Decoding successive computational stages of saliency processing.
Bogler C, Bode S, Haynes JD.
Published in Curr Biol. 2011 Oct 11;21(19):1667-71.
An important requirement for vision is to identify interesting and relevant regions of the environment for further processing. Some models assume that salient locations from a visual scene are encoded in a dedicated spatial saliency map [1, 2]. Then, a winner-take-all (WTA) mechanism [1, 2] is often believed to threshold the graded saliency representation and identify the most salient position in the visual field. Here we aimed to assess whether neural representations of graded saliency and the subsequent WTA mechanism can be dissociated. We presented images of natural scenes while subjects were in a scanner performing a demanding fixation task, and thus their attention was directed away. Signals in early visual cortex and posterior intraparietal sulcus (IPS) correlated with graded saliency as defined by a computational saliency model. Multivariate pattern classification [3, 4] revealed that the most salient position in the visual field was encoded in anterior IPS and frontal eye fields (FEF), thus reflecting a potential WTA stage. Our results thus confirm that graded saliency and WTA-thresholded saliency are encoded in distinct neural structures. This could provide the neural representation required for rapid and automatic orientation toward salient events in natural environments.
Neural responses to unattended products predict later consumer choices.
Tusche A, Bode S, Haynes JD.
Published in J Neurosci. 2010 Jun 9;30(23):8024-31.
Imagine you are standing at a street with heavy traffic watching someone on the other side of the road. Do you think your brain is implicitly registering your willingness to buy any of the cars passing by outside your focus of attention? To address this question, we measured brain responses to consumer products (cars) in two experimental groups using functional magnetic resonance imaging. Participants in the first group (high attention) were instructed to closely attend to the products and to rate their attractiveness. Participants in the second group (low attention) were distracted from products and their attention was directed elsewhere. After scanning, participants were asked to state their willingness to buy each product. During the acquisition of neural data, participants were not aware that consumer choices regarding these cars would subsequently be required. Multivariate decoding was then applied to assess the choice-related predictive information encoded in the brain during product exposure in both conditions. Distributed activation patterns in the insula and the medial prefrontal cortex were found to reliably encode subsequent choices in both the high and the low attention group. Importantly, consumer choices could be predicted equally well in the low attention as in the high attention group. This suggests that neural evaluation of products and associated choice-related processing does not necessarily depend on attentional processing of available items. Overall, the present findings emphasize the potential of implicit, automatic processes in guiding even important and complex decisions.
Beyond Topographic Representation: Decoding Visuospatial Attention from Local Activity Patterns in the Human Frontal Cortex
Christian Kalberlah, Yi Chen, Jakob Heinzle, John-Dylan Haynes
Published in Int J Imaging Syst Technol, 21, 201–210, 2011
The ability to detect where a person is attending is fundamental for brain-computer-interfaces. We explore how the attentional focus can be decoded from brain signals noninvasively acquired with functional magnetic resonance imaging (fMRI). Several cortical regions have previously been reported to have topographic maps reflecting the focus of visual attention. Interestingly, attentional maps were observed to be gradually less topographic when moving from early visual areas toward extra-occipital areas. Recent studies suggested that this might indicate a shift from topographically represented local processing to a global processing dominated by laterality. However, it remains unclear, to which extent the topographical representation of a region characterizes its quality to encode visuospatial attention. Here we addressed this problem by applying multivoxel pattern analysis to fMRI signals. In combination with a cortical surface-based mapping of spatial preference, our analysis revealed a broad cortical network that locally contains information about the locus of visual attention. The informative regions are not restricted to topographic areas, but even in frontal areas, where topographic organization is almost indiscernible, the attentional locus can be decoded from brain activity. Specifically, we find attentional information in the right middle frontal gyrus and the right ventrolateral prefrontal cortex. Furthermore, in these two areas information is sufficient to distinguish attentional loci within the ipsi- as well as the contra-lateral visual hemifields. The laterality dominance decreases when moving from occipital to frontal areas. Our results suggest that information about visuospatial attention is encoded beyond topographically organized regions by local patterns of brain activity.
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