@article {441, title = {A normalization model of visual search predicts single trial human fixations in an object search task.}, number = {008}, year = {2014}, month = {04/2014}, abstract = {

When searching for an object in a scene, how does the brain decide where to look next? Theories of visual search suggest the existence of a global attentional map, computed by integrating bottom-up visual information with top-down, target-specific signals. Where, when and how this integration is performed remains unclear. Here we describe a simple mechanistic model of visual search that is consistent with neurophysiological and neuroanatomical constraints, can localize target objects in complex scenes, and predicts single-trial human behavior in a search task among complex objects. This model posits that target-specific modulation is applied at every point of a retinotopic area selective for complex visual features and implements local normalization through divisive inhibition. The combination of multiplicative modulation and divisive normalization creates an attentional map in which aggregate activity at any location tracks the correlation between input and target features, with relative and controllable independence from bottom-up saliency. We first show that this model can localize objects in both composite images and natural scenes and demonstrate the importance of normalization for successful search. We next show that this model can predict human fixations on single trials, including error and target-absent trials. We argue that this simple model captures non-trivial properties of the attentional system that guides visual search in humans.

}, keywords = {Circuits for Intelligence, Pattern recognition}, author = {Thomas Miconi and Laura Groomes and Gabriel Kreiman} } @article {440, title = {Sensitivity to Timing and Order in Human Visual Cortex.}, number = {005}, year = {2014}, month = {04/2014}, abstract = {

Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual areas, information must progress from stage to stage very quickly. This rapid progression of information suggests that fine temporal details of the neural response may be important to the how the brain encodes visual signals. We investigated how changes in the relative timing of incoming visual stimulation affect the representation of object information by recording intracranial field potentials along the human ventral visual stream while subjects recognized objects whose parts were presented with varying asynchrony. Visual responses along the ventral stream were sensitive to timing differences between parts as small as 17 ms. In particular, there was a strong dependency on the temporal order of stimulus presentation, even at short asynchronies. This sensitivity to the order of stimulus presentation provides evidence that the brain may use differences in relative timing as a means of representing information.

}, keywords = {Circuits for Intelligence, Pattern recognition, Visual}, author = {Jedediah Singer and Joseph Madsen and WS Anderson and Gabriel Kreiman} } @article {217, title = {Spatiotemporal Dynamics Underlying Object Completion in Human Ventral Visual Cortex}, journal = {Neuron}, volume = {83}, year = {2014}, month = {08/06/2014}, pages = {736 - 748}, abstract = {

Natural vision often involves recognizing objects from partial information. Recognition of objects from parts presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. Here we recorded intracranial field potentials of 113 visually selective electrodes from epilepsy patients in response to whole and partial objects. Responses along the ventral visual stream, particularly the Inferior Occipital and Fusiform Gyri, remained selective despite showing only 9-25\% of the object areas. However, these visually selective signals emerged ~100 ms later for partial versus whole objects. These processing delays were particularly pronounced in higher visual areas within the ventral stream. This latency difference persisted when controlling for changes in contrast, signal amplitude, and the strength of selectivity. These results argue against a purely feed-forward explanation of recognition from partial information, and provide spatiotemporal constraints on theories of object recognition that involve recurrent processing.

}, keywords = {Circuits for Intelligence, vision}, issn = {08966273}, doi = {10.1016/j.neuron.2014.06.017}, url = {http://linkinghub.elsevier.com/retrieve/pii/S089662731400539Xhttp://api.elsevier.com/content/article/PII:S089662731400539X?httpAccept=text/xmlhttp://api.elsevier.com/content/article/PII:S089662731400539X?httpAccept=text/plain}, author = {Hanlin Tang and Buia, Calin and Radhika Madhavan and NE Crone and Joseph Madsen and WS Anderson and Gabriel Kreiman} }