About this Research Topic
In the last 20 years, the field of epilepsy surgery has experienced remarkable changes. These have mainly been due to the development of techniques related to advances in both non-invasive and invasive monitoring data. The goal of these new methods has been to better define the cortical areas responsible for the primary organization of epileptiform activity. Advances related to computational data analysis and more sophisticated methods of robotic-guided electrode implantations are also reshaping the field and paving the future for more efficient and safer surgical interventions.
By taking advantage of new radiological and computational innovations, modern methods of implantation of depth electrodes, including with the use of assistant robotic devices, are now available. The use of robots in stereotactic procedures has shown several advantages, including the potential to be more precise and accurate. Additionally, this has allowed multiple trajectory options without the need for numerous time consuming frame coordinate adjustments.
The described innovations clearly translate into reproducible outcomes with smaller margins of error, fewer complications during surgery, as well as reduced surgical time. Similarly, new computational methods allow for a more refined analysis of epileptic and non-epileptic networks, providing a unique perspective for Epileptologists and Neuroscientists.
This Research Topic has the goal of exemplifying these changes by highlighting advances in the field of epilepsy surgery and, in particular, advancements related to robotic applied techniques and computational neuroscience. Therefore, this Research Topic welcomes articles related to the following topics:
• Historical perspective and evolution of robotic neurosurgery;
• Robotic surgery in epilepsy;
• The use of robotic DBS and RNS and LITT for medically refractory epilepsy;
• Signal processing and computational analyses of SEEG data from SEEG implanted patients;
• Speech mapping in SEEG implanted patients.
Topic Editor Prof. Jorge Alvaro Gonzalez-Martinez has received a consulting grant from Zimmer Biomet. Prof.
Stéphan Chabardès has also worked as a consultant for Zimmer Biomet. Prof. Chauvel has declared no competing interests with regards to the Research Topic subject.
By taking advantage of new radiological and computational innovations, modern methods of implantation of depth electrodes, including with the use of assistant robotic devices, are now available. The use of robots in stereotactic procedures has shown several advantages, including the potential to be more precise and accurate. Additionally, this has allowed multiple trajectory options without the need for numerous time consuming frame coordinate adjustments.
The described innovations clearly translate into reproducible outcomes with smaller margins of error, fewer complications during surgery, as well as reduced surgical time. Similarly, new computational methods allow for a more refined analysis of epileptic and non-epileptic networks, providing a unique perspective for Epileptologists and Neuroscientists.
This Research Topic has the goal of exemplifying these changes by highlighting advances in the field of epilepsy surgery and, in particular, advancements related to robotic applied techniques and computational neuroscience. Therefore, this Research Topic welcomes articles related to the following topics:
• Historical perspective and evolution of robotic neurosurgery;
• Robotic surgery in epilepsy;
• The use of robotic DBS and RNS and LITT for medically refractory epilepsy;
• Signal processing and computational analyses of SEEG data from SEEG implanted patients;
• Speech mapping in SEEG implanted patients.
Topic Editor Prof. Jorge Alvaro Gonzalez-Martinez has received a consulting grant from Zimmer Biomet. Prof.
Stéphan Chabardès has also worked as a consultant for Zimmer Biomet. Prof. Chauvel has declared no competing interests with regards to the Research Topic subject.
Keywords: Epilepsy Surgery, Stereo-Electroencephalography, Robotics, Computational Neuroscience, Language
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