Case series investigations in cognitive neuropsychology

Abstract

Case series methodology involves the systematic assessment of a sample of related patients, with the goal of understanding how and why they differ from one another. This method has become increasingly important in cognitive neuropsychology, which has long been identified with single-subject research. We review case series studies dealing with impaired semantic memory, reading, and language production and draw attention to the affinity of this methodology for testing theories that are expressed as computational models and for addressing questions about neuroanatomy. It is concluded that case series methods usefully complement single-subject techniques.

Keywords:

• Aphasia
• Case series
• Lexical access
• Semantic memory
• Computational models

Acknowledgments

We acknowledge with gratitude the support of NIH/NIDCD (National Institutes of Health/National Institute on Deafness and Other Communication Disorders) Grant RO1DC000191–28 to M.F.S. and helpful suggestions from Dan Mirman and Simon Fischer-Baum on an earlier version of the manuscript.

Notes

¹A related concern about nonlinearity arises because most neuropsychological tests yield a percentage value—that is, a value on a scale from zero to a logical maximum such as 100%. Analyses that treat percentage score differences as equivalent across the scale may be misleading. Logistic regression, in which percentages are transformed into the logit of the response types—that is, ln[p(correct)/p(incorrect)]—is considered an appropriate remedy for this problem in percentage/proportion data (Jaeger, 2008), and we recommend that these methods be adopted where appropriate in neuropsychological case series analysis (Dilkina, McClelland, & Plaut, 2008). Moreover, with the advent of new software, logistic regression can now be done in a multilevelled manner, so that each measurement trial can be associated with a specific participant and item, and both participants and items can be treated as random effects (e.g., Nozari, Kittredge, Dell, & Schwartz, 2010).

²This is because formal errors at the lexical level require a sufficiently low semantic parameter so that lexical selection of the target is impaired, but a sufficiently strong phonological parameter that phonological feedback activates formal competitors (such as “mat”), and that, if “mat” is selected, it is correctly pronounced.