Assessing effective connectivity in epileptogenic networks: a model-based simulation approach

Different connectivity configurations were simulated using epileptogenic and non epileptogenic neuronal populations. Connectivity between them was measured using Partial Directed Coherence and Directed Transfer Function. The results were satisfactory and in some cases of clinical utility. The methodology that was used is discussed in comparison with previous works.Fil: Jacobacci, Florencia. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Sapir, Martín. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Collavini, Santiago. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Blenkmann, Alejandro Omar. Universidad Favaloro. Facultad de Ingeniería y Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentin

Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates

Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20?30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6?24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.Fil: Princich, Juan Pablo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Wassermann, Demian. Harvard Medical School; Estados Unidos de América;Fil: Latini, Facundo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Oddo, Silvia Andrea. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; ArgentinaFil: Seifer, Gustavo. Gobierno de la Ciudad de Buenos Aires. Hospital General de Agudos; ArgentinaFil: Kochen, Sara Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurcs. ; Argentin

Direct brain recordings reveal continuous encoding of structure in random stimuli

The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.Fil: Fuhrer, Julian. University of Oslo; NoruegaFil: Kyrre, Glette. University of Oslo; NoruegaFil: Ivanovic, Jugoslav. University of Oslo; NoruegaFil: Gunnar Larsson, Pål. University of Oslo; NoruegaFil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino UnidoFil: Kochen, Sara Silvia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; ArgentinaFil: Knight, Robert T.. University of California at Berkeley; Estados UnidosFil: Tørresen, Jim. University of Oslo; NoruegaFil: Solbakk, Anne Kristin. University of Oslo; Noruega. Helgeland Hospital; NoruegaFil: Endestad, Tor. University of Oslo; Noruega. Helgeland Hospital; NoruegaFil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Oslo; Norueg

Auditory deviance detection in the human insula

Supporting digital material and scripts Auditory deviance detection in the human insula: An intracranial EEG study doi: https://doi.org/10.1101/48730

Modeling intracranial electrodes

We have simulated several scenarios where intracranial EEG electrodes are implanted in an average brain. Files contain the position of electrodes over the cortex (ECoG grids) or inside the brain tissue (SEEG depth electrodes). Several locations over the cortex (57), rotations, array sizes (from 8 to 256 electrodes), and inter-electrode distances (3, 5, and 10 mm) have been simulated. Approximately 3300 grid and 850 depth implantation scenarios were simulated. Additionally, more than 50000CT artefacts produced by these electrodes were also simulated, using 12 different noise levels. We also simulated overlapping grids

Altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex

Data proving altered hierarchical auditory predictive processing after lesions to the orbitofrontal cortex. Auditory local-global paradigm experimental scripts and task stimuli, custom analysis code, processed scalp EEG data recording