The Encoding of Temporally Irregular and Regular Visual Patterns in the Human Brain

In the work reported here, we set out to study the neural systems that detect predictable temporal patterns and departures from them. We used functional magnetic resonance imaging (fMRI) to locate activity in the brains of subjects when they viewed temporally regular and irregular patterns produced by letters, numbers, colors and luminance. Activity induced by irregular sequences was located within dorsolateral prefrontal cortex, including an area that was responsive to irregular patterns regardless of the type of visual stimuli producing them. Conversely, temporally regular arrangements resulted in activity in the right frontal lobe (medial frontal gyrus), in the left orbito-frontal cortex and in the left pallidum. The results show that there is an abstractive system in the brain for detecting temporal irregularity, regardless of the source producing it

The influence of spatial pattern on visual short-term memory for contrast

Several psychophysical studies of visual short-term memory (VSTM) have shown high-fidelity storage capacity for many properties of visual stimuli. On judgments of the spatial frequency of gratings, for example, discrimination performance does not decrease significantly, even for memory intervals of up to 30 s. For other properties, such as stimulus orientation and contrast, however, such “perfect storage” behavior is not found, although the reasons for this difference remain unresolved. Here, we report two experiments in which we investigated the nature of the representation of stimulus contrast in VSTM using spatially complex, two-dimensional random-noise stimuli. We addressed whether information about contrast per se is retained during the memory interval by using a test stimulus with the same spatial structure but either the same or the opposite local contrast polarity, with respect to the comparison (i.e., remembered) stimulus. We found that discrimination thresholds got steadily worse with increasing duration of the memory interval. Furthermore, performance was better when the test and comparison stimuli had the same local contrast polarity than when they were contrast-reversed. Finally, when a noise mask was introduced during the memory interval, its disruptive effect was maximal when the spatial configuration of its constituent elements was uncorrelated with those of the comparison and test stimuli. These results suggest that VSTMfor contrast is closely tied to the spatial configuration of stimuli and is not transformed into a more abstract representation

The Spatial and Temporal Deployment of Voluntary Attention across the Visual Field

Several studies have addressed the question of the time it takes for attention to shift from one position in space to another. Here we present a behavioural paradigm which offers a direct access to an estimate of voluntary shift time by comparing, in the same task, a situation in which subjects are required to re-engage their attention at the same spatial location with a situation in which they need to shift their attention to another location, all other sensory, cognitive and motor parameters being equal. We show that spatial attention takes on average 55 ms to voluntarily shift from one hemifield to the other and 38 ms to shift within the same hemifield. In addition, we show that across and within hemifields attentional processes are different. In particular, attentional spotlight division appears to be more difficult to operate within than across hemifields

Neural Correlates of Visual Motion Prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities

Spatio-Temporal Brain Mapping of Motion-Onset VEPs Combined with fMRI and Retinotopic Maps

Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR)