Conceptual object representations in human anterior temporal cortex

The Effects of Attentional Focus on Brain Function During a Gross Motor Task

CONTEXT

Although the beneficial effects of using an external focus of attention are well documented in attainment and performance of movement execution, neural mechanisms underlying external focus' benefits are mostly unknown.

OBJECTIVE

To assess brain function during a lower-extremity gross motor movement while manipulating an internal and external focus of attention.

DESIGN

Cross-over study.

SETTING

Neuroimaging center Participants: A total of 10 healthy subjects (5 males and 5 females) Intervention: Participants completed external and internal focus of attention unilateral left 45° knee extension/flexion movements at a rate of 1.2 Hz laying supine in a magnetic resonance imaging scanner for 4 blocks of 30 seconds interspersed with 30-second rest blocks. During the internal condition, participants were instructed to "squeeze their quadriceps." During the external condition, participants were instructed to "focus on a target" positioned above their tibia.

MAIN OUTCOME MEASURES

T1 brain structural imaging was performed for registration of the functional data. For each condition, 3T functional magnetic resonance imaging blood oxygenation level dependent data representing 90 whole-brain volumes were acquired.

RESULTS

During the external relative to internal condition, increased activation was detected in the right occipital pole, cuneal cortex, anterior portion of the lingual gyrus, and intracalcarine cortex (Zmax = 4.5-6.2, P < .001). During the internal relative to external condition, increased activation was detected in the left primary motor cortex, left supplementary motor cortex, and cerebellum (Zmax = 3.4-3.5, P < .001).

CONCLUSIONS

Current results suggest that an external focus directed toward a visual target produces more brain activity in regions associated with vision and ventral streaming pathways, whereas an internal focus manipulated through instruction increases activation in brain regions that are responsible for motor control. Results from this study serve as baseline information for future prevention and rehabilitation investigations of how manipulating focus of attention can constructively affect neuroplasticity during training and rehabilitation.

Concrete vs. Abstract Semantics: From Mental Representations to Functional Brain Mapping

The nature of abstract and concrete semantics and differences between them have remained a debated issue in psycholinguistic and cognitive studies for decades. Most of the available behavioral and neuroimaging studies reveal distinctions between these two types of semantics, typically associated with a so-called “concreteness effect.” Many attempts have been made to explain these differences using various approaches, from purely theoretical linguistic and cognitive frameworks to neuroimaging experiments. In this brief overview, we will try to provide a snapshot of these diverse views and relationships between them and highlight the crucial issues preventing this problem from being solved. We will argue that one potentially beneficial way forward is to identify the neural mechanisms underpinning acquisition of the different types of semantics (e.g., by using neurostimulation techniques to establish causal relationships), which may help explain the distinctions found between the processing of concrete and abstract semantics.

The Cognitive Neuroscience of Stable and Flexible Semantic Typicality

Typicality effects are among the most well-studied phenomena in the study of concepts. The classical notion of typicality is that typical concepts share many features with category co-members and few features with members of contrast categories. However, this notion was challenged by evidence that typicality is highly context dependent and not always dependent on central tendency. Dieciuc and Folstein (2019) argued that there is strong evidence for both views and that the two types of typicality effects might depend on different mechanisms. A recent theoretical framework, the controlled semantic cognition framework (Lamdon Ralph et al., 2017) strongly emphasizes the classical view, but includes mechanisms that could potentially account for both kinds of typicality. In contrast, the situated cognition framework (Barsalou, 2009b) articulates the context-dependent view. Here, we review evidence from cognitive neuroscience supporting the two frameworks. We also briefly evaluate the ability of computational models associated with the CSC to account for phenomena supporting SitCog (Rogers and McClelland, 2004). Many predictions of both frameworks are borne out by recent cognitive neuroscience evidence. While the CSC framework can at least potentially account for many of the typicality phenomena reviewed, challenges remain, especially with regard to ad hoc categories.

Unveiling the dynamic interplay between the hub- and spoke-components of the brain's semantic system and its impact on human behaviour

The neural architecture of semantic knowledge comprises two key structures: (i) A set of widely dispersed regions, located adjacent to the sensorimotor cortices, serve as spokes that represent various modality-specific and context-dependent contents. (ii) The anterior-temporal lobe (ATL) serves as a hub that computes the nonlinear mappings required to transform modality-specific information into pan-modality, multifaceted concepts. Little is understood regarding whether neural dynamics between the hub and spokes might flexibly alter depending on the nature of a concept and how it impinges upon behaviour. Using fMRI, we demonstrate for the first time that the ATL serves as a 'pivot' which dynamically forms flexible long-range networks with cortical modules specialised for different domains (in the present case, the knowledge about actions and places). In two experiments, we manipulated semantic congruity and asked participants to recognise visually presented items. In Experiment 1 (dual-object displays), the ATL increased its functional coupling with the bilateral frontoparietal action-sensitive system when the objects formed a pair that permitted semantically meaningful action. In Experiment 2 (objects embedded in a scene), the ATL augmented its coupling with the retrosplenial cortex of the place-sensitive system when the objects and scene formed a semantically coherent ensemble. Causative connectivity revealed that, while communication between the hub and spokes was bidirectional, the hub's directional impact on spokes dwarfed the strength of the inverse spoke-to-hub connectivity. Furthermore, the size of behavioural congruity effects co-varied with the strength of neural coupling between the ATL hub and action- / place-related spokes, evident both at the within-individual level (the behavioural fluctuation across scanning runs) and between-individual level (the behavioural variation of between participants). Together, these findings have important implications for understanding the machinery that links neural dynamics with semantic cognition.

Effective learning is accompanied by high-dimensional and efficient representations of neural activity

A fundamental cognitive process is to map value and identity onto the objects we learn about. However, what space best embeds this mapping is not completely understood. Here we develop tools to quantify the space and organization of such a mapping in neural responses as reflected in functional MRI, to show that quick learners have a higher dimensional representation than slow learners, and hence more easily distinguishable whole-brain responses to objects of different value. Furthermore, we find that quick learners display more compact embedding of their neural responses, and hence have higher ratios of their stimuli dimension to their embedding dimension, which is consistent with greater efficiency of cognitive coding. Lastly, we investigate the neurophysiological drivers at smaller scales and study the complementary distinguishability of whole-brain responses. Our results demonstrate a spatial organization of neural responses characteristic of learning and offer geometric measures applicable to identifying efficient coding in higher-order cognitive processes.

Steady state visual evoked potentials in reading aloud: Effects of lexicality, frequency and orthographic familiarity

The present study explored the possibility to use Steady-State Visual Evoked Potentials (SSVEPs) as a tool to investigate the core mechanisms in visual word recognition. In particular, we investigated three benchmark effects of reading aloud: lexicality (words vs. pseudowords), frequency (high-frequency vs. low-frequency words), and orthographic familiarity ('familiar' versus 'unfamiliar' pseudowords). We found that words and pseudowords elicited robust SSVEPs. Words showed larger SSVEPs than pseudowords and high-frequency words showed larger SSVEPs than low-frequency words. SSVEPs were not sensitive to orthographic familiarity. We further localized the neural generators of the SSVEP effects. The lexicality effect was located in areas associated with early level of visual processing, i.e. in the right occipital lobe and in the right precuneus. Pseudowords produced more activation than words in left sensorimotor areas, rolandic operculum, insula, supramarginal gyrus and in the right temporal gyrus. These areas are devoted to speech processing and/or spelling-to-sound conversion. The frequency effect involved the left temporal pole and orbitofrontal cortex, areas previously implicated in semantic processing and stimulus-response associations respectively, and the right postcentral and parietal inferior gyri, possibly indicating the involvement of the right attentional network.

Concrete versus abstract forms of social concept: an fMRI comparison of knowledge about people versus social terms

The anterior temporal lobes (ATLs) play a key role in conceptual knowledge representation. The hub-and-spoke theory suggests that the contribution of the ATLs to semantic representation is (a) transmodal, i.e. integrating information from multiple sensorimotor and verbal modalities, and (b) pan-categorical, representing concepts from all categories. Another literature, however, suggests that this region's responses are modality- and category-selective; prominent examples include category selectivity for socially relevant concepts and face recognition. The predictions of each approach have never been directly compared. We used data from three studies to compare category-selective responses within the ATLs. Study 1 compared ATL responses to famous people versus another conceptual category (landmarks) from visual versus auditory inputs. Study 2 compared ATL responses to famous people from pictorial and written word inputs. Study 3 compared ATL responses to a different kind of socially relevant stimuli, namely abstract non-person-related words, in order to ascertain whether ATL subregions are engaged for social concepts more generally or only for person-related knowledge. Across all three studies a dominant bilateral ventral ATL cluster responded to all categories in all modalities. Anterior to this ‘pan-category’ transmodal region, a second cluster responded more weakly overall yet selectively for people, but did so equally for spoken names and faces (Study 1). A third region in the anterior superior temporal gyrus responded selectively to abstract socially relevant words (Study 3), but did not respond to concrete socially relevant words (i.e. written names; Study 2). These findings can be accommodated by the graded hub-and-spoke model of concept representation. On this view, the ventral ATL is the centre point of a bilateral ATL hub, which contributes to conceptual representation through transmodal distillation of information arising from multiple modality-specific association cortices. Partial specialization occurs across the graded ATL hub as a consequence of gradedly differential connectivity across the region.

This article is part of the theme issue ‘Varieties of abstract concepts: development, use and representation in the brain’.

Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study

BACKGROUND

Computerized multi-model training has been widely studied for its effect on delaying cognitive decline. In this study, we designed the first Chinese-version computer-based multi-model cognitive training for mild cognitive impairment (MCI) patients. Neuropsychological effects and neural activity changes assessed by functional MRI were both evaluated.

METHOD

MCI patients in the training group were asked to take training 3-4 times per week for 6 months. Neuropsychological and resting-state fMRI assessment were performed at baseline and at 6 months. Patients in both groups were continuously followed up for another 12 months and assessed by neuropsychological tests again.

RESULTS

78 patients in the training group and 63 patients in the control group accomplished 6-month follow-up. Training group improved 0.23 standard deviation (SD) of mini-mental state examination, while control group had 0.5 SD decline. Addenbrooke's cognitive examination-revised scores in attention (p = 0.002) and memory (p = 0.006), as well as stroop color-word test interference index (p = 0.038) and complex figure test-copy score (p = 0.035) were also in favor of the training effect. Difference between the changes of two groups after training was not statistically significant. The fMRI showed increased regional activity at bilateral temporal poles, insular cortices and hippocampus. However, difference between the changes of two groups after another 12 months was not statistically significant.

CONCLUSIONS

Multi-model cognitive training help MCI patients to gained cognition benefit, especially in memory, attention and executive function. Functional neuroimaging provided consistent neural activation evidence. Nevertheless, after one-year follow up after last training, training effects were not significant. The study provided new evidence of beneficial effect of multi-model cognitive training.

Conceptually Rich, Perceptually Sparse: Object Representations in 6-Month-Old Infants’ Working Memory

Six-month-old infants can store representations of multiple objects in working memory but do not always remember the objects’ features (e.g., shape). Here, we asked whether infants’ object representations (a) may contain conceptual content and (b) may contain this content even if perceptual features are forgotten. We hid two conceptually distinct objects (a humanlike doll and a nonhuman ball) one at a time in two separate locations and then tested infants’ memory for the first-hidden object by revealing either the original hidden object or an unexpected other object. Using looking time, we found that infants remembered the categorical identity of the hidden object but failed to remember its perceptual identity. Our results suggest that young infants may encode conceptual category in a representation of an occluded object, even when perceptual features are lost.

Distinctive semantic features in the healthy adult brain

The role of semantic features, which are distinctive (e.g., a zebra's stripes) or shared (e.g. has four legs) for accessing a concept, has been studied in detail in early neurodegenerative disease such as semantic dementia (SD). However, potential neural underpinnings of such processing have not been studied in healthy adults. The current study examines neural activation patterns using fMRI while participants completed a feature verification task, in which they identified shared or distinctive semantic features for a set of natural kinds and man-made artifacts. The results showed that the anterior temporal lobe bilaterally is an important area for processing distinctive features, and that this effect is stronger within natural kinds than man-made artifacts. These findings provide converging evidence from healthy adults that is consistent with SD research, and support a model of semantic memory in which patterns of specificity of semantic information can partially explain differences in neural activation between categories.

Neuroanatomical Correlates of the Unity and Diversity Model of Executive Function in Young Adults

Understanding the neuroanatomical correlates of individual differences in executive function (EF) is integral to a complete characterization of the neural systems supporting cognition. While studies have investigated EF-neuroanatomy relationships in adults, these studies often include samples with wide variation in age, which may mask relationships between neuroanatomy and EF specific to certain neurodevelopmental time points, and such studies often use unreliable single task measures of EF. Here we address both issues. First, we focused on a specific age at which the majority of neurodevelopmental changes are complete but at which age-related atrophy is not likely (N = 251; mean age of 28.71 years, SD = 0.57). Second, we assessed EF through multiple tasks, deriving three factors scores guided by the unity/diversity model of EF, which posits a common EF factor that influences all EF tasks, as well as an updating-specific and shifting-specific factor. We found that better common EF was associated with greater volume and surface area of regions in right middle frontal gyrus/frontal pole, right inferior temporal gyrus, as well as fractional anisotropy in portions of the right superior longitudinal fasciculus (rSLF) and the left anterior thalamic radiation. Better updating-specific ability was associated with greater cortical thickness of a cluster in left cuneus/precuneus, and reduced cortical thickness in regions of right superior frontal gyrus and right middle/superior temporal gyrus, but no aspects of white matter diffusion. In contrast, better shifting-specific ability was not associated with gray matter characteristics, but rather was associated with increased mean diffusivity and reduced radial diffusivity throughout much of the brain and reduced axial diffusivity in distinct clusters of the left superior longitudinal fasciculus, the corpus callosum, and the right optic radiation. These results demonstrate that associations between individual differences in EF ability and regional neuroanatomical properties occur not only within classic brain networks thought to support EF, but also in a variety of other regions and white matter tracts. These relationships appear to differ from observations made in emerging adults (Smolker et al., 2015), which might indicate that the brain systems associated with EF continue to experience behaviorally relevant maturational process beyond the early 20s.

Fast periodic visual stimulation to study tool-selective processing in the human brain

Because tools are manipulated for the purpose of action, they are often considered to be a specific object category that associates perceptual and motor properties. Their neural processing has been studied extensively by comparing the cortical activity elicited by the separate presentation of tool and non-tool objects, assuming that observed differences are solely due to activity selective for processing tools. Here, using a fast periodic visual stimulation (FPVS) paradigm, we isolated EEG activity selectively related to the processing of tool objects embedded in a stream of non-tool objects. Participants saw a continuous sequence of tool and non-tool images at a 3.7 Hz presentation rate, arranged as a repeating pattern of four non-tool images followed by one tool image. We expected the stimulation to generate an EEG response at the frequency of image presentation (3.7 Hz) and its harmonics, reflecting activity common to the processing of tool and non-tool images. Most importantly, if tool and non-tool images evoked different neural responses, we expected this differential activity to generate an additional response at the frequency of tool images (3.7 Hz/5 = 0.74 Hz). To ensure that this response was not due to unaccounted for systematic differences in low-level visual features, we also tested a phase-scrambled version of the sequence. The periodic insertion of tool stimuli within a stream of non-tool stimuli elicited a significant EEG response at the tool-selective frequency and its harmonics. This response was reduced when the images were phase-scrambled. We conclude that FPVS is a promising technique to selectively measure tool-related activity.

Tool selection and the ventral-dorsal organization of tool-related knowledge

Tool selection is a cognitive process necessary for tool use, and may rely on distinct knowledge under different conditions. This fMRI experiment was designed to identify neural substrates mediating tool selection under different conditions. Participants performed a picture‐matching task that presented a recipient object and an action‐goal, and required the selection of the best tool object from among four candidates. Some trials allowed selection of the prototypical tool, whereas others forced selection of either a functionally substitutable or impossible tool. Statistical contrasts revealed significantly different activation between Proto and Sub conditions in frontal, parietal, and temporal lobes. The middle temporal gyrus (MTG) bilaterally, and the right posterior cingulate were more strongly activated by prototypical tool selection, and left inferior parietal lobule (IPL), intraparietal sulcus (IPS), middle frontal gyrus, and precuneus were more strongly activated when selecting substitutable objects. These findings are concordant with previous neuroimaging studies of tool use knowledge in demonstrating that activation of the MTG represents functional knowledge for conventional tool usage, and activation of the IPL/IPS supports action (i.e., praxic) knowledge representations. These results contribute to the literature that dissociates the roles of ventral and dorsal streams in tool‐related knowledge and behavior, and emphasize the role of the left hemisphere for processing goal‐directed object interactions.

Abstract Representations of Object-Directed Action in the Left Inferior Parietal Lobule

Prior neuroimaging and neuropsychological research indicates that the left inferior parietal lobule in the human brain is a critical substrate for representing object manipulation knowledge. In the present functional MRI study we used multivoxel pattern analyses to test whether action similarity among objects can be decoded in the inferior parietal lobule independent of the task applied to objects (identification or pantomime) and stimulus format in which stimuli are presented (pictures or printed words). Participants pantomimed the use of objects, cued by printed words, or identified pictures of objects. Classifiers were trained and tested across task (e.g., training data: pantomime; testing data: identification), stimulus format (e.g., training data: word format; testing format: picture) and specific objects (e.g., training data: scissors vs. corkscrew; testing data: pliers vs. screwdriver). The only brain region in which action relations among objects could be decoded across task, stimulus format and objects was the inferior parietal lobule. By contrast, medial aspects of the ventral surface of the left temporal lobe represented object function, albeit not at the same level of abstractness as actions in the inferior parietal lobule. These results suggest compulsory access to abstract action information in the inferior parietal lobe even when simply identifying objects.

Topological Alterations and Symptom-Relevant Modules in the Whole-Brain Structural Network in Semantic Dementia

BACKGROUND

Semantic dementia (SD) is characterized by a selective decline in semantic processing. Although the neuropsychological pattern of this disease has been identified, its topological global alterations and symptom-relevant modules in the whole-brain anatomical network have not been fully elucidated.

OBJECTIVE

This study aims to explore the topological alteration of anatomical network in SD and reveal the modules associated with semantic deficits in this disease.

METHODS

We first constructed the whole-brain white-matter networks of 20 healthy controls and 19 patients with SD. Then, the network metrics of graph theory were compared between these two groups. Finally, we separated the network of SD patients into different modules and correlated the structural integrity of each module with the severity of the semantic deficits across patients.

RESULTS

The network of the SD patients presented a significantly reduced global efficiency, indicating that the long-distance connections were damaged. The network was divided into the following four distinctive modules: the left temporal/occipital/parietal, frontal, right temporal/occipital, and frontal/parietal modules. The first two modules were associated with the semantic deficits of SD.

CONCLUSION

These findings illustrate the skeleton of the neuroanatomical network of SD patients and highlight the key role of the left temporal/occipital/parietal module and the left frontal module in semantic processing.

Semantic representation in the white matter pathway

Object conceptual processing has been localized to distributed cortical regions that represent specific attributes. A challenging question is how object semantic space is formed. We tested a novel framework of representing semantic space in the pattern of white matter (WM) connections by extending the representational similarity analysis (RSA) to structural lesion pattern and behavioral data in 80 brain-damaged patients. For each WM connection, a neural representational dissimilarity matrix (RDM) was computed by first building machine-learning models with the voxel-wise WM lesion patterns as features to predict naming performance of a particular item and then computing the correlation between the predicted naming score and the actual naming score of another item in the testing patients. This correlation was used to build the neural RDM based on the assumption that if the connection pattern contains certain aspects of information shared by the naming processes of these two items, models trained with one item should also predict naming accuracy of the other. Correlating the neural RDM with various cognitive RDMs revealed that neural patterns in several WM connections that connect left occipital/middle temporal regions and anterior temporal regions associated with the object semantic space. Such associations were not attributable to modality-specific attributes (shape, manipulation, color, and motion), to peripheral picture-naming processes (picture visual similarity, phonological similarity), to broad semantic categories, or to the properties of the cortical regions that they connected, which tended to represent multiple modality-specific attributes. That is, the semantic space could be represented through WM connection patterns across cortical regions representing modality-specific attributes.

One of the most challenging questions in cognitive neuroscience is how semantic knowledge, for example, that “scissors” and “knives” are related in meaning, can emerge from primary sensory dimensions such as visual forms. It is often assumed that in the human brain, semantics are stored in regions of the brain cortex, where distinct types of modality-specific information are transferred to and bind together. We tested an alternative hypothesis—“representation by connection”—in which higher-order semantic information could be coded by means of connection patterns between cortical regions. Combining data from behavior and brain imaging of 80 patients with brain lesions, we applied machine learning to construct the mapping models between the lesion patterns on axonal tracts (white matter) and item-specific object-naming performances. We found that specific white matter lesions produced deficits in object naming associated with the object’s semantic space, but not relevant to its primary dimension. The naming performances of semantically related objects were better predicted from white matter lesion-pattern models. That is, the higher-order semantic space could be coded in patterns of brain connections by linking cortical areas that do not necessarily contain such information.

Controlled semantic cognition relies upon dynamic and flexible interactions between the executive 'semantic control' and hub-and-spoke 'semantic representation' systems

Built upon a wealth of neuroimaging, neurostimulation, and neuropsychology data, a recent proposal set forth a framework termed controlled semantic cognition (CSC) to account for how the brain underpins the ability to flexibly use semantic knowledge (Lambon Ralph et al., 2017; Nature Reviews Neuroscience). In CSC, the ‘semantic control’ system, underpinned predominantly by the prefrontal cortex, dynamically monitors and modulates the ‘semantic representation’ system that consists of a ‘hub’ (anterior temporal lobe, ATL) and multiple ‘spokes’ (modality-specific areas). CSC predicts that unfamiliar and exacting semantic tasks should intensify communication between the ‘control’ and ‘representation’ systems, relative to familiar and less taxing tasks. In the present study, we used functional magnetic resonance imaging (fMRI) to test this hypothesis. Participants paired unrelated concepts by canonical colours (a less accustomed task – e.g., pairing ketchup with fire-extinguishers due to both being red) or paired well-related concepts by semantic relationship (a typical task – e.g., ketchup is related to mustard). We found the ‘control’ system was more engaged by atypical than typical pairing. While both tasks activated the ATL ‘hub’, colour pairing additionally involved occipitotemporal ‘spoke’ regions abutting areas of hue perception. Furthermore, we uncovered a gradient along the ventral temporal cortex, transitioning from the caudal ‘spoke’ zones preferring canonical colour processing to the rostral ‘hub’ zones preferring semantic relationship. Functional connectivity also differed between the tasks: Compared with semantic pairing, colour pairing relied more upon the inferior frontal gyrus, a key node of the control system, driving enhanced connectivity with occipitotemporal ‘spoke’. Together, our findings characterise the interaction within the neural architecture of semantic cognition – the control system dynamically heightens its connectivity with relevant components of the representation system, in response to different semantic contents and difficulty levels.

Anterior Temporal Lobe Morphometry Predicts Categorization Ability

Categorization is the mental operation by which the brain classifies objects and events. It is classically assessed using semantic and non-semantic matching or sorting tasks. These tasks show a high variability in performance across healthy controls and the cerebral bases supporting this variability remain unknown. In this study we performed a voxel-based morphometry study to explore the relationships between semantic and shape categorization tasks and brain morphometric differences in 50 controls. We found significant correlation between categorization performance and the volume of the gray matter in the right anterior middle and inferior temporal gyri. Semantic categorization tasks were associated with more rostral temporal regions than shape categorization tasks. A significant relationship was also shown between white matter volume in the right temporal lobe and performance in the semantic tasks. Tractography revealed that this white matter region involved several projection and association fibers, including the arcuate fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and inferior longitudinal fasciculus. These results suggest that categorization abilities are supported by the anterior portion of the right temporal lobe and its interaction with other areas.

Integrative and distinctive coding of visual and conceptual object features in the ventral visual stream

A significant body of research in cognitive neuroscience is aimed at understanding how object concepts are represented in the human brain. However, it remains unknown whether and where the visual and abstract conceptual features that define an object concept are integrated. We addressed this issue by comparing the neural pattern similarities among object-evoked fMRI responses with behavior-based models that independently captured the visual and conceptual similarities among these stimuli. Our results revealed evidence for distinctive coding of visual features in lateral occipital cortex, and conceptual features in the temporal pole and parahippocampal cortex. By contrast, we found evidence for integrative coding of visual and conceptual object features in perirhinal cortex. The neuroanatomical specificity of this effect was highlighted by results from a searchlight analysis. Taken together, our findings suggest that perirhinal cortex uniquely supports the representation of fully specified object concepts through the integration of their visual and conceptual features.

The Temporal Pole Top-Down Modulates the Ventral Visual Stream During Social Cognition

The temporal pole (TP) has been associated with diverse functions of social cognition and emotion processing. Although the underlying mechanism remains elusive, one possibility is that TP acts as domain-general hub integrating socioemotional information. To test this, 26 participants were presented with 60 empathy-evoking film clips during fMRI scanning. The film clips were preceded by a linguistic sad or neutral context and half of the clips were accompanied by sad music. In line with its hypothesized role, TP was involved in the processing of sad context and furthermore tracked participants' empathic concern. To examine the neuromodulatory impact of TP, we applied nonlinear dynamic causal modeling to a multisensory integration network from previous work consisting of superior temporal gyrus (STG), fusiform gyrus (FG), and amygdala, which was extended by an additional node in the TP. Bayesian model comparison revealed a gating of STG and TP on fusiform-amygdalar coupling and an increase of TP to FG connectivity during the integration of contextual information. Moreover, these backward projections were strengthened by emotional music. The findings indicate that during social cognition, TP integrates information from different modalities and top-down modulates lower-level perceptual areas in the ventral visual stream as a function of integration demands.

Neural Representations of Belief Concepts: A Representational Similarity Approach to Social Semantics

The present experiment identified neural regions that represent a class of concepts that are independent of perceptual or sensory attributes. During functional magnetic resonance imaging scanning, participants viewed names of social groups (e.g. Atheists, Evangelicals, and Economists) and performed a one-back similarity judgment according to 1 of 2 dimensions of belief attributes: political orientation (Liberal to Conservative) or spiritualism (Spiritualist to Materialist). By generalizing across a wide variety of social groups that possess these beliefs, these attribute concepts did not coincide with any specific sensory quality, allowing us to target conceptual, rather than perceptual, representations. Multi-voxel pattern searchlight analysis was used to identify regions in which activation patterns distinguished the 2 ends of both dimensions: Conservative from Liberal social groups when participants focused on the political orientation dimension, and spiritual from Materialist groups when participants focused on the spiritualism dimension. A cluster in right precuneus exhibited such a pattern, indicating that it carries information about belief-attribute concepts and forms part of semantic memory—perhaps a component particularly concerned with psychological traits. This region did not overlap with the theory of mind network, which engaged nearby, but distinct, parts of precuneus. These findings have implications for the neural organization of conceptual knowledge, especially the understanding of social groups.

The neural representation of social status in the extended face-processing network

Social status is a salient cue that shapes our perceptions of other people and ultimately guides our social interactions. Despite the pervasive influence of status on social behavior, how information about the status of others is represented in the brain remains unclear. Here, we tested the hypothesis that social status information is embedded in our neural representations of other individuals. Participants learned to associate faces with names, job titles that varied in associated status, and explicit markers of reputational status (star ratings). Trained stimuli were presented in an functional magnetic resonance imaging experiment where participants performed a target detection task orthogonal to the variable of interest. A network of face-selective brain regions extending from the occipital lobe to the orbitofrontal cortex was localized and served as regions of interest. Using multivoxel pattern analysis, we found that face-selective voxels in the lateral orbitofrontal cortex - a region involved in social and nonsocial valuation, could decode faces based on their status. Similar effects were observed with two different status manipulations - one based on stored semantic knowledge (e.g., different careers) and one based on learned reputation (e.g., star ranking). These data suggest that a face-selective region of the lateral orbitofrontal cortex may contribute to the perception of social status, potentially underlying the preferential attention and favorable biases humans display toward high-status individuals.

On the partnership between neural representations of object categories and visual features in the ventral visual pathway

A dominant view in the cognitive neuroscience of object vision is that regions of the ventral visual pathway exhibit some degree of category selectivity. However, recent findings obtained with multivariate pattern analyses (MVPA) suggest that apparent category selectivity in these regions is dependent on more basic visual features of stimuli. In which case a rethinking of the function and organization of the ventral pathway may be in order. We suggest that addressing this issue of functional specificity requires clear coding hypotheses, about object category and visual features, which make contrasting predictions about neuroimaging results in ventral pathway regions. One way to differentiate between categorical and featural coding hypotheses is to test for residual categorical effects: effects of category selectivity that cannot be accounted for by visual features of stimuli. A strong method for testing these effects, we argue, is to make object category and target visual features orthogonal in stimulus design. Recent studies that adopt this approach support a feature-based categorical coding hypothesis according to which regions of the ventral stream do indeed code for object category, but in a format at least partially based on the visual features of stimuli.

Predicting the brain activation pattern associated with the propositional content of a sentence: Modeling neural representations of events and states

Even though much has recently been learned about the neural representation of individual concepts and categories, neuroimaging research is only beginning to reveal how more complex thoughts, such as event and state descriptions, are neurally represented. We present a predictive computational theory of the neural representations of individual events and states as they are described in 240 sentences. Regression models were trained to determine the mapping between 42 neurally plausible semantic features (NPSFs) and thematic roles of the concepts of a proposition and the fMRI activation patterns of various cortical regions that process different types of information. Given a semantic characterization of the content of a sentence that is new to the model, the model can reliably predict the resulting neural signature, or, given an observed neural signature of a new sentence, the model can predict its semantic content. The models were also reliably generalizable across participants. This computational model provides an account of the brain representation of a complex yet fundamental unit of thought, namely, the conceptual content of a proposition. In addition to characterizing a sentence representation at the level of the semantic and thematic features of its component concepts, factor analysis was used to develop a higher level characterization of a sentence, specifying the general type of event representation that the sentence evokes (e.g., a social interaction versus a change of physical state) and the voxel locations most strongly associated with each of the factors. Hum Brain Mapp 38:4865-4881, 2017. © 2017 Wiley Periodicals, Inc.

What semantic dementia teaches us about the functional organization of the left posterior fusiform gyrus

After demonstrating the relative preservation of fruit and vegetable knowledge in patients with semantic dementia (SD), we sought to identify the neural substrate of this unusual category effect. Nineteen patients with SD performed a semantic sorting task and underwent a morphometric 3T MRI scan. The grey-matter volumes of five regions within the temporal lobe were bilaterally computed, as well as those of two recently described areas (FG1 and FG2) within the posterior fusiform gyrus. In contrast to the other semantic categories we tested, fruit and vegetable scores were only predicted by left FG1 volume. We therefore found a specific relationship between the volume of a subregion within the left posterior fusiform gyrus and performance on fruits and vegetables in SD. We argue that the left FG1 is a convergence zone for the features that might be critical to successfully sort fruits and vegetables. We also discuss evidence for a functional specialization of the fusiform gyrus along two axes (lateral medial and longitudinal), depending on the nature of the concepts and on the level of processing complexity required by the ongoing task.

Neural representations of the concepts in simple sentences: Concept activation prediction and context effects

Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation.

Frequency-specific directed interactions in the human brain network for language

The brain's remarkable capacity for language requires bidirectional interactions between functionally specialized brain regions. We used magnetoencephalography to investigate interregional interactions in the brain network for language while 102 participants were reading sentences. Using Granger causality analysis, we identified inferior frontal cortex and anterior temporal regions to receive widespread input and middle temporal regions to send widespread output. This fits well with the notion that these regions play a central role in language processing. Characterization of the functional topology of this network, using data-driven matrix factorization, which allowed for partitioning into a set of subnetworks, revealed directed connections at distinct frequencies of interaction. Connections originating from temporal regions peaked at alpha frequency, whereas connections originating from frontal and parietal regions peaked at beta frequency. These findings indicate that the information flow between language-relevant brain areas, which is required for linguistic processing, may depend on the contributions of distinct brain rhythms.

Left Anterior Temporal Lobe and Bilateral Anterior Cingulate Cortex Are Semantic Hub Regions: Evidence from Behavior-Nodal Degree Mapping in Brain-Damaged Patients

The organizational principles of semantic memory in the human brain are still controversial. Although studies have shown that the semantic system contains hub regions that bind information from different sensorimotoric modalities to form concepts, it is unknown whether there are hub regions other than the anterior temporal lobe (ATL). Meanwhile, previous studies have rarely used network measurements to explore the hubs or correlated network indexes with semantic performance, although the most direct supportive evidence of hubs should come from the network perspective. To fill this gap, we correlated the brain-network index with semantic performance in 86 brain-damaged patients. We especially selected the nodal degree measure that reflects how well a node is connected in the network. The measure was calculated as the total number of connections of a given node with other nodes in the resting-state functional MRI network. Semantic ability was measured using the performance of both general and modality-specific (object form, color, motion, sound, manipulation, and function) semantic tasks. We found that the left ATL and the bilateral anterior cingulate cortex could be semantic hubs because the reduced nodal degree values of these regions could effectively predict the deficits in both general and modality-specific semantic performance. Moreover, the effects remained when the analyses were performed only in the patients who did not have lesions in these regions. The two hub regions might support semantic representations and executive control processes, respectively. These data provide empirical evidence for the distributed-plus-hub theory of semantic memory from the network perspective.

SIGNIFICANCE STATEMENT

Although the distributed-plus-hub organization of semantic memory has been proposed for several years, it remains unclear which hubs other than the anterior temporal lobe are included in the semantic system. Here, we identified such hubs from an innovative network perspective. The voxelwise nodal degree values were correlated with the performance of general and modality-specific semantic tasks in 86 patients with brain damage. We observed that the left anterior temporal lobe and bilateral anterior cingulate cortex could be semantic hubs because their decreased nodal degree values were significantly correlated with the severity of the deficit in semantic performance. The two hub regions might contribute to semantic representational and control processes, respectively. These findings offer new evidence for the distributed-plus-hub theory.

The neuro-cognitive representations of symbols: the case of concrete words

We live our lives surrounded by symbols (e.g., road signs, logos, but especially words and numbers), and throughout our life we use them to evoke, communicate and reflect upon ideas and things that are not currently present to our senses. Symbols are represented in our brains at different levels of complexity: at the first and most simple level, as physical entities, in the corresponding primary and secondary sensory cortices. The crucial property of symbols, however, is that, despite the simplicity of their surface forms, they have the power of evoking higher order multifaceted representations that are implemented in distributed neural networks spanning a large portion of the cortex. The rich internal states that reflect our knowledge of the meaning of symbols are what we call semantic representations. In this review paper, we summarize our current knowledge of both the cognitive and neural substrates of semantic representations, focusing on concrete words (i.e., nouns or verbs referring to concrete objects and actions), which, together with numbers, are the most-studied and well defined classes of symbols. Following a systematic descriptive approach, we will organize this literature review around two key questions: what is the content of semantic representations? And, how are semantic representations implemented in the brain, in terms of localization and dynamics? While highlighting the main current opposing perspectives on these topics, we propose that a fruitful way to make substantial progress in this domain would be to adopt a geometrical view of semantic representations as points in high dimensional space, and to operationally partition the space of concrete word meaning into motor-perceptual and conceptual dimensions. By giving concrete examples of the kinds of research that can be done within this perspective, we illustrate how we believe this framework will foster theoretical speculations as well as empirical research.

Task-context-dependent Linear Representation of Multiple Visual Objects in Human Parietal Cortex

A host of recent studies have reported robust representations of visual object information in the human parietal cortex, similar to those found in ventral visual cortex. In ventral visual cortex, both monkey neurophysiology and human fMRI studies showed that the neural representation of a pair of unrelated objects can be approximated by the averaged neural representation of the constituent objects shown in isolation. In this study, we examined whether such a linear relationship between objects exists for object representations in the human parietal cortex. Using fMRI and multivoxel pattern analysis, we examined object representations in human inferior and superior intraparietal sulcus, two parietal regions previously implicated in visual object selection and encoding, respectively. We also examined responses from the lateral occipital region, a ventral object processing area. We obtained fMRI response patterns to object pairs and their constituent objects shown in isolation while participants viewed these objects and performed a 1-back repetition detection task. By measuring fMRI response pattern correlations, we found that all three brain regions contained representations for both single object and object pairs. In the lateral occipital region, the representation for a pair of objects could be reliably approximated by the average representation of its constituent objects shown in isolation, replicating previous findings in ventral visual cortex. Such a simple linear relationship, however, was not observed in either parietal region examined. Nevertheless, when we equated the amount of task information present by examining responses from two pairs of objects, we found that representations for the average of two object pairs were indistinguishable in both parietal regions from the average of another two object pairs containing the same four component objects but with a different pairing of the objects (i.e., the average of AB and CD vs. that of AD and CB). Thus, when task information was held consistent, the same linear relationship may govern how multiple independent objects are represented in the human parietal cortex as it does in ventral visual cortex. These findings show that object and task representations coexist in the human parietal cortex and characterize one significant difference of how visual information may be represented in ventral visual and parietal regions.

Taxonomic and thematic semantic systems

Object concepts are critical for nearly all aspects of human cognition, from perception tasks like object recognition, to understanding and producing language, to making meaningful actions. Concepts can have 2 very different kinds of relations: similarity relations based on shared features (e.g., dog-bear), which are called "taxonomic" relations, and contiguity relations based on co-occurrence in events or scenarios (e.g., dog-leash), which are called "thematic" relations. Here, we report a systematic review of experimental psychology and cognitive neuroscience evidence of this distinction in the structure of semantic memory. We propose 2 principles that may drive the development of distinct taxonomic and thematic semantic systems: differences between which features determine taxonomic versus thematic relations, and differences in the processing required to extract taxonomic versus thematic relations. This review brings together distinct threads of behavioral, computational, and neuroscience research on semantic memory in support of a functional and neural dissociation, and defines a framework for future studies of semantic memory. (PsycINFO Database Record

Dynamic neural architecture for social knowledge retrieval

Social behavior is often shaped by the rich storehouse of biographical information that we hold for other people. In our daily life, we rapidly and flexibly retrieve a host of biographical details about individuals in our social network, which often guide our decisions as we navigate complex social interactions. Even abstract traits associated with an individual, such as their political affiliation, can cue a rich cascade of person-specific knowledge. Here, we asked whether the anterior temporal lobe (ATL) serves as a hub for a distributed neural circuit that represents person knowledge. Fifty participants across two studies learned biographical information about fictitious people in a 2-d training paradigm. On day 3, they retrieved this biographical information while undergoing an fMRI scan. A series of multivariate and connectivity analyses suggest that the ATL stores abstract person identity representations. Moreover, this region coordinates interactions with a distributed network to support the flexible retrieval of person attributes. Together, our results suggest that the ATL is a central hub for representing and retrieving person knowledge.

Tracking competition and cognitive control during language comprehension with multi-voxel pattern analysis

To successfully comprehend a sentence that contains a homonym, readers must select the ambiguous word's context-appropriate meaning. The outcome of this process is influenced both by top-down contextual support and bottom-up, word-specific characteristics. We examined how these factors jointly affect the neural signatures of lexical ambiguity resolution. We measured the similarity between multi-voxel patterns evoked by the same homonym in two distinct linguistic contexts: once after subjects read sentences that biased interpretation toward each homonym's most frequent, dominant meaning, and again after interpretation was biased toward a weaker, subordinate meaning. We predicted that, following a subordinate-biasing context, the dominant yet inappropriate meaning would nevertheless compete for activation, manifesting in increased similarity between the neural patterns evoked by the two word meanings. In left anterior temporal lobe (ATL), degree of within-word pattern similarity was positively predicted by the association strength of each homonym's dominant meaning. Further, within-word pattern similarity in left ATL was negatively predicted by item-specific responses in a region of left ventrolateral prefrontal cortex (VLPFC) sensitive to semantic conflict. These findings have implications for psycholinguistic models of lexical ambiguity resolution, and for the role of left VLPFC function during this process. Moreover, these findings demonstrate the utility of item-level, similarity-based analyses of fMRI data for our understanding of competition between co-activated word meanings during language comprehension.

Feature-selective Attention in Frontoparietal Cortex: Multivoxel Codes Adjust to Prioritize Task-relevant Information

Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the “adaptive coding hypothesis” [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820–829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.

Visual search for object categories is predicted by the representational architecture of high-level visual cortex

Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system.

NEW & NOTEWORTHY

Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex underlying visual object processing.

The neural and computational bases of semantic cognition

Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This Review summarizes key findings and issues arising from a decade of research into the neurocognitive and neurocomputational underpinnings of this ability, leading to a new framework that we term controlled semantic cognition (CSC). CSC offers solutions to long-standing queries in philosophy and cognitive science, and yields a convergent framework for understanding the neural and computational bases of healthy semantic cognition and its dysfunction in brain disorders.

The rTPJ's overarching cognitive function in networks for attention and theory of mind

Cortical networks underpinning attentional control and mentalizing converge at the right temporoparietal junction (rTPJ). It is debated whether the rTPJ is fractionated in neighboring, but separate functional modules underpinning attentional control and mentalizing, or whether one overarching cognitive mechanism explains the rTPJ's role in both domains. Addressing this question, we combined attentional control and mentalizing in a factorial design within one task. We added a social context condition, in which another individual's mental states became apparently task-relevant, to a spatial cueing paradigm. This allowed for assessing cue validity- and context-dependent functional activity and effective connectivity of the rTPJ within corresponding cortical networks. We found two discriminable rTPJ subregions, an anterior and a posterior one. Yet, we did not observe a sharp functional dissociation between these two, as both regions responded to attention cueing and social context manipulation. The results suggest that the rTPJ is part of both the ventral attention and the ToM network and that its function is defined by context-dependent coupling with the respective network. We argue that the rTPJ as a functional unit underpins an overarching cognitive mechanism in attentional control and mentalizing and discuss how the present results help to further specify this mechanism.