The nature of the language input affects brain activation during learning from a natural language.

Artificial language studies have demonstrated that learners are able to segment individual word-like units from running speech using the transitional probability information. However, this skill has rarely been examined in the context of natural languages, where stimulus parameters can be quite different. In this study, two groups of English-speaking learners were exposed to Norwegian sentences over the course of three fMRI scans. One group was provided with input in which transitional probabilities predicted the presence of target words in the sentences. This group quickly learned to identify the target words and fMRI data revealed an extensive and highly dynamic learning network. These results were markedly different from activation seen for a second group of participants. This group was provided with highly similar input that was modified so that word learning based on syllable co-occurrences was not possible. These participants showed a much more restricted network. The results demonstrate that the nature of the input strongly influenced the nature of the network that learners employ to learn the properties of words in a natural language.

A stereoscopic system for viewing the temporal evolution of brain activity clusters in response to linguistic stimuli.

In this paper, we present a novel application, 3D+Time Brain View, for the stereoscopic visualization of functional Magnetic Resonance Imaging (fMRI) data gathered from participants exposed to unfamiliar spoken languages. An analysis technique based on Independent Component Analysis (ICA) is used to identify statistically significant clusters of brain activity and their changes over time during different testing sessions. That is, our system illustrates the temporal evolution of participants' brain activity as they are introduced to a foreign language through displaying these clusters as they change over time. The raw fMRI data is presented as a stereoscopic pair in an immersive environment utilizing passive stereo rendering. The clusters are presented using a ray casting technique for volume rendering. Our system incorporates the temporal information and the results of the ICA into the stereoscopic 3D rendering, making it easier for domain experts to explore and analyze the data.

Modulating the focus of attention for spoken words at encoding affects frontoparietal activation for incidental verbal memory.

Attention is crucial for encoding information into memory, and current dual-process models seek to explain the roles of attention in both recollection memory and incidental-perceptual memory processes. The present study combined an incidental memory paradigm with event-related functional MRI to examine the effect of attention at encoding on the subsequent neural activation associated with unintended perceptual memory for spoken words. At encoding, we systematically varied attention levels as listeners heard a list of single English nouns. We then presented these words again in the context of a recognition task and assessed the effect of modulating attention at encoding on the BOLD responses to words that were either attended strongly, weakly, or not heard previously. MRI revealed activity in right-lateralized inferior parietal and prefrontal regions, and positive BOLD signals varied with the relative level of attention present at encoding. Temporal analysis of hemodynamic responses further showed that the time course of BOLD activity was modulated differentially by unintentionally encoded words compared to novel items. Our findings largely support current models of memory consolidation and retrieval, but they also provide fresh evidence for hemispheric differences and functional subdivisions in right frontoparietal attention networks that help shape auditory episodic recall.

Neural substrates of attentive listening assessed with a novel auditory Stroop task.

A common explanation for the interference effect in the classic visual Stroop test is that reading a word (the more automatic semantic response) must be suppressed in favor of naming the text color (the slower sensory response). Neuroimaging studies also consistently report anterior cingulate/medial frontal, lateral prefrontal, and anterior insular structures as key components of a network for Stroop-conflict processing. It remains unclear, however, whether automatic processing of semantic information can explain the interference effect in other variants of the Stroop test. It also is not known if these frontal regions serve a specific role in visual Stroop conflict, or instead play a more universal role as components of a more generalized, supramodal executive-control network for conflict processing. To address these questions, we developed a novel auditory Stroop test in which the relative dominance of semantic and sensory feature processing is reversed. Listeners were asked to focus either on voice gender (a more automatic sensory discrimination task) or on the gender meaning of the word (a less automatic semantic task) while ignoring the conflicting stimulus feature. An auditory Stroop effect was observed when voice features replaced semantic content as the "to-be-ignored" component of the incongruent stimulus. Also, in sharp contrast to previous Stroop studies, neural responses to incongruent stimuli studied with functional magnetic resonance imaging revealed greater recruitment of conflict loci when selective attention was focused on gender meaning (semantic task) over voice gender (sensory task). Furthermore, in contrast to earlier Stroop studies that implicated dorsomedial cortex in visual conflict processing, interference-related activation in both of our auditory tasks was localized ventrally in medial frontal areas, suggesting a dorsal-to-ventral separation of function in medial frontal cortex that is sensitive to stimulus context.