title: Comparison of Matching Pursuit Algorithm with Other Signal Processing Techniques for Computation of the Time-Frequency Power Spectrum of Brain Signals.
abstract: Signals recorded from the brain often show rhythmic patterns at different frequencies, which are tightly coupled to the external stimuli as well as the internal state of the subject. In addition, these signals have very transient structures related to spiking or sudden onset of a stimulus, which have durations not exceeding tens of milliseconds. Further, brain signals are highly nonstationary because both behavioral state and external stimuli can change on a short time scale. It is therefore essential to study brain signals using techniques that can represent both rhythmic and transient components of the signal, something not always possible using standard signal processing techniques such as short time fourier transform, multitaper method, wavelet transform, or Hilbert transform. In this review, we describe a multiscale decomposition technique based on an over-complete dictionary called matching pursuit (MP), and show that it is able to capture both a sharp stimulus-onset transient and a sustained gamma rhythm in local field potential recorded from the primary visual cortex. We compare the performance of MP with other techniques and discuss its advantages and limitations. Data and codes for generating all time-frequency power spectra are provided.
authors.affiliation: Department of Electrical Engineering.
authors.forename: Subhash
authors.initials: S
authors.lastname: Chandran K S
authors.affiliation: Indian Institute of Science Education and Research (IISER), Kolkata, India, 741246.
authors.forename: Ashutosh
authors.initials: A
authors.lastname: Mishra
authors.affiliation: Indian Institute of Science (IISc) Mathematics Initiative, Department of Mathematics, and.
authors.forename: Vinay
authors.initials: V
authors.lastname: Shirhatti
authors.affiliation: Department of Electrical Engineering, Centre for Neuroscience, Indian Institute of Science, Bangalore, India, 560012, and sray@cns.iisc.ernet.in.
authors.forename: Supratim
authors.identifier: http://orcid.org/0000-0002-1968-1382
authors.initials: S
authors.lastname: Ray
mesh_terms: D000465:Algorithms; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005583:Fourier Analysis; D006801:Humans; D000069550:Machine Learning; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D014793:Visual Cortex / Q000502:physiology*; D058067:Wavelet Analysis