The Influence of Feature Type, Feature Structure and Psycholinguistic Parameters on

the Naming Performance of Semantic Dementia and Alzheimer’s Patients.

Department of Psychology, University College London, UK

Krist Noonan* & Peter Garrard

(*) Significant at .05, (**) Significant at .01. * correspondence <noonank@lsbu.ac.uk>

•The ability to understand and interpret certain categories of conceptual knowledge can be lost following focal or degenerative brain damage.

•“Living kinds” are most frequently affected with non-living concepts often remaining “relatively” intact. This phenomena is know as category specific semantic impairment.

•The underlying principles of semantic memory are often disputed; different accounts exist based on feature type, feature structure and psycholinguistic parameters. No current studies have investigated the predictive power of these theories on a single set of patients

How is conceptual knowledge organized?

Three Explanations of Category Specific Semantic Impairments

Analysis 2: Predicting Group & Individual Patient Naming

Summary and Discussion

References[1] Warrington, E. K., & Shallice, T. (1984). Category-specific semantic impairments. Brain, 107: 829-853.

[2] Devlin, J.T., Gonnerman, L.M., Andersen, E.S. & Seidenberg, M.S. (1998) Category-specific semantic deficits in focal and widespread brain damage: A computational account. Journal of Cognitive Neuroscience, 10, 77-94.

[3] Sartori, G. & Lombardi, L. (2004). Semantic relevance and semantic disorders. Journal of Cognitive Neuroscience, 16, 439-452.

Analysis 3: Feature Structure and Disease Severity

Analysis 1: Performance Across Domain & Modality

Introduction

[1] Knowledge for living concepts is differentially reliant on perceptual information. Nonliving on functional information e.g. what a concept is used for (Fig 1, Analyses 1).

[2] Living concepts have more features which are shared and intercorrelated across items. Nonliving have more distinctive features. Patterns of knowledge impairment change as feature structure interacts with disease progression (Fig 2, Analyses 3).

[3] Semantic Relevance is the organizing principle of semantic memory. A feature is high in relevance when its consistently used across individuals to identify a concept (dominance) and distinguishes that concept from other exemplars (distinctiveness) (Fig 3, Analyses 2).

•Two patients show a category advantage for nonliving concepts.

•Only one of the two shows an advantage for functional descriptions.

•Five patients show better performance for functional descriptions but no accompanying advantage for non-living concepts.

RESULTS (accuracy across domain & modality of description)

• 5 Semantic Dementia (SD) & 5 Alzheimer’s (AD) patients were tested on a naming to description task.

• 58 living & 64 non-living concepts. Each concept had two descriptions one emphasizing perceptual, the other emphasizing functional information

METHOD

• Individual and group regression analyses were conducted to predict individual item naming.

•Including feature level predictor variables (relevance, dominance, distinctiveness & feature intercorrelation ), psycholinguistic variables (familiarity, word frequency & age of acquisition).

METHOD

RESULTS: Which variables influenced naming?

CONCLUSION

• The Sensory functional theory cannot accommodate the findings of this analysis which indicates that deficits in identifying concepts from perceptual knowledge can arise without the accompanying deficit for identifying living concepts.

CONCLUSIONS:

• Descriptions emphasizing functional knowledge.

• Psycholinguistic variables, especially familiarity.

• Semantic Relevance for SD group, although largely a result of the influence of patient VH.

PREDICTIONS & METHOD

• Non-Living concepts should be consistently predicted by feature distinctiveness (Devlin et al, 1998). • Living concepts should be predicted by the interaction between the proportion of shared and intercorrelated features in the initial stages of dementia (Devlin et al, 1998).

•Tested using individual regressions for each patient on separate living and non-living item subsets.

RESULTS

CONCLUSION

• The conceptual structure approach could not account for the majority of the patients’ naming performance.

Living vs Non-Living Perceptual vs Functional

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No category advantage remained when psycholinguistic variables were accounted for.

Semantic Relevance Theory is a poor predictor of successful naming.

Better performance based on functional Knowledge may be related to areas of temporal lobe atrophy seen in SD & AD.

•Variables included: (dominance, distinctiveness, feature intercorrelation, intercorrelation* distinctiveness & relevance).

Patients regression predictors plotted on a stylised representation of Devlin et al’s (1998) concept loss curves.

KH & RB only patients to have living concepts predicted by shared / intercorrelated features.

No patient showed non-living performance to be predicted by distinctiveness

1. All three of the feature level theories considered proved insufficient to explain the patterns of patient performance.

2. In contrast psycholinguistic variables consistently predicted naming performance across individual patients and both dementia groups. These findings indicate that concepts which are frequently encountered and acquired at an early age are more resistant to loss.

3. Descriptions composed of functional attribute knowledge provided an advantage for naming in many of the patients studied. It is proposed that this may result from the progressive damage to the inferior lateral and medial temporal lobes seen in SD and AD respectively. These brain regions are often associated with high-level visual knowledge and this may account for the patients impairments on naming concepts from perceptual (often visual) attribute knowledge.