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 duri...
We present a model relating analysis of abstract and concrete word meaning in terms of semantic feat...
In the ventral visual pathway, early visual areas encode light patterns on the retina in terms of im...
The quantitative modeling of semantic representations in the brain plays a key role in understanding...
Semantic processing from different input modalities is a fundamental issue in cognitive neuroscience...
Understanding the meanings of words and objects requires the activation of underlying conceptual rep...
Understanding themeanings of words and objects requires the activation of underlying conceptual repr...
Language comprehension engages a distributed network of frontotemporal, parietal, and sensorimotor r...
Left perirhinal cortex has been previously implicated in associative coding. According to a recent e...
Much of mental life consists in thinking about object concepts that are not currently within the sco...
INTRODUCTION: For years the commonalities underlying the semantic processing of different input-moda...
Knowledge of visual and nonvisual attributes of concrete entities is distributed over neocortical un...
INTRODUCTION:Representational Similarity Analysis (RSA) provides an opportunity to better understand...
We investigate the effects of two types of relationship between the words of a sentence or text – pr...
How verbal and nonverbal visuoperceptual input connects to semantic knowledge is a core question in ...
The anterior temporal lobe (ATL) is considered a crucial area for the representation of transmodal c...
We present a model relating analysis of abstract and concrete word meaning in terms of semantic feat...
In the ventral visual pathway, early visual areas encode light patterns on the retina in terms of im...
The quantitative modeling of semantic representations in the brain plays a key role in understanding...
Semantic processing from different input modalities is a fundamental issue in cognitive neuroscience...
Understanding the meanings of words and objects requires the activation of underlying conceptual rep...
Understanding themeanings of words and objects requires the activation of underlying conceptual repr...
Language comprehension engages a distributed network of frontotemporal, parietal, and sensorimotor r...
Left perirhinal cortex has been previously implicated in associative coding. According to a recent e...
Much of mental life consists in thinking about object concepts that are not currently within the sco...
INTRODUCTION: For years the commonalities underlying the semantic processing of different input-moda...
Knowledge of visual and nonvisual attributes of concrete entities is distributed over neocortical un...
INTRODUCTION:Representational Similarity Analysis (RSA) provides an opportunity to better understand...
We investigate the effects of two types of relationship between the words of a sentence or text – pr...
How verbal and nonverbal visuoperceptual input connects to semantic knowledge is a core question in ...
The anterior temporal lobe (ATL) is considered a crucial area for the representation of transmodal c...
We present a model relating analysis of abstract and concrete word meaning in terms of semantic feat...
In the ventral visual pathway, early visual areas encode light patterns on the retina in terms of im...
The quantitative modeling of semantic representations in the brain plays a key role in understanding...