Canonical Response Parameterization: Quantifying the structure of responses to single-pulse intracranial electrical brain stimulation

The effect of common parameters of bipolar stimulation on brain evoked potentials

OBJECTIVE

To identify optimal bipolar stimulation parameters for robust generation of brain evoked potentials (BEPs), namely the interelectrode distance (IED) and the intensity of stimulation (IS), in cortical and axonal stimulation.

METHODS

In 15 patients who underwent awake surgery for brain tumor removal, BEPs were elicited at different values of IED and IS, respectively: 5 mm-5 mA, 5 mm-10 mA, and 10 mm-10 mA. The number of BEPs elicited by stimulation, as well as the delays and amplitudes of the N1 waves were compared between the different groups of stimulation parameters and according to the stimulated brain structure (cortical vs. axonal).

RESULTS

The amplitudes of N1 increased with the intensity of bipolar stimulation, either in cortical or axonal stimulation, while N1 peak delays were not affected by the stimulation parameters. Furthermore, axonal stimulation produced more N1s than cortical stimulation, with lower latencies.

CONCLUSIONS

Understanding the relationship between stimulation parameters and BEP is of utmost importance to determine whether the generated N1 waves accurately reflect the underlying structural anatomy. Other factors, such as stimulation frequency or pulse width and shape, may also play a role and warrant further investigation.

SIGNIFICANCE

This study represents the first step in describing the influence of common bipolar stimulation parameters on robustness of BEPs by examining the impact of IED and IS on the N1 wave.

ER-detect: a pipeline for robust detection of early evoked responses in BIDS-iEEG electrical stimulation data

Human brain connectivity can be measured in different ways. Intracranial EEG (iEEG) measurements during single pulse electrical stimulation provide a unique way to assess the spread of electrical information with millisecond precision. To provide a robust workflow to process these cortico-cortical evoked potential (CCEP) data and detect early evoked responses in a fully automated and reproducible fashion, we developed Early Response (ER)-detect. ER-detect is an open-source Python package and Docker application to preprocess BIDS structured iEEG data and detect early evoked CCEP responses. ER-detect can use three response detection methods, which were validated against 14-manually annotated CCEP datasets from two different sites by four independent raters. Results showed that ER-detect's automated detection performed on par with the inter-rater reliability (Cohen's Kappa of ~0.6). Moreover, ER-detect was optimized for processing large CCEP datasets, to be used in conjunction with other connectomic investigations. ER-detect provides a highly efficient standardized workflow such that iEEG-BIDS data can be processed in a consistent manner and enhance the reproducibility of CCEP based connectivity results.

Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System

Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the "limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave." This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis.SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer's disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the "limbic HAP-wave." The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.

An orexigenic subnetwork within the human hippocampus

Only recently have more specific circuit-probing techniques become available to inform previous reports implicating the rodent hippocampus in orexigenic appetitive processing1-4. This function has been reported to be mediated at least in part by lateral hypothalamic inputs, including those involving orexigenic lateral hypothalamic neuropeptides, such as melanin-concentrating hormone5,6. This circuit, however, remains elusive in humans. Here we combine tractography, intracranial electrophysiology, cortico-subcortical evoked potentials, and brain-clearing 3D histology to identify an orexigenic circuit involving the lateral hypothalamus and converging in a hippocampal subregion. We found that low-frequency power is modulated by sweet-fat food cues, and this modulation was specific to the dorsolateral hippocampus. Structural and functional analyses of this circuit in a human cohort exhibiting dysregulated eating behaviour revealed connectivity that was inversely related to body mass index. Collectively, this multimodal approach describes an orexigenic subnetwork within the human hippocampus implicated in obesity and related eating disorders.