Work productivity, quality of life, and care needs: An unfolding epilepsy burden revealed in the Australian Epilepsy Project pilot study.

OBJECTIVE: Epilepsy is a common and serious neurological disorder. This cross-sectional analysis addresses the burden of epilepsy at different stages of the disease. METHODS: This pilot study is embedded within the Australian Epilepsy Project (AEP), aiming to provide epilepsy support through a national network of dedicated sites. For this analysis, adults aged 18-65 years with first unprovoked seizure (FUS), newly diagnosed epilepsy (NDE), or drug-resistant epilepsy (DRE) were recruited between February-August 2022. Baseline clinicodemographic data were collected from the participants who completed questionnaires to assess their quality of life (QOLIE-31, EQ-5D-5L), work productivity (Work Productivity and Activity Impairment [WPAI]), and care needs. Univariate analysis and multivariate regression was performed. RESULTS: 172 participants formed the study cohort (median age 34, interquartile range [IQR]: 26-45), comprising FUS (n = 44), NDE (n = 53), and DRE (n = 75). Mean QOLIE-31 score was 56 (standard deviation [SD] ± 18) and median EQ-5D-5L score was 0.77 (IQR: 0.56-0.92). QOLIE-31 but not EQ-5D-5L scores were significantly lower in the DRE group compared to FUS and NDE groups (p < 0.001). Overall, 64.5% of participants participated in paid work, with fewer DRE (52.0%) compared with FUS (76.7%) and NDE (72.5%) (p < 0.001). Compared to those not in paid employment, those in paid employment had significantly higher quality of life scores (p < 0.001). Almost 5.8% of participants required formal care (median 20 h/week, IQR: 12-55) and 17.7% required informal care (median 16 h/week, IQR: 7-101). SIGNIFICANCE: Epilepsy is associated with a large burden in terms of quality of life, productivity and care needs. PLAIN LANGUAGE SUMMARY: This is a pilot study from the Australian Epilepsy Project (AEP). It reports health economic data for adults of working age who live with epilepsy. It found that people with focal drug-resistant epilepsy had lower quality of life scores and were less likely to participate in paid employment compared to people with new diagnosis epilepsy. This study provides important local data regarding the burden of epilepsy and will help researchers in the future to measure the impact of the AEP on important personal and societal health economic outcomes.

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging.

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

White matter abnormalities characterize the acute stage of sports-related mild traumatic brain injury.

Sports-related concussion, a form of mild traumatic brain injury, is characterized by transient disturbances of brain function. There is increasing evidence that functional brain changes may be driven by subtle abnormalities in white matter microstructure, and diffusion MRI has been instrumental in demonstrating these white matter abnormalities in vivo. However, the reported location and direction of the observed white matter changes in mild traumatic brain injury are variable, likely attributable to the inherent limitations of the white matter models used. This cross-sectional study applies an advanced and robust technique known as fixel-based analysis to investigate fibre tract-specific abnormalities in professional Australian Football League players with a recent mild traumatic brain injury. We used the fixel-based analysis framework to identify common abnormalities found in specific fibre tracts in participants with an acute injury (≤12 days after injury; n = 14). We then assessed whether similar changes exist in subacute injury (>12 days and <3 months after injury; n = 15). The control group was 29 neurologically healthy control participants. We assessed microstructural differences in fibre density and fibre bundle morphology and performed whole-brain fixel-based analysis to compare groups. Subsequent tract-of-interest analyses were performed within five selected white matter tracts to investigate the relationship between the observed tract-specific abnormalities and days since injury and the relationship between these tract-specific changes with cognitive abnormalities. Our whole-brain analyses revealed significant increases in fibre density and bundle cross-section in the acute mild traumatic brain injury group when compared with controls. The acute mild traumatic brain injury group showed even more extensive differences when compared with the subacute injury group than with controls. The fibre structures affected in acute concussion included the corpus callosum, left prefrontal and left parahippocampal white matter. The fibre density and cross-sectional increases were independent of time since injury in the acute injury group, and were not associated with cognitive deficits. Overall, this study demonstrates that acute mild traumatic brain injury is characterized by specific white matter abnormalities, which are compatible with tract-specific cytotoxic oedema. These potential oedematous changes were absent in our subacute mild traumatic brain injury participants, suggesting that they may normalize within 12 days after injury, although subtle abnormalities may persist in the subacute stage. Future longitudinal studies are needed to elucidate individualized recovery after brain injury.

Wearable OPM-MEG: A changing landscape for epilepsy.

Magnetoencephalography with optically pumped magnometers (OPM-MEG) is an emerging and novel, cost-effective wearable system that can simultaneously record neuronal activity with high temporal resolution ("when" neuronal activity occurs) and spatial resolution ("where" neuronal activity occurs). This paper will first outline recent methodological advances in OPM-MEG compared to conventional superconducting quantum interference device (SQUID)-MEG before discussing how OPM-MEG can become a valuable and noninvasive clinical support tool in epilepsy surgery evaluation. Although OPM-MEG and SQUID-MEG share similar data features, OPM-MEG is a wearable design that fits children and adults, and it is also robust to head motion within a magnetically shielded room. This means that OPM-MEG can potentially extend the application of MEG into the neurobiology of severe childhood epilepsies with intellectual disabilities (e.g., epileptic encephalopathies) without sedation. It is worth noting that most OPM-MEG sensors are heated, which may become an issue with large OPM sensor arrays (OPM-MEG currently has fewer sensors than SQUID-MEG). Future implementation of triaxial sensors may alleviate the need for large OPM sensor arrays. OPM-MEG designs allowing both awake and sleep recording are essential for potential long-term epilepsy monitoring.

Artifact Reduction in Simultaneous EEG-fMRI: A Systematic Review of Methods and Contemporary Usage.

Simultaneous electroencephalography-functional MRI (EEG-fMRI) is a technique that combines temporal (largely from EEG) and spatial (largely from fMRI) indicators of brain dynamics. It is useful for understanding neuronal activity during many different event types, including spontaneous epileptic discharges, the activity of sleep stages, and activity evoked by external stimuli and decision-making tasks. However, EEG recorded during fMRI is subject to imaging, pulse, environment and motion artifact, causing noise many times greater than the neuronal signals of interest. Therefore, artifact removal methods are essential to ensure that artifacts are accurately removed, and EEG of interest is retained. This paper presents a systematic review of methods for artifact reduction in simultaneous EEG-fMRI from literature published since 1998, and an additional systematic review of EEG-fMRI studies published since 2016. The aim of the first review is to distill the literature into clear guidelines for use of simultaneous EEG-fMRI artifact reduction methods, and the aim of the second review is to determine the prevalence of artifact reduction method use in contemporary studies. We find that there are many published artifact reduction techniques available, including hardware, model based, and data-driven methods, but there are few studies published that adequately compare these methods. In contrast, recent EEG-fMRI studies show overwhelming use of just one or two artifact reduction methods based on literature published 15-20 years ago, with newer methods rarely gaining use outside the group that developed them. Surprisingly, almost 15% of EEG-fMRI studies published since 2016 fail to adequately describe the methods of artifact reduction utilized. We recommend minimum standards for reporting artifact reduction techniques in simultaneous EEG-fMRI studies and suggest that more needs to be done to make new artifact reduction techniques more accessible for the researchers and clinicians using simultaneous EEG-fMRI.

Artificial intelligence for clinical decision support in neurology.

Artificial intelligence is one of the most exciting methodological shifts in our era. It holds the potential to transform healthcare as we know it, to a system where humans and machines work together to provide better treatment for our patients. It is now clear that cutting edge artificial intelligence models in conjunction with high-quality clinical data will lead to improved prognostic and diagnostic models in neurological disease, facilitating expert-level clinical decision tools across healthcare settings. Despite the clinical promise of artificial intelligence, machine and deep-learning algorithms are not a one-size-fits-all solution for all types of clinical data and questions. In this article, we provide an overview of the core concepts of artificial intelligence, particularly contemporary deep-learning methods, to give clinician and neuroscience researchers an appreciation of how artificial intelligence can be harnessed to support clinical decisions. We clarify and emphasize the data quality and the human expertise needed to build robust clinical artificial intelligence models in neurology. As artificial intelligence is a rapidly evolving field, we take the opportunity to iterate important ethical principles to guide the field of medicine is it moves into an artificial intelligence enhanced future.

Teleneuropsychology in the time of COVID-19: The experience of The Australian Epilepsy Project.

PURPOSE: Traditional neuropsychological testing carries elevated COVID-19 risk for both examinee and examiner. Here we describe how the pilot study of the Australian Epilepsy Project (AEP) has transitioned to tele-neuropsychology (teleNP), enabling continued safe operations during the pandemic. METHODS: The AEP includes adults (age 18-60) with a first unprovoked seizure, new diagnosis of epilepsy or drug resistant focal epilepsy. Shortly after launching the study, COVID-related restrictions necessitated adaptation to teleNP, including delivery of verbal tasks via videoconference; visual stimulus delivery via document camera; use of web-hosted, computerised assessment; substitution of oral versions for written tests; online delivery of questionnaires; and discontinuation of telehealth incompatible tasks. RESULTS: To date, we have completed 24 teleNP assessments: 18 remotely (participant in own home) and six on-site (participant using equipment at research facility). Five face-to-face assessments were conducted prior to the transition to teleNP. Eight of 408 tests administered via teleNP (1.9 %) have been invalidated, for a variety of reasons (technical, procedural, environmental). Data confirm typical patterns of epilepsy-related deficits (p < .05) affecting processing speed, executive function, language and memory. Questionnaire responses indicate elevated rates of patients at high risk of mood (34 %) and anxiety disorder (38 %). CONCLUSION: Research teleNP assessments reveal a typical pattern of impairments in epilepsy. A range of issues must be considered when introducing teleNP, such as technical and administrative set up, test selection and delivery, and cohort suitability. TeleNP enables large-scale neuropsychological research during periods of social distancing (and beyond), and offers an opportunity to expand the reach and breadth of neuropsychological services.

Combined Isoflurane-Remifentanil Anaesthesia Permits Resting-State fMRI in Children with Severe Epilepsy and Intellectual Disability.

Head motion is a significant barrier to functional MRI (fMRI) in patients who are unable to tolerate awake scanning, including young children or those with cognitive and behavioural impairments. General anaesthesia minimises motion and ensures patient comfort, however the optimal anaesthesia regimen for fMRI in the paediatric setting is unknown. In this study, we tested the feasibility of anaesthetised fMRI in 11 patients (mean age = 9.8 years) with Lennox-Gastaut syndrome, a severe form of childhood-onset epilepsy associated with intellectual disability. fMRI was acquired during clinically-indicated MRI sessions using a synergistic anaesthesia regimen we typically administer for epilepsy neurosurgery: combined low-dose isoflurane (≤ 0.8% end-tidal concentration) with remifentanil (≤ 0.1 mcg/kg/min). Using group-level independent component analysis, we assessed the presence of resting-state networks by spatially comparing results in the anaesthetised patients to resting-state network templates from the 'Generation R' study of 536 similarly-aged non-anaesthetised healthy children (Muetzel et al. in Hum Brain Mapp 37(12):4286-4300, 2016). Numerous resting-state networks commonly studied in non-anaesthetised healthy children were readily identifiable in the anaesthetised patients, including the default-mode, sensorimotor, and frontoparietal networks. Independent component time-courses associated with these networks showed spectral characteristics suggestive of a neuronal origin of fMRI signal fluctuations, including high dynamic range and temporal frequency power predominantly below 0.1 Hz. These results demonstrate the technical feasibility of anaesthetised fMRI in children, suggesting that combined isoflurane-remifentanil anaesthesia may be an effective strategy to extend the emerging clinical applications of resting-state fMRI (for example, neurosurgical planning) to the variety of patient groups who may otherwise be impractical to scan.

Clinical benefit of presurgical EEG-fMRI in difficult-to-localize focal epilepsy: A single-institution retrospective review.

OBJECTIVE: The aim of this report is to present our clinical experience of electroencephalography-functional magnetic resonance imaging (EEG-fMRI) in localizing the epileptogenic focus, and to evaluate the clinical impact and challenges associated with the use of EEG-fMRI in pharmacoresistant focal epilepsy. METHODS: We identified EEG-fMRI studies (n = 118) in people with focal epilepsy performed at our center from 2003 to 2018. Participants were referred from our Comprehensive Epilepsy Program in an exploratory research effort to address often difficult clinical questions, due to complex and difficult-to-localize epilepsy. We assessed the success of each study, the clinical utility of the result, and when surgery was performed, the postoperative outcome. RESULTS: Overall, 50% of EEG-fMRI studies were successful, meaning that data were of good quality and interictal epileptiform discharges were recorded. With an altered recruitment strategy since 2012 with increased inclusion of patients who were inpatients for video-EEG monitoring, we found that this patients in this selected group were more likely to have epileptic discharges detected during EEG-fMRI (96% of inpatients vs 29% of outpatients, P<.0001). To date, 48% (57 of 118) of patients have undergone epilepsy surgery. In 10 cases (17% of the 59 successful studies) the EEG-fMRI result had a "critical impact" on the surgical decision. These patients were difficult to localize because of subtle abnormalities, apparently normal MRI, or extensive structural abnormalities. All 10 had a good seizure outcome at 1 year after surgery (mean follow-up 6.5 years). SIGNIFICANCE: EEG-fMRI results can assist identification of the epileptogenic focus in otherwise difficult-to-localize cases of pharmacoresistant focal epilepsy. Surgery determined largely by localization from the EEG-fMRI result can lead to good seizure outcomes. A limitation of this study is its retrospective design with nonconsecutive recruitment. Prospective clinical trials with well-defined inclusion criteria are needed to determine the overall benefit of EEG-fMRI for preoperative localization and postoperative outcome in focal epilepsy.

The epileptic network of Lennox-Gastaut syndrome: Cortically driven and reproducible across age.

OBJECTIVE: To identify brain regions underlying interictal generalized paroxysmal fast activity (GPFA), and their causal interactions, in children and adults with Lennox-Gastaut syndrome (LGS). METHODS: Concurrent scalp EEG-fMRI was performed in 2 separately analyzed patient groups with LGS: 10 children (mean age 8.9 years) scanned under isoflurane-remifentanil anesthesia and 15 older patients (mean age 31.7 years) scanned without anesthesia. Whole-brain event-related analysis determined GPFA-related activation in each group. Results were used as priors in a dynamic causal modeling (DCM) analysis comparing evidence for different neuronal hypotheses describing initiation and propagation of GPFA between cortex, thalamus, and brainstem. RESULTS: A total of 1,045 GPFA events were analyzed (cumulative duration 1,433 seconds). In both pediatric and older groups, activation occurred in distributed association cortical areas, as well as the thalamus and brainstem (p < 0.05, corrected for family-wise error). Activation was similar across individual patients with structural, genetic, and unknown etiologies of epilepsy, particularly in frontoparietal cortex. In both groups, DCM revealed that GPFA was most likely driven by prefrontal cortex, with propagation occurring first to the brainstem and then from brainstem to thalamus. CONCLUSIONS: We show reproducible evidence of a cortically driven process within the epileptic network of LGS. This network is present early (in children) and late (in older patients) in the course of the syndrome and across diverse etiologies of epilepsy, suggesting that LGS reflects shared "secondary network" involvement. A cortical-to-subcortical hierarchy is postulated whereby GPFA rapidly propagates from prefrontal cortex to the brainstem via extrapyramidal corticoreticular pathways, whereas the thalamus is engaged secondarily.

Thalamocortical functional connectivity in Lennox-Gastaut syndrome is abnormally enhanced in executive-control and default-mode networks.

OBJECTIVE: To identify abnormal thalamocortical circuits in the severe epilepsy of Lennox-Gastaut syndrome (LGS) that may explain the shared electroclinical phenotype and provide potential treatment targets. METHODS: Twenty patients with a diagnosis of LGS (mean age = 28.5 years) and 26 healthy controls (mean age = 27.6 years) were compared using task-free functional magnetic resonance imaging (MRI). The thalamus was parcellated according to functional connectivity with 10 cortical networks derived using group-level independent component analysis. For each cortical network, we assessed between-group differences in thalamic functional connectivity strength using nonparametric permutation-based tests. Anatomical locations were identified by quantifying spatial overlap with a histologically informed thalamic MRI atlas. RESULTS: In both groups, posterior thalamic regions showed functional connectivity with visual, auditory, and sensorimotor networks, whereas anterior, medial, and dorsal thalamic regions were connected with networks of distributed association cortex (including the default-mode, anterior-salience, and executive-control networks). Four cortical networks (left and right executive-control network; ventral and dorsal default-mode network) showed significantly enhanced thalamic functional connectivity strength in patients relative to controls. Abnormal connectivity was maximal in mediodorsal and ventrolateral thalamic nuclei. SIGNIFICANCE: Specific thalamocortical circuits are affected in LGS. Functional connectivity is abnormally enhanced between the mediodorsal and ventrolateral thalamus and the default-mode and executive-control networks, thalamocortical circuits that normally support diverse cognitive processes. In contrast, thalamic regions connecting with primary and sensory cortical networks appear to be less affected. Our previous neuroimaging studies show that epileptic activity in LGS is expressed via the default-mode and executive-control networks. Results of the present study suggest that the mediodorsal and ventrolateral thalamus may be candidate targets for modulating abnormal network behavior underlying LGS, potentially via emerging thalamic neurostimulation therapies.

Dynamic coupling between fMRI local connectivity and interictal EEG in focal epilepsy: A wavelet analysis approach.

Simultaneous scalp EEG-fMRI recording is a noninvasive neuroimaging technique for combining electrophysiological and hemodynamic aspects of brain function. Despite the time-varying nature of both measurements, their relationship is usually considered as time-invariant. The aim of this study was to detect direct associations between scalp-recorded EEG and regional changes of hemodynamic brain connectivity in focal epilepsy through a time-frequency paradigm. To do so, we developed a voxel-wise framework that analyses wavelet coherence between dynamic regional phase synchrony (DRePS, calculated from fMRI) and band amplitude fluctuation (BAF) of a target EEG electrode with dominant interictal epileptiform discharges (IEDs). As a proof of concept, we applied this framework to seven patients with focal epilepsy. The analysis produced patient-specific spatial maps of DRePS-BAF coupling, which highlight regions with a strong link between EEG power and local fMRI connectivity. Although we observed DRePS-BAF coupling proximate to the suspected seizure onset zone in some patients, our results suggest that DRePS-BAF is more likely to identify wider 'epileptic networks'. We also compared DRePS-BAF with standard EEG-fMRI analysis based on general linear modelling (GLM). There was, in general, little overlap between the DRePS-BAF maps and GLM maps. However, in some subjects the spatial clusters revealed by these two analyses appeared to be adjacent, particularly in medial posterior cortices. Our findings suggest that (1) there is a strong time-varying relationship between local fMRI connectivity and interictal EEG power in focal epilepsy, and (2) that DRePS-BAF reflect different aspects of epileptic network activity than standard EEG-fMRI analysis. These two techniques, therefore, appear to be complementary. Hum Brain Mapp 38:5356-5374, 2017. © 2017 Wiley Periodicals, Inc.

Cognitive network reorganization following surgical control of seizures in Lennox-Gastaut syndrome.

We previously observed that adults with Lennox-Gastaut syndrome (LGS) show abnormal functional connectivity among cognitive networks, suggesting that this may contribute to impaired cognition. Herein we report network reorganization following seizure remission in a child with LGS who underwent functional magnetic resonance imaging (fMRI) before and after resection of a cortical dysplasia. Concurrent electroencephalography (EEG) was acquired during presurgical fMRI. Presurgical and postsurgical functional connectivity were compared using (1) graph theoretical analyses of small-world network organization and node-wise strength; and (2) seed-based analyses of connectivity within and between five functional networks. To explore the specificity of these postsurgical network changes, connectivity was further compared to nine children with LGS who did not undergo surgery. The presurgical EEG-fMRI revealed diffuse activation of association cortex during interictal discharges. Following surgery and seizure control, functional connectivity showed increased small-world organization, stronger connectivity in subcortical structures, and greater within-network integration/between-network segregation. These changes suggest network improvement, and diverged sharply from the comparison group of nonoperated children. Following surgery, this child with LGS achieved seizure control and showed extensive reorganization of networks that underpin cognition. This case illustrates that the epileptic process of LGS can directly contribute to abnormal network organization, and that this network disruption may be reversible.

The diminishing dominance of the dominant hemisphere: Language fMRI in focal epilepsy.

"Which is the dominant hemisphere?" is a question that arises frequently in patients considered for neurosurgery. The concept of the dominant hemisphere implies uniformity of language lateralisation throughout the brain. It is increasingly recognised that this is not the case in the healthy control brain, and it is especially not so in neurological diseases such as epilepsy. In the present work we adapt our published objective lateralisation method (based on the construction of laterality curves) for use with sub-lobar cortical, subcortical and cerebellar regions of interest (ROIs). We apply this method to investigate regional lateralisation of language activation in 12 healthy controls and 18 focal epilepsy patients, using three different block design language fMRI paradigms, each tapping different aspects of language processing. We compared lateralisation within each ROI across tasks, and investigated how the quantity of data collected affected the ability to robustly estimate laterality across ROIs. In controls, lateralisation was stronger, and the variance across individuals smaller, in cortical ROIs, particularly in the Inferior Frontal (Broca) region. Lateralisation within temporal ROIs was dependent on the nature of the language task employed. One of the healthy controls was left lateralised anteriorly and right lateralised posteriorly. Consistent with previous work, departures from normality occurred in ~ 15-50% of focal epilepsy patients across the different ROIs, with atypicality most common in the Lateral Temporal (Wernicke) region. Across tasks and ROIs the absolute magnitude of the laterality estimate increased and its across participant variance decreased as more cycles of task and rest were included, stabilising at ~ 4 cycles (~ 4 min of data collection). Our data highlight the importance of considering language as a complex task where lateralisation varies at the subhemispheric scale. This is especially important for presurgical planning for focal resections where the concept of 'hemispheric dominance' may be misleading. This is a precision medicine approach that enables objective evaluation of language dominance within specific brain regions and can reveal surprising and unexpected anomalies that may be clinically important for individual cases.

Same Intervention-Different Reorganization: The Impact of Lesion Location on Training-Facilitated Somatosensory Recovery After Stroke.

BACKGROUND: The brain may reorganize to optimize stroke recovery. Yet relatively little is known about neural correlates of training-facilitated recovery, particularly after loss of body sensations. OBJECTIVE: Our aim was to characterize changes in brain activation following clinically effective touch discrimination training in stroke patients with somatosensory loss after lesions of primary/secondary somatosensory cortices or thalamic/capsular somatosensory regions using functional magnetic resonance imaging (fMRI). METHODS: Eleven stroke patients with somatosensory loss, 7 with lesions involving primary (S1) and/or secondary (S2) somatosensory cortex (4 male, 58.7 ± 13.3 years) and 4 with lesions primarily involving somatosensory thalamus and/or capsular/white matter regions (2 male, 58 ± 8.6 years) were studied. Clinical and MRI testing occurred at 6 months poststroke (preintervention), and following 15 sessions of clinically effective touch discrimination training (postintervention). RESULTS: Improved touch discrimination of a magnitude similar to previous clinical studies and approaching normal range was found. Patients with thalamic/capsular somatosensory lesions activated preintervention in left ipsilesional supramarginal gyrus, and postintervention in ipsilesional insula and supramarginal gyrus. In contrast, those with S1/S2 lesions did not show common activation preintervention, only deactivation in contralesional superior parietal lobe, including S1, and cingulate cortex postintervention. The S1/S2 group did, however, show significant change over time involving ipsilesional precuneus. This change was greater than for the thalamic/capsular group (P = .012; d = -2.43; CI = -0.67 to -3.76). CONCLUSION: Different patterns of change in activation are evident following touch discrimination training with thalamic/capsular lesions compared with S1/S2 cortical somatosensory lesions, despite common training and similar improvement.

Abnormal cognitive network interactions in Lennox-Gastaut syndrome: A potential mechanism of epileptic encephalopathy.

OBJECTIVE: In patients with Lennox-Gastaut syndrome (LGS), recurrent epileptic activity is thought to contribute to impaired cognition (epileptic encephalopathy). Using concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI), we recently showed that epileptiform discharges in LGS recruit large-scale networks that normally support key cognitive processes. In LGS, given that epileptic activity engages cognitive networks, and cognition is pervasively impaired, we hypothesized that cognitive network interactions in LGS are persistently abnormal. METHODS: We studied 15 LGS patients (mean age ± 1 standard deviation [SD] = 28.7 ± 10.6 years) and 17 healthy controls (mean age ± 1 SD = 27.6 ± 6.6 years) using task-free EEG-fMRI. Four networks of interest (default-mode, dorsal attention, executive control, and anterior salience) were defined using group-level independent components analysis (ICA). Functional connectivity within and between networks was determined for each subject, and then LGS network interactions were compared to network behavior in the control group. To test whether group differences were present in periods without scalp-detectable epileptiform discharges (i.e., persistent), we separately assessed discharge-affected and discharge-unaffected epochs in six patients with sufficient data for this analysis. RESULTS: In LGS, cognitive networks showed (1) reduced within-network integration, including weaker connectivity within the default-mode network, and (2) impaired between-network segregation, including stronger connectivity between the default-mode and dorsal attention networks. Abnormal interactions were present during fMRI periods with and without discharges, indicating that impaired network behavior may endure during periods without scalp-detectable epileptic activity. SIGNIFICANCE: In LGS, cognitive network interactions are persistently abnormal. Given that cognition typically worsens with the onset of LGS, and may improve after seizure control, our findings are consistent with the hypothesis that the epileptic process in LGS may initiate and perhaps sustain abnormal network behavior. We propose that epileptic encephalopathy may be a consequence of persistently disrupted cognitive network interactions.

Dynamic regional phase synchrony (DRePS): An Instantaneous Measure of Local fMRI Connectivity Within Spatially Clustered Brain Areas.

Dynamic functional brain connectivity analysis is a fast expanding field in computational neuroscience research with the promise of elucidating brain network interactions. Sliding temporal window based approaches are commonly used in order to explore dynamic behavior of brain networks in task-free functional magnetic resonance imaging (fMRI) data. However, the low effective temporal resolution of sliding window methods fail to capture the full dynamics of brain activity at each time point. These also require subjective decisions regarding window size and window overlap. In this study, we introduce dynamic regional phase synchrony (DRePS), a novel analysis approach that measures mean local instantaneous phase coherence within adjacent fMRI voxels. We evaluate the DRePS framework on simulated data showing that the proposed measure is able to estimate synchrony at higher temporal resolution than sliding windows of local connectivity. We applied DRePS analysis to task-free fMRI data of 20 control subjects, revealing ultra-slow dynamics of local connectivity in different brain areas. Spatial clustering based on the DRePS feature time series reveals biologically congruent local phase synchrony networks (LPSNs). Taken together, our results demonstrate three main findings. Firstly, DRePS has increased temporal sensitivity compared to sliding window correlation analysis in capturing locally synchronous events. Secondly, DRePS of task-free fMRI reveals ultra-slow fluctuations of ∼0.002-0.02 Hz. Lastly, LPSNs provide plausible spatial information about time-varying brain local phase synchrony. With the DRePS method, we introduce a framework for interrogating brain local connectivity, which can potentially provide biomarkers of human brain function in health and disease. Hum Brain Mapp 37:1970-1985, 2016. © 2016 Wiley Periodicals, Inc.