Subjects in children’s object relatives in Italian

We first review the results from a number of experiments with Italian children and adults presented in previous work (Belletti and Contemori, 2010; Contemori & Belletti, submitted), investigating the production of Subject (SRs) and Object relative clauses (ORs). We confirm passive as the preferred strategy adopted by children from age 5 when ORs are elicited in the production experiments. We then investigate further aspects of children's results that we had not previously addressed in detail. First, we analyse the ORs produced by children, focusing on the nature (overt/null) and position (pre/post-verbal) of the subject within the relative clause. Furthermore, we explore the emergence of passive and the decrease of ORs with postverbal subjects observed at age 5 as two related phenomena. Finally, we present results from a new preference production task which indicate that post-verbal subjects are preferably adopted by children in a felicitous way given the discourse pragmatics of the design. Null subjects are also produced in an adequate way. In the conditions adopted in which the subject of the relative clause is (1st or 3rd person) pronominal (active), ORs appear to be relatively easily produced by both younger and older children. We discuss the comparison of these new results with the previous ones and their relevance for the adopted featural approach to locality along the lines of Friedmann, Belletti, Rizzi (2009)

Relatives and passive object relatives in Italian-speaking children and adults: Intervention in production and comprehension

We investigate the production of relative clauses in Italian children aged 3 years, 4 months to 8 years, 10 months and in adults, focusing on object relatives (ORs). For both adults and older children, we test the production of passive ORs (PORs) as an alternative to the production of active ORs. We also test the comprehension of active ORs and PORs in older children, showing that the comprehension of the latter is significantly more accurate than the former. The persistent difficulty that children experience with ORs is interpreted as due to intervention, following Friedmann, Belletti, and Rizzi (2009). We assume Collins’ (2005) approach to passive and account for the increasing use and more accurate comprehension of PORs as a consequence of lack of intervention, as in Belletti (2009a)

Probing the effect of the expected-speed violation illusion

Motion perception is complex for the brain to process, involving interacting computations of distance, time, and speed. These computations can be biased by the context and the features of the perceived moving object, giving rise to several types of motion illusions. Recent research has shown that, in addition to object features and context, lifelong priors can bias attributes of perception. In the present work, we investigated if such long acquired expectations can bias speed perception. Using a two-interval forced-choice (2-IFC) task, we asked 160 participants in different experiments to judge which of two vehicles, one archetypically fast (e.g. a motorbike), and one comparatively slower (e.g. a bike), was faster. By varying the objective speeds of the two-vehicle types, and measuring the participants\u2019 point of subjective equality, we observed a consistent bias in participants\u2019 speed perception. Counterintuitively, in the first three experiments the speed of an archetypically slow vehicle had to be decreased relative to that of an archetypically fast vehicle, for the two to be judged as the same. Similarly, in the next three experiments, an archetypically fast vehicle\u2019s speed had to be increased relative to an archetypically slow vehicle\u2019s speed, for the two to be perceived as equal. Four additional control experiments replicated our results. We define this newly found bias as the expected-speed violation illusion (ESVI). We believe the ESVI as conceptually very similar to the size-weight illusion, and discuss it within the Bayesian framework of human perception

Perceptual learning improves contrast sensitivity, visual acuity, and foveal crowding in amblyopia

none5noBackground: Amblyopic observers present abnormal spatial interactions between a low-contrast sinusoidal target and highcontrast collinear flankers. It has been demonstrated that perceptual learning (PL) can modulate these low-level lateral interactions, resulting in improved visual acuity and contrast sensitivity. Objective: We measured the extent and duration of generalization effects to various spatial tasks (i.e., visual acuity, Vernier acuity, and foveal crowding) through PL on the target's contrast detection. Methods: Amblyopic observers were trained on a contrast-detection task for a central target (i.e., a Gabor patch) flanked above and belowby two high-contrast Gabor patches. The pre- and post-learning tasks included lateral interactions at different target-to-flankers separations (i.e., 2, 3, 4, 8λ) and included a range of spatial frequencies and stimulus durations as well as visual acuity, Vernier acuity, contrast-sensitivity function, and foveal crowding. Results: The results showed that perceptual training reduced the target's contrast-detection thresholds more for the longest target-to-flanker separation (i.e., 8λ).We also found generalization of PL to different stimuli and tasks: contrast sensitivity for both trained and untrained spatial frequencies, visual acuity for Sloan letters, and foveal crowding, and partially for Vernier acuity. Follow-ups after 5-7 months showed not only complete maintenance of PL effects on visual acuity and contrast sensitivity function but also further improvement in these tasks. Conclusion: These results suggest that PL improves facilitatory lateral interactions in amblyopic observers, which usually extend over larger separations than in typical foveal vision. The improvement in these basic visual spatial operations leads to a more efficient capability of performing spatial tasks involving high levels of visual processing, possibly due to the refinement of bottom-up and top-down networks of visual areas.noneBarollo M.; Contemori G.; Battaglini L.; Pavan A.; Casco C.Barollo M.; Contemori G.; Battaglini L.; Pavan A.; Casco C