The role that choice of model plays in predictions for epilepsy surgery

This is the final version. Available on open access from Nature Research via the DOI in this recordMathematical modelling has been widely used to predict the effects of perturbations to brain networks. An important example is epilepsy surgery, where the perturbation in question is the removal of brain tissue in order to render the patient free of seizures. Different dynamical models have been proposed to represent transitions to ictal states in this context. However, our choice of which mathematical model to use to address this question relies on making assumptions regarding the mechanism that defines the transition from background to the seizure state. Since these mechanisms are unknown, it is important to understand how predictions from alternative dynamical descriptions compare. Herein we evaluate to what extent three different dynamical models provide consistent predictions for the effect of removing nodes from networks. We show that for small, directed, connected networks the three considered models provide consistent predictions. For larger networks, predictions are shown to be less consistent. However consistency is higher in networks that have sufficiently large differences in ictogenicity between nodes. We further demonstrate that heterogeneity in ictogenicity across nodes correlates with variability in the number of connections for each node.Engineering and Physical Sciences Research Council (EPSRC)Medical Research Council (MRC)Epilepsy Research UKWellcome Trus

The Role of Excitability and Network Structure in the Emergence of Focal and Generalized Seizures

This is the final version. Available on open access from Frontiers Media via the DOI in this recordData Availability Statement: The code and synthetic networks generated are available upon request.Epileptic seizures are generally classified as either focal or generalized. It had been traditionally assumed that focal seizures imply localized brain abnormalities, whereas generalized seizures involve widespread brain pathologies. However, recent evidence suggests that large-scale brain networks are involved in the generation of focal seizures, and generalized seizures can originate in localized brain regions. Herein we study how network structure and tissue heterogeneities underpin the emergence of focal and widespread seizure dynamics. Mathematical modeling of seizure emergence in brain networks enables the clarification of the characteristics responsible for focal and generalized seizures. We consider neural mass network dynamics of seizure generation in exemplar synthetic networks and we measure the variance in ictogenicity across the network. Ictogenicity is defined as the involvement of network nodes in seizure activity, and its variance is used to quantify whether seizure patterns are focal or widespread across the network. We address both the influence of network structure and different excitability distributions across the network on the ictogenic variance. We find that this variance depends on both network structure and excitability distribution. High variance, i.e., localized seizure activity, is observed in networks highly heterogeneous with regard to the distribution of connections or excitabilities. However, networks that are both heterogeneous in their structure and excitability can underlie the emergence of generalized seizures, depending on the interplay between structure and excitability. Thus, our results imply that the emergence of focal and generalized seizures is underpinned by an interplay between network structure and excitability distribution.Medical Research Council (MRC)Epilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome TrustInnovate U

Computational modelling in source space from scalp EEG to inform presurgical evaluation of epilepsy

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordObjective: The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework to interrogate scalp EEG and determine epilepsy lateralization to aid in electrode implantation. Methods: We use eLORETA to map source activities from seizure epochs recorded from scalp EEG and consider 15 regions of interest (ROIs). Functional networks are then constructed using the phase-locking value and studied using a mathematical model. By removing different ROIs from the network and simulating their impact on the network’s ability to generate seizures in silico, the framework provides predictions of epilepsy lateralization. We consider 15 individuals from the EPILEPSIAE database and study a total of 62 seizures. Results were assessed by taking into account actual intracranial implantations and surgical outcome. Results: The framework provided potentially useful information regarding epilepsy lateralization in 12 out of the 15 individuals (p=0.02, binomial test). Conclusions: Our results show promise for the use of this framework to better interrogate scalp EEG to determine epilepsy lateralization. Significance: The framework may aid clinicians in the decision process to define where to implant electrodes for intracranial monitoring.Medical Research CouncilEpilepsy Research UKEngineering and Physical Sciences Research Council (EPSRC)Wellcome TrustEngineering and Physical Sciences Research Council (EPSRC)Innovate UKEuropean Union’s Horizon 2020Alzheimer's SocietyMedical Research Counci

O discurso dos profissionais sobre a demanda e a humanização

A humanização dos serviços da atenção primária à saúde depende, em grande parte, da resolução das necessidades em saúde e da conseqüente organização da demanda. OBJETIVO: O artigo objetiva conhecer as implicações da demanda sobre a humanização das práticas de atenção primária. METODOLOGIA: Trata-se de uma pesquisa exploratória com abordagem qualitativa. O universo empírico da pesquisa foi composto por 10 trabalhadores de uma Unidade Básica de Saúde: 1 gestora, 1 médica, 1 dentista, 2 enfermeiros, 3 técnicos em enfermagem, 1 atendente da portaria e 1 encarregado do almoxarifado. A coleta de dados aconteceu em 8 reuniões de discussão focal sobre temas como política de humanização, direito à saúde, integralidade, acolhimento, subjetividade em saúde, processos de trabalho. As discussões foram gravadas e transcritas. Os dados foram trabalhados pela análise do discurso. RESULTADOS: Como resultados, apareceram três repertórios lingüísticos ligados à demanda: compreensão das necessidades em saúde; entendimento do acolhimento como triagem e aplicação de protocolo; influência do modelo biomédico na organização dos serviços. A excessiva demanda e a falta de resolubilidade estão ligadas a uma compreensão das necessidades de saúde como o simples acesso à tecnologia, e do acolhimento apenas como triagem de sintomas. Os profissionais da enfermagem reportam como uma causa da excessiva demanda o fato de que os usuários sempre querem ser atendidos pelo médico, o que pode ser explicado pela cultura da atenção criada pelo modelo biomédico no qual eles próprios se encontram quando entendem as necessidades e o acolhimento na perspectiva biomédica.Humanization of Primary Health Care Services depends mostly on the resolution of the health needs and on the consequen organization of demand. OBJECTIVE: The article searches to know the implications of demand to the humanization of Primary Health Care practices. METHODOLOGY: It is an exploratory research with qualitative approach. The empirical universe was formed by 10 professionals: 1 manager; 1 physician; 1 dentist; 2 nurses, 3 nursing technicians; 1 reception attendant; 1 stockroom commissioner. Data were collected through 8 meetings in which discussion focused on themes such as humanization policy, right to health, integrality, users' reception, subjectivity in health, work processes. The discussions have been recorded and a transcription was made. Analysis of data was done through discourse analysis. RESULTS: As results, three linguistic repertories were found linked with the demand: the understanding of health needs; the understanding of users' reception as screening and application of protocols; the influence of the biomedical model in the organization of the services. The excessive demand and the lack of resolution are linked to the understanding of heath needs simply as access to technology, and of users' reception simply as screening of symptoms. Nurses claim that excessive demand is due to users always wanting to be seen by a physician, which can be explained by the health care culture created by the biomedical model which is also adopted by professionals when they understand health needs and the users' reception in the biomedical perspective