For the same reason, timing has important implications for studies on clinical populations. The functional interpretation of brain activation crucially depends on timing information. If we want to constrain a model of lexical access, for example, we need to know whether the signal we are analyzing reflects brain processes of lexical access itself, or follow-up processes related to decision making. Why should one care much about timing? Electrophysiological data are increasingly relevant for computational models of word recognition and other cognitive processes ( Barber and Kutas, 2007 Braun et al., 2006 Garagnani et al., 2008 Philiastides et al., 2006). We here use a multi-modal approach consisting of fast behavioral, ERP and combined EEG/MEG data to provide converging evidence for a time-line of word recognition. But despite decades of research, even the basic questions “How early is the brain sensitive to lexical and semantic information?” or “Are lexical and semantic information retrieved at the same time, or at different stages?” are yet unanswered. Behavioral and electrophysiological measures both provide timing information. Metabolic neuroimaging methods (such as functional magnetic resonance imaging, fMRI) have inherently limited time resolution, and cannot answer questions about absolute or relative timing of brain processes. In natural reading, our brain has to rapidly 1) identify symbols (letters and words) that share many features with a large set of orthographic competitors 2) link these symbols to representations of meaning (semantics) which are complex and shaped by years of learning and experience 3) integrate information from a continuous flow of these symbols into concepts and messages. Many authors have highlighted the remarkable speed and ease with which skilled readers can recognize printed words.

Reading is a skill that appears effortless and automatic to most of us.

Our results support models of word recognition that assume a continuous accumulation of task-related information from the stimulus, which might be described by Bayesian principles. Thus, behavior and brain responses provide coherent evidence that the brain starts retrieving lexical and semantic information near-simultaneously within 200 ms of word onset. Distributed source analysis of combined EEG/MEG data estimated neuronal generators for the lexicality effect around 200 ms in the left anterior middle temporal lobe. The earliest ERP differences between Go and NoGo conditions occurred around 160 ms for both LD and SD. Ex-Gaussian analysis of behavioral responses did not reveal reliable differences between LD and SD. We found that the earliest behavioral responses distinguishing stimulus categories can occur around 310 ms. We introduced eye-blink latencies as a dependent variable, in order to measure behavioral responses that are faster and less variable than traditional button presses. Participants performed lexical and semantic decisions (LD, SD) in a Go/NoGo paradigm. In our multimodal approach – combining fast behavioral measures, ERPs and EEG/MEG source estimation – we provide converging evidence for the latencies of earliest lexical and semantic information retrieval in visual word recognition. An integration of multiple sources of information would lead to more strongly constrained theoretical models, and help finding optimal measures when monitoring specific aspects of word recognition impairments in patient groups. Different domains of research have still not converged on a coherent account. However, even basic aspects of the time-line of word recognition are still controversial. We usually feel that we understand a familiar word “immediately”.

Analyze quick word