Low Firing Rates Research Articles

A low-cost perfusion heating system for slice electrophysiology

AbstractTemperature-critical applications, such as patch-clamp electrophysiology, require constant perfusion at a fixed temperature. However, maintaining perfusate at a specific temperature throughout various applications requires heaters or coolers with integrated feedback systems, which has historically increased complexity and cost. This makes such systems prohibitively expensive in research environments with lower funding rates, particularly in developing countries. We developed a custom temperature control system that relies on off-the-shelf components and few custom parts, which can be easily produced with common tools. Our system can be built for less than $30 and maintains a set perfusate temperature within 0.4 °C while introducing negligible electrical interference. Using this system, we demonstrate that Striatal Medium Spiny Neurons exhibit increased membrane resistance, longer membrane time constants, lower firing rates, and increased rheobase current at room temperature compared to physiological temperature.

Neuromuscular mechanisms for the fast decline in rate of force development with muscle disuse - a narrative review.

The removal of skeletal muscle tension (unloading or disuse) is followed by many changes in the neuromuscular system, including muscle atrophy and loss of isometric maximal strength (measured by maximal force, Fmax). Explosive strength, i.e. the ability to develop the highest force in the shortest possible time, to maximise rate of force development (RFD), is a fundamental neuromuscular capability, often more functionally relevant than maximal muscle strength. In the present review, we discuss data from studies that looked at the effect of muscle unloading on isometric maximal versus explosive strength. We present evidence that muscle unloading yields a greater decline in explosive relative to maximal strength. The longer the unloading duration, the smaller the difference between the decline in the two measures. Potential mechanisms that may explain the greater decline in measures of RFD relative to Fmax after unloading are higher recruitment thresholds and lower firing rates of motor units, slower twitch kinetics, impaired excitation-contraction coupling, and decreased tendon stiffness. Using a Hill-type force model, we showed that this ensemble of adaptations minimises the loss of force production at submaximal contraction intensities, at the expense of a disproportionately lower RFD. With regard to the high functional relevance of RFD on one hand, and the boosted detrimental effects of inactivity on RFD on the other hand, it seems crucial to implement specific exercises targeting explosive strength in populations that experience muscle disuse over a longer time.

Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy

Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs.

Detecting rhythmic spiking through the power spectra of point process model residuals.

Objective. Oscillations figure prominently as neurological disease hallmarks and neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to seek peaks in the spike train's power spectral density (PSD) which exceed a flat baseline. Yet for a non-oscillating neuron, the PSD is not flat: The recovery period ('RP', the post-spike drop in spike probability, starting with the refractory period) introduces global spectral distortion. An established 'shuffling' procedure corrects for RP distortion by removing the spectral component explained by the inter-spike interval (ISI) distribution. However, this procedure sacrifices oscillation-related information present in the ISIs, and therefore in the PSD. We asked whether point process models (PPMs) might achieve more selective RP distortion removal, thereby enabling improved oscillation detection.Approach. In a novel 'residuals' method, we first estimate the RP duration (nr) from the ISI distribution. We then fit the spike train with a PPM that predicts spike likelihood based on the time elapsed since the most recent of any spikes falling within the precedingnrmilliseconds. Finally, we compute the PSD of the model's residuals.Main results. We compared the residuals and shuffling methods' ability to enable accurate oscillation detection with flat baseline-assuming tests. Over synthetic data, the residuals method generally outperformed the shuffling method in classification of true- versus false-positive oscillatory power, principally due to enhanced sensitivity in sparse spike trains. In single-unit data from the internal globus pallidus (GPi) and ventrolateral anterior thalamus (VLa) of a parkinsonian monkey-in which alpha-beta oscillations (8-30 Hz) were anticipated-the residuals method reported the greatest incidence of significant alpha-beta power, with low firing rates predicting residuals-selective oscillation detection.Significance. These results encourage continued development of the residuals approach, to support more accurate oscillation detection. Improved identification of oscillations could promote improved disease models and therapeutic technologies.

Effects of hand dominance on myoelectric signal of non‑fatigued lumbar multifidus muscle during single arm lifts.

Some evidence indicates that lower back muscles located at the non‑dominant side of the body are more fatigue resistant than their opposite counterparts presumably due to preferential use of the dominant hand. The aim of the study was to determine if any distinction exists in the surface electromyographic activity of corresponding contralateral non‑fatigued lumbar multifidus (LM) muscles as a function of hand dominance. The relative to maximum root mean square, the median frequency (MdF) and spike shape parameters were computed from the surface myoelectric signals of ipsilateral and contralateral lumbar multifidus muscle of 46 adult healthy subjects (27 right‑handed, 19 left‑handed) during voluntary contractions evoked by the single arm lifts in prone position. Activation of LM as a contralateral muscle to lifted arm was greater than as ipsilateral muscle, independently of handedness. Regardless if LM performed ipsi‑ or contralateral action to the lifted arm, the mean spike amplitude, slope, number of peaks per spike and spike duration were greater and mean spike frequency as well as MdF were smaller in the muscle of dominant than non‑dominant side. Combined changes of spike shape measures indicate increased recruitment, lower firing rates and higher synchronization of motor units in the LM of dominant side as compared to its counterpart.

Regulation of spike propagation in feedforward neural networks through short-term synaptic plasticity

Both factors, multilayer Feedforward Neural Networks (FFNs) and short-term synaptic plasticity (STP), are considered crucial in the transmission and processing of neural signals. In this study, a 10-layer FFN was constructed to study the impact of STP on neuronal activity propagation. Neurons within the same layer do not have direct connections; instead, neurons between adjacent layers are randomly connected with a specific probability. The findings indicate that synaptic plasticity can regulate the network’s firing rate, synchronization, and output firing rate gain. Notably, short-term facilitation (STF) allows the network to exhibit high-pass filtering, while short-term depression (STD) achieves low-pass filtering. Combining STF and STD synapses in the FFN broadens the range of input firing rates effectively transmitted by the network. Increasing the proportion of STD-dominated synapses enhances the gain of low firing rate signals but reduces the gain of high firing rate signals. Adjusting the mix of synapses enables the network to implement bandpass filtering and control firing rate gain. These results underscore the effectiveness of modulating short-term synaptic plasticity in regulating neural activity propagation in FFNs.

Corticotropin releasing factor alters the functional diversity of accumbal cholinergic interneurons.

Cholinergic interneurons (ChIs) provide the main source of acetylcholine in the striatum and have emerged as a critical modulator of behavioral flexibility, motivation, and associative learning. In the dorsal striatum (DS), ChIs display heterogeneous firing patterns. Here, we investigated the spontaneous firing patterns of ChIs in the nucleus accumbens (NAc) shell, a region of the ventral striatum. We identified four distinct ChI firing signatures: regular single-spiking, irregular single-spiking, rhythmic bursting, and a mixed-mode pattern composed of bursting activity and regular single spiking. ChIs from females had lower firing rates compared with males and had both a higher proportion of mixed-mode firing patterns and a lower proportion of regular single-spiking neurons compared with males. We further observed that across the estrous cycle, the diestrus phase was characterized by higher proportions of irregular ChI firing patterns compared with other phases. Using pooled data from males and females, we examined how the stress-associated neuropeptide corticotropin releasing factor (CRF) impacts these firing patterns. ChI firing patterns showed differential sensitivity to CRF. This translated into differential ChI sensitivity to CRF across the estrous cycle. Furthermore, CRF shifted the proportion of ChI firing patterns toward more regular spiking activity over bursting patterns. Finally, we found that repeated stressor exposure altered ChI firing patterns and sensitivity to CRF in the NAc core, but not the NAc shell. These findings highlight the heterogeneous nature of ChI firing patterns, which may have implications for accumbal-dependent motivated behaviors.NEW & NOTEWORTHY Cholinergic interneurons (ChIs) within the dorsal and ventral striatum can exert a major influence on network output and motivated behaviors. However, the firing patterns and neuromodulation of ChIs within the ventral striatum, specifically the nucleus accumbens (NAc) shell, are understudied. Here, we report that NAc shell ChIs have heterogeneous ChI firing patterns that are labile and can be modulated by the stress-linked neuropeptide corticotropin releasing factor (CRF) and by the estrous cycle.

No sex differences in time-to-task failure and neuromuscular patterns of response during submaximal, bilateral, isometric leg extensions.

In general, it has been suggested that females are more fatigue-resistant than males, with the magnitude of difference being most pronounced during low-intensity sustained contractions. However, the mechanisms for the apparent sex difference have not yet been fully elucidated in the literature. This study aimed to examine sex-related differences in fatigability and patterns of neuromuscular responses for surface electromyographic (sEMG) and mechanomyographic (sMMG) amplitude and frequency (MPF) characteristics during a sustained submaximal bilateral, isometric leg extension muscle action. A sample of 20 young recreationally active males and females with previous resistance training experience performed a sustained, submaximal, bilateral isometric leg extension until task failure. Time-to-task failure was compared using a nonparametric bootstrap of the 95% confidence interval for the mean difference between males and females. Additionally, patterns of response for sEMG and sMMG amplitude and MPF of the dominant limb were examined using linear mixed effect models. There were no differences in time-to-task failure between males and females. Additionally, neuromuscular responses revealed similar patterns of responses between males and females. Interestingly, sEMG amplitude and sMMG amplitude and MPF all revealed non-linear responses, while sEMG MPF demonstrated linear responses. These data revealed that time-to-task failure was not different between males and females during sustained submaximal bilateral, isometric leg extension. Interestingly, the parallel, non-linear, increases in sEMG and sMMG amplitude may indicate fatigue induced increases in motor unit recruitment, while the parallel decreases in sMMG MPF may be explained by the intrinsic properties of later recruited motor units, which may have inherently lower firing rates than those recruited earlier.

Theta Phase Precession and the Dynamics of Spatiotemporal Asymmetry in Hippocampal Place Fields

A consistently observed characteristic of hippocampal place fields is the shifting of the field's center of mass and the subsequent development of asymmetry. This is evidenced by the expansion of the place field in an asymmetric manner over repeated traversals, wherein a rat's initial entry into the field prompts a low firing rate that substantially increases as it exits. Our study delves deeper into these spatiotemporal asymmetries of place field spiking, specifically examining their relationship with theta oscillations and disentangling the effects from environmental factors. Analysis of neuronal data from a T-maze alternation task revealed a distinct non-uniform firing pattern of place cells. This pattern was markedly skewed in relation to the phases of theta cycles, indicating a phase precession effect. We found that as the rat navigates through the place field, there is a systematic advancement of spike timing, with action potentials tending to cluster in the early phases of theta during the exit phase of the field. Such temporal coordination of spikes suggests that the timing of neural activity within theta cycles is as integral as spatial location, influencing the dynamics of place field expansion and potentially affecting the hippocampal local field potential. This discovery underscores the role of theta phase precession in spatial encoding, proposing a novel temporal component that could underpin the cognitive map within the hippocampus. R01 MH126236 R01 AG055544. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Electrophysiology and 3D-imaging reveal properties of human intracardiac neurons and increased excitability with atrial fibrillation.

Altered autonomic input to the heart plays a major role in atrial fibrillation (AF). Autonomic neurons termed ganglionated plexi (GP) are clustered on the heart surface to provide the last point of neural control of cardiac function. To date the properties of GP neurons in humans are unknown. Here we have addressed this knowledge gap in human GP neuron structure and physiology in patients with and without AF. Human right atrial GP neurons embedded in epicardial adipose tissue were excised during open heart surgery performed on both non-AF and AF patients and then characterised physiologically by whole cell patch clamp techniques. Structural analysis was also performed after fixation at both the single cell and at the entire GP levels via three-dimensional confocal imaging. Human GP neurons were found to exhibit unique properties and structural complexity with branched neurite outgrowth. Significant differences in excitability were revealed between AF and non-AF GP neurons as measured by lower current to induce action potential firing, a reduced occurrence of low action potential firing rates, decreased accommodation and increased synaptic density. Visualisation of entire GPs showed almost all neurons are cholinergic with a small proportion of noradrenergic and dual phenotype neurons. Phenotypic distribution differences occurred with AF including decreased cholinergic and dual phenotype neurons, and increased noradrenergic neurons. These data show both functional and structural differences occur between GP neurons from patients with and without AF, highlighting that cellular plasticity occurs in neural input to the heart that could alter autonomic influence on atrial function. KEY POINTS: The autonomic nervous system plays a critical role in regulating heart rhythm and the initiation of AF; however, the structural and functional properties of human autonomic neurons in the autonomic ganglionated plexi (GP) remain unknown. Here we perform the first whole cell patch clamp electrophysiological and large tissue confocal imaging analysis of these neurons from patients with and without AF. Our data show human GP neurons are functionally and structurally complex. Measurements of action potential kinetics show higher excitability in GP neurons from AF patients as measured by lower current to induce action potential firing, reduced low firing action potential rates, and decreased action potential accommodation. Confocal imaging shows increased synaptic density and noradrenergic phenotypes in patients with AF. Both functional and structural differences occur in GP neurons from patients with AF that could alter autonomic influence on atrial rhythm.

Exact low-dimensional description for fast neural oscillations with low firing rates.

Recently, low-dimensional models of neuronal activity have been exactly derived for large networks of deterministic, quadratic integrate-and-fire (QIF) neurons. Such firing rate models (FRM) describe the emergence of fast collective oscillations (>30Hz) via the frequency locking of a subset of neurons to the global oscillation frequency. However, the suitability of such models to describe realistic neuronal states is seriously challenged by the fact that during episodes of fast collective oscillations, neuronal discharges are often very irregular and have low firing rates compared to the global oscillation frequency. Here we extend the theory to derive exact FRM for QIF neurons to include noise and show that networks of stochastic neurons displaying irregular discharges at low firing rates during episodes of fast oscillations are governed by exactly the same evolution equationsas deterministic networks. Our results reconcile two traditionally confronted views on neuronal synchronization and upgrade the applicability of exact FRM to describe a broad range of biologically realistic neuronal states.

Menstrual Cycle Associated Alteration of Vastus Lateralis Motor Unit Function

BackgroundEstrogen and progesterone are the primary female sex hormones and have net excitatory and inhibitory effects, respectively, on neuronal function. Fluctuating concentrations across the menstrual cycle has led to several lines of research in relation to neuromuscular function and performance; however evidence from animal and cell culture models has yet to be demonstrated in human motor units coupled with quantification of circulating hormones. Intramuscular electromyography was used to record motor unit potentials and corresponding motor unit potential trains from the vastus lateralis of nine eumenorrheic females during the early follicular, ovulation and mid luteal phases of the menstrual cycle, alongside assessments of neuromuscular performance. Multi-level regression models were applied to explore effects of time and of contraction level. Statistical significance was accepted as p < 0.05.ResultsKnee extensor maximum voluntary contraction, jump power, force steadiness, and balance did not differ across the menstrual phases (all p > 0.4). Firing rate of low threshold motor units (10% maximum voluntary contraction) was lower during the ovulation and mid luteal phases (β = − 0.82 Hz, p < 0.001), with no difference in motor unit potentials analysed from 25% maximum voluntary contraction contractions. Motor unit potentials were more complex during ovulation and mid luteal phase (p < 0.03), with no change in neuromuscular junction transmission instability (p > 0.3).ConclusionsAssessments of neuromuscular performance did not differ across the menstrual cycle. The suppression of low threshold motor unit firing rate during periods of increased progesterone may suggest a potential inhibitory effect and an alteration of recruitment strategy; however this had no discernible effect on performance. These findings highlight contraction level-dependent modulation of vastus lateralis motor unit function over the eumenorrheic cycle, occurring independently of measures of performance.

Adaptive spike threshold dynamics associated with sparse spiking of hilar mossy cells are captured by a simple model.

Hilar mossy cells (hMCs) in the dentate gyrus (DG) receive inputs from DG granule cells (GCs), CA3 pyramidal cells and inhibitory interneurons, and provide feedback input to GCs. Behavioural and in vivo recording experiments implicate hMCs in pattern separation, navigation and spatial learning. Our experiments link hMC intrinsic excitability to their synaptically evoked in vivo spiking outputs. We performed electrophysiological recordings from DG neurons and found that hMCs displayed an adaptative spike threshold that increased both in proportion to the intensity of injected currents, and in response to spiking itself, returning to baseline over a long time scale, thereby instantaneously limiting their firing rate responses. The hMC activity is additionally limited by a prominent medium after-hyperpolarizing potential (AHP) generated by small conductance K+ channels. We hypothesize that these intrinsic hMC properties are responsible for their low in vivo firing rates. Our findings extend previous studies that compare hMCs, CA3 pyramidal cells and hilar inhibitory cells and provide novel quantitative data that contrast the intrinsic properties of these cell types. We developed a phenomenological exponential integrate-and-fire model that closely reproduces the hMC adaptive threshold nonlinearities with respect to their threshold dependence on input current intensity, evoked spike latency and long-lasting spike-induced increase in spike threshold. Our robust and computationally efficient model is amenable to incorporation into large network models of the DG that will deepen our understanding of the neural bases of pattern separation, spatial navigation and learning. KEY POINTS: Previous studies have shown that hilar mossy cells (hMCs) are implicated in pattern separation and the formation of spatial memory, but how their intrinsic properties relate to their in vivo spiking patterns is still unknown. Here we show that the hMCs display electrophysiological properties that distinguish them from the other hilar cell types including a highly adaptive spike threshold that decays slowly. The spike-dependent increase in threshold combined with an after-hyperpolarizing potential mediated by a slow K+ conductance is hypothesized to be responsible for the low-firing rate of the hMC observed in vivo. The hMC's features are well captured by a modified stochastic exponential integrate-and-fire model that has the unique feature of a threshold intrinsically dependant on both the stimulus intensity and the spiking history. This computational model will allow future work to study how the hMCs can contribute to spatial memory formation and navigation.

Sialic acid biosynthesis pathway blockade disturbs neuronal network formation in human iPSC-derived excitatory neurons.

N-acetylneuraminic acid (sialic acid) is present in large quantities in the brain and plays a crucial role in brain development, learning, and memory formation. How sialic acid contributes to brain development is not fully understood. The purpose of this study was to determine the effects of reduced sialylation on network formation in human iPSC-derived neurons (iNeurons). Using targeted mass spectrometry and antibody binding, we observed an increase in free sialic acid and polysialic acid during neuronal development, which was disrupted by treatment of iNeurons with a synthetic inhibitor of sialic acid biosynthesis. Sialic acid inhibition disturbed synapse formation and network formation on microelectrode array (MEA), showing short but frequent (network) bursts and an overall lower firing rate, and higher percentage of random spikes. This study shows that sialic acid is necessary for neuronal network formation during human neuronal development and provides a physiologically relevant model to study the role of sialic acid in patient-derived iNeurons.

Membrane potential dynamics of excitatory and inhibitory neurons in mouse barrel cortex during active whisker sensing.

Neocortical neurons can increasingly be divided into well-defined classes, but their activity patterns during quantified behavior remain to be fully determined. Here, we obtained membrane potential recordings from various classes of excitatory and inhibitory neurons located across different cortical depths in the primary whisker somatosensory barrel cortex of awake head-restrained mice during quiet wakefulness, free whisking and active touch. Excitatory neurons, especially those located superficially, were hyperpolarized with low action potential firing rates relative to inhibitory neurons. Parvalbumin-expressing inhibitory neurons on average fired at the highest rates, responding strongly and rapidly to whisker touch. Vasoactive intestinal peptide-expressing inhibitory neurons were excited during whisking, but responded to active touch only after a delay. Somatostatin-expressing inhibitory neurons had the smallest membrane potential fluctuations and exhibited hyperpolarising responses at whisking onset for superficial, but not deep, neurons. Interestingly, rapid repetitive whisker touch evoked excitatory responses in somatostatin-expressing inhibitory neurons, but not when the intercontact interval was long. Our analyses suggest that distinct genetically-defined classes of neurons at different subpial depths have differential activity patterns depending upon behavioral state providing a basis for constraining future computational models of neocortical function.

Electromyographic and mechanomyographic responses of the biceps brachii during concentric and eccentric muscle actions to failure at high and low relative loads.

This study examined neuromuscular responses of the biceps brachii (BB) for concentric and eccentric muscle actions during bilateral, dynamic constant external resistance (DCER), reciprocal forearm flexions and extensions to failure at high (80% 1 repetition maximum [1RM]) and low (30% 1RM) relative loads. Nine women completed 1RM testing and repetitions to failure (RTF) at 30 and 80% 1RM. Electromyographic (EMG) and mechanomyographic (MMG) amplitude (AMP) and mean power frequency (MPF) signals were measured from the BB. Analyses included repeated measures ANOVAs (p < 0.05) and post-hoc pairwise comparisons with Bonferroni corrected alpha of p < 0.008 and p < 0.01 for between and within factor pairwise comparisons, respectively. EMG AMP and MPF were significantly greater for concentric than eccentric muscle actions, regardless of load or time. However, time course of change analysis revealed parallel increases in EMG AMP for concentric and eccentric muscle actions during the RTF trials at 30% 1RM, but no change at 80% 1RM. There were significant increases in MMG AMP during concentric muscle actions, but decreases or no change during eccentric muscle actions. EMG and MMG MPF decreased over time, regardless of muscle action type and loading condition. The greater EMG AMP and MPF values during concentric compared to eccentric muscle actions may reflect the difference in the efficiency characteristic of these muscle actions. The neuromuscular responses suggested that fatigue may be mediated by recruitment of additional motor units with lower firing rates during concentric muscle actions, and changes in motor unit synchronization during eccentric muscle actions.

Calbindin-Expressing CA1 Pyramidal Neurons Encode Spatial Information More Efficiently.

Hippocampal pyramidal neurons (PNs) are traditionally conceptualized as homogeneous population. For the past few years, cumulating evidence has revealed the structural and functional heterogeneity of hippocampal pyramidal neurons. But the in vivo neuronal firing pattern of molecularly identified pyramidal neuron subclasses is still absent. In this study, we investigated the firing patterns of hippocampal PNs based on different expression profile of Calbindin (CB) during a spatial shuttle task in free moving male mice. We found that CB+ place cells can represent spatial information more efficiently than CB- place cells, albeit lower firing rates during running epochs. Furthermore, a subset of CB+ PNs shifted their theta firing phase during rapid-eye movement (REM) sleep states compared with running states. Although CB- PNs are more actively engaged in ripple oscillations, CB+ PNs showed stronger ripple modulation during slow-wave sleep (SWS). Our results pointed out the heterogeneity in neuronal representation between hippocampal CB+ and CB- PNs. Particularly, CB+ PNs encode spatial information more efficiently, which might be contributed by stronger afferents from the lateral entorhinal cortex to CB+ PNs.

Biophysical parameters control signal transfer in spiking network.

Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer. The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error. Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates. Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.

ERR2 and ERR3 promote the development of gamma motor neuron functional properties required for proprioceptive movement control

The ability of terrestrial vertebrates to effectively move on land is integrally linked to the diversification of motor neurons into types that generate muscle force (alpha motor neurons) and types that modulate muscle proprioception, a task that in mammals is chiefly mediated by gamma motor neurons. The diversification of motor neurons into alpha and gamma types and their respective contributions to movement control have been firmly established in the past 7 decades, while recent studies identified gene expression signatures linked to both motor neuron types. However, the mechanisms that promote the specification of gamma motor neurons and/or their unique properties remained unaddressed. Here, we found that upon selective loss of the orphan nuclear receptors ERR2 and ERR3 (also known as ERRβ, ERRγ or NR3B2, NR3B3, respectively) in motor neurons in mice, morphologically distinguishable gamma motor neurons are generated but do not acquire characteristic functional properties necessary for regulating muscle proprioception, thus disrupting gait and precision movements. Complementary gain-of-function experiments in chick suggest that ERR2 and ERR3 could operate via transcriptional activation of neural activity modulators to promote a gamma motor neuron biophysical signature of low firing thresholds and high firing rates. Our work identifies a mechanism specifying gamma motor neuron functional properties essential for the regulation of proprioceptive movement control.

Sleep and wake in a model of the thalamocortical system with Martinotti cells.

The mechanisms leading to the alternation between active (UP) and silent (DOWN) states during sleep slow waves (SWs) remain poorly understood. Previous models have explained the transition to the DOWN state by a progressive failure of excitation because of the build-up of adaptation currents or synaptic depression. However, these models are at odds with recent studies suggesting a role for presynaptic inhibition by Martinotti cells (MaCs) in generating SWs. Here, we update a classical large-scale model of sleep SWs to include MaCs and propose a different mechanism for the generation of SWs. In the wake mode, the network exhibits irregular and selective activity with low firing rates (FRs). Following an increase in the strength of background inputs and a modulation of synaptic strength and potassium leak potential mimicking the reduced effect of acetylcholine during sleep, the network enters a sleep-like regime in which local increases of network activity trigger bursts of MaC activity, resulting in strong disfacilitation of the local network via presynaptic GABAB1a -type inhibition. This model replicates findings on slow wave activity (SWA) during sleep that challenge previous models, including low and skewed FRs that are comparable between the wake and sleep modes, higher synchrony of transitions to DOWN states than to UP states, the possibility of triggering SWs by optogenetic stimulation of MaCs, and the local dependence of SWA on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.