Advancing methods to image and interpret neural activity in humans on fine temporal-spatial scales is critical to understanding how the brain works in health and disease. Magneto-/Electroencephalography (M/EEG) combined with structural MRI provides reliable recordings of cortical activity with millisecond precision. Recordings from subcortical structures, such as thalamus, have been limited due to low signal amplitudes and inherent difficulty in source localization. Further, our understanding of the generation of the macroscopic electrical currents producing these signals from cellular events is lacking. We will integrate M/EEG, computational modeling, and invasive electrophysiological recordings in human patients to optimize M/EEG inverse solvers to localize distributed thalamocortical (TC) sources and to interpret the underlying cellular events. To optimize our methods we will employ two paradigms known to robustly activate distinct thalamic and cortical sources in the sensorimotor system, including thalamus, SI, MI, SII: (1) median nerve (MN) evoked responses, &(2) motor evoked tremor activity in Essential Tremor (ET) patients. Our M/EEG inverse methods will take advantage of the fact low frequency (LF <100Hz) and high frequency (HF 100-800hz) evoked responses are disjoint in space and time and will combine this characteristic with precise anatomical head modeling constraints to localize concurrent cortical and thalamic activities. To interpret the cellular level events underlying the signals, we will expand a previously developed neural model of TC circuitry that accurately simulates LF SI tactile evoked source waveforms up to 125ms post-stimulus based on sequences of synaptic drive from thalamus and cortex. This model will be expanded to interpret the origin of observed LF and HF activity in the distributed TC network. Results will be validated and informed with invasive electrophysiological recording in ET patients undergoing deep brain stimulation (DBS) surgery.
AIM 1 : ADVANCE M/EEG TIME-FREQUENCY BASED INVERSE SOLVERS TO LOCALIZE TC EVOKED LF &HF ACTIVITY. We will establish that our advanced inverse methods can reliably localize sources in the thalamus, SI, MI, and SII, during (a) MN stimulation in healthy subjects &(b) MN and motor evoked tremor activity in ET patient, and that the responses from these sources are reflected in a sequence of LF and HF activities.
AIM 2 : INTERPRET CELLULAR LEVEL ORIGIN OF LF &HF SOURCE ACTIVITY WITH NEURAL MODELING. We will expand an existing computational model of a SI circuit that accurately simulates tactile evoked M/EEG measured source activity to an interconnected thalamic, SI, MI, and SII network. We will test the hypotheses that synaptic interactions between the networks can reproduce the sequences of activity measured Aim 1 and that the HF activity is created by burst firing, while the LF events represent initial synaptically driven slow dendriti processes and the envelope of the HF bursts.
AIM 3 : VALIDATE INVERSE METHODS AND MODEL PREDICTIONS WITH INVASIVE TC RECORDINGS. We will record LFP and spiking activity from the thalamus, and ECoG from the sensorimotor cortex, of ET patients undergoing DBS surgery during (a) MN stimulation &(b) motor evoked tremor activity. We will use the data to validate Aim 1 source localizations and Aim 2 model predictions. Data will also refine model development and hypotheses. Our integrated approach will provide novel insight into distributed TC activity that is not possible wih one method alone. We will develop free open source softwares that advance the ability to non-invasively (1) study TC interactions in humans with M/EEG &(2) interpret the cellular level origin of the activity. While our investigation is focused on the sensorimotor system, our methods will be broadly applicable to study activity in other brain networks, including deep structures like basal ganglia, and in many experimental paradigms. We will initiate a High School Neuroscience Outreach Program to educate Boston area High School students on human imaging and mathematical modeling in neuroscience. We will target local districts experiencing large budget cuts with elimination in extra-curricular enrichment. Our program will add a complimentary component to the math and biology curriculums.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
1R01MH106174-01
Application #
8837196
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Glanzman, Dennis L
Project Start
Project End
Budget Start
Budget End
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Brown University
Department
Neurosciences
Type
Schools of Medicine
DUNS #
City
Providence
State
RI
Country
United States
Zip Code
02912