Discrete Modules and Mesoscale Functional Circuits for Thermal Nociception within Primate S1 Cortex

fMRI, LFP, and anatomical evidence for hierarchical nociceptive routing pathway between somatosensory and insular cortices

The directional organization of multiple nociceptive regions, particularly within obscure operculoinsular areas, underlying multidimensional pain processing remains elusive. This study aims to establish the fundamental organization between somatosensory and insular cortices in routing nociceptive information. By employing an integrated multimodal approach of high-field fMRI, intracranial electrophysiology, and transsynaptic viral tracing in rats, we observed a hierarchically organized connection of S1/S2 → posterior insula → anterior insula in routing nociceptive information. The directional nociceptive pathway determined by early fMRI responses was consistent with that examined by early evoked LFP, intrinsic effective connectivity, and anatomical projection, suggesting fMRI could provide a valuable facility to discern directional neural circuits in animals and humans non-invasively. Moreover, our knowledge of the nociceptive hierarchical organization of somatosensory and insular cortices and the interface role of the posterior insula may have implications for the development of targeted pain therapies.

Detection and characterization of resting state functional networks in squirrel monkey brain

Resting-state fMRI based on analyzing BOLD signals is widely used to derive functional networks in the brain and how they alter during disease or injury conditions. Resting-state networks can also be used to study brain functional connectomes across species, which provides insights into brain evolution. The squirrel monkey (SM) is a non-human primate (NHP) that is widely used as a preclinical model for experimental manipulations to understand the organization and functioning of the brain. We derived resting-state networks from the whole brain of anesthetized SMs using Independent Component Analysis of BOLD acquisitions. We detected 15 anatomically constrained resting-state networks localized in the cortical and subcortical regions as well as in the white-matter. Networks encompassing visual, somatosensory, executive control, sensorimotor, salience and default mode regions, and subcortical networks including the Hippocampus-Amygdala, thalamus, basal-ganglia and brainstem region correspond well with previously detected networks in humans and NHPs. The connectivity pattern between the networks also agrees well with previously reported seed-based resting-state connectivity of SM brain. This study demonstrates that SMs share remarkable homologous network organization with humans and other NHPs, thereby providing strong support for their suitability as a translational animal model for research and additional insight into brain evolution across species.

The regulations on cortical activation and functional connectivity of the dorsolateral prefrontal cortex-primary somatosensory cortex elicited by acupuncture with reinforcing-reducing manipulation

Introduction

Traditional acupuncture with reinforcing-reducing manipulation is essential for clinical effectiveness, whereas the underlying central mechanism of it remains unknown. This study with multiple-channels functional near-infrared spectroscopy (fNIRS) aims to explore cerebral-response modes during acupuncture with reinforcing-reducing manipulations.

Materials and methods

Functional near-infrared spectroscopy data were recorded from 35 healthy participants during the lifting-thrusting reinforcing manipulation, the lifting-thrusting reducing manipulation, and the even reinforcing-reducing manipulation with lifting-thrusting. The general linear model based (GLM) cortical activation analysis and the functional connectivity (FC) based on region of interest (ROI) analysis were combined to be conducted.

Results

In comparison with the baseline, the results showed that three acupuncture with reinforcing-reducing manipulations similarly induced the hemodynamic responses in the bilateral dorsolateral prefrontal cortex (DLPFC) and increased FC between the DLPFC and primary somatosensory cortex (S1). Specifically, the even reinforcing-reducing manipulation deactivated the bilateral DLPFC, the frontopolar area (FP), the right primary motor cortex (M1), the bilateral S1, and the bilateral secondary somatosensory cortex (S2); The reducing manipulation deactivated the bilateral DLPFC; The reinforcing manipulation activated the bilateral DLPFC, the left S1, and the right S2. The between-group comparisons indicated that the reinforcing-reducing manipulation induced opposite hemodynamic responses in the bilateral DLPFC and the left S1 and exhibited different FC patterns in the left DLPFC-S1, within the right DLPFC, and between the left S1 and the left orbitofrontal cortex (OFC).

Conclusion

These findings verified the feasibility of fNIRS for investigating cerebral functional activities of acupuncture manipulations, suggesting that the regulations on the DLPFC-S1 cortex may be the potential central mechanism for the realization of acupuncture with reinforcing-reducing manipulation's effect.

Clinical trial registration

ClinicalTrials.gov, identifier, ChiCTR2100051893.

Graph theory analysis identified two hubs that connect sensorimotor and cognitive and cortical and subcortical nociceptive networks in the non-human primate

Pain perception involves multiple brain regions and networks. Understanding how these brain networks work together is fundamental for appreciating network-wise changes reported in patients with chronic pain disorders. Parcellating pain related networks and understanding their causal relationships is the first step to understand how painful information is processed, integrated, and modulated, and it requires direct manipulation of specific brain regions. Nonhuman primates (NHP) offer an ideal model system to achieve these goals because cortical and subcortical regions in the NHP brain are established based on a variety of different types of data collected in a way that is not feasible or, at least, extremely difficult in humans (i.e., histology data, tract-tracing, intracerebral recordings). In addition, different methodological techniques can also help characterize and further understand these brain cortical and subcortical regions over the course of development. Here we used a heat nociceptive stimulation that is proven to elicit activity of nociceptive neurons in the cortex to refine and parcellate the whole brain nociceptive functional networks, to identify key network hubs, and to characterize network-wise temporal dynamic signatures using high-resolution fMRI. We first functionally localized 24 cortical and subcortical regions that responded to heat nociceptive stimuli (somatosensory area 1/2, area 3a/3b, S2, posterior insula (pIns), anterior insula, area 7b, posterior parietal cortex, anterior cingulate cortex (ACC), prefrontal cortex, caudate, and mediodorsal (MD) and ventral posterior lateral (VPL) thalamic nuclei) and used them as seeds in resting state fMRI (rsfMRI) data analysis. We applied both hierarchical clustering and graph-theory analyses of the pairwise rsfMRI correlation metrics and identified five cortical and one subcortical sub-networks: strong resting state functional connectivity (rsFC) between ACC and prefrontal regions, parietal cortex and area 7b, S2 and posterior insula, areas 3a/3b and 1/2 within the S1 cortex, and thalamic MD and caudate nuclei. The rsFC strengths between cortical areas within each subnetwork were significantly stronger than those between subcortical regions. Regions within each sub-network also exhibited highly correlated temporal dynamics at rest, but the overall dynamic patterns varied drastically across sub-networks. Graph-theory analysis identified the MD nucleus as a hub that connects subcortical and cortical nociceptive sub-networks. The S2-pIns connection joins the sensory and affective/cognitive sub-networks.

Pain modalities in the body and brain: Current knowledge and future perspectives

Development and validation of pain biomarkers has become a major issue in pain research. Recent advances in multimodal data acquisition have allowed researchers to gather multivariate and multilevel whole-body measurements in patients with pain conditions, and data analysis techniques such as machine learning have led to novel findings in neural biomarkers for pain. Most studies have focused on the development of a biomarker to predict the severity of pain with high precision and high specificity, however, a similar approach to discriminate different modalities of pain is lacking. Identification of more accurate and specific pain biomarkers will require an in-depth understanding of the modality specificity of pain. In this review, we summarize early and recent findings on the modality specificity of pain in the brain, with a focus on distinct neural activity patterns between chronic clinical and acute experimental pain, direct, social, and vicarious pain, and somatic and visceral pain. We also suggest future directions to improve our current strategy of pain management using our knowledge of modality-specific aspects of pain.

A thermal nociceptive patch in the S2 cortex of nonhuman primates: a combined functional magnetic resonance imaging and electrophysiology study

ABSTRACT

Human functional magnetic resonance imaging (fMRI) and behavioral studies have established the roles of cortical areas along the Sylvian fissure in sensing subjective pain. Yet, little is known about how sensory aspects of painful information are represented and processed by neurons in these regions and how their electrophysiological activities are related to fMRI signals. The current study aims to partially address this critical knowledge gap by performing fMRI-guided microelectrode mapping and recording studies in the homologous region of the parietal operculum in squirrel monkeys under light anesthesia. In each animal studied (n = 8), we detected mesoscale mini-networks for heat nociception in cortical regions around the lateral sulcus. Within the network, we discovered a ∼1.5 × 1.5-mm2-sized cortical patch that solely contained heat nociceptive neurons that aligned with the heat fMRI activation locus. These neurons responded slowly to thermal (heat and cold) nociceptive stimuli exclusively, continued firing for several seconds after the succession of stimulation, and exhibited multidigit receptive fields and high spontaneous firing rates. Similar to the fMRI responses, increasing temperatures in the nociceptive range led to a nonlinear increase in firing rates. The finding of a clustering of heat nociceptive neurons provides novel insights into the unique functional organization of thermal nociception in the S2 subregion of the primate brain. With fMRI, it supports the existence of a modality-preferred heat nociceptive patch that is spatially separated and intermingled with touch patches containing neurons with comparable receptive fields and the presence of functionally distinct mini-networks in primate opercular cortex.

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Functional localizers are invaluable as they can help define regions of interest, provide cross-study comparisons, and most importantly, allow for the aggregation and meta-analyses of data across studies and laboratories. To achieve these goals within the non-human primate (NHP) imaging community, there is a pressing need for the use of standardized and validated localizers that can be readily implemented across different groups. The goal of this paper is to provide an overview of the value of localizer protocols to imaging research and we describe a number of commonly used or novel localizers within NHPs, and keys to implement them across studies. As has been shown with the aggregation of resting-state imaging data in the original PRIME-DE submissions, we believe that the field is ready to apply the same initiative for task-based functional localizers in NHP imaging. By coming together to collect large datasets across research group, implementing the same functional localizers, and sharing the localizers and data via PRIME-DE, it is now possible to fully test their robustness, selectivity and specificity. To do this, we reviewed a number of common localizers and we created a repository of well-established localizer that are easily accessible and implemented through the PRIME-RE platform.

Neocortical circuits in pain and pain relief

The sensory, associative and limbic neocortical structures play a critical role in shaping incoming noxious inputs to generate variable pain perceptions. Technological advances in tracing circuitry and interrogation of pathways and complex behaviours are now yielding critical knowledge of neocortical circuits, cellular contributions and causal relationships between pain perception and its abnormalities in chronic pain. Emerging insights into neocortical pain processing suggest the existence of neocortical causality and specificity for pain at the level of subdomains, circuits and cellular entities and the activity patterns they encode. These mechanisms provide opportunities for therapeutic intervention for improved pain management.

A nociresponsive specific area of human somatosensory cortex within BA3a: BA3c?

It is well recognized that in primates, including humans, noxious body stimulation evokes a neural response in the posterior bank of the central sulcus, in Brodmann cytoarchitectonic subdivisions 3b and 1 of the primary somatosensory cortex. This response is associated with the 1st/sharp pain and contributes to sensory discriminative aspects of pain perception and spatial localization of the noxious stimulus. However, neurophysiological studies in New World monkeys predict that in humans noxious stimulation also evokes a separate neural response-mediated by C-afferent drive and associated with the 2nd/burning pain-in the depth of the central sulcus in Brodmann area 3a (BA3a) at the transition between the somatosensory and motor cortices. To evoke such a response, it is necessary to use multi-second duration noxious stimulation, rather than brief laser pulses. Given the limited human pain-imaging literature on cortical responses induced by C-nociceptive input specifically within BA3a, here we used high spatial resolution 7T fMRI to study the response to thermonoxious skin stimulation. We observed the predicted response of BA3a in the depth of the central sulcus in five human volunteers. Review of the available evidence suggests that the nociresponsive region in the depth of the central sulcus is a structurally and functionally distinct cortical area that should not be confused with proprioceptive BA3a. It is most likely engaged in interoception and control of the autonomic nervous system, and contributes to the sympathetic response to noxious stimulation, arguably the most intolerable aspect of pain experience. Ablation of this region has been shown to reduce pain sensibility and might offer an effective means of ameliorating some pathological pain conditions.

Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data

Background

Multivoxel pattern analysis has provided new evidence on somatotopic representation in the human brain. However, the effects of stimulus modality (e.g., penetrating needle versus non-penetrating touch) and level of classification (e.g., multiclass versus binary classification) on patterns of brain activity encoding spatial information of body parts have not yet been studied. We hypothesized that performance of brain-based prediction models may vary across the types of stimuli, and neural patterns of voxels in the SI and parietal cortex would significantly contribute to the prediction of stimulated locations.

Objective

We aimed to (1) test whether brain responses to tactile stimuli could distinguish among stimulated locations on the body surface, (2) investigate whether the stimulus modality and number of classes affect classification performance, and (3) localize brain regions encoding the spatial information of somatosensory stimuli.

Methods

Fifteen healthy participants completed two functional magnetic resonance imaging (MRI) scans and were stimulated via the insertion of acupuncture needles or by non-invasive touch stimuli (5.46-sized von Frey filament). Participants received the stimuli at four different locations on the upper and lower limbs (two sites each) for 5 min while blood-oxygen-level-dependent activity (BOLD) was measured using 3-Tesla MRI. We performed multivariate pattern analysis (MVPA) using parameter estimate images of each trial for each participant and the support vector classifier (SVC) function, and the prediction accuracy and other MVPA outcomes were evaluated using stratified five-fold cross validation. We estimated the significance of the classification accuracy using a permutation test with randomly labeled training data (n = 10,000). Searchlight analysis was conducted to identify brain regions associated with significantly higher accuracy compared to predictions based on chance as obtained from a random classifier.

Results

For the four-class classification (classifying four stimulated points on the body), SVC analysis of whole-brain beta values in response to acupuncture stimulation was able to discriminate among stimulated locations (mean accuracy, 0.31; q < 0.01). The searchlight analysis found that values related to the right primary somatosensory cortex (SI) and intraparietal sulcus were significantly more accurate than those due to chance (p < 0.01). On the other hand, the same classifier did not predict stimulated locations accurately for touch stimulation (mean accuracy, 0.25; q = 0.66). For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q < 0.001) and touch stimulation (mean accuracy, 0.60; q < 0.01). Searchlight analysis revealed that predictions based on the right SI, primary motor cortex (MI), paracentral gyrus, and superior frontal gyrus were significantly more accurate compared to predictions based on chance (p < 0.05).

Conclusion

Our findings suggest that the SI, as well as the MI, intraparietal sulcus, paracentral gyrus, and superior frontal gyrus, is responsible for the somatotopic representation of body parts stimulated by tactile stimuli. The MVPA approach for identifying neural patterns encoding spatial information of somatosensory stimuli may be affected by the stimulus type (penetrating needle versus non-invasive touch) and the number of classes (classification of four small points on the body versus two large body parts). Future studies with larger samples will identify stimulus-specific neural patterns representing stimulated locations, independent of subjective tactile perception and emotional responses. Identification of distinct neural patterns of body surfaces will help in improving neural biomarkers for pain and other sensory percepts in the future.