Journal: Frontiers in Systems Neuroscience

Article Title: Altered Pallidocortical Low-Beta Oscillations During Self-Initiated Movements in Parkinson Disease

doi: 10.3389/fnsys.2020.00054

Figure Lengend Snippet: (A) Time-resolved pallidocortical coherence map aligned to the movement onset, which was obtained by averaging over all PD patients for each movement (frequency range: 8–60 Hz). (B) Boxplots showing the median values over PD patients of pallidocortical coherence averaged within each temporal period in low- and high-beta bands [*: p (corrected) < 0.05 by Wilcoxon’s signed rank test, where FDR < 0.05]. (C) Correlation analyses between clinical data (lateralized bradykinesia score) and low-beta pallidocortical coherence for SI movements in PD [*: p (corrected) < 0.05 by Spearman correlation, where FDR < 0.05].

Article Snippet: Within the PD cohort, the correlation between neural activities and clinical characteristics was evaluated by Spearman rank correlation method (MATLAB function corr.m ).

Techniques:

Journal: Frontiers in Human Neuroscience

Article Title: A Study of Word Complexity Under Conditions of Non-experimental, Natural Overt Speech Production Using ECoG

doi: 10.3389/fnhum.2021.711886

Figure Lengend Snippet: Correlation of the neural activity with the acquired linguistic parameters. (A) The logarithmic relative spectral magnitude (RSM) values at an individual electrode are depicted schematically in every time-frequency bin of the spectrum (the squares of the table) for a frequency range of 70–90 Hz (y axis) and −60 to 80 ms relative to word start (x axis). A Pearson’s correlation of the RSM values with a linguistic parameter of interest was calculated across all words of the given subject (B) . The correlation coefficients were projected on the time-frequency structure of the original spectrum (C) . This procedure allowed us to identify the time periods and frequencies in which the linguistic parameters showed correlations with the neural activity. The r values were color-coded and tested for significance. frq., frequency; log., natural logarithm; RSM, relative spectral magnitude; val., values; ling. param., linguistic parameters.

Article Snippet: We used Pearson’s correlation implemented in the built-in MATLAB function corr.m and tested the r values obtained for significance at p < 0.05.

Techniques: Activity Assay

Journal: Frontiers in Human Neuroscience

Article Title: A Study of Word Complexity Under Conditions of Non-experimental, Natural Overt Speech Production Using ECoG

doi: 10.3389/fnhum.2021.711886

Figure Lengend Snippet: Correlations between parameters accompanying the production of content words. For each subject (S1–S5), Pearson’s r correlation values between pairs of parameters are color-coded (see legend). Correlation values without statistical testing for significance are shown below the diagonal of red squares (a perfect positive correlation of each parameter with itself); above the diagonal: significant (<0.05) correlations. ss_ws, the duration from speech start to word start in ms; ws_we, the duration from word start to word end in ms; we_se, the duration from word end to speech end in ms; FRQ, lemma frequency extracted from the linguistic corpus ; EoA, ease-of-articulation index ; NoS, number of syllables in a spoken word; CVR, consonant-to-vowel-ratio (the number of consonants in a spoken word divided by the number of vowels); intensity, average intensity of the acoustic signal during word production in Db; EMG, average relative spectral magnitude values for electromyographic activity during word production recorded at the respective body part; L, left; R, right; QUADR/QUADL, EMG from the right/left quadriceps; DELR/DELL, EMG from the right/left deltoid muscles. The squares with black and gray outlines highlight the correlations that were reproducible across subjects.

Article Snippet: We used Pearson’s correlation implemented in the built-in MATLAB function corr.m and tested the r values obtained for significance at p < 0.05.

Techniques: Activity Assay, Muscles