8 results on '"Torlay, L"'
Search Results
2. A machine learning approach to explore cognitive signatures in patients with temporo-mesial epilepsy
- Author
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Roger, E., Torlay, L., Gardette, J., Mosca, C., Banjac, S., Minotti, L., Kahane, P., and Baciu, M.
- Published
- 2020
- Full Text
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3. Machine learning–XGBoost analysis of language networks to classify patients with epilepsy
- Author
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Torlay, L., Perrone-Bertolotti, M., Thomas, E., and Baciu, M.
- Published
- 2017
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- View/download PDF
4. Machine learning-XGBoost analysis of language networks to classify patients with epilepsy.
- Author
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Torlay, L, Perrone-Bertolotti, M, Thomas, E, Baciu, M, Torlay, L, Perrone-Bertolotti, M, Thomas, E, and Baciu, M
- Abstract
Our goal was to apply a statistical approach to allow the identification of atypical language patterns and to differentiate patients with epilepsy from healthy subjects, based on their cerebral activity, as assessed by functional MRI (fMRI). Patients with focal epilepsy show reorganization or plasticity of brain networks involved in cognitive functions, inducing 'atypical' (compared to 'typical' in healthy people) brain profiles. Moreover, some of these patients suffer from drug-resistant epilepsy, and they undergo surgery to stop seizures. The neurosurgeon should only remove the zone generating seizures and must preserve cognitive functions to avoid deficits. To preserve functions, one should know how they are represented in the patient's brain, which is in general different from that of healthy subjects. For this purpose, in the pre-surgical stage, robust and efficient methods are required to identify atypical from typical representations. Given the frequent location of regions generating seizures in the vicinity of language networks, one important function to be considered is language. The risk of language impairment after surgery is determined pre-surgically by mapping language networks. In clinical settings, cognitive mapping is classically performed with fMRI. The fMRI analyses allowing the identification of atypical patterns of language networks in patients are not sufficiently robust and require additional statistic approaches. In this study, we report the use of a statistical nonlinear machine learning classification, the Extreme Gradient Boosting (XGBoost) algorithm, to identify atypical patterns and classify 55 participants as healthy subjects or patients with epilepsy. XGBoost analyses were based on neurophysiological features in five language regions (three frontal and two temporal) in both hemispheres and activated with fMRI for a phonological (PHONO) and a semantic (SEM) language task. These features were combined into 135 cognitively plausible subset
- Published
- 2017
5. Modulation of Visually Induced Self-motion Illusions by α Transcranial Electric Stimulation over the Superior Parietal Cortex.
- Author
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Harquel S, Cian C, Torlay L, Cousin E, Barraud PA, Bougerol T, and Guerraz M
- Subjects
- Humans, Electric Stimulation, Parietal Lobe physiology, Cross-Over Studies, Illusions, Transcranial Direct Current Stimulation methods, Virtual Reality
- Abstract
The growing popularity of virtual reality systems has led to a renewed interest in understanding the neurophysiological correlates of the illusion of self-motion (vection), a phenomenon that can be both intentionally induced or avoided in such systems, depending on the application. Recent research has highlighted the modulation of α power oscillations over the superior parietal cortex during vection, suggesting the occurrence of inhibitory mechanisms in the sensorimotor and vestibular functional networks to resolve the inherent visuo-vestibular conflict. The present study aims to further explore this relationship and investigate whether neuromodulating these waves could causally affect the quality of vection. In a crossover design, 22 healthy volunteers received high amplitude and focused α-tACS (transcranial alternating current stimulation) over the superior parietal cortex while experiencing visually induced vection triggered by optokinetic stimulation. The tACS was tuned to each participant's individual α peak frequency, with θ-tACS and sham stimulation serving as controls. Overall, participants experienced better quality vection during α-tACS compared with control θ-tACS and sham stimulations, as quantified by the intensity of vection. The observed neuromodulation supports a causal relationship between parietal α oscillations and visually induced self-motion illusions, with their entrainment triggering overinhibition of the conflict within the sensorimotor and vestibular functional networks. These results confirm the potential of noninvasive brain stimulation for modulating visuo-vestibular conflicts, which could help to enhance the sense of presence in virtual reality environments., (© 2023 Massachusetts Institute of Technology.)
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- 2024
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6. Hippocampal activity during memory and visual perception: The role of representational content.
- Author
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Gardette J, Cousin E, Bourgin J, Torlay L, Pichat C, Moreaud O, and Hot P
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- Humans, Visual Perception physiology, Temporal Lobe physiology, Recognition, Psychology physiology, Magnetic Resonance Imaging, Hippocampus physiology, Perirhinal Cortex physiology
- Abstract
The functional organisation of the medial temporal lobe (MTL) has long been described on the basis of cognitive processes such as recollection or familiarity. However, this view has recently been challenged, and researchers have proposed decomposing cognitive phenomena into representations and operations. According to the representational view, representations, such as scenes for the hippocampus and objects for the perirhinal cortex, are critical in understanding the role of MTL regions in cognition. In the present study, 51 healthy young participants underwent functional magnetic resonance imaging (fMRI) while completing a visual-discrimination task. Subsequently, half of the participants performed a patch-cue recognition procedure in which "Rec" responses are believed to reflect the operation of pattern completion, whereas the other half performed a whole-item remember/know procedure. We replicated the previously-reported demonstration that hippocampal involvement in pattern completion is preferential for scenes as compared with objects. In contrast, the perirhinal cortex was more recruited for object processing than for scene processing. We further extended these results to the operations of strength-signal memory and visual discrimination. Finally, the modulation of hippocampal engagement in pattern completion by representational content was found to be specific to its anterior segment. This observation is consistent with the proposal that this segment would process broad/global representations, whereas the posterior hippocampus would perform sharp/local representations. Taken together, these results favour the representational view of MTL functional organisation, but support that this specialisation differs along the hippocampal long-axis., Competing Interests: Conflict of interest The authors declare that no conflict of interest exists., (Copyright © 2022 Elsevier Ltd. All rights reserved.)
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- 2022
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7. Prediction of the clinical and naming status after anterior temporal lobe resection in patients with epilepsy.
- Author
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Roger E, Torlay L, Banjac S, Mosca C, Minotti L, Kahane P, and Baciu M
- Abstract
By assessing the cognitive capital, neuropsychological evaluation (NPE) plays a vital role in the perioperative workup of patients with refractory focal epilepsy. In this retrospective study, we used cutting-edge statistical approaches to examine a group of 47 patients with refractory temporal lobe epilepsy (TLE), who underwent standard anterior temporal lobectomy (ATL). Our objective was to determine whether NPE may represent a robust predictor of the postoperative status, two years after surgery. Specifically, based on pre- and postsurgical neuropsychological data, we estimated the sensitivity of cognitive indicators to predict and to disentangle phenotypes associated with more or less favorable outcomes. Engel (ENG) scores were used to assess clinical outcome, and picture naming (NAM) performance to estimate naming status. Two methods were applied: (a) machine learning (ML) to explore cognitive sensitivity to postoperative outcomes; and (b) graph theory (GT) to assess network properties reflecting favorable vs. less favorable phenotypes after surgery. Specific neuropsychological indices assessing language, memory, and executive functions can globally predict outcomes. Interestingly, preoperative cognitive networks associated with poor postsurgical outcome already exhibit an atypical, highly modular and less densely interconnected configuration. We provide statistical and clinical tools to anticipate the condition after surgery and achieve a more personalized clinical management. Our results also shed light on possible mechanisms put in place for cognitive adaptation after acute injury of central nervous system in relation with surgery., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2021
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8. Hubs disruption in mesial temporal lobe epilepsy. A resting-state fMRI study on a language-and-memory network.
- Author
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Roger E, Pichat C, Torlay L, David O, Renard F, Banjac S, Attyé A, Minotti L, Lamalle L, Kahane P, and Baciu M
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- Adult, Cerebral Cortex diagnostic imaging, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction etiology, Epilepsy, Temporal Lobe complications, Epilepsy, Temporal Lobe diagnostic imaging, Female, Hippocampus diagnostic imaging, Hippocampus physiopathology, Humans, Limbic System diagnostic imaging, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net diagnostic imaging, Young Adult, Cerebral Cortex physiopathology, Cognitive Dysfunction physiopathology, Connectome methods, Epilepsy, Temporal Lobe physiopathology, Language, Limbic System physiopathology, Memory physiology, Nerve Net physiopathology
- Abstract
Mesial temporal lobe epilepsy (mTLE) affects the brain networks at several levels and patients suffering from mTLE experience cognitive impairment for language and memory. Considering the importance of language and memory reorganization in this condition, the present study explores changes of the embedded language-and-memory network (LMN) in terms of functional connectivity (FC) at rest, as measured with functional MRI. We also evaluate the cognitive efficiency of the reorganization, that is, whether or not the reorganizations support or allow the maintenance of optimal cognitive functioning despite the seizure-related damage. Data from 37 patients presenting unifocal mTLE were analyzed and compared to 48 healthy volunteers in terms of LMN-FC using two methods: pairwise correlations (region of interest [ROI]-to-ROI) and graph theory. The cognitive efficiency of the LMN-FC reorganization was measured using correlations between FC parameters and language and memory scores. Our findings revealed a large perturbation of the LMN hubs in patients. We observed a hyperconnectivity of limbic areas near the dysfunctional hippocampus and mainly a hypoconnectivity for several cortical regions remote from the dysfunctional hippocampus. The loss of FC was more important in left mTLE (L-mTLE) than in right (R-mTLE) patients. The LMN-FC reorganization may not be always compensatory and not always useful for patients as it may be associated with lower cognitive performance. We discuss the different connectivity patterns obtained and conclude that interpretation of FC changes in relation to neuropsychological scores is important to determine cognitive efficiency, suggesting the concept of "connectome" would gain to be associated with a "cognitome" concept., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)
- Published
- 2020
- Full Text
- View/download PDF
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