Influence of data sampling methods on the representation of neural spiking activity in vivo

In vivo single-unit recordings distinguish the basal spiking properties of neurons in different experimental settings and disease states. Here, we examined over 300 spike trains recorded from Purkinje cells and cerebellar nuclei neurons to test whether data sampling approaches influence the extraction of rich descriptors of firing properties. Our analyses included neurons recorded in awake and anesthetized control mice, as well as disease models of ataxia, dystonia, and tremor. We find that recording duration circumscribes overall representations of firing rate and pattern. Notably, shorter recording durations skew estimates for global firing rate variability towards lower values. We also find that only some populations of neurons in the same mouse are more similar to each other than to neurons recorded in different mice. These data reveal that recording duration and approach are primary considerations when interpreting task-independent single-neuron firing properties. If not accounted for, group differences may be concealed or exaggerated.

IGF1 Receptor Regulates Upward Firing Rate Homeostasis via the Mitochondrial Calcium Uniporter

Regulation of firing rate homeostasis constitutes a fundamental property of central neural circuits. While intracellular Ca2+ has long been hypothesized to be a feedback control signal, the molecular machinery enabling network-wide homeostatic response remains largely unknown. Here we show that deletion of insulin-like growth factor-1 receptor (IGF1R), a well-known regulator of neurodevelopment and ageing, limits firing rate homeostasis in response to inactivity, without altering the baseline firing rate distribution. Disruption of both synaptic and intrinsic homeostatic plasticity contributed to deficient firing rate homeostatic response. At the cellular level, a fraction of IGF1Rs was localized in mitochondria with the mitochondrial calcium uniporter complex (MCUc). IGF1R deletion suppressed mitochondrial Ca2+ (mitoCa2+) evoked by spike bursts by weakening mitochondria-to-cytosol Ca2+ coupling. This coupling was homeostatically maintained following inactivity in control, but upregulated in IGF1R-deficient neurons. MCUc overexpression in IGF1R-deficient neurons rescued the deficits in spike-to-mitoCa2+ coupling and firing rate homeostasis. Our findings highlight IGF1R as a key regulator of the integrated homeostatic response by tuning mitochondrial temporal filtering. Decline in mitochondrial reliability for burst transfer may drive dysregulation of firing rate homeostasis in brain disorders associated with abnormal IGF1R / MCUc signaling.

Non-monotonic effects of GABAergic synaptic inputs on neuronal firing

GABA is canonically known as the principal inhibitory neurotransmitter in the nervous system, usually acting by hyper-polarizing membrane potential. However, GABAergic currents can also exhibit non-inhibitory effects, depending on the brain region, developmental stage or pathological condition. Here, we investigate the diverse effects of GABA on the firing rate of several single neuron models, using both analytical calculations and numerical simulations. We find that the relationship between GABAergic synaptic conductance and output firing rate exhibits three qualitatively different regimes as a function of GABA reversal potential, νGABA: monotonically decreasing for sufficiently low νGABA (inhibitory), monotonically increasing for νGABA above firing threshold (excitatory); and a non-monotonic region for intermediate values of νGABA. In the non-monotonic regime, small GABA conductances have an excitatory effect while large GABA conductances show an inhibitory effect. We provide a phase diagram of different GABAergic effects as a function of GABA reversal potential and glutamate conductance. We find that noisy inputs increase the range of νGABA for which the non-monotonic effect can be observed. We also construct a micro-circuit model of striatum to explain observed effects of GABAergic fast spiking interneurons on spiny projection neurons, including non-monotonicity, as well as the heterogeneity of the effects. Our work provides a mechanistic explanation of paradoxical effects of GABAergic synaptic inputs, with implications for understanding the effects of GABA in neural computation and development.

The Increased In Vivo Firing of Pyramidal Cells But not Interneurons in the Anterior Cingulate Cortex After Neuropathic Pain

Chronic pain damages the balance between excitation and inhibition in the sensory cortex. It has been confirmed that the activity of cortical glutamatergic pyramidal cells increases after chronic pain. However, whether the activity of inhibitory interneurons synchronized changed remains obscure, especially in in vivo conditions. In the present study, we checked the firing rate of pyramidal cells and interneurons in the anterior cingulate cortex, a main cortical area for the regulation of nociceptive information in mice with spared nerve injury by using in vivo multi-channel recording system. We found that the firing rate of pyramidal cells but not interneurons increased in the ACC, which is further confirmed by the increased FOS expression in pyramidal cells but not interneurons, in mice with neuropathic pain. Selectively high frequency stimulation of the ACC nociceptive afferent fibers only potentiated the activity of pyramidal cells either. Our results thus suggest that the increased activity of pyramidal cells contributes to the damaged E/I balance in the ACC and is important for the pain hypersensitivity in mice with neuropathic pain.

Differential Effects of the Lateral Hypothalamus Lesion as an Origin of Orexin and Blockade of Orexin-1 Receptor in the Orbitoftontal Cortex and Anterior Cingulate Cortex on Their Neuronal Activity

Several studies revealed that orexins may take part in the regulation of the different forms of affective and cognitive processes during wakefulness. The orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC) as an important part of the prefrontal cortex (PFC) have a crucial role in cognitive processes such as reward and decision-making and has a high density of orexin receptor type 1 (OX1Rs). In the present study, to find out the role of OX1Rs in the OFC neurons firing rate, the OX1Rs were inhibited in this area after a10-min baseline recording. In the second part, the lateral hypothalamus (LH) as the main source of orexinergic neurons was inhibited and its effect on the firing rate and activity pattern of the ACC or OFC neurons were detected by using single-unit recording technique in the rats. Results showed that blockade of OX1Rs in the OFC could excite 8 and inhibit 1 neuron out of 11. Besides, the blockade of OX1Rs in the ACC could excite 6 and inhibit 3 neurons out of 10. Also, LH inactivation excited 5 out of 12 neurons and inhibited 6 neurons in the ACC. It excited 8 and inhibited 6 neurons out of 14 in the OFC. These data suggested that blockade of the OX1Rs excited 72% of the neurons, but LH inactivation had an exciting effect on just 50% of neurons in two main subregions of PFC. It seems that the PFC neurons receive the orexinergic inputs from the LH and indirectly from other sources.

Circulating testosterone and dehydroepiandrosterone are associated with individual motor unit features in untrained and highly active older men

Long-term exercise training has been considered as an effective strategy to counteract age-related hormonal declines and minimise muscle atrophy. However, human data relating circulating hormone levels with motor nerve function are scant. The aims of the study were to explore associations between circulating sex hormone levels and motor unit (MU) characteristics in older men, including masters athletes competing in endurance and power events. Forty-three older men (mean ± SD age: 69.9 ± 4.6 years) were studied based on competitive status. The serum concentrations of dehydroepiandrosterone (DHEA), total testosterone (T) and estradiol were quantified using liquid chromatography mass spectrometry. Intramuscular electromyographic signals were recorded from vastus lateralis (VL) during 25% of maximum voluntary isometric contractions and processed to extract MU firing rate (FR), and motor unit potential (MUP) features. After adjusting for athletic status, MU FR was positively associated with DHEA levels (p = 0.019). Higher testosterone and estradiol were associated with lower MUP complexity; these relationships remained significant after adjusting for athletic status (p = 0.006 and p = 0.019, respectively). Circulating DHEA was positively associated with MU firing rate in these older men. Higher testosterone levels were associated with reduced MUP complexity, indicating reduced electrophysiological temporal dispersion, which is related to decreased differences in conduction times along axonal branches and/or MU fibres. Although evident in males only, this work highlights the potential of hormone administration as a therapeutic interventional strategy specifically targeting human motor units in older age.

Closed-loop Controller Based on Reference Signal Tracking for Absence Seizures

Deep brain stimulation (DBS) targeting thalamus reticular nucleus (TRN) brain regions has been proven to play an irreplaceable role in the treatment of absence seizures. Compared with open-loop DBS, closed-loop DBS has been recognized by researchers for its advantages of significantly inhibiting seizures and having fewer side effects. However, due to the complexity of the nervous system, the mechanism of DBS control epilepsy is still unclear, which hinders the study of closed-loop DBS. In our study, based on the biophysical model jointly constituted by cortical, thalamic, and basal ganglia, we selected the 2-4 Hz spike and wave discharges (SWDs) of the cortical region as a biomarker for response to absence epilepsy, and the mean firing rate (MFR) of substantia nigra pars reticulata (SNr) was used as a reference signal for modulation of closed-loop DBS. Moreover, to obtain the linear relationship between the stimulus and the response, we adopted an algorithm that combines controlled auto-regressive (CAR) and recursive least squares (RLS), and we built a proportional integral (PI) controller to make the DBS stimulus parameters self-update to control the seizures. The numerical simulation results show that the closed-loop DBS controllers based on frequency modulation and amplitude modulation respectively not only successfully track the firing rate (FR) of SNr, but also significantly destroy the SWDs of cerebral cortex and restore it to the other two normal discharge modes.

Complexity Collapse, Fluctuating Synchrony, and Transient Chaos in Neural Networks With Delay Clusters

Neural circuits operate with delays over a range of time scales, from a few milliseconds in recurrent local circuitry to tens of milliseconds or more for communication between populations. Modeling usually incorporates single fixed delays, meant to represent the mean conduction delay between neurons making up the circuit. We explore conditions under which the inclusion of more delays in a high-dimensional chaotic neural network leads to a reduction in dynamical complexity, a phenomenon recently described as multi-delay complexity collapse (CC) in delay-differential equations with one to three variables. We consider a recurrent local network of 80% excitatory and 20% inhibitory rate model neurons with 10% connection probability. An increase in the width of the distribution of local delays, even to unrealistically large values, does not cause CC, nor does adding more local delays. Interestingly, multiple small local delays can cause CC provided there is a moderate global delayed inhibitory feedback and random initial conditions. CC then occurs through the settling of transient chaos onto a limit cycle. In this regime, there is a form of noise-induced order in which the mean activity variance decreases as the noise increases and disrupts the synchrony. Another novel form of CC is seen where global delayed feedback causes “dropouts,” i.e., epochs of low firing rate network synchrony. Their alternation with epochs of higher firing rate asynchrony closely follows Poisson statistics. Such dropouts are promoted by larger global feedback strength and delay. Finally, periodic driving of the chaotic regime with global feedback can cause CC; the extinction of chaos can outlast the forcing, sometimes permanently. Our results suggest a wealth of phenomena that remain to be discovered in networks with clusters of delays.

Memories in a network with excitatory and inhibitory plasticity are encoded in the spiking irregularity

Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have previously shown that assemblies can be formed in networks with multiple types of plasticity. But how exactly they are formed and how they encode information is yet to be fully understood. One possibility is that memories are stored in silent assemblies. Here we used a computational model to study the formation of silent assemblies in a network of spiking neurons with excitatory and inhibitory plasticity. We found that even though the formed assemblies were silent in terms of mean firing rate, they had an increased coefficient of variation of inter-spike intervals. We also found that this spiking irregularity could be read out with support of short-term plasticity, and that it could contribute to the longevity of memories.