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Computational neuroscience: analyzing human beta oscillations from ECoG data


Beta oscillations are neural rhythms in the range of 15-29 Hz that are powerful indicators of motor and sensory performance. Beta oscillations are thought to play an important role in the way the brain functions. They also have implications in neurological disorders, such as Parkinson's Disease. Essential to understanding the role of beta in healthy or abnormal sensorimotor processing is to understand its signature of activity and mechanisms of generation. Previous research indicates that spontaneous beta oscillations from the somatosensory cortex measured with Magnetoencephalography (MEG) and electroencephalography (EEG) in humans and with local field potential (LFP) in animals emerge as transient events lasting ~150ms, with a stereotypical waveform containing a sharp deflection lasting 50ms. Computational neural modeling showed these events could arise from a specific pattern of synaptic drive to the neocortex (Sherman et al. PNAS 2016). The question we address is if these beta features are generalizable to beta oscillations measured intracranially with electrocorticography (ECoG) in Essential Tremor patients. ECoG is a method very similar to EEG in the way it measures brain activity with electrodes, but it requires an invasive procedure because the electrodes are placed directly on the cortex. This decreases the likelihood of the signal being lost in background noise. In order to analyze our ECoG data I used the same spectrogram method used in Sherman et al. PNAS 2016 to identify beta oscillations. We found that some beta oscillations had similar characteristics to those found in MEG and LFP from Sherman et al. PNAS 2016. Further steps include quantifying the features of the ECoG beta events to determine if they have a characteristic waveform, applying our computational neural model to identify mechanisms of beta events in ECoG data, investigating median nerve evoked response, and comparing signals in healthy/diseased subjects.


Baya, Nikolas, "Computational neuroscience: analyzing human beta oscillations from ECoG data" (2016). Summer Research Symposium. Brown Digital Repository. Brown University Library.



  • Summer Research Symposium

    Each year, Brown University showcases the research of its undergraduates at the Summer Research Symposium. More than half of the student-researchers are UTRA recipients, while others receive funding from a variety of Brown-administered and national programs and fellowships and go …