Result 1 - 10 of total 404
1971
| Title variant | Sammlung ; Works |
|---|---|
| Language | English |
| Dates of publication | 1971-9999 |
| Publisher | Clarendon Press |
| Publishing place | Oxford |
| Document type | Book |
| Database | Former special subject collection: coastal and deep sea fishing |
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Brain communications
2023 Volume 5, Issue 2, Page(s) fcad040
Abstract: Adult diffuse gliomas are among the most difficult brain disorders to treat in part due to a lack of clarity regarding the anatomical origins and mechanisms of migration of the tumours. While the importance of studying networks of glioma spread has been ... ...
| Abstract | Adult diffuse gliomas are among the most difficult brain disorders to treat in part due to a lack of clarity regarding the anatomical origins and mechanisms of migration of the tumours. While the importance of studying networks of glioma spread has been recognized for at least 80 years, the ability to carry out such investigations in humans has emerged only recently. Here, we comprehensively review the fields of brain network mapping and glioma biology to provide a primer for investigators interested in merging these areas of inquiry for the purposes of translational research. Specifically, we trace the historical development of ideas in both brain network mapping and glioma biology, highlighting studies that explore clinical applications of network neuroscience, cells-of-origin of diffuse glioma and glioma-neuronal interactions. We discuss recent research that has merged neuro-oncology and network neuroscience, finding that the spatial distribution patterns of gliomas follow intrinsic functional and structural brain networks. Ultimately, we call for more contributions from network neuroimaging to realize the translational potential of cancer neuroscience. |
|---|---|
| Language | English |
| Publishing date | 2023-02-21 |
| Publishing country | England |
| Document type | Journal Article ; Review |
| ISSN | 2632-1297 |
| ISSN (online) | 2632-1297 |
| DOI | 10.1093/braincomms/fcad040 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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2021 Volume 241, Page(s) 118409
Abstract: Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. While ... ...
| Abstract | Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. While visualization techniques have been developed to interpret CNNs, bias inherent in the method of encoding abstract input data, as well as the natural variance of deep learning models, detract from the accuracy of these techniques. We introduce a stochastic encoding method in an ensemble of CNNs to classify functional connectomes by sex. We applied our method to resting-state and task data from the UK BioBank, using two visualization techniques to measure the salience of three brain networks involved in task- and resting-states, and their interaction. To regress confounding factors such as head motion, age, and intracranial volume, we introduced a multivariate balancing algorithm to ensure equal distributions of such covariates between classes in our data. We achieved a final AUROC of 0.8459. We found that resting-state data classifies more accurately than task data, with the inner salience network playing the most important role of the three networks overall in classification of resting-state data and connections to the central executive network in task data. |
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| MeSH term(s) | Biological Specimen Banks ; Brain/diagnostic imaging ; Brain/physiology ; Databases, Factual ; Deep Learning ; Female ; Humans ; Magnetic Resonance Imaging/methods ; Male ; Nerve Net/diagnostic imaging ; Nerve Net/physiology ; Psychomotor Performance/physiology ; Rest/physiology ; Sex Characteristics ; United Kingdom/epidemiology |
| Language | English |
| Publishing date | 2021-07-20 |
| Publishing country | United States |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 1147767-2 |
| ISSN | 1095-9572 ; 1053-8119 |
| ISSN (online) | 1095-9572 |
| ISSN | 1053-8119 |
| DOI | 10.1016/j.neuroimage.2021.118409 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 3664: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
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| Zs.MO 7: Show issues |
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BMJ Open Sport & Exercise Medicine, Vol 7, Iss
a two-year longitudinal observational study of concussion in motorsport
2021 Volume 1
Abstract: Introduction Concussion is a clinical diagnosis, based on self-reported patient symptoms supported by clinical assessments across many domains including postural control, ocular/vestibular dysfunction, and neurocognition. Concussion incidence may be ... ...
| Abstract | Introduction Concussion is a clinical diagnosis, based on self-reported patient symptoms supported by clinical assessments across many domains including postural control, ocular/vestibular dysfunction, and neurocognition. Concussion incidence may be rising in motorsport which, combined with unresolved challenges to accurate diagnosis and lack of guidance on the optimal return-to-race timeframe, creates a difficult environment for healthcare practitioners.Methods and analysis Research Evaluating Sports ConcUssion Events—Rapid Assessment of Concussion and Evidence for Return (RESCUE-RACER) evaluates motorsports competitors at baseline (Competitor Assessment at Baseline; Ocular, Neuroscientific (CArBON) study) and post-injury (Concussion Assessment and Return to motorSport (CARS) study), including longitudinal data. CArBON collects pre-injury neuroscientific data; CARS repeats the CArBON battery sequentially during recovery for competitors involved in a potentially concussive event. As its primary outcome, RESCUE-RACER will develop the evidence base for an accurate trackside diagnostic tool. Baseline objective clinical scoring (Sport Concussion Assessment Tool—5th edition (SCAT5)) and neurocognitive data (Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT)) will be assessed for specificity to motorsport and relationship to existing examinations. Changes to SCAT5 and ocular, vestibular, and reaction time function (Dx 100) will be estimated by the reliability change index as a practical tool for trackside diagnosis. Neuropsychological (Cambridge Neuropsychological Test Automated Battery (CANTAB)) assessments, brain MRI (7 Tesla) and salivary biomarkers will be compared with the new tool to establish utility in diagnosing and monitoring concussive injuries.Ethics and dissemination Ethical approval was received from East of England-Cambridge Central Research Ethics Committee (18/EE/0141). Participants will be notified of study outcomes via publications (to administrators) and summary reports (funder ... |
|---|---|
| Keywords | Medicine (General) ; R5-920 |
| Subject code | 170 |
| Language | English |
| Publishing date | 2021-02-01T00:00:00Z |
| Publisher | BMJ Publishing Group |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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2024 Volume 45, Issue 5, Page(s) e26555
Abstract: Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study ... ...
| Abstract | Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance. |
|---|---|
| MeSH term(s) | Humans ; Artificial Intelligence ; Schizophrenia/diagnostic imaging ; Neuroimaging ; Machine Learning ; Diagnosis, Computer-Assisted |
| Language | English |
| Publishing date | 2024-03-21 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 1197207-5 |
| ISSN | 1097-0193 ; 1065-9471 |
| ISSN (online) | 1097-0193 |
| ISSN | 1065-9471 |
| DOI | 10.1002/hbm.26555 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 4028: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (2.OG) ab Jg. 2022: Lesesaal (EG) |
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Neuroscience and biobehavioral reviews
2021 Volume 127, Page(s) 146–157
Abstract: To date, neuroimaging research has had a limited focus on non-social features of autism. As a result, neurobiological explanations for atypical sensory perception in autism are lacking. To address this, we quantitively condensed findings from the non- ... ...
| Abstract | To date, neuroimaging research has had a limited focus on non-social features of autism. As a result, neurobiological explanations for atypical sensory perception in autism are lacking. To address this, we quantitively condensed findings from the non-social autism fMRI literature in line with the current best practices for neuroimaging meta-analyses. Using activation likelihood estimation (ALE), we conducted a series of robust meta-analyses across 83 experiments from 52 fMRI studies investigating differences between autistic (n = 891) and typical (n = 967) participants. We found that typical controls, compared to autistic people, show greater activity in the prefrontal cortex (BA9, BA10) during perception tasks. More refined analyses revealed that, when compared to typical controls, autistic people show greater recruitment of the extrastriate V2 cortex (BA18) during visual processing. Taken together, these findings contribute to our understanding of current theories of autistic perception, and highlight some of the challenges of cognitive neuroscience research in autism. |
|---|---|
| MeSH term(s) | Autistic Disorder ; Humans ; Magnetic Resonance Imaging ; Neuroimaging ; Parietal Lobe ; Prefrontal Cortex ; Visual Perception |
| Language | English |
| Publishing date | 2021-04-19 |
| Publishing country | United States |
| Document type | Journal Article ; Meta-Analysis ; Research Support, Non-U.S. Gov't ; Review |
| ZDB-ID | 282464-4 |
| ISSN | 1873-7528 ; 0149-7634 |
| ISSN (online) | 1873-7528 |
| ISSN | 0149-7634 |
| DOI | 10.1016/j.neubiorev.2021.04.014 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 1371: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.
BMJ open sport & exercise medicine
2021 Volume 7, Issue 1, Page(s) e000879
Abstract: Introduction: Concussion is a clinical diagnosis, based on self-reported patient symptoms supported by clinical assessments across many domains including postural control, ocular/vestibular dysfunction, and neurocognition. Concussion incidence may be ... ...
| Abstract | Introduction: Concussion is a clinical diagnosis, based on self-reported patient symptoms supported by clinical assessments across many domains including postural control, ocular/vestibular dysfunction, and neurocognition. Concussion incidence may be rising in motorsport which, combined with unresolved challenges to accurate diagnosis and lack of guidance on the optimal return-to-race timeframe, creates a difficult environment for healthcare practitioners. Methods and analysis: Research Evaluating Sports ConcUssion Events-Rapid Assessment of Concussion and Evidence for Return (RESCUE-RACER) evaluates motorsports competitors at baseline (Competitor Assessment at Baseline; Ocular, Neuroscientific (CArBON) study) and post-injury (Concussion Assessment and Return to motorSport (CARS) study), including longitudinal data. CArBON collects pre-injury neuroscientific data; CARS repeats the CArBON battery sequentially during recovery for competitors involved in a potentially concussive event. As its primary outcome, RESCUE-RACER will develop the evidence base for an accurate trackside diagnostic tool. Baseline objective clinical scoring (Sport Concussion Assessment Tool-5th edition (SCAT5)) and neurocognitive data (Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT)) will be assessed for specificity to motorsport and relationship to existing examinations. Changes to SCAT5 and ocular, vestibular, and reaction time function (Dx 100) will be estimated by the reliability change index as a practical tool for trackside diagnosis. Neuropsychological (Cambridge Neuropsychological Test Automated Battery (CANTAB)) assessments, brain MRI (7 Tesla) and salivary biomarkers will be compared with the new tool to establish utility in diagnosing and monitoring concussive injuries. Ethics and dissemination: Ethical approval was received from East of England-Cambridge Central Research Ethics Committee (18/EE/0141). Participants will be notified of study outcomes via publications (to administrators) and summary reports (funder communications). Ideally, all publications will be open access. Trial registration number: February 2019 nationally (Central Portfolio Management System 38259) and internationally (ClinicalTrials.gov NCT03844282). |
|---|---|
| Language | English |
| Publishing date | 2021-01-13 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2817580-3 |
| ISSN | 2055-7647 |
| ISSN | 2055-7647 |
| DOI | 10.1136/bmjsem-2020-000879 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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2021 Volume 12, Issue 1, Page(s) 34
Abstract: Background: Autism has previously been characterized by both structural and functional differences in brain connectivity. However, while the literature on single-subject derivations of functional connectivity is extensively developed, similar methods of ...
| Abstract | Background: Autism has previously been characterized by both structural and functional differences in brain connectivity. However, while the literature on single-subject derivations of functional connectivity is extensively developed, similar methods of structural connectivity or similarity derivation from T1 MRI are less studied. Methods: We introduce a technique of deriving symmetric similarity matrices from regional histograms of grey matter volumes estimated from T1-weighted MRIs. We then validated the technique by inputting the similarity matrices into a convolutional neural network (CNN) to classify between participants with autism and age-, motion-, and intracranial-volume-matched controls from six different databases (29,288 total connectomes, mean age = 30.72, range 0.42-78.00, including 1555 subjects with autism). We compared this method to similar classifications of the same participants using fMRI connectivity matrices as well as univariate estimates of grey matter volumes. We further applied graph-theoretical metrics on output class activation maps to identify areas of the matrices that the CNN preferentially used to make the classification, focusing particularly on hubs. Limitations: While this study used a large sample size, the majority of data was from a young age group; furthermore, to make a viable machine learning study, we treated autism, a highly heterogeneous condition, as a binary label. Thus, these results are not necessarily generalizable to all subtypes and age groups in autism. Results: Our models gave AUROCs of 0.7298 (69.71% accuracy) when classifying by only structural similarity, 0.6964 (67.72% accuracy) when classifying by only functional connectivity, and 0.7037 (66.43% accuracy) when classifying by univariate grey matter volumes. Combining structural similarity and functional connectivity gave an AUROC of 0.7354 (69.40% accuracy). Analysis of classification performance across age revealed the greatest accuracy in adolescents, in which most data were present. Graph analysis of class activation maps revealed no distinguishable network patterns for functional inputs, but did reveal localized differences between groups in bilateral Heschl's gyrus and upper vermis for structural similarity. Conclusion: This study provides a simple means of feature extraction for inputting large numbers of structural MRIs into machine learning models. Our methods revealed a unique emphasis of the deep learning model on the structure of the bilateral Heschl's gyrus when characterizing autism. |
|---|---|
| MeSH term(s) | Adolescent ; Adult ; Autistic Disorder/diagnostic imaging ; Humans ; Magnetic Resonance Imaging |
| Language | English |
| Publishing date | 2021-05-10 |
| Publishing country | England |
| Document type | Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't |
| ZDB-ID | 2540930-X |
| ISSN | 2040-2392 ; 2040-2392 |
| ISSN (online) | 2040-2392 |
| ISSN | 2040-2392 |
| DOI | 10.1186/s13229-021-00439-5 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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2020 Volume 87, Issue 1, Page(s) E80–E81
| MeSH term(s) | Brain ; Cerebrum ; Neurosurgery ; Neurosurgical Procedures ; Organizations |
|---|---|
| Language | English |
| Publishing date | 2020-04-21 |
| Publishing country | United States |
| Document type | Letter ; Research Support, Non-U.S. Gov't ; Comment |
| ZDB-ID | 135446-2 |
| ISSN | 1524-4040 ; 0148-396X |
| ISSN (online) | 1524-4040 |
| ISSN | 0148-396X |
| DOI | 10.1093/neuros/nyaa094 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 1424: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
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| Zs.MO 539: Show issues |
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Cortex; a journal devoted to the study of the nervous system and behavior
2024 Volume 173, Page(s) 1–15
Abstract: The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination ... ...
| Abstract | The extent to which tumour-infiltrated brain tissue contributes to cognitive function remains unclear. We tested the hypothesis that cortical tissue infiltrated by diffuse gliomas participates in large-scale cognitive circuits using a unique combination of intracranial electrocorticography (ECoG) and resting-state functional magnetic resonance (fMRI) imaging in four patients. We also assessed the relationship between functional connectivity with tumour-infiltrated tissue and long-term cognitive outcomes in a larger, overlapping cohort of 17 patients. We observed significant task-related high gamma (70-250 Hz) power modulations in tumour-infiltrated cortex in response to increased cognitive effort (i.e., switch counting compared to simple counting), implying preserved functionality of neoplastic tissue for complex tasks probing executive function. We found that tumour locations corresponding to task-responsive electrodes exhibited functional connectivity patterns that significantly co-localised with canonical brain networks implicated in executive function. Specifically, we discovered that tumour-infiltrated cortex with larger task-related high gamma power modulations tended to be more functionally connected to the dorsal attention network (DAN). Finally, we demonstrated that tumour-DAN connectivity is evident across a larger cohort of patients with gliomas and that it relates to long-term postsurgical outcomes in goal-directed attention. Overall, this study contributes convergent fMRI-ECoG evidence that tumour-infiltrated cortex participates in large-scale neurocognitive circuits that support executive function in health. These findings underscore the potential clinical utility of mapping large-scale connectivity of tumour-infiltrated tissue in the care of patients with diffuse gliomas. |
|---|---|
| MeSH term(s) | Humans ; Brain/physiology ; Executive Function/physiology ; Cognition/physiology ; Brain Mapping/methods ; Magnetic Resonance Imaging/methods ; Glioma/diagnostic imaging ; Neural Pathways/physiology |
| Language | English |
| Publishing date | 2024-01-30 |
| Publishing country | Italy |
| Document type | Journal Article |
| ZDB-ID | 280622-8 |
| ISSN | 1973-8102 ; 0010-9452 |
| ISSN (online) | 1973-8102 |
| ISSN | 0010-9452 |
| DOI | 10.1016/j.cortex.2024.01.004 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
| Zs.A 687: Show issues | Location: Je nach Verfügbarkeit (siehe Angabe bei Bestand) bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular Jg. 1995 - 2021: Lesesall (1.OG) ab Jg. 2022: Lesesaal (EG) |
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