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Schematic diagram of Baddeley's working memory model
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Temporal lobe epilepsy (TLE) is the most prevalent form of complex partial seizures with temporal lobe origin of electrical abnormality. Studies have shown that recurrent seizures affect all aspects of cognitive functioning, including memory, language, praxis, executive functions, and social judgment, among several others. In this article, we will...
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Context 1
... impairment carries immense clinical importance not only because of the disability that it leads to, but also because of its association with LTM. This association has been highlighted in the recent models of WM in the role of the "episodic buffer" thus linking it to LTM systems [5] [ Figure 1]. Thus consequently, LTM will also be affected if STM is impaired in TLE. ...
Citations
... Functional seizure diagnostic criteria varied across studies; 70 (83%) of 84 studies met criteria for documented functional seizures, with two (2%) of 84, three (3%) of 84, and nine (11%) of 84 describing procedures consistent with clinically established, probable, and possible functional seizures, respectively. 15 On average, studies reported data from four cognitive tests (range [1][2][3][4][5][6][7][8][9][10][11][12][13][14], across 4·4 domains (range 1-10). ...
... The proportion of men per group was 28% (range 0-82) for functional seizures, 41% (range 0-85) for epilepsy, and 31% (range 0-66) for healthy comparisons. Mean age of seizure onset (in years) was 29 (4) for functional seizures and 19 (6) for epilepsy, and proportion with reported psychiatric diagnoses was 46% (range 0-100) for functional seizures, 31% (range 0-77) for epilepsy, and 9% (range 0-69) for healthy comparisons (appendix pp [8][9][10][11][12][13][14][15][16][17][18][19][20]. ...
... 30 Moreover, only two longitudinal studies of cognition in functional seizures were identified, which prevents an examination of the natural course of cognition in functional seizures over time. Regarding seizure characteristics, many of the patients with functional seizures were taking antiseizure medications at the time of cognitive testing (appendix pp [8][9][10][11][12][13][14][15][16][17][18][19][20], and these medications can have cognitive sideeffects. Additionally, important clinical features of the epilepsy cohorts (eg, seizure localisation, frequency, and degree of response to medications) were infrequently reported despite the fact that all of these factors have the potential to affect cognitive functioning. ...
Background
Cognition is a core component of functional seizures, but the literature on cognition in this disorder has been heterogeneous, with no clear unifying profile emerging from individual studies. The aim of this study was to do a systematic review and meta-analysis of cognitive performance in adults with functional seizures compared with epilepsy (including left temporal lobe epilepsy) and compared with healthy non-seizure cohorts.
Methods
In this systematic review and meta-analysis, starting Feb 6, 2023, replicated and updated on Oct 31, 2023, a medical librarian searched MEDLINE, Embase, PsycINFO, and Web of Science. Inclusion criteria were full reports documenting raw or standardised cognitive test data in adults with functional seizures compared with adults with epilepsy, prospectively recruited healthy comparisons, or published norms. Grey literature was retained and there were no language or date restrictions. We excluded studies only reporting on mixed functional seizures and epilepsy,
or mixed functional neurological samples, with no pure functional seizures group. Risk of bias was evaluated using a modified version of the Newcastle–Ottawa Scale. People with lived experiences were not involved in the design or execution of this study. This study is registered as CRD42023392385 in PROSPERO.
Findings
Of 3834 records initially identified, 84 articles were retained, including 8654 participants (functional seizures 4193, epilepsy 3638, and healthy comparisons 823). Mean age was 36 years (SD 12) for functional seizures, 36 years (12) for epilepsy, and 34 years (10) for healthy comparisons, and the proportion of women per group was 72% (range 18–100) for functional seizures, 59% (range 15–100) for epilepsy, and 69% (range 34–100) for healthy comparisons. Data on race or ethnicity were rarely reported in the individual studies. Risk of bias was moderate.
Cognitive performance was better in people with functional seizures than those with epilepsy (Hedges’ g=0·17 [95% CI 0·10–0·25)], p<0·0001), with moderate-to-high heterogeneity (Q[56]=128·91, p=0·0001, I²=57%). The functional seizures group performed better than the epilepsy group on global cognition and intelligence quotient (g=0·15 [0·02–0·28], p=0·022) and language (g=0·28 [0·14–0·43], p=0·0001), but not other cognitive domains. A larger effect was noted in language tests when comparing functional seizures with left temporal lobe epilepsy (k=5; g=0·51 [0·10 to 0·91], p=0·015). The functional seizures group underperformed relative to healthy comparisons (g=−0·61 [−0·78 to −0·44], p<0·0001), with significant differences in all cognitive domains. Meta regressions examining effects
of multiple covariates on global cognition were not significant.
Interpretation
Patients with functional seizures have widespread cognitive impairments that are likely to be clinically meaningful on the basis of moderate effect sizes in multiple domains. These deficits might be slightly less severe than those seen in many patients with epilepsy but nevertheless argue for consideration of clinical assessment and treatment.
... The examination of EEG signals is a major way to detect epileptic seizures in the brain. 14 EEG is an important tool used in laboratories to identify different aspects of seizures based on its characteristics before and during the seizures. In the past two decades, many experimental studies have shown that seizures happen after occurring of some changes in the spatial and temporal patterns of EEG signals. ...
Epilepsy is a brain disorder that causes patients to have multiple seizures. About 30% of patients with epilepsy are not treated with medication or surgery. The abnormal activity of brain before occurring of a seizure (about a few minutes before a seizure occurs) are known as the preictal area. Therefore, if we can predict this state, we can control possible seizures by using appropriate medications. In this study, we present a method for predicting epileptic seizures using electroencephalogram (EEG) signals. The method can identify the preictal region that occurs before the onset of seizures. In our proposed method, first the noise removal of EEG signals is performed, and then the necessary features are extracted using a convolution neural network. Finally, we use the feature vectors in order to train multiple classifiers, fully connected layer, random forest, and support vector machines with linear kernel. Additionally, we apply maximum voting, which is an ensemble method, to classify preictal segments from interictal ones. In this study, using EEG signals of patients from CHB‐MIT dataset, we were able to achieve sensitivity of 90.76%.
... These tests include an electroencephalogram (EEG) to measure brain activity and imaging scans such as functional magnetic resonance imaging (fMRI) to identify any structural abnormalities in the brain. Epilepsy brings substantial changes to certain parts of the brain regions such as the hippocampus, amygdala, frontal cortex, temporal cortex, and olfactory cortex [9][10][11] . However, these structural changes occur in a rather slow progression. ...
Epilepsy is a chronic neurological disease, characterized by spontaneous, unprovoked, recurrent seizures that may lead to long-term disability and premature death. Despite significant efforts made to improve epilepsy detection clinically and pre-clinically, the pervasive presence of noise in EEG signals continues to pose substantial challenges to their effective application. In addition, discriminant features for epilepsy detection have not been investigated yet. The objective of this study is to develop a hybrid model for epilepsy detection from noisy and fragmented EEG signals. We hypothesized that a hybrid model could surpass existing single models in epilepsy detection. Our approach involves manual noise rejection and a novel statistical channel selection technique to detect epilepsy even from noisy EEG signals. Our proposed Base-2-Meta stacking classifier achieved notable accuracy (0.98 ± 0.05), precision (0.98 ± 0.07), recall (0.98 ± 0.05), and F1 score (0.98 ± 0.04) even with noisy 5-s segmented EEG signals. Application of our approach to the specific problem like detection of epilepsy from noisy and fragmented EEG data reveals a performance that is not only superior to others, but also is translationally relevant, highlighting its potential application in a clinic setting, where EEG signals are often noisy or scanty. Our proposed metric DF-A (Discriminant feature-accuracy), for the first time, identified the most discriminant feature with models that give A accuracy or above (A = 95 used in this study). This groundbreaking approach allows for detecting discriminant features and can be used as potential electrographic biomarkers in epilepsy detection research. Moreover, our study introduces innovative insights into the understanding of these features, epilepsy detection, and cross-validation, markedly improving epilepsy detection in ways previously unavailable.
... Neuropsychological studies have identified several cognitive dysfunctions associated with TLE (4). Firstly, memory both short-and long-term memory can be affected; specifically, working memory dysfunction impairs visuospatial and verbal abilities (5). ...
Background: Temporal lobe epilepsy (TLE) is the most common form of partial epilepsy and increases the risk of cognitive impairment, negatively impacting the quality of life of affected individuals. Objectives: This study aimed to investigate cognitive function in patients with low socioeconomic status affected by TLE and identify factors influencing such function. Methods: This case-control study, conducted between July 2021 and August 2022, compared the cognitive function of 40 patients affected by TLE to 92 healthy controls. The Montreal cognitive assessment (MoCA) was used for neurocognitive evaluation. Data analysis was performed using SPSS 25.0 for Windows. Results: The mean age of the patient group was 33.35 years, compared to 35.37 years in the control group. Moreover, 70% of patients affected by TLE displayed cognitive impairment and demonstrated lower performance in cognitive functions than the control group (P < 0.05). Significant correlations were identified between overall MoCA scores and several factors, including seizure frequency, educational level, polytherapy, disease duration, and self-esteem scores (P < 0.05). Multivariate analysis revealed that seizure control and higher educational level were statistically significant predictors of overall MoCA scores in patients affected by TLE. Conclusions: In low-income patients affected by TLE, seizure control and a higher educational level emerged as predictors of cognitive performance. These findings underscore the importance of identifying and managing comorbidities and the need for tailored cognitive rehabilitation programs for this population.
... Crucially, WMem does not appear to involve temporal lobe structures, but rather maintenance of information in WMem is carried out within a fronto-parietal network [25]. WMem appears to be further impaired in patients with left TLE with hippocampal sclerosis, early onset of the disorder, and high frequency of seizures [27]. Functional Magnetic Resonance Imaging (fMRI) has shown bilateral activation of the frontal and parietal lobes using paradigms to evaluate WMem (e.g., N-back) [28], and such activity is impaired in TLE patients [18,29]. ...
Temporal lobe epilepsy (TLE) is a common form of medically intractable epilepsy. Although seizures originate in mesial temporal structures, there are widespread abnormalities of gray and white matter beyond the temporal lobes that negatively impact functional networks and cognition. Previous studies have focused either on the global impact on functional networks, or on the functional correlates of specific cognitive abilities. Here, we use a two-pronged approach to evaluate the link between whole-brain functional connectivity (FC) anomalies to overall cognitive performance, and how such abnormal connectivity alters the fronto-parietal brain regions involved in working memory (WMem), a cognitive disability often reported by TLE patients. We evaluated 31 TLE patients and 35 healthy subjects through extensive cognitive testing, resting-state functional magnetic resonance imaging (RS-fMRI), and task-based fMRI using Sternberg’s task to evaluate WMem. As a group, TLE patients displayed cognitive abnormalities across different domains, although considerable within-group variability was identified. TLE patients showed disruptions of functional networks between and within the default mode network (DMN) and task-positive networks (TPN) resulting in associations with cognitive performance. Furthermore, during the WMem task, TLE patients showed abnormal activity of fronto-parietal regions that were associated with other forms of memory, and alterations of seed-based connectivity analyses. Our results show that different degrees of abnormal functional brain activity and connectivity are related to the severity of disabilities across cognitive spheres. Differential co-activation patterns between patients and healthy subjects suggest potential compensatory mechanisms to preserve adequate cognitive performance.
... Advances in our understanding of disease effects on cognition have indicated that the severity of cognitive impairment in TLE exists on a continuous spectrum. (Hermann et al., 2021;Tai et al., 2018;Zhao et al., 2014) In addition, there is now evidence that despite TLE pathology, a significant subgroup of patients are able to maintain normative cognitive functioning. (Coras et al., 2014;Tai et al., 2018) This adaptive brain response is usually attributed to cognitive reorganization, involving a change in the brain representation of cognitive functions. ...
Despite their temporal lobe pathology, a significant subgroup of temporal lobe epilepsy (TLE) patients are able to maintain normative cognitive functioning. Here, we identify TLE patients with intact versus impaired cognitive profiles, and interrogate for the presence of both normative and highly individual intrinsic connectivity networks(ICN) – all towards understanding the transition from impaired to intact neurocognitive status. We retrospectively investigated data from 88 TLE patients and matched 91 healthy controls with resting-state functional MRI. Functional MRI data were decomposed using independent component analysis to obtain individualized ICNs. Here, we calculated the degree of match between individualized ICNs and canonical ICNs (e.g., Yeo et.al 17 resting-state network) and divided each participant’s ICNs into normative or non-normative status based on the degree of match. We found that the individualized networks matched the canonical networks less well in the cognitively impaired compared to the cognitively intact TLE patients. The cognitively impaired patients showed significant abnormalities in the profiles of both normative and non-normative networks, whereas the intact patients showed abnormalities only in non-normative networks. At the same time, we found normative networks held a strong, positive association with the neuropsychological measures, with this association negative in non-normative networks. We were able to provide the initial data demonstrating that significant cognitive deficits are associated with the status of highly-individual ICNs, making clear that the transition from intact to impaired cognitive status is not simply the result of disruption to normative brain networks.
... Neuropsychological evaluation in TLE has consistently revealed memory impairments in this population, a finding consistent with hippocampal atrophy identified in magnetic resonance imaging [11]. However, the profile of cognitive deficits found in TLE goes beyond memory abilities and what would be expected from a focal epileptogenic lesion [12][13][14], similar to what occurs in frontal lobe epilepsy [15]. Lower IQ in TLE has been reported, modulated by the age of onset of the disease, the duration of epilepsy, the frequency of seizures, and the presence of epileptic status episodes [16]. ...
... There are also differences in reasoning measured as "g factor" between TLE and healthy controls. These findings are consistent with previous studies [13,14,17]. Our results are similar to those found by Novak and collaborators in their review. ...
... To increase the sensitivity to characteristics of the languagerelated network, we used a sentence completion task engaging core language processing. Given that TLE affects language functions [50], we analyzed the relation between the graph-based metrics and language performance in people with TLE. ...
Objective:
Temporal lobe epilepsy (TLE) is a network disorder that alters the total organization of the language-related network. Task-based functional magnetic resonance imaging (fMRI) aimed at functional connectivity is a direct method to investigate how the network is reorganized. However, such studies are scarce and represented mostly by the resting-state analysis of the individual connections between regions. To fill this gap, we used a graph-based analysis, which allows us to cover the total language-related network changes, such as disruptions in an integration/segregation balance, during a language task in TLE.
Methods:
We collected task-based fMRI data with sentence completion from 19 healthy controls and 28 people with left TLE. Using graph-based analysis, we estimated how the language-related network segregated into modules and tested whether they differed between groups. We evaluated the total network integration and the integration within modules. To assess intermodular integration, we considered the number and location of connector hubs-regions with high connectivity.
Results:
The language-related network was differently segregated during language processing in the groups. While healthy controls showed a module consisting of left perisylvian regions, people with TLE exhibited a bilateral module formed by the anterior language-related areas and a module in the left temporal lobe, reflecting hyperconnectivity within the epileptic focus. As a consequence of this reorganization, there was a statistical tendency that the dominance of the intramodular integration over the total network integration was greater in TLE, which predicted language performance. The increase in the number of connector hubs in the right hemisphere, in turn, was compensatory in TLE.
Significance:
Our study provides insights into the reorganization of the language-related network in TLE, revealing specific network changes in segregation and integration. It confirms reduced global connectivity and compensation across the healthy hemisphere, commonly observed in epilepsy. These findings advance the understanding of the network-based reorganizational processes underlying language processing in TLE.
... 6 Other aspects of cognitive functioning have also been reported to be affected, including attention, executive function, judgment, insight, and problem solving. [7][8][9] These widespread cognitive consequences may cause a significant decline in the quality of life for TLE patients and are sometimes more debilitating than the seizures themselves. 10 Although different studies have provided important information on vulnerability factors for cognitive deficits in TLE patients, 11,12 the neurobiological mechanisms underlying cognitive impairment remain unclear. ...
Objective
Cognitive deficit is common in patients with temporal lobe epilepsy (TLE). Here, we aimed to investigate the modular architecture of functional networks associated with distinct cognitive states in TLE patients together with the role of the thalamus in modular networks.
Methods
Resting‐state functional magnetic resonance imaging scans were acquired from 53 TLE patients and 37 matched healthy controls. All patients received the Montreal Cognitive Assessment test and accordingly were divided into TLE patients with normal cognition (TLE‐CN, n = 35) and TLE patients with cognitive impairment (TLE‐CI, n = 18) groups. The modular properties of functional networks were calculated and compared including global modularity Q, modular segregation index, intramodular connections, and intermodular connections. Thalamic subdivisions corresponding to the modular networks were generated by applying a ‘winner‐take‐all’ strategy before analyzing the modular properties (participation coefficient and within‐module degree z‐score) of each thalamic subdivision to assess the contribution of the thalamus to modular functional networks. Relationships between network properties and cognitive performance were then further explored.
Results
Both TLE‐CN and TLE‐CI patients showed lower global modularity, as well as lower modular segregation index values for the ventral attention network and the default mode network. However, different patterns of intramodular and intermodular connections existed for different cognitive states. In addition, both TLE‐CN and TLE‐CI patients exhibited anomalous modular properties of functional thalamic subdivisions, with TLE‐CI patients presenting a broader range of abnormalities. Cognitive performance in TLE‐CI patients was not related to the modular properties of functional network but rather to the modular properties of functional thalamic subdivisions.
Conclusions
The thalamus plays a prominent role in modular networks and potentially represents a key neural mechanism underlying cognitive impairment in TLE.
... periments have discovered some correlations between brain areas and cognitive performance in TLE (Allone et al., 2017). Lateralization of epilepsy has been a frequently-reported finding (Bostock et al., 2017); for example, left TLE patients had more problems with verbal span in working memory and executive function tests, whereas right TLE ones showed visuospatial deficits and lower scores in auditory naming tasks and assessment of theory of mind (Rastogi et al., 2014). A few studies have found that patients with mesial temporal sclerosis (MTS), as the most common MRI lesion in refractory TLE, had more errors and lower scores in tests of executive functions than other TLE patients (Rastogi et al., 2014). ...
... Lateralization of epilepsy has been a frequently-reported finding (Bostock et al., 2017); for example, left TLE patients had more problems with verbal span in working memory and executive function tests, whereas right TLE ones showed visuospatial deficits and lower scores in auditory naming tasks and assessment of theory of mind (Rastogi et al., 2014). A few studies have found that patients with mesial temporal sclerosis (MTS), as the most common MRI lesion in refractory TLE, had more errors and lower scores in tests of executive functions than other TLE patients (Rastogi et al., 2014). However, no study has compared other structural MRI lesions in TLE with each other and for other cognitive domains. ...
... Supporting our results about the atrophy group, decreased volume of grey and white matter, as a quantitative marker for atrophy, has shown significant association with immediate and delayed memory impairment, lower IQ, and weaker executive functions in previous studies (Oyegbile et al., 2006). MTS was suggested as a related factor to the severity of working memory impairment based on a functional connectivity model and MRI volumetric analysis, but our data showed significantly worse working memory in a non-MTS group than MTS group (Rastogi et al., 2014). Moreover, evaluating patients' executive functions using the modified Wisconsin card sorting test (MWCST) and VFT has shown that the MTS group had lower scores and more errors in MW-CST than the non-MTS group and vice versa for VFT (Corcoran & Upton, 1993;Giovagnoli, 2001). ...
Introduction: Temporal lobe epilepsy (TLE) is the most prevalent form of drug-resistant
epilepsy with concurrent cognitive impairment. Prevention, earlier diagnosis, and personalized
management of cognitive deficits in TLE require more understanding of underlying structural
and functional brain Ialterations. No study has evaluated the performance of TLE patients in
different cognitive domains based on their structural brain lesions.
Methods: In this study, 69 refractory TLE patients underwent magnetic resonance imaging
(MRI) epilepsy protocol and several neuropsychological tests, consisting of the Wechsler adult
intelligence scale-revised, Rey-Osterrieth complex figure test, verbal fluency test, digit span
test, spatial span test, Wechsler memory scale-III, design fluency test, Rey visual design learning
test, auditory-verbal learning test, and trail making test. MRI findings were classified into the
following groups: Focal cortical dysplasia, gliosis, atrophy, mesial temporal sclerosis (MTS),
tumor, vascular malformation, and other lesions or normal. Results of neuropsychological
tests were compared between MRI groups using a generalized linear model with gamma
distribution and log link.
Results: Patients with MTS showed better performance in general intellectual functioning,
working memory, attentional span, and auditory-verbal learning compared to patients with
non-MTS MRI lesions. Atrophy and focal cortical dysplasia had the largest differences
from MTS.
Conclusion: Cognitive performance of refractory TLE patients varies concerning structural
brain alterations. Further neuroimaging studies of TLE lead to prevention and more accurate
management of cognitive decline in clinical settings.
