2 research outputs found
Linking dynamical and functional properties of intrinsically bursting neurons
Several studies have shown that bursting neurons can encode information in the number of spikes per burst: As the stimulus varies, so does the length of individual bursts.Therepresented stimuli, however, vary substantially among different sensory modalities and different neurons.The goal of this paper is to determine which kind of stimulus features can be encoded in burst length, and how those features depend on the mathematical properties of the underlying dynamical system.We show that the initiation and termination of each burst is triggered by specific stimulus features whose temporal characteristsics are determined by the types of bifurcations that initiate and terminate firing in each burst. As only a few bifurcations are possible, only a restricted number of encoded features exists. Here we focus specifically on describing parabolic, square-wave and elliptic bursters. We find that parabolic bursters, whose firing is initiated and terminated by saddle-node bifurcations, behave as prototypical integrators: Firing is triggered by depolarizing stimuli, and lasts for as long as excitation is prolonged. Elliptic bursters, contrastingly, constitute prototypical resonators, since both the initiating and terminating bifurcations possess well-defined oscillation time scales. Firing is therefore triggered by stimulus stretches of matching frequency and terminated by a phase-inversion in the oscillation. The behavior of square-wave bursters is somewhat intermediate, since they are triggered by a fold bifurcation of cycles of well-defined frequency but are terminated by a homoclinic bifurcation lacking an oscillating time scale. These correspondences show that stimulus selectivity is determined by the type of bifurcations. By testing several neuron models, we also demonstrate that additional biological properties that do not modify the bifurcation structure play a minor role in stimulus encoding. Moreover, we show that burst-length variability (and thereby, the capacity to transmit information) depends on a trade-off between the variance of the external signal driving the cell and the strength of the slow internal currents modulating bursts. Thus, our work explicitly links the computational properties of bursting neurons to the mathematical properties of the underlying dynamical systems
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Neuromodulation of Thalamic Sensory Processing of Tactile Stimuli
Neuromodulatory systems, such as the locus coeruleus (LC) - norepinephrine (NE) system, are integral in the modulation of behavioral state, which in turn exerts a heavy influence on sensory processing, perception, and behavior. LC neurons project diffusely through the forebrain as the sole source of NE. LC tonic firing rate has been shown to correlate with arousal level and behavioral performance. As the LC-NE system innervates sensory pathways and NE has been shown to affect neuronal response, the LC-NE system could potentially allow for state-dependent modulation of sensory processing. However, the precise link between LC activation and sensory processing in the various stages of the sensory pathway that underly perception remained elusive.
It is well established that thalamic relay nuclei play an essential role in gating the flow of sensory information to the neocortex, serving to establish cortical representation of sensory environment. Thalamocortical information transmission has been proposed to be strongly modulated by the dynamic interplay between the thalamic relay nuclei and the thalamic reticular nucleus (TRN). Neurons in the early stages of sensory pathways selectively respond to specific features of sensory stimuli. In the rodent vibrissa pathway, thalamocortical neurons in the ventral posteromedial nucleus (VPm) encode kinetic features of whisker movement, allowing stimuli to be encoded by distinctive, temporally precise firing patterns. Therefore, understanding feature selectivity is crucial to understanding sensory processing and perception. However, whether LC activation modulates this feature selectivity, and if it does, the mechanisms through which this modulation occurs, remained largely unknown.
This work investigates LC modulation of thalamic feature selectivity through reverse correlation analysis of single-unit recordings from different stages of the rat vibrissa pathway. LC activation increased feature selectivity, drastically improving thalamic information transmission. This improvement was dependent on both local activation of α-adrenergic receptors and modulation of T-type calcium channels in the thalamus and was not due to LC modulation of trigeminothalamic feedforward or corticothalamic feedback inputs. LC activation reduced thalamic bursting, but this change in thalamic firing mode was not the primary cause of the improved information transmission as tonic spikes with LC stimulation carried three-times the information than tonic spikes without LC stimulation. Modelling confirmed NE regulation of intrathalamic circuit dynamics led to the improved information transmission as LC-NE modulation of either relay or reticular nucleus alone cannot account for the improvement. These results suggest a new sub-dimension within the tonic mode in which brain state can optimize thalamic sensory processing through modulation of intrathalamic circuit dynamics.
Subsequent computational work was then performed to determine exactly how the encoding of sensory information by thalamic relay neurons was altered to allow for an increase in both information transmission efficiency and rate. The results show that LC-NE induced improvements in feature selectivity are not simply due to an increased signal-to-noise ratio, a shift from bursting to tonic firing, or improvements in reliability or precision. Rather, LC-NE-induced modulation of intrathalamic dynamics changed the temporal response structure thalamic neurons used to encode the same stimuli to a new structure that increased the information carried by both tonic and burst spikes. The shift in events times favors optimal encoding, as more events occur at ideal positions, i.e. when the stimulus most closely matches the neuron’s feature selectivity. Further, this work analyzed the ability to reconstruct the original stimulus using the evoked spike trains of multiple neurons and their recovered feature selectivity from an ideal observer point-of-view. The results showed that LC-activation improved the accuracy of this reconstruction, indicating it may improve the accuracy of perception of whisker stimuli.
Finally, to make this work translatable, the use of vagus nerve stimulation (VNS) was investigated as a potential method for minimally invasive enhancement of thalamic sensory processing. The vagus nerve, which runs through the side of the neck, has long been known to have profound effects on brain-state and VNS has been shown to evoke LC firing. This work elucidates the previously uninvestigated short-term effects of VNS on thalamic sensory processing. Similar to direct LC stimulation, VNS enhanced the feature selectivity of thalamic neurons, resulting in a significant increase in the efficiency and rate of stimulus-related information conveyed by thalamic spikes. VNS-induced improvement in thalamic sensory processing also coincided with a decrease in thalamic burst firing, suggesting the same underlying mechanism as the improvements induced with direct LC stimulation