere, 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/mscohere+function/pm40440290-110-5-9
    Average 90 stars, based on 1 article reviews
    magnitude-squared coherence function mscohere - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    other:

    Article Title: Beyond-local neural information processing in neuronal networks
    Article Snippet: We computed the coherence analysis with the Matlab function mscohere() .

    Article Title: Frequency-coded spatiotemporal control of telencephalic ictal oscillations and inter-cortical coherence by thalamus.
    Article Snippet: Coherence analysis between pairs of signals was conducted using the mscohere function in MATLAB (Mathworks, USA).

    Article Title: Vibrotactile auricular vagus nerve stimulation alters limbic system connectivity in humans: A pilot study.
    Article Snippet: Coherence was computed using the magnitude-squared coherence function in MATLAB (mscohere) with a window size of 2.5 seconds and 70% overlap.

    Article Title: Auditory regulation of hippocampal locomotion circuits by a non-canonical reticular-limbic pathway
    Article Snippet: In the experiments recording from both the mPFC and dorsal hippocampus the coherence between these areas was calculated using the Matlab command Mscohere.

    Article Title: Interictal EEG features as computational biomarkers of West syndrome
    Article Snippet: Estimation of bi-channel coherence ( ) was performed using the magnitude-squared coherence method in Matlab (mscohere) on delta/theta, alpha, and beta bands.

    Article Title: Data analysis protocol for early autonomic dysfunction characterization after severe traumatic brain injury
    Article Snippet: Coherence will be calculated using mscohere function in MATLAB ( ).

    Article Title: Myorhythmia: A Quantitative Study of Synchrony and Rhythmicity Between the Head and Upper Limbs
    Article Snippet: The coherence spectrum was computed with MATLAB mscohere(), which provided the frequency distribution of what is effectively the average coherence at each frequency.

    Article Title: Imaging high-frequency voltage dynamics in multiple neuron classes of behaving mammals
    Article Snippet: To assess the coherence between the optical and electrical traces ( – , – , ), we applied a Fourier-based approach and used the MATLAB function mscohere() to compute the coherence magnitude between the two time series, and we used the MATLAB function cpsd() to compute the coherence phase between the two time series.



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    a (left) Topographic representation of the 60 Hz <t>RIFT</t> signal (uncombined planar gradiometers), averaged over participants in the 0.1–0.5 s interval ( t = 0 s is the onset of the search display). The RIFT response is confined to the occipital sensors. (right) Source modelling demonstrates that the RIFT response was primarily generated in the early visual cortex. The source grid has been masked to show the 1% most strongly activated grid points (MNI coordinates [0 −92 −4]). b Grand average spectrum, obtained by averaging over the participant-specific sensors of interest, indicating peaks at the 60 and 67 Hz stimulation frequency. c Grand average of the time-frequency representation of coherence between <t>the</t> <t>MEG</t> sensors and the RIFT signal, demonstrating an early, unspecific response in the gamma-band, followed by narrow-band responses at the stimulation frequency. d Set size 16. The responses to the distractor colour are significantly reduced for guided compared to unguided search ( p < 0.05; multiple comparison controlled using a cluster-based permutation test in the 0.1–0.5 s interval). There is no evidence for target boosting for this set size. e Set size 32. The RIFT responses to the guided target colour are significantly enhanced and the responses to the guided distractor colour are significantly reduced compared to the unguided search condition ( p < 0.05; cluster-based permutation test).
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    a (left) Topographic representation of the 60 Hz <t>RIFT</t> signal (uncombined planar gradiometers), averaged over participants in the 0.1–0.5 s interval ( t = 0 s is the onset of the search display). The RIFT response is confined to the occipital sensors. (right) Source modelling demonstrates that the RIFT response was primarily generated in the early visual cortex. The source grid has been masked to show the 1% most strongly activated grid points (MNI coordinates [0 −92 −4]). b Grand average spectrum, obtained by averaging over the participant-specific sensors of interest, indicating peaks at the 60 and 67 Hz stimulation frequency. c Grand average of the time-frequency representation of coherence between <t>the</t> <t>MEG</t> sensors and the RIFT signal, demonstrating an early, unspecific response in the gamma-band, followed by narrow-band responses at the stimulation frequency. d Set size 16. The responses to the distractor colour are significantly reduced for guided compared to unguided search ( p < 0.05; multiple comparison controlled using a cluster-based permutation test in the 0.1–0.5 s interval). There is no evidence for target boosting for this set size. e Set size 32. The RIFT responses to the guided target colour are significantly enhanced and the responses to the guided distractor colour are significantly reduced compared to the unguided search condition ( p < 0.05; cluster-based permutation test).
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    Image Search Results


    a (left) Topographic representation of the 60 Hz RIFT signal (uncombined planar gradiometers), averaged over participants in the 0.1–0.5 s interval ( t = 0 s is the onset of the search display). The RIFT response is confined to the occipital sensors. (right) Source modelling demonstrates that the RIFT response was primarily generated in the early visual cortex. The source grid has been masked to show the 1% most strongly activated grid points (MNI coordinates [0 −92 −4]). b Grand average spectrum, obtained by averaging over the participant-specific sensors of interest, indicating peaks at the 60 and 67 Hz stimulation frequency. c Grand average of the time-frequency representation of coherence between the MEG sensors and the RIFT signal, demonstrating an early, unspecific response in the gamma-band, followed by narrow-band responses at the stimulation frequency. d Set size 16. The responses to the distractor colour are significantly reduced for guided compared to unguided search ( p < 0.05; multiple comparison controlled using a cluster-based permutation test in the 0.1–0.5 s interval). There is no evidence for target boosting for this set size. e Set size 32. The RIFT responses to the guided target colour are significantly enhanced and the responses to the guided distractor colour are significantly reduced compared to the unguided search condition ( p < 0.05; cluster-based permutation test).

    Journal: Communications Biology

    Article Title: Guided visual search is associated with target boosting and distractor suppression in early visual cortex

    doi: 10.1038/s42003-025-08321-3

    Figure Lengend Snippet: a (left) Topographic representation of the 60 Hz RIFT signal (uncombined planar gradiometers), averaged over participants in the 0.1–0.5 s interval ( t = 0 s is the onset of the search display). The RIFT response is confined to the occipital sensors. (right) Source modelling demonstrates that the RIFT response was primarily generated in the early visual cortex. The source grid has been masked to show the 1% most strongly activated grid points (MNI coordinates [0 −92 −4]). b Grand average spectrum, obtained by averaging over the participant-specific sensors of interest, indicating peaks at the 60 and 67 Hz stimulation frequency. c Grand average of the time-frequency representation of coherence between the MEG sensors and the RIFT signal, demonstrating an early, unspecific response in the gamma-band, followed by narrow-band responses at the stimulation frequency. d Set size 16. The responses to the distractor colour are significantly reduced for guided compared to unguided search ( p < 0.05; multiple comparison controlled using a cluster-based permutation test in the 0.1–0.5 s interval). There is no evidence for target boosting for this set size. e Set size 32. The RIFT responses to the guided target colour are significantly enhanced and the responses to the guided distractor colour are significantly reduced compared to the unguided search condition ( p < 0.05; cluster-based permutation test).

    Article Snippet: This interval was chosen to avoid confounds with the broadband gamma response to the onset of the display Fig. . For each window, coherence between the MEG and RIFT signal was estimated based on the Fast Fourier Transform (FFT; zero-padded to 512 samples), and averaged over all windows to obtain one coherence value per trial (as implemented by the mscohere function in MATLAB).

    Techniques: Generated, Comparison

    a (left, top) The coherence between the signal-trial MEG data and RIFT signal was quantified using a sliding-window FFT approach, whereby the coherence was estimated by averaging over the 0.1 s in the 0.2–0.5 s interval (moved in steps of 0.025 s). (left, bottom) The topography of the coherence (combined planar gradiometers) suggests a response in the occipital sensors. (right) The RIFT response to the target and distractor was then concatenated into one vector, and submitted to a GLM with the factors target colour (T), unguided (U), distractor colour (D), and time-on-task (tot). b The contrast between the regressors associated with the target colour and unguided, and between distractor colour and unguided, was compared to 0 using a cluster-based permutation test (5000 permutations). The model fitted to the set size 16 conditions yielded no significant results but suggested reduced responses for distractors compared to unguided stimuli ( p = 0.08). c The model fitted to the set size 32 conditions replicated the magnitude-squared coherence results reported above, with a significantly stronger response to the target colour compared to unguided and a significantly reduced response to the distractor colour.

    Journal: Communications Biology

    Article Title: Guided visual search is associated with target boosting and distractor suppression in early visual cortex

    doi: 10.1038/s42003-025-08321-3

    Figure Lengend Snippet: a (left, top) The coherence between the signal-trial MEG data and RIFT signal was quantified using a sliding-window FFT approach, whereby the coherence was estimated by averaging over the 0.1 s in the 0.2–0.5 s interval (moved in steps of 0.025 s). (left, bottom) The topography of the coherence (combined planar gradiometers) suggests a response in the occipital sensors. (right) The RIFT response to the target and distractor was then concatenated into one vector, and submitted to a GLM with the factors target colour (T), unguided (U), distractor colour (D), and time-on-task (tot). b The contrast between the regressors associated with the target colour and unguided, and between distractor colour and unguided, was compared to 0 using a cluster-based permutation test (5000 permutations). The model fitted to the set size 16 conditions yielded no significant results but suggested reduced responses for distractors compared to unguided stimuli ( p = 0.08). c The model fitted to the set size 32 conditions replicated the magnitude-squared coherence results reported above, with a significantly stronger response to the target colour compared to unguided and a significantly reduced response to the distractor colour.

    Article Snippet: This interval was chosen to avoid confounds with the broadband gamma response to the onset of the display Fig. . For each window, coherence between the MEG and RIFT signal was estimated based on the Fast Fourier Transform (FFT; zero-padded to 512 samples), and averaged over all windows to obtain one coherence value per trial (as implemented by the mscohere function in MATLAB).

    Techniques: Plasmid Preparation