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Review
. 2013 Dec 9;369(1634):20120398.
doi: 10.1098/rstb.2012.0398. Print 2014.

Connectionist neuropsychology: uncovering ultimate causes of acquired dyslexia

Anna M Woollams  1
Affiliations
Review

Connectionist neuropsychology: uncovering ultimate causes of acquired dyslexia

Anna M Woollams. Philos Trans R Soc Lond B Biol Sci. .

Abstract

Acquired dyslexia offers a unique window on to the nature of the cognitive and neural architecture supporting skilled reading. This paper provides an integrative overview of recent empirical and computational work on acquired dyslexia within the context of the primary systems framework as implemented in connectionist neuropsychological models. This view proposes that damage to general visual, phonological or semantic processing abilities are the root causes of different forms of acquired dyslexia. Recent case-series behavioural evidence concerning pure alexia, phonological dyslexia and surface dyslexia that supports this perspective is presented. Lesion simulations of these findings within connectionist models of reading demonstrate the viability of this approach. The commitment of such models to learnt representations allows them to capture key aspects of performance in each type of acquired dyslexia, particularly the associated non-reading deficits, the role of relearning and the influence of individual differences in the premorbid state of the reading system. Identification of these factors not only advances our understanding of acquired dyslexia and the mechanisms of normal reading but they are also relevant to the complex interactions underpinning developmental reading disorders.

Keywords: connectionist neuropsychology; phonological dyslexia; primary systems; pure alexia; reading; surface dyslexia.

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Figures

Figure 1.
Figure 1.
(a) Lesion overlap maps for the case series of patients with left posterior fusiform gyrus lesions according to the severity of their reading disorders (slope of the length effect) from [11], with the scale representing the number of participants out of the total in that group with lesions in a given area. (b) For the same patients, reading performance according to word length (i) and matching performance for unfamiliar Kanji symbols according to complexity and foil similarity (ii) from [11]. (c) The connectionist model from [29], which accepts retinotopic visual input (bottom layer of units, within each block, central on left and peripheral on right), with red indicating the set of units where the damage produced deficits in both word and face processing.
Figure 2.
Figure 2.
(a) Three example cases of lesions associated with phonological dyslexia from [44], encompassing posterior inferior frontal gyrus/Broca's area/precentral Gyrus (left), superior temporal gyrus (middle, arrow) and supramarginal gyrus (right, arrow). (b) Reading performance for 12 chronic stroke aphasic patients from [43] on the Psycholinguistic Assessments of Language Processing in Aphasia (PALPA) 31 low-frequency words and PALPA 36 nonwords, with severity determined by picture-naming ability (i) and 34 observations of progressive non-fluent aphasia patients’ reading from [13] on the Surface List low-frequency words and nonwords, with severity determined by picture-naming ability (ii). (c) The connectionist model from [45] with red indicating the connections damaged to simulate phonological dyslexia (dotted and solid arrows indicate 30 and 80% connectivity, respectively).
Figure 3.
Figure 3.
(a) Areas of hypometabolism for the semantic dementia patients considered by [59]—note the absence of abnormality in BA37, within the red dashed circle in the leftmost slice. (b) A schematic of the connectionist model from [12] with versions of the model trained with decreasing levels of semantic support from left to right and red indicating the damage used to simulate surface dyslexia. The weight of the lines indicate the strength of connections developed during training, from a more semantic model on the left (blue) to a more direct model on the right (green). (c) Simulation of low-frequency exception word reading (LE) according to degree of semantic damage in this model, with blue corresponding to greater and green corresponding to lesser premorbid semantic reliance (i) and 100 observations of low-frequency exception word reading from 51 semantic dementia patients according to average of performance on picture naming and spoken word-to-picture matching (ii) from [12], with asterisks indicating outliers.
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