Comparison of minimally invasive to standard temporal lobectomy approaches to epilepsy surgery: Seizure relief and visual confrontation naming outcomes.

The purpose of this study was to systematically examine three different surgical approaches in treating left medial temporal lobe epilepsy (mTLE) (viz., subtemporal selective amygdalohippocampectomy [subSAH], stereotactic laser amygdalohippocampotomy [SLAH], and anterior temporal lobectomy [ATL]), to determine which procedures are most favorable in terms of visual confrontation naming and seizure relief outcome. This was a retrospective study of 33 adults with intractable mTLE who underwent left temporal lobe surgery at three different epilepsy surgery centers who also underwent pre-, and at least 6-month post-surgical neuropsychological testing. Measures included the Boston Naming Test (BNT) and the Engel Epilepsy Surgery Outcome Scale. Fisher's exact tests revealed a statistically significant decline in naming in ATLs compared to SLAHs, but no other significant group differences. 82% of ATL and 36% of subSAH patients showed a significant naming decline whereas no SLAH patient (0%) had a significant naming decline. Significant postoperative naming improvement was seen in 36% of SLAH patients in contrast to 9% improvement in subSAH patients and 0% improvement in ATLs. Finally, there were no statistically significant differences between surgical approaches with regard to seizure freedom outcome, although there was a trend towards better seizure relief outcome among the ATL patients. Results support a possible benefit of SLAH in preserving visual confrontation naming after left TLE surgery. While result interpretation is limited by the small sample size, findings suggest outcome is likely to differ by surgical approach, and that further research on cognitive and seizure freedom outcomes is needed to inform patients and providers of potential risks and benefits with each.

Selective Posterior Cerebral Artery Wada Better Predicts Good Memory and Naming Outcomes Following Selective Stereotactic Thermal Ablation for Medial Temporal Lobe Epilepsy Than Internal Carotid Artery Wada.

The conventional intracarotid amobarbital (Wada) test has been used to assess memory function in patients being considered for temporal lobe epilepsy (TLE) surgery. Minimally invasive approaches that target the medial temporal lobe (MTL) and spare neocortex are increasingly used, but a knowledge gap remains in how to assess memory and language risk from these procedures. We retrospectively compared results of two versions of the Wada test, the intracarotid artery (ICA-Wada) and posterior cerebral artery (PCA-Wada) approaches, with respect to predicting subsequent memory and language outcomes, particularly after stereotactic laser amygdalohippocampotomy (SLAH). We included all patients being considered for SLAH who underwent both ICA-Wada and PCA-Wada at a single institution. Memory and confrontation naming assessments were conducted using standardized neuropsychological tests to assess pre- to post-surgical changes in cognitive performance. Of 13 patients who initially failed the ICA-Wada, only one patient subsequently failed the PCA-Wada (p=0.003, two-sided binomial test with p 0 =0.5) demonstrating that these tests assess different brain regions or networks. PCA-Wada had a high negative predictive value for the safety of SLAH, compared to ICA-Wada, as none of the patients who underwent SLAH after passing the PCA-Wada experienced catastrophic memory decline (0 of 9 subjects, p <.004, two-sided binomial test with p 0 =0.5), and all experienced a good cognitive outcome. In contrast, the single patient who received a left anterior temporal lobectomy after failed ICA- and passed PCA-Wada experienced a persistent, near catastrophic memory decline. On confrontation naming, few patients exhibited disturbance during the PCA-Wada. Following surgery, SLAH patients showed no naming decline, while open resection patients, whose surgeries all included ipsilateral temporal lobe neocortex, experienced significant naming difficulties (Fisher's exact test, p <.05). These findings demonstrate that (1) failing the ICA-Wada falsely predicts memory decline following SLAH, (2) PCA-Wada better predicts good memory outcomes of SLAH for MTLE, and (3) the MTL brain structures affected by both PCA-Wada and SLAH are not directly involved in language processing.

Computerized adaptive test strategies for the matrix reasoning subtest of the Wechsler Adult Intelligence Scale, 4th Edition (WAIS-IV).

OBJECTIVE: Most neuropsychological tests were developed without the benefit of modern psychometric theory. We used item response theory (IRT) methods to determine whether a widely used test - the 26-item Matrix Reasoning subtest of the WAIS-IV - might be used more efficiently if it were administered using computerized adaptive testing (CAT). METHOD: Data on the Matrix Reasoning subtest from 2197 participants enrolled in the National Neuropsychology Network (NNN) were analyzed using a two-parameter logistic (2PL) IRT model. Simulated CAT results were generated to examine optimal short forms using fixed-length CATs of 3, 6, and 12 items and scores were compared to the original full subtest score. CAT models further explored how many items were needed to achieve a selected precision of measurement (standard error ≤ .40). RESULTS: The fixed-length CATs of 3, 6, and 12 items correlated well with full-length test results (with r = .90, .97 and .99, respectively). To achieve a standard error of .40 (approximate reliability = .84) only 3-7 items had to be administered for a large percentage of individuals. CONCLUSIONS: This proof-of-concept investigation suggests that the widely used Matrix Reasoning subtest of the WAIS-IV might be shortened by more than 70% in most examinees while maintaining acceptable measurement precision. If similar savings could be realized in other tests, the accessibility of neuropsychological assessment might be markedly enhanced, and more efficient time use could lead to broader subdomain assessment.

Association Between Hippocampal Volume and African Neuropsychology Memory Tests in Adult Individuals with Probable Alzheimer's Disease in Democratic Republic of Congo.

BACKGROUND: Western studies indicate potential associations between hippocampal volume and memory in the trajectory of Alzheimer's disease (AD). However, limited availability of neuroimaging technology and neuropsychological tests appropriate for sub-Saharan African (SSA) countries makes it difficult to establish neuroanatomical associations of hippocampus and memory in this locale. OBJECTIVE: This study examined hippocampal volumes and memory in healthy control (HC) and probable AD groups in the Democratic Republic of Congo (DRC). METHODS: Forty-six subjects with probable AD and 29 HC subjects were screened using the Community Instrument for Dementia and the Alzheimer Questionnaire. Participants underwent neuroimaging in Kinshasa, DRC, and memory was evaluated using the African Neuropsychology Battery (ANB). Multiple linear regression was used to determine associations between hippocampal volumes and memory. RESULTS: Patients with probable AD performed significantly worse than HCs on ANB memory measures, and exhibited greater cerebral atrophy, which was significantly pronounced in the medial temporal lobe region (hippocampus, entorhinal cortex). Both AD and HC subjects exhibited high rates of white matter hyperintensities compared to international base rate prevalence, which was significantly worse for probable AD. Both also exhibited elevated rates of microhemorrhages. Regression analysis demonstrated a significant association between hippocampal volume and ANB memory tests. Hippocampal atrophy discriminated probable AD from the HC group. CONCLUSIONS: This study establishes the feasibility of conducting neuroimaging research in the SSA, demonstrates many known neuroimaging findings in probable AD patients hold up using culturally appropriate memory tasks, and suggest cardiovascular problems are a greater issue in SSA than in Western countries.

A virtual reality paradigm with dynamic scene stimuli for use in memory research.

Episodic memory may essentially be memory for one's place within a temporally unfolding scene from a first-person perspective. Given this, pervasively used static stimuli may only capture one small part of episodic memory. A promising approach for advancing the study of episodic memory is immersing participants within varying scenes from a first-person perspective. We present a pool of distinct scene stimuli for use in virtual environments and a paradigm that is implementable across varying levels of immersion on multiple virtual reality (VR) platforms and adaptable to studying various aspects of scene and episodic memory. In our task, participants are placed within a series of virtual environments from a first-person perspective and guided through a virtual tour of scenes during a study phase and a test phase. In the test phase, some scenes share a spatial layout with studied scenes; others are completely novel. In three experiments with varying degrees of immersion, we measure scene recall, scene familiarity-detection during recall failure, the subjective experience of déjà vu, the ability to predict the next turn on a tour, the subjective sense of being able to predict the next turn on a tour, and the factors that influence memory search and the inclination to generate candidate recollective information. The level of first-person immersion mattered to multiple facets of episodic memory. The paradigm presents a useful means of advancing mechanistic understanding of how memory operates in realistic dynamic scene environments, including in combination with cognitive neuroscience methods such as functional magnetic resonance imaging and electrophysiology.

Psychiatric changes after stereotactic laser amygdalohippocampotomy for medial temporal lobe epilepsy.

PURPOSE: Stereotactic laser amygdalohippocampotomy (SLAH) is a minimally invasive surgical treatment for drug-resistant temporal lobe epilepsy (TLE) that has comparable rates of seizure freedom to traditional open resective TLE surgery. The objective of this study was to determine psychiatric outcome (i.e., depression and anxiety changes, psychosis) after SLAH, to explore possible contributory factors to these changes, and to determine the prevalence of de novo psychopathology. METHODS: We explored mood and anxiety in 37 adult patients with TLE undergoing SLAH using the Beck psychiatric symptoms scales (i.e., Beck Depression Inventory-II [BDI-II] and Beck Anxiety Inventory [BAI]) preoperatively and 6 months following surgery. Multivariable regression analysis was conducted to identify predictors of worse depression or anxiety symptoms following SLAH. The prevalence of de novo psychopathology following SLAH was also determined. RESULTS: We found a significant decrease in BDI-II (mean decline from 16.3 to 10.9, p = 0.004) and BAI (mean decline from 13.3 to 9.0, p = 0.045) scores following SLAH at the group level. While the rate of resolution of depression (from 62% to 49%) did not achieve statistical significance (p = 0.13, McNemar's), the rate of resolution of anxiety (from 57% to 35%) was statistically significant (p = 0.03, McNemar's). The de novo rate of psychopathology (i.e., new onset depression or anxiety) following SLAH was 1 of 7 (14%). Using a metric of meaningful change rather than complete symptom resolution, 16 of 37 (43%) patients experienced improvement in depression and 6 of 37 (16%) experienced worsening. For anxiety, 14 of 37 (38%) experienced meaningful improvement and 8 of 37 (22%) experienced worsening. Baseline performance on the Beck Scales was the only factor contributing to outcome status. DISCUSSION: In one of the first studies to evaluate psychiatric outcomes after SLAH, we found promising overall trends toward stability or significant improvement in symptom burden at the group level for both depression and anxiety. There was also a significant improvement in clinical anxiety, though the decrease in clinical depression was not significant, likely owing to the limitations of sample size. SLAH may improve overall psychiatric symptoms, similarly to traditional resective TLE surgery, but de novo psychopathology and postoperative psychiatric morbidity remain significant issues, and larger samples are necessary to determine causal contributory factors.

Withdrawal of antiseizure medications after MRI-Guided laser interstitial thermal therapy in extra-temporal lobe epilepsy.

PURPOSE: This study investigated the success rate of antiseizure medications (ASMs) withdrawal following MRI Guided Laser Interstitial Thermal Therapy (MRg-LITT) for extra-temporal lobe epilepsy (ETLE), and identified predictors of seizure recurrence. METHODS: We retrospectively assessed 27 patients who underwent MRg-LITT for ETLE. Patients' demographics, disease characteristics, and post-surgical outcomes were evaluated for their potential to predict seizure recurrence associated with ASMs withdrawal. RESULTS: The median period of observation post MRg-LITT was 3 years (range 18 - 96 months) and the median period to initial ASMs reduction was 0.5 years (range 1-36 months). ASMs reduction was attempted in 17 patients (63%), 5 (29%) of whom had seizure recurrence after initial reduction. Nearly all patient who relapsed regained seizure control after reinstitution of their ASMs regimen. Pre-operative seizure frequency (p = 0.002) and occurrence of acute post-operative seizures (p = 0.01) were associated with increased risk for seizure recurrence post ASMs reduction. At the end of the observation period, 11% of patients were seizure free without drugs, 52% were seizure free with drugs and 37% still experienced seizures despite ASMs. Compared with pre-operative status, the number of ASMs was reduced in 41% of patients, unchanged in 55% of them and increased in only 4% of them. CONCLUSIONS: Successful MRg-LITT for ETLE allows for ASMs reduction in a significant portion of patients and complete ASMs withdrawal in a subset of them. Patients with higher pre-operative seizure frequency or occurrence of acute post operative seizures exhibit higher chances relapse post ASMs reduction.

An ERP measure of non-conscious memory reveals dissociable implicit processes in human recognition using an open-source automated analytic pipeline.

Non-conscious processing of human memory has traditionally been difficult to objectively measure and thus understand. A prior study on a group of hippocampal amnesia (N = 3) patients and healthy controls (N = 6) used a novel procedure for capturing neural correlates of implicit memory using event-related potentials (ERPs): old and new items were equated for varying levels of memory awareness, with ERP differences observed from 400 to 800 ms in bilateral parietal regions that were hippocampal-dependent. The current investigation sought to address the limitations of that study by increasing the sample of healthy subjects (N = 54), applying new controls for construct validity, and developing an improved, open-source tool for automated analysis of the procedure used for equating levels of memory awareness. Results faithfully reproduced prior ERP findings of parietal effects that a series of systematic control analyses validated were not contributed to nor contaminated by explicit memory. Implicit memory effects extended from 600 to 1000 ms, localized to right parietal sites. These ERP effects were found to be behaviorally relevant and specific in predicting implicit memory response times, and were topographically dissociable from other traditional ERP measures of implicit memory (miss vs. correct rejections) that instead occurred in left parietal regions. Results suggest first that equating for reported awareness of memory strength is a valid, powerful new method for revealing neural correlates of non-conscious human memory, and second, behavioral correlations suggest that these implicit effects reflect a pure form of priming, whereas misses represent fluency leading to the subjective experience of familiarity.

Stereoelectroencephalography-guided radiofrequency ablation of the epileptogenic zone as a treatment and predictor of future success of further surgical intervention.

OBJECTIVE: Stereoelectroencephalography (SEEG)-guided radiofrequency ablation (RFA) is increasingly being used as a treatment for drug-resistant localization-related epilepsy. The aim of this study is to analyze the successes and failures using RFA and how response correlates with surgical epilepsy treatment outcomes. METHODS: We retrospectively reviewed 62 patients who underwent RFA via SEEG electrodes. After excluding five, the remaining 57 were classified into subgroups based on procedures and outcomes. Forty patients (70%) underwent a secondary surgical procedure, of whom 32 were delayed: 26 laser interstitial thermal therapy (LITT), five resection, one neuromodulation. We determined the predictive value of RFA outcome upon subsequent surgical outcome by categorizing the delayed secondary surgery outcome as success (Engel I/II) versus failure (Engel III/IV). Demographic information, epilepsy characteristics, and the transient time of seizure freedom after RFA were calculated for each patient. RESULTS: Twelve of 49 patients (24.5%) who had RFA alone and delayed follow-up achieved Engel class I. Of the 32 patients who underwent a delayed secondary surgical procedure, 15 achieved Engel class I and nine Engel class II (24 successes), and eight were considered failures (Engel class III/IV). The transient time of seizure freedom after RFA was significantly longer in the success group (4 months, SD = 2.6) as compared to the failure group (.75 months, SD = 1.16; p < .001). Additionally, there was a higher portion of preoperative lesional findings in patients in the RFA alone and delayed surgical success group (p = .03) and a longer time to seizure recurrence in the presence of lesions (p < .05). Side effects occurred in 1% of patients. SIGNIFICANCE: In this series, RFA provided a treatment during SEEG-guided intracranial monitoring that led to seizure freedom in ~25% of patients. Of the 70% who underwent delayed surgery, longer transient time of seizure freedom after RFA was predictive of the results of the secondary surgeries, 74% of which were LITT.

Depression and anxiety in caregivers of patients with functional seizures.

OBJECTIVE: Contrary to patients, the psychological impact of functional seizures to caregivers has not been adequately investigated. This study aimed to evaluate the rates and determinants of depression and anxiety in caregivers of patients with functional seizures. METHODS: Patients with functional seizures and their caregivers completed surveys about demographic, disease-related, and psychosocial characteristics. Rates and determinants of depression and anxiety were evaluated using the Beck Depression and Anxiety Inventory scores as dependent variables and patient and caregiver characteristics as independent variables. RESULTS: Twenty-nine patients (76% female, mean age of 37 years) and their caregivers (59% female, mean age of 43 years) were recruited. Symptoms of anxiety and/or depression were present in 96% of patients (96% depression, 92% anxiety) and 59% of caregivers (52% depression, 50% anxiety). Specifically, 31% of caregivers manifested mild depression, 14% moderate depression, and 7% severe depression, whereas 48% were not depressed. Similarly, 14% of caregivers manifested mild anxiety, 29% moderate anxiety, and 7% severe anxiety, whereas 50% were not anxious. Patient and caregiver depression levels strongly correlated (r = .73, p < .0001). The presence of anxiety and depression in the caregiver was associated with male patient gender (p = .02), patient depression level (p = .002), the caregiver being a parent or sibling (p = .02), and caregiver burden (p = .0009). SIGNIFICANCE: Caregivers of patients with functional seizures experience high rates of anxiety and depression, explained by specific demographic and psychosocial factors that could act as intervention targets.

Convolutional Neural Network Algorithm to Determine Lateralization of Seizure Onset in Patients With Epilepsy: A Proof-of-Principle Study.

BACKGROUND AND OBJECTIVES: A new frontier in diagnostic radiology is the inclusion of machine-assisted support tools that facilitate the identification of subtle lesions often not visible to the human eye. Structural neuroimaging plays an essential role in the identification of lesions in patients with epilepsy, which often coincide with the seizure focus. In this study, we explored the potential for a convolutional neural network (CNN) to determine lateralization of seizure onset in patients with epilepsy using T1-weighted structural MRI scans as input. METHODS: Using a dataset of 359 patients with temporal lobe epilepsy (TLE) from 7 surgical centers, we tested whether a CNN based on T1-weighted images could classify seizure laterality concordant with clinical team consensus. This CNN was compared with a randomized model (comparison with chance) and a hippocampal volume logistic regression (comparison with current clinically available measures). Furthermore, we leveraged a CNN feature visualization technique to identify regions used to classify patients. RESULTS: Across 100 runs, the CNN model was concordant with clinician lateralization on average 78% (SD = 5.1%) of runs with the best-performing model achieving 89% concordance. The CNN outperformed the randomized model (average concordance of 51.7%) on 100% of runs with an average improvement of 26.2% and outperformed the hippocampal volume model (average concordance of 71.7%) on 85% of runs with an average improvement of 6.25%. Feature visualization maps revealed that in addition to the medial temporal lobe, regions in the lateral temporal lobe, cingulate, and precentral gyrus aided in classification. DISCUSSION: These extratemporal lobe features underscore the importance of whole-brain models to highlight areas worthy of clinician scrutiny during temporal lobe epilepsy lateralization. This proof-of-concept study illustrates that a CNN applied to structural MRI data can visually aid clinician-led localization of epileptogenic zone and identify extrahippocampal regions that may require additional radiologic attention. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with drug-resistant unilateral temporal lobe epilepsy, a convolutional neural network algorithm derived from T1-weighted MRI can correctly classify seizure laterality.

Intracranial investigation of piriform cortex epilepsy during odor presentation.

The piriform cortex (PC) is part of the olfactory system, principally receiving input from the lateral olfactory tract and projecting to downstream components of the olfactory network, including the amygdala. Based on preclinical studies, PC is vulnerable to injury and can be easily kindled as an onset site for seizures. While the role of PC in human epilepsy has been studied indirectly and the subject of speculation, cases of demonstrated PC seizure onset from direct intracranial recording are rare. We present a pediatric patient with drug-resistant focal reflex epilepsy and right mesial temporal sclerosis with habitual seizures triggered by coconut aroma. The patient underwent stereoelectroencephalography with implantation of olfactory cortices including PC, through which we identified PC seizure onset, mapped high-frequency activity associated with presentation of olfactory stimuli and performance on cognitive tasks, and reproduced habitual seizures via cortical stimulation of PC. Coconut odor did not trigger seizures in our work with the patient. Surgical workup resulted in resection of the patient's right amygdala, PC, and mesial temporal pole, following which she has been seizure free for 20 months without functional decline in cognition or smell. Histological findings from resected tissue showed astrogliosis and subpial gliosis.

The effect of responsive neurostimulation (RNS) on neuropsychiatric and psychosocial outcomes in drug-resistant epilepsy.

OBJECTIVE: The impact of responsive neurostimulation (RNS) on neuropsychiatric and psychosocial outcomes has not been extensively evaluated outside of the original clinical trials and post-approval studies. The goal of this study was to ascertain the potential real-world effects of RNS on cognitive, psychiatric, and quality of life (QOL) outcomes in relation to seizure outcomes by examining 50 patients undergoing RNS implantation for drug-resistant epilepsy (DRE). METHODS: We performed a retrospective review of all patients treated at our institution with RNS for DRE with at least 12 months of follow-up. In addition to baseline demographic and disease-related characteristics, we collected cognitive (Full-Scale Intelligence Quotient, Verbal Comprehension, and Perceptual Reasoning Index), psychiatric (Beck Depression and Anxiety Inventory Scores), and QOL (QOLIE-31) outcomes at 6 and 12 months after RNS implantation and correlated them with seizure outcomes. RESULTS: Fifty patients (median age 39.5 years, 64% female) were treated with RNS for DRE in our institution from 2005 to 2020. Of the 37 of them who had well-documented pre and post-implantation seizure diaries, the 6-month median seizure frequency reduction was 88%, the response rate (50% or greater seizure frequency reduction) was 78%, and 32% of patients were free of disabling seizures in this timeframe. There was no statistically significant difference at a group level in any of the evaluated cognitive, psychiatric, and QOL outcomes at 6 and 12 months post-implantation compared to the pre-implantation baseline, irrespective of seizure outcomes, although a subset of patients experienced a decline in mood or cognitive variables. SIGNIFICANCE: Responsive neurostimulation does not appear to have a statistically significant negative or positive impact on neuropsychiatric and psychosocial status at the group level. We observed significant variability in outcome, with a minority of patients experiencing worse behavioral outcomes, which seemed related to RNS implantation. Careful outcome monitoring is required to identify the subset of patients experiencing a poor response and to make appropriate adjustments in care.

The Future of Cognitive Screening in Neurodegenerative Diseases.

Cognitive screening instruments (CSI) have variable sensitivity and specificity to the cognitive changes associated with dementia syndromes, and the most recent systematic review found insufficient evidence to support the benefit of cognitive screening tools in older adults residing within the community. Consequently, there is a critical need to improve CSI methods, which have not yet incorporated advances in psychometrics, neuroscience, and technology. The primary goal of this article is to provide a framework for transitioning from legacy CSIs to advanced dementia screening measurement. In line with ongoing efforts in neuropsychology and the call for next-generation digital assessment for early detection of AD, we propose a psychometrically advanced (including application of item response theory methods), automated selective assessment model that provides a framework to help propel an assessment revolution. Further, we present a three-phase model for modernizing CSIs and discuss critical diversity and inclusion issues, current challenges in differentiating normal from pathological aging, and ethical considerations.

MRI-based deep learning can discriminate between temporal lobe epilepsy, Alzheimer's disease, and healthy controls.

BACKGROUND: Radiological identification of temporal lobe epilepsy (TLE) is crucial for diagnosis and treatment planning. TLE neuroimaging abnormalities are pervasive at the group level, but they can be subtle and difficult to identify by visual inspection of individual scans, prompting applications of artificial intelligence (AI) assisted technologies. METHOD: We assessed the ability of a convolutional neural network (CNN) algorithm to classify TLE vs. patients with AD vs. healthy controls using T1-weighted magnetic resonance imaging (MRI) scans. We used feature visualization techniques to identify regions the CNN employed to differentiate disease types. RESULTS: We show the following classification results: healthy control accuracy = 81.54% (SD = 1.77%), precision = 0.81 (SD = 0.02), recall = 0.85 (SD = 0.03), and F1-score = 0.83 (SD = 0.02); TLE accuracy = 90.45% (SD = 1.59%), precision = 0.86 (SD = 0.03), recall = 0.86 (SD = 0.04), and F1-score = 0.85 (SD = 0.04); and AD accuracy = 88.52% (SD = 1.27%), precision = 0.64 (SD = 0.05), recall = 0.53 (SD = 0.07), and F1 score = 0.58 (0.05). The high accuracy in identification of TLE was remarkable, considering that only 47% of the cohort had deemed to be lesional based on MRI alone. Model predictions were also considerably better than random permutation classifications (p < 0.01) and were independent of age effects. CONCLUSIONS: AI (CNN deep learning) can classify and distinguish TLE, underscoring its potential utility for future computer-aided radiological assessments of epilepsy, especially for patients who do not exhibit easily identifiable TLE associated MRI features (e.g., hippocampal sclerosis).

In people with temporal lobe epilepsy, seizures start in a particular part of the brain positioned behind the ears called the temporal lobe. It is difficult for a doctor to detect that a person has temporal lobe epilepsy using brain scans. In this study, we developed a computer model that was able to identify people with temporal lobe epilepsy from scans of their brain. This computer model could be used to help doctors identify temporal lobe epilepsy from brain scans in the future.

Development and application of the International Classification of Cognitive Disorders in Epilepsy (IC-CoDE): Initial results from a multi-center study of adults with temporal lobe epilepsy.

[Correction Notice: An Erratum for this article was reported online in Neuropsychology on Sep 15 2022 (see record 2023-01997-001). In the original article, there was an error in Figure 2. In the box at the top left of the figure, the fourth explanation incorrectly stated, "Generalized impairment = At least one test < -1.0 or -1.5SD in three or more domains." The correct wording is "Generalized impairment = At least two tests < -1.0 or -1.5SD in each of three or more domains." All versions of this article have been corrected.] Objective: To describe the development and application of a consensus-based, empirically driven approach to cognitive diagnostics in epilepsy research-The International Classification of Cognitive Disorders in Epilepsy (IC-CoDE) and to assess the ability of the IC-CoDE to produce definable and stable cognitive phenotypes in a large, multi-center temporal lobe epilepsy (TLE) patient sample. METHOD: Neuropsychological data were available for a diverse cohort of 2,485 patients with TLE across seven epilepsy centers. Patterns of impairment were determined based on commonly used tests within five cognitive domains (language, memory, executive functioning, attention/processing speed, and visuospatial ability) using two impairment thresholds (≤1.0 and ≤1.5 standard deviations below the normative mean). Cognitive phenotypes were derived across samples using the IC-CoDE and compared to distributions of phenotypes reported in existing studies. RESULTS: Impairment rates were highest on tests of language, followed by memory, executive functioning, attention/processing speed, and visuospatial ability. Application of the IC-CoDE using varying operational definitions of impairment (≤ 1.0 and ≤ 1.5 SD) produced cognitive phenotypes with the following distribution: cognitively intact (30%-50%), single-domain (26%-29%), bi-domain (14%-19%), and generalized (10%-22%) impairment. Application of the ≤ 1.5 cutoff produced a distribution of phenotypes that was consistent across cohorts and approximated the distribution produced using data-driven approaches in prior studies. CONCLUSIONS: The IC-CoDE is the first iteration of a classification system for harmonizing cognitive diagnostics in epilepsy research that can be applied across neuropsychological tests and TLE cohorts. This proof-of-principle study in TLE offers a promising path for enhancing research collaborations globally and accelerating scientific discoveries in epilepsy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Specificity of performance validity tests in patients with confirmed epilepsy.

Objective: While assessment of performance validity is essential to neuropsychological evaluations, use of performance validity tests (PVTs) in an epilepsy population has raised concerns due to factors that may result in performance fluctuations. The current study assessed whether specificity was maintained at previously suggested cutoffs in a confirmed epilepsy population on the Warrington Recognition Memory Test (WRMT) - Words and Test of Memory Malingering (TOMM). Method: Eighty-two confirmed epilepsy patients were administered the WRMT-Words and TOMM as part of a standardized neuropsychological evaluation. Frequency tables were utilized to investigate specificity rates on these two PVTs. Results: The suggested WRMT-Words Accuracy Score cutoff of ≤42 was associated with a specificity rate of 90.2%. Five out of the 8 individuals falling below the Accuracy Score cutoff scored 42, suggesting specificity could be further improved by slightly lowering the cutoff. The WRMT-Words Total Time cutoff of ≥207 seconds was associated with 95.1% specificity. A TOMM Trial 1 cutoff of <40 was associated with 93.9% specificity, while the established cutoff of <45 on Trial 2 and the Retention Trial yielded specificity rates of 98.6% and 100.0%, respectively. Conclusions: Our findings demonstrate acceptable performance on two PVTs in a select confirmed epilepsy population without a history of brain surgery, active seizures during testing, and/or low IQ, irrespective of various factors such as seizure type, seizure lateralization/localization, and language lateralization. The possible presence of interictal discharges were not controlled for in the current study, which may have contributed to reduced PVT performances.

Case study of invalid to valid shift in cognitive performance following successful treatment of psychogenic nonepileptic seizure events.

Patients with psychogenic nonepileptic seizure (PNES) who fail performance validity testing (PVT) may appear to produce non-valid cognitive profiles. Consequently, they may not get referred to treatment and events persist, with worsening disability and high resource utilization. As a result, we report pre- and post-treatment neuropsychological evaluation findings in a 59-year-old woman with a confirmed diagnosis of PNES established using video-EEG monitoring. At pre-treatment baseline neuropsychological evaluation, PNES events occurred weekly to daily. Performance was impaired across PVTs and across multiple cognitive domains. After behavioral intervention specific to PNES, these events substantially reduced in frequency to rare stress-induced flares. Post-treatment neuropsychological evaluation revealed marked improvement of most cognitive and behavioral scores from baseline, and valid PVT scores. We review predisposing, precipitating, and perpetuating factors for PNES and cognitive impairment in this case and discuss the patient's outcome from treatment. Effectively managing PNES events and dissociative tendencies while reducing unnecessary pharmacological interventions appears to have allowed this patient to function closer to her optimal state. This case illustrates the complexity of Functional Neurologic Disorder (FND) clinical presentation and challenges the assumption that suboptimal neuropsychological performance predicts poor treatment engagement and outcome. We showcase the reversibility of PNES and cognitive manifestations of FND using targeted psychotherapeutic interventions, which resulted in reduced disability and associated healthcare costs, as well as re-engagement in life.

Opening a conceptual space for metamemory experience.

The experiences associated with remembering, including metamemory feelings about the act of remembering and attempts at remembering, are not often integrated into general accounts of memory. For example, David Rubin (2022) proposes a unified, three-dimensional conceptual space for mapping memory states, a map that does not systematically specify metamemory feelings. Drawing on Rubin's model, we define a distinct role for metamemory in relation to first-order memory content. We propose a fourth dimension for the model and support the proposal with conceptual, neurocognitive, and clinical lines of reasoning. We use the modified model to illustrate several cases, and show how it helps to conceptualize a new category of memory state: autonoetic knowing, exemplified by déjà vu. We also caution not to assume that memory experience is directly correlated with or caused by memory content, an assumption Tulving (1989) labeled the doctrine of concordance.

Moving towards a taxonomy of cognitive impairments in epilepsy: application of latent profile analysis to 1178 patients with temporal lobe epilepsy.

In efforts to understand the cognitive heterogeneity within and across epilepsy syndromes, cognitive phenotyping has been proposed as a new taxonomy aimed at developing a harmonized approach to cognitive classification in epilepsy. Data- and clinically driven approaches have been previously used with variability in the phenotypes derived across studies. In our study, we utilize latent profile analysis to test several models of phenotypes in a large multicentre sample of patients with temporal lobe epilepsy and evaluate their demographic and clinical profiles. For the first time, we examine the added value of replacing missing data and examine factors that may be contributing to missingness. A sample of 1178 participants met the inclusion criteria for the study, which included a diagnosis of temporal lobe epilepsy and the availability of comprehensive neuropsychological data. Models with two to five classes were examined using latent profile analysis and the optimal model was selected based on fit indices, posterior probabilities and proportion of sample sizes. The models were also examined with imputed data to investigate the impact of missing data on model selection. Based on the fit indices, posterior probability and distinctiveness of the latent classes, a three-class solution was the optimal solution. This three-class solution comprised a group of patients with multidomain impairments, a group with impairments predominantly in language and a group with no impairments. Overall, the multidomain group demonstrated a worse clinical profile and comprised a greater proportion of patients with mesial temporal sclerosis, a longer disease duration and a higher number of anti-seizure medications. The four-class and five-class solutions demonstrated the lowest probabilities of a group membership. Analyses with imputed data demonstrated that the four-class solution was the optimal solution; however, there was a weak agreement between the missing and imputed data sets for the four-Class solutions (κ = 0.288, P < 0.001). This study represents the first to use latent profile analysis to test and compare multiple models of cognitive phenotypes in temporal lobe epilepsy and to determine the impact of missing data on model fit. We found that the three-phenotype model was the most meaningful based on several fit indices and produced phenotypes with unique demographic and clinical profiles. Our findings demonstrate that latent profile analysis is a rigorous method to identify phenotypes in large, heterogeneous epilepsy samples. Furthermore, this study highlights the importance of examining the impact of missing data in phenotyping methods. Our latent profile analysis-derived phenotypes can inform future studies aimed at identifying cognitive phenotypes in other neurological disorders.