Estimation of the Timing of Human Visual Perception from Magnetoencephalography

Abstract

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.

Object Detection and Recognition for Assistive Robots: Experimentation and Implementation

“…As it can be observed, our results highlight the efficiency when parallel computing is used; computation times remain almost unchanged between Keeping in mind our final goal, an autonomous assistive robot, the system should provide a similar response time regardless of the task at hand, as it is the case, and, ideally, this response time should be the same as that of human beings. As our results show, the obtained response time is similar in all the studied cases (up to 50 target objects) and below 0.5 seconds, approximately twice the average human reaction time (between 200-250 milliseconds [88] [89] [90]). In the context of human-computer interaction [91] [92] [93], a response time below 0.1 second is regarded as an instantaneous reaction, whereas a response delay between 0.1 and 1.0 second is considered as fast enough for a fluent interaction, even though the user would notice the delay.…”

Medial Prefrontal Theta Bursts Precede Rapid Motor Responses during Visual Selective Attention

“…3B) is reminiscent of the demonstration by Hanes et al (1995) of monotonic ramping up of firing rates of neurons in the frontal eye fields of monkeys up to the release of cued saccades. Amano et al (2006) also showed correlations of reaction time with average and single-trial magnetoencephalographic signal above occipital cortex and to a lesser extend over frontal cortex. This indicates our RT correlation results in the frontal cortex may be related to a general mechanism for releasing speeded button presses that is not particular to the task we used.…”

Sequential Sampling Models Without Random Between-Trial Variability: The Racing Diffusion Model of Speeded Decision

“…More recently, researchers have related measurements of electrophysiology in monkeys (Cook & Maunsell, 2002), and MEG and EEG in humans (Amano et al, 2006;Tandonnet, Burle, Hasbroucq, & Vidal, 2005;Vidal, Burle, Grapperon, & Hasbroucq, 2011) to the RTs to detect simple visual stimuli. By doing so, researchers could partition out the time needed for visual perception, which is approximately 150-200 ms.…”