Independent Components Analysis “Artifact Correction” Distorts EEG Phase in Artifact Free Segments

EEG artifact is defined as any electrical potential that is not produced by the brain, e.g., eye movement or head movement or muscle, 50 Hz-60 Hz line noise, etc. The most commonly used method of artifact elimination from an EEG recording is to delete the parts of the EEG recording that contain artifact and thereby leave the artifact free parts of the recording unchanged. Recently, Independent Components Analysis (ICA) has been used to decompose the original EEG into a set of components and then subjectively identify components that statistically load on one or more Independent Components (ICs) and using a smaller set of ICs then replace the original EEG recording with a different time series referred to as the ICA replacement or ICA-R. The purpose of this study is to mathematically and empirically test the distortion of the artifact free parts of the EEG when using ICA-R to replace the entire EEG digital record. The results of Joint-Time-Frequency-Analysis (JTFA) and the FFT spectral analyses demonstrated that ICA-Replacement of the original EEG produced phase distortions at each and every time point of the recording between all channel pairs. In contrast, the standard method of deleting the segments of an EEG recording that contain artifact did not distort the artifact free segments of the EEG recording. Conclusions are that ICA Replacement (ICA-R) is a severe distortion of the phase differences and time differences of the electrophysiology of the human scalp recorded Electroencephalogram (EEG) and invalidates all subsequent analyses that rely upon the imaginary part of the crossspectrum including scalp coherence, phase and network analyses that are dependent on the physics of electrical and magnetic fields.

Investigation of Origanum libanoticum Essential Oils Chemical Polymorphism by Independent Components Analysis (ICA)

The essential oils obtained from Origanum libanoticum Boiss., a plant endemic to Lebanon, were analyzed by GC/MS. Seventy compounds were identified, covering till 99.8% of the total oil composition. All samples were p-cymene and/or β-caryophyllene chemotype, with variable percentage of other compounds such as α-pinene, myrcene, α-phellandrene, limonene, etc. Compared to traditional drying method, lyophilized samples provided the highest essential oil (EO) yields and yields were higher at flowering stage (Chouwen: 0.33% in 2013 and 0.32% in 2014; Qartaba: 0.27% in 2013 and 0.37% in 2014). According to independent components analysis (ICA), date and site of harvest, altitude and drying technique had no effect on the variation of O. libanoticum EO chemical composition. An annual variation of EOs composition was observed since a particular variation in some major components concentration was revealed monthly and annually between 2013 and 2014.

Modulation of Resting Connectivity Between the Mesial Frontal Cortex and Basal Ganglia

The mesial prefrontal cortex, cingulate cortex and the ventral striatum are key nodes of the human mesial fronto-striatal circuit involved in decision-making and executive function and pathological disorders. Here we ask whether deep wide-field repetitive transcranial magnetic stimulation (rTMS) targeting the mesial prefrontal cortex (MPFC) influences resting state functional connectivity. In Study 1, we examined functional connectivity using resting state multi-echo and independent components analysis in 154 healthy subjects to characterize default connectivity in the MPFC and mid-cingulate cortex (MCC). In Study 2, we used inhibitory, 1 Hz deep rTMS with the H7-coil targeting MPFC and dorsal anterior cingulate (dACC) in a separate group of 20 healthy volunteers and examined pre-and post-TMS functional connectivity using seed-based and independent components analysis. In Study 1, we show that MPFC and MCC have distinct patterns of functional connectivity with MPFC–ventral striatum showing negative, whereas MCC–ventral striatum showing positive functional connectivity. Low-frequency rTMS decreased functional connectivity of MPFC and dACC with the ventral striatum. We further showed enhanced connectivity between MCC and ventral striatum. These findings emphasize how deep inhibitory rTMS using the H7-coil can influence underlying network functional connectivity by decreasing connectivity of the targeted MPFC regions, thus potentially enhancing response inhibition and decreasing drug cue reactivity processes relevant to addictions. The unexpected finding of enhanced default connectivity between MCC and ventral striatum may be related to the decreased influence and connectivity between the MPFC and MCC. These findings are highly relevant to the treatment of disorders relying on the mesioprefrontal–cingulo–striatal circuit.