Object recognition is enabled by an experience-dependent appraisal of visual features in the brain's value system.

This paper addresses perceptual synthesis by comparing responses evoked by visual stimuli before and after they are recognized, depending on prior exposure. Using magnetoencephalography, we analyzed distributed patterns of neuronal activity - evoked by Mooney figures - before and after they were recognized as meaningful objects. Recognition induced changes were first seen at 100-120 â€‹ms, for both faces and tools. These early effects - in right inferior and middle occipital regions - were characterized by an increase in power in the absence of any changes in spatial patterns of activity. Within a later 210-230 â€‹ms window, a quite different type of recognition effect appeared. Regions of the brain's value system (insula, entorhinal cortex and cingulate of the right hemisphere for faces and right orbitofrontal cortex for tools) evinced a reorganization of their neuronal activity without an overall power increase in the region. Finally, we found that during the perception of disambiguated face stimuli, a face-specific response in the right fusiform gyrus emerged at 240-290 â€‹ms, with a much greater latency than the well-known N170m component, and, crucially, followed the recognition effect in the value system regions. These results can clarify one of the most intriguing issues of perceptual synthesis, namely, how a limited set of high-level predictions, which is required to reduce the uncertainty when resolving the ill-posed inverse problem of perception, can be available before category-specific processing in visual cortex. We suggest that a subset of local spatial features serves as partial cues for a fast re-activation of object-specific appraisal by the value system. The ensuing top-down feedback from value system to visual cortex, in particular, the fusiform gyrus enables high levels of processing to form category-specific predictions. This descending influence of the value system was more prominent for faces than for tools, the fact that reflects different dependence of these categories on value-related information.

GALA: group analysis leads to accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings.

Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)-a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses.

Abnormal pre-attentive arousal in young children with autism spectrum disorder contributes to their atypical auditory behavior: an ERP study.

Auditory sensory modulation difficulties and problems with automatic re-orienting to sound are well documented in autism spectrum disorders (ASD). Abnormal preattentive arousal processes may contribute to these deficits. In this study, we investigated components of the cortical auditory evoked potential (CAEP) reflecting preattentive arousal in children with ASD and typically developing (TD) children aged 3-8 years. Pairs of clicks ('S1' and 'S2') separated by a 1 sec S1-S2 interstimulus interval (ISI) and much longer (8-10 sec) S1-S1 ISIs were presented monaurally to either the left or right ear. In TD children, the P50, P100 and N1c CAEP components were strongly influenced by temporal novelty of clicks and were much greater in response to the S1 than the S2 click. Irrespective of the stimulation side, the 'tangential' P100 component was rightward lateralized in TD children, whereas the 'radial' N1c component had higher amplitude contralaterally to the stimulated ear. Compared to the TD children, children with ASD demonstrated 1) reduced amplitude of the P100 component under the condition of temporal novelty (S1) and 2) an attenuated P100 repetition suppression effect. The abnormalities were lateralized and depended on the presentation side. They were evident in the case of the left but not the right ear stimulation. The P100 abnormalities in ASD correlated with the degree of developmental delay and with the severity of auditory sensory modulation difficulties observed in early life. The results suggest that some rightward-lateralized brain networks that are crucially important for arousal and attention re-orienting are compromised in children with ASD and that this deficit contributes to sensory modulation difficulties and possibly even other behavioral deficits in ASD.