A Combination of Pre- and Postprocessing Techniques to Enhance Self-Paced BCIs

Mental task onset detection from the continuous electroencephalogram (EEG) in real time is a critical issue in self-paced brain computer interface (BCI) design. The paper shows that self-paced BCI performance can be significantly improved by combining a range of simple techniques including (1) constant-Q filters with varying bandwidth size depending on the center frequency, instead of constant bandwidth filters for frequency decomposition of the EEG signal in the 6 to 36 Hz band; (2) subject-specific postprocessing parameter optimization consisting of dwell time and threshold, and (3) debiasing before postprocessing by readjusting the classification output based on the current and previous brain states, to reduce the number of false detections. This debiasing block is shown to be optimal when activated only in special cases which are predetermined during the training phase. Analysis of the data recorded from seven subjects executing foot movement shows a statistically significant 10% () average improvement in true positive rate (TPR) and a 1% reduction in false positive rate (FPR) detections compared with previous work on the same data

Assessing retino-geniculo-cortical connectivities in Alzheimer's Disease with a neural mass model

Longitudinal studies have shown that increase ofmean frequency within the theta band may be considered as an early symptom of progression into Alzheimer’s Disease (AD). Also, slowing of mean frequency within the alpha band has long since been known to be a defi nitive marker in AD. This work is aimed at developing a better understanding of alterations in neuronal connectivity underlying Electroencephalogram (EEG) changes in AD. Specif cally, connectivity changes in the dorsolateral geniculo-cortical pathway are studied using a neural mass computational model. Connectivity parameters in the model are informed by the most recent experimental data on mammalian Lateral Geniculate Nucleus (dorsal). A slowing of the mean power spectra of the model output is observed with increase in both excitatory and inhibitory parameters in the intra-thalamic and thalamocortical pathways and a decrease of sensory pathway synaptic connectivity. The biological plausibility of the results suggest potential of further model extension in AD research

Recent Advances in Prediction-based EEG Preprocessing for Improved Brain-Computer Interface Performance

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The effects of a supermarket-based intervention on the nutritional quality of private-label foods: a prospective study

Private-label products, products owned by supermarkets, are a growing area of the food supply. The aim of this study was to assess the effect of an intervention that provided an Australian supermarket ('intervention supermarket') with comparative nutrition data to improve the healthiness of their private-label range. Between 2015 and 2016, the intervention supermarket received reports that ranked the nutritional quality of their products against competitors. Changes in the nutrient content (sodium, sugar, saturated fat, energy and Health Star Rating) of products from the intervention supermarket between 2015 and 2018 were compared against changes achieved for three comparators (private-label products from two other supermarkets and branded products). The intervention supermarket achieved a significantly greater reduction in the sodium content of their products relative to all three comparators, which ranged between -104 and -52 mg/100 g (all p 0.05). Providing comparative nutrition information to a supermarket may be ineffective in improving the healthiness of their private-label products, likely due to competing factors that play a role in the decision-making process behind product reformulation and product discontinuation/innovation