SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUS-TAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told

An argument is categorical if its premises and conclusion are of the form All members ofC have property F, where C is a natural category like FALCON or BIRD, and P remains the same across premises and conclusion. An example is Grizzly bears love onions. Therefore, all bears love onions

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Abstract It is briefly discussed here the problem of supraspecific categories. The Author thinks that they are not "products of our mind", as it is co mmonly repeated, but that they rather reflect so mething happened in natural history, which designs, as far as we can presently

Caltech-UCSD Birds 200 (CUB-200) is a challenging image dataset annotated with 200 bird species. It was created to enable the study of subordinate categorization, which is not possible with other popular datasets that focus on basic level categories (such as PASCAL VOC, Caltech-101, etc

-related potentials. An enhanced early negative component (N170, 164 ms) was found when bird and dog experts categorized objects in their domain of expertise relative to when they categorized objects outside their domain of expertise. This finding indicates that objects from well-learned categories are neurologically

Birds routinely execute aerial maneuvers that are far beyond the capabilities of our best aircraft control systems. The complexity and variability of the aerodynamics during these maneuvers are formidable, with dominant flow structures (e.g., vortices) that are difficult to predict robustly from

’ ’ written three times), while neutral trials contain single semantic category common animals (e.g., ‘‘bird’’). Nine normal right-handed adult volunteers underwent fMRI while performing the Counting Stroop. Group fMRI data revealed significant (P # 10-4) activity in the cognitive division of anterior

-to-side as a threat (or for courtship). It is interesting that certain types of oscillatory motion patterns appear across such a variety of species. In Table 1, we list a set of oscillatory motion patterns which appear widely throughout the animal kingdom and that in particular are used by birds as a form

this knowledge has remained unresolved. We designed a stimulus set consisting of six highly similar bird types that can hardly be distinguished without training. All bird types were morphed with one another to create different exemplars of each category. After visual training, fMRI showed that responses