Evelina Thunell

Different colors of light lead to different adaptation and activation as determined by high-density EEG

Light adaptation is crucial for coping with the varying levels of ambient light. Using high-density electroencephalography (EEG), we investigated how adaptation to light of different colors affects brain responsiveness. In a within-subject design, sixteen young participants were adapted first to dim white light and then to blue, green, red, or white bright light (one color per session in a randomized order). Immediately after both dim and bright light adaptation, we presented brief light pulses and recorded event-related potentials (ERPs). We analyzed ERP response strengths and brain topographies and determined the underlying sources using electrical source imaging. Between 150 and 261 ms after stimulus onset, the global field power (GFP) was higher after dim than bright light adaptation. This effect was most pronounced with red light and localized in the frontal lobe, the fusiform gyrus, the occipital lobe and the cerebellum. After bright light adaptation, within the first 100 ms after light onset, stronger responses were found than after dim light adaptation for all colors except for red light. Differences between conditions were localized in the frontal lobe, the cingulate gyrus, and the cerebellum. These results indicate that very short-term EEG brain responses are influenced by prior light adaptation and the spectral quality of the light stimulus. We show that the early EEG responses are differently affected by adaptation to different colors of light which may contribute to known differences in performance and reaction times in cognitive tests.

Retinotopic encoding of the Ternus-Pikler display reflected in the early visual areas

The visual representation of the world is often assumed to be retinotopic, and many visual brain areas are indeed organized retinotopically. Visual perception, however, is not based on a reference frame anchored in retinotopic coordinates. For example, when an object moves, motion of its constituent parts is perceived relative to the object rather than in retinotopic coordinates. The moving object thus serves as a nonretinotopic reference system for computing the properties of its parts. It is largely unknown how the brain accomplishes this feat. Here, we used the Ternus-Pikler display to pit retinotopic processing in a stationary reference system against nonretinotopic processing in a moving one. Using 7T fMRI, we found that the average blood-oxygen-level dependent activations in V1, V2, and V3 reflected the retinotopic properties, but not the nonretinotopic percepts, of the Ternus-Pikler display. In the human motion processing complex (hMT+), activations were compatible with both retinotopic and nonretinotopic encoding. Thus, hMT+ may be the first visual area encoding the nonretinotopic percepts of the Ternus-Pikler display.

Putting low-level vision into global context: Why vision cannot be reduced to basic circuits

To cope with the complexity of vision, most models in neuroscience and computer vision are of hierarchical and feedforward nature. Low-level vision, such as edge and motion detection, is explained by basic low-level neural circuits, whose outputs serve as building blocks for more complex circuits computing higher level features such as shape and entire objects. There is an isomorphism between states of the outer world, neural circuits, and perception, inspired by the positivistic philosophy of the mind. Here, we show that although such an approach is conceptually and mathematically appealing, it fails to explain many phenomena including crowding, visual masking, and non-retinotopic processing.

EEG and fMRI correlates of non-retinotopic motion processing in the human visual system

While most of the visual brain areas are organized retinotopically, perception is typically non-retinotopic. For example, as a bicycle passes by, we perceive a reflector on its wheel to move in a circular or prolate cycloidal orbit. By contrast, the true retinotopic trajectory traced out by the reflector is a curtate cycloid. We cannot see the retinotopic motion because the horizontal motion of the bicycle is discounted from the motion of the reflector. The bicycle thus serves as a moving, non-retinotopic reference system, within which the motion of the reflector is computed. Despite the important role of non-retinotopic processing in visual perception, almost nothing is known about its neural correlates. Here, we used the Ternus-Pikler display to contrast retinotopic processing in a stationary reference system against non-retinotopic processing in a moving one. In a 7T fMRI experiment, we found hMT+ to be the first area in the visual processing stream where non-retinotopic percepts were reflected in the BOLD signals. The signals in the early visual areas (V1-V3) instead reflected the retinotopic stimulation. We propose that hMT+ computes the motion of the reference system and immediately discounts this motion in order to compute relative motions. This is in line with our EEG study, where we found neural correlates of non-retinotopic perception already from the earliest evoked peak around 120 ms after stimulus onset and throughout the rest of the visual processing. Meeting abstract presented at VSS 2015.

The neural correlates of non-retinotopic processing in human visual cortex: a 7T fMRI study

Under normal viewing conditions, due to e.g. the motion of objects, the retinotopic representation of the environment constantly changes. Yet we perceive the world as stable and we easily keep track of moving objects, indicating the presence of non-retinotopic representations in the brain. We investigated the neural correlates of such non-retinotopic processing in the human visual cortex by means of high-resolution fMRI. To this end, we used a Ternus-Pikler display: Three horizontally aligned dark/light gray checker-boards moved back and fourth in a left-right apparent motion while participants kept their gaze fixated above the stimulus, resulting in a non-retinotopic integration of the elements across frames. In a second condition, only two checker-boards were presented at the same location in each frame, thus causing the elements to be integrated retinotopically. Crucially, the checker-boards could be either flickering, i.e. inverting polarity with each frame, or non-flickering. This retinotopic flickering or non-flickering is perceived in the 2-element conditions. In the 3-element conditions, however, because of the non-retinotopic correspondence, the percept is inverted such that the non-flickering checker-boards are perceived to flicker and vice versa. In V1, we found a higher BOLD response for retinotopically flickering stimuli, as expected, but the activity did not depend on the percept of flickering vs. non-flickering. In hMT+ we found a stronger response for the 3-element conditions, which could be due to the apparent motion as well as the larger size of the stimuli. More interestingly, there was also an interaction effect, namely higher activity for perceived flickering than perceived non-flickering. Thus, apart from the retinotopic properties of the stimuli, also the endogenous percept of non-retinotopic origin is reflected in the hMT+ activity.

Neural correlates of non-retinotopic motion integration

Under normal viewing conditions, due to the motion of objects and to eye movements, the retinotopic representation of the environment constantly changes. Yet we perceive the world as stable, and we easily keep track of moving objects. Here, we investigated the neural correlates of non-retinotopic motion integration using high-density EEG. We used a Ternus-Pikler display to establish either a retinotopic or non-retinotopic frame of reference. Three disks were presented for 250 ms followed by an ISI of 150 ms. The disks then reappeared either at the same location (retinotopic reference frame), or shifted sideways (non-retinotopic reference frame). After another ISI, the sequence started over again. In the middle disk, a dot was either changing positions across frames in a rotating fashion, or stayed in the same position. Every 5th to 9th frame, the dot started or stopped rotating, and observers reported this with a button-press. We found higher EEG responses for rotating than static dots. This effect occurred rather late (>200 ms), i.e. after basic stimulus encoding (P1 component). Importantly, these results hold for both the retinotopic and the non-retinotopic conditions, indicating that the encoding of rotation does not depend on reference frame. In line with this, reference frame effects were observed at earlier latencies and did not interact with rotation effects. Electrical source imaging showed that the underlying neural processing of this non-retinotopic effect seems to be located partially in extrastriate visual areas.