کلیه در مقابل ویژگی های مبتنی بر لوب مدیال زمانی

A central question for cognitive neuroscience is how feature-combinations that give rise to episodic/source memories are encoded in the brain. Although there is much evidence that the hippocampus (HIP) is involved in feature binding, and some evidence that other brain regions are as well, there is relatively little evidence about the nature of the resulting representations in different brain regions. We used multivoxel pattern analysis (MVPA) to investigate how feature combinations might be represented, contrasting two possibilities, feature-based versus holistic. Participants viewed stimuli that were composed of three source features – a person (face or body), a scene (indoor or outdoor), and an object (bike or luggage) – which were combined to make eight unique stimulus identities. We reasoned that regions that can classify the eight identities (a multiclass classification) but not the individual features (a binary classification) likely have a holistic representation of each identity. In contrast, regions that can classify the eight identities and can classify each feature are likely to contain feature-based representations of these identities. To further probe the extent of feature-based or holistic classification in each region, we developed and validated a novel approach that directly compares binary and multiclass classification. We found clear evidence for holistic representation in the parahippocampal cortex (PHC), consistent with theories that posit that pattern-separation-like binding mechanisms are not unique to the HIP. Further clarifying the mechanisms of feature binding should benefit from systematic comparisons of multi-feature representations and whether they vary with task, type of stimulus, and/or experience.