A rigorous leave-one-subject-out benchmark on public auditory EEG data shows five-vowel decoding accuracy of 25.5 percent (chance 20 percent) using differential entropy features and LightGBM, with vowel information present but weak and localized to early auditory transients.
Shift-invariant multilinear decomposition of neuroimag- ing data
5 Pith papers cite this work. Polarity classification is still indexing.
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A new NMF variant estimates integer and non-integer temporal shifts plus stretching in the frequency domain to improve brain tissue delineation in emission tomography data.
PCA-derived global factor from gray-matter isotropic volume fraction in NODDI data correlates with specific cognitive scores in HCP Young Adult cohort.
fNIRS data and participant-independent ML models were used to estimate cognitive effort via relative neural efficiency and involvement, showing segment differences and close match between predicted and actual performance-derived effort.
Bootstrapped multi-level analysis of functional connectivity data reveals reduced DMN connectivity, increased deactivation, and 13 significantly differing regions (mostly frontal) in schizophrenia versus controls.
citing papers explorer
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How Well Can We Decode Vowels from Auditory EEG -- A Rigorous Cross-Subject Benchmark with Honest Assessment
A rigorous leave-one-subject-out benchmark on public auditory EEG data shows five-vowel decoding accuracy of 25.5 percent (chance 20 percent) using differential entropy features and LightGBM, with vowel information present but weak and localized to early auditory transients.
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Shift- and stretch-invariant non-negative matrix factorization with an application to brain tissue delineation in emission tomography data
A new NMF variant estimates integer and non-integer temporal shifts plus stretching in the frequency domain to improve brain tissue delineation in emission tomography data.
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General Microstructure Factor Analysis of Diffusion MRI in Gray-Matter Predicts Cognitive Scores
PCA-derived global factor from gray-matter isotropic volume fraction in NODDI data correlates with specific cognitive scores in HCP Young Adult cohort.
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Beyond Cognitive Load: AI-Based Estimation of Cognitive Effort Using Brain Signals During Digital Tasks
fNIRS data and participant-independent ML models were used to estimate cognitive effort via relative neural efficiency and involvement, showing segment differences and close match between predicted and actual performance-derived effort.
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Diffuse and Localized Functional Dysconnectivity in Schizophrenia: a Bootstrapped Top-Down Approach
Bootstrapped multi-level analysis of functional connectivity data reveals reduced DMN connectivity, increased deactivation, and 13 significantly differing regions (mostly frontal) in schizophrenia versus controls.