Peripheral and central delay in processing high spatial frequencies: reaction time and VEP latency studies

Mihaylova, Milena; Stomonyakov, V.; Vassilev, A.

doi:10.1016/s0042-6989(98)00165-5

Cited by 56 publications

(40 citation statements)

References 28 publications

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“…The delay value was estimated as the difference between the actual RT and the detection latency estimated by each model, averaged over all thee coherence levels. For the peak detector model, the slopes were much smaller than 1 (0.190 Ϯ 0.092), which is in agreement with previous reports (Osaka and Yamamoto, 1978;Musselwhite and Jeffreys, 1985;Mihaylova et al, 1999;Patzwahl and Zanker, 2000;Kawakami et al, 2002;Vassilev et al, 2002). For the level detector model, the slopes were increased but were not sufficiently close to 1 (0.810 Ϯ 0.122).…”

Section: Resultssupporting

confidence: 90%

“…Although some EEG studies have suggested that the latency of the peak response changes in parallel with the manual RT (Vaughan et al, 1966;Jaskowski et al, 1990), most EEG/MEG studies (Osaka and Yamamoto, 1978;Musselwhite and Jeffreys, 1985;Mihaylova et al, 1999;Patzwahl and Zanker, 2000;Kawakami et al, 2002;Vassilev et al, 2002), including the present one (Figs. 2 and 6), indicate that the change in the peak latency is too small to account for the change in RT (peak detector model).…”

Section: Model Comparisonmentioning

confidence: 67%

“…Previous attempts to relate RT with EEG or MEG responses generally failed in quantitatively predicting RT from the peak latency of the evoked response (Osaka and Yamamoto, 1978;Musselwhite and Jeffreys, 1985;Mihaylova et al, 1999;Patzwahl and Zanker, 2000;Kawakami et al, 2002;Vassilev et al, 2002). These results are not disappointing, however, given that there is no theoretical reason to expect the peak latency to correspond to the completion of a perceptual process.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of the Timing of Human Visual Perception from Magnetoencephalography

Amano¹,

Goda²,

Nishida³

et al. 2006

J. Neurosci.

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To explore the timing and the underlying neural dynamics of visual perception, we analyzed the relationship between the manual reaction time (RT) to the onset of a visual stimulus and the time course of the evoked neural response simultaneously measured by magnetoencephalography (MEG). The visual stimuli were a transition from incoherent to coherent motion of random dots and an onset of a chromatic grating from a uniform field, which evoke neural responses in different cortical sites. For both stimuli, changes in median RT with changing stimulus strength (motion coherence or chromatic contrast) were accurately predicted, with a stimulus-independent postdetection delay, from the time that the temporally integrated MEG response crossed a threshold (integrator model). In comparison, the prediction of RT was less accurate from the peak MEG latency, or from the time that the nonintegrated MEG response crossed a threshold (level detector model). The integrator model could also account for, at least partially, intertrial changes in RT or in perception (hit/miss) to identical stimuli. Although we examined MEG-RT relationships mainly for data averaged over trials, the integrator model could show some correlations even for single-trial data. The model predictions deteriorated when only early visual responses presumably originating from the striate cortex were used as the input to the integrator model. Our results suggest that the perceptions for visual stimulus appearances are established in extrastriate areas [around MT (middle temporal visual area) for motion and around V4 (fourth visual area) for color] ϳ150 -200 ms before subjects manually react to the stimulus.

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Section: Resultssupporting

confidence: 90%

Section: Model Comparisonmentioning

confidence: 67%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Estimation of the Timing of Human Visual Perception from Magnetoencephalography

Amano¹,

Goda²,

Nishida³

et al. 2006

J. Neurosci.

View full text Add to dashboard Cite

show abstract

“…The observation of typical VEP latencies for pattern reversal at high and low luminance contrast documents consistency of the visual presentation via LCD goggles during simultaneous BOLD MRI and efficacy of the postprocessing software for gradient and cardioballistic artifact reduction (33,34). Additionally, visual stimulation by motion onset led to a prominent N2 component over left temporal derivations at a latency of 180 ms. Again, this finding is in line with previous observations of N2 as a highly sensitive correlate to contrast and motion (16,18,35).…”

Section: Discussionsupporting

confidence: 54%

Simultaneous recordings of visual evoked potentials and BOLD MRI activations in response to visual motion processing

2005

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Visual motion processing in humans was studied by simultaneous 32-channel electroencephalography (EEG) recordings of visual evoked potentials and BOLD MRI activations at 2.9 T. The paradigms compared three different random dot patterns (12 s duration) with stationary random dots (18 s) or with each other. The stimuli represented pattern reversal (500 ms switches between two stationary patterns), motion onset (200 ms of starfield motion followed by 1000 ms of stationary dots) and motion reversal (reversal of moving starfield directions every 1000 ms). Whereas motion-evoked visual potentials, and in particular the N2 component in occipito-temporal channels, were most prominent for motion onset, the most extended BOLD MRI activations and strongest signal changes in V5/MTþ were obtained in response to motion reversal. These apparently contradictory findings most likely reflect different physiological aspects of the neural activity associated with visual motion processing. For example, desynchronized activity of subpopulations of cortical neurons inside V5/MTþ is expected to attenuate visual evoked potentials in scalp recordings while continuously driving metabolic demands that lead to sustained BOLD MRI responses. The understanding of the physiological correlates and neural processes underlying either technique is fundamental to exploring fully the potential of combined EEG-MRI for studying human brain function at both high temporal and spatial resolution.

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“…Similarly, previous studies have reported that contrast affects reaction times for detecting both stimulus and motion onset for sinusoidal gratings (Burr et al 1998;Harwerth and Levi 1978;Lupp et al 1976;Mihaylova et al 1999;Tartaglione et al 1975). The contrast effect on simple reaction times for detecting stationary sinusoidal gratings has a mean slope increase of about 8 ms per log 2 contrast decrease at 0.5 cpd (Fig.…”

Section: Time Delaysupporting

confidence: 53%

Effect of Contrast on the Active Control of a Moving Line

Li¹,

Sweet²,

Stone³

2005

Journal of Neurophysiology

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Li, Li, Barbara T. Sweet, and Leland S. Stone. Effect of contrast on the active control of a moving line. J Neurophysiol 93: 2873-2886, 2005. First published December 22, 2004 doi:10.1152/jn.00200.2004. In many passive visual tasks, human perceptual judgments are contrast dependent. To explore whether these contrast dependencies of visual perception also affect closed-loop manual control tasks, we examined visuomotor performance as humans actively controlled a moving luminance-defined line over a range of contrasts. Four subjects were asked to use a joystick to keep a horizontal line centered on a display as its vertical position was perturbed by a sum of sinusoids under two control regimes. The total root mean square (RMS) position error decreased quasi-linearly with increasing log contrast across the tested range (mean slope across subjects: Ϫ8.0 and Ϫ7.7% per log 2 contrast, for the two control regimes, respectively). Frequency-response (Bode) plots showed a systematic increase in openloop gain (mean slope: 1.44 and 1.30 dB per log 2 contrast, respectively), and decrease in phase lag with increasing contrast, which can be accounted for by a decrease in response time delay (mean slope: 32 and 40 ms per log 2 contrast, respectively). The performance data are well fit by a Crossover Model proposed by McRuer and Krendel, which allowed us to identify both visual position and motion cues driving performance. This analysis revealed that the position and motion cues used to support manual control under both control regimes appear equally sensitive to changes in stimulus contrast. In conclusion, our data show that active control of a moving visual stimulus is as dependent on contrast as passive perception and suggest that this effect is attributed to a shared contrast sensitivity early in the visual pathway, before any specialization for motion processing.

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Peripheral and central delay in processing high spatial frequencies: reaction time and VEP latency studies

Cited by 56 publications

References 28 publications

Estimation of the Timing of Human Visual Perception from Magnetoencephalography

Estimation of the Timing of Human Visual Perception from Magnetoencephalography

Simultaneous recordings of visual evoked potentials and BOLD MRI activations in response to visual motion processing

Effect of Contrast on the Active Control of a Moving Line

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