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Current models propose that the brain uses a multi-layered architecture to reduce the high dimensional visual input to lower dimensional representations that support face, object and scene categorizations. However, understanding the brain mechanisms that support such information reduction for behavior remains challenging. We addressed the challenge using a novel information theoretic framework that quantifies the relationships between three key variables: single-trial information randomly sampled from an ambiguous scene, source-space MEG responses and perceptual decision behaviors. In each observer, behavioral analysis revealed the scene features that subtend their decisions. Independent source space analyses revealed the flow of these and other features in cortical activity. We show where (at the junction between occipital cortex and ventral regions), when (up until 170 ms post stimulus) and how (by separating task-relevant and irrelevant features) brain regions reduce the high-dimensional scene to construct task-relevant feature representations in the right fusiform gyrus that support decisions. Our results inform the occipito-temporal pathway mechanisms that reduce and select information to produce behavior.. CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/284158 doi: bioRxiv preprint first posted online Mar. 18, 2018; 3 Over the past decade, there has been extensive studies of the regions of the brain that support face, object and scene recognition using different methodologies and modalities of brain measurements (e.g. electrophysiology, E/MEG and fMRI), including across species. A converging set of results now suggests a hierarchically organized architecture of brain regions, spanning the occipital and temporal lobes (1-17), where categorizations unfold over the first few hundred milliseconds of post stimulus processing (18)(19)(20)(21)(22). This same architecture is flexibly involved in multiple categorization tasks that require multiple representational bases. With extensive knowledge of the where and when, the next challenge is to unravel the thorny how.That is, how detailed information processing mechanisms in the occipitoventral pathway dynamically implement flexible visual categorization by selecting, from the high-dimensional input, the low-dimensional information basis required for behavior?In other words, how does our brain extract, from the features of the visual scene that it initially represents, those that are actually useful for the categorization task?To start addressing this considerable challenge, we used Dali's ambiguous painting Slave Market with Disappearing Bust of Voltaire (see Figure1, Stimulus) as a case-study stimulus because it is a complex visual scene that affords two distinct perceptions. We applied the Bubbles technique (Gosselin & Schyns, 20001) to character...

SummaryOver the past decade, extensive studies of the brain regions that support face, object, and scene recognition suggest that these regions have a hierarchically organized architecture that spans the occipital and temporal lobes [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], where visual categorizations unfold over the first 250 ms of processing [15, 16, 17, 18, 19]. This same architecture is flexibly involved in multiple tasks that require task-specific representations—e.g. categorizing the same object as “a car” or “a Porsche.” While we partly understand where and when these categorizations happen in the occipito-ventral pathway, the next challenge is to unravel how these categorizations happen. That is, how does high-dimensional input collapse in the occipito-ventral pathway to become low dimensional representations that guide behavior? To address this, we investigated what information the brain processes in a visual perception task and visualized the dynamic representation of this information in brain activity. To do so, we developed stimulus information representation (SIR), an information theoretic framework, to tease apart stimulus information that supports behavior from that which does not. We then tracked the dynamic representations of both in magneto-encephalographic (MEG) activity. Using SIR, we demonstrate that a rapid (∼170 ms) reduction of behaviorally irrelevant information occurs in the occipital cortex and that representations of the information that supports distinct behaviors are constructed in the right fusiform gyrus (rFG). Our results thus highlight how SIR can be used to investigate the component processes of the brain by considering interactions between three variables (stimulus information, brain activity, behavior), rather than just two, as is the current norm.

Modeling individual preferences reveals that face beauty is not universally perceived across cultures Highlights d We modeled individual preferences for attractive faces in two cultures d Attractive face features differ from the face average and sexual dimorphism d Instead, culture and individual preferences shape attractive face features d Attractive face features from a culture are used to judge other-ethnicity faces

Highlights d DNNs modeled how humans rate the similarity of familiar faces to random face stimuli d A generative model controlled the shape and texture features of the face stimuli d The best DNN predicted human behavior because it used similar face-shape features d Explaining human behavior from causal features is difficult with naturalistic images