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The processing of multisensory information is based upon the capacity of brain regions, such as the superior temporal cortex, to combine information across modalities. However, it is still unclear whether the representation of coherent auditory and visual events requires any prior audiovisual experience to develop and function. Here we measured brain synchronization during the presentation of an audiovisual, audio-only or video-only version of the same narrative in distinct groups of sensory-deprived (congenitally blind and deaf) and typically developed individuals. Intersubject correlation analysis revealed that the superior temporal cortex was synchronized across auditory and visual conditions, even in sensory-deprived individuals who lack any audiovisual experience. This synchronization was primarily mediated by low-level perceptual features, and relied on a similar modality-independent topographical organization of slow temporal dynamics. The human superior temporal cortex is naturally endowed with a functional scaffolding to yield a common representation across multisensory events.

In everyday life, the stream of affect results from the interaction between past experiences, expectations and the unfolding of events. How the brain represents the relationship between time and affect has been hardly explored, as it requires modeling the complexity of everyday life in the laboratory setting. Movies condense into hours a multitude of emotional responses, synchronized across subjects and characterized by temporal dynamics alike real-world experiences. Here, we use time-varying intersubject brain synchronization and real-time behavioral reports to test whether connectivity dynamics track changes in affect during movie watching. The results show that polarity and intensity of experiences relate to the connectivity of the default mode and control networks and converge in the right temporoparietal cortex. We validate these results in two experiments including four independent samples, two movies and alternative analysis workflows. Finally, we reveal chronotopic connectivity maps within the temporoparietal and prefrontal cortex, where adjacent areas preferentially encode affect at specific timescales.

The study of dreams represents a crucial intersection between philosophical, psychological, neuroscientific, and clinical interests. Importantly, one of the main sources of insight into dreaming activity are the (oral or written) reports provided by dreamers upon awakening from their sleep. Classically, two main types of information are commonly extracted from dream reports: structural and semantic, content-related information. Extracted structural information is typically limited to the simple count of words or sentences in a report. Instead, content analysis usually relies on quantitative scores assigned by two or more (blind) human operators through the use of predefined coding systems. Within this review, we will show that methods borrowed from the field of linguistic analysis, such as graph analysis, dictionary-based content analysis, and distributional semantics approaches, could be used to complement and, in many cases, replace classical measures and scales for the quantitative structural and semantic assessment of dream reports. Importantly, these methods allow the direct (operator-independent) extraction of quantitative information from language data, hence enabling a fully objective and reproducible analysis of conscious experiences occurring during human sleep. Most importantly, these approaches can be partially or fully automatized and may thus be easily applied to the analysis of large datasets.

SUMMARYHands are regularly in sight in everyday life. This visibility affects motor control, perception, and attention, as visual information is integrated into an internal model of sensorimotor control. Spontaneous brain activity, i.e., ongoing activity in the absence of an active task (rest), is correlated among somatomotor regions that are jointly activated during motor tasks1. Moreover, recent studies suggest that spontaneous activity patterns do not only replay at rest task activation patterns, but also maintain a model of the statistical regularities (priors) of the body and environment, which may be used to predict upcoming behavior2–4. Here we test whether spontaneous activity in the human somatomotor cortex is modulated by visual stimuli that display hands vs. non-hand stimuli, and by the use/action they represent. We analyzed activity with fMRI and multivariate pattern analysis to examine the similarity between spontaneous (rest) activity patterns and task-evoked patterns to the presentation of natural hands, robot hands, gloves, or control stimuli (food). In the left somatomotor cortex we observed a stronger (multi-voxel) spatial correlation between resting-state activity and natural hand picture patterns, as compared to other stimuli. A trend analysis showed that task-rest pattern similarity was influenced by inferred visual and motor attributes (i.e., correlation for hand>robot>glove>food). We did not observe any task-rest similarity in the visual cortex. We conclude that somatomotor brain regions code at rest for visual representations of hand stimuli and their inferred use.

Object recognition relies on different transformations of the retinal input, carried out by the visual system, that range from local contrast to object shape and category. While some of those transformations are thought to occur at specific stages of the visual hierarchy, the features they represent are correlated (e.g., object shape and identity) and selectivity for the same feature overlaps in many brain regions. This may be explained either by collinearity across representations or may instead reflect the coding of multiple dimensions by the same cortical population. Moreover, orthogonal and shared components may differently impact distinctive stages of the visual hierarchy. We recorded functional MRI activity while participants passively attended to object images and employed a statistical approach that partitioned orthogonal and shared object representations to reveal their relative impact on brain processing. Orthogonal shape representations (silhouette, curvature, and medial axis) independently explained distinct and overlapping clusters of selectivity in the occitotemporal and parietal cortex. Moreover, we show that the relevance of shared representations linearly increases moving from posterior to anterior regions. These results indicate that the visual cortex encodes shared relations between different features in a topographic fashion and that object shape is encoded along different dimensions, each representing orthogonal features.NEW & NOTEWORTHY There are several possible ways of characterizing the shape of an object. Which shape description better describes our brain responses while we passively perceive objects? Here, we employed three competing shape models to explain brain representations when viewing real objects. We found that object shape is encoded in a multidimensional fashion and thus defined by the interaction of multiple features.

In neuroimaging studies, small sample sizes and the resultant reduced statistical power to detect effects that are not large, combined with inadequate analytic choices, concur to produce inflated or false-positive findings. To mitigate these issues, researchers often restrict analyses to specific brain areas, using the region of interest (ROI) approach. Crucially, ROI analysis assumes the a priori justified definition of the target region. Nonetheless, reports often lack details about where in the timeline, ranging from study conception to the data analysis and interpretation of findings, were ROIs selected. Frequently, the rationale for ROI selection is vague or inadequately founded on the existing literature. These shortcomings have important implications for ROI-based studies, augmenting the risk that observed effects are inflated or even false positives. Tools like preregistration and registered reports could address this problem, ensuring the validity of ROI-based studies. The benefits could be enhanced by additional practices such as selection of ROIs using quantitative methods (i.e., meta-analysis) and the sharing of whole-brain unthresholded maps of effect size, as well as of binary ROIs, in publicly accessible repositories.

In brain-wide association studies (BWAS), researchers correlate behavior with the inter-individual variability in functional or structural properties of distinct brain regions. Marek, Tervo-Clemmens, and colleagues (hereinafter, M&TC) empirically assess statistical power, replication rate, type I error, sign error, and effect size inflation in BWAS using data from three large-scale neuroimaging initiatives (i.e., ABCD, Human Connectome Project - HCP -, and UK Biobank). Their results indicate that reproducible brain-behavior associations require thousands of observations. Here, leveraging synthetic and HCP data, we demonstrate that their calculations overestimate the sample size needed to detect reproducible effects by one order of magnitude.

The processing of multisensory information is based upon the capacity of brain regions, such as the superior temporal cortex, to combine information across modalities. However, it is still unclear whether the representation of coherent auditory and visual events does require any prior audiovisual experience to develop and function. In three fMRI experiments, intersubject correlation analysis measured brain synchronization during the presentation of an audiovisual, audio-only or video-only versions of the same narrative in distinct groups of sensory-deprived (congenitally blind and deaf) and typically-developed individuals. The superior temporal cortex synchronized across auditory and visual conditions, even in sensory-deprived individuals who lack any audiovisual experience. This synchronization was primarily mediated by low-level perceptual features and relied on a similar modality-independent topographical organization of temporal dynamics. The human superior temporal cortex is naturally endowed with a functional scaffolding to yield a common representation across multisensory events.

Functional Quantitative Susceptibility Mapping (fQSM) allows for the quantitative measurement of time-varying magnetic susceptibility across cortical and subcortical brain structures with a potentially higher spatial specificity than conventional fMRI. While the usefulness of fQSM with General Linear Model and “On/Off” paradigms has been assessed, little is known about the potential applications and limitations of this technique in more sophisticated experimental paradigms and analyses, such as those currently used in modern neuroimaging. To thoroughly characterize fQSM activations, here we used 7T MRI, tonotopic mapping, as well as univariate (i.e., GLM and population Receptive Field) and multivariate (Representational Similarity Analysis; RSA) analyses. Although fQSM detected less tone-responsive voxels than fMRI, they were more consistently localized in gray matter. Also, the majority of active gray matter voxels exhibited negative fQSM response, signaling the expected oxyhemoglobin increase, whereas positive fQSM activations were mainly in white matter. Though fMRI- and fQSM-based tonotopic maps were overall comparable, the representation of frequency tunings in tone-sensitive regions was significantly more balanced for fQSM. Lastly, RSA revealed that frequency information from the auditory cortex could be successfully retrieved by using either methods. Overall, fQSM produces complementary results to conventional fMRI, as it captures small-scale variations in the activation pattern which inform multivariate measures. Although positive fQSM responses deserve further investigation, they do not impair the interpretation of contrasts of interest. The quantitative nature of fQSM, its spatial specificity and the possibility to simultaneously acquire canonical fMRI support the use of this technique for longitudinal and multicentric studies and pre-surgical mapping.

EEG slow waves, the hallmarks of NREM sleep are thought to be crucial for the regulation of several important processes, including learning, sensory disconnection and the removal of brain metabolic wastes. Animal research indicates that slow waves may involve complex interactions within and between cortical and subcortical structures. Conventional EEG in humans, however, has a low spatial resolution and is unable to accurately describe changes in the activity of subcortical and deep cortical structures. To overcome these limitations, here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to slow waves of light sleep. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the posterior brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were instead found in several areas, including insula and somatomotor cortex. Specifically, a slow signal increase preceded slow-wave onset and was followed by a delayed, stronger signal decrease. Similar hemodynamic changes were found to occur at different delays across most cortical brain areas, mirroring the propagation of electrophysiological slow waves, from centro-frontal to inferior temporo-occipital cortices. Finally, we found that the amplitude of electrophysiological slow waves was positively related to the magnitude and inversely related to the delay of cortical and subcortical BOLD-signal changes. These regional patterns of brain activity are consistent with theoretical accounts of the functions of sleep slow waves.

Humans use emotions to decipher complex cascades of internal events. However, which mechanisms link descriptions of affective states to brain activity is unclear, with evidence supporting either local or distributed processing. A biologically favorable alternative is provided by the notion of gradient, which postulates the isomorphism between functional representations of stimulus features and cortical distance. Here, we use fMRI activity evoked by an emotionally charged movie and continuous ratings of the perceived emotion intensity to reveal the topographic organization of affective states. Results show that three orthogonal and spatially overlapping gradients encode the polarity, complexity and intensity of emotional experiences in right temporo-parietal territories. The spatial arrangement of these gradients allows the brain to map a variety of affective states within a single patch of cortex. As this organization resembles how sensory regions represent psychophysical properties (e.g., retinotopy), we propose emotionotopy as a principle of emotion coding., People can experience a wide variety of emotions, and how the brain represents these varying affective states is a matter of debate. Here the authors show that coding mechanisms of emotions in right temporo-parietal cortex resemble those of low-level stimulus features in primary sensory regions.

Humans typically perceive visual patterns in a global manner, and are remarkably capable of extracting object shapes based on properties such as proximity, closure, symmetry, and good continuation. Notwithstanding people’s attitude toward perceptual grouping, the research highlighted differences in disembedding performance across individuals, summarized by the field dependence/independence dimension. Previous studies revealed that age and educational attainment explain part of this variability, whereas the role of sex is still highly debated. Also, which stimulus features primarily influence inter-individual variations in perceptual grouping has to be fully determined.Building upon these premises, we assessed the role of age, level of education and sex on performance at the Leuven-Embedded Figure Test - a proxy of disembedding abilities - in a sample of 391 cisgender individuals. We also investigated whether stimulus symmetry, closure, complexity, and continuation relate to task accuracy as a function of personal characteristics.Overall, target asymmetry and continuation with the embedding context increase task difficulty, whereas target complexity demonstrates a U-shaped relationship with disembedding performance. Further, results unveil sex differences that have not been reported so far in adults and support the association between age, educational attainment, and disembedding abilities. Male individuals also benefit more from target symmetry and closure and are better at recognizing shapes when the embedding context is challenging. Lastly, highly educated adults better recognize asymmetrical and open targets, as well as shapes embedded in complex contexts. Taken together, our findings show how shape features relate to individual characteristics in explaining field independence.

Background Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions, and to properly inform the rehabilitative process. Furthermore, the design and control of mechatronic devices can also benefit from such neuroscientific outcomes, with important implications for assistive and rehabilitation robotics and advanced human-machine interaction. To reach these goals, we believe that an exhaustive data collection on human behavior is a mandatory step. For this reason, we release U-Limb, a large, multi-modal, multi-center data collection on human upper limb movements, with the aim of fostering trans-disciplinary cross-fertilization. Contribution This collection of signals consists of data from 91 able-bodied and 65 post-stroke participants and is organized at 3 levels: (i) upper limb daily living activities, during which kinematic and physiological signals (electromyography, electro-encephalography, and electrocardiography) were recorded; (ii) force-kinematic behavior during precise manipulation tasks with a haptic device; and (iii) brain activity during hand control using functional magnetic resonance imaging., GigaScience, 10 (6), ISSN:2047-217X

Botvinik-Nezer, Rotem et al., Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed., European Union’s Horizon 2020 research and innovation programme (https://ec.europa.eu/programmes/horizon2020/en) under the Marie Skłodowska-Curie grant agreement no. 665501. A. Eed was supported by a predoctoral fellowship La Caixa-Severo Ochoa from Obra Social La Caixa. S.B.E. was supported by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement no. 785907 (HBP SGA2).

EEG slow waves, the hallmarks of NREM sleep, are closely linked to the restorative function of sleep and their regional cortical distribution reflects plasticity- and learning-related processes. Here we took advantage of simultaneous EEG-fMRI recordings to map cortical and subcortical hemodynamic (BOLD) fluctuations time-locked to sleep slow waves. Recordings were performed in twenty healthy adults during an afternoon nap. Slow waves were associated with BOLD-signal increases in the brainstem and in portions of thalamus and cerebellum characterized by preferential functional connectivity with limbic and somatomotor areas, respectively. At the cortical level, significant BOLD-signal decreases were found in several areas, including insula and somatomotor cortex, and were preceded by slow signal increases that peaked around slow-wave onset. EEG slow waves and BOLD fluctuations showed similar cortical propagation patterns, from centro-frontal to temporo-occipital cortices. These regional patterns of hemodynamic-electrical coupling are consistent with theoretical accounts of the functions of sleep slow waves.

SummaryThe striate cortex is no longer considered exclusively visual in its function. Proofs that its activity is modulated by acoustic inputs have accrued. By employing category-based and feature modeling approaches, here we characterized V1 activity (in absence of retinal input) during the processing of natural and synthetically derived sounds. First, we showed that distinct sound categories could be dissociated by the analysis of V1 multivoxel response patterns. Hence, we assessed whether a hallmark of sound neural representations is mapped in V1. In each sound category, we modeled sound envelopes and assessed whether these were represented at the single-voxel level in the striate cortex and, as a control, in the temporal cortex. The hierarchical organization of sound categories allowed to exert control over dimensions that could spuriously lead to sound envelope V1 mapping. Variations of sound amplitude over time were successfully decoded in V1 regardless of the category class. Results confirm that the human striate cortex receives acoustic category-based input and demonstrate that V1 is a genuine locus of sound envelope representation.

Studies in non-human animal models have revealed that in early development, the onset of visual input gates the critical period closure of some auditory functions. The study of rare individuals whose sight was restored after a period of congenital blindness offers the rare opportunity to assess whether early visual input is a prerequisite for the full development of auditory functions in humans as well. Here, we investigated whether a few months of delayed visual onset would affect the development of Auditory Brainstem Responses (ABRs). ABRs are widely used in the clinical practice to assess both functionality and development of the subcortical auditory pathway and, provide reliable data at the individual level. We collected Auditory Brainstem Responses from two case studies, young children (both having less than 5 years of age) who experienced a transient visual deprivation since birth due to congenital bilateral dense cataracts (BC), and who acquired sight at about two months of age. As controls, we tested 41 children (sighted controls, SC) with typical development, as well as two children who were treated (at about two months of age) for congenital monocular cataracts (MC). The SC group data served to predict, at the individual level, wave latencies of each BC and MC participant. Statistics were performed both at the single subject as well as at the group levels on latencies of main ABR waves (I, III, V and SN10). Results revealed delayed response latencies for both BC children compared with the SC group starting from the wave III. Conversely, no difference emerged between MC children and the SC group. These findings suggest that in case the onset of patterned visual input is delayed, the functional development of the subcortical auditory pathway lags behind typical developmental trajectories. Ultimately results are in favor of the presence of a crossmodal sensitive period in the human subcortical auditory system.

The organization of semantic information in the brain has been mainly explored through category-based models, on the assumption that categories broadly reflect the organization of conceptual knowledge. However, the analysis of concepts as individual entities, rather than as items belonging to distinct superordinate categories, may represent a significant advancement in the comprehension of how conceptual knowledge is encoded in the human brain. Here, we studied the individual representation of thirty concrete nouns from six different categories, across different sensory modalities (i.e., auditory and visual) and groups (i.e., sighted and congenitally blind individuals) in a core hub of the semantic network, the left angular gyrus, and in its neighboring regions within the lateral parietal cortex. Four models based on either perceptual or semantic features at different levels of complexity (i.e., low- or high-level) were used to predict fMRI brain activity using representational similarity encoding analysis. When controlling for the superordinate component, high-level models based on semantic and shape information led to significant encoding accuracies in the intraparietal sulcus only. This region is involved in feature binding and combination of concepts across multiple sensory modalities, suggesting its role in high-level representation of conceptual knowledge. Moreover, when the information regarding superordinate categories is retained, a large extent of parietal cortex is engaged. This result indicates the need to control for the coarse-level categorial organization when performing studies on higher-level processes related to the retrieval of semantic information.

Object recognition relies on different transformations of the retinal input, carried out by the visual system, that range from local contrast to object shape and category. While some of those transformations are thought to occur at specific stages of the visual hierarchy, the features they represent are correlated (e.g., object shape and identity) and selectivity for the same feature overlaps in many brain regions. This may be explained either by collinearity across representations, or may instead reflect the coding of multiple dimensions by the same cortical population. Moreover, orthogonal and shared components may differently impact on distinctive stages of the visual hierarchy. We recorded functional MRI (fMRI) activity while participants passively attended to object images and employed a statistical approach that partitioned orthogonal and shared object representations to reveal their relative impact on brain processing. Orthogonal shape representations (silhouette, curvature and medial-axis) independently explained distinct and overlapping clusters of selectivity in occitotemporal (OTC) and parietal cortex. Moreover, we show that the relevance of shared representations linearly increases moving from posterior to anterior regions. These results indicate that the visual cortex encodes shared relations between different features in a topographic fashion and that object shape is encoded along different dimensions, each representing orthogonal features.New & NoteworthyThere are several possible ways of characterizing the shape of an object. Which shape description better describes our brain responses while we passively perceive objects? Here, we employed three competing shape models to explain brain representations when viewing real objects. We found that object shape is encoded in a multi-dimensional fashion and thus defined by the interaction of multiple features.

The slow waves of NREM-sleep (0.5-4Hz) reflect experience-dependent plasticity and play a direct role in the restorative functions of sleep. Importantly, slow waves behave as traveling waves and their propagation is assumed to reflect the structural properties of white matter connections. Based on this assumption, the corpus callosum (CC) may represent the main responsible for cross-hemispheric slow wave propagation. To verify this hypothesis, here we studied a group of patients who underwent total callosotomy due to drug-resistant epilepsy. Overnight high-density (hd)-EEG recordings (256 electrodes) were performed in five totally callosotomized in-patients (CP; 40-53y, 2F), in three control non-callosotomized neurological in-patients (NP; 44-66y, 2F, 1M epileptic), and in an additional sample of 24 healthy adult subjects (HS; 20-47y, 13F). Data were inspected to select NREM-sleep epochs and artefactual or non-physiological activity was rejected. Slow waves were detected using an automated algorithm and their properties and propagation patterns were computed. For each slow wave parameter and for each patient, the relative z-score and the corresponding p-value were calculated with respect to the distribution represented by the HS-group. Group differences were considered significant only when a Bonferroni corrected P < 0.05 was observed in all the CP and in none of the NP. A regression-based adjustment was used to exclude potential confounding effects of age. Slow wave density, amplitude, slope and propagation speed did not differ across CP and HS. In all CP slow waves displayed a significantly reduced probability of cross-hemispheric propagation and a stronger inter-hemispheric asymmetry. Moreover, we found that the incidence of large slow waves tended to differ across hemispheres within individual NREM epochs, with a relative predominance of the right over the left hemisphere in both CP and HS. The absolute magnitude of this inter-hemispheric difference was significantly greater in CP relative to HS. This effect did not depend on differences in slow wave origin within each hemisphere across groups. Present results indicate that the integrity of the CC is essential for the cross-hemispheric traveling of sleep slow waves, supporting the assumption of a direct relationship between white matter structural integrity and cross-hemispheric slow wave propagation. Our findings also imply a prominent role of cortico-cortical connections, rather than cortico-subcortico-cortical loops, in slow wave cross-hemispheric synchronization. Finally, this data indicate that the lack of the CC does not lead to differences in sleep depth, in terms of slow wave generation/origin, across brain hemispheres.

Classical studies have isolated a distributed network of temporal and frontal areas engaged in the neural representation of speech perception and production. With modern literature arguing against unique roles for these cortical regions, different theories have favored either neural code-sharing or cortical space-sharing, thus trying to explain the intertwined spatial and functional organization of motor and acoustic components across the fronto-temporal cortical network. In this context, the focus of attention has recently shifted toward specific model fitting, aimed at motor and/or acoustic space reconstruction in brain activity within the language network. Here, we tested a model based on acoustic properties (formants), and one based on motor properties (articulation parameters), where model-free decoding of evoked fMRI activity during perception, imagery, and production of vowels had been successful. Results revealed that phonological information organizes around formant structure during the perception of vowels; interestingly, such a model was reconstructed in a broad temporal region, outside of the primary auditory cortex, but also in the pars triangularis of the left inferior frontal gyrus. Conversely, articulatory features were not associated with brain activity in these regions. Overall, our results call for a degree of interdependence based on acoustic information, between the frontal and temporal ends of the language network.

Biological vision relies on representations of the physical world at different levels of complexity. Relevant features span from simple low-level properties, as contrast and spatial frequencies, to object-based attributes, as shape and category. However, how these features are integrated into coherent percepts is still debated. Moreover, these dimensions often share common biases: for instance, stimuli from the same category (e.g., tools) may have similar shapes. Here, using magnetoencephalography, we revealed the temporal dynamics of feature processing in human subjects attending to pictures of items pertaining to different semantic categories. By employing Relative Weights Analysis, we mitigated collinearity between model-based descriptions of stimuli and showed that low-level properties (contrast and spatial frequencies), shape (medial-axis) and category are represented within the same spatial locations early in time: 100-150ms after stimulus onset. This fast and overlapping processing may result from independent parallel computations, with categorical representation emerging later than the onset of low-level feature processing, yet before shape coding. Categorical information is represented both before and after shape also suggesting a role for this feature in the refinement of categorical matching.

One of the major challenges in visual neuroscience is represented by foreground-background segmentation. Data from nonhuman primates show that segmentation leads to two distinct, but associated processes: the enhancement of neural activity during figure processing (i.e., foreground enhancement) and the suppression of background-related activity (i.e., background suppression). To study foreground-background segmentation in ecological conditions, we introduce a novel method based on parametric modulation of low-level image properties followed by application of simple computational image-processing models. By correlating the outcome of this procedure with human fMRI activity measured during passive viewing of 334 natural images, we reconstruct easily interpretable “neural images” from seven visual areas: V1, V2, V3, V3A, V3B, V4 and LOC. Results show evidence of foreground enhancement for all tested regions, while background suppression specifically occurs in V4 and LOC. “Neural images” reconstructed from V4 and LOC revealed a preserved spatial resolution of foreground textures, indicating a richer representation of the salient part of natural images, rather than a simplistic model of object shape. Our results indicate that scene segmentation is an automatic process that occurs during natural viewing, even when individuals are not required to perform any particular task.

How the human brain represents distinct motor features into a unique finalized action still remains undefined. Previous models proposed the distinct features of a motor act to be hierarchically organized in separated, but functionally interconnected, cortical areas. Here, we hypothesized that distinct patterns across a wide expanse of cortex may actually subserve a topographically organized coding of different categories of actions that represents, at a higher cognitive level and independently from the distinct motor features, the action and its final aim as a whole. Using functional magnetic resonance imaging and pattern classification approaches on the neural responses of 14 right-handed individuals passively watching short movies of hand-performed tool-mediated, transitive, and meaningful intransitive actions, we were able to discriminate with a high accuracy and characterize the category-specific response patterns. Actions are distinctively coded in distributed and overlapping neural responses within an action-selective network, comprising frontal, parietal, lateral occipital and ventrotemporal regions. This functional organization, that we named action topography, subserves a higher-level and more abstract representation of finalized actions and has the capacity to provide unique representations for multiple categories of actions. Hum Brain Mapp 36:3832–3844, 2015. © 2015 Wiley Periodicals, Inc.

While there is ample evidence that the structure and function of visual cortical areas are affected by early visual deprivation, little is known of how early blindness modifies subcortical relay and association thalamic nuclei, as well as mesencephalic structures. Therefore, in the present multicenter study, we used MRI to measure volume of the superior and inferior colliculi, as well as of the thalamic nuclei relaying sensory and motor information to the neocortex, parcellated according to atlas-based thalamo-cortical connections, in 29 individuals with congenital blindness of peripheral origin (17 M, age 35.7 ± 14.3 years) and 29 sighted subjects (17 M, age 31.9 ± 9.0). Blind participants showed an overall volume reduction in the left (p = 0.008) and right (p = 0.007) thalami, as compared to the sighted individuals. Specifically, the lateral geniculate (i.e., primary visual thalamic relay nucleus) was 40% reduced (left: p = 4 × 10(-6), right: p1 × 10(-6)), consistent with findings from animal studies. In addition, associated thalamic nuclei that project to temporal (left: p = 0.005, right: p = 0.005), prefrontal (left: p = 0.010, right: p = 0.014), occipital (left: p = 0.005, right: p = 0.023), and right premotor (p = 0.024) cortical regions were also significantly reduced in the congenitally blind group. Conversely, volumes of the relay nuclei directly involved in auditory, motor, and somatosensory processing were not affected by visual deprivation. In contrast, no difference in volume was observed in either the superior or the inferior colliculus between the two groups. Our findings indicate that visual loss since birth leads to selective volumetric changes within diencephalic, but not mesencephalic, structures. Both changes in reciprocal cortico-thalamic connections or modifications in the intrinsic connectivity between relay and association nuclei of the thalamus may contribute to explain these alterations in thalamic volumes. Sparing of the superior colliculi is in line with their composite, multisensory projections, and with their not exclusive visual nature.