Publications by authors named "Kathryn A Davis"

77 Publications

Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states.

Commun Biol 2021 Feb 16;4(1):210. Epub 2021 Feb 16.

Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA.

A major challenge in neuroscience is determining a quantitative relationship between the brain's white matter structural connectivity and emergent activity. We seek to uncover the intrinsic relationship among brain regions fundamental to their functional activity by constructing a pairwise maximum entropy model (MEM) of the inter-ictal activation patterns of five patients with medically refractory epilepsy over an average of ~14 hours of band-passed intracranial EEG (iEEG) recordings per patient. We find that the pairwise MEM accurately predicts iEEG electrodes' activation patterns' probability and their pairwise correlations. We demonstrate that the estimated pairwise MEM's interaction weights predict structural connectivity and its strength over several frequencies significantly beyond what is expected based solely on sampled regions' distance in most patients. Together, the pairwise MEM offers a framework for explaining iEEG functional connectivity and provides insight into how the brain's structural connectome gives rise to large-scale activation patterns by promoting co-activation between connected structures.
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http://dx.doi.org/10.1038/s42003-021-01700-6DOI Listing
February 2021

Patterns of seizure spread in temporal lobe epilepsy are associated with distinct white matter tracts.

Epilepsy Res 2021 Feb 5;171:106571. Epub 2021 Feb 5.

Medical University of South Carolina, Charleston, SC, USA. Electronic address:

Objective: It is commonly hypothesized that seizure spread patterns in patients with focal epilepsy are associated with structural brain pathways. However, this relationship is poorly understood and has not been fully demonstrated in patients with temporal lobe epilepsy. Here, we sought to determine whether directionality of seizure spread (DSS) is associated with specific cerebral white matter tracts in patients with temporal lobe epilepsy.

Methods: Thirty-three adult patients with temporal lobe epilepsy who underwent stereoelectroencephalography (sEEG) and magnetic resonance diffusion tensor imaging (MR-DTI) as part of their standard-of-care clinical evaluation were included in the study. DSS was defined as anterior-posterior (AP) or medial-lateral (ML) spread based upon sEEG evaluation by two independent specialists who demonstrated excellent inter-rater agreement (Cohen's kappa = .92). DTI connectometry was used to assess differences between seizure spread pattern groups along major fiber pathways regarding fractional anisotropy (FA).

Results: Twenty-four participants showed seizures with AP spread and nine participants showed seizures with ML spread. There were no significant differences between the groups on their demographic and clinical profile. Patients with ML seizures had higher FA along the corpus callosum and, to a lesser degree, some portions of the bilateral cingulate tracts. In contrast, patients with AP seizures had higher FA along several anterior-posterior white matter projections bundles, including the cingulate fasciculus and the inferior longitudinal, with significantly less involvement of the corpus callosum compared with ML seizures.

Significance: This study confirms the hypothesis that the anatomical pattern of electrophysiological ictal propagation is associated with the structural reinforcement of supporting pathways in temporal lobe epilepsy. This observation can help elucidate mechanisms of ictal propagation and may guide future translational approaches to curtail seizure spread.
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http://dx.doi.org/10.1016/j.eplepsyres.2021.106571DOI Listing
February 2021

Multimodal in vivo recording using transparent graphene microelectrodes illuminates spatiotemporal seizure dynamics at the microscale.

Commun Biol 2021 Jan 29;4(1):136. Epub 2021 Jan 29.

Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA.

Neurological disorders such as epilepsy arise from disrupted brain networks. Our capacity to treat these disorders is limited by our inability to map these networks at sufficient temporal and spatial scales to target interventions. Current best techniques either sample broad areas at low temporal resolution (e.g. calcium imaging) or record from discrete regions at high temporal resolution (e.g. electrophysiology). This limitation hampers our ability to understand and intervene in aberrations of network dynamics. Here we present a technique to map the onset and spatiotemporal spread of acute epileptic seizures in vivo by simultaneously recording high bandwidth microelectrocorticography and calcium fluorescence using transparent graphene microelectrode arrays. We integrate dynamic data features from both modalities using non-negative matrix factorization to identify sequential spatiotemporal patterns of seizure onset and evolution, revealing how the temporal progression of ictal electrophysiology is linked to the spatial evolution of the recruited seizure core. This integrated analysis of multimodal data reveals otherwise hidden state transitions in the spatial and temporal progression of acute seizures. The techniques demonstrated here may enable future targeted therapeutic interventions and novel spatially embedded models of local circuit dynamics during seizure onset and evolution.
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http://dx.doi.org/10.1038/s42003-021-01670-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7846732PMC
January 2021

Time-evolving controllability of effective connectivity networks during seizure progression.

Proc Natl Acad Sci U S A 2021 Feb;118(5)

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104;

Over one third of the estimated 3 million people with epilepsy in the United States are medication resistant. Responsive neurostimulation from chronically implanted electrodes provides a promising treatment alternative to resective surgery. However, determining optimal personalized stimulation parameters, including when and where to intervene to guarantee a positive patient outcome, is a major open challenge. Network neuroscience and control theory offer useful tools that may guide improvements in parameter selection for control of anomalous neural activity. Here we use a method to characterize dynamic controllability across consecutive effective connectivity (EC) networks based on regularized partial correlations between implanted electrodes during the onset, propagation, and termination regimes of 34 seizures. We estimate regularized partial correlation adjacency matrices from 1-s time windows of intracranial electrocorticography recordings using the Graphical Least Absolute Shrinkage and Selection Operator (GLASSO). Average and modal controllability metrics calculated from each resulting EC network track the time-varying controllability of the brain on an evolving landscape of conditionally dependent network interactions. We show that average controllability increases throughout a seizure and is negatively correlated with modal controllability throughout. Our results support the hypothesis that the energy required to drive the brain to a seizure-free state from an ictal state is smallest during seizure onset, yet we find that applying control energy at electrodes in the seizure onset zone may not always be energetically favorable. Our work suggests that a low-complexity model of time-evolving controllability may offer insights for developing and improving control strategies targeting seizure suppression.
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http://dx.doi.org/10.1073/pnas.2006436118DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7865160PMC
February 2021

Quantitative FDG PET asymmetry features predict long-term seizure recurrence in refractory epilepsy.

Epilepsy Behav 2021 Jan 21:107714. Epub 2021 Jan 21.

Center for Neuroengineering and Therapeutics, University of Pennsylvania, 240 Skirkanich Hall, 210 S 33rd St, Philadelphia, PA 19104, United States; Department of Neurology, Hospital of the University of Pennsylvania, 3400 Spruce St, 3 West Gates Bldg, Philadelphia, PA 19104, United States. Electronic address:

Objective: Fluorodeoxyglucose-positron emission tomography (FDG-PET) is an established, independent, strong predictor of surgical outcome in refractory epilepsy. In this study, we explored the added value of quantitative [F]FDG-PET features combined with clinical variables, including electroencephalography (EEG), [F]FDG-PET, and magnetic resonance imaging (MRI) qualitative interpretations, to predict long-term seizure recurrence (mean post-op follow-up of 5.85 ± 3.77 years).

Methods: Machine learning predictive models of surgical outcome were created using a random forest classifier trained on quantitative features in 89 patients with drug-refractory temporal lobe epilepsy evaluated at the Hospital of the University of Pennsylvania epilepsy surgery program (2003-2016). Quantitative features were calculated from asymmetry features derived from image processing using Advanced Normalization Tools (ANTs).

Results: The best-performing model used quantification and had an out-of-bag accuracy of 0.71 in identifying patients with seizure recurrence (Engel IB or worse) which outperformed that using qualitative clinical data by 10%. This model is shared through open-source software for research use. In addition, several asymmetry features in temporal and extratemporal regions that were significantly associated with seizure freedom are identified for future study.

Significance: Complex quantitative [F]FDG-PET imaging features can predict seizure recurrence in patients with refractory temporal lobe epilepsy. These initial retrospective results in a cohort with long-term follow-up suggest that using quantitative imaging features from regions in the epileptogenic network can inform the clinical decision-making process.
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http://dx.doi.org/10.1016/j.yebeh.2020.107714DOI Listing
January 2021

Network Analyses in Epilepsy: Are Nodes and Edges Ready for Clinical Translation?

Neurology 2021 02 22;96(5):195-196. Epub 2020 Dec 22.

From the Department of Neurology (K.A.D.) and Center for Neuroengineering and Therapeutics (K.A.D.), University of Pennsylvania, Philadelphia; Vanderbilt University Institute of Imaging Science (V.L.M.), Department of Radiology and Radiological Sciences, Department of Neurological Surgery (V.L.M.), and Department of Neurology, Vanderbilt University Medical Center; and Department of Biomedical Engineering, Vanderbilt University, Nashville.

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http://dx.doi.org/10.1212/WNL.0000000000011316DOI Listing
February 2021

7T Epilepsy Task Force Consensus Recommendations on the Use of 7T MRI in Clinical Practice.

Neurology 2021 02 22;96(7):327-341. Epub 2020 Dec 22.

From the Neurobiology Research Unit (G.O., L.H.P.), and Epilepsy Clinic (L.H.P.), Department of Neurology, Rigshospitalet Copenhagen University Hospital; Faculty of Health and Medical Sciences (G.O.), UCPH, Denmark; Departments of Neurology and Neurosurgery (T.J.V.), UMC Utrecht Brain Center, and Department of Radiology (A.v.d.K.), University Medical Center Utrecht, Utrecht University; Department of Radiology (A.v.d.K.), Netherlands Cancer Institute Antoni van Leeuwenhoek Hospital, Amsterdam; Lund University Bioimaging Center (K.M.B.), Lund University, Sweden; Department of Neurology (A.J.C.), Neurophysiology and Neurosurgery, ACE Kempenhaeghe/MUMC, Heeze/Maastricht, the Netherlands; Department of Radiology (J.M.S.) and Penn Epilepsy Center (K.D.), Hospital of the University of Pennsylvania, Philadelphia; Department of Neurology (T.R.H.) and Center for Magnetic Resonance Research (P.-F.V.d.M., R.E.M.), University of Minnesota, Minneapolis; Department of Radiology and Nuclear Medicine (J.F.A.J.), Maastricht University Medical Center; School for Mental Health and Neuroscience (J.F.A.J.), Maastricht University; Department of Electrical Engineering (J.F.A.J.), Eindhoven University of Technology, the Netherlands; Imaging Institute (S.E.J.) and Epilepsy Center (I.W.), Cleveland Clinic, OH; Department of Neurology and Radiology (J.W.P.), University of Pittsburg, PA; Department of Neurosurgery (K.R.), Medical University of Vienna, Austria; Departments of Neurology and Clinical Sciences (M.C.S.), Lund University Hospital, Sweden; Department of Biomedical Imaging and Image Guided Therapy (S.T.), High Field MR Center, Medical University of Vienna, Austria; Neuroradiology Division, Diagnostic Unit (M.I.V.), University Hospitals and Faculty of Medicine of Geneva, Switzerland; Epileptology Department - INS (F.B.) and CRMBM - CEMEREM (J.-P.R., M.G.), Timone Hospital APHM, Aix Marseille Univ, INSERM, CNRS, France; Neuroimaging of Epilepsy Laboratory (NOEL) (N.B., A.B.), Montreal Neurological Institute (B.B.), and McConnell Brain Imaging Centre (N.B., A.B.), McGill University, Montreal, Canada; Department of Radiology (I.B.-B.), Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Sweden; Department of Translational Research and New Technologies in Medicine and Surgery (M.C.), University of Pisa, Italy; Department of Neurology (S.R.D.), University of Pennsylvania, Philadelphia; NeuroSpin (L.H.-P., A.V.), Paris-Saclay University, CEA, CNRS, BAOBAB, Gif-sur-Yvette, France; UMR 1141 (L.H.-P), University of Paris, France; EEG Section (S.I.), NINDS, NIH, Bethesda, MD; Department of Medical Imaging (M.T.J.), Children's Hospital at London Health Sciences Centre; Department of Medical Biophysics (M.T.J., A.R.K.), Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Canada; Imaging Research Laboratories (A.R.K.), Robarts Research Institute, London, ON, Canada; Functional Neurosurgery Department (S.L.), Beijing Children's Hospital of Capital Medical University, Beijing, China; Department of Radiology (S.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; NYU Grossman School of Medicine (H.P.), New York; Harvard MIT Division of Health Sciences and Technology (J.R.P., S.S.), Massachusetts Institute of Technology, Cambridge; Athinoula A. Martinos Center for Biomedical Imaging (J.R.P., S.S.), Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA; Scannexus Ultrahigh Field MRI Research Center (E.S., C.J.W.), Maastricht; Department of Radiology and Nuclear Medicine (T.J.V.), Meander Medical Center, Amersfoort, the Netherlands; Wellcome Centre for Integrative Neuroimaging (N.V.), FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; EEG and Epilepsy Unit (S.V.), Neurology, Department of Clinical Neurosciences, University Hospitals and Faculty of Medicine of Geneva, Switzerland; State Key Lab of Brain and Cognitive Science (R.X.), Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, China; Neuroscience Department (R.G.), Children's Hospital A. Meyer-University of Florence; and IMAGO 7 Foundation (R.G.), Florence, Italy.

Identifying a structural brain lesion on MRI has important implications in epilepsy and is the most important factor that correlates with seizure freedom after surgery in patients with drug-resistant focal onset epilepsy. However, at conventional magnetic field strengths (1.5 and 3T), only approximately 60%-85% of MRI examinations reveal such lesions. Over the last decade, studies have demonstrated the added value of 7T MRI in patients with and without known epileptogenic lesions from 1.5 and/or 3T. However, translation of 7T MRI to clinical practice is still challenging, particularly in centers new to 7T, and there is a need for practical recommendations on targeted use of 7T MRI in the clinical management of patients with epilepsy. The 7T Epilepsy Task Force-an international group representing 21 7T MRI centers with experience from scanning over 2,000 patients with epilepsy-would hereby like to share its experience with the neurology community regarding the appropriate clinical indications, patient selection and preparation, acquisition protocols and setup, technical challenges, and radiologic guidelines for 7T MRI in patients with epilepsy. This article mainly addresses structural imaging; in addition, it presents multiple nonstructural MRI techniques that benefit from 7T and hold promise as future directions in epilepsy. Answering to the increased availability of 7T MRI as an approved tool for diagnostic purposes, this article aims to provide guidance on clinical 7T MRI epilepsy management by giving recommendations on referral, suitable 7T MRI protocols, and image interpretation.
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http://dx.doi.org/10.1212/WNL.0000000000011413DOI Listing
February 2021

Unilateral thalamic lesion mimicking genetic generalized epilepsy.

Epileptic Disord 2020 Dec;22(6):836-838

Department of Neurology.

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http://dx.doi.org/10.1684/epd.2020.1235DOI Listing
December 2020

Theta Synchrony Is Increased near Neural Populations That Are Active When Initiating Instructed Movement.

eNeuro 2021 Jan-Feb;8(1). Epub 2021 Feb 8.

Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104.

Theta oscillations (3-8 Hz) in the human brain have been linked to perception, cognitive control, and spatial memory, but their relation to the motor system is less clear. We tested the hypothesis that theta oscillations coordinate distributed behaviorally relevant neural representations during movement using intracranial electroencephalography (iEEG) recordings from nine patients ( = 490 electrodes) as they performed a simple instructed movement task. Using high frequency activity (HFA; 70-200 Hz) as a marker of local spiking activity, we identified electrodes that were positioned near neural populations that showed increased activity during instruction and movement. We found that theta synchrony was widespread throughout the brain but was increased near regions that showed movement-related increases in neural activity. These results support the view that theta oscillations represent a general property of brain activity that may also play a specific role in coordinating widespread neural activity when initiating voluntary movement.
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http://dx.doi.org/10.1523/ENEURO.0252-20.2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901148PMC
February 2021

Inconsistent reporting of drug-drug interactions for hormonal contraception and antiepileptic drugs - Implications for reproductive health for women with epilepsy.

Epilepsy Behav 2021 Jan 9;114(Pt A):107626. Epub 2020 Dec 9.

Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA. Electronic address:

Drug compendia are the source of safety prescribing information. We assessed the reporting concordance of drug-drug interactions between hormonal contraception and antiepileptic drugs (AEDs) among eight leading international drug compendia. Antiepileptic drugs reported to interact with ≥1 form of hormonal contraception were reviewed. Scaled concordance was quantified using linearly weighted percent agreement (wPA). Differences in interaction severity rankings between hormonal contraception forms were evaluated using the Wilcoxon signed-rank test. There was high agreement among compendia for interactions of combined hormonal contraception interactions with AEDs (wPA = 0.82-0.84), especially potent enzyme-inducing AEDs (wPA = 0.89). However, concordance was reduced for AED interactions with progestin-only contraception (wPA = 0.69-0.81). Extreme interaction reporting discrepancies were found for less potent enzyme-inducing AEDs. The greatest variability in interaction reporting was observed for injectable and intrauterine contraception (wPA = 0.69 and 0.70, respectively), which are the only hormonal contraception options currently classified as not interacting with enzyme-inducing AEDs. Drug-drug interaction reporting variability can have major clinical implications and highlights critical knowledge gaps in the care of women with epilepsy of childbearing age. Further research on AED-contraceptive interactions is needed to standardize compendia reporting and enhance evidence-based clinical guidelines for women with epilepsy.
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http://dx.doi.org/10.1016/j.yebeh.2020.107626DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855647PMC
January 2021

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy.

J Clin Neurophysiol 2020 Dec 8. Epub 2020 Dec 8.

Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A..

Introduction: The authors tested the hypothesis that the EEG feature generalized polyspike train (GPT) is associated with drug-resistant idiopathic generalized epilepsy (IGE).

Methods: The authors conducted a single-center case-control study of patients with IGE who had outpatient EEGs performed between 2016 and 2020. The authors classified patients as drug-resistant or drug-responsive based on clinical review and in a masked manner reviewed EEG data for the presence and timing of GPT (a burst of generalized rhythmic spikes lasting less than 1 second) and other EEG features. A relationship between GPT and drug resistance was tested before and after controlling for EEG duration. The EEG duration needed to observe GPT was also calculated.

Results: One hundred three patients were included (70% drug-responsive and 30% drug-resistant patients). Generalized polyspike train was more prevalent in drug-resistant IGE (odds ratio, 3.8; 95% confidence interval, 1.3-11.4; P = 0.02). This finding persisted when controlling for EEG duration both with stratification and with survival analysis. A median of 6.5 hours (interquartile range, 0.5-12.7 hours) of EEG recording was required to capture the first occurrence of GPT.

Conclusions: The findings support the hypothesis that GPT is associated with drug-resistant IGE. Prolonged EEG recording is required to identify this feature. Thus, >24-hour EEG recording early in the evaluation of patients with IGE may facilitate prognostication.
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http://dx.doi.org/10.1097/WNP.0000000000000803DOI Listing
December 2020

Exposure to early childhood maltreatment and its effect over time on social cognition.

Dev Psychopathol 2020 Oct 19:1-11. Epub 2020 Oct 19.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.

Social cognitive deficits can have many negative consequences, spanning social withdrawal to psychopathology. Prior work has shown that child maltreatment may associate with poorer social cognitive skills in later life. However, no studies have examined this association from early childhood into adolescence. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4,438), we examined the association between maltreatment (caregiver physical or emotional abuse; sexual or physical abuse), assessed repeatedly (every 1-3 years) from birth to age 9, and social cognitive skills at ages 7.5, 10.5, and 14 years. We evaluated the role of both the developmental timing (defined by age at exposure) and accumulation of maltreatment (defined as the number of occasions exposed) using a least angle regression variable selection procedure, followed by structural equation modeling. Among females, accumulation of maltreatment explained the most variation in social cognitive skills. For males, no significant associations were found. These findings underscore the importance of early intervention to minimize the accumulation of maltreatment and showcase the importance of prospective studies to understand the development of social cognition over time.
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http://dx.doi.org/10.1017/S095457942000139XDOI Listing
October 2020

The mental health effects of pet death during childhood: is it better to have loved and lost than never to have loved at all?

Eur Child Adolesc Psychiatry 2020 Sep 10. Epub 2020 Sep 10.

Center for Genomic Medicine, Department of Psychiatry, Harvard Medical School, Massachusetts General Hospital, Center On the Developing Child at Harvard University, 185 Cambridge Street, Simches Research Building 6th Floor, Boston, MA, 02114, USA.

Pet ownership is common. Growing evidence suggests children form deep emotional attachments to their pets. Yet, little is known about children's emotional reactions to a pet's death. The goal of this study was to describe the relationship between experiences of pet death and risk of childhood psychopathology and determine if it was "better to have loved and lost than never to have loved at all". Data came from the Avon Longitudinal Study of Parents and Children, a UK-based prospective birth cohort (n = 6260). Children were characterized based on their exposure to pet ownership and pet death from birth to age 7 (never loved; loved without loss; loved with loss). Psychopathology symptoms at age 8 were compared across groups using multivariable linear regression. Psychopathology symptoms were higher among children who had loved with loss compared to those who had loved without loss (β = 0.35, p = 0.013; 95% CI = 0.07, 0.63), even after adjustment for other adversities. This group effect was more pronounced in males than in females. There was no difference in psychopathology symptoms between children who had loved with loss and those who had never loved (β = 0.20, p = 0.31, 95% CI = -0.18-0.58). The developmental timing, recency, or accumulation of pet death was unassociated with psychopathology symptoms. Pet death may be traumatic for children and associated with subsequent mental health difficulties. Where childhood pet ownership and pet bereavement is concerned, Tennyson's pronouncement may not apply to children's grief responses: it may not be "better to have loved and lost than never to have loved at all".
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http://dx.doi.org/10.1007/s00787-020-01594-5DOI Listing
September 2020

Corrigendum to 'Adversity exposure during sensitive periods predicts accelerated epigenetic aging in children' [Psychoneuroendocrinology 113 March (2020) 104484].

Psychoneuroendocrinology 2020 Nov 27;121:104829. Epub 2020 Aug 27.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, 02115, USA; McCance Center for Brain Health at Massachusetts General Hospital, Boston, MA, 02114, USA. Electronic address:

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http://dx.doi.org/10.1016/j.psyneuen.2020.104829DOI Listing
November 2020

Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study.

Ann Neurol 2020 11 10;88(5):970-983. Epub 2020 Sep 10.

Department of Neurology, Medical University of South Carolina, Charleston, SC, USA.

Objective: Medial temporal lobe epilepsy (TLE) is the most common form of medication-resistant focal epilepsy in adults. Despite removal of medial temporal structures, more than one-third of patients continue to have disabling seizures postoperatively. Seizure refractoriness implies that extramedial regions are capable of influencing the brain network and generating seizures. We tested whether abnormalities of structural network integration could be associated with surgical outcomes.

Methods: Presurgical magnetic resonance images from 121 patients with drug-resistant TLE across 3 independent epilepsy centers were used to train feed-forward neural network models based on tissue volume or graph-theory measures from whole-brain diffusion tensor imaging structural connectomes. An independent dataset of 47 patients with TLE from 3 other epilepsy centers was used to assess the predictive values of each model and regional anatomical contributions toward surgical treatment results.

Results: The receiver operating characteristic area under the curve based on regional betweenness centrality was 0.88, significantly higher than a random model or models based on gray matter volumes, degree, strength, and clustering coefficient. Nodes most strongly contributing to the predictive models involved the bilateral parahippocampal gyri, as well as the superior temporal gyri.

Interpretation: Network integration in the medial and lateral temporal regions was related to surgical outcomes. Patients with abnormally integrated structural network nodes were less likely to achieve seizure freedom. These findings are in line with previous observations related to network abnormalities in TLE and expand on the notion of underlying aberrant plasticity. Our findings provide additional information on the mechanisms of surgical refractoriness. ANN NEUROL 2020;88:970-983.
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http://dx.doi.org/10.1002/ana.25888DOI Listing
November 2020

Pearls & Oy-sters: Bilateral globus pallidus lesions in a patient with COVID-19.

Neurology 2020 09 25;95(10):454-457. Epub 2020 Jun 25.

From the Department of Neurology (C.V.K.-S., J.L.M., A.R., M.A.G., B.L.C., K.A.D.), Department of Radiology (R.L.W., S.M., J.M.S., J.H.M., J.W.L.), Division of Pulmonary, Allergy, and Critical Care (D.G.D., J.E.M.), and Division of Infectious Diseases (M.Z.D., R.N.E.), Perelman School of Medicine at the University of Pennsylvania; and Division of Neurology (J.L.M.), the Children's Hospital of Philadelphia, PA.

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http://dx.doi.org/10.1212/WNL.0000000000010157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7538218PMC
September 2020

Features of Childhood Maltreatment and Resilience Capacity in Adulthood: Results from a Large Community-Based Sample.

J Trauma Stress 2020 10 14;33(5):665-676. Epub 2020 Jun 14.

Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA.

Childhood maltreatment is consistently associated with poor outcomes. However, few epidemiological studies have examined the association between childhood maltreatment and adult resilience capacity, defined as one's perceived ability to cope successfully with challenges. This study aimed to determine associations between adult resilience capacity and specific types and features of childhood maltreatment. Participants were African American adults recruited from a public urban hospital in Atlanta, GA (N = 1,962) between 2005 and 2013. Childhood maltreatment, including witnessing domestic violence or physical, emotional, and sexual abuse, was assessed retrospectively using the Traumatic Events Inventory. Perceived resilience capacity was assessed using the Connor-Davidson Resilience Scale. Linear regressions were performed assessing the association between resilience capacity and childhood maltreatment exposure in general, as well as specific dimensions of exposure, including type, co-occurrence, and developmental timing, adjusting for covariates. Participants exposed to any maltreatment reported lower resilience capacity than unexposed peers, B = -0.38, SE = 0.04, p < .001. All maltreatment types were negatively associated with resilience capacity, even after adjusting for other lifetime trauma exposure. Only emotional abuse remained significantly associated with resilience capacity after accounting for current psychological distress, B = -0.11, SE = 0.05, p = .022. Maltreatment co-occurrence followed an inverse dose-response relationship with resilience capacity: For each additional maltreatment type, scores decreased by 0.18 units (SD = 0.02), p < .001. Finally, the developmental timing of maltreatment did not reveal any differential influences on resilience capacity. The results suggest that childhood emotional abuse and co-occurrence of maltreatment types may be particularly deleterious to adult resilience capacity.
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http://dx.doi.org/10.1002/jts.22543DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7828462PMC
October 2020

The sensitivity of network statistics to incomplete electrode sampling on intracranial EEG.

Netw Neurosci 2020 1;4(2):484-506. Epub 2020 May 1.

Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

Network neuroscience applied to epilepsy holds promise to map pathological networks, localize seizure generators, and inform targeted interventions to control seizures. However, incomplete sampling of the epileptic brain because of sparse placement of intracranial electrodes may affect model results. In this study, we evaluate the sensitivity of several published network measures to incomplete spatial sampling and propose an algorithm using network subsampling to determine confidence in model results. We retrospectively evaluated intracranial EEG data from 28 patients implanted with grid, strip, and depth electrodes during evaluation for epilepsy surgery. We recalculated global and local network metrics after randomly and systematically removing subsets of intracranial EEG electrode contacts. We found that sensitivity to incomplete sampling varied significantly across network metrics. This sensitivity was largely independent of whether seizure onset zone contacts were targeted or spared from removal. We present an algorithm using random subsampling to compute patient-specific confidence intervals for network localizations. Our findings highlight the difference in robustness between commonly used network metrics and provide tools to assess confidence in intracranial network localization. We present these techniques as an important step toward translating personalized network models of seizures into rigorous, quantitative approaches to invasive therapy.
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http://dx.doi.org/10.1162/netn_a_00131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286312PMC
May 2020

The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity.

Brain Stimul 2020 Sep - Oct;13(5):1183-1195. Epub 2020 May 21.

Department of Biomedical Engineering, Columbia University, New York, 10027, USA. Electronic address:

Background: Researchers have used direct electrical brain stimulation to treat a range of neurological and psychiatric disorders. However, for brain stimulation to be maximally effective, clinicians and researchers should optimize stimulation parameters according to desired outcomes.

Objective: The goal of our large-scale study was to comprehensively evaluate the effects of stimulation at different parameters and locations on neuronal activity across the human brain.

Methods: To examine how different kinds of stimulation affect human brain activity, we compared the changes in neuronal activity that resulted from stimulation at a range of frequencies, amplitudes, and locations with direct human brain recordings. We recorded human brain activity directly with electrodes that were implanted in widespread regions across 106 neurosurgical epilepsy patients while systematically stimulating across a range of parameters and locations.

Results: Overall, stimulation most often had an inhibitory effect on neuronal activity, consistent with earlier work. When stimulation excited neuronal activity, it most often occurred from high-frequency stimulation. These effects were modulated by the location of the stimulating electrode, with stimulation sites near white matter more likely to cause excitation and sites near gray matter more likely to inhibit neuronal activity.

Conclusion: By characterizing how different stimulation parameters produced specific neuronal activity patterns on a large scale, our results provide an electrophysiological framework that clinicians and researchers may consider when designing stimulation protocols to cause precisely targeted changes in human brain activity.
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http://dx.doi.org/10.1016/j.brs.2020.05.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494653PMC
May 2020

Epilepsy Lesion Localization is not Predicted by Developmental Venous Anomaly Location or its FDG-PET Metabolic Activity.

J Neuroimaging 2020 07 8;30(4):544-550. Epub 2020 May 8.

Department of Neuroradiology, The Hospital of the University of Pennsylvania, Philadelphia, PA.

Background And Purpose: This study's purpose is to correlate location and metabolic activity of developmental venous anomalies (DVAs) in epilepsy patients to the seizure focus as determined by ictal/interictal encephaloelectrogram (EEG).

Methods: A retrospective search was performed for epilepsy patients with DVAs who underwent brain F-fluorodeoxyglucose positron emission tomography ( F-FDG-PET) and magnetic resonance imaging (MRI). MRI exams were analyzed to characterize DVA location and associated structural findings. MRI and PET images were co-registered and assessment of F-FDG uptake in the DVA territory was performed. The electronic medical record was reviewed for each subject to determine seizure semiology and site of seizure focus by ictal/interictal EEG.

Results: Twenty-eight DVAs in 25 patients were included. Twelve DVAs demonstrated regional metabolic abnormality on F-FDG-PET. There was no significant correlation between DVA site and seizure focus on EEG. DVA location was concordant with EEG seizure focus in three subjects, and all three demonstrated hypometabolism on F-FDG-PET. This significance remains indeterminate, as one of these DVAs was associated with cavernoma, which could serve as the true seizure focus, and one of the patients underwent resection of the DVA without decrease in seizure frequency. Furthermore, there was no statistically significant relationship between DVA metabolic activity and DVA-EEG lobar or laterality concordance.

Conclusions: In this sample, there is no significant correlation between location of DVA and seizure focus, and hypometabolism within the DVA territory is not predictive of EEG/DVA co-localization. As use of F-FDG-PET for evaluation of epilepsy increases, knowledge of this poor correlation is important to avoid diagnostic confusion and potentially unnecessary surgery in epilepsy patients.
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http://dx.doi.org/10.1111/jon.12722DOI Listing
July 2020

Model-based design for seizure control by stimulation.

J Neural Eng 2020 03 26;17(2):026009. Epub 2020 Mar 26.

Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, United States of America. U.S. Army Research Laboratory, Aberdeen Proving Ground, MD 21005, United States of America.

Objective: Current brain stimulation paradigms are largely empirical rather than theoretical. An opportunity exists to improve upon their modest effectiveness in closed-loop control strategies with the development of theoretically grounded, model-based designs.

Approach: Inspired by this need, here we couple experimental data and mathematical modeling with a control-theoretic strategy for seizure termination. We begin by exercising a dynamical systems approach to model seizures (n = 94) recorded using intracranial EEG (iEEG) from 21 patients with medication-resistant, localization-related epilepsy.

Main Results: Although each patient's seizures displayed unique spatial and temporal patterns, their evolution can be parsimoniously characterized by the same model form. Idiosyncracies of the model can inform individualized intervention strategies, specifically in iEEG samples with well-localized seizure onset zones. Temporal fluctuations in the spatial profiles of the oscillatory modes show that seizure onset marks a transition into a regime in which the underlying system supports prolonged rhythmic and focal activity. Based on these observations, we propose a control-theoretic strategy that aims to stabilize ictal activity using static output feedback for linear time-invariant switching systems. Finally, we demonstrate in silico that our proposed strategy allows us to dampen the emerging focal oscillatory sources using only a small set of electrodes.

Significance: Our integrative study informs the development of modulation and control algorithms for neurostimulation that could improve the effectiveness of implantable, closed-loop anti-epileptic devices.
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http://dx.doi.org/10.1088/1741-2552/ab7a4eDOI Listing
March 2020

Adversity exposure during sensitive periods predicts accelerated epigenetic aging in children.

Psychoneuroendocrinology 2020 03 6;113:104484. Epub 2019 Nov 6.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA; Stanley Center for Psychiatric Research, The Broad Institute of Harvard and MIT, Cambridge, MA, 02142, USA; Department of Psychiatry, Harvard Medical School, Boston, MA, 02115, USA; McCance Center for Brain Health at Massachusetts General Hospital, Boston, MA, 02114, USA. Electronic address:

Objectives: Exposure to adversity has been linked to accelerated biological aging, which in turn has been shown to predict numerous physical and mental health problems. In recent years, measures of DNA methylation-based epigenetic age--known as "epigenetic clocks"--have been used to estimate accelerated epigenetic aging. Although a small number of studies have found an effect of adversity exposure on epigenetic age in children, none have investigated if there are "sensitive periods" when adversity is most impactful.

Methods: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 973), we tested the prospective association between repeated measures of childhood exposure to seven types of adversity on epigenetic age assessed at age 7.5 using the Horvath and Hannum epigenetic clocks. With a Least Angle Regression variable selection procedure, we evaluated potential sensitive period effects.

Results: We found that exposure to abuse, financial hardship, or neighborhood disadvantage during sensitive periods in early and middle childhood best explained variability in the deviation of Hannum-based epigenetic age from chronological age, even after considering the role of adversity accumulation and recency. Secondary sex-stratified analyses identified particularly strong sensitive period effects. These effects were undetected in analyses comparing children "exposed" versus "unexposed" to adversity. We did not identify any associations between adversity and epigenetic age using the Horvath epigenetic clock.

Conclusions: Our results suggest that adversity may alter methylation processes in ways that either directly or indirectly perturb normal cellular aging and that these effects may be heightened during specific life stages.
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http://dx.doi.org/10.1016/j.psyneuen.2019.104484DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832214PMC
March 2020

Spatial distribution of interictal spikes fluctuates over time and localizes seizure onset.

Brain 2020 02;143(2):554-569

Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

The location of interictal spikes is used to aid surgical planning in patients with medically refractory epilepsy; however, their spatial and temporal dynamics are poorly understood. In this study, we analysed the spatial distribution of interictal spikes over time in 20 adult and paediatric patients (12 females, mean age = 34.5 years, range = 5-58) who underwent intracranial EEG evaluation for epilepsy surgery. Interictal spikes were detected in the 24 h surrounding each seizure and spikes were clustered based on spatial location. The temporal dynamics of spike spatial distribution were calculated for each patient and the effects of sleep and seizures on these dynamics were evaluated. Finally, spike location was assessed in relation to seizure onset location. We found that spike spatial distribution fluctuated significantly over time in 14/20 patients (with a significant aggregate effect across patients, Fisher's method: P < 0.001). A median of 12 sequential hours were required to capture 80% of the variability in spike spatial distribution. Sleep and postictal state affected the spike spatial distribution in 8/20 and 4/20 patients, respectively, with a significant aggregate effect (Fisher's method: P < 0.001 for each). There was no evidence of pre-ictal change in the spike spatial distribution for any patient or in aggregate (Fisher's method: P = 0.99). The electrode with the highest spike frequency and the electrode with the largest area of downstream spike propagation both localized the seizure onset zone better than predicted by chance (Wilcoxon signed-rank test: P = 0.005 and P = 0.002, respectively). In conclusion, spikes localize seizure onset. However, temporal fluctuations in spike spatial distribution, particularly in relation to sleep and post-ictal state, can confound localization. An adequate duration of intracranial recording-ideally at least 12 sequential hours-capturing both sleep and wakefulness should be obtained to sufficiently sample the interictal network.
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http://dx.doi.org/10.1093/brain/awz386DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537381PMC
February 2020

Teeth as Potential New Tools to Measure Early-Life Adversity and Subsequent Mental Health Risk: An Interdisciplinary Review and Conceptual Model.

Biol Psychiatry 2020 03 17;87(6):502-513. Epub 2019 Dec 17.

Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts; Henry and Allison McCance Center for Brain Health, Massachusetts General Hospital, Boston, Massachusetts; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts. Electronic address:

Early-life adversity affects nearly half of all youths in the United States and is a known risk factor for psychiatric disorders across the life course. One strategy to prevent mental illness may be to target interventions toward children who are exposed to adversity, particularly during sensitive periods when these adversities may have even more enduring effects. However, a major obstacle impeding progress in this area is the lack of tools to reliably and validly measure the existence and timing of early-life adversity. In this review, we summarize empirical work across dentistry, anthropology, and archaeology on human tooth development and discuss how teeth preserve a time-resolved record of our life experiences. Specifically, we articulate how teeth have been examined in these fields as biological fossils in which the history of an individual's early-life experiences is permanently imprinted; this area of research is related to, but distinct from, studies of oral health. We then integrate these insights with knowledge about the role of psychosocial adversity in shaping psychopathology risk to present a working conceptual model, which proposes that teeth may be an understudied yet suggestive new tool to identify individuals at risk for mental health problems following early-life psychosocial stress exposure. We end by presenting a research agenda and discussion of future directions for rigorously testing this possibility and with a call to action for interdisciplinary research to meet the urgent need for new biomarkers of adversity and psychiatric outcomes.
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http://dx.doi.org/10.1016/j.biopsych.2019.09.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822497PMC
March 2020

Alzheimer-like amyloid and tau alterations associated with cognitive deficit in temporal lobe epilepsy.

Brain 2020 01;143(1):191-209

Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Temporal lobe epilepsy represents a major cause of drug-resistant epilepsy. Cognitive impairment is a frequent comorbidity, but the mechanisms are not fully elucidated. We hypothesized that the cognitive impairment in drug-resistant temporal lobe epilepsy could be due to perturbations of amyloid and tau signalling pathways related to activation of stress kinases, similar to those observed in Alzheimer's disease. We examined these pathways, as well as amyloid-β and tau pathologies in the hippocampus and temporal lobe cortex of drug-resistant temporal lobe epilepsy patients who underwent temporal lobe resection (n = 19), in comparison with age- and region-matched samples from neurologically normal autopsy cases (n = 22). Post-mortem temporal cortex samples from Alzheimer's disease patients (n = 9) were used as positive controls to validate many of the neurodegeneration-related antibodies. Western blot and immunohistochemical analysis of tissue from temporal lobe epilepsy cases revealed increased phosphorylation of full-length amyloid precursor protein and its associated neurotoxic cleavage product amyloid-β*56. Pathological phosphorylation of two distinct tau species was also increased in both regions, but increases in amyloid-β1-42 peptide, the main component of amyloid plaques, were restricted to the hippocampus. Furthermore, several major stress kinases involved in the development of Alzheimer's disease pathology were significantly activated in temporal lobe epilepsy brain samples, including the c-Jun N-terminal kinase and the protein kinase R-like endoplasmic reticulum kinase. In temporal lobe epilepsy cases, hippocampal levels of phosphorylated amyloid precursor protein, its pro-amyloidogenic processing enzyme beta-site amyloid precursor protein cleaving enzyme 1, and both total and hyperphosphorylated tau expression, correlated with impaired preoperative executive function. Our study suggests that neurodegenerative and stress-related processes common to those observed in Alzheimer's disease may contribute to cognitive impairment in drug-resistant temporal lobe epilepsy. In particular, we identified several stress pathways that may represent potential novel therapeutic targets.
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http://dx.doi.org/10.1093/brain/awz381DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6935754PMC
January 2020

Unsupervised machine-learning classification of electrophysiologically active electrodes during human cognitive task performance.

Sci Rep 2019 11 22;9(1):17390. Epub 2019 Nov 22.

Mayo Clinic, Dept. of Neurology, Rochester, MN, USA.

Identification of active electrodes that record task-relevant neurophysiological activity is needed for clinical and industrial applications as well as for investigating brain functions. We developed an unsupervised, fully automated approach to classify active electrodes showing event-related intracranial EEG (iEEG) responses from 115 patients performing a free recall verbal memory task. Our approach employed new interpretable metrics that quantify spectral characteristics of the normalized iEEG signal based on power-in-band and synchrony measures. Unsupervised clustering of the metrics identified distinct sets of active electrodes across different subjects. In the total population of 11,869 electrodes, our method achieved 97% sensitivity and 92.9% specificity with the most efficient metric. We validated our results with anatomical localization revealing significantly greater distribution of active electrodes in brain regions that support verbal memory processing. We propose our machine-learning framework for objective and efficient classification and interpretation of electrophysiological signals of brain activities supporting memory and cognition.
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http://dx.doi.org/10.1038/s41598-019-53925-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6874617PMC
November 2019

Virtual resection predicts surgical outcome for drug-resistant epilepsy.

Brain 2019 12;142(12):3892-3905

Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.

Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.
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http://dx.doi.org/10.1093/brain/awz303DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6885672PMC
December 2019

High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients.

Neuroimage Clin 2019 19;23:101908. Epub 2019 Jun 19.

Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.

Patients with drug-resistant focal epilepsy are often candidates for invasive surgical therapies. In these patients, it is necessary to accurately localize seizure generators to ensure seizure freedom following intervention. While intracranial electroencephalography (iEEG) is the gold standard for mapping networks for surgery, this approach requires inducing and recording seizures, which may cause patient morbidity. The goal of this study is to evaluate the utility of mapping interictal (non-seizure) iEEG networks to identify targets for surgical treatment. We analyze interictal iEEG recordings and neuroimaging from 27 focal epilepsy patients treated via surgical resection. We generate interictal functional networks by calculating pairwise correlation of iEEG signals across different frequency bands. Using image coregistration and segmentation, we identify electrodes falling within surgically resected tissue (i.e. the resection zone), and compute node-level and edge-level synchrony in relation to the resection zone. We further associate these metrics with post-surgical outcomes. Greater overlap between resected electrodes and highly synchronous electrodes is associated with favorable post-surgical outcomes. Additionally, good-outcome patients have significantly higher connectivity localized within the resection zone compared to those with poorer postoperative seizure control. This finding persists following normalization by a spatially-constrained null model. This study suggests that spatially-informed interictal network synchrony measures can distinguish between good and poor post-surgical outcomes. By capturing clinically-relevant information during interictal periods, our method may ultimately reduce the need for prolonged invasive implants and provide insights into the pathophysiology of an epileptic brain. We discuss next steps for translating these findings into a prospectively useful clinical tool.
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http://dx.doi.org/10.1016/j.nicl.2019.101908DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617333PMC
August 2020

White Matter Network Architecture Guides Direct Electrical Stimulation through Optimal State Transitions.

Cell Rep 2019 Sep;28(10):2554-2566.e7

Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics and Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Optimizing direct electrical stimulation for the treatment of neurological disease remains difficult due to an incomplete understanding of its physical propagation through brain tissue. Here, we use network control theory to predict how stimulation spreads through white matter to influence spatially distributed dynamics. We test the theory's predictions using a unique dataset comprising diffusion weighted imaging and electrocorticography in epilepsy patients undergoing grid stimulation. We find statistically significant shared variance between the predicted activity state transitions and the observed activity state transitions. We then use an optimal control framework to posit testable hypotheses regarding which brain states and structural properties will efficiently improve memory encoding when stimulated. Our work quantifies the role that white matter architecture plays in guiding the dynamics of direct electrical stimulation and offers empirical support for the utility of network control theory in explaining the brain's response to stimulation.
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http://dx.doi.org/10.1016/j.celrep.2019.08.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6849479PMC
September 2019

Childhood maltreatment experiences and problematic sexual outcomes in adult males who have sexually offended: Further evidence of the potency of male caregiver psychological abuse.

Child Abuse Negl 2019 10 19;96:104097. Epub 2019 Aug 19.

Department of Psychology, Brandeis University, Waltham, MA, United States.

Background: Although research on the developmental antecedents of sexual offending has tended to focus on sexual abuse, recent research in juveniles and adults who have sexually offended suggests that psychological abuse perpetrated by a male caregiver may be a particularly important factor in the development of problematic sexual interests and behaviors.

Objective: This study aimed to extend previous findings by investigating the association between psychological abuse by a male caregiver and problematic sexual outcomes in a sample of adult males who had sexually offended.

Participants: Participants were 529 adult males incarcerated for sexual offenses, 21% of whom were civilly committed.

Methods: Childhood maltreatment and problematic sexual outcomes were assessed using the Multidimensional Assessment of Sex and Aggression, a contingency-based inventory that assesses domains related to sexual aggression. Hierarchical regressions were calculated examining the association between childhood abuse types and sexual outcomes.

Results: Childhood sexual abuse was associated with child sexual (β = .247, p < .001) and other paraphilic interests (β = .189, p < .001). Male caregiver psychological abuse also emerged as marginally associated with child sexual interest (β = .100, p = .059), even after controlling for other abuse types.

Conclusions: These results partially replicate recent findings in a juvenile sample and challenge conventional developmental theories of sexual offending, by suggesting that male caregiver psychological abuse may play a role in the etiology of child sexual interest among males who have sexually offended. This study also suggests a possible gender symmetry effect moderating the developmental consequences of abuse.
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http://dx.doi.org/10.1016/j.chiabu.2019.104097DOI Listing
October 2019