Coherent concepts are computed in the anterior temporal lobes

Abstract

In his Philosophical Investigations, Wittgenstein famously noted that the formation of semantic representations requires more than a simple combination of verbal and nonverbal features to generate conceptually based similarities and differences. Classical and contemporary neuroscience has tended to focus upon how different neocortical regions contribute to conceptualization through the summation of modality-specific information. The additional yet critical step of computing coherent concepts has received little attention. Some computational models of semantic memory are able to generate such concepts by the addition of modality-invariant information coded in a multidimensional semantic space. By studying patients with semantic dementia, we demonstrate that this aspect of semantic memory becomes compromised following atrophy of the anterior temporal lobes and, as a result, the patients become increasingly influenced by superficial rather than conceptual similarities.

Fig. 1.

Diagrams of the distributed semantic hypothesis, the hub-and-spoke model, and examples of the ATL atrophy present in semantic dementia. In many traditional and contemporary accounts of conceptualization, semantic representations are formed as a by-product of the interaction between sensory, verbal, and motor association cortices. This notion is summarized in A. A revision of this idea is presented in B in which, in addition to modality-specific sources, conceptualization also involves modality-invariant representations. Through their interaction, this framework is able to address various key computational challenges that are posed when concepts are formed from transmodal experience (see text). In this study, we tested the hypothesis that this invariant contribution can break down after damage to the ATL by assessing a series of patients with semantic dementia, which produces a selective semantic impairment in the context of relatively localized atrophy of the ATL. Sample MR images from one patient (MT) are shown in C.

Fig. 2.

Example of the complex relationship between features and concepts. As can be seen, although some visual similarities and features are related (e.g., made of copper, requires specific cleaning), many are not (e.g., fragile). Instead, there is a complex tapestry of features, each of which extend over a different area. These complex arrangements can be mapped by projecting the modality-specific information into a high-dimensional, modality-invariant space (in the anterior temporal lobes). See text.

Fig. 3.

Semantic dementia performance on the matching-to-sample task. Performance for six SD patients and control participants is shown in the top panel. Error bars denote the SE of the control mean per condition. Asterisks denote abnormal performance. Examples of the five types of item within the choice array are shown below the relevant conditions (see SI Text for further details). Each trial contained a mixture of targets and foils. The targets included both typical and atypical examples of each target concept (e.g., cat, ball, fish, shoe). There were also three types of foil. Some were pseudotypical examples which, although not an exemplar of the target concept, share many features in common; some were partially related; and the remainder were unrelated. The SD patients made a combination of two types of selection error: (i) undergeneralization—failures to pick examples of the target concept (especially of the atypical exemplars) and (ii) overgeneralization—incorrect selection of nonconcept items (particularly pseudotypical and some partially related choices).

Fig. 4.

Conceptual differentiation versus surface similarity structure. These animal pictures are arranged (approximately) according to visual similarity. As a result, the boundary of the concept cat has to have a complex shape (i) if the structurally different exemplars of cats are to be included and (ii) if the visually similar non-cats are to be excluded (A). Such complex boundaries can be coded within a fully functional, multidimensional (ATL) amodal semantic space. When this space breaks down in the context of brain damage, however, only simple boundaries can be coded (B). As a result, some items are falsely excluded from the cat concept (undergeneralizations, marked in red) and some are incorrectly drawn within the cat concept boundary (overgeneralizations, marked in blue).