SUMMARY Neurons in piriform cortex receive input from a random collection of glomeruli, resulting in odor representations that lack the stereotypic organization of the olfactory bulb. We have performed in vivo optical imaging and mathematical modeling to demonstrate that correlations are retained in the transformation from bulb to piriform cortex, a feature essential for generalization across odors. Random connectivity also implies that the piriform representation of a given odor will differ among different individuals and across brain hemispheres in a single individual. We show that these different representations can nevertheless support consistent agreement about odor quality across a range of odors. Our model also demonstrates that, whereas odor discrimination and categorization require far fewer neurons than reside in piriform cortex, consistent generalization may require the full complement of piriform neurons.

Primary sensory cortex has long been believed to play a straightforward role in the initial processing of sensory information. Yet, the superficial layers of cortex overall are sparsely active, even during sensory stimulation; additionally, cortical activity is influenced by other modalities, task context, reward, and behavioral state. Our study demonstrates that reinforcement learning dramatically alters representations among longitudinally imaged neurons in superficial layers of mouse primary somatosensory cortex. Learning an object detection task recruits previously unresponsive neurons, enlarging the neuronal population sensitive to touch and behavioral choice. Cortical responses decrease upon repeated stimulus presentation outside of the behavioral task. Moreover, training improves population encoding of the passage of time, and unexpected deviations in trial timing elicit even stronger responses than touches do. In conclusion, the superficial layers of sensory cortex exhibit a high degree of learning-dependent plasticity and are strongly modulated by non-sensory but behaviorally-relevant features, such as timing and surprise.

The current study examines Causal Essentialism, derived from Psychological Essentialism of concepts (Medin & Ortony, 1989). We examine whether people believe that members of a category share some underlying essence that is both necessary and sufficient for category membership and that also causes surface features. The main claim is that Causal Essentialism is restricted to categories that correspond to our intuitive notions of existing kinds, and hence is more attenuated for categories that are based on arbitrary criteria. Experiments 1 and 3 found that people overtly endorse causal essences in non-arbitrary kinds but are less likely to do so for arbitrary categories. Experiments 2 and 4 found that people were more willing to generalize a member's known causal relations (or lack thereof) when dealing with a kind than when dealing with an arbitrary category. These differences between kinds and arbitrary categories were found across various domains-not only categories of living things, but also for artifacts. These findings have certain real-world implications, including how people make sense of mental disorders that are treated as real kinds.Some categories, like "robins," and "chairs," are intuitively more appropriate than other categories, like "things that weigh about 2 pounds, are white, and have a smooth surface" and "a group of mental disorder patients whose last names began with

Primary sensory cortex has long been believed to play a straightforward role in the initial processing of sensory information. Yet, the superficial layers of cortex overall are sparsely active, even during sensory stimulation; moreover, cortical activity is influenced by other modalities, task context, reward, and behavioral state. Our study demonstrates that reinforcement learning dramatically alters representations among longitudinally imaged neurons in superficial layers of mouse primary somatosensory cortex. Learning an object detection task recruits previously unresponsive neurons, enlarging the neuronal population sensitive to touch and behavioral choice. In contrast, cortical responses decrease upon repeated exposure to unrewarded stimuli. Moreover, training improved population encoding of the passage of time, and unexpected deviations in trial timing elicited even stronger responses than touch did. In conclusion, the superficial layers of sensory cortex exhibit a high degree of learning-dependent plasticity and are strongly modulated by non-sensory but behaviorally-relevant features, such as timing and surprise.