Attention modulations of posterior alpha as a control signal for two-dimensional brain–computer interfaces

Gerven, Marcel van; Jensen, Ole

doi:10.1016/j.jneumeth.2009.01.016

Cited by 137 publications

(138 citation statements)

References 24 publications

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“…This could be convincingly pointed out by its left-lateralized activity pattern irrespective of response-hand laterality ( Figure 7A), and by the non-motor region in which it was generated, namely, the LOT Noteworthy, a recently proposed framework postulates that alpha activity reflects functional inhibition (Jensen and Mazaheri, 2010). This interpretation was derived from reports of alpha power suppression in task-engaged brain areas (van Gerven and Jensen, 2009;Handel et al, 2010), and alternatively of alpha power enhancement in non-engaged areas (Haegens et al, 2010). Thus, alpha suppression as observed here could be indicative of the functional engagement of the LOT as a selective activation pattern gating fully conscious perception of words.…”

Section: Scalp Topographies and Brain Views (Sagittal And Axial Planementioning

confidence: 63%

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness

et al. 2013

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The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to fullblown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.

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Section: Scalp Topographies and Brain Views (Sagittal And Axial Planementioning

confidence: 63%

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness

et al. 2013

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“…A large number of EEG and MEG studies have shown that oscillations in different frequency bands are related to specific brain functions (Cornwell et al, 2008;Tesche and Karhu, 2000;Urakami, 2008;van Dijk et al, 2008;van Gerven and Jensen, 2009). Additionally, there is increasing evidence that functional interactions between different brain regions are mediated by the synchronization of their oscillations.…”

Section: Introductionmentioning

confidence: 99%

EEG Power Asymmetry and Functional Connectivity as a Marker of Treatment Effectiveness in DBS Surgery for Depression

Quraan

Protzner

Daskalakis

et al. 2013

Neuropsychopharmacol

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Recently, deep brain stimulation (DBS) has been evaluated as an experimental therapy for treatment-resistant depression. Although there have been encouraging results in open-label trials, about half of the patients fail to achieve meaningful benefit. Although progress has been made in understanding the neurobiology of MDD, the ability to characterize differences in brain dynamics between those who do and do not benefit from DBS is lacking. In this study, we investigated EEG resting-state data recorded from 12 patients that have undergone DBS surgery. Of those, six patients were classified as responders to DBS, defined as an improvement of 50% or more on the 17-item Hamilton Rating Scale for Depression (HAMD-17). We compared hemispheric frontal theta and parietal alpha power asymmetry and synchronization asymmetry between responders and non-responders. Hemispheric power asymmetry showed statistically significant differences between responders and non-responders with healthy controls showing an asymmetry similar to responders but opposite to non-responders. This asymmetry was characterized by an increase in frontal theta in the right hemisphere relative to the left combined with an increase in parietal alpha in the left hemisphere relative to the right in non-responders compared with responders. Hemispheric mean synchronization asymmetry showed a statistically significant difference between responders and non-responders in the theta band, with healthy controls showing an asymmetry similar to responders but opposite to non-responders. This asymmetry resulted from an increase in frontal synchronization in the right hemisphere relative to the left combined with an increase in parietal synchronization in the left hemisphere relative to the right in non-responders compared with responders. Connectivity diagrams revealed long-range differences in frontal/central-parietal connectivity between the two groups in the theta band. This pattern was observed irrespective of whether EEG data were collected with active DBS or with the DBS stimulation turned off, suggesting stable functional and possibly structural modifications that may be attributed to plasticity.

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“…18 Modulation of the posterior alpha rhythm as recorded by MEG was felt to produce satisfactory control of a 2-dimensional BCI task. 19 Functional magnetic resonance imaging (fMRI) and functional near-infrared imaging (fNIR) measure the blood oxygenation of a cerebral region and correlate with neural activity. 1 Lee et al 20 demonstrated that control of a robotic arm only through the person's thought processes was possible using a real-time fMRI-based BCI.…”

Section: Brain-computer Interfacesmentioning

confidence: 99%

“…The device operation provides feedback to the user, thus closing the control loop. 19 Because of its relative ease of implementation and performance, one of the most researched BCI paradigms is the visual P300 speller, 5 which has been demonstrated successfully in both healthy and disabled persons for typing, [35][36][37][38][39][40][41][42] Internet browsing, 43 guidance of a wheelchair along predetermined paths, [44][45][46][47] and other applications. Like the P300 evoked response, steady-state visual evoked potentials are innate and require no training, but they are capable of providing faster response times.…”

Section: Device Outputmentioning

confidence: 99%

Brain-Computer Interfaces in Medicine

Shih

Krusienski

Wolpaw

2012

Mayo Clinic Proceedings

564

279

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Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. U ntil recently, the dream of being able to control one's environment through thoughts had been in the realm of science fiction. However, the advance of technology has brought a new reality: Today, humans can use the electrical signals from brain activity to interact with, influence, or change their environments. The emerging field of brain-computer interface (BCI) technology may allow individuals unable to speak and/or use their limbs to once again communicate or operate assistive devices for walking and manipulating objects. Brain-computer interface research is an area of high public awareness. Videos on YouTube as well as news reports in the lay media indicate intense curiosity and interest in a field that hopefully one day soon will dramatically improve the lives of many disabled persons affected by a number of different disease processes.This review seeks to provide the general medical community with an introduction to BCIs. We define BCI and then review some of the seminal discoveries in this rapidly emerging field, the brain signals used by BCIs, the essential components of a BCI system, current BCI systems, and the key issues now engaging researchers. Challenges are inherent in translating any new technology to practical and useful clinical applications, and BCIs are no exception. We discuss the potent...

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Attention modulations of posterior alpha as a control signal for two-dimensional brain–computer interfaces

Cited by 137 publications

References 24 publications

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness

EEG Power Asymmetry and Functional Connectivity as a Marker of Treatment Effectiveness in DBS Surgery for Depression

Brain-Computer Interfaces in Medicine

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