The representation of object concepts in the brain

Distributed representations of behavior-derived object dimensions in the human visual system

Object vision is commonly thought to involve a hierarchy of brain regions processing increasingly complex image features, with high-level visual cortex supporting object recognition and categorization. However, object vision supports diverse behavioral goals, suggesting basic limitations of this category-centric framework. To address these limitations, we mapped a series of dimensions derived from a large-scale analysis of human similarity judgments directly onto the brain. Our results reveal broadly distributed representations of behaviorally-relevant information, demonstrating selectivity to a wide variety of novel dimensions while capturing known selectivities for visual features and categories. Behavior-derived dimensions were superior to categories at predicting brain responses, yielding mixed selectivity in much of visual cortex and sparse selectivity in category-selective clusters. This framework reconciles seemingly disparate findings regarding regional specialization, explaining category selectivity as a special case of sparse response profiles among representational dimensions, suggesting a more expansive view on visual processing in the human brain.

Brain-wide representation of social knowledge

Understanding how the human brain maps different dimensions of social conceptualizations remains a key unresolved issue. We performed a functional magnetic resonance imaging (MRI) study in which participants were exposed to audio definitions of personality traits and asked to simulate experiences associated with the concepts. Half of the concepts were affective (e.g. empathetic), and the other half were non-affective (e.g. intelligent). Orthogonally, half of the concepts were highly likable (e.g. sincere) and half were socially undesirable (e.g. liar). Behaviourally, we observed that the dimension of social desirability reflected the participant's subjective ratings better than affect. FMRI decoding results showed that both social desirability and affect could be decoded in local patterns of activity through distributed brain regions including the superior temporal, inferior frontal, precuneus and key nodes of the default mode network in posterior/anterior cingulate and ventromedial prefrontal cortex. Decoding accuracy was better for social desirability than affect. A representational similarity analysis further demonstrated that a deep language model significantly predicted brain activity associated with the concepts in bilateral regions of superior and anterior temporal lobes. The results demonstrate a brain-wide representation of social knowledge, involving default model network systems that support the multimodal simulation of social experience, with a further reliance on language-related preprocessing.

The prediction potential indexes the meaning and communicative function of upcoming utterances

Prediction has a fundamental role in language processing. However, predictions can be made at different levels, and it is not always clear whether speech sounds, morphemes, words, meanings, or communicative functions are anticipated during dialogues. Previous studies reported specific brain signatures of communicative pragmatic function, in particular enhanced brain responses immediately after encountering an utterance used to request an object from a partner, but relatively smaller ones when the same utterance was used for naming the object. The present experiment now investigates whether similar neuropragmatic signatures emerge in recipients before the onset of upcoming utterances carrying different predictable communicative functions. Trials started with a context question and object pictures displayed on the screen, raising the participant's expectation that words from a specific semantic category (food or tool) would subsequently be used to either name or request one of the objects. Already 600 msec before utterance onset, a larger prediction potential was observed when a request was anticipated relative to naming expectation. As this result is congruent with the neurophysiological difference previously observed right after the critical utterance, the anticipatory brain activity may index predictions about the social-communicative function of upcoming utterances. In addition, we also found that the predictable semantic category of the upcoming word was likewise reflected in the anticipatory brain potential. Thus, the neurophysiological characteristics of the prediction potential can capture different types of upcoming linguistic information, including semantic and pragmatic aspects of an upcoming utterance and communicative action.

Drawing from name in semantic dementia reveals graded object knowledge representations in anterior temporal lobe

Semantic dementia (SD) is characterized by progressive impairment in conceptual knowledge due to anterior temporal lobe (ATL) neurodegeneration. Extended neuropsychological assessments can quantitatively demonstrate the semantic impairment, but this graded loss of knowledge can also be readily observed in the qualitative observation of patients' recall of single concepts. Here, we present the results of a simple task of object drawing-from-name, by patients with SD (N = 19), who have isolated atrophy of the ATL bilaterally. Both cross-sectionally and longitudinally, patient drawings demonstrated a pattern of degradation in which rare and distinctive features (such as the hump on a camel) were lost earliest in disease course, and there was an increase in the intrusion of prototypical features (such as the typical small ears of most mammals on an elephant) with more advanced disease. Crucially, patient drawings showed a continuum of conceptual knowledge loss rather than a binary 'present' or 'absent' state. Overall, we demonstrate that qualitative evaluation of line drawings of animals and objects provides fascinating insights into the transmodal semantic deficit in SD. Our results are consistent with a distributed-plus-hub model of semantic memory. The graded nature of the deficit in semantic performance observed in our subset of longitudinally observed patients suggests that the temporal lobe binds feature-based semantic attributes in its central convergence zone.

Graded and sharp transitions in semantic function in left temporal lobe

Recent work has focussed on how patterns of functional change within the temporal lobe relate to whole-brain dimensions of intrinsic connectivity variation (Margulies et al., 2016). We examined two such 'connectivity gradients' reflecting the separation of (i) unimodal versus heteromodal and (ii) visual versus auditory-motor cortex, examining visually presented verbal associative and feature judgments, plus picture-based context and emotion generation. Functional responses along the first dimension sometimes showed graded change between modality-tuned and heteromodal cortex (in the verbal matching task), and other times showed sharp functional transitions, with deactivation at the extremes and activation in the middle of this gradient (internal generation). The second gradient revealed more visual than auditory-motor activation, regardless of content (associative, feature, context, emotion) or task process (matching/generation). We also uncovered subtle differences across each gradient for content type, which predominantly manifested as differences in relative magnitude of activation or deactivation.

Understanding behavioral and cognitive dispositions as subsystem topologies within cognitive models: A proposal

In our 2023 paper, entitled "Modeling interactions between the embodied and the narrative self: Dynamics of the self-pattern within LIDA," Kugele, Newen, Franklin, and I propose a functional description and implementation of a central element of Gallagher & Newen's pattern theory of self, which identifies an agent's self with a dynamic pattern of so-called cognitive aspects which govern their thought and behavior (Gallagher, 2013; Newen, 2018; Gallagher & Daly, 2018). The pattern theory explicitly rejects the traditional conceptualization of the self as a unitary entity with certain properties that resides within agents, with the idea of a pattern of aspects being central to its ability to account for the dynamic, yet relatively stable development of most natural agents' selves. Implementing the pattern theory within Learning Intelligent Distribution Agent revealed that, in order for a cognitive architecture to account for both the dynamic and stable nature of an agent's self-pattern, aspects of that pattern had to be realized by dispositions of the agent to either think or act in a certain way. In this commentary, I argue that this fundamental role of dispositions extends to cognitive processes in general and that cognitive systems should be understood in terms of the dynamical interactions of dispositions over time. In order to facilitate such an understanding, dispositions will have to be identified with topologies of cognitive (sub)systems. I provide an example of such a topology by reference to informational topologies in neuronal systems.

Feats: A database of semantic features for early produced noun concepts

Semantic feature production norms have several desirable characteristics that have supported models of representation and processing in adults. However, several key challenges have limited the use of semantic feature norms in studies of early language acquisition. First, existing norms provide uneven and inconsistent coverage of early-acquired concepts that are typically produced and assessed in children under the age of three, which is a time of tremendous growth of early vocabulary skills. Second, it is difficult to assess the degree to which young children may be familiar with normed features derived from these adult-generated datasets. Third, it has been difficult to adopt standard methods to generate semantic network models of early noun learning. Here, we introduce Feats-a tool that was designed to make headway on these challenges by providing a database, the Language Learning and Meaning Acquisition (LLaMA) lab Noun Norms that extends a widely used set of feature norms McRae et al. Behavior Research Methods 37, 547-559, (2005) to include full coverage of noun concepts on a commonly used early vocabulary assessment. Feats includes several tools to facilitate exploration of features comprising early-acquired nouns, assess the developmental appropriateness of individual features using toddler-accessibility norms, and extract semantic network statistics for individual vocabulary profiles. We provide a tutorial overview of Feats. We additionally validate our approach by presenting an analysis of an overlapping set of concepts collected across prior and new data collection methods. Furthermore, using network graph analyses, we show that the extended set of norms provides novel, reliable results given their enhanced coverage.

Characterizing the discriminability of visual categorical information in strongly connected voxels

Functional brain responses are strongly influenced by connectivity. Recently, we demonstrated a major example of this: category discriminability within occipitotemporal cortex (OTC) is enhanced for voxel sets that share strong functional connectivity to distal brain areas, relative to those that share lesser connectivity. That is, within OTC regions, sets of 'most-connected' voxels show improved multivoxel pattern discriminability for tool-, face-, and place stimuli relative to voxels with weaker connectivity to the wider brain. However, understanding whether these effects generalize to other domains (e.g. body perception network), and across different levels of the visual processing streams (e.g. dorsal as well as ventral stream areas) is an important extension of this work. Here, we show that this so-called connectivity-guided decoding (CGD) effect broadly generalizes across a wide range of categories (tools, faces, bodies, hands, places). This effect is robust across dorsal stream areas, but less consistent in earlier ventral stream areas. In the latter regions, category discriminability is generally very high, suggesting that extraction of category-relevant visual properties is less reliant on connectivity to downstream areas. Further, CGD effects are primarily expressed in a category-specific manner: For example, within the network of tool regions, discriminability of tool information is greater than non-tool information. The connectivity-guided decoding approach shown here provides a novel demonstration of the crucial relationship between wider brain connectivity and complex local-level functional responses at different levels of the visual processing streams. Further, this approach generates testable new hypotheses about the relationships between connectivity and local selectivity.

Four fundamental dimensions underlie the perception of human actions

We evaluate the actions of other individuals based upon a variety of movements that reveal critical information to guide decision making and behavioural responses. These signals convey a range of information about the actor, including their goals, intentions and internal mental states. Although progress has been made to identify cortical regions involved in action processing, the organising principles underlying our representation of actions still remains unclear. In this paper we investigated the conceptual space that underlies action perception by assessing which qualities are fundamental to the perception of human actions. We recorded 240 different actions using motion-capture and used these data to animate a volumetric avatar that performed the different actions. 230 participants then viewed these actions and rated the extent to which each action demonstrated 23 different action characteristics (e.g., avoiding-approaching, pulling-pushing, weak-powerful). We analysed these data using Exploratory Factor Analysis to examine the latent factors underlying visual action perception. The best fitting model was a four-dimensional model with oblique rotation. We named the factors: friendly-unfriendly, formidable-feeble, planned-unplanned, and abduction-adduction. The first two factors of friendliness and formidableness explained approximately 22% of the variance each, compared to planned and abduction, which explained approximately 7-8% of the variance each; as such we interpret this representation of action space as having 2 + 2 dimensions. A closer examination of the first two factors suggests a similarity to the principal factors underlying our evaluation of facial traits and emotions, whilst the last two factors of planning and abduction appear unique to actions.

Manipulating objects during learning shrinks the global scale of spatial representations in memory: a virtual reality study

Goal-directed approaches to perception usually consider that distance perception is shaped by the body and its potential for interaction. Although this phenomenon has been extensively investigated in the field of perception, little is known about the effect of motor interactions on memory, and how they shape the global representation of large-scale spaces. To investigate this question, we designed an immersive virtual reality environment in which participants had to learn the positions of several items. Half of the participants had to physically (but virtually) grab the items with their hand and drop them at specified locations (active condition). The other half of the participants were simply shown the items which appeared at the specified position without interacting with them (passive condition). Half of the items used during learning were images of manipulable objects, and the other half were non manipulable objects. Participants were subsequently asked to draw a map of the virtual environment from memory, and to position all the items in it. Results show that active participants recalled the global shape of the spatial layout less precisely, and made more absolute distance errors than passive participants. Moreover, global scaling compression bias was higher for active participants than for passive participants. Interestingly, manipulable items showed a greater compression bias compared to non-manipulable items, yet they had no effect on correlation scores and absolute non-directional distance errors. These results are discussed according to grounded approaches of spatial cognition, emphasizing motor simulation as a possible mechanism for position retrieval from memory.

Neural substrates of specific and general autobiographical memory retrieval in younger and older adults

Healthy aging is associated with a shift away from the retrieval of specific episodic autobiographical memories (AMs), towards more general and semanticized memories. Younger adults modulate activity in the default mode network according to the episodic specificity of AM retrieval. However, little is known about whether aging disrupts this neural modulation. In the current study we examine age-related changes in the modulation of whole-brain networks in response to three tasks falling along a gradient of episodic specificity. Younger and older adults retrieved specific (unique) AMs, general (routine) AMs, and semantic (general knowledge) memories. We found that both younger and older adults modulated default mode regions in response to varying episodic specificity. In addition, younger adults upregulated activity in several default mode regions with increasing episodic specificity, while older adults either did not modulate these regions, or downregulated activity in these regions. In contrast, older adults upregulated activity in the left temporal pole for tasks with higher episodic specificity. These brain activation patterns converge with prior findings that specific AMs are diminished in episodic richness with age, but are supplemented with conceptual and general information. Age-related reductions in the modulation of default mode regions might contribute to the shift away from episodic retrieval and towards semantic retrieval, resulting in reduced episodic specificity of personal memories.

Effect of Object on Kinesthetic Motor Imagery in Autism Spectrum Disorder: A Pilot Study Based on Eye-Tracking Methodology

Introduction

Social disturbance is a significant autism spectrum disorder (ASD) symptom. Action representation, which is a fundamental component of social interaction, can be investigated through kinesthetic motor imagery (KMI). KMI has been commonly studied with the well-developed laterality judgment paradigm, wherein participants are required to discriminate the laterality of a hand rotated by different angles along one or more axes. Here, we investigated the KMI processing in individuals with ASD by hand laterality judgment paradigm with eye-tracking methodology.

Methods

The current study included 22 participants with ASD and 22 typical developing (TD) peers matched for age, gender, and intelligence. Participants were asked to judge the laterality of hand-with-tooth brush images.

Results

Compared to the TD controls, individuals with ASD performed KMI with lower accuracy and longer response time in both correct and incorrect action conditions. The incorrect action representation had greater effect on KMI for individuals with ASD. Differences in eye-movement patterns were also observed, characterized by individuals with ASD were more focused on the object area while TD peers were more focused on the hand area.

Conclusion

Results suggest that while altered KMI performance was observed, the incorrect action representation elicited more engagement of KMI in both groups. The object-centered eye-movement pattern may contribute to the refine of motor simulation intervention for individuals with ASD.

The Geometry of Low- and High-Level Perceptual Spaces

Low-level features are typically continuous (e.g., the gamut between two colors), but semantic information is often categorical (there is no corresponding gradient between dog and turtle) and hierarchical (animals live in land, water, or air). To determine the impact of these differences on cognitive representations, we characterized the geometry of perceptual spaces of five domains: a domain dominated by semantic information (animal names presented as words), a domain dominated by low-level features (colored textures), and three intermediate domains (animal images, lightly texturized animal images that were easy to recognize, and heavily texturized animal images that were difficult to recognize). Each domain had 37 stimuli derived from the same animal names. From 13 participants (9F), we gathered similarity judgments in each domain via an efficient psychophysical ranking paradigm. We then built geometric models of each domain for each participant, in which distances between stimuli accounted for participants' similarity judgments and intrinsic uncertainty. Remarkably, the five domains had similar global properties: each required 5-7 dimensions, and a modest amount of spherical curvature provided the best fit. However, the arrangement of the stimuli within these embeddings depended on the level of semantic information: dendrograms derived from semantic domains (word, image, and lightly texturized images) were more "tree-like" than those from feature-dominated domains (heavily texturized images and textures). Thus, the perceptual spaces of domains along this feature-dominated to semantic-dominated gradient shift to a tree-like organization when semantic information dominates, while retaining a similar global geometry.

Neural processing of prototypicality and simplicity of product design in forming design preferences

The current study investigates the neural correlates when processing prototypicality and simplicity-affecting the preference of product design. Despite its significance, not much is known about how our brain processes these visual qualities of design when forming design preferences. We posit that, although fluency is the perceptual judgment accounting for the positive effects of both prototypicality and simplicity on design preference, the neural substrates for the fluency judgment associated with prototypicality would differ from those associated with simplicity. To investigate these issues, we conducted an fMRI study of preference decisions for actual product designs with different levels of prototypicality and simplicity. The results show a significant functional gradient between the preference processing of simplicity and prototypicality-i.e., involvement of the early ventral stream of visual information processing for simplicity evaluation but recruitment of the late ventral stream and parietal-frontal brain regions for prototypicality evaluation. The interaction between the simplicity and prototypicality evaluations was found in the extrastriate cortex in the right hemisphere. The segregated brain involvements suggest that the fluency judgment for prototypicality and simplicity contribute to preference choice in different levels of cognitive hierarchy in the perceptual mechanism of the design preference.

Language with vision: A study on grounded word and sentence embeddings

Grounding language in vision is an active field of research seeking to construct cognitively plausible word and sentence representations by incorporating perceptual knowledge from vision into text-based representations. Despite many attempts at language grounding, achieving an optimal equilibrium between textual representations of the language and our embodied experiences remains an open field. Some common concerns are the following. Is visual grounding advantageous for abstract words, or is its effectiveness restricted to concrete words? What is the optimal way of bridging the gap between text and vision? To what extent is perceptual knowledge from images advantageous for acquiring high-quality embeddings? Leveraging the current advances in machine learning and natural language processing, the present study addresses these questions by proposing a simple yet very effective computational grounding model for pre-trained word embeddings. Our model effectively balances the interplay between language and vision by aligning textual embeddings with visual information while simultaneously preserving the distributional statistics that characterize word usage in text corpora. By applying a learned alignment, we are able to indirectly ground unseen words including abstract words. A series of evaluations on a range of behavioral datasets shows that visual grounding is beneficial not only for concrete words but also for abstract words, lending support to the indirect theory of abstract concepts. Moreover, our approach offers advantages for contextualized embeddings, such as those generated by BERT (Devlin et al, 2018), but only when trained on corpora of modest, cognitively plausible sizes. Code and grounded embeddings for English are available at ( https://github.com/Hazel1994/Visually_Grounded_Word_Embeddings_2 ).

Temporal differences and commonalities between hand and tool neural processing

Object recognition is a complex cognitive process that relies on how the brain organizes object-related information. While spatial principles have been extensively studied, less studied temporal dynamics may also offer valuable insights into this process, particularly when neural processing overlaps for different categories, as it is the case of the categories of hands and tools. Here we focus on the differences and/or similarities between the time-courses of hand and tool processing under electroencephalography (EEG). Using multivariate pattern analysis, we compared, for different time points, classification accuracy for images of hands or tools when compared to images of animals. We show that for particular time intervals (~ 136-156 ms and ~ 252-328 ms), classification accuracy for hands and for tools differs. Furthermore, we show that classifiers trained to differentiate between tools and animals generalize their learning to classification of hand stimuli between ~ 260-320 ms and ~ 376-500 ms after stimulus onset. Classifiers trained to distinguish between hands and animals, on the other hand, were able to extend their learning to the classification of tools at ~ 150 ms. These findings suggest variations in semantic features and domain-specific differences between the two categories, with later-stage similarities potentially related to shared action processing for hands and tools.

A neural network model of hippocampal contributions to category learning

In addition to its critical role in encoding individual episodes, the hippocampus is capable of extracting regularities across experiences. This ability is central to category learning, and a growing literature indicates that the hippocampus indeed makes important contributions to this form of learning. Using a neural network model that mirrors the anatomy of the hippocampus, we investigated the mechanisms by which the hippocampus may support novel category learning. We simulated three category learning paradigms and evaluated the network's ability to categorize and recognize specific exemplars in each. We found that the trisynaptic pathway within the hippocampus-connecting entorhinal cortex to dentate gyrus, CA3, and CA1-was critical for remembering exemplar-specific information, reflecting the rapid binding and pattern separation capabilities of this circuit. The monosynaptic pathway from entorhinal cortex to CA1, in contrast, specialized in detecting the regularities that define category structure across exemplars, supported by the use of distributed representations and a relatively slower learning rate. Together, the simulations provide an account of how the hippocampus and its constituent pathways support novel category learning.

Cortical time-course of evidence accumulation during semantic processing

Our understanding of the surrounding world and communication with other people are tied to mental representations of concepts. In order for the brain to recognize an object, it must determine which concept to access based on information available from sensory inputs. In this study, we combine magnetoencephalography and machine learning to investigate how concepts are represented and accessed in the brain over time. Using brain responses from a silent picture naming task, we track the dynamics of visual and semantic information processing, and show that the brain gradually accumulates information on different levels before eventually reaching a plateau. The timing of this plateau point varies across individuals and feature models, indicating notable temporal variation in visual object recognition and semantic processing.

On the functional brain networks involved in tool-related action understanding

Tool-use skills represent a significant cognitive leap in human evolution, playing a crucial role in the emergence of complex technologies. Yet, the neural mechanisms underlying such capabilities are still debated. Here we explore with fMRI the functional brain networks involved in tool-related action understanding. Participants viewed images depicting action-consistent (e.g., nail-hammer) and action-inconsistent (e.g., scarf-hammer) object-tool pairs, under three conditions: semantic (recognizing the tools previously seen in the pairs), mechanical (assessing the usability of the pairs), and control (looking at the pairs without explicit tasks). During the observation of the pairs, task-based left-brain functional connectivity differed within conditions. Compared to the control, both the semantic and mechanical conditions exhibited co-activations in dorsal (precuneus) and ventro-dorsal (inferior frontal gyrus) regions. However, the semantic condition recruited medial and posterior temporal areas, whereas the mechanical condition engaged inferior parietal and posterior temporal regions. Also, when distinguishing action-consistent from action-inconsistent pairs, an extensive frontotemporal neural circuit was activated. These findings support recent accounts that view tool-related action understanding as the combined product of semantic and mechanical knowledge. Furthermore, they emphasize how the left inferior parietal and anterior temporal lobes might be considered as hubs for the cross-modal integration of physical and conceptual knowledge, respectively.

Neurobiological mechanisms for language, symbols and concepts: Clues from brain-constrained deep neural networks

Neural networks are successfully used to imitate and model cognitive processes. However, to provide clues about the neurobiological mechanisms enabling human cognition, these models need to mimic the structure and function of real brains. Brain-constrained networks differ from classic neural networks by implementing brain similarities at different scales, ranging from the micro- and mesoscopic levels of neuronal function, local neuronal links and circuit interaction to large-scale anatomical structure and between-area connectivity. This review shows how brain-constrained neural networks can be applied to study in silico the formation of mechanisms for symbol and concept processing and to work towards neurobiological explanations of specifically human cognitive abilities. These include verbal working memory and learning of large vocabularies of symbols, semantic binding carried by specific areas of cortex, attention focusing and modulation driven by symbol type, and the acquisition of concrete and abstract concepts partly influenced by symbols. Neuronal assembly activity in the networks is analyzed to deliver putative mechanistic correlates of higher cognitive processes and to develop candidate explanations founded in established neurobiological principles.

Minor Changes Change Memories: Functional Magnetic Resonance Imaging and Behavioral Reflections of Episodic Prediction Errors

Episodic memories can be modified, a process that is potentially driven by mnemonic prediction errors. In the present study, we used modified cues to induce prediction errors of different episodic relevance. Participants encoded episodes in the form of short toy stories and then returned for an fMRI session on the subsequent day. Here, participants were presented either original episodes or slightly modified versions thereof. Modifications consisted of replacing a single object within the episode and either challenged the gist of an episode (gist modifications) or left it intact (surface modifications). On the next day, participants completed a post-fMRI memory test that probed memories for originally encoded episodes. Both types of modifications triggered brain activation in regions we previously found to be involved in the processing of content-based mnemonic prediction errors (i.e., the exchange of an object). Specifically, these were ventrolateral pFC, intraparietal cortex, and lateral occipitotemporal cortex. In addition, gist modifications triggered pronounced brain responses, whereas those for surface modification were only significant in the right inferior frontal sulcus. Processing of gist modifications also involved the posterior temporal cortex and the precuneus. Interestingly, our findings confirmed the posterior hippocampal role of detail processing in episodic memory, as evidenced by increased posterior hippocampal activity for surface modifications compared with gist modifications. In the post-fMRI memory test, previous experience with surface modified, but not gist-modified episodes, increased erroneous acceptance of the same modified versions as originally encoded. Whereas surface-level prediction errors might increase uncertainty and facilitate confusion of alternative episode representations, gist-level prediction errors seem to trigger the clear distinction of independent episodes.

Mechanisms and neuroanatomy of response selection in tool and non-tool action tasks: Evidence from left-hemisphere stroke

The ability to select between potential actions is central to the complex process of tool use. After left hemisphere stroke, individuals with limb apraxia make more hand action errors when gesturing the use of tools with conflicting hand actions for grasping-to-move and use (e.g., screwdriver) relative to tools that are grasped-to-move and used with the same hand action (e.g., hammer). Prior research indicates that this grasp-use interference effect is driven by abnormalities in the competitive action selection process. The goal of this project was to determine whether common mechanisms and neural substrates support the competitive selection of task-appropriate responses in both tool and non-tool domains. If so, the grasp-use interference effect in a tool use gesturing task should be correlated with response interference effects in the classic Eriksen flanker and Simon tasks, and at least partly overlapping neural regions should subserve the 3 tasks. Sixty-four left hemisphere stroke survivors (33 with apraxia) participated in the tool- and non-tool interference tasks and underwent T1 anatomical MRI. There were robust grasp-use interference effects (grasp-use conflict test) and response interference effects (Eriksen flanker and Simon tasks), but these effects were not correlated. Lesion-symptom mapping analyses showed that lesions to the left inferior parietal lobule, ventral premotor cortex, and insula were associated with grasp-use interference. Lesions to the left inferior parietal lobule, postcentral gyrus, insula, caudate, and putamen were associated with response interference in the Eriksen flanker task. Lesions to the left caudate and putamen were also associated with response interference in the Simon task. Our results suggest that the selection of hand posture for tool use is mediated by distinct cognitive mechanisms and partly distinct neuroanatomic substrates from those mapping a stimulus to an appropriate motor response in non-tool domains.

A common neural code for meaning in discourse production and comprehension

How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.

Neural and behavioral signatures of the multidimensionality of manipulable object processing

Understanding how we recognize objects requires unravelling the variables that govern the way we think about objects and the neural organization of object representations. A tenable hypothesis is that the organization of object knowledge follows key object-related dimensions. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the decisions we typically engage in our daily lives - e.g., identifying a hammer in the context of other tools. We extracted object-related dimensions from subjective human judgments on a set of manipulable objects. We show that the extracted dimensions are cognitively interpretable and relevant - i.e., participants are able to consistently label them, and these dimensions can guide object categorization; and are important for the neural organization of knowledge - i.e., they predict neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of manipulable object knowledge.

Integration of event experiences to build relational knowledge in the human brain

We investigated how the human brain integrates experiences of specific events to build general knowledge about typical event structure. We examined an episodic memory area important for temporal relations, anterior-lateral entorhinal cortex, and a semantic memory area important for action concepts, middle temporal gyrus, to understand how and when these areas contribute to these processes. Participants underwent functional magnetic resonance imaging while learning and recalling temporal relations among novel events over two sessions 1 week apart. Across distinct contexts, individual temporal relations among events could either be consistent or inconsistent with each other. Within each context, during the recall phase, we measured associative coding as the difference of multivoxel correlations among related vs unrelated pairs of events. Neural regions that form integrative representations should exhibit stronger associative coding in the consistent than the inconsistent contexts. We found evidence of integrative representations that emerged quickly in anterior-lateral entorhinal cortex (at session 1), and only subsequently in middle temporal gyrus, which showed a significant change across sessions. A complementary pattern of findings was seen with signatures during learning. This suggests that integrative representations are established early in anterior-lateral entorhinal cortex and may be a pathway to the later emergence of semantic knowledge in middle temporal gyrus.

Transcranial Direct Current Stimulation Effects on the Neural Substrate of Conceptual Representations

The aim of this study was to shed light on the neural substrate of conceptual representations starting from the construct of higher-order convergence zones and trying to evaluate the unitary or non-unitary nature of this construct. We used the 'Thematic and Taxonomic Semantic (TTS) task' to investigate (a) the neural substrate of stimuli belonging to biological and artifact categories, (b) the format of stimuli presentation, i.e., verbal or pictorial, and (c) the relation between stimuli, i.e., categorial or contextual. We administered anodal transcranial direct current stimulation (tDCS) to different brain structures during the execution of the TTS task. Twenty healthy participants were enrolled and divided into two groups, one investigating the role of the anterior temporal lobes (ATL) and the other the temporo-parietal junctions (TPJ). Each participant underwent three sessions of stimulation to facilitate a control condition and to investigate the role of both hemispheres. Results showed that ATL stimulation influenced all conceptual representations in relation to the format of presentation (i.e., left-verbal and right-pictorial). Moreover, ATL stimulation modulated living categories and taxonomic relations specifically, whereas TPJ stimulation did not influence semantic task performances.

Cortical topographic motifs emerge in a self-organized map of object space

The human ventral visual stream has a highly systematic organization of object information, but the causal pressures driving these topographic motifs are highly debated. Here, we use self-organizing principles to learn a topographic representation of the data manifold of a deep neural network representational space. We find that a smooth mapping of this representational space showed many brain-like motifs, with a large-scale organization by animacy and real-world object size, supported by mid-level feature tuning, with naturally emerging face- and scene-selective regions. While some theories of the object-selective cortex posit that these differently tuned regions of the brain reflect a collection of distinctly specified functional modules, the present work provides computational support for an alternate hypothesis that the tuning and topography of the object-selective cortex reflect a smooth mapping of a unified representational space.

Changes in Functional Connectivity of Hippocampal Subregions in Patients with Obstructive Sleep Apnea after Six Months of Continuous Positive Airway Pressure Treatment

Previous studies have shown that the structural and functional impairments of hippocampal subregions in patients with obstructive sleep apnea (OSA) are related to cognitive impairment. Continuous positive airway pressure (CPAP) treatment can improve the clinical symptoms of OSA. Therefore, this study aimed to investigate functional connectivity (FC) changes in hippocampal subregions of patients with OSA after six months of CPAP treatment (post-CPAP) and its relationship with neurocognitive function. We collected and analyzed baseline (pre-CPAP) and post-CPAP data from 20 patients with OSA, including sleep monitoring, clinical evaluation, and resting-state functional magnetic resonance imaging. The results showed that compared with pre-CPAP OSA patients, the FC between the right anterior hippocampal gyrus and multiple brain regions, and between the left anterior hippocampal gyrus and posterior central gyrus were reduced in post-CPAP OSA patients. By contrast, the FC between the left middle hippocampus and the left precentral gyrus was increased. The changes in FC in these brain regions were closely related to cognitive dysfunction. Therefore, our findings suggest that CPAP treatment can effectively change the FC patterns of hippocampal subregions in patients with OSA, facilitating a better understanding of the neural mechanisms of cognitive function improvement, and emphasizing the importance of early diagnosis and timely treatment of OSA.

Investigating the Extent to which Distributional Semantic Models Capture a Broad Range of Semantic Relations

Distributional semantic models (DSMs) are a primary method for distilling semantic information from corpora. However, a key question remains: What types of semantic relations among words do DSMs detect? Prior work typically has addressed this question using limited human data that are restricted to semantic similarity and/or general semantic relatedness. We tested eight DSMs that are popular in current cognitive and psycholinguistic research (positive pointwise mutual information; global vectors; and three variations each of Skip-gram and continuous bag of words (CBOW) using word, context, and mean embeddings) on a theoretically motivated, rich set of semantic relations involving words from multiple syntactic classes and spanning the abstract-concrete continuum (19 sets of ratings). We found that, overall, the DSMs are best at capturing overall semantic similarity and also can capture verb-noun thematic role relations and noun-noun event-based relations that play important roles in sentence comprehension. Interestingly, Skip-gram and CBOW performed the best in terms of capturing similarity, whereas GloVe dominated the thematic role and event-based relations. We discuss the theoretical and practical implications of our results, make recommendations for users of these models, and demonstrate significant differences in model performance on event-based relations.

Novel objects with causal event schemas elicit selective responses in tool- and hand-selective lateral occipitotemporal cortex

Tool-selective lateral occipitotemporal cortex (LOTC) responds preferentially to images of tools (hammers, brushes) relative to non-tool objects (clocks, shoes). What drives these responses? Unlike other objects, tools exert effects on their surroundings. We tested whether LOTC responses are influenced by event schemas that denote different temporal relations. Participants learned about novel objects embedded in different event sequences. Causer objects moved prior to the appearance of an environmental event (e.g. stars), while Reactor objects moved after an event. Visual features and motor association were controlled. During functional magnetic resonance imaging, participants viewed still images of the objects. We localized tool-selective LOTC and non-tool-selective parahippocampal cortex (PHC) by contrasting neural responses to images of familiar tools and non-tools. We found that LOTC responded more to Causers than Reactors, while PHC did not. We also measured responses to images of hands, which elicit overlapping responses with tools. Across inferior temporal cortex, voxels' tool and hand selectivity positively predicted a preferential response to Causers. We conclude that an event schema typical of tools is sufficient to drive LOTC and that category-preferential responses across the temporal lobe may reflect relational event structures typical of those domains.

Decoding semantic representations in mind and brain

A key goal for cognitive neuroscience is to understand the neurocognitive systems that support semantic memory. Recent multivariate analyses of neuroimaging data have contributed greatly to this effort, but the rapid development of these novel approaches has made it difficult to track the diversity of findings and to understand how and why they sometimes lead to contradictory conclusions. We address this challenge by reviewing cognitive theories of semantic representation and their neural instantiation. We then consider contemporary approaches to neural decoding and assess which types of representation each can possibly detect. The analysis suggests why the results are heterogeneous and identifies crucial links between cognitive theory, data collection, and analysis that can help to better connect neuroimaging to mechanistic theories of semantic cognition.

A large dataset of semantic ratings and its computational extension

Evidence from psychology and cognitive neuroscience indicates that the human brain's semantic system contains several specific subsystems, each representing a particular dimension of semantic information. Word ratings on these different semantic dimensions can help investigate the behavioral and neural impacts of semantic dimensions on language processes and build computational representations of language meaning according to the semantic space of the human cognitive system. Existing semantic rating databases provide ratings for hundreds to thousands of words, which can hardly support a comprehensive semantic analysis of natural texts or speech. This article reports a large database, the Six Semantic Dimension Database (SSDD), which contains subjective ratings for 17,940 commonly used Chinese words on six major semantic dimensions: vision, motor, socialness, emotion, time, and space. Furthermore, using computational models to learn the mapping relations between subjective ratings and word embeddings, we include the estimated semantic ratings for 1,427,992 Chinese and 1,515,633 English words in the SSDD. The SSDD will aid studies on natural language processing, text analysis, and semantic representation in the brain.

Critical role of the ventral temporal lobe in naming

OBJECTIVE

Lexical retrieval deficits are characteristic of a variety of different neurological disorders. However, the exact substrates responsible for this are not known. We studied a large cohort of patients undergoing surgery in the dominant temporal lobe for medically intractable epilepsy (n = 95) to localize brain regions that were associated with anomia.

METHODS

We performed a multivariate voxel-based lesion-symptom mapping analysis to correlate surgical lesions within the temporal lobe with changes in naming ability. Additionally, we used a surface-based mixed-effects multilevel analysis to estimate group-level broadband gamma activity during naming across a subset of patients with electrocorticographic recordings and integrated these results with lesion-deficit findings.

RESULTS

We observed that ventral temporal regions, centered around the middle fusiform gyrus, were significantly associated with a decline in naming. Furthermore, we found that the ventral aspect of temporal lobectomies was linearly correlated to a decline in naming, with a clinically significant decline occurring once the resection extended 6 cm from the anterior tip of the temporal lobe on the ventral surface. On electrocorticography, the majority of these cortical regions were functionally active following visual processing. These loci coincide with the sites of susceptibility artifacts during echoplanar imaging, which may explain why this region has been previously underappreciated as the locus responsible for postoperative naming deficits.

SIGNIFICANCE

Taken together, these data highlight the crucial contribution of the ventral temporal cortex in naming and its important role in the pathophysiology of anomia following temporal lobe resections. As such, surgical strategies should attempt to preserve this region to mitigate postoperative language deficits.

Compensatory cognition in neurological diseases and aging: A review of animal and human studies

Specialized individual circuits in the brain are recruited for specific functions. Interestingly, multiple neural circuitries continuously compete with each other to acquire the specialized function. However, the dominant among them compete and become the central neural network for that particular function. For example, the hippocampal principal neural circuitries are the dominant networks among many which are involved in learning processes. But, in the event of damage to the principal circuitry, many times, less dominant networks compensate for the primary network. This review highlights the psychopathologies of functional loss and the aspects of functional recuperation in the absence of the hippocampus.

Functionally and structurally distinct fusiform face area(s) in over 1000 participants

The fusiform face area (FFA) is a widely studied region causally involved in face perception. Even though cognitive neuroscientists have been studying the FFA for over two decades, answers to foundational questions regarding the function, architecture, and connectivity of the FFA from a large (N>1000) group of participants are still lacking. To fill this gap in knowledge, we quantified these multimodal features of fusiform face-selective regions in 1053 participants in the Human Connectome Project. After manually defining over 4,000 fusiform face-selective regions, we report five main findings. First, 68.76% of hemispheres have two cortically separate regions (pFus-faces/FFA-1 and mFus-faces/FFA-2). Second, in 26.69% of hemispheres, pFus-faces/FFA-1 and mFus-faces/FFA-2 are spatially contiguous, yet are distinct based on functional, architectural, and connectivity metrics. Third, pFus-faces/FFA-1 is more face-selective than mFus-faces/FFA-2, and the two regions have distinct functional connectivity fingerprints. Fourth, pFus-faces/FFA-1 is cortically thinner and more heavily myelinated than mFus-faces/FFA-2. Fifth, face-selective patterns and functional connectivity fingerprints of each region are more similar in monozygotic than dizygotic twins and more so than architectural gradients. As we share our areal definitions with the field, future studies can explore how structural and functional features of these regions will inform theories regarding how visual categories are represented in the brain.

Functionally and structurally distinct fusiform face area(s) in over 1000 participants

The fusiform face area (FFA) is a widely studied region causally involved in face perception. Even though cognitive neuroscientists have been studying the FFA for over two decades, answers to foundational questions regarding the function, architecture, and connectivity of the FFA from a large (N>1000) group of participants are still lacking. To fill this gap in knowledge, we quantified these multimodal features of fusiform face-selective regions in 1053 participants in the Human Connectome Project. After manually defining over 4,000 fusiform face-selective regions, we report five main findings. First, 68.76% of hemispheres have two cortically separate regions (pFus-faces/FFA-1 and mFus-faces/FFA-2). Second, in 26.69% of hemispheres, pFus-faces/FFA-1 and mFus-faces/FFA-2 are spatially contiguous, yet are distinct based on functional, architectural, and connectivity metrics. Third, pFus-faces/FFA-1 is more face-selective than mFus-faces/FFA-2, and the two regions have distinct functional connectivity fingerprints. Fourth, pFus-faces/FFA-1 is cortically thinner and more heavily myelinated than mFus-faces/FFA-2. Fifth, face-selective patterns and functional connectivity fingerprints of each region are more similar in monozygotic than dizygotic twins and more so than architectural gradients. As we share our areal definitions with the field, future studies can explore how structural and functional features of these regions will inform theories regarding how visual categories are represented in the brain.

Meta-analytic evidence for a novel hierarchical model of conceptual processing

Conceptual knowledge plays a pivotal role in human cognition. Grounded cognition theories propose that concepts consist of perceptual-motor features represented in modality-specific perceptual-motor cortices. However, it is unclear whether conceptual processing consistently engages modality-specific areas. Here, we performed an activation likelihood estimation (ALE) meta-analysis across 212 neuroimaging experiments on conceptual processing related to 7 perceptual-motor modalities (action, sound, visual shape, motion, color, olfaction-gustation, and emotion). We found that conceptual processing consistently engages brain regions also activated during real perceptual-motor experience of the same modalities. In addition, we identified multimodal convergence zones that are recruited for multiple modalities. In particular, the left inferior parietal lobe (IPL) and posterior middle temporal gyrus (pMTG) are engaged for three modalities: action, motion, and sound. These "trimodal" regions are surrounded by "bimodal" regions engaged for two modalities. Our findings support a novel model of the conceptual system, according to which conceptual processing relies on a hierarchical neural architecture from modality-specific to multimodal areas up to an amodal hub.

Structural and functional connectivity of the inferior temporal numeral area

A growing body of evidence suggests that in adults, there is a spatially consistent "inferior temporal numeral area" (ITNA) in the occipitotemporal cortex that appears to preferentially process Arabic digits relative to non-numerical symbols and objects. However, very little is known about why the ITNA is spatially segregated from regions that process other orthographic stimuli such as letters, and why it is spatially consistent across individuals. In the present study, we used diffusion-weighted imaging and functional magnetic resonance imaging to contrast structural and functional connectivity between left and right hemisphere ITNAs and a left hemisphere letter-preferring region. We found that the left ITNA had stronger structural and functional connectivity than the letter region to inferior parietal regions involved in numerical magnitude representation and arithmetic. Between hemispheres, the left ITNA showed stronger structural connectivity with the left inferior frontal gyrus (Broca's area), while the right ITNA showed stronger structural connectivity to the ipsilateral inferior parietal cortex and stronger functional coupling with the bilateral IPS. Based on their relative connectivity, our results suggest that the left ITNA may be more readily involved in mapping digits to verbal number representations, while the right ITNA may support the mapping of digits to quantity representations.

SpaVerb-WN-A megastudy of naming times for 4562 Spanish verbs: Effects of psycholinguistic and motor content variables

Several studies have been carried out in various languages to explore the role of the main psycholinguistic variables in word naming, mainly in nouns. However, reading of verbs has not been explored to the same extent, despite the differences that have been found between the processing of nouns and verbs. To reduce this research gap, we present here SpaVerb-WN, a megastudy of word naming in Spanish, with response times (RT) for 4562 verbs. RT were obtained from at least 20 healthy adult participants in a reading-aloud task. Several research questions on the role of syllable frequency, word length, neighbourhood, frequency, age of acquisition (AoA), and the novel variable 'motor content' in verb naming were also examined. Linear mixed-effects model analyses indicated that (1) RT increase in with increasing word length and with decreasing neighbourhood size, (2) syllable frequency does not show a significant effect on RT, (3) AoA mediates the effect of motor content, with a positive slope of motor content at low AoA scores and a negative slope at high AoA scores, and (4) there is an interaction between word frequency and AoA, in which the AoA effect for low-frequency verbs gradually decreases as frequency increases. The results are discussed in relation to existing evidence and in the context of the consistency of the spelling-sound mappings in Spanish.

Curiosity enhances incidental object encoding in 8-month-old infants

Recent research with adults indicates that curiosity induced by uncertainty enhances learning and memory outcomes and that the resolution of curiosity has a special role in curiosity-driven learning. However, the role of curiosity-based learning in early development is unclear. Here we presented 8-month-old infants with a novel looking time procedure to explore (a) whether uncertainty-induced curiosity enhances learning of incidental information and (b) whether uncertainty-induced curiosity leads infants to seek uncertainty resolution over novelty. In Experiment 1, infants saw blurred images to induce curiosity (Curiosity sequence) or a clear image (Non-curiosity sequence) followed by presentation of incidental objects. Despite looking equally to the incidental objects in both sequences, in a subsequent object recognition phase infants looked longer to incidental objects presented in the Non-curiosity condition compared with the Curiosity condition, indicating that curiosity induced by blurred pictures enhanced the processing of the incidental object, leading to a novelty preference for the incidental object shown in the Non-Curiosity condition. In Experiment 2, a blurred picture of a novel toy was first presented, followed by its corresponding clear picture paired with a clear picture of a new novel toy side by side. Infants showed no preference for either image, providing no evidence for a drive to resolve uncertainty. Overall, the current experiments suggest that curiosity has a broad attention-enhancing effect in infancy. Taking into account existing studies with older children and adults, we propose a developmental change in the function of curiosity, from this attentional enhancement to more goal-directed information seeking in older children and adults.

Damage to temporoparietal cortex is sufficient for impaired semantic control

Semantic control allows us to focus semantic activation on currently relevant aspects of knowledge, even in the face of competition or when the required information is weakly encoded. Diverse cortical regions, including left prefrontal and posterior temporal cortex, are implicated in semantic control, however; the relative contribution of these regions is unclear. For the first time, we compared semantic aphasia (SA) patients with damage restricted to temporoparietal cortex (TPC; N = 8) to patients with infarcts encompassing prefrontal cortex (PF+; N = 22), to determine if prefrontal lesions are necessary for semantic control deficits. These SA groups were also compared with semantic dementia (SD; N = 10), characterised by degraded semantic representations. We asked whether TPC cases with semantic impairment show controlled retrieval deficits equivalent to PF+ cases or conceptual degradation similar to patients with SD. Independent of lesion location, the SA subgroups showed similarities, whereas SD patients showed a qualitatively distinct semantic impairment. Relative to SD, both TPC and PF+ SA subgroups: (1) showed few correlations in performance across tasks with differing control demands, but a strong relationship between tasks of similar difficulty; (2) exhibited attenuated effects of lexical frequency and concept familiarity, (3) showed evidence of poor semantic regulation in their verbal output - performance on picture naming was substantially improved when provided with a phonological cue, and (4) showed effects of control demands, such as retrieval difficulty, which were equivalent in severity across TPC and PF+ groups. These findings show that semantic impairment in SA is underpinned by damage to a distributed semantic control network, instantiated across anterior and posterior cortical areas.

Brain correlates of action word memory revealed by fMRI

Understanding language semantically related to actions activates the motor cortex. This activation is sensitive to semantic information such as the body part used to perform the action (e.g. arm-/leg-related action words). Additionally, motor movements of the hands/feet can have a causal effect on memory maintenance of action words, suggesting that the involvement of motor systems extends to working memory. This study examined brain correlates of verbal memory load for action-related words using event-related fMRI. Seventeen participants saw either four identical or four different words from the same category (arm-/leg-related action words) then performed a nonmatching-to-sample task. Results show that verbal memory maintenance in the high-load condition produced greater activation in left premotor and supplementary motor cortex, along with posterior-parietal areas, indicating that verbal memory circuits for action-related words include the cortical action system. Somatotopic memory load effects of arm- and leg-related words were observed, but only at more anterior cortical regions than was found in earlier studies employing passive reading tasks. These findings support a neurocomputational model of distributed action-perception circuits (APCs), according to which language understanding is manifest as full ignition of APCs, whereas working memory is realized as reverberant activity receding to multimodal prefrontal and lateral temporal areas.

Look at what I can do: Object affordances guide visual attention while speakers describe potential actions

As we act on the world around us, our eyes seek out objects we plan to interact with. A growing body of evidence suggests that overt visual attention selects objects in the environment that could be interacted with, even when the task precludes physical interaction. In previous work, objects that afford grasping interactions influenced attention when static scenes depicted reachable spaces, and attention was otherwise better explained by general informativeness. Because grasping is but one of many object interactions, previous work may have downplayed the influence of object affordances on attention. The current study investigated the relationship between overt visual attention and object affordances versus broadly construed semantic information in scenes as speakers describe or memorize scenes. In addition to meaning and grasp maps-which capture informativeness and grasping object affordances in scenes, respectively-we introduce interact maps, which capture affordances more broadly. In a mixed-effects analysis of 5 eyetracking experiments, we found that meaning predicted fixated locations in a general description task and during scene memorization. Grasp maps marginally predicted fixated locations during action description for scenes that depicted reachable spaces only. Interact maps predicted fixated regions in description experiments alone. Our findings suggest observers allocate attention to scene regions that could be readily interacted with when talking about the scene, while general informativeness preferentially guides attention when the task does not encourage careful consideration of objects in the scene. The current study suggests that the influence of object affordances on visual attention in scenes is mediated by task demands.

Using High-Density Electroencephalography to Explore Spatiotemporal Representations of Object Categories in Visual Cortex

Visual object perception involves neural processes that unfold over time and recruit multiple regions of the brain. Here, we use high-density EEG to investigate the spatiotemporal representations of object categories across the dorsal and ventral pathways. In , human participants were presented with images from two animate object categories (birds and insects) and two inanimate categories (tools and graspable objects). In , participants viewed images of tools and graspable objects from a different stimulus set, one in which a shape confound that often exists between these categories (elongation) was controlled for. To explore the temporal dynamics of object representations, we employed time-resolved multivariate pattern analysis on the EEG time series data. This was performed at the electrode level as well as in source space of two regions of interest: one encompassing the ventral pathway and another encompassing the dorsal pathway. Our results demonstrate shape, exemplar, and category information can be decoded from the EEG signal. Multivariate pattern analysis within source space revealed that both dorsal and ventral pathways contain information pertaining to shape, inanimate object categories, and animate object categories. Of particular interest, we note striking similarities obtained in both ventral stream and dorsal stream regions of interest. These findings provide insight into the spatio-temporal dynamics of object representation and contribute to a growing literature that has begun to redefine the traditional role of the dorsal pathway.

Dissociation between function and manipulation in semantic representations of motor impaired subjects: A new test

A fundamental problem in semantic cognition is the representation of human concepts in the brain. Much of the knowledge acquired in the last decades comes from the study of dissociations found in patients with acquired difficulties in language, perception, and action. In particular, some deficits involve loss of knowledge about tools. The dissociation between two relevant aspects of tools, function and manipulation, has been the focus of several studies. In this paper, a new test designed to study the dissociation between function and manipulation is proposed and normative values for a control population are provided. This novel test was additionally administered to and evaluated in a group of Parkinson's disease patients. The Graded-Controlled Hub-and-Spoke model of Lambon Ralph, Jefferies, Patterson and Rogers was used as a theoretical guide to interpret the results.

Facial attractiveness is more associated with individual warmth than with competence: behavioral and neural evidence

Individuals appear to infer others' psychological characteristics according to facial attractiveness and these psychological characteristics can be classified into two categories in social cognition, that is, warmth and competence. However, which category of psychological characteristic is more associated with face attractiveness and its neural mechanisms have not been explored. To address this, participants were asked to judge others' warmth and competence traits based on face attractiveness, while their brains were scanned using functional magnetic resonance imaging (fMRI). They also assessed the attractiveness of faces after scanning. Behavioral results showed that the correlation between face attractiveness and warmth ratings was significantly higher than that with competence ratings. fMRI results demonstrated that the dorsomedial prefrontal cortex (dmPFC), temporoparietal junction (TPJ), lateral prefrontal cortex, and lateral temporal lobe were more involved in the warmth task. Moreover, attractiveness ratings were negatively correlated with activation of the dmPFC and TPJ only in the warmth task. Furthermore, the attractiveness ratings were negatively correlated with the defined dmPFC, region related to attractiveness judgement, only in the warmth task. In conclusion, people are more inclined to infer others' warmth than competence characteristics from face attractiveness, that is, face attractiveness is more associated with warmth than with competence.