Speed of lexical decision correlates with diffusion anisotropy in left parietal and frontal white matter: Evidence from diffusion tensor imaging

https://doi.org/10.1016/j.neuropsychologia.2007.04.011Get rights and content

Abstract

Speed of visual word recognition is an important variable affecting linguistic competence. Although speed of visual word recognition varies widely between individuals, the neural basis of reaction time (RT) differences is poorly understood. Recently, a magnetic resonance technique called diffusion tensor imaging (DTI) has been shown to provide information about white matter (WM) microstructure in vivo. Here, we used DTI to explore whether visual word recognition RT correlates with regional fractional anisotropy (FA) values in the WM of healthy young adults. Participants completed a speeded lexical decision task that involved visual input, linguistic processes, and a motor response output. Results indicated that lexical decision RT was correlated negatively with FA in WM of inferior parietal and frontal language regions rather than in WM of visual or motor regions. Voxels within the inferior parietal and frontal correlation clusters were composed primarily of DTI-based tracts oriented in the anterior–posterior orientation at or near the superior longitudinal fasciculus (SLF) and likely including other smaller association fibers. These results provide new microstructural evidence demonstrating that speed of lexical decision is associated with the degree to which portions of frontal and parietal WM are directionally oriented.

Introduction

Visual word recognition involves the ability to distinguish strings of letters that have a lexical status from those that do not. The ability for rapid visual word recognition contributes to reading ability and comprehension of written language (Perfetti, 1994). By contrast, delayed speed of word recognition contributes to developmental reading disorders (Sigmundsson, 2005), and is a common symptom of language-related degenerative brain disorders (Gold et al., 2005; Plaut, McClelland, Seidenberg, & Patterson, 1996). Not surprisingly, then, psycholinguistic variables influencing speed of visual word recognition have been studied for over 100 years (Catell, 1890). In research settings, this skill is usually explored via the speeded visual lexical decision task, in which participants decide as quickly and accurately as possible whether visual letter strings represent words or nonwords. Results from studies using the visual lexical decision task have been influential in the development of models of visual word recognition (Coltheart, Rastle, Perry, Langdon, & Ziegler, 2001; McClelland & Rumelhart, 1981), and mapping the neural correlates of visual word recognition processes (Binder et al., 2003, Heim et al., 2005, Rumsey et al., 1997).

The most common dependent variable explored in visual lexical decision is reaction time (RT). Although most young healthy adults score near ceiling on lexical decision tasks, speed of visual word recognition varies widely across different individuals (Balota, Cortese, Sergent-Marshall, Spieler, & Yap, 2004). There is evidence that cognitive RTs may be in part heritable (Ho, Baker, & Decker, 1988; Posthuma, Mulder, Boomsma, & de Geus, 2002). However, the neural basis of RT differences is poorly understood. This may be due in part to the fact that, until recently, no technique existed for the measurement of microstructural properties of cerebral white matter (WM) in vivo. A long-standing hypothesis is that cognitive RT depends on microstructural properties of cerebral WM, such as degree of myelination (Flechsig, 1920). Increased myelination may promote faster nerve conduction velocity which could promote faster RT (Jack, Noble, & Tsien, 1983).

Recently, a magnetic resonance technique called diffusion tensor imaging (DTI) has been shown to provide information about WM microstructure in vivo. DTI provides a voxel-by-voxel estimate of both the degree and orientation of directionality along which water molecules move preferentially. The degree to which molecular displacements are directionally dependent is referred to as fractional anisotropy (FA). The FA measure ranges from 0, representing diffusion that is equal in all directions, to 1, representing diffusion that occurs exclusively along one direction. The FA measure varies systematically across different compartments of the brain. For example, FA is low in the ventricles, where water movement is relatively unconstrained and thus isotropic. In contrast, FA is relatively high in cerebral WM, because the highly organized structure of WM fiber tracts causes water diffusion to be anisotropic, or unequal across different directions (Catani, 2006; Basser, Mattiello, & Le Bihan, 1994a; Basser, Pajevic, Pierpaoli, Duda, & Aldroubi, 2000; Le Bihan, 2003).

The biological variables contributing to diffusion anisotropy in WM have not been fully identified but include the degree of myelination, and the density and orientation coherence of axons (reviewed in Beaulieu, 2002). For example, histological studies have demonstrated that myelination of axons increases anisotropy (Wimberger et al., 1995) and demyelination of axons decreases anisotropy (Werring, Clark, Barker, Thomson, & Miller, 1999). Consequently, the FA measure is highest in cerebral WM structures that contain the largest numbers of myelinated fibers running in parallel, such as the corpus callosum (Shimony et al., 1999). The established relationship between degree of myelination and speed of nerve conduction velocity (Jack et al., 1983) raises the possibility that increased FA in specific WM regions may be associated with behavioral RT. In fact, several studies have reported a relationship between regional FA and behavioral RT in healthy young adults associated with an oddball task (Madden et al., 2004) and a visuospatial task (Tuch et al., 2005).

The aim of the present study was to determine if speed of visual word recognition correlates with regional FA in WM of young healthy adults. If so, WM correlation clusters may be composed of DTI-based tracts oriented primarily toward adjacent cortex, overlying cortex, or each other. In the present study, these different possibilities were explored by correlating healthy young adults’ lexical decision RT with their regional cerebral FA values, and exploring the orientation of axons within RT–FA correlation clusters. Results provide new evidence for a relationship between speed of visual word recognition and FA in left inferior frontal and parietal WM.

Section snippets

Participants

Sixteen young healthy volunteers (9 females; mean age = 24, S.D. = 5; mean years of education = 14.4, S.D. = 2.2) participated. All participants provided written informed consent in a manner approved by the University of Kentucky Institutional Review Board and were paid for participating. All participants were right-handed, as assessed by the Edinburg Handedness Inventory, native English speakers, who reported no neurological disease, and had normal or corrected-to-normal visual acuity.

Behavioral procedures

Participants

Behavioral

Mean accuracy was near ceiling for both word (M = 96.2%; S.D. = 2.7) and nonword trials (M = 92.4%; S.D. = 3.2). The minimal variance found between participants’ mean accuracies precluded correlation of accuracy with FA. In contrast, substantial variance was found between participants’ mean reaction times (RTs) for correct word (M = 574 ms; S.D. = 73) and nonword (M = 644 ms; S.D. = 77) trials.

Imaging

The first voxel-wise, whole-brain analysis sought to determine if lexical decision RT (averaged across correct word and

Discussion

The present study sought to determine if speed of visual word recognition correlates with microstructural properties of cerebral white matter (WM). Participants performed a visual lexical decision task and diffusion tensor images were acquired subsequently to correlate reaction time (RT) with fractional anisotropy (FA). Voxel-wise, whole-brain analyses indicated a negative correlation between lexical decision RT and FA in two left hemisphere WM regions. Individuals with relatively fast lexical

Acknowledgments

This research was supported by National Institutes of Health grants DC007315 and P50 AG05144-21. The authors thank Drs. Anders Andersen and Charles Smith for helpful discussions.

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