Human single-neuron activity is modulated by intracranial theta burst stimulation of the basolateral amygdala
- Interdepartmental Program in Neuroscience, University of Utah, United States
- Department of Neurosurgery, University of Utah, United States
- Department of Psychology, University of Utah, United States
- Department of Neurology, University of Utah, United States
- Department of Neurosurgery, Brigham and Women’s Hospital, United States
- Department of Psychology, Emory University, United States
- Department of Radiology, Washington University School of Medicine, United States
- Department of Neurology, Washington University School of Medicine, United States
- Department of Neurological Surgery, Washington University School of Medicine, United States
- National Center for Adaptive Neurotechnologies, United States
Figures
Figure 1 with 3 supplements
Microelectrode locations, unit counts, and experimental design.
(A) Behnke Fried-style macro/micro depth electrode (left) and microelectrode bundle locations projected in MNI space (right). (B) The proportion of units recorded from each brain area (left) and the proportion of units that met the criteria for inclusion in analyses (average pre-trial baseline firing rate ≥0.1 Hz) (right). (C) Counts of total (gray) and included (colored) units within each region. (D) Intracranial recording and stimulation took place in the context of a two-phase (encoding, retrieval) visual recognition memory task. A series of neutral valence images were shown (3 s), half of which were followed by direct electrical stimulation (1 s). Retrieval memory was tested during a self-paced task ~24 hr later. (E) Simulated theta burst stimulation trace (left) and individual stimulation pulse (right); charge-balanced, bipolar, biphasic rectangular pulses were delivered over a 1 s period. HIP = hippocampus (coral), OFC = orbitofrontal cortex (yellow), AMY = amygdala (blue), ACC = anterior cingulate cortex (purple).
Figure 1—figure supplement 1
Anatomical location of stimulated electrodes.
A coronal slice from the T1-weighted MRI scan is shown for each patient who participated in the study (n=16). Electrode contacts within the same plane of the image are shown with blue circles, and the bipolar pair of stimulated contacts within the basolateral amygdala is highlighted in red.
Figure 1—figure supplement 2
Unit quality metrics.
(A) Number of units detected per implanted microelectrode bundle. (B) Mean firing rate (Hz) across recording session. (C) Percent of interspike intervals <3 ms. (D) Interspike interval coefficient of variation. (E) Mean presence ratio of firing within units (1 s bins). (F) Signal-to-noise ratio of unit waveform peak. (G) Mean signal-to-noise ratio across the entire unit waveform. (H) Representative example of stereotyped, high-amplitude stimulation-artifact waveform; non-physiological waveforms were excluded from analysis.
Figure 1—figure supplement 3
Characterization of units based on laterality relative to stimulation.
(A) Unit counts on the contralateral (Contra) or ipsilateral (Ipsi) side of stimulation. (B) Unit counts separated by laterality and region. (C) Stacked histograms of Euclidean distance between microelectrode bundle location and stimulation contacts, separated by laterality (bin size = 5 mm).
Figure 2 with 1 supplement
Example raster plots depicting heterogeneous responses to stimulation.
(A) Representative example of modulation during stimulation. The high-pass-filtered, trial-averaged LFP from the corresponding microwire is shown (top) above the spike raster for an example unit located in the hippocampus (middle); the gray shaded region depicts the duration of stimulation with onset at t=0. The average firing rate across trials was estimated by convolving the binned spike counts (100 ms bins) with a Gaussian kernel (bottom). (B) The difference in the number of spikes in the 1 s peri-stimulation epochs for each trial is shown (top). We subsequently performed a Wilcoxon signed-rank test on the during- and post-stimulation spike counts for each trial vs. the pre-trial baseline and compared the empirical test statistic against a null distribution generated by shuffling the epoch labels 1000 times (bottom); the gray-shaded region represents the distribution containing 95% of observed values. (C) Some units (left, left-middle) exhibited increased firing rates, whereas others (right-middle, right) had their firing suppressed. The temporal dynamics of the firing rate modulation (e.g. onset, duration) were highly variable across units. The averaged waveform for each of the visualized units is shown below its corresponding peri-stimulation raster plot (WFs = waveforms); the shaded region represents standard deviation across waveforms.
Figure 2—figure supplement 1
Control analyses for the detection of modulated units.
The same permutation-based analyses reported in the manuscript were repeated under different control conditions. The percent of units (total n=203) that met the firing rate threshold for inclusion (pink), the percent of included units modulated in the stim condition (purple), and the percent of included units modulated in the no-stim condition are shown. (A) The threshold for inclusion of units was varied from 0 to 3 Hz (0.1 step size); the black dashed line represents the ≥0.1 Hz threshold used in the manuscript. (B) To control for the possibility that nonphysiological stimulation artifacts may preclude the detection of temporally adjacent spiking, we removed segments of data beginning at the onset of each burst of pulses (0–60 ms, 5 ms step size). Identical temporal windows were removed from the corresponding pre- and post-stimulation epochs to mitigate effects resulting solely from summation over different epoch sizes (reduced spike counts with shorter windows). (C) Visualization of the predicted probability of detecting modulation across synthetic neurons with variable firing rates and modulation effect sizes; FR = firing rate.
Figure 3 with 4 supplements
Characterization of modulation in neuronal firing rate.
(A) Percent of modulated units observed across trials separated by stim (purple) vs. no-stim conditions (orange). (B) Percent of modulated units as a function of recording region. (C) Comparison of baseline firing rate in units separated by condition (stim vs. no-stim) and outcome (NS = not significant, Mod = modulated). (D) Venn diagram depicting the shared and independent proportions of units modulated by image onset (Image) and the two experimental conditions (stim vs. no-stim). (E) Scatterplot of pre-stimulation firing rate relative to the firing rate during the two contrast windows (during, post) for the stim (left) and no-stim (right) conditions. Modulated units are highlighted in purple (stim) or orange (no-stim), whereas units without a significant change are shown in gray. (F) Temporal dynamics of pseudo-population coactivity within each condition, represented by the first three principal components of the trial-averaged firing rates. The gray-shaded region depicts the duration of stimulation with onset at t=0. Images were presented on screen for 3 s, with onset at t = –3. * p<0.05, *** p<0.001, NS = not significant.
Figure 3—figure supplement 1
Analysis of modulation in spiking rhythmicity.
(A) Representative autocorrelograms (ACG) for a single neuron. The pairwise differences in spike timing were computed for each trial and epoch (bin size = 5 ms, max lag = 250 ms), then smoothed with a Gaussian kernel. The peak in the normalized ACG across trials was computed for each epoch. (B) Kernel density estimate of the peak ACG lag, separated by epoch. (C) The peak ACG lags were split by whether the neuron was modulated (Mod) or unaffected by stimulation (NS = not significant) for each of the two contrasts: pre- vs. during-stim (left) and pre- vs. post-stim (right).
Figure 3—figure supplement 2
Sub-analysis of stimulation parameters used across experiments.
Comparison of the proportion of stimulation-modulated units across sessions with 1 mA (n=23) vs. 0.5 mA (n=7). (B) Comparison of the proportion of stimulation-modulated units across sessions testing distinct pulse frequencies: 33 Hz vs. 80 Hz (n=1) and 50 Hz vs. 80 Hz (n=6). The values above individual bars represent the number of sessions using that stimulation parameter. NS = not significant.
Figure 3—figure supplement 3
Analysis of pseudo-population activity within regions, separated by laterality relative to stimulation.
Pseudo-population activity was characterized within each region via a linear dimensionality reduction on the trial-averaged firing rates. The temporal dynamics of each region’s first three principal components are shown for (A) units ipsilateral to stimulation and (B) units contralateral to stimulation. HIP = hippocampus (coral), OFC = orbitofrontal cortex (yellow), AMY = amygdala (blue), ACC = anterior cingulate cortex (purple).
Figure 3—figure supplement 4
Analysis of multiunit activity (MUA) response to stimulation.
(A) Example trace of MUA in one channel during a single stimulation trial. Threshold crossings are highlighted with a pink dot overlaid on the MUA signal with a corresponding hash below. (B) The percentage of channels with significantly modulated MUA, separated by the direction of effect. (C) The percentage of channels with significantly modulated MUA, separated by direction effect and region. Inc (red; post > pre) vs. Dec (blue; post < pre). HIP = hippocampus, OFC = orbitofrontal cortex, AMY = amygdala, ACC = anterior cingulate cortex. *** p<0.001, NS = not significant.
Figure 4
Separation of presumed excitatory and inhibitory neurons by waveform morphology.
(A) Two metrics were calculated using the averaged waveforms for each detected unit: the valley-to-peak width (VP) and peak half-width (PHW). (B) Scatterplot of the relationship between VP and PHW; note that units with identical metrics are overlaid. Using k-means clustering, we identified two distinct response clusters, representing presumed excitatory (E, blue) and inhibitory (I, red) neurons. The units from which the example waveforms were taken are outlined in black. Probability distributions for each metric are shown along the axes. (C) Total number of units within each cluster, separated by region. (D) Comparison of baseline firing rates, separated by cluster. (E) Percent of modulated units in each cluster. *p<0.05, NS = not significant.
Figure 5 with 1 supplement
Summary of behavioral performance during memory task.
(A) Memory performance for each session is quantified using d’ (left); gray lines connect d’ scores across conditions for an individual session. Boxplot of the observed difference in d’ scores across conditions (right). (B) Hit rate (percent of old images correctly recognized) and false alarm rate (percent of new images incorrectly labeled as old) across conditions. (C) Change in recognition memory performance was split into two categories using a d’ difference threshold of ±0.5: responder (positive or negative; Δd’, pink) and non-responder (~d’, gray). Individual d’ scores are shown (left) with points colored by outcome category; dotted lines demarcate category boundaries, and the gray-shaded region represents negligible change. The number of sessions within each outcome category (middle) and the proportion of modulated units as a function of outcome category, separated by region (right). NS = not significant.
Figure 5—figure supplement 1
The effect of stimulation proximity to white matter and distance to recorded neurons.
(A) Kernel density estimate of the Euclidean distance from stimulation contacts to nearest WM structure (in mm); hash marks represent individual observations. (B) The change in memory performance (Δd’) was linearly regressed onto the distance from the stimulated contacts to white matter.
Additional files
-
MDAR checklist
- https://cdn.elifesciences.org/articles/106481/elife-106481-mdarchecklist1-v1.pdf
-
Supplementary file 1
Patient demographics and clinical characteristics.
- https://cdn.elifesciences.org/articles/106481/elife-106481-supp1-v1.docx
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Human single-neuron activity is modulated by intracranial theta burst stimulation of the basolateral amygdala
eLife 14:RP106481.
https://doi.org/10.7554/eLife.106481.3
