Publications by authors named "Jeffrey R Binder"

In studies using representational similarity analysis (RSA) of fMRI data, the reliability of the neural representational dissimilarity matrix (RDM) is a limiting factor in the ability to detect neural correlates of a model. A common strategy for boosting neural RDM reliability is to employ repeated presentations of the stimulus set across imaging runs or sessions. However, little is known about how the benefits of stimulus repetition are affected by repetition suppression, or how they compare with the benefits of increasing the number of participants.

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While the two types of intransitive verbs, i.e., unergative and unaccusative, are hypothesised to be syntactically represented, many have proposed a semantic account where abstract properties related to agentivity and telicity, often conceptualised as binary properties, determine the classification.

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Understanding the computational operations involved in conceptual composition is fundamental for theories of language. However, the existing literature on this topic remains fragmented, comprising disconnected theories from various fields. For instance, while formal semantic theories in Linguistics rely on type-driven interpretation without explicitly representing the conceptual content of lexical items, neurolinguistic research suggests that the brain is sensitive to conceptual factors during word composition.

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Article Synopsis
  • Tulving defined semantic memory as a large storehouse of meanings crucial for language and cognition, prompting various fields to research it with unique methods and terms.
  • The varied interpretations of key concepts like "concept" across disciplines create confusion, contributing to the replication crisis in psychology and impacting communication and theory development.
  • To address these issues, a multidisciplinary semantic glossary is being developed to provide clear definitions and foster shared understanding among researchers while acknowledging the challenges of bias and prescriptiveness.
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Introduction: Emerging evidence illustrates that temporal lobe epilepsy (TLE) involves network disruptions represented by hyperexcitability and other seizure-related neural plasticity. However, these associations are not well-characterized. Our study characterizes the whole brain white matter connectome abnormalities in TLE patients compared to healthy controls (HCs) from the prospective Epilepsy Connectome Project study.

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Unlabelled: Much is known regarding the major white matter pathways connecting the right and left temporal lobes, which project through the posterior corpus callosum, the anterior commissure, and the dorsal hippocampal commissure. However, details about the spatial location of these tracts are unclear, including their exact course and proximity to cortical and subcortical structures, the spatial relations between corpus callosum and anterior commissure projections, and the caudal extent of transcallosal connections within the splenium. We present an atlas of these tracts derived from high angular resolution diffusion tractography maps, providing improved visualization of the spatial relationships of these tracts.

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Whilst the concept of a general mental factor known as '' has been of longstanding interest, for unknown reasons, it has never been interrogated in epilepsy despite the 100+ year empirical history of the neuropsychology of epilepsy. This investigation seeks to identify within a comprehensive neuropsychological data set and compare participants with temporal lobe epilepsy to controls, characterize the discriminatory power of compared with domain-specific cognitive metrics, explore the association of with clinical epilepsy and sociodemographic variables and identify the structural and network properties associated with in epilepsy. Participants included 110 temporal lobe epilepsy patients and 79 healthy controls between the ages of 19 and 60.

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Neuropsychological and neuroimaging studies provide evidence for a degree of category-related organization of conceptual knowledge in the brain. Some of this evidence indicates that body part concepts are distinctly represented from other categories; yet, the neural correlates and mechanisms underlying these dissociations are unclear. We expand on the limited prior data by measuring functional magnetic resonance imaging responses induced by body part words and performing a series of analyses investigating the cortical representation of this semantic category.

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We introduce a novel, data-driven topological data analysis (TDA) approach for embedding brain networks into a lower-dimensional space in quantifying the dynamics of temporal lobe epilepsy (TLE) obtained from resting-state functional magnetic resonance imaging (rs-fMRI). This embedding facilitates the orthogonal projection of 0D and 1D topological features, allowing for the visualization and modeling of the dynamics of functional human brain networks in a resting state. We then quantify the topological disparities between networks to determine the coordinates for embedding.

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This review examines whether and how the "default mode" network (DMN) contributes to semantic processing. We review evidence implicating the DMN in the processing of individual word meanings and in sentence- and discourse-level semantics. Next, we argue that the areas comprising the DMN contribute to semantic processing by coordinating and integrating the simultaneous activity of local neuronal ensembles across multiple unimodal and multimodal cortical regions, creating a transient, global neuronal ensemble.

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Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance.

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Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging.

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Objective: Social determinants of health, including the effects of neighborhood disadvantage, impact epilepsy prevalence, treatment, and outcomes. This study characterized the association between aberrant white matter connectivity in temporal lobe epilepsy (TLE) and disadvantage using a US census-based neighborhood disadvantage metric, the Area Deprivation Index (ADI), derived from measures of income, education, employment, and housing quality.

Methods: Participants including 74 TLE patients (47 male, mean age = 39.

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Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome that empirically represents a network disorder, which makes graph theory (GT) a practical approach to understand it. Multi-shell diffusion-weighted imaging (DWI) was obtained from 89 TLE and 50 controls. GT measures extracted from harmonized DWI matrices were used as factors in a support vector machine (SVM) analysis to discriminate between groups, and in a k-means algorithm to find intrinsic structural phenotypes within TLE.

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The relationship between temporal lobe epilepsy and psychopathology has had a long and contentious history with diverse views regarding the presence, nature and severity of emotional-behavioural problems in this patient population. To address these controversies, we take a new person-centred approach through the application of unsupervised machine learning techniques to identify underlying latent groups or behavioural phenotypes. Addressed are the distinct psychopathological profiles, their linked frequency, patterns and severity and the disruptions in morphological and network properties that underlie the identified latent groups.

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Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance.

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Objectives: The objectives of this study were to examine the association between cognitive decline and quality of life (QoL) change in a large sample of individuals with drug-resistant epilepsy who underwent resective surgery and to examine whether the association between cognitive decline and QoL is differentially affected by seizure classification outcome (Engel Class 1 vs. 2-4) or side of surgery (left vs. right hemisphere).

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The Selective Reminding Test (SRT) is widely used in pre-surgical evaluations for people with epilepsy; however, important characteristics such as reliability and stability over time within an epilepsy-specific control cohort are unclear. In this study, we document test-retest reliabilities, practice effects, and Reliable Change Indices (RCI) for this test in a sample of right temporal lobe epilepsy patients who are left hemisphere dominant for language and underwent surgical resection on the right temporal lobe. A sample of 101 adults with a right temporal lobe seizure focus (mean age = 38.

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Auditory stream segregation and informational masking were investigated in brain-lesioned individuals, age-matched controls with no neurological disease, and young college-age students. A psychophysical paradigm known as rhythmic masking release (RMR) was used to examine the ability of participants to identify a change in the rhythmic sequence of 20-ms Gaussian noise bursts presented through headphones and filtered through generalized head-related transfer functions to produce the percept of an externalized auditory image (i.e.

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PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults.

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Machine learning analyses were performed on graph theory (GT) metrics extracted from brain functional and morphological data from temporal lobe epilepsy (TLE) patients in order to identify intrinsic network phenotypes and characterize their clinical significance. Participants were 97 TLE and 36 healthy controls from the Epilepsy Connectome Project. Each imaging modality (i.

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Neuroimaging, neuropsychological, and psychophysical evidence indicate that concept retrieval selectively engages specific sensory and motor brain systems involved in the acquisition of the retrieved concept. However, it remains unclear which supramodal cortical regions contribute to this process and what kind of information they represent. Here, we used representational similarity analysis of two large fMRI datasets with a searchlight approach to generate a detailed map of human brain regions where the semantic similarity structure across individual lexical concepts can be reliably detected.

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People with aphasia often show partial impairments on a given task. This trial-to-trial variability offers a potential window into understanding how damaged language networks function. We test the hypothesis that successful word reading in participants with phonological system damage reflects semantic system recruitment.

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Background And Objectives: Naming decline after left temporal lobe epilepsy (TLE) surgery is common and difficult to predict. Preoperative language fMRI may predict naming decline, but this application is still lacking evidence. We performed a large multicenter cohort study of the effectiveness of fMRI in predicting naming deficits after left TLE surgery.

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The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex.

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