@article {1726, title = {Face Patch Resting State Networks Link Face Processing to Social Cognition.}, journal = {PLoS Biology}, volume = {13}, year = {2015}, month = {09/2015}, pages = {e1002245}, abstract = {

Faces transmit a wealth of social information. How this information is exchanged between face-processing centers and brain areas supporting social cognition remains largely unclear. Here we identify these routes using resting state functional magnetic resonance imaging in macaque monkeys. We find that face areas functionally connect to specific regions within frontal, temporal, and parietal cortices, as well as subcortical structures supporting emotive, mnemonic, and cognitive functions. This establishes the existence of an extended face-recognition system in the macaque. Furthermore, the face patch resting state networks and the default mode network in monkeys show a pattern of overlap akin to that between the social brain and the default mode network in humans: this overlap specifically includes the posterior superior temporal sulcus, medial parietal, and dorsomedial prefrontal cortex, areas supporting high-level social cognition in humans. Together, these results reveal the embedding of face areas into larger brain networks and suggest that the resting state networks of the face patch system offer a new, easily accessible venue into the functional organization of the social brain and into the evolution of possibly uniquely human social skills.

}, keywords = {Face recognition, neural nerworks, prefrontal cortex, social cognition}, issn = {1545-7885}, doi = {10.1371/journal.pbio.1002245}, url = {http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002245}, author = {Schwiedrzik, Caspar M and Wilbert Zarco and Everling, Stefan and W. A. Freiwald} } @article {357, title = {Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines?}, number = {003}, year = {2014}, month = {03/2014}, abstract = {

The standard approach to unconstrained face recognition in natural photographs is via a detection, alignment, recognition pipeline. While that approach has achieved impressive results, there are several reasons to be dissatisfied with it, among them is its lack of biological plausibility. A recent theory of invariant recognition by feedforward hierarchical networks, like HMAX, other convolutional networks, or possibly the ventral stream, implies an alternative approach to unconstrained face recognition. This approach accomplishes detection and alignment implicitly by storing transformations of training images (called templates) rather than explicitly detecting and aligning faces at test time. Here we propose a particular locality-sensitive hashing based voting scheme which we call {\textquotedblleft}consensus of collisions{\textquotedblright} and show that it can be used to approximate the full 3-layer hierarchy implied by the theory. The resulting end-to-end system for unconstrained face recognition operates on photographs of faces taken under natural conditions, e.g., Labeled Faces in the Wild (LFW), without aligning or cropping them, as is normally done. It achieves a drastic improvement in the state of the art on this end-to-end task, reaching the same level of performance as the best systems operating on aligned, closely cropped images (no outside training data). It also performs well on two newer datasets, similar to LFW, but more difficult: LFW-jittered (new here) and SUFR-W.

}, keywords = {Computer vision, Face recognition, Hierarchy, Invariance}, author = {Qianli Liao and JZ. Leibo and Youssef Mroueh and Tomaso Poggio} } @article {225, title = {Neural Mechanisms of Object-Based Attention}, journal = {Science}, volume = {344}, year = {2014}, month = {04/2014}, pages = {424 - 427}, abstract = {

How we attend to objects and their features that cannot be separated by location is not understood. We presented two temporally and spatially overlapping streams of objects, faces versus houses, and used magnetoencephalography and functional magnetic resonance imaging to separate neuronal responses to attended and unattended objects. Attention to faces versus houses enhanced the sensory responses in the fusiform face area (FFA) and parahippocampal place area (PPA), respectively. The increases in sensory responses were accompanied by induced gamma synchrony between the inferior frontal junction, IFJ, and either FFA or PPA, depending on which object was attended. The IFJ appeared to be the driver of the synchrony, as gamma phases were advanced by 20 ms in IFJ compared to FFA or PPA. Thus, the IFJ may direct the flow of visual processing during object-based attention, at least in part through coupled oscillations with specialized areas such as FFA and PPA.

}, keywords = {Face recognition, Theories for Intelligence, Visual Intelligence}, issn = {0036-8075}, doi = {10.1126/science.1247003}, url = {http://www.sciencemag.org/cgi/doi/10.1126/science.1247003}, author = {Baldauf, D. and R. Desimone} }