Left perirhinal cortex codes for similarity in meaning between written words: Comparison with auditory word input

An inclusive multivariate approach to neural localization of language components

To determine how language is implemented in the brain, it is important to know which brain areas are primarily engaged in language processing and which are not. Existing protocols for localizing language are typically univariate, treating each small unit of brain volume as independent. One prominent example that focuses on the overall language network in functional magnetic resonance imaging (fMRI) uses a contrast between neural responses to sentences and sets of pseudowords (pronounceable nonwords). This contrast reliably activates peri-sylvian language areas but is less sensitive to extra-sylvian areas that are also known to support aspects of language such as word meanings (semantics). In this study, we assess areas where a multivariate, pattern-based approach shows high reproducibility across multiple measurements and participants, identifying these areas as multivariate regions of interest (mROI). We then perform a representational similarity analysis (RSA) of an fMRI dataset where participants made familiarity judgments on written words. We also compare those results to univariate regions of interest (uROI) taken from previous sentences > pseudowords contrasts. RSA with word stimuli defined in terms of their semantic distance showed greater correspondence with neural patterns in mROI than uROI. This was confirmed in two independent datasets, one involving single-word recognition, and the other focused on the meaning of noun-noun phrases by contrasting meaningful phrases > pseudowords. In all cases, areas of spatial overlap between mROI and uROI showed the greatest neural association. This suggests that ROIs defined in terms of multivariate reproducibility can help localize components of language such as semantics. The multivariate approach can also be extended to focus on other aspects of language such as phonology, and can be used along with the univariate approach for inclusively mapping language cortex.

Sentence-level embeddings reveal dissociable word- and sentence-level cortical representation across coarse- and fine-grained levels of meaning

In this large-sample (N = 64) fMRI study, sentence embeddings (text-embedding-ada-002, OpenAI) and representational similarity analysis were used to contrast sentence-level and word-level semantic representation. Overall, sentence-level information resulted in a 20-25 % increase in the model's ability to captures neural representation when compared to word-level only information (word-order scrambled embeddings). This increase was relatively undifferentiated across the cortex. However, when coarse-grained (across thematic category) and fine-grained (within thematic category) combinatorial meaning were separately assessed, word- and sentence-level representations were seen to strongly dissociate across the cortex and to do so differently as a function of grain. Coarse-grained sentence-level representations were evident in occipitotemporal, ventral temporal and medial prefrontal cortex, while fine-grained differences were seen in lateral prefrontal and parietal cortex, middle temporal gyrus, the precuneus, and medial prefrontal cortex. This result indicates dissociable cortical substrates underly single concept versus combinatorial meaning and that different cortical regions specialise for fine- and coarse-grained meaning.

Semantic representations in inferior frontal and lateral temporal cortex during picture naming, reading, and repetition

Reading, naming, and repetition are classical neuropsychological tasks widely used in the clinic and psycholinguistic research. While reading and repetition can be accomplished by following a direct or an indirect route, pictures can be named only by means of semantic mediation. By means of fMRI multivariate pattern analysis, we evaluated whether this well-established fundamental difference at the cognitive level is associated at the brain level with a difference in the degree to which semantic representations are activated during these tasks. Semantic similarity between words was estimated based on a word association model. Twenty subjects participated in an event-related fMRI study where the three tasks were presented in pseudo-random order. Linear discriminant analysis of fMRI patterns identified a set of regions that allow to discriminate between words at a high level of word-specificity across tasks. Representational similarity analysis was used to determine whether semantic similarity was represented in these regions and whether this depended on the task performed. The similarity between neural patterns of the left Brodmann area 45 (BA45) and of the superior portion of the left supramarginal gyrus correlated with the similarity in meaning between entities during picture naming. In both regions, no significant effects were seen for repetition or reading. The semantic similarity effect during picture naming was significantly larger than the similarity effect during the two other tasks. In contrast, several regions including left anterior superior temporal gyrus and left ventral BA44/frontal operculum, among others, coded for semantic similarity in a task-independent manner. These findings provide new evidence for the dynamic, task-dependent nature of semantic representations in the left BA45 and a more task-independent nature of the representational activation in the lateral temporal cortex and ventral BA44/frontal operculum.

Representation of event and object concepts in ventral anterior temporal lobe and angular gyrus

Semantic knowledge includes understanding of objects and their features and also understanding of the characteristics of events. The hub-and-spoke theory holds that these conceptual representations rely on multiple information sources that are integrated in a central hub in the ventral anterior temporal lobes. The dual-hub theory expands this framework with the claim that the ventral anterior temporal lobe hub is specialized for object representation, while a second hub in angular gyrus is specialized for event representation. To test these ideas, we used representational similarity analysis, univariate and psychophysiological interaction analyses of fMRI data collected while participants processed object and event concepts (e.g. "an apple," "a wedding") presented as images and written words. Representational similarity analysis showed that angular gyrus encoded event concept similarity more than object similarity, although the left angular gyrus also encoded object similarity. Bilateral ventral anterior temporal lobes encoded both object and event concept structure, and left ventral anterior temporal lobe exhibited stronger coding for events. Psychophysiological interaction analysis revealed greater connectivity between left ventral anterior temporal lobe and right pMTG, and between right angular gyrus and bilateral ITG and middle occipital gyrus, for event concepts compared to object concepts. These findings support the specialization of angular gyrus for event semantics, though with some involvement in object coding, but do not support ventral anterior temporal lobe specialization for object concepts.

Hippocampal Functions Modulate Transfer-Appropriate Cortical Representations Supporting Subsequent Memory

The hippocampus plays a central role as a coordinate system or index of information stored in neocortical loci. Nonetheless, it remains unclear how hippocampal processes integrate with cortical information to facilitate successful memory encoding. Thus, the goal of the current study was to identify specific hippocampal-cortical interactions that support object encoding. We collected fMRI data while 19 human participants (7 female and 12 male) encoded images of real-world objects and tested their memory for object concepts and image exemplars (i.e., conceptual and perceptual memory). Representational similarity analysis revealed robust representations of visual and semantic information in canonical visual (e.g., occipital cortex) and semantic (e.g., angular gyrus) regions in the cortex, but not in the hippocampus. Critically, hippocampal functions modulated the mnemonic impact of cortical representations that are most pertinent to future memory demands, or transfer-appropriate representations Subsequent perceptual memory was best predicted by the strength of visual representations in ventromedial occipital cortex in coordination with hippocampal activity and pattern information during encoding. In parallel, subsequent conceptual memory was best predicted by the strength of semantic representations in left inferior frontal gyrus and angular gyrus in coordination with either hippocampal activity or semantic representational strength during encoding. We found no evidence for transfer-incongruent hippocampal-cortical interactions supporting subsequent memory (i.e., no hippocampal interactions with cortical visual/semantic representations supported conceptual/perceptual memory). Collectively, these results suggest that diverse hippocampal functions flexibly modulate cortical representations of object properties to satisfy distinct future memory demands.Significance Statement The hippocampus is theorized to index pieces of information stored throughout the cortex to support episodic memory. Yet how hippocampal processes integrate with cortical representation of stimulus information remains unclear. Using fMRI, we examined various forms of hippocampal-cortical interactions during object encoding in relation to subsequent performance on conceptual and perceptual memory tests. Our results revealed novel hippocampal-cortical interactions that utilize semantic and visual representations in transfer-appropriate manners: conceptual memory supported by hippocampal modulation of frontoparietal semantic representations, and perceptual memory supported by hippocampal modulation of occipital visual representations. These findings provide important insights into the neural mechanisms underlying the formation of information-rich episodic memory and underscore the value of studying the flexible interplay between brain regions for complex cognition.

Independency of Coding for Affective Similarities and for Word Co-occurrences in Temporal Perisylvian Neocortex

Word valence is one of the principal dimensions in the organization of word meaning. Co-occurrence-based similarities calculated by predictive natural language processing models are relatively poor at representing affective content, but very powerful in their own way. Here, we determined how these two canonical but distinct ways of representing word meaning relate to each other in the human brain both functionally and neuroanatomically. We re-analysed an fMRI study of word valence. A co-occurrence-based model was used and the correlation with the similarity of brain activity patterns was compared to that of affective similarities. The correlation between affective and co-occurrence-based similarities was low (r = 0.065), confirming that affect was captured poorly by co-occurrence modelling. In a whole-brain representational similarity analysis, word embedding similarities correlated significantly with the similarity between activity patterns in a region confined to the superior temporal sulcus to the left, and to a lesser degree to the right. Affective word similarities correlated with the similarity in activity patterns in this same region, confirming previous findings. The affective similarity effect extended more widely beyond the superior temporal cortex than the effect of co-occurrence-based similarities did. The effect of co-occurrence-based similarities remained unaltered after partialling out the effect of affective similarities (and vice versa). To conclude, different aspects of word meaning, derived from affective judgements or from word co-occurrences, are represented in superior temporal language cortex in a neuroanatomically overlapping but functionally independent manner.

Typicality in the brain during semantic and episodic memory decisions

Concept typicality is a key semantic dimension supporting the categorical organization of items based on their features, such that typical items share more features with other members of their category than atypical items, which are more distinctive. Typicality effects manifest in better accuracy and faster response times during categorization tasks, but higher performance for atypical items in episodic memory tasks, due to their distinctiveness. At a neural level, typicality has been linked to the anterior temporal lobe (ATL) and the inferior frontal gyrus (IFG) in semantic decision tasks, but patterns of brain activity during episodic memory tasks remain to be understood. We investigated the neural correlates of typicality in semantic and episodic memory to determine the brain regions associated with semantic typicality and uncover effects arising when items are reinstated during retrieval. In an fMRI study, 26 healthy young subjects first performed a category verification task on words representing typical and atypical concepts (encoding), and then completed a recognition memory task (retrieval). In line with previous literature, we observed higher accuracy and faster response times for typical items in the category verification task, while atypical items were better recognized in the episodic memory task. During category verification, univariate analyses revealed a greater involvement of the angular gyrus for typical items and the inferior frontal gyrus for atypical items. During the correct recognition of old items, regions belonging to the core recollection network were activated. We then compared the similarity of the representations from encoding to retrieval (ERS) using Representation Similarity Analyses. Results showed that typical items were reinstated more than atypical ones in several regions including the left precuneus and left anterior temporal lobe (ATL). This suggests that the correct retrieval of typical items requires finer-grained processing, evidenced by greater item-specific reinstatement, which is needed to resolve their confusability with other members of the category due to their higher feature similarity. Our findings confirm the centrality of the ATL in the processing of typicality while extending it to memory retrieval.

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.

Similarity-based fMRI-MEG fusion reveals hierarchical organisation within the brain's semantic system

Our ability to understand and interact with our environment relies upon conceptual knowledge of the meaning of objects. This process is supported by a distributed network of frontal, parietal, and temporal brain regions. Insight into the differential roles of various elements of this system can be inferred from the timing of activation, and here we use similarity-based fMRI-MEG fusion to understand when the representational spaces in different elements of the semantic system converge with representational spaces in the evolving MEG signal. Participants performed a semantic-typicality judgment of written words drawn from nine different semantic categories in separate fMRI and MEG sessions. Results indicate an initial period of congruence between MEG and fMRI informational spaces dominated by the posterior inferior temporal gyrus and the ventral temporal cortex between 350-450 msec. This is followed by a second period of convergence between 450-795 msec where MEG and fMRI representational spaces conform in left angular gyrus and precuneus in addition to ventral temporal cortex. Results are consistent with the multistage recruitment of the semantic system, initially involving automatic aspects of the representational system and later extending to broader elements of the semantic system more strongly associated with internalised cognition.

Posterior Intraparietal Sulcus Mediates Detection of Salient Stimuli Outside the Endogenous Focus of Attention

Visual consciousness is shaped by the interplay between endogenous selection and exogenous capture. If stimulus saliency is aligned with a subject’s attentional priorities, endogenous selection will be facilitated. In case of a misalignment, endogenous selection may be compromised as attentional capture is a strong and automatic process. We manipulated task-congruent versus -incongruent saliency in a functional magnetic resonance imaging change-detection task and analyzed brain activity patterns in the cortex surrounding the intraparietal sulcus (IPS) within the Julich-Brain probabilistic cytoarchitectonic mapping reference frame. We predicted that exogenous effects would be seen mainly in the posterior regions of the IPS (hIP4–hIP7–hIP8), whereas a conflict between endogenous and exogenous orienting would elicit activity from more anterior cytoarchitectonic areas (hIP1–hIP2–hIP3). Contrary to our hypothesis, a conflict between endogenous and exogenous orienting had an effect early in the IPS (mainly in hIP7 and hIP8). This is strong evidence for an endogenous component in hIP7/8 responses to salient stimuli beyond effects of attentional bottom-up sweep. Our results suggest that hIP7 and hIP8 are implicated in the individuation of attended locations based on saliency as well as endogenous instructions.

Representations of conceptual information during automatic and active semantic access

When we read a word or see an object, conceptual meaning is automatically accessed. However, previous research investigating non-perceptual sensitivity to semantic class has employed active tasks. In this fMRI study, we tested whether conceptual representations in regions constituting the semantic network are invoked during passive semantic access and whether these representations are modulated by the need to access deeper knowledge. Seventeen healthy subjects performed a semantically active typicality judgment task and a semantically passive phonetic decision task, in both the written and the spoken input-modalities. Stimuli consisted of one hundred forty-four concepts drawn from six semantic categories. Multivariate Pattern Analysis (MVPA) revealed that the left posterior middle temporal gyrus (pMTG), posterior ventral temporal cortex (pVTC) and pars triangularis of the left inferior frontal gyrus (IFG) showed a stronger sensitivity to semantic category when active rather than passive semantic access is required. Using a cross-task training/testing classifier, we determined that conceptual representations were not only active in these regions during passive semantic access but that the neural representation of these categories was common to both active and passive access. Collectively, these results show that while representations in the pMTG, pVTC and IFG are strongly modulated by active conceptual access, consistent representational patterns are present during active and passive conceptual access in these same regions.

Grid-like and distance codes for representing word meaning in the human brain

Relational information about items in memory is thought to be represented in our brain thanks to an internal comprehensive model, also referred to as a "cognitive map". In the human neuroimaging literature, two signatures of bi-dimensional cognitive maps have been reported: the grid-like code and the distance-dependent code. While these kinds of representation were previously observed during spatial navigation and, more recently, during processing of perceptual stimuli, it is still an open question whether they also underlie the representation of the most basic items of language: words. Here we taught human participants the meaning of novel words as arbitrary labels for a set of audiovisual objects varying orthogonally in size and sound. The novel words were therefore conceivable as points in a navigable 2D map of meaning. While subjects performed a word comparison task, we recorded their brain activity using functional magnetic resonance imaging (fMRI). By applying a combination of representational similarity and fMRI-adaptation analyses, we found evidence of (i) a grid-like code, in the right postero-medial entorhinal cortex, representing the relative angular positions of words in the word space, and (ii) a distance-dependent code, in medial prefrontal, orbitofrontal, and mid-cingulate cortices, representing the Euclidean distance between words. Additionally, we found evidence that the brain also separately represents the single dimensions of word meaning: their implied size, encoded in visual areas, and their implied sound, in Heschl's gyrus/Insula. These results support the idea that the meaning of words, when they are organized along two dimensions, is represented in the human brain across multiple maps of different dimensionality. SIGNIFICANT STATEMENT: How do we represent the meaning of words and perform comparative judgements on them in our brain? According to influential theories, concepts are conceivable as points of an internal map (where distance represents similarity) that, as the physical space, can be mentally navigated. Here we use fMRI to show that when humans compare newly learnt words, they recruit a grid-like and a distance code, the same types of neural codes that, in mammals, represent relations between locations in the environment and support physical navigation between them.

Deficits in recent but not lifetime familiarity in amnestic mild cognitive impairment

People with amnestic mild cognitive impairment (aMCI) repeat questions, seemingly without any sense of familiarity (i.e., recognition of prior occurrence without recollection of episodic context). Accumulation of neurofibrillary tau in preclinical Alzheimer's disease begins in perirhinal cortex, a medial temporal lobe region linked to familiarity. Both observations would predict impaired familiarity assessment in aMCI; however, the extant evidence is mixed. To reveal familiarity impairments, it may be necessary to minimize the influence of recollection. In the current study, older adults with aMCI and healthy controls were administered two tasks on which a well-characterized patient (NB) with selective familiarity impairments due to surgical left temporal lobe excision sparing the hippocampus showed abnormal performance: frequency judgments for words exposed to in a recent study phase and judgments of cumulative lifetime familiarity for object concepts denoted by words. We also administered a process dissociation procedure (PDP) task that previously revealed spared familiarity in aMCI. We predicted that familiarity would be spared in aMCI on the PDP task, but impaired when assessed by frequency judgments for recent laboratory exposures and lifetime familiarity judgments. Familiarity was spared on the PDP task, but was impaired when probed with frequency judgments for recently exposed words in aMCI. Lifetime familiarity was also not impaired in aMCI. These results highlight the benefits of studying familiarity under conditions that minimize recollection and the value of frequency judgments in revealing familiarity deficits, and suggest that perirhinal cortex may not be necessary for accessing familiarity accumulated over a lifetime of experience.

Representation of associative and affective semantic similarity of abstract words in the lateral temporal perisylvian language regions

The examination of semantic cognition has traditionally identified word concreteness as well as valence as two of the principal dimensions in the representation of conceptual knowledge. More recently, corpus-based vector space models as well as graph-theoretical analysis of large-scale task-related behavioural responses have revolutionized our insight into how the meaning of words is structured. In this fMRI study, we apply representational similarity analysis to investigate the conceptual representation of abstract words. Brain activity patterns were related to a cued-association based graph as well as to a vector-based co-occurrence model of word meaning. Twenty-six subjects (19 females and 7 males) performed an overt repetition task during fMRI. First, we performed a searchlight classification procedure to identify regions where activity is discriminable between abstract and concrete words. These regions were left inferior frontal gyrus, the upper and lower bank of the superior temporal sulcus bilaterally, posterior middle temporal gyrus and left fusiform gyrus. Representational Similarity Analysis demonstrated that for abstract words, the similarity of activity patterns in the cortex surrounding the superior temporal sulcus bilaterally and in the left anterior superior temporal gyrus reflects the similarity in word meaning. These effects were strongest for semantic similarity derived from the cued association-based graph and for affective similarity derived from either of the two models. The latter effect was mainly driven by positive valence words. This research highlights the close neurobiological link between the information structure of abstract and affective word content and the similarity in activity pattern in the lateral and anterior temporal language system.

Multivariate analysis reveals anatomical correlates of naming errors in primary progressive aphasia

Primary progressive aphasia (PPA) is an overarching term for a heterogeneous group of neurodegenerative diseases which affect language processing. Impaired picture naming has been linked to atrophy of the anterior temporal lobe in the semantic variant of PPA. Although atrophy of the anterior temporal lobe proposedly impairs picture naming by undermining access to semantic knowledge, picture naming also entails object recognition and lexical retrieval. Using multivariate analysis, we investigated whether cortical atrophy relates to different types of naming errors generated during picture naming in 43 PPA patients (13 semantic, 9 logopenic, 11 nonfluent, and 10 mixed variant). Omissions were associated with atrophy of the anterior temporal lobes. Semantic errors, for example, mistaking a rhinoceros for a hippopotamus, were associated with atrophy of the left mid and posterior fusiform cortex and the posterior middle and inferior temporal gyrus. Semantic errors and atrophy in these regions occurred in each PPA subtype, without major between-subtype differences. We propose that pathological changes to neural mechanisms associated with semantic errors occur across the PPA spectrum.

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.

Redefining the resolution of semantic knowledge in the brain: Advances made by the introduction of models of semantics in neuroimaging

The boundaries of our understanding of conceptual representation in the brain have been redrawn since the introduction of explicit models of semantics. These models are grounded in vast behavioural datasets acquired in healthy volunteers. Here, we review the most important techniques which have been applied to detect semantic information in neuroimaging data and argue why semantic models are possibly the most valuable addition to the research of semantics in recent years. Using multivariate analysis, predictions based on patient lesion data have been confirmed during semantic processing in healthy controls. Secondly, this new method has given rise to new research avenues, e.g. the detection of semantic processing outside of the temporal cortex. As a future line of work, the same research strategy could be useful to study neurological conditions such as the semantic variant of primary progressive aphasia, which is characterized by pathological semantic processing.

Temporal dynamics of access to amodal representations of category-level conceptual information

Categories describe semantic divisions between classes of objects and category-based models are widely used for investigation of the conceptual system. One critical issue in this endeavour is the isolation of conceptual from perceptual contributions to category-differences. An unambiguous way to address this confound is combining multiple input-modalities. To this end, we showed participants person/place stimuli using name and picture modalities. Using multivariate methods, we searched for category-sensitive neural patterns shared across input-modalities and thus independent from perceptual properties. The millisecond temporal resolution of magnetoencephalography (MEG) allowed us to consider the precise timing of conceptual access and, by confronting latencies between the two modalities ("time generalization"), how latencies of processing depends on the input-modality. Our results identified category-sensitive conceptual representations common between modalities at three stages and that conceptual access for words was delayed by about 90 msec with respect to pictures. We also show that for pictures, the first conceptual pattern of activity (shared between both words and pictures) occurs as early as 110 msec. Collectively, our results indicated that conceptual access at the category-level is a multistage process and that different delays in access across these two input-modalities determine when these representations are activated.

Recognition memory shielded from semantic but not perceptual interference in normal aging

Normal aging impairs long-term declarative memory, and evidence suggests that this impairment may be driven partly by structural or functional changes in the medial temporal lobe (MTL). Theories of MTL memory function therefore make predictions for age-related memory loss. One theory - the Representational-Hierarchical account - makes two specific predictions. First, recognition memory performance in older participants should be impaired by feature-level interference, in which studied items contain many shared, and thus repeatedly appearing, perceptual features. Second, if the interference in a recognition memory task - i.e., the information that repeats across items - resides at a higher level of complexity than simple perceptual features, such as semantic gist, older adults should be less impacted by such interference than young adults. We tested these predictions using the Deese-Roediger-McDermott paradigm, by creating feature-level (i.e., perceptual) interference with phonemically/orthographically related word categories, and higher-level associative interference with semantically related word categories. We manipulated category size in order to compare the effect of less versus more interference (i.e., small versus large category size), which served to (1) avoid potential item confounds arising from systematic differences between words belonging to perceptually- versus semantically-related categories, and (2) ensure that any effect of interference was due to information encoded at study, rather than pre-experimentally. Further, we used signal detection theory (SDT) to interpret our data, rather than examining false alarm (FA) rates in isolation. The d' measure derived from SDT avoids contamination of the memory measure by response bias, and lies on an interval scale, allowing memory performance in different conditions to be compared without violating assumptions of the statistical tests. Older participants were relatively more impaired by perceptual interference and less impaired by semantic interference than young adults. This pattern is at odds with many current theories of age-related memory loss, but is in line with the Representational-Hierarchical account.

Representation of Semantic Similarity in the Left Intraparietal Sulcus: Functional Magnetic Resonance Imaging Evidence

According to a recent study, semantic similarity between concrete entities correlates with the similarity of activity patterns in left middle IPS during category naming. We examined the replicability of this effect under passive viewing conditions, the potential role of visuoperceptual similarity, where the effect is situated compared to regions that have been previously implicated in visuospatial attention, and how it compares to effects of object identity and location. Forty-six subjects participated. Subjects passively viewed pictures from two categories, musical instruments and vehicles. Semantic similarity between entities was estimated based on a concept-feature matrix obtained in more than 1,000 subjects. Visuoperceptual similarity was modeled based on the HMAX model, the AlexNet deep convolutional learning model, and thirdly, based on subjective visuoperceptual similarity ratings. Among the IPS regions examined, only left middle IPS showed a semantic similarity effect. The effect was significant in hIP1, hIP2, and hIP3. Visuoperceptual similarity did not correlate with similarity of activity patterns in left middle IPS. The semantic similarity effect in left middle IPS was significantly stronger than in the right middle IPS and also stronger than in the left or right posterior IPS. The semantic similarity effect was similar to that seen in the angular gyrus. Object identity effects were much more widespread across nearly all parietal areas examined. Location effects were relatively specific for posterior IPS and area 7 bilaterally. To conclude, the current findings replicate the semantic similarity effect in left middle IPS under passive viewing conditions, and demonstrate its anatomical specificity within a cytoarchitectonic reference frame. We propose that the semantic similarity effect in left middle IPS reflects the transient uploading of semantic representations in working memory.

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.

Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes

A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. "sandy beach") describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and frontal cortices. This similarity of neural activity patterns across the two input types, for categories that co-activate local brain regions, provides strong evidence of a common semantic code for pictures and words in the brain.

Perirhinal cortex tracks degree of recent as well as cumulative lifetime experience with object concepts

Evidence from numerous sources indicates that recognition of the prior occurrence of objects requires computations of perirhinal cortex (PrC) in the medial temporal lobe (MTL). Extant research has primarily probed recognition memory based on item exposure in a recent experimental study episode. Outside the laboratory, however, familiarity for objects typically accrues gradually with learning across many different episodic contexts, which can be distributed over a lifetime of experience. It is currently unknown whether PrC also tracks this cumulative lifetime experience with object concepts. To address this issue, we conducted a functional magnetic resonance imaging (fMRI) experiment in healthy individuals in which we compared judgments of the perceived lifetime familiarity with object concepts, a task that has previously been employed in many normative studies on concept knowledge, with frequency judgments for recent laboratory exposure in a study phase. Guided by neurophysiological data showing that neurons in primate PrC signal prior object exposure at multiple time scales, we predicted that PrC responses would track perceived prior experience in both types of judgments. Left PrC and a number of cortical regions that are often co-activated as part of the default-mode network showed an increase in Blood-Oxygen-Level Dependent (BOLD) response in relation to increases in the perceived cumulative lifetime familiarity of object concepts. These regions included the left hippocampus, left mid-lateral temporal cortex, as well as anterior and posterior cortical midline structures. Critically, left PrC was found to be the only region that showed this response in combination with the typically observed decrease in signal for perceived recent exposure in the experimental study phase. These findings provide, to our knowledge, the first evidence that ties signals in human PrC to variations in cumulative lifetime experience with object concepts. They offer a new link between the role of PrC in recognition memory and its broader role in conceptual processing.

Multivariate Pattern Analysis Reveals Category-Related Organization of Semantic Representations in Anterior Temporal Cortex

The neural substrates of semantic representation have been the subject of much controversy. The study of semantic representations is complicated by difficulty in disentangling perceptual and semantic influences on neural activity, as well as in identifying stimulus-driven, "bottom-up" semantic selectivity unconfounded by top-down task-related modulations. To address these challenges, we trained human subjects to associate pseudowords (TPWs) with various animal and tool categories. To decode semantic representations of these TPWs, we used multivariate pattern classification of fMRI data acquired while subjects performed a semantic oddball detection task. Crucially, the classifier was trained and tested on disjoint sets of TPWs, so that the classifier had to use the semantic information from the training set to correctly classify the test set. Animal and tool TPWs were successfully decoded based on fMRI activity in spatially distinct subregions of the left medial anterior temporal lobe (LATL). In addition, tools (but not animals) were successfully decoded from activity in the left inferior parietal lobule. The tool-selective LATL subregion showed greater functional connectivity with left inferior parietal lobule and ventral premotor cortex, indicating that each LATL subregion exhibits distinct patterns of connectivity. Our findings demonstrate category-selective organization of semantic representations in LATL into spatially distinct subregions, continuing the lateral-medial segregation of activation in posterior temporal cortex previously observed in response to images of animals and tools, respectively. Together, our results provide evidence for segregation of processing hierarchies for different classes of objects and the existence of multiple, category-specific semantic networks in the brain.

SIGNIFICANCE STATEMENT

The location and specificity of semantic representations in the brain are still widely debated. We trained human participants to associate specific pseudowords with various animal and tool categories, and used multivariate pattern classification of fMRI data to decode the semantic representations of the trained pseudowords. We found that: (1) animal and tool information was organized in category-selective subregions of medial left anterior temporal lobe (LATL); (2) tools, but not animals, were encoded in left inferior parietal lobe; and (3) LATL subregions exhibited distinct patterns of functional connectivity with category-related regions across cortex. Our findings suggest that semantic knowledge in LATL is organized in category-related subregions, providing evidence for the existence of multiple, category-specific semantic representations in the brain.