A Novel Stimulation Paradigm For a Brain-computer Interface Based On Ssvep

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A brain-machine interface for assistive robotic control

Brain-machine interfaces (BMIs) are the only currently viable means of communication for many individuals suffering from locked-in syndrome (LIS) – profound paralysis that results in severely limited or total loss of voluntary motor control. By inferring user intent from task-modulated neurological signals and then translating those intentions into actions, BMIs can enable LIS patients increased autonomy. Significant effort has been devoted to developing BMIs over the last three decades, but only recently have the combined advances in hardware, software, and methodology provided a setting to realize the translation of this research from the lab into practical, real-world applications. Non-invasive methods, such as those based on the electroencephalogram (EEG), offer the only feasible solution for practical use at the moment, but suffer from limited communication rates and susceptibility to environmental noise. Maximization of the efficacy of each decoded intention, therefore, is critical. This thesis addresses the challenge of implementing a BMI intended for practical use with a focus on an autonomous assistive robot application. First an adaptive EEG- based BMI strategy is developed that relies upon code-modulated visual evoked potentials (c-VEPs) to infer user intent. As voluntary gaze control is typically not available to LIS patients, c-VEP decoding methods under both gaze-dependent and gaze- independent scenarios are explored. Adaptive decoding strategies in both offline and online task conditions are evaluated, and a novel approach to assess ongoing online BMI performance is introduced. Next, an adaptive neural network-based system for assistive robot control is presented that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. Exploratory learning, or “learning by doing,” is an unsupervised method in which the robot is able to build an internal model for motor planning and coordination based on real-time sensory inputs received during exploration. Finally, a software platform intended for practical BMI application use is developed and evaluated. Using online c-VEP methods, users control a simple 2D cursor control game, a basic augmentative and alternative communication tool, and an assistive robot, both manually and via high-level goal-oriented commands

Attentional Enhancement of Tracked Stimuli in Early Visual Cortex Has Limited Capacity

Funding Information: Received Mar. 28, 2022; revised Sep. 22, 2022; accepted Sep. 26, 2022. Author contributions: N.A. and S.K.A. designed research; N.A. and S.K.A. performed research; S.K.A. contributed unpublished reagents/analytic tools; N.A. analyzed data; N.A. wrote the first draft of the paper; N.A. and S.K.A. edited the paper; N.A. and S.K.A. wrote the paper. This work was supported by the Biotechnology and Biological Sciences Research Council Grant BB/ P002404/1 (to S.K.A.) and the Leverhulme Early Career Fellowship ECF-2020-488 (to N.A.). We thank Alex O. Holcombe and Christian Merkel for their many insightful comments and suggestions. We also thank Rafael Lemarchand for his help in data collection. The authors declare no competing financial interests. Correspondence should be addressed to Nika Adamian at [email protected] reviewe

Brain computer interfaces: an engineering view. Design, implementation and test of a SSVEP-based BCI.

This thesis presents the realization of a compact, yet flexible BCI platform, which, when compared to most commercially-available solution, can offer an optimal trade-off between the following requirements: (i) minimal, easy experimental setup; (ii) flexibility, allowing simultaneous studies on other bio-potentials; (iii) cost effectiveness (e.g. < 1000 €); (iv) robust design, suitable for operation outside lab environments. The thesis encompasses all the project phases, from hardware design and realization, up to software and signal processing. The work started from the development of the hardware acquisition unit. It resulted in a compact, battery-operated module, whose medium-to-large scale production costs are in the range of 300 €. The module features 16 input channels and can be used to acquire different bio-potentials, including EEG, EMG, ECG. Module performance is very good (RTI noise < 1.3 uVpp), and was favourably compared against a commercial device (g.tec USBamp). The device was integrated into an ad-hoc developed Matlab-based platform, which handles the hardware control, as well as the data streaming, logging and processing. Via a specifically developed plug-in, incoming data can also be streamed to a TOBI-interface compatible system. As a demonstrator, the BCI was developed for AAL (Ambient Assisted Living) system-control purposes, having in mind the following requirements: (i) online, self-paced BCI operation (i.e., the BCI monitors the EEG in real-time and must discern between intentional control periods, and non-intentional, rest ones, interpreting the user’s intent only in the first case); (ii) calibration-free approach (“ready-to-use”, “Plug&Play”); (iii) subject-independence (general approach). The choice of the BCI operating paradigm fell on Steady State visual Evoked Potential (SSVEP). Two offline SSVEP classification algorithms were proposed and compared against reference literature, highlighting good performance, especially in terms of lower computational complexity. A method for improving classification accuracy was presented, suitable for use in online, self-paced scenarios (since it can be used to discriminate between intentional control periods and non-intentional ones). Results show a very good performance, in particular in terms of false positives immunity (0.26 min^-1), significantly improving over the state of the art. The whole BCI setup was tested both in lab condition, as well as in relatively harsher ones (in terms of environmental noise and non-idealities), such as in the context of the Handimatica 2014 exhibition. In both cases, a demonstrator allowing control of home appliances through BCI was developed

Visual attention in naturalistic scenes across the lifespan.

Visual attentional skills continue to develop through childhood and do not reach maturity until adolescence. On the other end of the spectrum, older adults’ visual attentional skills are declining with age. The development and decline of these skills can lead to difficulties in day to day activities such as throwing or catching a ball, cycling, crossing a road, or even maintaining stability when walking. Alongside this, children and older adults are among the most vulnerable groups in road crossing situations, with older adults accounting for almost 50% of road crossing fatalities in the EU. A link has been suggested between visual attentional control skills and the vulnerability of older adults and children to pedestrian accidents but little has been done to investigate this link. In this PhD, I set out to investigate in fine- grained detail the involvement of attentional control skills in road crossing decisions in children, younger, and older adults. To this aim four experiments were run. The first experiment tested younger adults and children from five to 15 years old in a road crossing situation where participants had to watch videos of road traffic and decide when they could safely cross the road. The participants’ eye movements were recorded. I found that younger children made riskier crossing decisions compared to older children and young adults. Younger children were also less able to inhibit attentional capture by distractors and were less able to disengage overt attention from moving targets when the visual load was high. In the second experiment, I used a similar paradigm with young and older adults. My findings revealed that older adults were less able to inhibit attentional capture by distractors compared to younger adults. Despite this attentional bias, older adults made safe crossing decisions. This experiment involved only one direction of traffic and more complex situations (several traffic directions, different speeds, large field of view) might be more taxing for older people and impact their abilities to make safe crossing decisions. As such, in the third experiment I used a virtual reality set-up in order to test scenarios of varying complexity. I also tracked the participants’ eye movements across a wide field of view (180°). My results showed that older adults were able in simple situations to make safe crossing decisions and they chose larger gaps between vehicles than younger adults. In more complex situations such as when cars travel faster, older adults made more risky crossing decisions. In experiments one and two, participants looked predominantly at the point where cars appeared on the road and did not overtly follow the cars down the road. This finding suggested a dissociation between overt and covert attention in the context of road-crossing. In order to explore this dissociation and its potential deficit in children and older people, I developed a technique using in conjunction eye-tracking and steady state visually evoked potential (SSVEP). In this paradigm, participants overtly tracked a moving object and covertly monitored the appearance of a new object at the appearance point. I found a drop in the SSVEP power signal prior to the appearance of the second moving object while the participants’ eyes were still overtly tracking the first object. This result suggests during smooth pursuit a decrease in attentional resources allocated to the foveated object when there is a shift of covert attention towards a second object. In future studies, I aim to use this paradigm to explore more precisely the dynamic of overt and covert attention in more realistic scenario and with children and older participants. This research used novel approaches to address the socially relevant and timely question of pedestrian safety. To this aim, I used a variety of methods ranging from eye-tracking to image processing, EEG and VR, and I developed new techniques tailored to the questions at hand. For the first time, I directly investigated the relationships between visual exploration, road crossing decisions and changes in attentional control through the lifespan. My findings show that children below the age of 10 are less able to inhibit attentional capture by distractors, which increased the risk of unsafe crossing decisions. In similar, simple situations, older adults also show an attentional bias towards distractors, but they maintain the ability to make safe crossing decisions. VR experiments with systematic manipulations of the complexity of the road crossing scene revealed that older adults make riskier crossing decisions in specific situations such as when cars travel quickly, or from different directions. This research furthers our understanding of attentional control through the lifespan as well as providing insights for pedestrian safety. As such, it provides avenues for the development of training and safety guidelines for pedestrians

A novel visual stimulation paradigm: exploiting individual primary visual cortex geometry to boost steady state visual evoked potentials (SSVEP)

The steady-state visual evoked potential (SSVEP) is an electroencephalographic response to flickering stimuli generated in significant part by activity in primary visual cortex (V1). SSVEP signal-to-noise ratio is generally low for stimuli that are located in the visual periphery, at frequencies higher than 20 Hz, or at low contrast. Because of the typical cruciform geometry of V1, large stimuli tend to excite neighboring cortical regions of opposite orientation, likely resulting in electric field cancellation. In Study 1, we explored ways to exploit V1 geometry in order to boost scalp SSVEP amplitude via oscillatory summation, by manipulating flicker-phase offsets among angular segments of a large annular stimulus. We found that by dividing the annulus into standard octants, flickering upper horizontal octants with opposite temporal phase to the lower horizontal ones, and left vertical octants opposite to the right vertical ones, the normalized SSVEP power was enhanced by 202% relative to the conventional condition with no temporal phase offsets. In two further conditions we individually customized the phase-segment boundaries based on early-latency topographical shifts in pattern-pulse multifocal visual-evoked potentials (PPMVEP) derived for each of 32 equal-sized segments. Adjusting the boundaries between 8 phase-segments by visual inspection resulted in significant enhancement of normalized SSVEP power of 383%, a further significant improvement over the standard octants condition. An automatic segment-phase assignment algorithm based on the relative strength of vertically- and horizontally-oriented multifocal VEP scalp potential amplitudes produced an enhancement of 300%. In Study 2, we applied the same principle to obtain more reliable measures of visual evoked activity to obtain surround suppression measures. Here we report for the first time, a novel vii paradigm that exploits simple signal processing, sensory physiology and psychophysical evidences in order to extract a direct index of surround suppression using EEG. Surround suppression effects were tested for low and high flickering frequencies in two different configurations of a flickering stimulus (foreground, FG) on a static surrounding pattern (background, BG): foveal, where the stimulus was a unique central disc, and peripheral, where four discs were presented at symmetrical locations around the horizontal meridian. We varied FG and BG contrast combinations and also evaluated the influence of differences in spatial phase and orientation between the surrounding pattern and the foreground. Across a population of sixteen healthy subjects, we found that the foreground contrast response function was significantly suppressed in proportion with the contrast of the background, and that, like psychophysical measures, this suppression effect was greater when the background was oriented in parallel with the foreground than when it was orthogonal. Suppression effects were also greater for the peripheral stimulus condition. This is the first demonstration of a clear surround suppression effect in the visual evoked potentials of humans, and paves the way for the first definitive measurement of the relative contributions of under-inhibition and over-excitation to hyperexcitability in epilepsy

Development of a Practical Visual-Evoked Potential-Based Brain-Computer Interface

There are many different neuromuscular disorders that disrupt the normal communication pathways between the brain and the rest of the body. These diseases often leave patients in a `locked-in state, rendering them unable to communicate with their environment despite having cognitively normal brain function. Brain-computer interfaces (BCIs) are augmentative communication devices that establish a direct link between the brain and a computer. Visual evoked potential (VEP)- based BCIs, which are dependent upon the use of salient visual stimuli, are amongst the fastest BCIs available and provide the highest communication rates compared to other BCI modalities. However. the majority of research focuses solely on improving the raw BCI performance; thus, most visual BCIs still suffer from a myriad of practical issues that make them impractical for everyday use. The focus of this dissertation is on the development of novel advancements and solutions that increase the practicality of VEP-based BCIs. The presented work shows the results of several studies that relate to characterizing and optimizing visual stimuli. improving ergonomic design. reducing visual irritation, and implementing a practical VEP-based BCI using an extensible software framework and mobile devices platforms

Attentional modulation in early visual cortex : a focused reanalysis of steady-state visual evoked potential studies

Funding information This work was supported by a grant from the Biotechnology and Biological Sciences Research Council (BB/P002404/1) awarded to S. K. A. and Leverhulme Early Career Fellowship ECF-2020-488 awarded to N.A.Peer reviewedPostprin