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Results for “Evoked Potentials, Visual”

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Stimulus novelty, task relevance and the visual evoked potential in man

The visual evoked potential (VEP) to rare, task-relevant (counted) numerical stimuli was compared with VEPs to rare, task-irrelevant stimuli, both being randomly interspersed within a sequence of tachistoscopically-flashed background numbers. These task-irrelevant stimuli were of two classes: (1) easily recognizable (e.g., simple geometric shapes) and (2) completely novel (i.e., complex, colorful abstract-type drawings which were unrecognizable). It was found that such novel stimuli did, in fact, evoke large P3 waves, but they had different scalp distributions from those which followed the task-relevant stimuli. This indicates that at least two types of late positive P3 waves exist, differing both in brain source and psychological correlates.

Courchesne, E.↗
NASA NTRS1977

Visual evoked potentials and selective attention to points in space

Visual evoked potentials (VEPs) were recorded to sequences of flashes delivered to the right and left visual fields while subjects responded promptly to designated stimuli in one field at a time (focused attention), in both fields at once (divided attention), or to neither field (passive). Three stimulus schedules were used: the first was a replication of a previous study (Eason, Harter, and White, 1969) where left- and right-field flashes were delivered quasi-independently, while in the other two the flashes were delivered to the two fields in random order (Bernoulli sequence). VEPs to attended-field stimuli were enhanced at both occipital (O2) and central (Cz) recording sites under all stimulus sequences, but different components were affected at the two scalp sites. It was suggested that the VEP at O2 may reflect modality-specific processing events, while the response at Cz, like its auditory homologue, may index more general aspects of selective attention.

Van Voorhis, S.↗
NASA NTRS1974

Auditory and visual evoked potentials during hyperoxia

Experimental study of the auditory and visual averaged evoked potentials (AEPs) recorded during hyperoxia, and investigation of the effect of hyperoxia on the so-called contingent negative variation (CNV). No effect of hyperoxia was found on the auditory AEP, the visual AEP, or the CNV. Comparisons with previous studies are discussed.

Smith, D. B. D.↗
NASA NTRS1975

Stimulus novelty, task relevance and the visual evoked potential in man

The effect of task relevance on P3 (waveform of human evoked potential) waves and the methodologies used to deal with them are outlined. Visual evoked potentials (VEPs) were recorded from normal adult subjects performing in a visual discrimination task. Subjects counted the number of presentations of the numeral 4 which was interposed rarely and randomly within a sequence of tachistoscopically flashed background stimuli. Intrusive, task-irrelevant (not counted) stimuli were also interspersed rarely and randomly in the sequence of 2s; these stimuli were of two types: simples, which were easily recognizable, and novels, which were completely unrecognizable. It was found that the simples and the counted 4s evoked posteriorly distributed P3 waves while the irrelevant novels evoked large, frontally distributed P3 waves. These large, frontal P3 waves to novels were also found to be preceded by large N2 waves. These findings indicate that the P3 wave is not a unitary phenomenon but should be considered in terms of a family of waves, differing in their brain generators and in their psychological correlates.

Courchesne, E.↗
NASA NTRS2005

Brain-Computer Interfaces for 1-D and 2-D Cursor Control: Designs Using Volitional Control of the EEG Spectrum or Steady-State Visual Evoked Potentials

We have developed and tested two EEG-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KF LS classifier to map power spectra of 30-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject s average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: a) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal EOG signals, b) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from eight electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about three minutes. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 seconds for movement initiation and turning.

Trejo, Leonard J.↗
NASA NTRS1986

Analytical comparison of transient and steady state visual evoked cortical potentials

To better describe the linear-dynamic properties of the human visual-cortical response system, transient and steady state Visual Evoked Response Potentials (VERP) were observed. The stimulus presentation device provided both the evoking stimulus (flickering or pulsing lights) and a video task display. The steady state stimulus was modulated by a complex, ten frequency, sum-of-sines, wave. The transient VERP was the time-locked average of the EEG to a series of narrow light pulses (pulse width of 10 msec). The Fourier transform of the averaged pulses had properties that approximate band limited white noise, i.e., a flat spectrum over the frequency region spanned by the 10 summed sines. The Fourier transform of both the steady state and the transient evoked potentials resulted in transfer that are equivalent and therefore comparable. To investigate the effects of task loading on evoked potentials, a grammatical reasoning task was provided. Results support the relevancy of continued application of a systems engineering approach for describing neurosensory functioning.

Junker, A. M.↗
NASA NTRS1999

EEG Analysis of the Effects of Therapeutic Cooling on the Cognitive Performance of Multiple Sclerosis Patients

The objective of this project was to determine whether a controlled period of head and torso cooling would enhance the cognitive performance of multiple sclerosis patients. Nineteen MS patients (11 men and 8 women) participated in the study. Control data were taken from nineteen healthy volunteers (12 men and 7 women). All but six of nineteen MS patients tested improved their cognitive performance, as measured by their scores on the Rao test battery. A second objective was to gain insight into the neurological effects of cooling. Visual evoked potentials (VEPs) stimulated by a reversing checkerboard pattern were recorded before and after cooling. We found that cooling selectively benefited the cognitive performance of those MS patients whose pre-cooling VEPs were abnormally shaped (which is an indication of visual pathway impairment due to demyelinization). Moreover, for female MS patients, the degree of cognitive performance improvement following cooling was correlated with a change in the shape of their VEPs toward a more normal shape following cooling.

Montgomery, Leslie D.↗
NASA NTRS2002

Estimating Single-Trial Responses in EEG

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Shah, A. S.↗
NASA NTRS2003

Differentially Variable Component Analysis (dVCA): Identifying Multiple Evoked Components using Trial-to-Trial Variability

Electric potentials and magnetic fields generated by ensembles of synchronously active neurons in response to external stimuli provide information essential to understanding the processes underlying cognitive and sensorimotor activity. Interpreting recordings of these potentials and fields is difficult as each detector records signals simultaneously generated by various regions throughout the brain. We introduce the differentially Variable Component Analysis (dVCA) algorithm, which relies on trial-to-trial variability in response amplitude and latency to identify multiple components. Using simulations we evaluate the importance of response variability to component identification, the robustness of dVCA to noise, and its ability to characterize single-trial data. Finally, we evaluate the technique using visually evoked field potentials recorded at incremental depths across the layers of cortical area VI, in an awake, behaving macaque monkey.

Knuth, Kevin H.↗
NASA NTRS1998

Neural learning rules for the vestibulo-ocular reflex

Mechanisms for the induction of motor learning in the vestibulo-ocular reflex (VOR) were evaluated by recording the patterns of neural activity elicited in the cerebellum by a range of stimuli that induce learning. Patterns of climbing-fiber, vestibular, and Purkinje cell simple-spike signals were examined during sinusoidal head movement paired with visual image movement at stimulus frequencies from 0.5 to 10 Hz. A comparison of simple-spike and vestibular signals contained the information required to guide learning only at low stimulus frequencies, and a comparison of climbing-fiber and simple-spike signals contained the information required to guide learning only at high stimulus frequencies. Learning could be guided by comparison of climbing-fiber and vestibular signals at all stimulus frequencies tested, but only if climbing fiber responses were compared with the vestibular signals present 100 msec earlier. Computational analysis demonstrated that this conclusion is valid even if there is a broad range of vestibular signals at the site of plasticity. Simulations also indicated that the comparison of vestibular and climbing-fiber signals across the 100 msec delay must be implemented by a subcellular "eligibility" trace rather than by neural circuits that delay the vestibular inputs to the site of plasticity. The results suggest two alternative accounts of learning in the VOR. Either there are multiple mechanisms of learning that use different combinations of neural signals to drive plasticity, or there is a single mechanism tuned to climbing-fiber activity that follows activity in vestibular pathways by approximately 100 msec.

NASA Discipline Neuroscience↗