The overall goal of this project is to better understand the brain basis of word recognition as it unfolds in both space and time. Accomplishing this will require fulfilling the training goal of supplementing the applicant's existing expertise in functional magnetic resonance imaging (fMRI) with new skills in magnetoencephalography (MEG). Word recognition is known to involve integration of orthographic (visual form), phonological (sound form), and semantic (meaning) information. What is not known is the degree to which this information is accessed sequentially or in parallel, the precise contribution of different brain areas to these distinct processes, or the exact order in which brain areas are engaged to support them. A detailed understand of this complex neural system is critical for understanding reading acquisition and developmental language disorders such as dyslexia, for which deficits in orthographic, phonological, and semantic processing can arise in various parts of the brain at various times. The methods used for investigating the neural basis of word recognition are generally optimized for measuring activity across either space (e.g., with fMRI) or time (e.g., with event-related potentials, ERP). Recently, MEG methods have advanced to the point where they can provide good spatial resolution, approaching but not equivalent to that of fMRI, while also yielding very high temporal resolution equivalent to that obtained with ERP. Studies integrating temporal and spatial results should, for example, help distinguish between automatic and controlled processing of orthography, phonology, and semantics. Starting from a neural model of word recognition with predictions about the spatial distribution of brain activation across time, we propose experiments to test the predictions according to three Specific Aims: (1) Specify the location and timecourse of semantic processing (mentored phase), (2) specify the location and timecourse of orthographic processing, and (3) specify the location and timecourse of phonological processing. Accomplishing these aims will lead to a more complete account of how, where, and when brain systems act to accomplish word recognition. The scientific knowledge gained is expected to be directly relevant to developmental and acquired reading disorders.

Public Health Relevance

The overall goal of this project is to better understand the brain basis of word recognition as it unfolds in both space and time. Recognizing words is fundamental to reading, and in modern society reading disorders such as dyslexia can have a severe negative impact on quality of life. One could imagine ultimately translating knowledge about what brain areas for reading are activated when into a brain-imaging based indicator for whether a particular therapy for dyslexia is producing only strategy-based (later, controlled) changes, or whether its effects have translated into changes in early automatic processing, indicating possible long-term benefits.

National Institute of Health (NIH)
Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
Career Transition Award (K99)
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Pediatrics Subcommittee (CHHD)
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Miller, Brett
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Medical College of Wisconsin
Schools of Medicine
United States
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Graves, William W; Boukrina, Olga; Mattheiss, Samantha R et al. (2017) Reversing the Standard Neural Signature of the Word-Nonword Distinction. J Cogn Neurosci 29:79-94
Mattheiss, Samantha R; Alexander, Edward J; Graves, William W (2017) Elaborative feedback: Engaging reward and task-relevant brain regions promotes learning in pseudoword reading aloud. Cogn Affect Behav Neurosci :
Binder, Jeffrey R; Pillay, Sara B; Humphries, Colin J et al. (2016) Surface errors without semantic impairment in acquired dyslexia: a voxel-based lesion-symptom mapping study. Brain 139:1517-26
Graves, William W; Binder, Jeffrey R; Desai, Rutvik H et al. (2014) Anatomy is strategy: skilled reading differences associated with structural connectivity differences in the reading network. Brain Lang 133:1-13
Boukrina, Olga; Graves, William W (2013) Neural networks underlying contributions from semantics in reading aloud. Front Hum Neurosci 7:518
Graves, William W; Binder, Jeffrey R; Seidenberg, Mark S (2013) Noun-noun combination: meaningfulness ratings and lexical statistics for 2,160 word pairs. Behav Res Methods 45:463-9