New insights into name category-related effects: is the Age of Acquisition a possible factor?

Abstract

Background: Electrophysiological, hemodynamic and neuropsychological studies have provided evidence of dissociation in the way words belonging to different semantic categories (e.g., animals, tools, actions) are represented in the brain. The aim of the present study was to investigate whether a word's semantic domain may affect the amplitude and latency of ERP components, independently of any other factor.

Methods: EEGs were recorded from 16 volunteers engaged in a lexical decision task (word/non-word discrimination) involving 100 words (flora and fauna names). This task allowed us to evaluate differences in processing between words belonging to different categories (fauna vs. flora) independently of task demands. All stimuli were balanced in terms of length, frequency of occurrence, familiarity and imageability. Low Resolution Electromagnetic Tomography (LORETA) was performed on ERP difference waves of interest.

Results: Our findings showed that the two categories were discriminated as early as 200 ms post-stimulus, with larger responses to flora names over the left occipito-temporal areas, namely BA37 and BA20. Category-related ERP differences were also observed in the amplitudes of the later centro-parietal N400, posterior P300 and anterior LP components. Behavioral responses to words denoting fauna were more accurate than to words denoting flora.

Conclusion: Overall, it seems that it was easier to access the lexical properties of fauna, probably because of their biologically relevant status. The results are discussed in the light of the possible role played by different factors.

Figure 1

Illustration of experimental procedure, with indication of stimulus duration (in ms) and inter-stimulus interval.

Figure 2

Grand-average ERP waveforms recorded at fronto-central, centro-parietal, occipito-temporal and occipito-lateral sites in response to flora and fauna. The arrows indicate the ERP components considered in this study.

Figure 3

Back view of topographical distribution of voltage obtained in response to fauna names and in response to flora names during the 170–220 ms post-stimulus interval.

Figure 4

Source localization relative to difference voltage obtained by subtracting grand-average ERPs to fauna names from ERPs to flora names (flora – fauna) during the 170–220 ms post-stimulus interval. The solution showed a strong source of activation located in the left inferior temporal gyrus (BA37 and BA20). Grid spacing = 5 mm; Tikhonov regularization: estimated SNR = 3; Power RMS = 17.8 μV.

Figure 5

Source localization relative to difference voltage obtained by subtracting grand-average ERPs to flora names from ERPs to fauna names (fauna – flora) during the 470–530 ms post-stimulus interval. The solution showed strong activation of the occipito-temporal regions of the right hemisphere. The Figure shows dipoles located in the fusiform gyrus (BA20), parahippocampal gyrus (BA28) and middle temporal gyrus (BA21). Grid spacing = 5 mm; Tikhonov regularization: estimated SNR = 3; Power RMS = 34.1 μV.