Abstract
Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.
Highlights
Cerebral palsy (CP) is a heterogeneous group of disorders, the unifying feature of which is an impairment of fine and gross motor function due to dysgenesis or injury in early brain development.[1]
A new general linear model (GLM)/independent component analysis (ICA) method was proposed for the analysis of functional near-infrared spectroscopy (fNIRS) data acquired during a finger tapping task where unintentional mirror motions were present
Custom regressors were created from motion tracking or EMG data, and fNIRS signals were unmixed by applying ICA to the ΔHbO time-series data
Summary
Cerebral palsy (CP) is a heterogeneous group of disorders, the unifying feature of which is an impairment of fine and gross motor function due to dysgenesis or injury in early brain development.[1] In patients with CP, motor function does not necessarily predict or represent the underlying physiology. Observation of neurological activation patterns would help create a more coherent understanding of how brain function relates to motor control deficits.[2] Sensorimotor activation patterns of the brain in children with CP have been mapped by functional magnetic resonance imaging (fMRI) in several recent studies.[3,4,5,6] fMRI requires subjects to remain still for extended periods of time in a restricted space, which is difficult to do when working with children with CP. Functional near-infrared spectroscopy (fNIRS) has been demonstrated as a feasible alternate neuroimaging technique that enables brain activation measurements under relatively unrestricted conditions.[7] fNIRS detects the changes in light absorption
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