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Soto-Faraco, S.

Publications and source records attributed to Soto-Faraco, S..

2 recordsLinked to original sources

Integrating When and What Information in the Left Parietal Lobe Allows Language Rule Generalization

A crucial aspect when learning a language is discovering the rules that govern how words are combined in order to convey meanings. Since rules are characterized by sequential co-occurrences between elements (e.g. These cupcakes are unbelievable), tracking the statistical relationships between these elements is fundamental. However, statistical learning alone cannot fully account for the ability to create abstract rule representations that can be generalized, a paramount requirement of linguistic rules. Here, we provide evidence that, after the statistical relations between words have been extracted, the engagement of goal-directed attention is key to enable rule generalization. Incidental learning performance during a rule-learning task on an artificial language revealed a progressive shift from statistical learning to goal-directed attention. In addition, and consistent with the recruitment of attention, fMRI analyses of late learning stages showed left parietal activity within a broad bilateral dorsal fronto-parietal network. Critically, rTMS on participants peak of activation within the left parietal cortex impaired their ability to generalize learned rules to a structurally analogous new language. No stimulation or rTMS on a non-relevant brain region did not have the same interfering effect on generalization. Performance on an additional attentional task showed that rTMS on the same parietal site hindered participants ability to integrate what (stimulus identity) and when (stimulus timing) information about an expected target. The present findings suggest that learning rules from speech is a two-stage process: following statistical learning, goal-directed attention -involving left parietal regions- integrates what and when stimulus information to facilitate rapid rule generalization.

neuroscience

Characteristic sounds facilitate object search in real-life scenes

Real-world multisensory events do not only provide temporally and spatially correlated information, but also semantic correspondences about object identity. Semantically consistent sounds can enhance visual detection, identification and search performance, but these effects are always demonstrated in simple and stereotyped displays that lack ecological validity. In order to address identity-based crossmodal relationships in real world scenarios, we designed a visual search task using complex, dynamic scenes. Participants searched objects in video clips from real life scenes with background sounds. Auditory cues embedded in the background sounds could be target-consistent, distracter-consistent, neutral and no sound (just background noise). We found that characteristic sounds enhance visual search of relevant objects in natural scenes but fail to increase the salience of irrelevant distracters. Our findings generalize previous results on object-based crossmodal interactions with simple stimuli and shed light upon how audio-visual semantically congruent relationships play out in real life contexts.

neuroscience