The impact of epilepsy surgery on the structural connectome and its relation to outcome

BACKGROUND: Temporal lobe surgical resection brings seizure remission in up to 80% of patients, with long-term complete seizure freedom in 41%. However, it is unclear how surgery impacts on the structural white matter network, and how the network changes relate to seizure outcome. METHODS: We used white matter fibre tractography on preoperative diffusion MRI to generate a structural white matter network, and postoperative T1-weighted MRI to retrospectively infer the impact of surgical resection on this network. We then applied graph theory and machine learning to investigate the properties of change between the preoperative and predicted postoperative networks. RESULTS: Temporal lobe surgery had a modest impact on global network efficiency, despite the disruption caused. This was due to alternative shortest paths in the network leading to widespread increases in betweenness centrality post-surgery. Measurements of network change could retrospectively predict seizure outcomes with 79% accuracy and 65% specificity, which is twice as high as the empirical distribution. Fifteen connections which changed due to surgery were identified as useful for prediction of outcome, eight of which connected to the ipsilateral temporal pole. CONCLUSIONS: Our results suggest that the use of network change metrics may have clinical value for predicting seizure outcome. This approach could be used to prospectively predict outcomes given a suggested resection mask using preoperative data only

Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

Personalized medicine requires that treatments adapt to not only the patient but also changing factors within each individual. Although epilepsy is a dynamic disorder characterized by pathological fluctuations in brain state, surprisingly little is known about whether and how seizures vary in the same patient. We quantitatively compared within-patient seizure network evolutions using intracranial electroencephalographic (iEEG) recordings of over 500 seizures from 31 patients with focal epilepsy (mean 16.5 seizures per patient). In all patients, we found variability in seizure paths through the space of possible network dynamics. Seizures with similar pathways tended to occur closer together in time, and a simple model suggested that seizure pathways change on circadian and/or slower timescales in the majority of patients. These temporal relationships occurred independent of whether the patient underwent antiepileptic medication reduction. Our results suggest that various modulatory processes, operating at different timescales, shape within-patient seizure evolutions, leading to variable seizure pathways that may require tailored treatment approaches

Independent components of human brain morphology

Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex

Structural brain network abnormalities and the probability of seizure recurrence after epilepsy surgery

OBJECTIVE: We assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences. METHODS: We examined data from 51 patients with TLE who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the preoperative structural, diffusion, and postoperative structural MRI, we generated 2 networks: presurgery network and surgically spared network. Standardizing these networks with respect to controls, we determined the number of abnormal nodes before surgery and expected to be spared by surgery. We incorporated these 2 abnormality measures and 13 commonly acquired clinical data from each patient into a robust machine learning framework to estimate patient-specific chances of seizures persisting after surgery. RESULTS: Patients with more abnormal nodes had a lower chance of complete seizure freedom at 1 year and, even if seizure-free at 1 year, were more likely to relapse within 5 years. The number of abnormal nodes was greater and their locations more widespread in the surgically spared networks of patients with poor outcome than in patients with good outcome. We achieved an area under the curve of 0.84 ± 0.06 and specificity of 0.89 ± 0.09 in predicting unsuccessful seizure outcomes (International League Against Epilepsy [ILAE] 3–5) as opposed to complete seizure freedom (ILAE 1) at 1 year. Moreover, the model-predicted likelihood of seizure relapse was significantly correlated with the grade of surgical outcome at year 1 and associated with relapses up to 5 years after surgery. CONCLUSION: Node abnormality offers a personalized, noninvasive marker that can be combined with clinical data to better estimate the chances of seizure freedom at 1 year and subsequent relapse up to 5 years after ATLR. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that node abnormality predicts postsurgical seizure recurrence

Epileptogenic networks in extra temporal lobe epilepsy

\ua9 2023 Massachusetts Institute of Technology.Extra temporal lobe epilepsy (eTLE) may involve heterogenous widespread cerebral networks. We investigated the structural network of an eTLE cohort, at the postulated epileptogenic zone later surgically removed, as a network node: the resection zone (RZ). We hypothesized patients with an abnormal connection to/from the RZ to have proportionally increased abnormalities based on topological proximity to the RZ, in addition to poorer post-operative seizure outcome. Structural and diffusion MRI were collected for 22 eTLE patients pre-and post-surgery, and for 29 healthy controls. The structural connectivity of the RZ prior to surgery, measured via generalized fractional anisotropy (gFA), was compared with healthy controls. Abnormal connections were identified as those with substantially reduced gFA (z < −1.96). For patients with one or more abnormal connections to/from the RZ, connections with closer topological distance to the RZ had higher proportion of abnormalities. The minority of the seizure-free patients (3/11) had one or more abnormal connections, while most non-seizure-free patients (8/11) had abnormal connections to the RZ. Our data suggest that eTLE patients with one or more abnormal structural connections to/from the RZ had more proportional abnormal connections based on topological distance to the RZ and associated with reduced chance of seizure freedom post-surgery

Epileptogenic networks in extra temporal lobe epilepsy

Extra temporal lobe epilepsy (eTLE) may involve heterogenous widespread cerebral networks. We investigated the structural network of an eTLE cohort, at the postulated epileptogenic zone later surgically removed, as a network node: the resection zone (RZ). We hypothesized patients with an abnormal connection to/from the RZ to have proportionally increased abnormalities based on topological proximity to the RZ, in addition to poorer post-operative seizure outcome. Structural and diffusion MRI were collected for 22 eTLE patients pre-and post-surgery, and for 29 healthy controls. The structural connectivity of the RZ prior to surgery, measured via generalized fractional anisotropy (gFA), was compared with healthy controls. Abnormal connections were identified as those with substantially reduced gFA (z < −1.96). For patients with one or more abnormal connections to/from the RZ, connections with closer topological distance to the RZ had higher proportion of abnormalities. The minority of the seizure-free patients (3/11) had one or more abnormal connections, while most non-seizure-free patients (8/11) had abnormal connections to the RZ. Our data suggest that eTLE patients with one or more abnormal structural connections to/from the RZ had more proportional abnormal connections based on topological distance to the RZ and associated with reduced chance of seizure freedom post-surgery

Nuclei in Strongly Magnetised Neutron Star Crusts

We discuss the ground state properties of matter in outer and inner crusts of neutron stars under the influence of strong magnetic fields. In particular, we demonstrate the effects of Landau quantization of electrons on compositions of neutron star crusts. First we revisit the sequence of nuclei and the equation of state of the outer crust adopting the Baym, Pethick and Sutherland (BPS) model in the presence of strong magnetic fields and most recent versions of the theoretical and experimental nuclear mass tables. Next we deal with nuclei in the inner crust. Nuclei which are arranged in a lattice, are immersed in a nucleonic gas as well as a uniform background of electrons in the inner crust. The Wigner-Seitz approximation is adopted in this calculation and each lattice volume is replaced by a spherical cell. The coexistence of two phases of nuclear matter - liquid and gas, is considered in this case. We obtain the equilibrium nucleus corresponding to each baryon density by minimizing the free energy of the cell. We perform this calculation using Skyrme nucleon-nucleon interaction with different parameter sets. We find nuclei with larger mass and charge numbers in the inner crust in the presence of strong magnetic fields than those of the zero field case for all nucleon-nucleon interactions considered here. However, SLy4 interaction has dramatic effects on the proton fraction as well as masses and charges of nuclei. This may be attributed to the behaviour of symmetry energy with density in the sub-saturation density regime. Further we discuss the implications of our results to shear mode oscillations of magnetars.Comment: presented in "Exciting Physics Symposium" held in Makutsi, South Africa in November, 2011 and to be published in a book by Springer Verla

Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?

Decision support systems (DSSs) are important in decision-making environments with conflicting interests. Many DSSs developed have not been used in practice. Experts argue that these tools do not respond to real user needs and that the inclusion of stakeholders in the development process is the solution. However, it is not clear which features of participatory development of DSSs result in improved uptake and better outcomes. A review of papers, reporting on case studies where DSSs and other decision tools (information systems, software and scenario tools) were developed with elements of participation, was carried out. The cases were analysed according to a framework created as part of this research; it includes criteria to evaluate the development process and the outcomes. Relevant aspects to consider in the participatory development processes include establishing clear objectives, timing and location of the process; keeping discussions on track; favouring participation and interaction of individuals and groups; and challenging creative thinking of the tool and future scenarios. The case studies that address these issues show better outcomes; however, there is a large degree of uncertainty concerning them because developers have typically neither asked participants about their perceptions of the processes and resultant tools nor have they monitored the use and legacy of the tools over the long term.The authors would like to thank COST Action FP0804-Forest Management Decision Support Systems (FORSYS) for financing a three month Short-Term Scientific Mission (STSM) in Forest Research (Roslin, UK) in 2012, making possible this research; Spanish Ministry of Economy and Competitiveness for supporting the project Multicriteria Techniques and Participatory Decision-Making for Sustainable Management (Ref. ECO2011-27369) where the leading author is involved; and the Regional Ministry of Education, Culture and Sports (Valencia, Spain) for financing a research fellowship (Ref. ACIF/2010/248).Valls Donderis, P.; Ray, D.; Peace, A.; Stewart, A.; Lawrence, A.; Galiana, F. (2013). Participatory development of decision support systems: which features of the process lead to improved uptake and better outcomes?. Scandinavian Journal of Forest Research. 29(1):71-83. https://doi.org/10.1080/02827581.2013.837950S7183291Arnstein, S. R. (1969). A Ladder Of Citizen Participation. Journal of the American Institute of Planners, 35(4), 216-224. doi:10.1080/01944366908977225Atwell, R. C., Schulte, L. A., & Westphal, L. M. (2011). Tweak, Adapt, or Transform: Policy Scenarios in Response to Emerging Bioenergy Markets in the U.S. Corn Belt. Ecology and Society, 16(1). doi:10.5751/es-03854-160110Barac, A., Kellner, K., & De Klerk, N. (2004). Land User Participation in Developing a Computerised Decision Support System for Combating Desertification. Environmental Monitoring and Assessment, 99(1-3), 223-231. doi:10.1007/s10661-004-4022-6Bennet, A., & Bennet, D. (2008). The Decision-Making Process in a Complex Situation. Handbook on Decision Support Systems 1, 3-20. doi:10.1007/978-3-540-48713-5_1Blackstock, K. L., Kelly, G. J., & Horsey, B. L. (2007). Developing and applying a framework to evaluate participatory research for sustainability. Ecological Economics, 60(4), 726-742. doi:10.1016/j.ecolecon.2006.05.014Breuer, N. E., Cabrera, V. E., Ingram, K. T., Broad, K., & Hildebrand, P. E. (2007). AgClimate: a case study in participatory decision support system development. Climatic Change, 87(3-4), 385-403. doi:10.1007/s10584-007-9323-7Bunch, M. J., & Dudycha, D. J. (2004). Linking conceptual and simulation models of the Cooum River: collaborative development of a GIS-based DSS for environmental management. Computers, Environment and Urban Systems, 28(3), 247-264. doi:10.1016/s0198-9715(03)00021-8Byrne, E., & Sahay, S. (2007). Participatory design for social development: A South African case study on community-based health information systems. Information Technology for Development, 13(1), 71-94. doi:10.1002/itdj.20052Cain, J. ., Jinapala, K., Makin, I. ., Somaratna, P. ., Ariyaratna, B. ., & Perera, L. . (2003). Participatory decision support for agricultural management. A case study from Sri Lanka. Agricultural Systems, 76(2), 457-482. doi:10.1016/s0308-521x(02)00006-9Chakraborty, A. (2011). Enhancing the role of participatory scenario planning processes: Lessons from Reality Check exercises. Futures, 43(4), 387-399. doi:10.1016/j.futures.2011.01.004Cinderby, S., Bruin, A. de, Mbilinyi, B., Kongo, V., & Barron, J. (2011). Participatory geographic information systems for agricultural water management scenario development: A Tanzanian case study. Physics and Chemistry of the Earth, Parts A/B/C, 36(14-15), 1093-1102. doi:10.1016/j.pce.2011.07.039Drew, C. H., Nyerges, T. L., & Leschine, T. M. (2004). Promoting Transparency of Long‐Term Environmental Decisions: The Hanford Decision Mapping System Pilot Project. Risk Analysis, 24(6), 1641-1664. doi:10.1111/j.0272-4332.2004.00556.xDriedger, S. M., Kothari, A., Morrison, J., Sawada, M., Crighton, E. J., & Graham, I. D. (2007). Using participatory design to develop (public) health decision support systems through GIS. International Journal of Health Geographics, 6(1), 53. doi:10.1186/1476-072x-6-53Evers, M. (2008). An analysis of the requirements for DSS on integrated river basin management. Management of Environmental Quality: An International Journal, 19(1), 37-53. doi:10.1108/14777830810840354Iivari, N. (2011). Participatory design in OSS development: interpretive case studies in company and community OSS development contexts. Behaviour & Information Technology, 30(3), 309-323. doi:10.1080/0144929x.2010.503351Innes, J. E., & Booher, D. E. (1999). Consensus Building and Complex Adaptive Systems. Journal of the American Planning Association, 65(4), 412-423. doi:10.1080/01944369908976071Jakku, E., & Thorburn, P. J. (2010). A conceptual framework for guiding the participatory development of agricultural decision support systems. Agricultural Systems, 103(9), 675-682. doi:10.1016/j.agsy.2010.08.007Jessel, B., & Jacobs, J. (2005). Land use scenario development and stakeholder involvement as tools for watershed management within the Havel River Basin. Limnologica, 35(3), 220-233. doi:10.1016/j.limno.2005.06.006Kautz, K. (2011). Investigating the design process: participatory design in agile software development. Information Technology & People, 24(3), 217-235. doi:10.1108/09593841111158356Kowalski, K., Stagl, S., Madlener, R., & Omann, I. (2009). Sustainable energy futures: Methodological challenges in combining scenarios and participatory multi-criteria analysis. European Journal of Operational Research, 197(3), 1063-1074. doi:10.1016/j.ejor.2007.12.049Lawrence, A. (2006). ‘No Personal Motive?’ Volunteers, Biodiversity, and the False Dichotomies of Participation. Ethics, Place & Environment, 9(3), 279-298. doi:10.1080/13668790600893319Mao, J., & Song, W. (2008). Empirical study of distinct features and challenges of joint development of information systems: The case of ABC bank. Tsinghua Science and Technology, 13(3), 414-419. doi:10.1016/s1007-0214(08)70066-xMenzel, S., Nordström, E.-M., Buchecker, M., Marques, A., Saarikoski, H., & Kangas, A. (2012). Decision support systems in forest management: requirements from a participatory planning perspective. European Journal of Forest Research, 131(5), 1367-1379. doi:10.1007/s10342-012-0604-yMoote, M. A., Mcclaran, M. P., & Chickering, D. K. (1997). RESEARCH: Theory in Practice: Applying Participatory Democracy Theory to Public Land Planning. Environmental Management, 21(6), 877-889. doi:10.1007/s002679900074Peleg, M., Shachak, A., Wang, D., & Karnieli, E. (2009). Using multi-perspective methodologies to study users’ interactions with the prototype front end of a guideline-based decision support system for diabetic foot care. International Journal of Medical Informatics, 78(7), 482-493. doi:10.1016/j.ijmedinf.2009.02.008Pretty, J. N. (1995). Participatory learning for sustainable agriculture. World Development, 23(8), 1247-1263. doi:10.1016/0305-750x(95)00046-fReed MS. 2008. Stakeholder participation for environmental management: a literature review. Sustainability Research Institute, School of Earth and Environment, University of Leeds.Reed, M. S., & Dougill, A. J. (2010). Linking degradation assessment to sustainable land management: A decision support system for Kalahari pastoralists. Journal of Arid Environments, 74(1), 149-155. doi:10.1016/j.jaridenv.2009.06.016Rowe, G., & Frewer, L. J. (2000). Public Participation Methods: A Framework for Evaluation. Science, Technology, & Human Values, 25(1), 3-29. doi:10.1177/016224390002500101Schielen, R. M. J., & Gijsbers, P. J. A. (2003). DSS-large rivers: developing a DSS under changing societal requirements. Physics and Chemistry of the Earth, Parts A/B/C, 28(14-15), 635-645. doi:10.1016/s1474-7065(03)00109-8Sheppard, S. R. J., & Meitner, M. (2005). Using multi-criteria analysis and visualisation for sustainable forest management planning with stakeholder groups. Forest Ecology and Management, 207(1-2), 171-187. doi:10.1016/j.foreco.2004.10.032Thursky, K. A., & Mahemoff, M. (2007). User-centered design techniques for a computerised antibiotic decision support system in an intensive care unit. International Journal of Medical Informatics, 76(10), 760-768. doi:10.1016/j.ijmedinf.2006.07.011Webler, S. T., Thomas. (1999). Voices from the Forest: What Participants Expect of a Public Participation Process. Society & Natural Resources, 12(5), 437-453. doi:10.1080/089419299279524Van Meensel, J., Lauwers, L., Kempen, I., Dessein, J., & Van Huylenbroeck, G. (2012). Effect of a participatory approach on the successful development of agricultural decision support systems: The case of Pigs2win. Decision Support Systems, 54(1), 164-172. doi:10.1016/j.dss.2012.05.002Von Geibler, J., Kristof, K., & Bienge, K. (2010). Sustainability assessment of entire forest value chains: Integrating stakeholder perspectives and indicators in decision support tools. Ecological Modelling, 221(18), 2206-2214. doi:10.1016/j.ecolmodel.2010.03.02

Low frequency radio properties of the z>5 quasar population

Optically luminous quasars at z > 5 are important probes of super-massive black hole (SMBH) formation. With new and future radio facilities, the discovery of the brightest low-frequency radio sources in this epoch would be an important new probe of cosmic reionization through 21-cm absorption experiments. In this work, we systematically study the low-frequency radio properties of a sample of 115 known spectroscopically confirmed z > 5 quasars using the second data release of the Low Frequency Array (LOFAR) Two Metre Sky survey (LoTSS-DR2), reaching noise levels of ∼80 µJy beam−1 (at 144 MHz) over an area of ∼ 5720 deg2 . We find that 41 sources (36%) are detected in LoTSS-DR2 at > 2σ significance and we explore the evolution of their radio properties (power, spectral index, and radio loudness) as a function of redshift and rest-frame ultra-violet properties. We obtain a median spectral index of −0.29+0.10 −0.09 by stacking 93 quasars using LoTSS-DR2 and Faint Images of the Radio Sky at Twenty Centimetres (FIRST) data at 1.4 GHz, in line with observations of quasars at z < 3. We compare the radio loudness of the high-z quasar sample to a lower-z quasar sample at z ∼ 2 and find that the two radio loudness distributions are consistent with no evolution, although the low number of high-z quasars means that we cannot rule out weak evolution. Furthermore, we make a first order empirical estimate of the z = 6 quasar radio luminosity function, which is used to derive the expected number of high-z sources that will be detected in the completed LoTSS survey. This work highlights the fact that new deep radio observations can be a valuable tool in selecting high-z quasar candidates for follow-up spectroscopic observations by decreasing contamination of stellar dwarfs and reducing possible selection biases introduced by strict colour cuts