基本信息
浏览量:25
职业迁徙
个人简介
In past research, I have studied visual processing, attention, and visual skill learning, using neurophysiological techniques and iontophoresis in Macaque monkeys, as well as visual processing and working memory using MEG in human participants. In all my research, a crucial underlying question is how communication works in the brain, and how it underlies our capacity to perceive, attend, learn, and create memories. A crucial insight is that the information we process is selective: As the brain is constantly bombarded with input, a selection mechanism (attention) will limit processing to behaviourally relevant stimuli, which tend also to be the ones held (and kept) in memory. Moreover, exposure to the same stimuli in a specific behavioural context can induce learning (e.g., increase expertise in selecting the relevant stimulus or stimulus feature). To understand neuronal communication in the various paradigms I have used various forms of spectral analysis based on current synchronization theories. However, I came to the insight that current theories based on spectral coherence tend to ignore the importance of frequency dynamics and differences. With others in our group, I therefore started to develop a different approach which has frequency dynamics as a core element. As our new theory of synchronization (referred to as Dynamic Frequency Matching, DFM) matured, I became interested in testing it in human patients undergoing invasive recordings in the context of clinical treatment. In the summer of 2016, the Dean of the Faculty of Psychology and Neuroscience (FPN) and Heads of the Departments of Neurology and Neurophysiology at the University hospital (MUMC) invited me to start a new cooperation with the aim of acquiring human invasive electrophysiology during cognitive tasks. This collaboration is also central to a new cross faculty institute, the Maastricht Centre of Integrative Neuroscience. We hope to generate both fundamental research and to improve the care of the patient group we work with. Specifically, the description of synchronization at a more mechanistic level can help to describe pathological forms of neural communication, which may also help in devising treatment by deep brain stimulation, or targeting surgical intervention. In this respect, we have access to patients with one of two recording modalities: Patients with intractable epilepsy have electrocorticography (EC0G) recording from the surface of the cortex for several days before respective surgery. Patients with a variety of conditions (epilepsy, Parkinson’s, Tourette’s etc) are implanted for microelectrode recordings during and shortly after implantation of deep brain stimulation (DBS) electrodes. Both patient groups offer opportunities to gather unique data. To coordinate our collaboration, I have organized meetings between FPN and UMC members to exchange ideas and plans. I have joined the team of supervisors for Mario Archila Melendez’s PhD thesis, which will be the first project to produce publications on this data. I have furthermore, passed the Good Clinical Practice course and sought to widen our collaborators in the Netherlands and beyond by meeting with researchers from Tilburg, Groningen and Frankfurt. All of these actions form the basis and context for the present proposal. In summary, in the next 5 to 10 years, I plan to test DFM in a range of experiments, using complementary work using invasive recordings in patients and MEG research in human participants.
研究兴趣
论文共 84 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
European journal of neuroscience/EJN European journal of neuroscience (2024)
Hani Kushlaf,Drago Bratkovic,Barry J. Byrne,Kristl G. Claeys, Jordi Díaz‐Manera,Mazen M. Dimachkie,Priya S. Kishnani,Mark Roberts,Antonio Toscano, J. Castelli, Fred Holdbrook, Sheela Sitaraman Das, Yasmine Wasfi, Benedikt G. H. Schoser,Tahseen Mozaffar
Neurologyno. 17_supplement_1 (2024)
加载更多
作者统计
#Papers: 83
#Citation: 2752
H-Index: 23
G-Index: 52
Sociability: 6
Diversity: 3
Activity: 29
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn