Visual and electrical evoked response recorded from subdural electrodes implanted above the visual cortex in normal dogs under two methods of anesthesia

Margalit, Eyal; Weiland, James D.; Clatterbuck, Richard E.; Fujii, Gildo Y.; Maia, Maurício; Tameesh, M.; Torres, G.; D’Anna, Salvatore A.; Desai, Sanjay V.; Piyathaisere, Duke V.; Olivi, Alessandro; Juan, Eugene de; Humayun, Mark S.

doi:10.1016/s0165-0270(02)00345-x

Cited by 84 publications

(49 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…It has dramatically higher spatial resolution than EEG [i.e., tenths of millimeters vs centimeters (Freeman et al, 2003)], broader bandwidth (Staba et al, 2002), higher characteristic amplitude, and far less vulnerability to artifacts such as EMG (Freeman et al, 2003). At the same time, because ECoG does not require penetration of the cortex, it may have greater long-term stability than intracortical recordings (Loeb et al, 1977;Bullara et al, 1979;Yuen et al, 1987;Margalit et al, 2003).…”

Section: Ecog Signalsmentioning

confidence: 99%

Advanced Neurotechnologies for Chronic Neural Interfaces: New Horizons and Clinical Opportunities

Kipke¹,

Shain²,

Buzsáki³

et al. 2008

J. Neurosci.

258

176

View full text Add to dashboard Cite

IntroductionTechnological advances in neural interfaces are providing increasingly more powerful "toolkits" of designs, materials, components, and integrated devices for establishing high-fidelity chronic neural interfaces. For a broad class of neuroscience studies, the primary requirements of these interfaces include recording and/or stimulating from a number of discretely sampled volumes at requisite spatial resolutions for specific periods of time. Translational and clinical applications present additional requirements for safety, usability, reliability, patient acceptance, and cost effectiveness. Innovative solutions result from the constructive tension between ever-increasing application requirements and incorporation of technological advances into usable devices. The purpose of this minireview is to present snapshots of the current state-of-the-art in chronic, microscale neural interfaces by highlighting several leading neuroscience applications and discussing their implications for next-generation interface devices.

show abstract

Section: Ecog Signalsmentioning

confidence: 99%

Advanced Neurotechnologies for Chronic Neural Interfaces: New Horizons and Clinical Opportunities

Kipke¹,

Shain²,

Buzsáki³

et al. 2008

J. Neurosci.

258

176

View full text Add to dashboard Cite

show abstract

“…ECoG has higher spatial resolution than EEG (i.e., tenths of millimeters versus centimeters [8]), broader bandwidth (i.e., 0-200 Hz versus 0-40 Hz), higher amplitude (i.e., 50-100 µV maximum versus 10-20 µV), and far less vulnerability to artifacts such as EMG [8,9,15]. At the same time, because ECoG is recorded by subdural electrode arrays and thus does not require electrodes that penetrate into cortex, it is likely to have greater long-term stability and might also be safer than single-neuron recording [16,17].…”

Section: Introductionmentioning

confidence: 99%

A brain–computer interface using electrocorticographic signals in humans

et al. 2004

View full text Add to dashboard Cite

Brain-computer interfaces (BCIs) enable users to control devices with electroencephalographic (EEG) activity from the scalp or with single-neuron activity from within the brain. Both methods have disadvantages: EEG has limited resolution and requires extensive training, while single-neuron recording entails significant clinical risks and has limited stability. We demonstrate here for the first time that electrocorticographic (ECoG) activity recorded from the surface of the brain can enable users to control a one-dimensional computer cursor rapidly and accurately. We first identified ECoG signals that were associated with different types of motor and speech imagery. Over brief training periods of 3-24 min, four patients then used these signals to master closed-loop control and to achieve success rates of 74-100% in a one-dimensional binary task. In additional open-loop experiments, we found that ECoG signals at frequencies up to 180 Hz encoded substantial information about the direction of two-dimensional joystick movements. Our results suggest that an ECoG-based BCI could provide for people with severe motor disabilities a non-muscular communication and control option that is more powerful than EEG-based BCIs and is potentially more stable and less traumatic than BCIs that use electrodes penetrating the brain. M This article features online multimedia enhancements

show abstract

“…ECoG has higher spatial resolution than EEG (i.e., tenths of millimeters vs. centimeters [12]), broader bandwidth (i.e., 0-500 Hz [13] vs. 0-50 Hz), higher characteristic amplitude (i.e., 50-100 μV vs. 10-20 μV), and far less vulnerability to artifacts such as EMG [12] or ambient noise. At the same time, because ECoG does not require penetration of the cortex, it is likely to have greater long-term stability [14,15,16,17] and to produce less tissue damage and reaction than intracortical recordings.…”

Section: Introductionmentioning

confidence: 99%

Two-dimensional movement control using electrocorticographic signals in humans

et al. 2008

View full text Add to dashboard Cite

We show here that a brain-computer interface (BCI) using electrocorticographic activity (ECoG) and imagined or overt motor tasks enable humans to control a computer cursor in two dimensions. Over a brief training period of 12-36 min, each of five human subjects acquired substantial control of particular ECoG features recorded from several locations over the same hemisphere, and achieved average success rates of 53-73% in a two-dimensional four-target center-out task in which chance accuracy was 25%. Our results support the expectation that ECoG-based BCIs can combine high performance with technical and clinical practicality, and also indicate promising directions for further research.

show abstract

Visual and electrical evoked response recorded from subdural electrodes implanted above the visual cortex in normal dogs under two methods of anesthesia

Cited by 84 publications

References 20 publications

Advanced Neurotechnologies for Chronic Neural Interfaces: New Horizons and Clinical Opportunities

Advanced Neurotechnologies for Chronic Neural Interfaces: New Horizons and Clinical Opportunities

A brain–computer interface using electrocorticographic signals in humans

Two-dimensional movement control using electrocorticographic signals in humans

Contact Info

Product

Resources

About