Modulation of Human Spatial-temporal Memory by Deep Brain Stimulation
Poster No:
5
Submission Type:
Abstract Submission
Authors:
Yan Li1, Tao Yu2, Tong Li1, Xiaojing Peng1, Ying Gao2, Nikolai Axmacher3, Gui Xue1
Institutions:
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, Beijing, 2Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, Beijing, 3Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr Univ, Bochum, North Rhine-Westphalia
First Author:
Yan Li
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Co-Author(s):
Tao Yu
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University
Beijing, Beijing
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University
Beijing, Beijing
Tong Li
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Xiaojing Peng
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Ying Gao
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University
Beijing, Beijing
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University
Beijing, Beijing
Nikolai Axmacher
Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr Univ
Bochum, North Rhine-Westphalia
Department of Neuropsychology, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr Univ
Bochum, North Rhine-Westphalia
Gui Xue
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University
Beijing, Beijing
Introduction:
As a neuromodulation technique, deep brain stimulation is often used for ameliorating cognitive disabilities, such as improving memory impairment. Existing evidence showed that direct stimulation resulted in different effects in memory performance. Some reported that stimulation impaired memory performance (e.g., Jacobs et al., 2016), while others reported that stimulation improved memory (e.g., Suthana et al., 2012). Therefore, in the present study, we intend to find out different memory performance induced by selective stimulation site and stimulation frequency.
Methods:
Participants
Twenty-eight medically refractory frontal or temporal epilepsy patients (mean age = 24.03y, sd = 8.36y, 10 female) who were implanted with SEEG depth electrodes were collected in Xuanwu hospital.
Experimental procedure & Stimulation protocol
A white square moved in the 4*4 grid, and the participants were instructed to learn the sequence and the location of the moving square (Fig1A). All participants learned 3 locations in each color background and they were self-adapted to memorize (1) two to three color backgrounds and (2) repeat four to six times based on their practice performance. After the 10s distractor task, participants were asked to replicate the sequence in each color grid. There were three blocks of spatial temporal sequences in each session.
During the encoding period, participants either received stimulation in the hippocampus or no stimulation (Stim-off condition). Stimulation was delivered in the continuous biphasic rectangular pulse at 0.5 mA with 90μs pulse width at 5 Hz or 50 Hz, using RISHENA stimulator (RISHENA, China). Intracranial EEG data was recorded using amplifiers from Brain Products for the whole task periods, with the sampling rate of 2500 Hz.
Electrode localization
Location for each contact was identified by co-registering the post-implanted CT scans and the pre-implanted MRI image, and we segmented individual's structural T1 image using FreeSurfer and obtained the anatomical label for each contact.
White matter categorization
All stimulation sites were re-categorized as either located in the gray matter or near white matter, following the procedure from Mohan et al (2020). We calculated the midpoints of the anode and cathode electrodes, and a sphere with a radius of 4 mm was constructed centered on this midpoint. Then, we estimated the number of white matter vertices located in the sphere. Finally, we grouped the stimulation sites as gray matter or near white matter by taking the median of the white matter vertices' number. Here, the median number of white matter vertices located inside the sphere is 165.
Twenty-eight medically refractory frontal or temporal epilepsy patients (mean age = 24.03y, sd = 8.36y, 10 female) who were implanted with SEEG depth electrodes were collected in Xuanwu hospital.
Experimental procedure & Stimulation protocol
A white square moved in the 4*4 grid, and the participants were instructed to learn the sequence and the location of the moving square (Fig1A). All participants learned 3 locations in each color background and they were self-adapted to memorize (1) two to three color backgrounds and (2) repeat four to six times based on their practice performance. After the 10s distractor task, participants were asked to replicate the sequence in each color grid. There were three blocks of spatial temporal sequences in each session.
During the encoding period, participants either received stimulation in the hippocampus or no stimulation (Stim-off condition). Stimulation was delivered in the continuous biphasic rectangular pulse at 0.5 mA with 90μs pulse width at 5 Hz or 50 Hz, using RISHENA stimulator (RISHENA, China). Intracranial EEG data was recorded using amplifiers from Brain Products for the whole task periods, with the sampling rate of 2500 Hz.
Electrode localization
Location for each contact was identified by co-registering the post-implanted CT scans and the pre-implanted MRI image, and we segmented individual's structural T1 image using FreeSurfer and obtained the anatomical label for each contact.
White matter categorization
All stimulation sites were re-categorized as either located in the gray matter or near white matter, following the procedure from Mohan et al (2020). We calculated the midpoints of the anode and cathode electrodes, and a sphere with a radius of 4 mm was constructed centered on this midpoint. Then, we estimated the number of white matter vertices located in the sphere. Finally, we grouped the stimulation sites as gray matter or near white matter by taking the median of the white matter vertices' number. Here, the median number of white matter vertices located inside the sphere is 165.
Results:
We implemented the generalized linear mixed-effects model in order to investigate whether characteristics of stimulation site and frequency would affect stimulation effect (Fig1B). We defined independent variables as (1) the corresponding location of the stimulation site and seizure onset zone (SOZ), (2) white matter proximity and (3) stimulation frequency. Here, we found a marginal significant three-way interactive effect (χ2=5.59, p=.061). We conducted the simple effect analysis and found that if the stimulation site is located in the SOZ, stimulation would not significantly change memory performance. However, if the stimulation site was located outside the SOZ, 5 Hz stimulation in gray matter would reduce the probability of recall (z=-3.72, p<.001), whereas stimulation near white matter would improve memory performance (z=2.36, p=.037).
Conclusions:
In the present study, we found that the selection of stimulation site and frequency contributed to the stimulation effect. If we stimulate in the SOZ, the stimulation shows no effect on the memory performance. Yet, if we stimulate outside the SOZ, low frequency stimulation in gray matter will impair memory performance, while high frequency stimulation near white matter enhances memory performance.
Brain Stimulation:
Deep Brain Stimulation 1
Learning and Memory:
Learning and Memory Other 2
Keywords:
Epilepsy
Memory
White Matter
Other - Deep brain stimulation
1|2Indicates the priority used for review
Provide references using author date format
Mohan, et al. (2020). The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity. Brain Stimulation. Vol. 3, no. 5, pp. 1183-1195.
Suthana, et al. (2012). Memory enhancement and deep-brain stimulation of the entorhinal area. The New England Journal of Medicine, Vol. 366, no. 6, pp. 502-510.