Information theoretic analysis of pulmonary stretch receptor spike trains

Neural encoding schemes of tactile information in afferent activity of the vibrissal system

When rats acquire sensory information by actively moving their vibrissae, a neural code is manifested at different levels of the sensory system. Behavioral studies in tactile discrimination agree that rats can distinguish different roughness surfaces by whisking their vibrissae. The present study explores the existence of neural encoding in the afferent activity of one vibrissal nerve. Two neural encoding schemes based on "events" were proposed (cumulative event count and median inter-event time). The events were detected by using an event detection algorithm based on multiscale decomposition of the signal (Continuous Wavelet Transform). The encoding schemes were quantitatively evaluated through the maximum amount of information which was obtained by the Shannon's mutual information formula. Moreover, the effect of difference distances between rat snout and swept surfaces on the information values was also studied. We found that roughness information was encoded by events of 0.8 ms duration in the cumulative event count and event of 1.0 to 1.6 ms duration in the median inter-event count. It was also observed that an extreme decrease of the distance between rat snout and swept surfaces significantly reduces the information values and the capacity to discriminate among the sweep situations.

Pulmonary stretch receptor spike time precision increases with lung inflation amplitude and airway smooth muscle tension

Slowly adapting pulmonary stretch receptors (SARs) respond to different lung inflation volumes with distinct spike counts and patterns, conveying information regarding the rate and depth of breathing to the cardiovascular and respiratory control systems. Previous studies demonstrated that SARs respond to repetitions of the same lung inflation faithfully, suggesting the possibility of modeling an SAR's discrete response pattern to a stimulus using a statistically based method. Urethane-anesthetized rabbit SAR spike trains were recorded in response to repeated 9-, 12-, and 15-ml lung inflations, and used to construct model spike trains using K-means clustering. Analysis of the statistics of the responses to different lung inflation volumes revealed that SARs fire with more temporal precision in response to larger lung inflations, because the standard deviations of real spikes clustered around the modeled spike times of responses to 15-ml stimuli were smaller than those produced by 12 or 9 ml, even at the same absolute firing frequencies. This implied that the mechanical coupling of SAR endings with pulmonary tissue is critical in determining spike time reliability. To test this, we collected SAR responses during bronchial constriction, compared them with those produced by the same SARs under normal airway resistance, and found that their firing reliability improved during bronchial constriction. These results suggest that airway distension and mechanical coupling of the receptor endings with the airway wall (partially determined by smooth muscle tone) are important determinants of SAR spike time reliability.

Evaluation of EMG processing techniques using Information Theory

Background

Electromyographic signals can be used in biomedical engineering and/or rehabilitation field, as potential sources of control for prosthetics and orthotics. In such applications, digital processing techniques are necessary to follow efficient and effectively the changes in the physiological characteristics produced by a muscular contraction. In this paper, two methods based on information theory are proposed to evaluate the processing techniques.

Methods

These methods determine the amount of information that a processing technique is able to extract from EMG signals. The processing techniques evaluated with these methods were: absolute mean value (AMV), RMS values, variance values (VAR) and difference absolute mean value (DAMV). EMG signals from the middle deltoid during abduction and adduction movement of the arm in the scapular plane was registered, for static and dynamic contractions. The optimal window length (segmentation), abduction and adduction movements and inter-electrode distance were also analyzed.

Results

Using the optimal segmentation (200 ms and 300 ms in static and dynamic contractions, respectively) the best processing techniques were: RMS, AMV and VAR in static contractions, and only the RMS in dynamic contractions. Using the RMS of EMG signal, variations in the amount of information between the abduction and adduction movements were observed.

Conclusions

Although the evaluation methods proposed here were applied to standard processing techniques, these methods can also be considered as alternatives tools to evaluate new processing techniques in different areas of electrophysiology.

Temporal precision of neuronal information in a rapid perceptual judgment

In many situations, such as pedestrians crossing a busy street or prey evading predators, rapid decisions based on limited perceptual information are critical for survival. The brevity of these perceptual judgments constrains how neuronal signals are integrated or pooled over time because the underlying sequence of processes, from sensation to perceptual evaluation to motor planning and execution, all occur within several hundred milliseconds. Because most previous physiological studies of these processes have relied on tasks requiring considerably longer temporal integration, the neuronal basis of such rapid decisions remains largely unexplored. In this study, we examine the temporal precision of neuronal activity associated with a rapid perceptual judgment. We find that the activity of individual neurons over tens of milliseconds can reliably convey information about sensory events and was well correlated with the animals' judgments. There was a strong correlation between sensory reliability and the correlation with behavioral choice, suggesting that rapid decisions were preferentially based on the most reliable sensory signals. We also find that a simple model in which the responses of a small number of individual neurons (<5) are summed can completely explain behavioral performance. These results suggest that neuronal circuits are sufficiently precise to allow for cognitive decisions to be based on small numbers of action potentials from highly reliable neurons.

Retention of lung distension information in pump cell spike trains

Respiratory control requires feedback signals from the viscera, including mechanoreceptors and chemoreceptors. We previously showed that typical pulmonary stretch receptor (PSR) spike trains provide the central nervous system with approximately 31% of the theoretical maximum information regarding the amplitude of lung distension. However, it is unknown whether the spatiotemporal convergence of many PSR inputs onto second-order neurons (e.g., pump cells) results in more, or less, information about the stimulus carried by second-order cell spike trains. We recorded pump cell activity in adult, anesthetized, paralyzed, artificially ventilated rabbits during continuous manipulation of ventilator rate and volume to test the hypothesis that less information is carried by spike trains of individual pump cells than PSRs. Using previously developed analytic methods, we quantified the information carried by the pump cell spike trains and compared it with the same values derived from PSR data. Our results provide evidence that rejects our hypothesis: pump cells as a group did not carry significantly less information about the lung distension stimulus than PSRs, although that trend was implied by the data. By comparing the response variances with the theoretical minimum, we discovered that the trend toward information loss depends on response strength, with higher mean responses associated with larger response variances in pump cells than in PSRs. Thus spatiotemporal integration may result in information loss within certain analytic/stimulus parameters, but this is counterbalanced by the consistency of pump cell responses during brief integration times and/or low stimulus amplitudes, resulting in retention of total information.

Single neurons in the dentate gyrus and CA1 of the hippocampus exhibit inverse patterns of encoding during trace fear conditioning

Trace fear conditioning is a hippocampus-dependent learning task that requires the association of an auditory conditioned stimulus (CS) and a shock unconditioned stimulus (US) that are separated by a 20-s trace interval. Single-neuron activity was recorded simultaneously from the dentate gyrus (DG) and CA1 of rats during unpaired pseudoconditioning and subsequent trace fear conditioning. Single neurons in DG showed a progressive increase in learning-related activity to the CS and US across trace fear conditioning. Single neurons in CA1 showed an early increase in responding to the CS, which developed into a decrease in firing later in trace conditioning. Correlation analyses showed that DG and CA1 units exhibit inverse patterns of responding to the CS during trace fear conditioning.

Synaptic modulation of the interspike interval signatures of bursting pyloric neurons

The pyloric network of the lobster stomatogastric nervous system is one of the best described assemblies of oscillatory neurons producing bursts of action potentials. While the temporal patterns of bursts have been investigated in detail, those of spikes have received less attention. Here we analyze the intraburst firing patterns of pyloric neurons and the synaptic interactions shaping their dynamics in millisecond time scales not performed before. We find that different pyloric neurons express characteristic, cell-specific firing patterns in their bursts. Nonlinear analysis of the interspike intervals (ISIs) reveals distinctive temporal structures ('interspike interval signatures'), which are found to depend on the synaptic connectivity of the network. We compare ISI patterns of the pyloric dilator (PD), lateral pyloric (LP), and ventricular dilator (VD) neurons in 1) normal conditions, 2) after blocking glutamatergic synaptic connections, and 3) in various functional configurations of the three neurons. Manipulation of the synaptic connectivity results in characteristic changes in the ISI signatures of the postsynaptic neurons. The intraburst firing pattern of the PD neuron is regularized by the inhibitory synaptic connection from the LP neuron as revealed in current-clamp experiments and also as reconstructed with a dynamic clamp. On the other hand, mutual inhibition between the LP and VD neurons tend to produce more irregular bursts with increased spike jitter. The results show that synaptic interactions fine-tune the output of pyloric neurons. The present data also suggest a way of processing of synaptic information: bursting neurons are capable of encoding incoming signals by altering the fine structure of their intraburst spike patterns.