Cortex; a journal devoted to the study of the nervous system and behavior
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Face pareidolia is the illusory perception of non-existent faces. The present study, for the first time, contrasted behavioral and neural responses of face pareidolia with those of letter pareidolia to explore face-specific behavioral and neural responses during illusory face processing. Participants were shown pure-noise images but were led to believe that 50% of them contained either faces or letters; they reported seeing faces or letters illusorily 34% and 38% of the time, respectively. ⋯ This finding suggests that the rFFA plays a specific role not only in processing of real faces but also in illusory face perception, perhaps serving to facilitate the interaction between bottom-up information from the primary visual cortex and top-down signals from the prefrontal cortex (PFC). Whole brain analyses revealed a network specialized in face pareidolia, including both the frontal and occipitotemporal regions. Our findings suggest that human face processing has a strong top-down component whereby sensory input with even the slightest suggestion of a face can result in the interpretation of a face.
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Speech signals are often compromised by disruptions originating from external (e.g., masking noise) or internal (e.g., inaccurate articulation) sources. Speech comprehension thus entails detecting and replacing missing information based on predictive and restorative neural mechanisms. The present study targets predictive mechanisms by investigating the influence of a speech segment's predictability on early, modality-specific electrophysiological responses to this segment's omission. ⋯ Suggestive of a general auditory predictive mechanism at work, this main observation was robust against varying source of predictive information or attentional allocation, differing between the two experiments. Source localization further suggested the omission response enhancement by predictability to emerge from left superior temporal gyrus and left angular gyrus in both experiments, with additional experiment-specific contributions. These results are consistent with the existence of predictive coding mechanisms in the central auditory system, and suggestive of the general predictive properties of the auditory system to support spoken word recognition.
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Amyotrophic Lateral Sclerosis (ALS) is associated in about half of the cases with behavioral and cognitive disorders, including impairments in socio-emotional processing, considered as key-features for the diagnosis of the behavioral variant of frontotemporal dementia (bv-FTD). The neurostructural bases of emotional deficits in ALS, however, still remain largely unexplored. Here we aim to assess emotion recognition in non-demented sporadic ALS patients compared with healthy controls, and to explore for the first time its microstructural white-matter correlates. ⋯ Moreover, the Diffusion Tensor Imaging analyses revealed a correlation between this impairment and the alteration of white-matter integrity along the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus. Our findings indicate the presence of an early emotion recognition deficit in non-demented sporadic ALS patients, associated with microstructural changes in ventral associative bundles connecting occipital, temporo-limbic and orbitofrontal regions in the right hemisphere. These changes may represent a frontotemporal-limbic microstructural marker of socio-emotional impairment in ALS.
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In healthy conditions, group-level fMRI resting state analyses identify ten resting state networks (RSNs) of cognitive relevance. Here, we aim to assess the ten-network model in severely brain-injured patients suffering from disorders of consciousness and to identify those networks which will be most relevant to discriminate between patients and healthy subjects. ⋯ FMRI multiple-network resting state connectivity is disrupted in severely brain-injured patients suffering from disorders of consciousness. When performing ICA, multiple-network testing and control for neuronal properties of the identified RSNs can advance fMRI system-level characterization. Automatic data-driven patient classification is the first step towards future single-subject objective diagnostics based on fMRI resting state acquisitions.
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Traumatic brain injury (TBI) is associated with neuronal loss, diffuse axonal injury and executive dysfunction. Whereas executive dysfunction has traditionally been associated with prefrontal lesions, ample evidence suggests that those functions requiring behavioral flexibility critically depend on the interaction between frontal cortex, basal ganglia and thalamus. To test whether structural integrity of this fronto-striato-thalamic circuit can account for executive impairments in TBI we automatically segmented the thalamus, putamen and caudate of 25 patients and 21 healthy controls and obtained diffusion weighted images. ⋯ Global volume of the nuclei showed no clear relationship with task performance. However, the shape analysis revealed that participants with smaller volume of those subregions that have connections with the prefrontal cortex and rostral motor areas showed higher switch costs and mixing costs, and made more errors while switching. These results support the idea that flexible cognitive control over action depends on interactions within the fronto-striato-thalamic circuit.