Two distinct proprioceptive representations of voluntary movements in primate spinal neurons

When willingly setting our body in motion, we simultaneously know where and how our limbs are moving. While this indicates that proprioceptive information is readily represented in the neurons of the central nervous system, it is still unclear how. We recorded the activity of spinal neurons with direct projections from muscle spindle afferents in four monkeys, while they performed simple wrist movements. Against the assumption that these spinal neurons act as a simple relay of afferent input, we found the majority (56%) of neurons had firing patterns incongruent with a simple representation of spindle activity, and the minority had congruent patterns. Two groups of neurons showed distinct intrinsic characteristics (spike width, base firing rate and firing irregularity), and distinct control of their input-output gain. These results are the first demonstration that proprioceptive representation is achieved by the coordinated activity of distinct groups of neurons during volitional movement.

Models of utricular bouton afferents: role of afferent-hair cell connectivity in determining spike train regularity

Vestibular bouton afferent terminals in turtle utricle can be categorized into four types depending on their location and terminal arbor structure: lateral extrastriolar (LES), striolar, juxtastriolar, and medial extrastriolar (MES). The terminal arbors of these afferents differ in surface area, total length, collecting area, number of boutons, number of bouton contacts per hair cell, and axon diameter (Huwe JA, Logan CJ, Williams B, Rowe MH, Peterson EH. J Neurophysiol 113: 2420–2433, 2015). To understand how differences in terminal morphology and the resulting hair cell inputs might affect afferent response properties, we modeled representative afferents from each region, using reconstructed bouton afferents. Collecting area and hair cell density were used to estimate hair cell-to-afferent convergence. Nonmorphological features were held constant to isolate effects of afferent structure and connectivity. The models suggest that all four bouton afferent types are electrotonically compact and that excitatory postsynaptic potentials are two to four times larger in MES afferents than in other afferents, making MES afferents more responsive to low input levels. The models also predict that MES and LES terminal structures permit higher spontaneous firing rates than those in striola and juxtastriola. We found that differences in spike train regularity are not a consequence of differences in peripheral terminal structure, per se, but that a higher proportion of multiple contacts between afferents and individual hair cells increases afferent firing irregularity. The prediction that afferents having primarily one bouton contact per hair cell will fire more regularly than afferents making multiple bouton contacts per hair cell has implications for spike train regularity in dimorphic and calyx afferents. NEW & NOTEWORTHY Bouton afferents in different regions of turtle utricle have very different morphologies and afferent-hair cell connectivities. Highly detailed computational modeling provides insights into how morphology impacts excitability and also reveals a new explanation for spike train irregularity based on relative numbers of multiple bouton contacts per hair cell. This mechanism is independent of other proposed mechanisms for spike train irregularity based on ionic conductances and can explain irregularity in dimorphic units and calyx endings.

Flocculus Purkinje cell signals in mouse Cacna1a calcium channel mutants of escalating severity: an investigation of the role of firing irregularity in ataxia

Mutation of the Cacna1a gene for the P/Q (CaV2.1) calcium channel invariably leads to cerebellar dysfunction. The dysfunction has been attributed to disrupted rhythmicity of cerebellar Purkinje cells, but the hypothesis remains unproven. If irregular firing rates cause cerebellar dysfunction, then the irregularity and behavioral deficits should covary in a series of mutant strains of escalating severity. We compared firing irregularity in floccular and anterior vermis Purkinje cells in the mildly affected rocker and moderately affected tottering Cacna1a mutants and normal C57BL/6 mice. We also measured the amplitude and timing of modulations of floccular Purkinje cell firing rate during the horizontal vestibuloocular reflex (VOR, 0.25–1 Hz) and the horizontal and vertical optokinetic reflex (OKR, 0.125–1 Hz). We recorded Purkinje cells selective for rotational stimulation about the vertical axis (VAPCs) and a horizontal axis (HAPCs). Irregularity scaled with behavioral deficit severity in the flocculus but failed to do so in the vermis, challenging the irregularity hypothesis. Mutant VAPCs exhibited unusually strong modulation during VOR and OKR, the response augmentation scaling with phenotypic severity. HAPCs exhibited increased OKR modulation but in tottering only. The data contradict prior claims that modulation amplitude is unaffected in tottering but support the idea that attenuated compensatory eye movements in Cacna1a mutants arise from defective transfer of Purkinje cell signals to downstream circuitry, rather than attenuated synaptic transmission within the cerebellar cortex. Shifts in the relative sizes of the VAPC and HAPC populations raise the possibility that Cacna1a mutations influence the development of floccular zone architecture.

Does High Firing Irregularity Enhance Learning?

In this note, we demonstrate that the high firing irregularity produced by the leaky integrate-and-fire neuron with the partial somatic reset mechanism, which has been shown to be the most likely candidate to reflect the mechanism used in the brain for reproducing the highly irregular cortical neuron firing at high rates (Bugmann, Christodoulou, & Taylor, 1997 ; Christodoulou & Bugmann, 2001 ), enhances learning. More specifically, it enhances reward-modulated spike-timing-dependent plasticity with eligibility trace when used in spiking neural networks, as shown by the results when tested in the simple benchmark problem of XOR, as well as in a complex multiagent setting task.

Estimating Network Parameters From Combined Dynamics of Firing Rate and Irregularity of Single Neurons

High firing irregularity is a hallmark of cortical neurons in vivo, and modeling studies suggest a balance of excitation and inhibition is necessary to explain this high irregularity. Such a balance must be generated, at least partly, from local interconnected networks of excitatory and inhibitory neurons, but the details of the local network structure are largely unknown. The dynamics of the neural activity depends on the local network structure; this in turn suggests the possibility of estimating network structure from the dynamics of the firing statistics. Here we report a new method to estimate properties of the local cortical network from the instantaneous firing rate and irregularity (CV2) under the assumption that recorded neurons are a part of a randomly connected sparse network. The firing irregularity, measured in monkey motor cortex, exhibits two features; many neurons show relatively stable firing irregularity in time and across different task conditions; the time-averaged CV2 is widely distributed from quasi-regular to irregular (CV2 = 0.3–1.0). For each recorded neuron, we estimate the three parameters of a local network [balance of local excitation-inhibition, number of recurrent connections per neuron, and excitatory postsynaptic potential (EPSP) size] that best describe the dynamics of the measured firing rates and irregularities. Our analysis shows that optimal parameter sets form a two-dimensional manifold in the three-dimensional parameter space that is confined for most of the neurons to the inhibition-dominated region. High irregularity neurons tend to be more strongly connected to the local network, either in terms of larger EPSP and inhibitory PSP size or larger number of recurrent connections, compared with the low irregularity neurons, for a given excitatory/inhibitory balance. Incorporating either synaptic short-term depression or conductance-based synapses leads many low CV2 neurons to move to the excitation-dominated region as well as to an increase of EPSP size.

Estimating Instantaneous Irregularity of Neuronal Firing

Cortical neurons in vivo had been regarded as Poisson spike generators that convey no information other than the rate of random firing. Recently, using a metric for analyzing local variation of interspike intervals, researchers have found that individual neurons express specific patterns in generating spikes, which may symbolically be termed regular, random, or bursty, rather invariantly in time. In order to study the dynamics of firing patterns in greater detail, we propose here a Bayesian method for estimating firing irregularity and the firing rate simultaneously for a given spike sequence, and we implement an algorithm that may render the empirical Bayesian estimation practicable for data comprising a large number of spikes. Application of this method to electrophysiological data revealed a subtle correlation between the degree of firing irregularity and the firing rate for individual neurons. Irregularity of firing did not deviate greatly around the low degree of dependence on the firing rate and remained practically unchanged for individual neurons in the cortical areas V1 and MT, whereas it fluctuated greatly in the lateral geniculate nucleus of the thalamus. This indicates the presence and absence of autocontrolling mechanisms for maintaining patterns of firing in the cortex and thalamus, respectively.