Measuring visual electrophysiological responses in individuals with low-functioning autism: a feasibility and pilot study

Background Although visual abnormalities are considered common in individuals with autism spectrum disorders, the associated electrophysiological markers have remained elusive. One impediment has been that methodological challenges often preclude testing individuals with low-functioning autism (LFA). Methods In this feasibility and pilot study, we tested a hybrid visual evoked potential paradigm tailored to individuals with LFA that combines passively presented visual stimuli to elicit scalp-recorded evoked responses with a behavioral paradigm to maintain visual attention. We conducted a pilot study to explore differences in visual evoked response patterns across three groups: individuals with LFA, with high-functioning autism (HFA), and with typical development. Results All participants with LFA met criteria for study feasibility by completing the recordings and producing measurable cortical evoked waveform responses. The LFA group had longer (delayed) cortical response latencies on average as compared with the HFA and typical development groups. We also observed group differences in visually induced alpha spectral power: the LFA group showed little to no prestimulus alpha activity in contrast to the HFA and typical development groups that showed increased prestimulus alpha activity. This observation was confirmed by the bootstrapped confidence intervals, suggesting that the absence of prestimulus alpha power may be a potential electrophysiological marker of LFA. Conclusion Our results confirm the utility of tailoring visual electrophysiology paradigms to individuals with LFA in order to facilitate inclusion of individuals across the autism spectrum in studies of visual processing.

Decoding Human Visual Colour EEG Information Using Machine Learning and Visual Evoked Potentials

With the rapid development of brain-computer interfaces (BCIs), human visual decoding, one of the important research directions of BCIs, has attracted a substantial amount of attention. However, most visual decoding studies have focused on graphic and image decoding. In this paper, we first demonstrate the possibility of building a new kind of task-irrelevant, simple and fast-stimulus BCI-based experimental paradigm that relies on visual evoked potentials (VEPs) during colour observation. Additionally, the features of visual colour information were found through reliable real-time decoding. We selected 9 subjects who did not have colour blindness to participate in our tests. These subjects were asked to observe red, green, and blue screens in turn with an interstimulus interval of 1 second. The machine learning results showed that the visual colour classification accuracy had a maximum of 93.73%. The latency evoked by visual colour stimuli was within the P300 range, i.e., 176.8 milliseconds for the red screen, 206.5 milliseconds for the green screen, and 225.3 milliseconds for the blue screen. The experimental results hereby show that the VEPs can be used for reliable colour real-time decoding.

A high-performance brain switch based on code-modulated visual evoked potentials

Objective. Asynchronous brain-computer interfaces (BCIs) are more practical and natural compared to synchronous BCIs. A brain switch is a standard asynchronous BCI, which can automatically detect the specified change of the brain and discriminate between the control state and the idle state. The current brain switches still face challenges on relatively long reaction time (RT) and high false positive rate (FPR). Approach. In this paper, an online electroencephalography-based brain switch is designed to realize a fast reaction and keep long idle time (IDLE) without false positives (FPs) using code-modulated visual evoked potentials (c-VEPs). Two stimulation paradigms were designed and compared in the experiments: multi-code concatenate modulation (concatenation mode) and single-code periodic modulation (periodic mode). Using a task-related component analysis-based detection algorithm, EEG data can be decoded into a series of code indices. Brain states can be detected by a template matching approach with a sliding window on the output series. Main results. The online experiments achieved an average RT of 1.49 seconds when the average IDLE for each FP was 68.57 minutes (1.46e-2 FP/min) or an average RT of 1.67 seconds without FPs. Significance. This study provides a practical c-VEP based brain switch system with both fast reaction and low FPR during idle state, which can be used in various BCI applications.

Assessing the Effect of the Refresh Rate of a Device on Various Motion Stimulation Frequencies Based on Steady-State Motion Visual Evoked Potentials

The refresh rate is one of the important parameters of visual presentation devices, and assessing the effect of the refresh rate of a device on motion perception has always been an important direction in the field of visual research. This study examined the effect of the refresh rate of a device on the motion perception response at different stimulation frequencies and provided an objective visual electrophysiological assessment method for the correct selection of display parameters in a visual perception experiment. In this study, a flicker-free steady-state motion visual stimulation with continuous scanning frequency and different forms (sinusoidal or triangular) was presented on a low-latency LCD monitor at different refresh rates. Seventeen participants were asked to observe the visual stimulation without head movement or eye movement, and the effect of the refresh rate was assessed by analyzing the changes in the intensity of their visual evoked potentials. The results demonstrated that an increased refresh rate significantly improved the intensity of motion visual evoked potentials at stimulation frequency ranges of 7–28 Hz, and there was a significant interaction between the refresh rate and motion frequency. Furthermore, the increased refresh rate also had the potential to enhance the ability to perceive similar motion. Therefore, we recommended using a refresh rate of at least 120 Hz in motion visual perception experiments to ensure a better stimulation effect. If the motion frequency or velocity is high, a refresh rate of≥240 Hz is also recommended.

Standardization and Validation of the Flash Visual Evoked Potential-P2 Conversion Scores in the Diagnosis of Amnestic Mild Cognitive Impairment and Alzheimer's Dementia

Amnestic mild cognitive impairment (aMCI), which is characterized by normal daily activity, but a significant decline in episodic memory, is now widely accepted as a risk factor for the development of Alzheimer's dementia (AD). Research suggests that many of the same neuropathological changes associated with AD also occur in patients diagnosed with aMCI. A recent review of the literature revealed that the latency of the flash visual-evoked potential-P2 (FVEP-P2) may possess pathognomonic information that may assist in the early detection of aMCI. While standards exist for the recording of FVEP-P2, individual clinics often use recording parameters that may differ, resulting in latencies that may not generalize beyond the clinic that produced them. The present article illustrates the process by which the FVEP-P2 latency can be standardized across clinics using FVEP-P2 Conversion Scores. We then demonstrate the diagnostic accuracy of the newly developed scores. Method: In the present investigation, we used the previously unpublished data containing the FVEP-P2 latencies of 45 AD and 60 controls. Result: We were able to demonstrate the process by which individual clinics may first standardize FVEP-P2 latencies and then examine patient performance using FVEP-P2 Conversion Scores, providing clinicians with a richer context from which to examine the patient performance. Conclusion: Consistent with the findings of previous research, the findings of the present investigation support the use of the FVEP-P2 Conversion Scores in the diagnosis of AD. Future directions, including the modification of recording parameters associated with the FVEP-P2, are also discussed.