Similar object shape representation encoded in the inferolateral occipitotemporal cortex of sighted and early blind people.

We can sense an object's shape by vision or touch. Previous studies suggested that the inferolateral occipitotemporal cortex (ILOTC) implements supramodal shape representations as it responds more to seeing or touching objects than shapeless textures. However, such activation in the anterior portion of the ventral visual pathway could be due to the conceptual representation of an object or visual imagery triggered by touching an object. We addressed these possibilities by directly comparing shape and conceptual representations of objects in early blind (who lack visual experience/imagery) and sighted participants. We found that bilateral ILOTC in both groups showed stronger activation during a shape verification task than during a conceptual verification task made on the names of the same manmade objects. Moreover, the distributed activity in the ILOTC encoded shape similarity but not conceptual association among objects. Besides the ILOTC, we also found shape representation in both groups' bilateral ventral premotor cortices and intraparietal sulcus (IPS), a frontoparietal circuit relating to object grasping and haptic processing. In contrast, the conceptual verification task activated both groups' left perisylvian brain network relating to language processing and, interestingly, the cuneus in early blind participants only. The ILOTC had stronger functional connectivity to the frontoparietal circuit than to the left perisylvian network, forming a modular structure specialized in shape representation. Our results conclusively support that the ILOTC selectively implements shape representation independently of visual experience, and this unique functionality likely comes from its privileged connection to the frontoparietal haptic circuit.

OsmiR5519 regulates grain size and weight and down-regulates sucrose synthase gene RSUS2 in rice (Oryza sativa L.).

MAIN CONCLUSION: The up-regulation of OsmiR5519 results in the decrease of grain size, weight and seed setting rate. OsmiR5519 plays important roles in the process of grain filling and down-regulates sucrose synthase gene RSUS2. MicroRNAs (miRNAs) are one class of small non-coding RNAs that act as crucial regulators of plant growth and development. In rice, the conserved miRNAs were revealed to regulate the yield components, but the function of rice-specific miRNAs has been rarely studied. The rice-specific OsmiR5519 was found to be abundantly expressed during reproductive development, but its biological roles remain unknown. In this study, the function of rice-specific OsmiR5519 was characterized with the miR5519-overexpressing line (miR5519-OE) and miR5519-silenced line (STTM5519). At seedling stage, the content of sucrose, glucose and fructose was obviously lower in the leaves of miR5519-OE lines than those of wild-type (WT) line. The grain size and weight were decreased significantly in miR5519-OE lines, compared to those of WT rice. The cell width of hull in miR5519-OE was smaller than that in WT. The seed setting rate was notably reduced in miR5519-OE lines, but not in STTM5519 lines. Cytological observation demonstrated that the inadequate grain filling was the main reason for the decline of seed setting rate in miR5519-OE lines. The percentage of the defects of grain amounted to 40% in miR5519-OE lines, which almost equaled to the decreased value of seed setting rate. Furthermore, the sucrose synthase gene RSUS2 was identified as a target of OsmiR5519 via RNA ligase-mediated 3'-amplification of cDNA ends (3'-RLM-RACE), dual luciferase assays and transient expression assays. In summary, our results suggest that OsmiR5519 regulates grain size and weight and down-regulates RSUS2 in rice.

Dynamic network reorganization underlying neuroplasticity: the deficits-severity-related language network dynamics in patients with left hemispheric gliomas involving language network.

Brain network dynamics not only endow the brain with flexible coordination for various cognitive processes but also with a huge potential of neuroplasticity for development, skill learning, and after cerebral injury. Diffusive and progressive glioma infiltration triggers the neuroplasticity for functional compensation, which is an outstanding pathophysiological model for the investigation of network reorganization underlying neuroplasticity. In this study, we employed dynamic conditional correlation to construct framewise language networks and investigated dynamic reorganizations in 83 patients with left hemispheric gliomas involving language networks (40 patients without aphasia and 43 patients with aphasia). We found that, in healthy controls (HCs) and patients, the language network dynamics in resting state clustered into 4 temporal-reoccurring states. Language deficits-severity-dependent topological abnormalities of dFCs were observed. Compared with HCs, suboptimal language network dynamics were observed for those patients without aphasia, while more severe network disruptions were observed for those patients with aphasia. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the 4 states significantly predicted individual patients' language scores. These findings shed light on our understanding of metaplasticity in glioma. Glioma-induced language network reorganizations were investigated under a dynamic "meta-networking" (network of networks) framework. In healthy controls and patients with glioma, the framewise language network dynamics in resting-state robustly clustered into 4 temporal-reoccurring states. The spatial but not temporal language deficits-severity-dependent abnormalities of dFCs were observed in patients with left hemispheric gliomas involving language network. Language network dynamics significantly predicted individual patients' language scores.

The domain-separation language network dynamics in resting state support its flexible functional segregation and integration during language and speech processing.

Modern linguistic theories and network science propose that language and speech processing are organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct framewise time-varying language networks and k-means clustering was employed to investigate the temporal-reoccurring patterns. We found that the framewise language network dynamics in resting state were robustly clustered into four states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of speech perception and lexical-phonological processing, speech production, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and was regarded as a baseline state. Temporally, the first three states appeared exclusively in limited time bins (∼15%), and most of the time (> 55%), state 4 was dominant. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in resting state, which forms a dynamic "meta-network" framework to support flexible functional segregation and integration during language and speech processing.

OsmiRNA5488 Regulates the Development of Embryo Sacs and Targets OsARF25 in Rice (Oryza sativa L.).

Small RNAs are a class of non-coding RNAs that typically range from 20 to 24 nucleotides in length. Among them, microRNAs (miRNAs) are particularly important regulators for plant development. The biological function of the conserved miRNAs has been studied extensively in plants, while that of the species-specific miRNAs has been studied in-depth. In this study, the regulatory role of a rice-specific OsmiRNA5488 (OsmiR5488) was characterized with the miR5488-overexpressed line (miR5488-OE) and miR5488-silenced line (STTM-5488). The seed-setting rate was notably reduced in miR5488-OE lines, but not in STTM-5488 lines. Cytological observation demonstrated the different types of abnormal mature embryo sacs, including the degeneration of embryo sacs and other variant types, in miR5488-OE lines. The percentage of the abnormal mature embryo sacs accounted for the reduced value of the seed-setting rate. Furthermore, OsARF25 was identified as a target of OsmiR5488 via RNA ligase-mediated 3'-amplifification of cDNA ends, dual luciferase assays, and transient expression assays. The primary root length was decreased with the increases in auxin concentrations in miR5488-OE lines compared to wild-type rice. Summarily, our results suggested that OsmiR5488 regulates the seed-setting rate and down-regulates the targeted gene OsARF25.

Linguistic experience acquisition for novel stimuli selectively activates the neural network of the visual word form area.

The human ventral visual cortex is functionally organized into different domains that sensitively respond to different categories, such as words and objects. There is heated debate over what principle constrains the locations of those domains. Taking the visual word form area (VWFA) as an example, we tested whether the word preference in this area originates from the bottom-up processes related to word shape (the shape hypothesis) or top-down connectivity of higher-order language regions (the connectivity hypothesis). We trained subjects to associate identical, meaningless, non-word-like figures with high-level features of either words or objects. We found that the word-feature learning for the figures elicited the neural activation change in the VWFA, and learning performance effectively predicted the activation strength of this area after learning. Word-learning effects were also observed in other language areas (i.e., the left posterior superior temporal gyrus, postcentral gyrus, and supplementary motor area), with increased functional connectivity between the VWFA and the language regions. In contrast, object-feature learning was not associated with obvious activation changes in the language regions. These results indicate that high-level language features of stimuli can modulate the activation of the VWFA, providing supportive evidence for the connectivity hypothesis of words processing in the ventral occipitotemporal cortex.

Doctor, Teacher, and Stethoscope: Neural Representation of Different Types of Semantic Relations.

Concepts can be related in many ways. They can belong to the same taxonomic category (e.g., "doctor" and "teacher," both in the category of people) or be associated with the same event context (e.g., "doctor" and "stethoscope," both associated with medical scenarios). How are these two major types of semantic relations coded in the brain? We constructed stimuli from three taxonomic categories (people, manmade objects, and locations) and three thematic categories (school, medicine, and sports) and investigated the neural representations of these two dimensions using representational similarity analyses in human participants (10 men and nine women). In specific regions of interest, the left anterior temporal lobe (ATL) and the left temporoparietal junction (TPJ), we found that, whereas both areas had significant effects of taxonomic information, the taxonomic relations had stronger effects in the ATL than in the TPJ ("doctor" and "teacher" closer in ATL neural activity), with the reverse being true for thematic relations ("doctor" and "stethoscope" closer in TPJ neural activity). A whole-brain searchlight analysis revealed that widely distributed regions, mainly in the left hemisphere, represented the taxonomic dimension. Interestingly, the significant effects of the thematic relations were only observed after the taxonomic differences were controlled for in the left TPJ, the right superior lateral occipital cortex, and other frontal, temporal, and parietal regions. In summary, taxonomic grouping is a primary organizational dimension across distributed brain regions, with thematic grouping further embedded within such taxonomic structures.SIGNIFICANCE STATEMENT How are concepts organized in the brain? It is well established that concepts belonging to the same taxonomic categories (e.g., "doctor" and "teacher") share neural representations in specific brain regions. How concepts are associated in other manners (e.g., "doctor" and "stethoscope," which are thematically related) remains poorly understood. We used representational similarity analyses to unravel the neural representations of these different types of semantic relations by testing the same set of words that could be differently grouped by taxonomic categories or by thematic categories. We found that widely distributed brain areas primarily represented taxonomic categories, with the thematic categories further embedded within the taxonomic structure.

Fine Subdivisions of the Semantic Network Supporting Social and Sensory-Motor Semantic Processing.

Neuroimaging studies have consistently indicated that semantic processing involves a brain network consisting of multimodal cortical regions distributed in the frontal, parietal, and temporal lobes. However, little is known about how semantic information is organized and processed within the network. Some recent studies have indicated that sensory-motor semantic information modulates the activation of this network. Other studies have indicated that this network responds more to social semantic information than to other information. Using fMRI, we collectively investigated the brain activations evoked by social and sensory-motor semantic information by manipulating the sociality and imageability of verbs in a word comprehension task. We detected 2 subgroups of brain regions within the network showing sociality and imageability effects, respectively. The 2 subgroups of regions are distinct but overlap in bilateral angular gyri and adjacent middle temporal gyri. A follow-up analysis of resting-state functional connectivity showed that dissociation of the 2 subgroups of regions is partially associated with their intrinsic functional connectivity differences. Additionally, an interaction effect of sociality and imageability was observed in the left anterior temporal lobe. Our findings indicate that the multimodal cortical semantic network has fine subdivisions that process and integrate social and sensory-motor semantic information.

Organizational Principles of Abstract Words in the Human Brain.

words constitute nearly half of the human lexicon and are critically associated with human abstract thoughts, yet little is known about how they are represented in the brain. We tested the neural basis of 2 classical cognitive notions of abstract meaning representation: by linguistic contexts and by semantic features. We collected fMRI BOLD responses for 360 abstract words and built theoretical representational models from state-of-the-art corpus-based natural language processing models and behavioral ratings of semantic features. Representational similarity analyses revealed that both linguistic contextual and semantic feature similarity affected the representation of abstract concepts, but in distinct neural levels. The corpus-based similarity was coded in the high-level linguistic processing system, whereas semantic feature information was reflected in distributed brain regions and in the principal component space derived from whole-brain activation patterns. These findings highlight the multidimensional organization and the neural dissociation between linguistic contextual and featural aspects of abstract concepts.

Intrinsic functional network architecture of human semantic processing: Modules and hubs.

Semantic processing entails the activation of widely distributed brain areas across the temporal, parietal, and frontal lobes. To understand the functional structure of this semantic system, we examined its intrinsic functional connectivity pattern using a database of 146 participants. Focusing on areas consistently activated during semantic processing generated from a meta-analysis of 120 neuroimaging studies (Binder et al., 2009), we found that these regions were organized into three stable modules corresponding to the default mode network (Module DMN), the left perisylvian network (Module PSN), and the left frontoparietal network (Module FPN). These three dissociable modules were integrated by multiple connector hubs-the left angular gyrus (AG) and the left superior/middle frontal gyrus linking all three modules, the left anterior temporal lobe linking Modules DMN and PSN, the left posterior portion of dorsal intraparietal sulcus (IPS) linking Modules DMN and FPN, and the left posterior middle temporal gyrus (MTG) linking Modules PSN and FPN. Provincial hubs, which converge local information within each system, were also identified: the bilateral posterior cingulate cortices/precuneus, the bilateral border area of the posterior AG and the superior lateral occipital gyrus for Module DMN; the left supramarginal gyrus, the middle part of the left MTG and the left orbital inferior frontal gyrus (IFG) for Module FPN; and the left triangular IFG and the left IPS for Module FPN. A neuro-functional model for semantic processing was derived based on these findings, incorporating the interactions of memory, language, and control.

Representing object categories by connections: Evidence from a mutivariate connectivity pattern classification approach.

The representation of object categories is a classical question in cognitive neuroscience and compelling evidence has identified specific brain regions showing preferential activation to categories of evolutionary significance. However, the potential contributions to category processing by tuning the connectivity patterns are largely unknown. Adopting a continuous multicategory paradigm, we obtained whole-brain functional connectivity (FC) patterns of each of four categories (faces, scenes, animals and tools) in healthy human adults and applied multivariate connectivity pattern classification analyses. We found that the whole-brain FC patterns made high-accuracy predictions of which category was being viewed. The decoding was successful even after the contributions of regions showing classical category-selective activations were excluded. We further identified the discriminative network for each category, which span way beyond the classical category-selective regions. Together, these results reveal novel mechanisms about how categorical information is represented in large-scale FC patterns, with general implications for the interactive nature of distributed brain areas underlying high-level cognition. Hum Brain Mapp 37:3685-3697, 2016. © 2016 Wiley Periodicals, Inc.

[Aberrant topological properties of whole-brain functional network in chronic right-sided sensorineural hearing loss: a resting-state functional MRI study].

OBJECTIVE: To investigate the topological properties of the functional brain network in unilateral sensorineural hearing loss patients. METHODS: In this study, we acquired resting-state BOLD- fMRI data from 19 right-sided SNHL patients and 31 healthy controls with normal hearing and constructed their whole brain functional networks. Two-sample two-tailed t-tests were performed to investigate group differences in topological parameters between the USNHL patients and the controls. Partial correlation analysis was conducted to determine the relationships between the network metrics and USNHL-related variables. RESULTS: Both USNHL patients and controls exhibited small-word architecture in their brain functional networks within the range 0. 1 - 0. 2 of sparsity. Compared to the controls, USNHL patients showed significant increase in characteristic path length and normalized characteristic path length, but significant decrease in global efficiency. Clustering coefficient, local efficiency and normalized clustering coefficient demonstrated no significant difference. Furthermore, USNHL patients exhibited no significant association between the altered network metrics and the duration of USNHL or the severity of hearing loss. CONCLUSION: Our results indicated the altered topological properties of whole brain functional networks in USNHL patients, which may help us to understand pathophysiologic mechanism of USNHL patients.

Altered grid-like coding in early blind people.

Cognitive maps in the hippocampal-entorhinal system are central for the representation of both spatial and non-spatial relationships. Although this system, especially in humans, heavily relies on vision, the role of visual experience in shaping the development of cognitive maps remains largely unknown. Here, we test sighted and early blind individuals in both imagined navigation in fMRI and real-world navigation. During imagined navigation, the Human Navigation Network, constituted by frontal, medial temporal, and parietal cortices, is reliably activated in both groups, showing resilience to visual deprivation. However, neural geometry analyses highlight crucial differences between groups. A 60° rotational symmetry, characteristic of a hexagonal grid-like coding, emerges in the entorhinal cortex of sighted but not blind people, who instead show a 90° (4-fold) symmetry, indicative of a square grid. Moreover, higher parietal cortex activity during navigation in blind people correlates with the magnitude of 4-fold symmetry. In sum, early blindness can alter the geometry of entorhinal cognitive maps, possibly as a consequence of higher reliance on parietal egocentric coding during navigation.

MEG frequency tagging reveals a grid-like code during attentional movements.

Grid-cells firing fields tile the environment with a 6-fold periodicity during both locomotion and visual exploration. Here, we tested, in humans, whether movements of covert attention elicit grid-like coding using frequency tagging. Participants observed visual trajectories presented sequentially at fixed rate, allowing different spatial periodicities (e.g., 4-, 6-, and 8-fold) to have corresponding temporal periodicities (e.g., 1, 1.5, and 2 Hz), thus resulting in distinct spectral responses. We found a higher response for the (grid-like) 6-fold periodicity and localized this effect in medial-temporal sources. In a control experiment featuring the same temporal periodicity but lacking spatial structure, the 6-fold effect did not emerge, suggesting its dependency on spatial movements of attention. We report evidence that grid-like signals in the human medial-temporal lobe can be elicited by covert attentional movements and suggest that attentional coding may provide a suitable mechanism to support the activation of cognitive maps during conceptual navigation.

Spatiotemporal dynamics of abstract and concrete semantic representations.

Dual Coding Theories (DCT) suggest that meaning is represented in the brain by a double code: a language-derived code in the Anterior Temporal Lobe (ATL) and a sensory-derived code in perceptual and motor regions. Concrete concepts should activate both codes, while abstract ones rely solely on the linguistic code. To test these hypotheses, the present magnetoencephalography (MEG) experiment had participants judge whether visually presented words relate to the senses while we recorded brain responses to abstract and concrete semantic components obtained from 65 independently rated semantic features. Results evidenced early involvement of anterior-temporal and inferior-frontal brain areas in both abstract and concrete semantic information encoding. At later stages, occipital and occipito-temporal regions showed greater responses to concrete compared to abstract features. The present findings suggest that the concreteness of words is processed first with a transmodal/linguistic code, housed in frontotemporal brain systems, and only after with an imagistic/sensorimotor code in perceptual regions.

A social-semantic working-memory account for two canonical language areas.

Language and social cognition are traditionally studied as separate cognitive domains, yet accumulative studies reveal overlapping neural correlates at the left ventral temporoparietal junction (vTPJ) and the left lateral anterior temporal lobe (lATL), which have been attributed to sentence processing and social concept activation. We propose a common cognitive component underlying both effects: social-semantic working memory. We confirmed two key predictions of our hypothesis using functional MRI. First, the left vTPJ and lATL showed sensitivity to sentences only when the sentences conveyed social meaning; second, these regions showed persistent social-semantic-selective activity after the linguistic stimuli disappeared. We additionally found that both regions were sensitive to the socialness of non-linguistic stimuli and were more tightly connected with the social-semantic-processing areas than with the sentence-processing areas. The converging evidence indicates the social-semantic working-memory function of the left vTPJ and lATL and challenges the general-semantic and/or syntactic accounts for the neural activity of these regions.

The brain network in support of social semantic accumulation.

Some studies have indicated that a specific 'social semantic network' represents the social meanings of words. However, studies of the comprehension of complex materials, such as sentences and narratives, have indicated that the same network supports the online accumulation of connected semantic information. In this study, we examined the hypothesis that this network does not simply represent the social meanings of words but also accumulates connected social meanings from texts. We defined the social semantic network by conducting a meta-analysis of previous studies on social semantic processing and then examined the effects of social semantic accumulation using a functional Magnetic Resonance Imaging (fMRI) experiment. Two important findings were obtained. First, the social semantic network showed a stronger social semantic effect in sentence and narrative reading than in word list reading, indicating the amplitude of social semantic activation can be accumulated in the network. Second, the activation of the social semantic network in sentence and narrative reading can be better explained by the holistic social-semantic-richness rating scores of the stimuli than by those of the constitutive words, indicating the social semantic contents can be integrated in the network. These two findings convergently indicate that the social semantic network supports the accumulation of connected social meanings.

Brain network reconfiguration for narrative and argumentative thought.

Our brain constructs reality through narrative and argumentative thought. Some hypotheses argue that these two modes of cognitive functioning are irreducible, reflecting distinct mental operations underlain by separate neural bases; Others ascribe both to a unitary neural system dedicated to long-timescale information. We addressed this question by employing inter-subject measures to investigate the stimulus-induced neural responses when participants were listening to narrative and argumentative texts during fMRI. We found that following both kinds of texts enhanced functional couplings within the frontoparietal control system. However, while a narrative specifically implicated the default mode system, an argument specifically induced synchronization between the intraparietal sulcus in the frontoparietal control system and multiple perisylvian areas in the language system. Our findings reconcile the two hypotheses by revealing commonalities and differences between the narrative and the argumentative brain networks, showing how diverse mental activities arise from the segregation and integration of the existing brain systems.

Dissociating the neural correlates of the sociality and plausibility effects in simple conceptual combination.

Neuroimaging studies have indicated that a brain network distributed in the supramodal cortical regions of the frontal, temporal, and parietal lobes plays a central role in conceptual processing. The activation of this network is modulated by two orthogonal dimensions in conceptual processing-the semantic features of individual concepts and the meaningfulness of conceptual combinations-but it remains unclear how the network is functionally organized along these two dimensions. In this fMRI study, we focused on two specific factors, i.e. the social semantic richness of words and the semantic plausibility of word combinations, along the two dimensions. In literature, the distributions of the effects of the two factors are very similar, but have not been rigorously compared in one study. We orthogonally manipulated the two factors in a phrase comprehension task and found a clear dissociation between their effects. The combination of these results with our previous findings reveals three adjacently distributed subnetworks of the supramodal semantic network, associated with the sociality effect, imageability effect, and semantic plausibility effect, respectively. Further analysis of the resting-state functional connectivity data indicated that the functional dissociation among the three subnetworks is associated with their underlying intrinsic connectivity structures.

Coin, telephone, and handcuffs: Neural correlates of social knowledge of inanimate objects.

A variety of objects are made to serve social functions. The use of these objects has greatly enriched and expanded our social behaviors. How do our brains represent the social knowledge of inanimate objects such as coins, telephones, and handcuffs? According to a recent version of the grounded theory, social knowledge of inanimate objects might be grounded in the mentalizing network, as the social functions of inanimate objects are closely associated with the intentions of the people using them. However, there is also evidence that the mentalizing network may only get activated when a human/mental agent is detected. Using fMRI, we explored the neural correlates of social knowledge of inanimate objects by comparing the brain activation evoked by high-sociality object nouns (e.g., banknote) with that evoked by low-sociality object nouns (e.g., battery). The left anterior superior temporal sulcus, a classic part of the mentalizing network, showed higher activation for the high-sociality inanimate object nouns than for the low-sociality ones in the whole-brain analysis. Several other areas of the mentalizing network showed sensitivity to object sociality in small volume correction and/or region-of-interest analyses. Our findings indicate that social knowledge of inanimate objects is supported by brain areas in the mentalizing network.