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Mackey, S.

Publications and source records attributed to Mackey, S..

7 recordsLinked to original sources

Intracranial electrophysiology reveals distinct neural representations of nociception and salience in the human brain

Neuroimaging studies have shown close overlap between neural representations of nociceptive stimuli and non-nociceptive, salient stimuli (such as low-probability sounds), leading to the proposal that nociception and salience share a common neural substrate in the human brain. Here we use high-resolution intracranial recordings from 13 neurosurgical patients (2,018 total electrodes) to show that neural representations of nociception and salience are anatomically and functionally distinct in the human brain. 77% of 107 electrodes that encoded nociceptive stimuli did not encode low-probability sounds ("nociceptive representations"), whereas 23% encoded both nociceptive and low-probability sounds ("salience representations"). Nociceptive representations were distinct from salience representations in terms of anatomical prevalence (posterior insula, inferior parietal, and perirolandic cortex vs. anterior insula, thalamus, and inferior frontal gyrus), timing (nociception preceded salience by 120 ms on a trial-by-trial basis), and function (intracranial electrical stimulation was more likely to cause sensory experience when applied near nociceptive representations, as compared to salience representations). These results provide strong evidence that nociception and salience have distinct neural substrates in the human brain, and that selective measurement of these distinct processes may help understand patient-to-patient variability in chronic pain and develop personalized brain stimulation treatments.

neuroscience↗

Functional disruption of vgsc reveals haplosufficiency with implications for insecticide resistance and genetic control in Anopheles gambiae

Pyrethroid insecticides on bednets have been the mainstay of malaria control since the millennium by killing mosquitoes. The target of these pyrethroids is the voltage-gated sodium channel (VGSC). Resistance mutations at the pyrethroid binding site (L995F/S) have spread widely, but functional tools to dissect vgsc itself have lagged behind the population-genetic surveillance data. Manipulation of vgsc via knockout or functional mutation would be a vital step towards understanding its contribution to insecticide resistance, as well as exploring its utility as a genetic control target. Here we generate and characterise two CRISPR-edited An. gambiae lines: an exonic knockout (vgscKO) and an intronic CRISPR-mediated cassette exchange intermediate (vgscInt) sited near SNPs linked to L995F. Both insertions are viable and fertile in heterozygosity but homozygous lethal, demonstrating that vgsc is haplosufficient and therefore the locus represents a viable target for population suppression genetic control strategies. These insertions can also be used as balancers for studying vgsc mutations without the confounding effects of wild type alleles. We investigate the insecticide resistance phenotype of vgscKO and demonstrate that knocking out one copy of vgsc produces reduced susceptibility to deltamethrin and DDT at sub-discriminating doses, with implications for vgsc-mediated mechanisms of insecticide resistance.

genetics↗

CREST: A Cortical Resting-State EEG Spatial Transformer for Chronic Pain Inference

Chronic pain mechanisms are complex, spanning multiple brain regions and networks. We ask whether resting brain activity carries a readout of that state. From a few minutes of resting-state electroencephalography (EEG), we generate a spectrogram to represent how each region of the cortex oscillates across frequency and time and pass it through CREST (Cortical Resting-state EEG Spatial Transformer): a frozen image-recognition network that reads each region as an image--here, a spectrogram--paired with a graph model that weighs the 56 cortical regions together to classify chronic-pain status. Across 125 people (74 with chronic pain, 51 healthy controls), evaluated through a leave-one-subject-out cross-validation, CREST separates the two groups with an area under the receiver operating characteristic curve (AUROC) = 0.782 (permutation p < 0.005). Control experiments implicate each persons individual alpha rhythm. Clinical relevanceA resting-state EEG readout of chronic MSK pain could clarify pathophysiology and inform treatment.

neuroscience↗

Opioid- and NMDA-receptor-dependent neural plasticity mediates long-term analgesia from motor cortical stimulation

Exogenous opioids that activate -opioid receptors (MORs) in nociceptive circuits mediate transient pain relief lasting minutes to hours but have more limited utility for treating chronic pain. By comparison, electrical or magnetic stimulation of the motor cortex can induce pain relief lasting weeks, for which the underlying mechanisms have remained unclear. Here we report an unconventional role for endogenous opioidergic signaling in the rapid induction of long-lasting analgesia from motor cortical stimulation, which triggers opioid-peptide-dependent neural plasticity in the rostral ventromedial medulla (RVM), a key node in the brains descending pain control pathways. To dissect the circuit and cellular bases for these effects, we created a miniaturized, millimeter-sized device allowing focal, non-invasive transcranial magnetic stimulation (TMS) of the mouse motor cortex. In mice with chronic neuropathic pain, reflexive and affective pain behaviors diminished for 1-2 weeks after one session of TMS treatment. Chemogenetic and optogenetic manipulations showed that motor cortical layer 5 pyramidal neurons with axonal projections to the RVM mediated TMS-induced pain relief. High-density electrophysiological recordings revealed that TMS treatment shifted the balance of RVM activity between pain-ON and pain-OFF neurons to a state promoting greater suppression of pain. Genetic and neuropharmacological manipulations revealed that NMDA-receptor-dependent signaling and MOR activation by endogenous opioid peptides in the RVM jointly mediate the long-lasting analgesia induced by a transient bout of TMS. Strikingly, enkephalinase inhibition in the RVM during TMS treatment enhanced the amplitude and duration of analgesia, showing that transiently boosting endogenous opioidergic signaling during TMS increases analgesia-conferring plasticity. In accord, re-analyses of data from human subjects with chronic pain support the idea that opioid administration amplifies analgesia from motor cortical TMS. Overall, our results showcase miniaturized TMS devices as versatile tools for basic and translational neuroscience and detail a hybrid, long-range neural network and NMDA- and opioid-receptor-dependent plasticity mechanism for durable pain relief. These findings point the way to mechanistically grounded, synergistic neurostimulation and drug therapies for brain diseases and disorders that jointly target neural circuit and molecular signaling pathways.

neuroscience↗

Differential encoding of noxious heat and self-reported pain along corticospinal networks: a simultaneous spinal cord-brain fMRI study

Chronic pain poses a substantial public health burden. Elucidating how the healthy central nervous system (CNS) differentially encodes objective stimulus intensity and subjective experiences of pain perception may offer key insights into the central mechanisms contributing to chronic pain. Functional MRI (fMRI) combined with controlled noxious stimulation provides a powerful means to explore neural representations of nociception and pain perception. Here, we applied noxious heat at three intensities (46 {degrees}C, 47 {degrees}C, 48 {degrees}C, 8 trials each randomized) to the right forearm of 28 healthy women during simultaneous spinal cord-brain fMRI to investigate how distributed corticospinal activity and connectivity encode stimulus intensity and subjective pain. Activity increased with stimulus temperature across regions involved in pain processing--including somatosensory, motor, prefrontal, insular, and subcortical areas--as well as in the ipsilateral dorsal and ventral spinal cord. Spinal- brain functional connectivity was observed between the right dorsal horn and pain-related brain regions such as primary and secondary somatosensory cortex, insula, anterior cingulate cortex, thalamus, and periaqueductal gray, and was positively associated with individual pain ratings. Using representational similarity analysis (RSA), we found that multivoxel activation patterns in the brain and spinal cord, as well as corticospinal connectivity patterns, reliably tracked stimulus temperature, while only subsets of cortical regions (e.g., insula, sensorimotor, and frontal cortices) encoded subjective pain. Notably, spinal cord representations were primarily organized by stimulus temperature rather than perceived pain intensity. These findings demonstrate that simultaneous spinal cord-brain fMRI combined with multivariate modeling can identify sensory and perceptual components of nociceptive processing across the neuroaxis. Such approaches advance mechanistic understanding of pain and may inform the development of CNS-based biomarkers for chronic pain assessment and intervention.

neuroscience↗

Mapping Hand Function with Simultaneous Brain-Spinal Cord Functional MRI

INTRODUCTIONHand motor control depends on intricate brain-spinal cord interactions that regulate muscle activity. Hand function can be disrupted by injury to the brain, spinal cord, and peripheral nerves leading to weakness and impaired coordination. Functional MRI (fMRI) can map motor-related neural activity and potentially characterize the mechanisms underlying hand weakness and diminished coordination. Although brain motor control has been extensively studied, spinal cord mechanisms remain less explored. Here we use simultaneous brain-spinal cord fMRI to map neural activity related to hand strength and dexterity across the central nervous system using force matching and finger tapping tasks. This study pioneers the use of simultaneous brain-spinal cord fMRI to comprehensively map hand function, offering novel insights into coordinated motor processing across the central nervous system. METHODSWe performed simultaneous brain-spinal cord fMRI in 28 right-handed healthy volunteers (age: 40.0 {+/-} 13.8 years, 14 females, 14 males) using a 3T GE SIGNA Premier scanner equipped with a 21-channel head-neck coil. Participants performed a force-matching task at 10%, 20%, and 30% of maximum voluntary contraction using a hand dynamometer. For the finger tapping task, participants completed button-presses at 1 Hz with a 5-button response pad for three task levels: single-digit response with the second digit only (low), single-digit response with all digits in a sequential order (medium), single-digit response with all digits in a random order (high). Visual cues and feedback were provided during the tasks. Brain and spinal cord images were processed separately using FSL and the Spinal Cord Toolbox, with motion correction, physiological noise filtering, and spatial normalization to standard templates. Subject level activity maps were generated and entered into group level analyses to explore both activations and deactivations. For the brain, we used a mixed effect design with a voxelwise threshold of Z score > 3.10 and cluster threshold of p < 0.05. For the spinal cord, we used a fixed effect design with a voxelwise threshold of Z score > 1.64 and cluster threshold of p < 0.05. Region of interest (ROI) analyses were conducted to examine localized changes in activation across task levels RESULTSBoth tasks elicited activation in motor and sensory regions of the brain and spinal cord, with graded responses in the left primary motor (M1), left primary sensory (S1) cortex, and right spinal cord gray matter across task levels. Deactivation of the right M1 and S1 was also present for both tasks. Deactivation of the left spinal cord gray matter was present in the high task level of the force matching task. The ROI analysis findings complemented the group level activity maps. DISCUSSIONOur study provides a detailed map of brain-spinal cord interactions in hand function, revealing graded neural activation and inhibition patterns across motor and sensory regions. Interhemispheric inhibition, reflected in right M1 deactivation, likely restricts extraneous motor output during unilateral tasks. For force matching, the deactivation of the left ventral and dorsal horns of the spinal cord, provides the first evidence that the inhibition of motor areas during a unilateral motor task extends to the spinal cord. Whether this inhibition results from direct descending modulation from the brain or interneuronal inhibition in the cord remains to be interrogated. These findings expand our understanding of central motor control mechanisms and could inform rehabilitation strategies for individuals with motor impairments. CONCLUSIONSOur simultaneous brain-spinal cord fMRI approach provides novel insights into the neural coordination of hand function, enhancing our understanding of motor control and its modulation. This approach may offer a foundation for studying motor dysfunction in conditions such as stroke, spinal cord injury, and neurodegenerative diseases.

neuroscience↗

EPISeg: Automated segmentation of the spinal cord on echo planar images using open-access multi-center data

Functional magnetic resonance imaging (fMRI) of the spinal cord is relevant for studying sensation, movement, and autonomic function. Preprocessing of spinal cord fMRI data involves segmentation of the spinal cord on gradient-echo echo planar imaging (EPI) images. Current automated segmentation methods do not work well on these data, due to the low spatial resolution, susceptibility artifacts causing distortions and signal drop-out, ghosting, and motion-related artifacts. Consequently, this segmentation task demands a considerable amount of manual effort which takes time and is prone to user bias. In this work, we (i) gathered a multi-center dataset of spinal cord gradient-echo EPI with ground-truth segmentations and shared it on OpenNeuro https://openneuro.org/datasets/ds005143/versions/1.3.0, and (ii) developed a deep learning-based model, EPISeg, for the automatic segmentation of the spinal cord on gradient-echo EPI data. We observe a significant improvement in terms of segmentation quality compared to other available spinal cord segmentation models. Our model is resilient to different acquisition protocols as well as commonly observed artifacts in fMRI data. The training code is available at https://github.com/sct-pipeline/fmri-segmentation/, and the model has been integrated into the Spinal Cord Toolbox as a command-line tool.

neuroscience↗