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1.
J Ophthalmol ; 2014: 850606, 2014.
Article in English | MEDLINE | ID: mdl-24719754

ABSTRACT

Saccadic latency is reduced by a temporal gap between fixation point and target, by identification of a target feature, and by movement in a new direction (inhibition of saccadic return, ISR). A simple additive model was compared with a shared resources model that predicts a three-way interaction. Twenty naïve participants made horizontal saccades to targets left and right of fixation in a randomised block design. There was a significant three-way interaction among the factors on saccade latency. This was revealed in a two-way interaction between feature identification and the gap versus no gap factor which was only apparent when the saccade was in the same direction as the previous saccade. No interaction was apparent when the saccade was in the opposite direction. This result supports an attentional inhibitory effect that is present during ISR to a previous location which is only partly released by the facilitative effect of feature identification and gap. Together, anticipatory error data and saccade latency interactions suggest a source of ISR at a higher level of attention, possibly localised in the dorsolateral prefrontal cortex and involving tonic activation.

2.
IEEE Trans Biomed Eng ; 55(7): 1809-21, 2008 Jul.
Article in English | MEDLINE | ID: mdl-18595799

ABSTRACT

A new noise reduction algorithm is presented for signals displaying repeated patterns or multiple trials. Each pattern is stored in a matrix, forming a set of events, which is termed multievent signal. Each event is considered as an affine transform of a basic template signal that allows for time scaling and shifting. Wavelet transforms, decimated and undecimated, are applied to each event. Noise reduction on the set of coefficients of the transformed events is applied using either wavelet denoising or principal component analysis (PCA) noise reduction methodologies. The method does not require any manual selection of coefficients. Nonstationary multievent synthetic signals are employed to demonstrate the performance of the method using normalized mean square error against classical wavelet and PCA based algorithms. The new method shows a significant improvement in low SNRs (typically 0 dB). On the experimental side, evoked potentials in a visual oddball paradigm are used. The reduced-noise visual oddball event-related potentials reveal gradual changes in morphology from trial to trial (especially for N1-P2 and N2-P3 waves at Fz), which can be hypothetically linked to attention or decision processes. The new noise reduction method is, thus, shown to be particularly suited for recovering single-event features in nonstationary low SNR multievent contexts.


Subject(s)
Algorithms , Artifacts , Brain/physiology , Electroencephalography/methods , Evoked Potentials/physiology , Humans , Sensitivity and Specificity
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