Ishita Basu1, Madeline M Robertson2, Britni Crocker3, Noam Peled4, Kara Farnes5, Deborah I Vallejo-Lopez3, Helen Deng6, Matthew Thombs2, Clarissa Martinez-Rubio2, Jennifer J Cheng2, Eric McDonald2, Darin D Dougherty7, Emad N Eskandar2, Alik S Widge8, Angelique C Paulk9, Sydney S Cash3. 1. Nayef Al-Rodhan Laboratories, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA. 2. Nayef Al-Rodhan Laboratories, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA. 3. Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA. 4. Department of Radiology, MGH/HST Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA. 5. Nayef Al-Rodhan Laboratories, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA. 6. Nayef Al-Rodhan Laboratories, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Radiology, MGH/HST Martinos Center for Biomedical Imaging, Charlestown, MA, 02129, USA. 7. Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA. 8. Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, 02129, USA; Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02124, USA. 9. Nayef Al-Rodhan Laboratories, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA. Electronic address: apaulk@mgh.harvard.edu.
Abstract
BACKGROUND: Electrical neuromodulation via implanted electrodes is used in treating numerous neurological disorders, yet our knowledge of how different brain regions respond to varying stimulation parameters is sparse. OBJECTIVE/HYPOTHESIS: We hypothesized that the neural response to electrical stimulation is both region-specific and non-linearly related to amplitude and frequency. METHODS: We examined evoked neural responses following 400 ms trains of 10-400 Hz electrical stimulation ranging from 0.1 to 10 mA. We stimulated electrodes implanted in cingulate cortex (dorsal anterior cingulate and rostral anterior cingulate) and subcortical regions (nucleus accumbens, amygdala) of non-human primates (NHP, N = 4) and patients with intractable epilepsy (N = 15) being monitored via intracranial electrodes. Recordings were performed in prefrontal, subcortical, and temporal lobe locations. RESULTS: In subcortical regions as well as dorsal and rostral anterior cingulate cortex, response waveforms depended non-linearly on frequency (Pearson's linear correlation r < 0.39), but linearly on current (r > 0.58). These relationships between location, and input-output characteristics were similar in homologous brain regions with average Pearson's linear correlation values r > 0.75 between species and linear correlation values between participants r > 0.75 across frequency and current values per brain region. Evoked waveforms could be described by three main principal components (PCs) which allowed us to successfully predict response waveforms across individuals and across frequencies using PC strengths as functions of current and frequency using brain region specific regression models. CONCLUSIONS: These results provide a framework for creation of an atlas of input-output relationships which could be used in the principled selection of stimulation parameters per brain region.
BACKGROUND: Electrical neuromodulation via implanted electrodes is used in treating numerous neurological disorders, yet our knowledge of how different brain regions respond to varying stimulation parameters is sparse. OBJECTIVE/HYPOTHESIS: We hypothesized that the neural response to electrical stimulation is both region-specific and non-linearly related to amplitude and frequency. METHODS: We examined evoked neural responses following 400 ms trains of 10-400 Hz electrical stimulation ranging from 0.1 to 10 mA. We stimulated electrodes implanted in cingulate cortex (dorsal anterior cingulate and rostral anterior cingulate) and subcortical regions (nucleus accumbens, amygdala) of non-human primates (NHP, N = 4) and patients with intractable epilepsy (N = 15) being monitored via intracranial electrodes. Recordings were performed in prefrontal, subcortical, and temporal lobe locations. RESULTS: In subcortical regions as well as dorsal and rostral anterior cingulate cortex, response waveforms depended non-linearly on frequency (Pearson's linear correlation r < 0.39), but linearly on current (r > 0.58). These relationships between location, and input-output characteristics were similar in homologous brain regions with average Pearson's linear correlation values r > 0.75 between species and linear correlation values between participants r > 0.75 across frequency and current values per brain region. Evoked waveforms could be described by three main principal components (PCs) which allowed us to successfully predict response waveforms across individuals and across frequencies using PC strengths as functions of current and frequency using brain region specific regression models. CONCLUSIONS: These results provide a framework for creation of an atlas of input-output relationships which could be used in the principled selection of stimulation parameters per brain region.
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