scholarly journals An evaluation of language in brain tumour patients using a new cognitive-motivated testing protocol

2021 ◽  
Author(s):  
◽  
Josh Faulkner
Keyword(s):  
Task Performance ◽  
Brain Tumour ◽  
Language Processing ◽  
Test Performance ◽  
Cognitive Skills ◽  
Motor Planning ◽  
Semantic Knowledge ◽  
Lexical Selection ◽  
Core Skills ◽  
Lesion Symptom Mapping

<p>In patients undergoing tumour resection surgery, assessment of language is vital, given its crucial role in everyday social functioning. However, despite the unique neuropathological mechanisms in tumours, current literature presents variable results regarding language capabilities in this population. In this thesis we have developed a new neuropsychological test battery, the Brief Language Assessment for Surgical Tumours (BLAST), to specifically evaluate language in brain tumour patients. The BLAST adopts a core skills approach, which identifies and examines 11 core cognitive skills that have been derived based on current cognitive and psycholinguistic theories, and are required for everyday language processing. In this study, we administered the BLAST to a cohort of 40 undifferentiated tumour surgery patients, both pre and postoperatively.  Also tested were 60 healthy controls categorised into three age groups (18-29, 30-50 and 51+years). We examined various aspects of overall test performance in order to evaluate: 1) the overall sensitivity of the test battery at detecting abnormalities in this population; 2) selectivity: the relative incidence of impairments across the various subtests; and 3) their sensitivity to change following surgery. We also explored the effects of lesion localisation and other lesion characteristics (malignancy, oedema and volume) on test performance. Following this, we then used participants' test performance to create operationalised measures of our 11 core cognitive skills, and evaluated these measures in a similar way to the basic test scores. Finally, we used Voxel-Based Lesion Symptom Mapping to determine the specific anatomical predictors for each core cognitive skill score. When investigating overall task performance, we found that 94% of preoperative patients and 90% of postoperative patients were impaired in at least one task within the BLAST. Also, 65% and 68% of patients had impaired scores on at least one core skill preoperatively and postoperatively respectively. It was also found that the core skills measures were effective at discriminating amongst different neurological profiles. Specifically, patients with a left posterior tumour had significantly lower scores than other groups on measures of accessing semantic knowledge, lexical selection and phonological encoding, either pre or postoperatively, or both. Conversely, patients with a left frontal tumour had significantly lower scores on measures of articulatory motor planning and verb retrieval. Our Voxel-Lesion-Symptom-Mapping analysis corroborated these findings. Lesions within the left superior temporal lobe significantly predicted lows scores in accessing semantic knowledge, lexical selection and phonological encoding. Conversely, lesions within the left inferior, as well as the superior posterior frontal lobe, significantly predicted low scores on goal-driven response selection, articulatory-motor planning and verb retrieval.  We conclude that a core skills approach may be a more effective means of assessing language in tumour populations than more conventional tools that emphasise overall task performance. Such derived measures are sensitive to impairments in this population, and are less likely to be confounded by nonlinguistic impairments that can impact significantly on overall task scores. They may also be useful in guiding postoperative rehabilitation. Further, the scores derived here are associated with quite specific neural substrates, making them potentially useful in guiding surgery and reducing postoperative linguistic deficits. Finally, we conclude that the investigation of tumour populations can also provide unique theoretical insights into language processing and its neural underpinnings in its own right.</p>

scholarly journals An evaluation of language in brain tumour patients using a new cognitive-motivated testing protocol

2021 ◽  
Author(s):  
◽  
Josh Faulkner
Keyword(s):  
Task Performance ◽  
Brain Tumour ◽  
Language Processing ◽  
Test Performance ◽  
Cognitive Skills ◽  
Motor Planning ◽  
Semantic Knowledge ◽  
Lexical Selection ◽  
Core Skills ◽  
Lesion Symptom Mapping

<p>In patients undergoing tumour resection surgery, assessment of language is vital, given its crucial role in everyday social functioning. However, despite the unique neuropathological mechanisms in tumours, current literature presents variable results regarding language capabilities in this population. In this thesis we have developed a new neuropsychological test battery, the Brief Language Assessment for Surgical Tumours (BLAST), to specifically evaluate language in brain tumour patients. The BLAST adopts a core skills approach, which identifies and examines 11 core cognitive skills that have been derived based on current cognitive and psycholinguistic theories, and are required for everyday language processing. In this study, we administered the BLAST to a cohort of 40 undifferentiated tumour surgery patients, both pre and postoperatively.  Also tested were 60 healthy controls categorised into three age groups (18-29, 30-50 and 51+years). We examined various aspects of overall test performance in order to evaluate: 1) the overall sensitivity of the test battery at detecting abnormalities in this population; 2) selectivity: the relative incidence of impairments across the various subtests; and 3) their sensitivity to change following surgery. We also explored the effects of lesion localisation and other lesion characteristics (malignancy, oedema and volume) on test performance. Following this, we then used participants' test performance to create operationalised measures of our 11 core cognitive skills, and evaluated these measures in a similar way to the basic test scores. Finally, we used Voxel-Based Lesion Symptom Mapping to determine the specific anatomical predictors for each core cognitive skill score. When investigating overall task performance, we found that 94% of preoperative patients and 90% of postoperative patients were impaired in at least one task within the BLAST. Also, 65% and 68% of patients had impaired scores on at least one core skill preoperatively and postoperatively respectively. It was also found that the core skills measures were effective at discriminating amongst different neurological profiles. Specifically, patients with a left posterior tumour had significantly lower scores than other groups on measures of accessing semantic knowledge, lexical selection and phonological encoding, either pre or postoperatively, or both. Conversely, patients with a left frontal tumour had significantly lower scores on measures of articulatory motor planning and verb retrieval. Our Voxel-Lesion-Symptom-Mapping analysis corroborated these findings. Lesions within the left superior temporal lobe significantly predicted lows scores in accessing semantic knowledge, lexical selection and phonological encoding. Conversely, lesions within the left inferior, as well as the superior posterior frontal lobe, significantly predicted low scores on goal-driven response selection, articulatory-motor planning and verb retrieval.  We conclude that a core skills approach may be a more effective means of assessing language in tumour populations than more conventional tools that emphasise overall task performance. Such derived measures are sensitive to impairments in this population, and are less likely to be confounded by nonlinguistic impairments that can impact significantly on overall task scores. They may also be useful in guiding postoperative rehabilitation. Further, the scores derived here are associated with quite specific neural substrates, making them potentially useful in guiding surgery and reducing postoperative linguistic deficits. Finally, we conclude that the investigation of tumour populations can also provide unique theoretical insights into language processing and its neural underpinnings in its own right.</p>

scholarly journals The Cologne Picture Naming Test for Language Mapping and Monitoring (CoNaT): An Open Set of 100 Black and White Object Drawings

2021 ◽  
Vol 12 ◽  
Author(s):  
Carolin Weiss Lucas ◽  
Julia Pieczewski ◽  
Sophia Kochs ◽  
Charlotte Nettekoven ◽  
Christian Grefkes ◽  
...  
Keyword(s):  
Task Performance ◽  
Brain Tumour ◽  
Educational Level ◽  
Picture Naming ◽  
Healthy Subjects ◽  
Clinical Use ◽  
Language Mapping ◽  
Black And White ◽  
Language Functions ◽  
Open Set

Language assessment using a picture naming task crucially relies on the interpretation of the given verbal response by the rater. To avoid misinterpretations, a language-specific and linguistically controlled set of unambiguous, clearly identifiable and common object–word pairs is mandatory. We, here, set out to provide an open-source set of black and white object drawings, particularly suited for language mapping and monitoring, e.g., during awake brain tumour surgery or transcranial magnetic stimulation, in German language. A refined set of 100 black and white drawings was tested in two consecutive runs of randomised picture order and was analysed in respect of correct, prompt, and reliable object recognition and naming in a series of 132 healthy subjects between 18 and 84 years (median 25 years, 64% females) and a clinical pilot cohort of 10 brain tumour patients (median age 47 years, 80% males). The influence of important word- and subject-related factors on task performance and reliability was investigated. Overall, across both healthy subjects and patients, excellent correct object naming rates (97 vs. 96%) as well as high reliability coefficients (Goodman–Kruskal's gamma = 0.95 vs. 0.86) were found. However, the analysis of variance revealed a significant, overall negative effect of low word frequency (p &lt; 0.05) and high age (p &lt; 0.0001) on task performance whereas the effect of a low educational level was only evident for the subgroup of 72 or more years of age (p &lt; 0.05). Moreover, a small learning effect was observed across the two runs of the test (p &lt; 0.001). In summary, this study provides an overall robust and reliable picture naming tool, optimised for the clinical use to map and monitor language functions in patients. However, individual familiarisation before the clinical use remains advisable, especially for subjects that are comparatively prone to spontaneous picture naming errors such as older subjects of low educational level and patients with clinically apparent word finding difficulties.

scholarly journals Teste de Progresso na Escola Médica: uma Revisão Sistemática acerca da Literatura

2020 ◽  
Vol 44 (1) ◽  
Author(s):  
Ademir Garcia Reberti ◽  
Nayme Hechem Monfredini ◽  
Olavo Franco Ferreira Filho ◽  
Dalton Francisco de Andrade ◽  
Carlos Eduardo Andrade Pinheiro ◽  
...  
Keyword(s):  
Student Performance ◽  
Test Performance ◽  
Cognitive Skills ◽  
Assessment Tool ◽  
Objective Assessment ◽  
Active Role ◽  
Medical Schools ◽  
Multiple Choice Questions ◽  
Progress Test ◽  
Advanced Search

Abstract: Progress Test is an objective assessment, consisting of 60 to 150 multiple-choice questions, designed to promote an assessment of the cognitive skills expected at the end of undergraduate school. This test is applied to all students on the same day, so that it is possible to compare the results between grades and analyze the development of knowledge performance throughout the course. This study aimed to carry out a systematic and literary review about Progress Test in medical schools in Brazil and around the world, understanding the benefits of its implementation for the development of learning for the student, the teacher and the institution. The study was carried out from July 2018 to April 2019, which addressed articles published from January 2002 to March 2019. The keywords used were: “Progress Test in Medical Schools” and “Item Response Theory in Medicine” in the PubMed, Scielo, and Lilacs platforms. There was no language limitation in article selection, but the research was carried out in English. A total of 192,026 articles were identified, and after applying advanced search filters, 11 articles were included in the study. The Progress Test (PTMed) has been applied in medical schools, either alone or in groups of partner schools, since the late 1990s. The test results build the students’ performance curves, which allow us to identify weaknesses and strengths of the students in the several areas of knowledge related to the course. The Progress Test is not an exclusive instrument for assessing student performance, but it is also important as an assessment tool for academic management use and thus, it is crucial that institutions take an active role in the preparation and analysis of this assessment data. Assessments designed to test clinical competence in medical students need to be valid and reliable. For the evaluative method to be valid it is necessary that the subject be extensively reviewed and studied, aiming at improvements and adjustments in test performance.

scholarly journals Towards Robust Text Classification with Semantics-Aware Recurrent Neural Architecture

2019 ◽  
Vol 1 (2) ◽  
pp. 575-589 ◽  
Author(s):  
Blaž Škrlj ◽  
Jan Kralj ◽  
Nada Lavrač ◽  
Senja Pollak
Keyword(s):  
Text Mining ◽  
Language Processing ◽  
Text Classification ◽  
Deep Neural Networks ◽  
Semantic Knowledge ◽  
Text Documents ◽  
Neural Architecture ◽  
Classification Tasks ◽  
And Gender ◽  
Semantic Resources

Deep neural networks are becoming ubiquitous in text mining and natural language processing, but semantic resources, such as taxonomies and ontologies, are yet to be fully exploited in a deep learning setting. This paper presents an efficient semantic text mining approach, which converts semantic information related to a given set of documents into a set of novel features that are used for learning. The proposed Semantics-aware Recurrent deep Neural Architecture (SRNA) enables the system to learn simultaneously from the semantic vectors and from the raw text documents. We test the effectiveness of the approach on three text classification tasks: news topic categorization, sentiment analysis and gender profiling. The experiments show that the proposed approach outperforms the approach without semantic knowledge, with highest accuracy gain (up to 10%) achieved on short document fragments.

scholarly journals TMIC-46. GLIOMA-INDUCED SYNAPTOGENESIS IS ENRICHED WITHIN FUNCTIONAL CONNECTIVITY NETWORK HUBS AND INFLUENCES LANGUAGE PROCESSING IN ADULT IDH WT GLIOBLASTOMA

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi257-vi258
Author(s):  
Saritha Krishna ◽  
Sofia Kakaizada ◽  
Claudia Valdivia ◽  
Kyounghee Seo ◽  
David Raleigh ◽  
...  
Keyword(s):  
Neural Networks ◽  
Functional Connectivity ◽  
Task Performance ◽  
Language Processing ◽  
Hippocampal Neurons ◽  
Neuronal Excitability ◽  
Glioma Cells ◽  
Network Connectivity ◽  
Marker Expression ◽  
Neuron Interactions

Abstract INTRODUCTION Little is known about the mechanisms by which gliomas integrate into functional neural networks and influence complex cognitive processes such as language. Glioma-neuron interactions are bidirectional, with increased neuronal activity promoting tumor growth and the latter in turn influencing neuronal excitability and synaptic connections. It remains unknown whether glioma-neuron interactions play a role in maintaining long-range neural networks subserving cognition in humans. We test the hypothesis that glioma-neuron interactions (“synaptogenic glioma cells”) are enriched within intratumoral high functional connectivity (FC) network hubs, thereby influencing language processing via release of synaptogenic factors into the tumor microenvironment. METHODS We employed magnetoencephalography imaginary coherence measures to identify intratumoral high (HFC) and low (LFC) functional connectivity network hubs in newly diagnosed glioblastoma patients. Primary patient samples and cultures from HFC and LFC sites were assessed for pre and post-synaptic marker expression (IF), cocultured with murine hippocampal neurons, and induced neuron organoids. ECOG Field recordings were performed on HFC/LFC tumors. Secreted proteins were measured from patient serum and LFC/HFC culture supernatant. Language assessments were performed to correlate task performance with FC measures. RESULTS Primary patient samples from HFC regions are enriched for glioblastoma cells with a synaptogenic profile as characterized by pre- and post-synaptic marker expression at both tissue and cellular level (coculture with mouse hippocampal neuron and organoid models). RNA sequencing and proteomic analyses from HFC samples revealed a neurogenic signature including thrombospondin 1 (TSP1). Overexpression of TSP1 in LFC primary patient cultures rescues the synaptogenic and proliferative phenotype. Importantly, we found a linear relationship between intratumoral HFC with patient serum TSP1 (ELISA) with a further correlation with language task performance. CONCLUSION An enriched population of synaptogenic glioma cells are organized within intratumoral high network connectivity regions. Glioma-induced neuronal synaptogenesis contributes to the microenvironment in support of network connectivity through secretion of TSP1.

scholarly journals Common Ground Information Affects Reference Resolution: Evidence From Behavioral Data, ERPs, and Eye-Tracking

2020 ◽  
Vol 11 ◽  
Author(s):  
Maria Richter ◽  
Mariella Paul ◽  
Barbara Höhle ◽  
Isabell Wartenburger
Keyword(s):  
Eye Tracking ◽  
Language Processing ◽  
Cognitive Skills ◽  
Common Ground ◽  
Event Related Potentials ◽  
Referential Communication ◽  
Reference Resolution ◽  
Early Integration ◽  
Related Potentials ◽  
Socially Situated

One of the most important social cognitive skills in humans is the ability to “put oneself in someone else’s shoes,” that is, to take another person’s perspective. In socially situated communication, perspective taking enables the listener to arrive at a meaningful interpretation of what is said (sentence meaning) and what is meant (speaker’s meaning) by the speaker. To successfully decode the speaker’s meaning, the listener has to take into account which information he/she and the speaker share in their common ground (CG). We here further investigated competing accounts about when and how CG information affects language comprehension by means of reaction time (RT) measures, accuracy data, event-related potentials (ERPs), and eye-tracking. Early integration accounts would predict that CG information is considered immediately and would hence not expect to find costs of CG integration. Late integration accounts would predict a rather late and effortful integration of CG information during the parsing process that might be reflected in integration or updating costs. Other accounts predict the simultaneous integration of privileged ground (PG) and CG perspectives. We used a computerized version of the referential communication game with object triplets of different sizes presented visually in CG or PG. In critical trials (i.e., conflict trials), CG information had to be integrated while privileged information had to be suppressed. Listeners mastered the integration of CG (response accuracy 99.8%). Yet, slower RTs, and enhanced late positivities in the ERPs showed that CG integration had its costs. Moreover, eye-tracking data indicated an early anticipation of referents in CG but an inability to suppress looks to the privileged competitor, resulting in later and longer looks to targets in those trials, in which CG information had to be considered. Our data therefore support accounts that foresee an early anticipation of referents to be in CG but a rather late and effortful integration if conflicting information has to be processed. We show that both perspectives, PG and CG, contribute to socially situated language processing and discuss the data with reference to theoretical accounts and recent findings on the use of CG information for reference resolution.

scholarly journals A Natural Language Processing Approach to Automated Highlighting of New Information in Clinical Notes

2020 ◽  
Vol 10 (8) ◽  
pp. 2824
Author(s):  
Yu-Hsiang Su ◽  
Ching-Ping Chao ◽  
Ling-Chien Hung ◽  
Sheng-Feng Sung ◽  
Pei-Ju Lee
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Task Performance ◽  
Language Processing ◽  
Automated Identification ◽  
Clinical Notes ◽  
New Information ◽  
Perceived Workload ◽  
The Impact ◽  
User Experiment

Electronic medical records (EMRs) have been used extensively in most medical institutions for more than a decade in Taiwan. However, information overload associated with rapid accumulation of large amounts of clinical narratives has threatened the effective use of EMRs. This situation is further worsened by the use of “copying and pasting”, leading to lots of redundant information in clinical notes. This study aimed to apply natural language processing techniques to address this problem. New information in longitudinal clinical notes was identified based on a bigram language model. The accuracy of automated identification of new information was evaluated using expert annotations as the reference standard. A two-stage cross-over user experiment was conducted to evaluate the impact of highlighting of new information on task demands, task performance, and perceived workload. The automated method identified new information with an F1 score of 0.833. The user experiment found a significant decrease in perceived workload associated with a significantly higher task performance. In conclusion, automated identification of new information in clinical notes is feasible and practical. Highlighting of new information enables healthcare professionals to grasp key information from clinical notes with less perceived workload.

scholarly journals Math-word embedding in math search and semantic extraction

2020 ◽  
Vol 125 (3) ◽  
pp. 3017-3046 ◽  
Author(s):  
André Greiner-Petter ◽  
Abdou Youssef ◽  
Terry Ruas ◽  
Bruce R. Miller ◽  
Moritz Schubotz ◽  
...  
Keyword(s):  
Machine Learning ◽  
Information Retrieval ◽  
Language Processing ◽  
Digital Library ◽  
Question Answering ◽  
Semantic Knowledge ◽  
Word Embedding ◽  
Mathematical Functions ◽  
Search Tasks ◽  
Math Search

AbstractWord embedding, which represents individual words with semantically fixed-length vectors, has made it possible to successfully apply deep learning to natural language processing tasks such as semantic role-modeling, question answering, and machine translation. As math text consists of natural text, as well as math expressions that similarly exhibit linear correlation and contextual characteristics, word embedding techniques can also be applied to math documents. However, while mathematics is a precise and accurate science, it is usually expressed through imprecise and less accurate descriptions, contributing to the relative dearth of machine learning applications for information retrieval in this domain. Generally, mathematical documents communicate their knowledge with an ambiguous, context-dependent, and non-formal language. Given recent advances in word embedding, it is worthwhile to explore their use and effectiveness in math information retrieval tasks, such as math language processing and semantic knowledge extraction. In this paper, we explore math embedding by testing it on several different scenarios, namely, (1) math-term similarity, (2) analogy, (3) numerical concept-modeling based on the centroid of the keywords that characterize a concept, (4) math search using query expansions, and (5) semantic extraction, i.e., extracting descriptive phrases for math expressions. Due to the lack of benchmarks, our investigations were performed using the arXiv collection of STEM documents and carefully selected illustrations on the Digital Library of Mathematical Functions (DLMF: NIST digital library of mathematical functions. Release 1.0.20 of 2018-09-1, 2018). Our results show that math embedding holds much promise for similarity, analogy, and search tasks. However, we also observed the need for more robust math embedding approaches. Moreover, we explore and discuss fundamental issues that we believe thwart the progress in mathematical information retrieval in the direction of machine learning.

Cognitive Control along the Language Spectrum: From the Typical Bilingual Child to Language Impairment

2019 ◽  
Vol 40 (04) ◽  
pp. 256-271
Author(s):  
Klara Marton ◽  
Thorfun Gehebe ◽  
Lia Pazuelo
Keyword(s):  
Cognitive Control ◽  
Language Processing ◽  
Language Impairment ◽  
Cognitive Skills ◽  
Critical Role ◽  
Bilingual Children ◽  
Interference Control ◽  
Negative Effects ◽  
Control Functions ◽  
Language Deficit

AbstractCognitive control refers to the ability to perform goal-directed behaviors in the presence of other compelling actions or in the face of habitual practices. Cognitive control functions play a critical role in children's language processing and literacy development. In recent years, many clinicians have expanded their assessment and treatment to target specific cognitive skills. Our goal is to provide a review of recent findings on cognitive control functions in children with different language status (i.e., monolingual and bilingual children with and without language impairment). While children with language impairment show performance deficits in specific cognitive functions (e.g., working memory updating and interference control), typically developing bilingual children often outperform their monolingual peers in cognitive control tasks. However, the relationship between bilingualism and cognitive control has been controversial. Several factors that influence these variations are discussed. Given the findings on the joint impact of bilingualism and language impairment on cognitive control functions, we identify conditions in which bilingualism attenuates the negative effects of the language deficit and conditions in which language impairment has a stronger effect than bilingualism. Critical issues of bilingual assessment, suggestions, and future directions are discussed.

Metacognition, cognition and learning: Old dubitations and new directions

1994 ◽  
Vol 7 ◽  
pp. 18-31
Author(s):  
Graham Davidson
Keyword(s):  
Task Performance ◽  
Test Performance ◽  
Cultural Context ◽  
Cognitive Task ◽  
Cultural Groups ◽  
Cultural Research ◽  
New Directions ◽  
Level Of Knowledge ◽  
Cognition And Learning ◽  
Definition Of

Research into metacognition, a relatively new construct in the cognitive sciences, has been prodigious over the last decade. This is despite continuing doubts about its heuristic value. Initial doubts emphasised difficulties associated with definition of the construct, the limited predictive power of metacognitive task performance in relation to actual cognitive task or test performance and, relatedly, difficulties in operationalising the construct in specific thinking and problem solving contexts. Subsequent cross-cultural research has focussed on the degree to which metacognitive thinking is situationalised according to cultural context and thinking task, despite the implication that such thinking, by nature, is “multicontextual.” It then questioned the extent to which different social and cultural groups differ in their construction of the metacognitive level of knowledge and its relevance to their everyday life task performance and thinking.

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