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Article review by Alexander Backus

Distributed representations meeting article review . Aim: Investigate whether an object-based system of scene recognition exists in LOC and/or PPA. Article review by Alexander Backus . Experimental design E1. 104 scenes 208 object images (exemplars) associated with the scenes

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Article review by Alexander Backus

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  1. Distributed representations meeting article review Aim: Investigate whether an object-based system of scene recognition exists in LOC and/or PPA Article review by Alexander Backus

  2. Experimental design E1 104 scenes 208 object images (exemplars) associated with the scenes Presented interleaved for 1s with 2s ISI Subjects silently named each scene/object If scene representations in LOC (LO + pF) and/or PPA are built from the constituent exemplars, it is possible to classify scene-evoked patterns with combinations of object-evoked patterns.

  3. Scene classification analysis

  4. Results E1 Confound: for scenes, subjects might have attended serially to the single constituent objects E2: faster stimulus presentation (150ms)

  5. Results E2 Confound: relationship between scene- and object-evoked patterns reflect template development for object search? E3: first a block with only scenes, then a block with only objects

  6. Results E3

  7. Other analyses Which common features of scenes and objects does LO encode? Visual/semantic? Classify each object category on the basis of patterns evoked by the other object category from the same context: Train on: & , test on: & LO primarily encodes visual features for short stimulus presentation times, but also semantic features for longer presentation times

  8. Other analyses Is there information outside of the ROIs? Whole-brain searchlight procedure Motor-related pF PPA LO LO is unique among occipitotemporal visual areas in possessing an object-based scene recognition mechanism

  9. Other analyses Is an object-based scene recognition mechanism actually used? 4AFC task with briefly presented scenes (50ms) Zero, one or two of the constituent objects were obscured Significant effect of number of objects removed on performance and RT Scene identification falters when both of the exemplars are removed, but only if enough of the image is obscured to simultaneously affect image-based system

  10. Conclusions An object-based scene recognition mechanism in LO PPA concerned with large-scale spatial features LO patterns are built from individual object patterns

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