Multiplexed Spike Coding and Adaptation in the Thalamus.
ABSTRACT: High-frequency "burst" clusters of spikes are a generic output pattern of many neurons. While bursting is a ubiquitous computational feature of different nervous systems across animal species, the encoding of synaptic inputs by bursts is not well understood. We find that bursting neurons in the rodent thalamus employ "multiplexing" to differentially encode low- and high-frequency stimulus features associated with either T-type calcium "low-threshold" or fast sodium spiking events, respectively, and these events adapt differently. Thus, thalamic bursts encode disparate information in three channels: (1) burst size, (2) burst onset time, and (3) precise spike timing within bursts. Strikingly, this latter "intraburst" encoding channel shows millisecond-level feature selectivity and adapts across statistical contexts to maintain stable information encoded per spike. Consequently, calcium events both encode low-frequency stimuli and, in parallel, gate a transient window for high-frequency, adaptive stimulus encoding by sodium spike timing, allowing bursts to efficiently convey fine-scale temporal information.
Project description:Neurons in various regions of the brain generate spike bursts. While the number of spikes within a burst has been shown to carry information, information coding by interspike intervals (ISIs) is less well understood. In particular, a burst with k spikes has k-1 intraburst ISIs, and these k-1 ISIs could theoretically encode k-1 independent values. In this study, we demonstrate that such combinatorial coding occurs for retinal bursts. By recording ganglion cell spikes from isolated salamander retinae, we found that intraburst ISIs encode oscillatory light sequences that are much faster than the light intensity modulation encoded by the number of spikes. When a burst has three spikes, the two intraburst ISIs combinatorially encode the amplitude and phase of the oscillatory sequence. Analysis of trial-to-trial variability suggested that intraburst ISIs are regulated by two independent mechanisms responding to orthogonal oscillatory components, one of which is common to bursts with a different number of spikes. Therefore, the retina encodes multiple stimulus features by exploiting all degrees of freedom of burst spike patterns, i.e., the spike number and multiple intraburst ISIs.
Project description:Thalamic neurons have been long assumed to fire in tonic mode during perceptive states, and in burst mode during sleep and unconsciousness. However, recent evidence suggests that bursts may also be relevant in the encoding of sensory information. Here, we explore the neural code of such thalamic bursts. In order to assess whether the burst code is generic or whether it depends on the detailed properties of each bursting neuron, we analyzed two neuron models incorporating different levels of biological detail. One of the models contained no information of the biophysical processes entailed in spike generation, and described neuron activity at a phenomenological level. The second model represented the evolution of the individual ionic conductances involved in spiking and bursting, and required a large number of parameters. We analyzed the models' input selectivity using reverse correlation methods and information theory. We found that n-spike bursts from both models transmit information by modulating their spike count in response to changes to instantaneous input features, such as slope, phase, amplitude, etc. The stimulus feature that is most efficiently encoded by bursts, however, need not coincide with one of such classical features. We therefore searched for the optimal feature among all those that could be expressed as a linear transformation of the time-dependent input current. We found that bursting neurons transmitted 6 times more information about such more general features. The relevant events in the stimulus were located in a time window spanning ~100 ms before and ~20 ms after burst onset. Most importantly, the neural code employed by the simple and the biologically realistic models was largely the same, implying that the simple thalamic neuron model contains the essential ingredients that account for the computational properties of the thalamic burst code. Thus, our results suggest the n-spike burst code is a general property of thalamic neurons.
Project description:Neuronal firing in the hippocampal formation relative to the phase of local field potentials (LFP) has a key role in memory processing and spatial navigation. Firing can be in either tonic or burst mode. Although bursting neurons are common in the hippocampal formation, the characteristics of their locking to LFP phase are not completely understood. We investigated phase-locking properties of bursting neurons using simulations generated by a dual compartmental model of a pyramidal neuron adapted to match the bursting activity in the subiculum of a rat. The model was driven with stochastic input signals containing a power spectral profile consistent with physiologically relevant frequencies observed in LFP. The single spikes and spike bursts fired by the model were locked to a preferred phase of the predominant frequency band where there was a peak in the power of the driving signal. Moreover, the preferred phase of locking shifted with increasing burst size, providing evidence that LFP phase can be encoded by burst size. We also provide initial support for the model results by analysing example data of spontaneous LFP and spiking activity recorded from the subiculum of a single urethane-anaesthetised rat. Subicular neurons fired single spikes, two-spike bursts and larger bursts that locked to a preferred phase of either dominant slow oscillations or theta rhythms within the LFP, according to the model prediction. Both power-modulated phase-locking and gradual shift in the preferred phase of locking as a function of burst size suggest that neurons can use bursts to encode timing information contained in LFP phase into a spike-count code.
Project description:We now test the hypothesis that post-inhibitory bursting in the human pallidal receiving nucleus of the thalamus (ventral oral) mediates inhibitory pallido-thalamic transmission during dystonia. We have compared thalamic single neuron activity in nine patients with organic dystonia to that in a patient with psychogenic dystonia (Psyd) and in healthy waking monkeys. In organic dystonia, EMG power is commonly concentrated at the lowest frequency of the smoothed autopower spectrum (0.39Hz). Therefore, segments of spike trains with a signal-to-noise ratio ?2 at 0.39Hz were termed dystonia frequency (DF) segments, which occurred more commonly during dystonia related to movement. Those with a SNR<2 were termed non-dystonia frequency (nDF) segments, which were associated with spontaneous dystonia. We concentrated on nDF activity since neuronal activity in our controls was measured at rest. Neuronal spike trains were categorized into those with post-inhibitory bursts (G, grouped), with single spikes (NG, non-grouped), or with both single spikes and bursts (I, intermediate). nDF spike trains in ventral oral had more G category firing in dystonia than in controls. The burst rate and the pre-burst silent period in nDF firing of organic dystonia were consistently greater than those of both the monkeys and the patient with Psyd. The distribution of the pre-burst silent period was bimodal with a longer mode of approximately GABAb (gamma amino butyric acid receptor-type b) duration. These results demonstrate distinct differences of post-inhibitory bursting in organic dystonia versus controls. The presence of inhibitory events consistent with GABAb duration suggests interventions for treatment of dystonia.
Project description:Burst spike patterns are common in regions of the hippocampal formation such as the subiculum and medial entorhinal cortex (MEC). Neurons in these areas are immersed in extracellular electrical potential fluctuations often recorded as the local field potential (LFP). LFP rhythms within different frequency bands are linked to different behavioral states. For example, delta rhythms are often associated with slow-wave sleep, inactivity and anesthesia; whereas theta rhythms are prominent during awake exploratory behavior and REM sleep. Recent evidence suggests that bursting neurons in the hippocampal formation can encode LFP features. We explored this hypothesis using a two-compartment model of a bursting pyramidal neuron driven by time-varying input signals containing spectral peaks at either delta or theta rhythms. The model predicted a neural code in which bursts represented the instantaneous value, phase, slope and amplitude of the driving signal both in their timing and size (spike number). To verify whether this code is employed in vivo, we examined electrophysiological recordings from the subiculum of anesthetized rats and the MEC of a behaving rat containing prevalent delta or theta rhythms, respectively. In both areas, we found bursting cells that encoded information about the instantaneous voltage, phase, slope and/or amplitude of the dominant LFP rhythm with essentially the same neural code as the simulated neurons. A fraction of the cells encoded part of the information in burst size, in agreement with model predictions. These results provide in-vivo evidence that the output of bursting neurons in the mammalian brain is tuned to features of the LFP.
Project description:Purkinje cells (PC) control deep cerebellar nuclei (DCN), which in turn inhibit inferior olive nucleus, closing a positive feedback loop via climbing fibers. PC highly express potassium BK channels but their contribution to the olivo-cerebellar loop is not clear. Using multiple-unit recordings in alert mice we found in that selective deletion of BK channels in PC induces a decrease in their simple spike firing with a beta-range bursting pattern and fast intraburst frequency (~200?Hz). To determine the impact of this abnormal rhythm on the olivo-cerebellar loop we analyzed simultaneous rhythmicity in different cerebellar structures. We found that this abnormal PC rhythmicity is transmitted to DCN neurons with no effect on their mean firing frequency. Long term depression at the parallel-PC synapses was altered and the intra-burst complex spike spikelets frequency was increased without modification of the mean complex spike frequency in BK-PC-/- mice. We argue that the ataxia present in these conditional knockout mice could be explained by rhythmic disruptions transmitted from mutant PC to DCN but not by rate code modification only. This suggests a neuronal mechanism for ataxia with possible implications for human disease.
Project description:Both phase-amplitude coupling (PAC) and beta-bursts in the subthalamic nucleus have been significantly linked to symptom severity in Parkinson's disease (PD) in humans and emerged independently as competing biomarkers for closed-loop deep brain stimulation (DBS). However, the underlying nature of subthalamic PAC is poorly understood and its relationship with transient beta burst-events has not been investigated. To address this, we studied macro- and micro electrode recordings of local field potentials (LFPs) and single unit activity from 15 hemispheres in 10 PD patients undergoing DBS surgery. PAC between beta phase and high frequency oscillation (HFO) amplitude was compared to single unit firing rates, spike triggered averages, power spectral densities, inter spike intervals and phase-spike locking, and was studied in periods of beta-bursting. We found a significant synchronisation of spiking to HFOs and correlation of mean firing rates with HFO-amplitude when the latter was coupled to beta phase (i.e. in the presence of PAC). In the presence of PAC, single unit power spectra displayed peaks in the beta and HFO frequency range and the HFO frequency was correlated with that in the LFP. Furthermore, inter spike interval frequencies peaked in the same frequencies for which PAC was observed. Finally, PAC significantly increased with beta burst-duration. Our findings offer new insight in the pathology of Parkinson's disease by providing evidence that subthalamic PAC reflects the locking of spiking activity to network beta oscillations and that this coupling progressively increases with beta-burst duration. These findings suggest that beta-bursts capture periods of increased subthalamic input/output synchronisation in the beta frequency range and have important implications for therapeutic closed-loop DBS. SIGNIFICANCE STATEMENT: Identifying biomarkers for closed-loop deep brain stimulation (DBS) has become an increasingly important issue in Parkinson's Disease (PD) research. Two such biomarkers, phase-amplitude coupling (PAC) and beta-bursts, recorded from the implanted electrodes in subthalamic nucleus in PD patients, correlate with motor impairment. However, the physiological basis of PAC, and it relationship to beta bursts, is unclear. We provide multiple lines of evidence that PAC in the human STN reflects the locking of spiking activity to network beta oscillations and that this coupling progressively increases with the duration of beta-bursts. This suggests that beta-bursts capture increased subthalamic input/output synchronisation and provides new insights in PD pathology with direct implications for closed-loop DBS therapy strategies.
Project description:The synchronization of neuronal activity is thought to enhance information processing. There is much evidence supporting rhythmically bursting external tufted cells (ETCs) of the rodent olfactory bulb glomeruli coordinating the activation of glomerular interneurons and mitral cells via dendrodendritic excitation. However, as bursting has variable significance at axodendritic cortical synapses, it is not clear if ETC bursting imparts a specific functional advantage over the preliminary spike in dendrodendritic synaptic networks. To answer this question, we investigated the influence of single ETC bursts and spikes with the in vitro rat olfactory bulb preparation at different levels of processing, via calcium imaging of presynaptic ETC dendrites, dual electrical recording of ETC -interneuron synaptic pairs, and multicellular calcium imaging of ETC-induced population activity. Our findings supported single ETC bursts, versus single spikes, driving robust presynaptic calcium signaling, which in turn was associated with profound extension of the initial monosynaptic spike-driven dendrodendritic excitatory postsynaptic potential. This extension could be driven by either the spike-dependent or spike-independent components of the burst. At the population level, burst-induced excitation was more widespread and reliable compared with single spikes. This further supports the ETC network, in part due to a functional advantage of bursting at excitatory dendrodendritic synapses, coordinating synchronous activity at behaviorally relevant frequencies related to odor processing in vivo.
Project description:Mammalian thalamocortical relay (TCR) neurons switch their firing activity between a tonic spiking and a bursting regime. In a combined experimental and computational study, we investigated the features in the input signal that single spikes and bursts in the output spike train represent and how this code is influenced by the membrane voltage state of the neuron. Identical frozen Gaussian noise current traces were injected into TCR neurons in rat brain slices as well as in a validated three-compartment TCR model cell. The resulting membrane voltage traces and spike trains were analyzed by calculating the coherence and impedance. Reverse correlation techniques gave the Event-Triggered Average (ETA) and the Event-Triggered Covariance (ETC). This demonstrated that the feature selectivity started relatively long before the events (up to 300 ms) and showed a clear distinction between spikes (selective for fluctuations) and bursts (selective for integration). The model cell was fine-tuned to mimic the frozen noise initiated spike and burst responses to within experimental accuracy, especially for the mixed mode regimes. The information content carried by the various types of events in the signal as well as by the whole signal was calculated. Bursts phase-lock to and transfer information at lower frequencies than single spikes. On depolarization the neuron transits smoothly from the predominantly bursting regime to a spiking regime, in which it is more sensitive to high-frequency fluctuations. The model was then used to elucidate properties that could not be assessed experimentally, in particular the role of two important subthreshold voltage-dependent currents: the low threshold activated calcium current (IT) and the cyclic nucleotide modulated h current (Ih). The ETAs of those currents and their underlying activation/inactivation states not only explained the state dependence of the firing regime but also the long-lasting concerted dynamic action of the two currents. Finally, the model was used to investigate the more realistic "high-conductance state", where fluctuations are caused by (synaptic) conductance changes instead of current injection. Under "standard" conditions bursts are difficult to initiate, given the high degree of inactivation of the T-type calcium current. Strong and/or precisely timed inhibitory currents were able to remove this inactivation.
Project description:Cerebellar Purkinje cells mediate accurate eye movement coordination. However, it remains unclear how oculomotor adaptation depends on the interplay between the characteristic Purkinje cell response patterns, namely tonic, bursting, and spike pauses. Here, a spiking cerebellar model assesses the role of Purkinje cell firing patterns in vestibular ocular reflex (VOR) adaptation. The model captures the cerebellar microcircuit properties and it incorporates spike-based synaptic plasticity at multiple cerebellar sites. A detailed Purkinje cell model reproduces the three spike-firing patterns that are shown to regulate the cerebellar output. Our results suggest that pauses following Purkinje complex spikes (bursts) encode transient disinhibition of target medial vestibular nuclei, critically gating the vestibular signals conveyed by mossy fibres. This gating mechanism accounts for early and coarse VOR acquisition, prior to the late reflex consolidation. In addition, properly timed and sized Purkinje cell bursts allow the ratio between long-term depression and potentiation (LTD/LTP) to be finely shaped at mossy fibre-medial vestibular nuclei synapses, which optimises VOR consolidation. Tonic Purkinje cell firing maintains the consolidated VOR through time. Importantly, pauses are crucial to facilitate VOR phase-reversal learning, by reshaping previously learnt synaptic weight distributions. Altogether, these results predict that Purkinje spike burst-pause dynamics are instrumental to VOR learning and reversal adaptation.