• Neuroinformatics
• Journal of Vision close

Relatively little is known about the processes, both linear and nonlinear, by which signals are combined beyond V1. By presenting two stimulus components simultaneously, flickering at different temporal frequencies (frequency tagging) while measuring steady-state visual evoked potentials, we can assess responses to the individual components, including direct measurements of suppression on each other, and various nonlinear responses to their combination found at intermodulation frequencies. The result is a rather rich dataset of frequencies at which responses can be found. We presented pairs of sinusoidal gratings at different temporal frequencies, forming plaid patterns that were "coherent" (looking like a checkerboard) and "noncoherent" (looking like a pair of transparently overlaid gratings), and found clear intermodulation responses to compound stimuli, indicating nonlinear summation. This might have been attributed to cross-orientation suppression except that the pattern of intermodulation responses differed for coherent and noncoherent patterns, whereas the effects of suppression (measured at the component frequencies) did not. A two-stage model of nonlinear summation involving conjunction detection with a logical AND gate described the data well, capturing the difference between coherent and noncoherent plaids over a wide array of possible response frequencies. Multistimulus frequency-tagged EEG in combination with computational modeling may be a very valuable tool in studying the conjunction of these signals. In the current study the results suggest a second-order mechanism responding selectively to coherent plaid patterns.

The sense of touch is frequently paired with a visual stimulus that provides information on how the sensation will be experienced. This is true for both active touch-when a person moves to touch an object-and passive touch-when an object moves to touch a person. However, limited research has been conducted on how active and passive touch are processed by the cortex, as well as how prediction of the sensory experience influences that processing. Here, we use electroencephalography (EEG) to measure cortical activity while virtual reality creates the visual expectation of touching an object that is paired with vibrotactile feedback. In the active condition, the participant will reach toward and receive tactile input from the virtual object. In the passive condition, the virtual object will move toward and provide tactile input to the participant. This experiment will measure an electrophysiological phenomenon called the mismatch negativity (MMN), a distinct deflection in the EEG waveform shown to index a deviation from an established pattern in sensory stimuli. To elicit an MMN, we will manipulate the duration of the vibrotactile stimuli, with 80% being 100 ms long and 20% being 160 ms long. Our experiment is the first to assess the MMN in an active tactile context. Preliminary data (n=4) show a robust N1 component and MMN in response to active and passive touch. Further data collection is ongoing.