Biology subjects

Jones, S. R.

Publications and source records attributed to Jones, S. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Kappa opioid receptors regulate cocaine effects on nucleus accumbens dopamine through phosphorylation of dopamine transporter at the threonine 53 site

Chronic cocaine exposure leads to tolerance of the dopamine transporter (DAT) to cocaine and heightened kappa opioid receptor (KOR)-induced inhibition of dopamine (DA) release in the nucleus accumbens (NAc). KORs on presynaptic DA terminals inhibit DA release and modulate DAT function, but whether KOR signaling causes DAT tolerance is unknown. We demonstrate that rats self-administering cocaine escalate their intake, and the KOR antagonist norbinaltorphimine (nBNI) blunts this escalation. We employed fast-scan cyclic voltammetry (FSCV) in acute brain slices containing the NAc core from these rats and found that the cocaine exposure paradigm resulted in tolerance of the DAT to cocaine, an effect absent in animals pre-treated with nBNI. In drug-naive mice, either superfusion of the KOR agonist U50,488 or a single in vivo injection of U69,593 inhibited DA release and reduced cocaine-induced inhibition of DA reuptake, reproducing the tolerance phenotype without any drug history. We replicated this finding in the NAc of rats, and with the uptake inhibitor nomifensine in rhesus macaques, indicating conservation across rodents and non-human primates. As KOR activation results in phosphorylation of the threonine-53 site on the DAT, we tested whether this is required for the KOR-mediated DAT tolerance to cocaine. We show that a mouse line with a phosphorylation-insensitive alanine-53 mutation of the DAT has enhanced DA release and uptake. Remarkably, KOR agonism no longer mediated DAT tolerance to cocaine in these mice, demonstrating the dependence of this effect on the threonine-53 site and highlighting a KOR-driven mechanism underlying cocaine tolerance at the DAT.

neuroscience↗

bioRxiv2026

Uncovering putative neural mechanisms of neurotherapeutic impacts on EEG using the Human Neocortical Neurosolver

SHORT ABSTRACTA key barrier to developing effective drugs for disorders of the central nervous system (CNS) is understanding their impact on neural circuits. This protocol demonstrates how physics-based neural simulations can be used to interpret electrophysiological biomarkers of neurotherapeutics, providing a mechanistically grounded approach to the development of neurotherapeutics. LONG ABSTRACTElectroencephalography (EEG) and electrophysiology methods provide millisecond resolution biomarkers for central nervous system disorders and are used to assess treatment-related effects. However, lack of understanding about the neural mechanisms generating such biomarkers impedes the development of diagnostics and therapeutics based on these signals. The Human Neocortical Neurosolver (HNN) is an open-source biophysical modeling software that connects localized EEG biomarkers to their multi-scale neural generators. This protocol demonstrates a hypothesis-driven workflow using HNN to test possible neural mechanisms of neurotherapy-induced EEG biomarkers by optimizing parameters to achieve a fit between simulated and empirical current source waveforms. Corresponding multi-scale cell- and circuit-level activity can then be visualized and quantified, providing validation targets for model predictions in follow up empirical studies. An example is provided which shows how to examine the generating mechanisms of the early event-related potential (ERP) components of an auditory evoked response (P1, N1 and P2) and to assess changes following neural circuit modification due to neurotherapeutic administration. This protocol demonstration enables scientists to design simulation experiments to develop testable predictions on how EEG biomarkers reflect neural circuit mechanisms of example therapeutics. A similar protocol can be applied to study disease mechanisms or other therapies.

neuroscience↗

bioRxiv2025

Neurophysiology of mismatch negativity generation: a biophysical modeling study

The mismatch negativity, or MMN, is a ubiquitous evoked brain response elicited by any discriminable change of an otherwise regular stimulus sequence. Despite its potential clinical relevance - the MMN is known to be affected by brain state, lesions, and neurologic/psychiatric disorders - and a growing body of animal work, the underlying neurophysiology of the MMN is not well understood. This hinders translation of circuit-level animal findings and mitigates the utility of the MMN as a neurologic/psychiatric biomarker. Here, we used biophysical modeling to examine the neurophysiological basis of the MMN as measured in a canonical auditory oddball paradigm with frequency deviants (i.e., tones whose frequency was shifted slightly with respect to standard tones). The response to standards was successfully modeled by a typical feedforward-followed-by-feedback input sequence. The response to deviants required additional, prolonged input to supragranular layers, consistent with input from the non-lemniscal thalamus. This additional input resulted in downward-going pyramidal-neuron currents in both layer 2/3 (via indirect somatic inhibition) and, critically, layer 5 (via direct apical excitation), which together generated the MMN. The results suggest that current circuit-level models of MMN generation derived from animal models are incomplete, and that further work is required to characterize the underlying neurophysiology of the MMN. SIGNIFICANCE STATEMENTThe mismatch negativity, or MMN, is a change-related brain response and one of the most widely studied brain responses in neuroscience. However, despite its prevalence and potential utility as a biomarker for neurological and psychiatric disorders, its underlying neurophysiology is not well understood. We combined MEG with biophysical modeling to better understand the cells, circuits, and cortical laminae that contribute to deviance processing and the MMN in humans.

neuroscience↗

bioRxiv2025

Kappa opioid receptors delay sucrose self-administration by modulating dopamine ramps before operant responding

Chronic consumption of drugs of abuse increases sensitivity of the dynorphin/kappa opioid receptor (KOR) stress system, which reduces striatal dopamine signaling and promotes drug taking. However, there is mixed evidence on how KOR-modulation of dopamine affects operant behavior in the absence of addiction. To address this gap, we injected dLight1.2 in the nucleus accumbens of male and female C57BL/6J mice and trained them to self-administer sucrose. Mice were injected with the KOR agonist U50,488H, with or without the KOR antagonist aticaprant, prior to each session. U50,488H did not affect dopamine responses during the lever press and did not alter total presses or consumption. The primary effects of KOR activation were to delay initiation of lever pressing, and to diminish the rapid ramp-up in dopamine seen before lever presses. The first lever press of each session was preceded by the largest dopamine ramp; however, ramp size did not correlate with latency under any condition. We further tested whether KOR-modulation of dopamine ramps affects behavior throughout the session. We found that the total amount of dopamine activity 10 seconds before the lever press predicted when the next lever press would occur, specifically after U50,488H injection. When the phasic peaks were subtracted from this to quantify a slower dopamine ramp, time to the next lever press could be predicted and this effect was strongest after U50,488H injection. As U50,488H reduces basal dopamine signaling, we propose that dopamine ramps prior to behavior have a larger signal-to-noise ratio during KOR activation. This relatively greater increase in dopamine from baseline could increase the salience of the decision to perform reward-associated actions, which may play a role in habitual behaviors like drug taking.

neuroscience↗

bioRxiv2025

Characterization of a novel mouse model of Dopamine Transporter Deficiency Syndrome and pharmacological therapeutic strategies

The dopamine transporter (DAT) is an essential protein in the maintenance of dopamine homeostasis in the brain. Thus, single amino acid changes in the gene that encodes for DAT can be sufficient to induce disease, such as Dopamine Transporter Deficiency Syndrome (DTDS). DTDS-associated variants are posited to cause DAT protein misfolding, retention in the endoplasmic reticulum, and a consequent depletion or loss of DAT at the cell surface. In turn, proper dopaminergic regulation is lost. Current treatments for DTDS are largely ineffective, and improved therapeutic options are greatly needed. To this end, we have created a novel mouse model of DTDS harboring the A313V knock-in DAT variant, a proxy for the DTDS-causing A314V variant in humans. We show that the A313V knock-in DAT mice are hyperactive, have increased striatal tissue content of dopamine and its metabolites homovanillic acid (HVA) and DOPAC, and impaired dopamine uptake. We demonstrate that FDA approved compounds alpha-methyl-para-tyrosine ([a]MPT) and amphetamine (AMPH) ameliorate hyperactivity in this mouse model. Moreover, [a]MPT may be a disease-modifying treatment by addressing the hyperdopaminergic tone underlying this hyperactivity. In contrast, noribogaine, a pharmacological chaperone for DAT, is unable to rescue DAT expression. Taken together, these findings show that the A313V knock-in DAT variant mice recapitulate several defining phenotypes seen in patients with DTDS, and provide evidence for two novel treatments for the disease.

pharmacology and toxicology↗

bioRxiv2025

Fiber photometry analysis for spontaneous dopamine signals: The z-scored data are not the data

Fluorescent sensors have revolutionized the measurement of molecules in the brain, and the dLight dopamine sensor has been used extensively to examine reward- and cue-evoked dopamine release, but only recently has the field turned its attention to spontaneous release events. Analysis of spontaneous events typically requires evaluation of hundreds of events over minutes to hours, and the most common method of analysis, z-scoring, was not designed for this purpose. Here, we compare the accuracy and reliability of three different analysis methods to identify pharmacologically induced changes in dopamine release and uptake in freely moving C57BL/6J mice. The D1-like receptor antagonist SCH23390 was used to prevent dLight sensors from interacting with dopamine in the extracellular space, while cocaine was used to inhibit uptake and raclopride to increase release of dopamine in the nucleus accumbens. We examined peak-to-peak frequency, peak amplitude, and width, the time spent above an established cutoff. The three methods were 1) the widely-used "Z-Score Method", which automatically smooths baseline drift and normalizes recordings using signal-to-noise ratios, 2) a "Manual Method", in which local baselines were adjusted manually and individual cutoffs were determined for each subject, and 3) the "Prominence Method" that combines z-scoring with prominence assessment to tag individual peaks, then returns to the preprocessed data for kinetic analysis. First, SCH23390 drastically reduced the number of signals detected as expected, but only when the Manual Method was used. Z-scoring failed to identify any changes, due to its amplification of noise when signals were diminished. Cocaine increased signal width as expected using the Manual and Prominence Methods, but not the Z-Score Method. Finally, raclopride- induced increases in amplitude were correctly identified by the Manual and Prominence Methods. The Z-Score Method failed to identify any of the changes in dopamine release and uptake kinetics. Thus, analysis of spontaneous dopamine signals requires assessment of the %{Delta}F/F values, ideally using the Manual Method, and the use of z- scoring is not appropriate. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=137 SRC="FIGDIR/small/639080v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1687207org.highwire.dtl.DTLVardef@165fa1org.highwire.dtl.DTLVardef@e06800org.highwire.dtl.DTLVardef@cbf31e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2025

Ensemble priming via competitive inhibition: local mechanisms of sensory context storage and deviance detection in the neocortical column

The process by which neocortical neurons and circuits amplify their response to an unexpected change in stimulus, typically referred to as deviance detection (DD), has traditionally been thought to be the product of specialized cell types and/or routing from distinct brain areas. Here, we explore a different theory, whereby DD emerges intrinsically from local network-level interactions within a neocortical column. We propose that deviance-driven neural dynamics are generated by ensembles of excitatory and inhibitory neurons that have a fundamental inhibitory connectivity motif: competitive inhibition between reciprocally connected neural representations under modulation from feed-forward selective (dis)inhibition. Implementing this motif in two computational models with different levels of biophysical abstraction, we were able to simulate a variety of phenomena pertaining to the experimentally observed shifts in neural tuning during DD across neurons, time, and stimulus history. We further tested hypotheses related to our theory and examined the robustness of emergent phenomena consistent with prior experimental observations. Our results show that ensemble priming via competitive inhibition under modulation from selective (dis)inhibition can serve as a local mechanism for encoding short-term stimulus memory, enabling deviance-driven shifts in stimulus representation. This work establishes a novel theoretical paradigm that resolves previously confounding aspects of predictive sensory processing in Neocortex, and we provide a number of corollary predictions that can be tested in future in vivo studies.

neuroscience↗

bioRxiv2024

Synaptogyrin-3 Prevents Cocaine Addiction and Dopamine Deficits

Synaptogyrin-3, a functionally obscure synaptic vesicle protein, interacts with vesicular monoamine and dopamine transporters, bringing together dopamine release and reuptake sites. Synaptogyrin-3 was reduced by chronic cocaine exposure in both humans and rats, and synaptogyrin-3 levels inversely correlated with motivation to take cocaine in rats. Synaptogyrin-3 overexpression in dopamine neurons reduced cocaine self-administration, decreased anxiety-like behavior, and enhanced cognitive flexibility. Overexpression also enhanced nucleus accumbens dopamine signaling and prevented cocaine-induced deficits, suggesting a putative therapeutic role for synaptogyrin-3 in cocaine use disorder.

neuroscience↗

bioRxiv2024

Synchrony between midbrain gene transcription and dopamine terminal regulation is modulated by chronic alcohol drinking

Alcohol use disorder is marked by disrupted behavioral and emotional states which persist into abstinence. The enduring synaptic alterations that remain despite the absence of alcohol are of interest for interventions to prevent relapse. Here, 28 male rhesus macaques underwent over 20 months of alcohol drinking interspersed with three 30-day forced abstinence periods. After the last abstinence period, we paired direct sub-second dopamine monitoring via ex vivo voltammetry in nucleus accumbens slices with RNA-sequencing of the ventral tegmental area. We found persistent augmentation of dopamine transporter function, kappa opioid receptor sensitivity, and dynorphin release - all inhibitory regulators which act to decrease extracellular dopamine. Surprisingly, though transcript expression was not altered, the relationship between gene expression and functional readouts of these encoded proteins was highly dynamic and altered by drinking history. These results outline the long-lasting synaptic impact of alcohol use and suggest that assessment of transcript-function relationships is critical for the rational design of precision therapeutics.

neuroscience↗

bioRxiv2024

Kappa Opioid Receptors Negatively Regulate Real Time Spontaneous Dopamine Signals by Reducing Release and Increasing Uptake

AbstractThe role of the dynorphin/kappa opioid receptor (KOR) system in dopamine (DA) regulation has been extensively investigated. KOR activation reduces extracellular DA concentrations and increases DA transporter (DAT) activity and trafficking to the membrane. To explore KOR influences on real-time DA fluctuations, we used the photosensor dLight1.2 with fiber photometry in the nucleus accumbens (NAc) core of freely moving male and female C57BL/6 mice. First, we established that the rise and fall of spontaneous DA signals were due to DA release and reuptake, respectively. Then mice were systemically administered the KOR agonist U50,488H (U50), with or without pretreatment with the KOR antagonist aticaprant (ATIC). U50 reduced both the amplitude and width of spontaneous signals in males, but only reduced width in females. Further, the slope of the correlation between amplitude and width was increased in both sexes, suggesting that DA uptake rates were increased. U50 also reduced the frequency of signals in both males and females. All effects of KOR activation were stronger in males. Overall, KORs exerted significant inhibitory control over spontaneous DA signaling, acting through at least three mechanisms - inhibiting DA release, promoting DAT-mediated uptake, and reducing the frequency of signals.

neuroscience↗

bioRxiv2023

4D intravital imaging studies iden1fy platelets as the predominant cellular procoagulant surface in a mouse model of hemostasis

Interplay between platelets, coagulation/fibrinolytic factors, and endothelial cells (ECs) is necessary for effective hemostatic plug formation. This study describes a novel four-dimensional (4D) imaging platform to visualize and quantify hemostatic plug components with high spatiotemporal resolution. Fibrin accumulation following laser-induced endothelial ablation was observed at the EC-platelet plug interface, controlled by the antagonistic balance between fibrin generation and breakdown. Phosphatidylserine (PS) was first detected in close physical proximity to the fibrin ring, followed by exposure across the endothelium. Impaired PS exposure in cyclophilinD-/- mice resulted in a significant reduction in fibrin accumulation. Adoptive transfer and inhibitor studies demonstrated a key role for platelets, but not ECs, in fibrin generation during hemostatic plug formation. Inhibition of fibrinolysis with tranexamic acid (TXA) led to increased fibrin accumulation in WT mice, but not in cyclophilinD-/- mice or WT mice treated with antiplatelet drugs. These studies implicate platelets as the functionally dominant procoagulant surface during hemostatic plug formation. In addition, they suggest that impaired fibrin formation due to reduced platelet procoagulant activity is not reversed by TXA treatment.

cell biology↗

bioRxiv2023

Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference

Biophysically detailed neural models are a powerful technique to study neural dynamics in health and disease with a growing number of established and openly available models. A major challenge in the use of such models is that parameter inference is an inherently difficult and unsolved problem. Identifying unique parameter distributions that can account for observed neural dynamics, and differences across experimental conditions, is essential to their meaningful use. Recently, simulation based inference (SBI) has been proposed as an approach to perform Bayesian inference to estimate parameters in detailed neural models. SBI overcomes the challenge of not having access to a likelihood function, which has severely limited inference methods in such models, by leveraging advances in deep learning to perform density estimation. While the substantial methodological advancements offered by SBI are promising, their use in large scale biophysically detailed models is challenging and methods for doing so have not been established, particularly when inferring parameters that can account for time series waveforms. We provide guidelines and considerations on how SBI can be applied to estimate time series waveforms in biophysically detailed neural models starting with a simplified example and extending to specific applications to common MEG/EEG waveforms using the the large scale neural modeling framework of the Human Neocortical Neurosolver. Specifically, we describe how to estimate and compare results from example oscillatory and event related potential simulations. We also describe how diagnostics can be used to assess the quality and uniqueness of the posterior estimates. The methods described provide a principled foundation to guide future applications of SBI in a wide variety of applications that use detailed models to study neural dynamics. Author summaryA central problem in computational neural modeling is estimating model parameters that can account for observed activity patterns. While several techniques exist to perform parameter inference in special classes of abstract neural models, there are comparatively few approaches for large scale biophysically detailed neural models. In this work, we describe challenges and solutions in applying a deep learning based statistical framework to estimate parameters in a biophysically detailed large scale neural model, and emphasize the particular difficulties in estimating parameters for time series data. Our example uses a multi-scale model designed to connect human MEG/EEG recordings to the underlying cell and circuit level generators. Our approach allows for crucial insight into how cell-level properties interact to produce measured neural activity, and provides guidelines for diagnosing the quality of the estimate and uniqueness of predictions for different MEG/EEG biomarkers.

neuroscience↗

bioRxiv2022

Nicotine Modifies Responding for Cocaine in a Concurrent Rodent Self-administration Model

Prevailing preclinical models of cocaine use have not resulted in an FDA-approved treatment for cocaine use disorder, potentially due to a focus on cocaine use in isolation, which may not translate well to polysubstance use in clinical populations. Clinically, nicotine has been shown to increase cocaines potency and reinforcing efficacy, but some preclinical studies suggest that non-contingent nicotine exposure is not sufficient to alter cocaine self-administration in rats; therefore, this experiment examined if the addition of nicotine to the cocaine solution would alter self-administration behavior. Male Sprague Dawley rats (N=7) were trained to self-administer cocaine (0.75mg/kg/inf), and tested on a long access, fixed ratio 1 schedule of reinforcement (6 hour sessions, unlimited inf, 5 days), for cocaine alone (0.75mg/kg/inf), followed by cocaine and nicotine (0.75mg/kg/inf cocaine+0.03mg/kg/inf nicotine). Finally, rats responded on a progressive ratio schedule for varied doses of cocaine with and without concurrent nicotine at a consistent dose (1.5, 0.75, 0.375, 0.19mg/kg/inf cocaine{+/-} 0.03mg/kg/inf nicotine). Unexpectedly, under long access conditions, rats self-administering cocaine and nicotine responded less than for cocaine alone, and did not escalate responding. However, under progressive ratio conditions, responding for cocaine and nicotine was greater than responding for cocaine alone across low and moderate cocaine doses, and decreased at high cocaine doses, indicating a leftward shift in the dose response curve. Together, these data highlight the importance of evaluating multiple outcome measures in nicotine + cocaine paradigms, and suggest that concurrent self-administration of cocaine and nicotine results in greater motivated responding than for cocaine alone.

neuroscience↗

bioRxiv2022

Heroin Self-Administration Induces Altered Dopamine Terminal Dynamics in the Nucleus Accumbens

Administration of heroin results in the engagement of multiple brain regions and the rewarding and addictive effects are mediated, at least partially, through activation of the mesolimbic dopamine system. However, less is known about dopamine system function following chronic exposure to heroin. Withdrawal from chronic heroin exposure is likely to drive a state of low dopamine in the nucleus accumbens (NAc), as previously observed during withdrawal from other drug classes. Thus, we aimed to investigate alterations in NAc dopamine terminal function following chronic heroin self-administration to identify a mechanism for dopaminergic adaptations. Adult male Long Evans rats were trained to self-administer heroin (0.05 mg/kg/inf, IV) and then placed on a long access (FR1, 6-hrs, unlimited inf, 0.05 mg/kg/inf) protocol to induce escalation of intake. After one day of withdrawal, male rats exhibited lower basal extracellular levels of dopamine as well as reduced dopaminergic responses to a heroin challenge (0.1 mg/kg/inf, IV). Following heroin self-administration, rats had decreased basal extracellular levels of dopamine and blunted dopamine response following a heroin challenge (0.1 mg/kg/inf, IV) in the NAc compared to saline controls. FSCV revealed that heroin-exposed rats have reduced stimulated dopamine release during tonic-like, single-pulse stimulations but increased phasic-like dopamine release during multi-pulse stimulation trains (5 pulses, 5-100Hz) in addition to an altered dynamic range of release stimulation intensities when compared to controls. Further, we found that presynaptic D3 autoreceptor and kappa-opioid receptor activity was increased following heroin self-administration. These results reveal a marked low dopamine state following heroin-exposure and suggest the combination of altered dopamine release dynamics may contribute to increased heroin seeking.

neuroscience↗

bioRxiv2021

Biophysical and Architectural Mechanisms of Subthalamic Theta under Response Conflict

The cortico-basal ganglia circuit is needed to suppress prepotent actions and to facilitate controlled behavior. Under conditions of response conflict, the frontal cortex and subthalamic nucleus [STN] exhibit increased spiking and theta band power, which are linked to adaptive regulation of behavioral output. The electrophysiological mechanisms underlying these neural signatures of impulse control remain poorly understood. To address this lacuna, we constructed a novel large-scale, biophysically principled model of the subthalamopallidal [STN-Globus Pallidus externus (GPe)] network, and examined the mechanisms that modulate theta power and spiking in response to cortical input. Simulations confirmed that theta power does not emerge from intrinsic network dynamics but is robustly elicited in response to cortical input as burst events representing action selection dynamics. Rhythmic burst events of multiple cortical populations, representing a state of conflict where cortical motor plans vacillate in the theta range, led to prolonged STN theta and increased spiking, consistent with empirical literature. Notably, theta band signaling required NMDA, but not AMPA, currents, which were in turn related to a triphasic STN response characterized by spiking, silence and bursting periods. Finally, theta band resonance was also strongly modulated by architectural connectivity, with maximal theta arising when multiple cortical populations project to individual STN "conflict detector" units, due to an NMDA-dependent supralinear response. Our results provide insights into the biophysical principles and architectural constraints that give rise to STN dynamics during response conflict, and how their disruption can lead to impulsivity and compulsivity.

neuroscience↗

bioRxiv2021

Distinct neocortical mechanisms underlie human SI responses to median nerve and laser evoked peripheral activation

Magneto- and/or electro-encephalography (M/EEG) are non-invasive clinically-relevant tools that have long been used to measure electromagnetic fields in somatosensory cortex evoked by innocuous and noxious somatosensory stimuli. Two commonly applied stimulation paradigms that produce distinct responses in primary somatosensory cortex (SI) linked to innocuous and noxious sensations are electrical median nerve (MN) stimulation and cutaneous laser-evoked (LE) stimulation to the dorsum of the hand, respectively. Despite their prevalence, the physiological mechanisms that produce stereotypic macroscale MN and LE responses have yet to be fully articulated, limiting their utility in understanding brain dynamics associated with non-painful and/or painful somatosensation. Through a literature review, we detailed features of MN and LE responses source-localized to SI that are robust and reproducible across studies. We showed that the first peak in the MN response at [~]20 ms post-stimulus (i.e., MN N1) corresponds to outward-directed deep-to-superficial electrical current flow through the cortical laminae, which is followed by inward-directed current at [~]30 ms (i.e., MN P1). In contrast, the initial LE response occurs later at [~]170 ms (i.e., LE N1) and is oriented inward and opposite the direction of the MN N1. We then examined the neocortical circuit mechanisms contributing to the robust features of each response using the Human Neocortical Neurosolver (HNN) neural modeling software tool (Neymotin et al., 2020). Using HNN as a hypothesis development and testing tool, model results predicted the MN response can be simulated with a sequence of layer specific thalamocortical and cortico-cortical synaptic drive similar to that previously reported for tactile evoked responses (Jones et al., 2007; Neymotin et al., 2020), with the novel discovery that an early excitatory input to supragranular layers at [~]30 ms is an essential mechanism contributing to the inward current flow of the MN P1. Model results further predicted that the initial [~]170 ms inward current flow of the LE N1 was generated by a burst of repetitive gamma-frequency ([~]40 Hz) excitatory synaptic drive to supragranular layers, consistent with prior reports of LE gamma-frequency activity. These results make novel and detailed multiscale predictions about the dynamic laminar circuit mechanisms underlying temporal and spectral features of MN and LE responses in SI and can guide further investigations in follow-up studies. Ultimately, these findings may help with the development of targeted therapeutics for pathological somatosensation, such as somatic sensitivity and acute neuropathic pain.

neuroscience↗

bioRxiv2021

Thalamocortical mechanisms regulating the relationship between transient beta events and human tactile perception

Transient neocortical events with high spectral power in the 15-29Hz beta band are among the most reliable predictors of sensory perception. Prestimulus beta event rates in primary somatosensory cortex correlate with sensory suppression, most effectively 100-300ms before stimulus onset. However, the neural mechanisms underlying this perceptual association are unknown. We combined human magnetoencephalography (MEG) measurements with biophysical neural modeling to test potential cellular and circuit mechanisms that underlie observed correlations between prestimulus beta events and tactile detection. Extending prior studies, we found that simulated bursts from higher-order, non-lemniscal thalamus were sufficient to drive beta event generation and to recruit slow supragranular inhibition acting on a 300ms time scale to suppress sensory information. Further analysis showed that the same beta generating mechanism can lead to facilitated perception for a brief period when beta events occur simultaneously with tactile stimulation before inhibition is recruited. These findings were supported by close agreement between model-derived predictions and empirical MEG data. The post-event suppressive mechanism explains an array of studies that associate beta with decreased processing, while the during-event faciliatory mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.

neuroscience↗

bioRxiv2021

Laminar dynamics of beta bursts in human motor cortex

Modulation of motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient bursting events rather than slowly modulating oscillations, suggesting a more rapid, information-encoding functional role than previously believed. Insight into how beta bursts are generated in sensorimotor circuits can provide important constraints to theories about their functional role for movement control. To this end, we leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings.

neuroscience↗