The Precentral Gyrus Contributions to the Early Time-Course of Grapheme-to-Phoneme Conversion

As part of silent reading models, visual orthographic information is transduced into an auditory phonological code in a process of grapheme-to-phoneme conversion (GPC). This process is often identified with lateral temporal-parietal regions associated with auditory phoneme encoding. However, the role of articulatory phonemic representations and the precentral gyrus in GPC is ambiguous. Though the precentral gyrus is implicated in many functional MRI studies of reading, it is not clear if the time course of activity in this region is consistent with the precentral gyrus being involved in GPC. We recorded cortical electrophysiology during a bimodal match/mismatch task from eight patients with perisylvian subdural electrodes to examine the time course of neural activity during a task which necessitated GPC. Patients made a match/mismatch decision between a three-letter string and the following auditory bi-phoneme. We characterized the distribution and timing of evoked broadband high gamma (BHG; 70–170 Hz) as well as phase-locking between electrodes. The precentral gyrus emerged with a high concentration of broadband high gamma responses to visual and auditory language as well as mismatch effects. The pars opercularis, supramarginal gyrus, and superior temporal gyrus were also involved. The precentral gyrus showed strong phase-locking with the caudal fusiform gyrus during letter-string presentation and with surrounding perisylvian cortex during the bimodal visual-auditory comparison period. These findings hint at a role for precentral cortex in transducing visual into auditory codes during silent reading.

Effects of iconicity in lexical decision

abstractIn contrast to arbitrariness, a recent perspective is that words contain both arbitrary and iconic aspects. We investigated iconicity in word recognition, and the possibility that iconic words have special links between phonological and semantic features that may facilitate their processing. In Experiment 1, participants completed a lexical decision task (“Is this letter string a word?”) including words varying in their iconicity. Notably, we manipulated stimulus presentation conditions such that the items were visually degraded for half of the participants; this manipulation has been shown to increase reliance on phonology. Responses to words higher in iconicity were faster and more accurate, but this did not interact with condition. In Experiment 2 we explicitly directed participants’ attention to phonology by using a phonological lexical decision task (“Does this letter string sound like a word?”). Responses to words that were higher in iconicity were once again faster. These results demonstrate facilitatory effects of iconicity in lexical processing, thus showing that the benefits of iconic mappings extend beyond those reported for language learning and those argued for language evolution.

Visual Word Recognition

Learning to read is arguably the most important aspect of a child’s schooling, and provides the key means to obtaining new knowledge into adulthood. Yet, unlike human capacity for spoken language, reading is not a universal part of human experience. Instead, reading is a relatively recent cultural invention, acquired only through years of instruction and practice. Understanding the functional mechanisms that underpin this astonishing form of expertise is a central aim of modern psycholinguistics, and has been a question of interest since the beginnings of psychology as a scientific discipline. This chapter considers how we identify a printed letter string as a unique word and compute its meaning, focusing in particular on evidence gathered from the analysis of behavior. It identifies the most important emerging questions and describes areas in which neuroscience methods may make a substantive contribution.

Why is nonword reading so variable in adult skilled readers?

When the task is reading nonwords aloud, skilled adult readers are very variable in the responses they produce: a nonword can evoke as many as 24 different responses in a group of such readers. Why is nonword reading so variable? We analysed a large database of reading responses to nonwords, which documented that two factors contribute to this variability. The first factor is variability in graphemic parsing (the parsing of a letter string into its constituent graphemes): the same nonword can be graphemically parsed in different ways by different readers. The second factor is phoneme assignment: even when all subjects produce the same graphemic parsing of a nonword, they vary in what phonemes they assign to the resulting set of graphemes. We consider the implications of these results for the computational modelling of reading, for the assessment of impairments of nonword reading, and for the study of reading aloud in other alphabetically written languages and in nonalphabetic writing systems.

Why is nonword reading so variable in adult skilled readers?

When the task is reading nonwords aloud, skilled adult readers are very variable in the responses they produce: a nonword can evoke as many as 24 different responses in a group of such readers. Why is nonword reading so variable? We analysed a large database of reading responses to nonwords, and identified two factors responsible for this variability. The first factor is variability in graphemic parsing (the parsing of a letter string into its constituent graphemes): the same nonword can be graphemically parsed in different ways by different readers. The second factor is phoneme assignment: even when all subjects produce the same graphemic parsing of a nonword, they vary in what phonemes they assign to the resulting set of graphemes. We consider the implications of these results for the computational modelling of reading, for the assessment of impairments of nonword reading, and for the study of reading aloud in other alphabetically-written languages and in nonalphabetic writing systems.

Why is nonword reading so variable in adult skilled readers?

When the task is reading nonwords aloud, skilled adult readers are very variable in the responses they produce: a nonword can evoke as many as 24 different responses in a group of such readers. Why is nonword reading so variable? We analysed a large database of reading responses to nonwords, and identified two factors responsible for this variability. The first factor is variability in graphemic parsing (the parsing of a letter string into its constituent graphemes): the same nonword can be graphemically parsed in different ways by different readers. The second factor is phoneme assignment: even when all subjects produce the same graphemic parsing of a nonword, they vary in what phonemes they assign to the resulting set of graphemes. We consider the implications of these results for the computational modelling of reading, for the assessment of impairments of nonword reading, and for the study of reading aloud in other alphabetically-written languages and in nonalphabetic writing systems.

Auditory and Visual Crossmodal Correspondences With Haptically Perceived Liquid Viscosity

Past research on crossmodal correspondences as they relate to tactile perception has largely been restricted to solid substances. We investigated the role of haptically explored liquid viscosity in crossmodal correspondences with visually presented luminance, saturation, roundedness, size, number and visual elevation, as well as pure-tone pitch and kiki–bouba-type letter strings. In Experiment 1, we presented two tactile and two visual or auditory stimuli simultaneously, and found significant inter-participant agreement () when pairing viscosity with luminance, saturation, roundedness, size, pitch and letter string type. To assess whether these crossmodal correspondences were relative or absolute, another 32 participants were presented, in Experiment 2, with two tactile stimuli but only one visual/auditory stimulus per trial. In this second experiment, we found that high viscosity was paired with low luminance, roundness, low saturation, and the bouba-type letter string, while low viscosity was paired with high pitch. However, the inverse associations (e.g. low viscosity with high luminance, high viscosity with low pitch) were not significant. These findings indicate that viscosity can be added to the list of dimensions that invoke crossmodal correspondences, and that the majority of crossmodal correspondences involving viscosity are absolute rather than relative, since they appear without explicit comparisons along the visual/auditory dimensions we measured.