EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks.

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a "reach/saccade to spatial target" cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI

Blobs versus bars:psychophysical evidence supports two types of orientation response in human color vision

The classic hypothesis of Livingstone and Hubel (1984, 1987) proposed two types of color pathways in primate visual cortex based on recordings from single cells: a segregated, modularpathway that signals color but provides little information about shape or form and a second pathway that signals color differences and so defines forms without the need to specify their colors. A major problem has been to reconcile this neurophysiological hypothesis with the behavioral data. A wealth of psychophysical studies has demonstrated that color vision has orientation-tuned responses and little impairment on form related tasks, but these have not revealed any direct evidence for nonoriented mechanisms. Here we use a psychophysical method of subthreshold summation across orthogonal orientations for isoluminant red-green gratings in monocular and dichoptic viewing conditions to differentiate between nonoriented and orientation-tuned responses to color contrast. We reveal nonoriented color responses at low spatial frequencies (0.25-0.375 c/deg) under monocular conditions changing to orientation-tuned responses at higher spatial frequencies (1.5 c/deg) and under binocular conditions. We suggest that two distinct pathways coexist in color vision at the behavioral level, revealed at different spatial scales: one is isotropic, monocular, and best equipped for the representation of surface color, and the other is orientation-tuned, binocular, and selective for shape and form. This advances our understanding of the organization of the neural pathways involved in human color vision and provides a strong link between neurophysiological and behavioral data

Effect of visual feedback on the occipital-parietal-motor network in Parkinson's disease with freezing of gait.

Freezing of gait (FOG) is an elusive phenomenon that debilitates a large number of Parkinson's disease (PD) patients regardless of stage of disease, medication status, or deep brain stimulation implantation. Sensory feedback cues, especially visual feedback cues, have been shown to alleviate FOG episodes or even prevent episodes from occurring. Here, we examine cortical information flow between occipital, parietal, and motor areas during the pre-movement stage of gait in a PD-with-FOG patient that had a strong positive behavioral response to visual cues, one PD-with-FOG patient without any behavioral response to visual cues, and age-matched healthy controls, before and after training with visual feedback. Results for this case study show differences in cortical information flow between the responding PD-with-FOG patient and the other two subject types, notably, an increased information flow in the beta range. Tentatively suggesting the formation of an alternative cortical sensory-motor pathway during training with visual feedback, these results are proposed as subject for further verification employing larger cohorts of patients

Understanding walking and cycling:summary of key findings and recommendations

It is widely recognized that there is a need to increase levels of active and sustainable travel in British urban areas. The Understanding Walking and Cycling (UWAC) project, funded by the EPSRC, has examined the factors influencing everyday travel decisions and proposes a series of policy measures to increase levels of walking and cycling for short trips in urban areas. A wide range of both quantitative and qualitative data were collected in four English towns (Lancaster, Leeds, Leicester and Worcester), including a questionnaire survey, spatial analysis of the built environment, interviews (static and whilst mobile) and detailed ethnographies. Key findings of the research are that whilst attitudes to walking and cycling are mostly positive or neutral, many people who would like to engage in more active travel fail to do so due to a combination of factors. These can be summarised as: Concerns about the physical environment, especially with regard to safety when walking or cycling; The difficulty of fitting walking and cycling into complex household routines (especially with young children); The perception that walking and cycling are in some ways abnormal things to do. It is suggested that policies to increase levels of walking and cycling should focus not only on improving infrastructure (for instance through fully segregated cycle routes along main roads and restriction on vehicle speeds), but also must tackle broader social, economic, cultural and legal factors that currently inhibit walking and cycling. Together, such changes can create an environment in which driving for short trips in urban areas is seen as abnormal and walking or cycling seem the obvious choices. A joint project by by Lancaster University, Oxford Brookes University and the University of Leeds

Economic Analysis of Improving Cold Tolerance in Rice in Australia

The occurrence of low night temperatures during reproductive development is one of the factors most limiting rice yields in southern Australia. Yield losses due to cold temperature are the result of incomplete pollen formation and subsequent floret sterility. Researchers have found that in 75% of years, rice farmers suffer losses between 0.5 and 2.5 t/ha. Research is being undertaken to identify overseas rice varieties, that are cold tolerant under the local weather conditions and by using those genotypes as parent material, develop cold tolerance varieties of rice. A yield simulation model was used to measure reduction in losses due to cold at different minimum threshold temperatures, while the SAMBOY Rice model was used to measure the costs and returns of a breeding program for cold tolerance. The results of the economic analysis reveal that new cold tolerant varieties would lead to significant increase in financial benefits through reduction in losses due to cold, and an increase in yield from the better use on nitrogen by the cold tolerant varieties. The returns to investment on the research project are estimated to be high

EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing

We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments

Expressions 2000

https://openspace.dmacc.edu/expressions/1019/thumbnail.jp