Inhibitory Populations Research Articles

Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex.

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.Significance Statement Information about sounds is represented in the auditory cortex by neuronal population activity that has a characteristic sparse structure. Cortical neuronal populations comprise multiple types of excitatory and inhibitory neurons. Here, we find that activating different types of inhibitory neurons differentially controls population neuronal representations, with one type of inhibitory neurons increasing the differences in the identity of the cells recruited to represent the different sounds, and another inhibitory neuron type changing the relative activity level of overlapping neuronal populations. Such transformations may be beneficial for different types of auditory behaviors, suggesting that these different types of inhibitory neurons may be recruited under different behavioral constraints in optimizing neuronal representations of sounds.

Structural influences on synaptic plasticity: The role of presynaptic connectivity in the emergence of E/I co-tuning.

Cortical neurons are versatile and efficient coding units that develop strong preferences for specific stimulus characteristics. The sharpness of tuning and coding efficiency is hypothesized to be controlled by delicately balanced excitation and inhibition. These observations suggest a need for detailed co-tuning of excitatory and inhibitory populations. Theoretical studies have demonstrated that a combination of plasticity rules can lead to the emergence of excitation/inhibition (E/I) co-tuning in neurons driven by independent, low-noise signals. However, cortical signals are typically noisy and originate from highly recurrent networks, generating correlations in the inputs. This raises questions about the ability of plasticity mechanisms to self-organize co-tuned connectivity in neurons receiving noisy, correlated inputs. Here, we study the emergence of input selectivity and weight co-tuning in a neuron receiving input from a recurrent network via plastic feedforward connections. We demonstrate that while strong noise levels destroy the emergence of co-tuning in the readout neuron, introducing specific structures in the non-plastic pre-synaptic connectivity can re-establish it by generating a favourable correlation structure in the population activity. We further show that structured recurrent connectivity can impact the statistics in fully plastic recurrent networks, driving the formation of co-tuning in neurons that do not receive direct input from other areas. Our findings indicate that the network dynamics created by simple, biologically plausible structural connectivity patterns can enhance the ability of synaptic plasticity to learn input-output relationships in higher brain areas.

Examining motor evidence for the pause-then-cancel model of action-stopping: insights from motor system physiology.

Stopping initiated actions is fundamental to adaptive behavior. Longstanding, single-process accounts of action-stopping have been challenged by recent, two-process, "pause-then-cancel" models. These models propose that action-stopping involves two inhibitory processes: 1) a fast Pause process, which broadly suppresses the motor system as the result of detecting any salient event, and 2) a slower Cancel process, which involves motor suppression specific to the cancelled action. A purported signature of the Pause process is global suppression, or the reduced corticospinal excitability (CSE) of task-unrelated effectors early on in action-stopping. However, unlike the Pause process, few (if any) motor system signatures of a Cancel process have been identified. Here, we used single- and paired-pulse transcranial magnetic stimulation (TMS) methods to comprehensively measure the local physiological excitation and inhibition of both responding and task-unrelated motor effector systems during action-stopping. Specifically, we measured CSE, short-interval intracortical inhibition (SICI), and the duration of the cortical silent period (CSP). Consistent with key predictions from the pause-then-cancel model, CSE measurements at the responding effector indicated that additional suppression was necessary to counteract Go-related increases in CSE during action-stopping, particularly at later timepoints. Increases in SICI on Stop-signal trials did not differ across task-related and task-unrelated effectors, or across timepoints. This suggests SICI as a potential source of global suppression. Increases in CSP duration on Stop-signal trials were more prominent at later timepoints and were related to individual differences in CSE. Our study provides further evidence from motor system physiology that multiple inhibitory processes influence action-stopping.NEW & NOTEWORTHY Current debate surrounds whether single- or dual-process models better account for human action-stopping ability. We show that motor suppression of a successfully stopped muscle follows a distinct time course compared with when that same muscle is unrelated to the stopping task. Our results further suggest that distinct local inhibitory neuron populations contribute to these unique sources of suppression. Our study provides evidence from motor system physiology that multiple inhibitory processes influence action-stopping.

"Distinct inhibitory neurons differently shape neuronal codes for sound intensity in the auditory cortex".

Cortical circuits contain multiple types of inhibitory neurons which shape how information is processed within neuronal networks. Here, we asked whether somatostatin-expressing (SST) and vasoactive intestinal peptide-expressing (VIP) inhibitory neurons have distinct effects on population neuronal responses to noise bursts of varying intensities. We optogenetically stimulated SST or VIP neurons while simultaneously measuring the calcium responses of populations of hundreds of neurons in the auditory cortex of male and female awake, head-fixed mice to sounds. Upon SST neuronal activation, noise bursts representations became more discrete for different intensity levels, relying on cell identity rather than strength. By contrast, upon VIP neuronal activation, noise bursts of different intensity level activated overlapping neuronal populations, albeit at different response strengths. At the single-cell level, SST and VIP neuronal activation differentially modulated the response-level curves of monotonic and nonmonotonic neurons. SST neuronal activation effects were consistent with a shift of the neuronal population responses toward a more localist code with different cells responding to sounds of different intensity. By contrast, VIP neuronal activation shifted responses towards a more distributed code, in which sounds of different intensity level are encoded in the relative response of similar populations of cells. These results delineate how distinct inhibitory neurons in the auditory cortex dynamically control cortical population codes. Different inhibitory neuronal populations may be recruited under different behavioral demands, depending on whether categorical or invariant representations are advantageous for the task.

Firing rate models for gamma oscillations in I-I and E-I networks.

Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.

Single-cell multiregion dissection of Alzheimer’s disease

Alzheimer’s disease is the leading cause of dementia worldwide, but the cellular pathways that underlie its pathological progression across brain regions remain poorly understood1–3. Here we report a single-cell transcriptomic atlas of six different brain regions in the aged human brain, covering 1.3 million cells from 283 post-mortem human brain samples across 48 individuals with and without Alzheimer’s disease. We identify 76 cell types, including region-specific subtypes of astrocytes and excitatory neurons and an inhibitory interneuron population unique to the thalamus and distinct from canonical inhibitory subclasses. We identify vulnerable populations of excitatory and inhibitory neurons that are depleted in specific brain regions in Alzheimer’s disease, and provide evidence that the Reelin signalling pathway is involved in modulating the vulnerability of these neurons. We develop a scalable method for discovering gene modules, which we use to identify cell-type-specific and region-specific modules that are altered in Alzheimer’s disease and to annotate transcriptomic differences associated with diverse pathological variables. We identify an astrocyte program that is associated with cognitive resilience to Alzheimer’s disease pathology, tying choline metabolism and polyamine biosynthesis in astrocytes to preserved cognitive function late in life. Together, our study develops a regional atlas of the ageing human brain and provides insights into cellular vulnerability, response and resilience to Alzheimer’s disease pathology.

Spinal projecting neurons in rostral ventromedial medulla co-regulate motor and sympathetic tone

Many behaviors require the coordinated actions of somatic and autonomic functions. However, the underlying mechanisms remain elusive. By opto-stimulating different populations of descending spinal projecting neurons (SPNs) in anesthetized mice, we show that stimulation of excitatory SPNs in the rostral ventromedial medulla (rVMM) resulted in a simultaneous increase in somatomotor and sympathetic activities. Conversely, opto-stimulation of rVMM inhibitory SPNs decreased both activities. Anatomically, these SPNs innervate both sympathetic preganglionic neurons and motor-related regions in the spinal cord. Fiber-photometry recording indicated that the activities of rVMM SPNs correlate with different levels of muscle and sympathetic tone during distinct arousal states. Inhibiting rVMM excitatory SPNs reduced basal muscle and sympathetic tone, impairing locomotion initiation and high-speed performance. In contrast, silencing the inhibitory population abolished muscle atonia and sympathetic hypoactivity during rapid eye movement (REM) sleep. Together, these results identify rVMM SPNs as descending spinal projecting pathways controlling the tone of both the somatomotor and sympathetic systems.

Distinct lateral hypothalamic CaMKIIα neuronal populations regulate wakefulness and locomotor activity

For nearly a century, evidence has accumulated indicating that the lateral hypothalamus (LH) contains neurons essential to sustain wakefulness. While lesion or inactivation of LH neurons produces a profound increase in sleep, stimulation of inhibitory LH neurons promotes wakefulness. To date, the primary wake-promoting cells that have been identified in the LH are the hypocretin/orexin (Hcrt) neurons, yet these neurons have little impact on total sleep or wake duration across the 24-h period. Recently, we and others have identified other LH populations that increase wakefulness. In the present study, we conducted microendoscopic calcium imaging in the LH concomitant with EEG and locomotor activity (LMA) recordings and found that a subset of LH neurons that express Ca2+/calmodulin-dependent protein kinase IIα (CaMKIIα) are preferentially active during wakefulness. Chemogenetic activation of these neurons induced sustained wakefulness and greatly increased LMA even in the absence of Hcrt signaling. Few LH CaMKIIα-expressing neurons are hypocretinergic or histaminergic while a small but significant proportion are GABAergic. Ablation of LH inhibitory neurons followed by activation of the remaining LH CaMKIIα neurons induced similar levels of wakefulness but blunted the LMA increase. Ablated animals showed no significant changes in sleep architecture but both spontaneous LMA and high theta (8 to 10 Hz) power during wakefulness were reduced. Together, these findings indicate the existence of two subpopulations of LH CaMKIIα neurons: an inhibitory population that promotes locomotion without affecting sleep architecture and an excitatory population that promotes prolonged wakefulness even in the absence of Hcrt signaling.

Mouse hippocampal CA1 VIP interneurons detect novelty in the environment and support recognition memory

In the CA1 hippocampus, vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) play a prominent role in disinhibitory circuit motifs. However, the specific behavioral conditions that lead to circuit disinhibition remain uncertain. To investigate the behavioral relevance of VIP-IN activity, we employed wireless technologies allowing us to monitor and manipulate their function in freely behaving mice. Our findings reveal that, during spatial exploration in new environments, VIP-INs in the CA1 hippocampal region become highly active, facilitating the rapid encoding of novel spatial information. Remarkably, both VIP-INs and pyramidal neurons (PNs) exhibit increased activity when encountering novel changes in the environment, including context- and object-related alterations. Concurrently, somatostatin- and parvalbumin-expressing inhibitory populations show an inverse relationship with VIP-IN and PN activity, revealing circuit disinhibition that occurs on a timescale of seconds. Thus, VIP-IN-mediated disinhibition may constitute a crucial element in the rapid encoding of novelty and the acquisition of recognition memory.

A mean-field model of gamma-frequency oscillations in networks of excitatory and inhibitory neurons.

Gamma oscillations are widely seen in the cerebral cortex in different states of the wake-sleep cycle and are thought to play a role in sensory processing and cognition. Here, we study the emergence of gamma oscillations at two levels, in networks of spiking neurons, and a mean-field model. At the network level, we consider two different mechanisms to generate gamma oscillations and show that they are best seen if one takes into account the synaptic delay between neurons. At the mean-field level, we show that, by introducing delays, the mean-field can also produce gamma oscillations. The mean-field matches the mean activity of excitatory and inhibitory populations of the spiking network, as well as their oscillation frequencies, for both mechanisms. This mean-field model of gamma oscillations should be a useful tool to investigate large-scale interactions through gamma oscillations in the brain.

Local origin of excitatory–inhibitory tuning equivalence in a cortical network

The interplay between excitation and inhibition determines the fidelity of cortical representations. The receptive fields of excitatory neurons are often finely tuned to encoded features, but the principles governing the tuning of inhibitory neurons remain elusive. In this study, we recorded populations of neurons in the mouse postsubiculum (PoSub), where the majority of excitatory neurons are head-direction (HD) cells. We show that the tuning of fast-spiking (FS) cells, the largest class of cortical inhibitory neurons, was broad and frequently radially symmetrical. By decomposing tuning curves using the Fourier transform, we identified an equivalence in tuning between PoSub-FS and PoSub-HD cell populations. Furthermore, recordings, optogenetic manipulations of upstream thalamic populations and computational modeling provide evidence that the tuning of PoSub-FS cells has a local origin. These findings support the notion that the equivalence of neuronal tuning between excitatory and inhibitory cell populations is an intrinsic property of local cortical networks.

Biophysical modulation and robustness of itinerant complexity in neuronal networks.

Transient synchronization of bursting activity in neuronal networks, which occurs in patterns of metastable itinerant phase relationships between neurons, is a notable feature of network dynamics observed in vivo. However, the mechanisms that contribute to this dynamical complexity in neuronal circuits are not well understood. Local circuits in cortical regions consist of populations of neurons with diverse intrinsic oscillatory features. In this study, we numerically show that the phenomenon of transient synchronization, also referred to as metastability, can emerge in an inhibitory neuronal population when the neurons' intrinsic fast-spiking dynamics are appropriately modulated by slower inputs from an excitatory neuronal population. Using a compact model of a mesoscopic-scale network consisting of excitatory pyramidal and inhibitory fast-spiking neurons, our work demonstrates a relationship between the frequency of pyramidal population oscillations and the features of emergent metastability in the inhibitory population. In addition, we introduce a method to characterize collective transitions in metastable networks. Finally, we discuss potential applications of this study in mechanistically understanding cortical network dynamics.

Emergent dynamics in fractional-order Wilson–Cowan neural network systems

The firing dynamics of excitable systems are critical to understand organized responses in cortical networks. In this paper, we examine a fractional-order Wilson–Cowan (W–C) neural network model composed of excitatory and inhibitory neuron populations, utilizing Caputo’s fractional-order derivative formalism to explore the influence of fractional-order dynamics on firing behavior. The significance of extending to the fractional-order domain lies in the model’s theoretical framework, which inherently retains memory and hereditary characteristics. We investigate memory-dependent response functions and average neuronal characteristics, enabling us to formulate a fractional-order model that incorporates past dynamics into the neuronal populations’ features. This generalized model is capable of producing alternations between spiking and bursting phenomena, including mixed-mode oscillations (MMOs). Using stability and bifurcation analyses, we delineate the parameter space within which variations in firing patterns emerge. One notable impact of the model’s memory property is the potential stabilization of neuronal activity. We demonstrate that our numerical findings are in alignment with the analytical predictions and that the memory trace depends on the fractional-order dynamics.

Applications of information geometry to spiking neural network activity.

The space of possible behaviors that complex biological systems may exhibit is unimaginably vast, and these systems often appear to be stochastic, whether due to variable noisy environmental inputs or intrinsically generated chaos. The brain is a prominent example of a biological system with complex behaviors. The number of possible patterns of spikes emitted by a local brain circuit is combinatorially large, although the brain may not make use of all of them. Understanding which of these possible patterns are actually used by the brain, and how those sets of patterns change as properties of neural circuitry change is a major goal in neuroscience. Recently, tools from information geometry have been used to study embeddings of probabilistic models onto a hierarchy of model manifolds that encode how model outputs change as a function of their parameters, giving a quantitative notion of "distances" between outputs. We apply this method to a network model of excitatory and inhibitory neural populations to understand how the competition between membrane and synaptic response timescales shapes the network's information geometry. The hyperbolic embedding allows us to identify the statistical parameters to which the model behavior is most sensitive, and demonstrate how the ranking of these coordinates changes with the balance of excitation and inhibition in the network.

Abstract 17051: Oxytocin Receptor in the Spinal Neuraxial Modulation of Ventricular Excitability

Introduction: Cardiac sympathoexcitation is a major contributor to the pathogenesis of ventricular tachyarrhymias (VTs) during ischemia reperfusion (I/R) and chronic myocardial infarction (MI). Afferent network connections in the intermediolateral cell column (IML) and dorsal horn (DH) control sympathetic output to the heart. Our team reported spinal cord stimulation (SCS), decreased cardiac sympathoexcitation and reduced VTs during ischemia. Oxytocin (OXT) is a known neuromodulator; however, whether OXT signaling can modulate the cardiospinal neural network is unknown. Hypothesis: SCS neuromodulation is reducing sympathoexcitation and VTs through OXT signaling pathways. Methods: Two models of cardiac ischemia were used in Yorkshire domestic swine. In acute I/R, a suture was placed around the left anterior descending (LAD) coronary artery, after sternotomy. Chronic infarction (MI) was created by accessing the femoral with fluoroscopy guidance. Polystyrene microspheres (1ml) were injected via a 3mm angioplasty balloon catheter to the LAD. Animals then recovered post-MI for 6-8wk. SCS treatment was delivered through a four-pole lead which was inserted in the epidural space (T1-T4)(50Hz, 0.4ms pulse duration). T2-T4 spinal cord was collected postmortem for molecular analysis. Fluorescence in situ hybridization (FISH) protocol for RNAscope Fluorescent v2 Assay (ACD) was followed. Cell counts represented as 3 puncta or more centered around DAPI. Results: We report that OXT receptor positive cells significantly decreased as a result of I/R and MI (p<0.001, two-way ANOVA n=4-5 animals, average of 2-3 slices per animal). Within the DH the majority of OXT positive cells were inhibitory GABAergic neurons. Within the IML, a majority of the cells regulated by I/R and MI were microglia, and both an inhibitory and excitatory population contributed to the onset of ischemia. SCS treatment after I/R and MI resulted in the recovery of this OXT receptor cell population. Conclusions: By evaluating the role of OXT in reducing cardiac sympathoexcitation at the level of the spinal cord, we provide new insights into optimizing current neuromodulation approaches and developing new pharmacologic therapies.

Role of interneuron subtypes in controlling trial-by-trial output variability in the neocortex

Trial-by-trial variability is a ubiquitous property of neuronal activity in vivo which shapes the stimulus response. Computational models have revealed how local network structure and feedforward inputs shape the trial-by-trial variability. However, the role of input statistics and different interneuron subtypes in this process is less understood. To address this, we investigate the dynamics of stimulus response in a cortical microcircuit model with one excitatory and three inhibitory interneuron populations (PV, SST, VIP). Our findings demonstrate that the balance of inputs to different neuron populations and input covariances are the primary determinants of output trial-by-trial variability. The effect of input covariances is contingent on the input balances. In general, the network exhibits smaller output trial-by-trial variability in a PV-dominated regime than in an SST-dominated regime. Importantly, our work reveals mechanisms by which output trial-by-trial variability can be controlled in a context, state, and task-dependent manner.

Synaptic alterations and neuronal firing in human epileptic neocortical excitatory networks.

Epilepsy is a prevalent neurological condition, with underlying neuronal mechanisms involving hyperexcitability and hypersynchrony. Imbalance between excitatory and inhibitory circuits, as well as histological reorganization are relatively well-documented in animal models or even in the human hippocampus, but less is known about human neocortical epileptic activity. Our knowledge about changes in the excitatory signaling is especially scarce, compared to that about the inhibitory cell population. This study investigated the firing properties of single neurons in the human neocortex in vitro, during pharmacological blockade of glutamate receptors, and additionally evaluated anatomical changes in the excitatory circuit in tissue samples from epileptic and non-epileptic patients. Both epileptic and non-epileptic tissues exhibited spontaneous population activity (SPA), NMDA receptor antagonization reduced SPA recurrence only in epileptic tissue, whereas further blockade of AMPA/kainate receptors reversibly abolished SPA emergence regardless of epilepsy. Firing rates did not significantly change in excitatory principal cells and inhibitory interneurons during pharmacological experiments. Granular layer (L4) neurons showed an increased firing rate in epileptic compared to non-epileptic tissue. The burstiness of neurons remained unchanged, except for that of inhibitory cells in epileptic recordings, which decreased during blockade of glutamate receptors. Crosscorrelograms computed from single neuron discharge revealed both mono- and polysynaptic connections, particularly involving intrinsically bursting principal cells. Histological investigations found similar densities of SMI-32-immunopositive long-range projecting pyramidal cells in both groups, and shorter excitatory synaptic active zones with a higher proportion of perforated synapses in the epileptic group. These findings provide insights into epileptic modifications from the perspective of the excitatory system and highlight discrete alterations in firing patterns and synaptic structure. Our data suggest that NMDA-dependent glutamatergic signaling, as well as the excitatory synaptic machinery are perturbed in epilepsy, which might contribute to epileptic activity in the human neocortex.

Temporal characteristics of gamma rhythm constrain properties of noise in an inhibition-stabilized network model.

Gamma rhythm refers to oscillatory neural activity between 30 and 80Hz, induced in visual cortex by stimuli such as iso-luminant hues or gratings. The power and peak frequency of gamma depend on the properties of the stimulus such as size and contrast. Gamma waveform is typically arch-shaped, with narrow troughs and broad peaks, and can be replicated in a self-oscillating Wilson-Cowan (WC) model operating in an appropriate regime. However, oscillations in this model are infinitely long, unlike physiological gamma that occurs in short bursts. Further, unlike the model, gamma is faster after stimulus onset and slows down over time. Here, we first characterized gamma burst duration in local field potential data recorded from two monkeys as they viewed full screen iso-luminant hues. We then added different types of noise in the inputs to the WC model and tested how that affected duration and temporal dynamics of gamma. While the model failed with the often-used Poisson noise, Ornstein-Uhlenbeck noise applied to both the excitatory and the inhibitory populations replicated the duration and slowing of gamma and replicated the shape and stimulus dependencies. Thus, the temporal dynamics of gamma oscillations put constraints on the type and properties of underlying neural noise.

Inhibitory stabilized network behaviour in a balanced neural mass model of a cortical column

Strong inhibitory recurrent connections can reduce the tendency for a neural network to become unstable. This is known as inhibitory stabilization; networks that are unstable in the absence of strong inhibitory feedback because of their unstable excitatory recurrent connections are known as Inhibition Stabilized Networks (ISNs). One of the characteristics of ISNs is their “paradoxical response”, where perturbing the inhibitory neurons with additional excitatory input results in a decrease in their activity after a temporal delay instead of increasing their activity. Here, we develop a model of populations of neurons across different layers of cortex. Within each layer, there is one population of inhibitory neurons and one population of excitatory neurons. The connectivity weights across different populations in the model are derived from a synaptic physiology database provided by the Allen Institute. The model shows a gradient of excitation–inhibition balance across different layers in the cortex, where superficial layers are more inhibitory dominated compared to deeper layers. To investigate the presence of ISNs across different layers, we measured the membrane potentials of neural populations in the model after perturbing inhibitory populations. The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime. These results accord with neurophysiological findings that explored the presence of ISNs across different layers in the cortex. The results show that there may be a systematic macroscopic gradient of inhibitory stabilization across different layers in the cortex that depends on the level of excitation–inhibition balance, and that the strength of the paradoxical response increases as the model moves closer to bifurcation points.

ID: 206155 Rapid Adaption of Dorsal Horn Inhibitory Populations to Dorsal Column Stimulation

Epidural spinal cord stimulation (SCS) has been used for over 50 years to treat refractory pain and avoid addictive opioid therapies. However, there is an incomplete understanding of how these neuromodulatory devices mediate pain relief, which has precluded effective clinical implementation. One of the mechanisms of SCS-mediated pain relief is through activation of inhibitory superficial dorsal horn circuits, as elegantly proposed in the Gate Control Theory (GCT). The properties of sustained Aβ-fiber stimulation evoked responses in molecularly defined inhibitory dorsal horn populations remain poorly defined and were investigated here using an optical approach.