Quantifying neural coding of event timing

Intermuscular Coherence in the Presence of Electrical Stimulation

The nervous system uses oscillations to convey information efficiently. Inter-muscular coherence in the 15-35 Hz range is thought to represent common cortical drive to muscles, but is also in the frequency band in which electrical stimulation is applied to restore movement following neurological disease or injury. We wished to determine if, when stimulation is applied at the peak frequency of the coherence spectra it was still possible to determine voluntary effort. Using healthy human subjects we stimulated muscles in the arms and legs, separate experiments, while recording EMG activity from pairs of muscles including the stimulated muscles. Offline coherence analysis was performed. When stimulation is greater than motor threshold, and applied at the peak of the coherence spectra a new peak appears in the spectra, presumably representing a new frequency of oscillation within the nervous system. This does not appear at lower stimulation levels, or with lower frequencies. The nervous system is capable of switching oscillatory frequencies to account for noise in the environment.

The unsolved role of heightened connectivity from the unaffected hemisphere to paretic arm muscles in chronic stroke

OBJECTIVE

Ipsilateral connectivity from the non-stroke hemisphere to paretic arm muscles appears to play little role in functional recovery, which instead depends on contralateral connectivity from the stroke hemisphere. Yet the incidence of ipsilateral projections in stroke survivors is often reported to be higher than normal. We tested this directly using a sensitive measure of connectivity to proximal arm muscles.

METHOD

TMS of the stroke and non-stroke motor cortex evoked responses in pre-activated triceps and deltoid muscles of 17 stroke survivors attending reaching training. Connectivity was defined as a clear MEP or a short-latency silent period in ongoing EMG in ≥ 50% of stimulations. We measured reaching accuracy at baseline, improvement after training and upper limb Fugl-Meyer (F-M) score.

RESULTS

Incidence of ipsilateral connections to triceps (47%) and deltoid (58%) was high, but unrelated to baseline reaching accuracy and F-M scores. Instead, these were related to contralateral connectivity from the stroke hemisphere. Absolute but not proportional improvement after training was greater in patients with ipsilateral responses.

CONCLUSIONS

Despite enhanced ipsilateral connectivity, arm function and learning was related most strongly to contralateral pathway integrity from the stroke hemisphere.

SIGNIFICANCE

Further work is needed to decipher the role of ipsilateral connections.

Estimation of neuronal firing rate using Bayesian Adaptive Kernel Smoother (BAKS)

Neurons use sequences of action potentials (spikes) to convey information across neuronal networks. In neurophysiology experiments, information about external stimuli or behavioral tasks has been frequently characterized in term of neuronal firing rate. The firing rate is conventionally estimated by averaging spiking responses across multiple similar experiments (or trials). However, there exist a number of applications in neuroscience research that require firing rate to be estimated on a single trial basis. Estimating firing rate from a single trial is a challenging problem and current state-of-the-art methods do not perform well. To address this issue, we develop a new method for estimating firing rate based on a kernel smoothing technique that considers the bandwidth as a random variable with prior distribution that is adaptively updated under an empirical Bayesian framework. By carefully selecting the prior distribution together with Gaussian kernel function, an analytical expression can be achieved for the kernel bandwidth. We refer to the proposed method as Bayesian Adaptive Kernel Smoother (BAKS). We evaluate the performance of BAKS using synthetic spike train data generated by biologically plausible models: inhomogeneous Gamma (IG) and inhomogeneous inverse Gaussian (IIG). We also apply BAKS to real spike train data from non-human primate (NHP) motor and visual cortex. We benchmark the proposed method against established and previously reported methods. These include: optimized kernel smoother (OKS), variable kernel smoother (VKS), local polynomial fit (Locfit), and Bayesian adaptive regression splines (BARS). Results using both synthetic and real data demonstrate that the proposed method achieves better performance compared to competing methods. This suggests that the proposed method could be useful for understanding the encoding mechanism of neurons in cognitive-related tasks. The proposed method could also potentially improve the performance of brain-machine interface (BMI) decoder that relies on estimated firing rate as the input.

Corticospinal gating during action preparation and movement in the primate motor cortex

During everyday actions there is a need to be able to withhold movements until the most appropriate time. This motor inhibition is likely to rely on multiple cortical and subcortical areas, but the primary motor cortex (M1) is a critical component of this process. However, the mechanisms behind this inhibition are unclear, particularly the role of the corticospinal system, which is most often associated with driving muscles and movement. To address this, recordings were made from identified corticospinal (PTN, n = 94) and corticomotoneuronal (CM, n = 16) cells from M1 during an instructed delay reach-to-grasp task. The task involved the animals withholding action for ~2 s until a GO cue, after which they were allowed to reach and perform the task for a food reward. Analysis of the firing of cells in M1 during the delay period revealed that, as a population, non-CM PTNs showed significant suppression in their activity during the cue and instructed delay periods, while CM cells instead showed a facilitation during the preparatory delay. Analysis of cell activity during movement also revealed that a substantial minority of PTNs (27%) showed suppressed activity during movement, a response pattern more suited to cells involved in withholding rather than driving movement. These results demonstrate the potential contributions of the M1 corticospinal system to withholding of actions and highlight that suppression of activity in M1 during movement preparation is not evenly distributed across different neural populations.

NEW & NOTEWORTHY Recordings were made from identified corticospinal (PTN) and corticomotoneuronal (CM) cells during an instructed delay task. Activity of PTNs as a population was suppressed during the delay, in contrast to CM cells, which were facilitated. A minority of PTNs showed a rate profile that might be expected from inhibitory cells and could suggest that they play an active role in action suppression, most likely through downstream inhibitory circuits.

Corticospinal Inputs to Primate Motoneurons Innervating the Forelimb from Two Divisions of Primary Motor Cortex and Area 3a

Previous anatomical work in primates has suggested that only corticospinal axons originating in caudal primary motor cortex ("new M1") and area 3a make monosynaptic cortico-motoneuronal connections with limb motoneurons. By contrast, the more rostral "old M1" is proposed to control motoneurons disynaptically via spinal interneurons. In six macaque monkeys, we examined the effects from focal stimulation within old and new M1 and area 3a on 135 antidromically identified motoneurons projecting to the upper limb. EPSPs with segmental latency shorter than 1.2 ms were classified as definitively monosynaptic; these were seen only after stimulation within new M1 or at the new M1/3a border (incidence 6.6% and 1.3%, respectively; total n = 27). However, most responses had longer latencies. Using measures of the response facilitation after a second stimulus compared with the first, and the reduction in response latency after a third stimulus compared with the first, we classified these late responses as likely mediated by either long-latency monosynaptic (n = 108) or non-monosynaptic linkages (n = 108). Both old and new M1 generated putative long-latency monosynaptic and non-monosynaptic effects; the majority of responses from area 3a were non-monosynaptic. Both types of responses from new M1 had significantly greater amplitude than those from old M1. We suggest that slowly conducting corticospinal fibers from old M1 generate weak late monosynaptic effects in motoneurons. These may represent a stage in control of primate motoneurons by the cortex intermediate between disynaptic output via an interposed interneuron seen in nonprimates and the fast direct monosynaptic connections present in new M1.

SIGNIFICANCE STATEMENT

The corticospinal tract in Old World primates makes monosynaptic connections to motoneurons; previous anatomical work suggests that these connections come only from corticospinal tract (CST) neurons in the subdivision of primary motor cortex within the central sulcus ("new M1") and area 3a. Here, we show using electrophysiology that cortico-motoneuronal connections from fast conducting CST fibers are indeed made exclusively from new M1 and its border with 3a. However, we also show that all parts of M1 and 3a have cortico-motoneuronal connections over more slowly conducting CST axons, as well as exert disynaptic effects on motoneurons via interposed interneurons. Differences between old and new M1 are thus more subtle than previously thought.

The Gamma renewal process as an output of the diffusion leaky integrate-and-fire neuronal model

Statistical properties of spike trains as well as other neurophysiological data suggest a number of mathematical models of neurons. These models range from entirely descriptive ones to those deduced from the properties of the real neurons. One of them, the diffusion leaky integrate-and-fire neuronal model, which is based on the Ornstein-Uhlenbeck (OU) stochastic process that is restricted by an absorbing barrier, can describe a wide range of neuronal activity in terms of its parameters. These parameters are readily associated with known physiological mechanisms. The other model is descriptive, Gamma renewal process, and its parameters only reflect the observed experimental data or assumed theoretical properties. Both of these commonly used models are related here. We show under which conditions the Gamma model is an output from the diffusion OU model. In some cases, we can see that the Gamma distribution is unrealistic to be achieved for the employed parameters of the OU process.

Variance Based Measure for Optimization of Parametric Realignment Algorithms

Neuronal responses to sensory stimuli or neuronal responses related to behaviour are often extracted by averaging neuronal activity over large number of experimental trials. Such trial-averaging is carried out to reduce noise and to diminish the influence of other signals unrelated to the corresponding stimulus or behaviour. However, if the recorded neuronal responses are jittered in time with respect to the corresponding stimulus or behaviour, averaging over trials may distort the estimation of the underlying neuronal response. Temporal jitter between single trial neural responses can be partially or completely removed using realignment algorithms. Here, we present a measure, named difference of time-averaged variance (dTAV), which can be used to evaluate the performance of a realignment algorithm without knowing the internal triggers of neural responses. Using simulated data, we show that using dTAV to optimize the parameter values for an established parametric realignment algorithm improved its efficacy and, therefore, reduced the jitter of neuronal responses. By removing the jitter more effectively and, therefore, enabling more accurate estimation of neuronal responses, dTAV can improve analysis and interpretation of the neural responses.

Neurons with stereotyped and rapid responses provide a reference frame for relative temporal coding in primate auditory cortex

The precise timing of spikes of cortical neurons relative to stimulus onset carries substantial sensory information. To access this information the sensory systems would need to maintain an internal temporal reference that reflects the precise stimulus timing. Whether and how sensory systems implement such reference frames to decode time-dependent responses, however, remains debated. Studying the encoding of naturalistic sounds in primate (Macaca mulatta) auditory cortex we here investigate potential intrinsic references for decoding temporally precise information. Within the population of recorded neurons, we found one subset responding with stereotyped fast latencies that varied little across trials or stimuli, while the remaining neurons had stimulus-modulated responses with longer and variable latencies. Computational analysis demonstrated that the neurons with stereotyped short latencies constitute an effective temporal reference for relative coding. Using the response onset of a simultaneously recorded stereotyped neuron allowed decoding most of the stimulus information carried by onset latencies and the full spike train of stimulus-modulated neurons. Computational modeling showed that few tens of such stereotyped reference neurons suffice to recover nearly all information that would be available when decoding the same responses relative to the actual stimulus onset. These findings reveal an explicit neural signature of an intrinsic reference for decoding temporal response patterns in the auditory cortex of alert animals. Furthermore, they highlight a role for apparently unselective neurons as an early saliency signal that provides a temporal reference for extracting stimulus information from other neurons.

Influence of a nanorod molecular layer on the biological activity of neuronal cells. A semiclassical model for complex solid/liquid interfaces with carbon nanotubes

A general account of electric effects is given for a biological phase interacting with a nanorod molecular layer by means of the formed hard-soft and solid-liquid interfaces. In particular, the frequency enhancement previously detected for the spontaneous activity of neuronal cultures interfaced with carbon nanotubes is quantitatively explained upon a quantum/semiclassical description, where the duration of a biological signal is viewed as the (average) lifetime of a decaying state (or population of states), and the effect of the carbon phase as a linewidth broadening. Four contributions were principally accounted for, one biological, for the synaptic strength, one electrochemical, for the overall capacitance increase implied by the nanotube double layers, one geometric, for the typical scales ruling the electron and ion conduction mechanisms, and one electromagnetic-like, translating the membrane polarization changes. These calculations predict an enhancement factor equal on average to ≃6.39, against a former experimental value ≃6.08.

Reading between the spikes of the hypothalamic neural code

Reading the spike coding of hypothalamic neurones presents a considerable challenge because they exhibit highly irregular firing patterns. Electrophysiologists working in the motor and sensory systems, in which neurones fire more regularly, have devised satisfactory methods to describe the firing of cells, although the statistical assumptions that underlie the methods do not apply to hypothalamic neurones. Measurement of neural activity is nevertheless vital to characterise the activity of neuroendocrine cells. It has thus become necessary to develop methods suitable for the analysis of the highly irregular spike discharge patterns of both spontaneous and stimulus-evoked firing of hypothalamic neurones. We review techniques used to meet this challenge and demonstrate their considerable capacity to address important physiological questions. We also introduce a novel approach for valid statistical estimation of the information conveyed by the response of a single neurone to a periodic stimulus. The approach demonstrated significant diurnal rhythms of synaptic connectivity between hypothalamic nuclei.

Information Carried by Population Spike Times in the Whisker Sensory Cortex can be Decoded Without Knowledge of Stimulus Time

Computational analyses have revealed that precisely timed spikes emitted by somatosensory cortical neuronal populations encode basic stimulus features in the rat's whisker sensory system. Efficient spike time based decoding schemes both for the spatial location of a stimulus and for the kinetic features of complex whisker movements have been defined. To date, these decoding schemes have been based upon spike times referenced to an external temporal frame – the time of the stimulus itself. Such schemes are limited by the requirement of precise knowledge of the stimulus time signal, and it is not clear whether stimulus times are known to rats making sensory judgments. Here, we first review studies of the information obtained from spike timing referenced to the stimulus time. Then we explore new methods for extracting spike train information independently of any external temporal reference frame. These proposed methods are based on the detection of stimulus-dependent differences in the firing time within a neuronal population. We apply them to a data set using single-whisker stimulation in anesthetized rats and find that stimulus site can be decoded based on the millisecond-range relative differences in spike times even without knowledge of stimulus time. If spike counts alone are measured over tens or hundreds of milliseconds rather than milliseconds, such decoders are much less effective. These results suggest that decoding schemes based on millisecond-precise spike times are likely to subserve robust and information-rich transmission of information in the somatosensory system.

Variability of visual responses of superior colliculus neurons depends on stimulus velocity

Visually responding neurons in the superficial, retinorecipient layers of the cat superior colliculus receive input from two primarily parallel information processing channels, Y and W, which is reflected in their velocity response profiles. We quantified the time-dependent variability of responses of these neurons to stimuli moving with different velocities by Fano factor (FF) calculated in discrete time windows. The FF for cells responding to low-velocity stimuli, thus receiving W inputs, increased with the increase in the firing rate. In contrast, the dynamics of activity of the cells responding to fast moving stimuli, processed by Y pathway, correlated negatively with FF whether the response was excitatory or suppressive. These observations were tested against several types of surrogate data. Whereas Poisson description failed to reproduce the variability of all collicular responses, the inclusion of secondary structure to the generating point process recovered most of the observed features of responses to fast moving stimuli. Neither model could reproduce the variability of low-velocity responses, which suggests that, in this case, more complex time dependencies need to be taken into account. Our results indicate that Y and W channels may differ in reliability of responses to visual stimulation. Apart from previously reported morphological and physiological differences of the cells belonging to Y and W channels, this is a new feature distinguishing these two pathways.