Taste coding in the parabrachial nucleus of the pons in awake, freely licking rats and comparison with the nucleus of the solitary tract

In the rodent, the parabrachial nucleus of the pons (PbN) receives information about taste directly from the nucleus of the solitary tract (NTS). Here we examined how information about taste quality (sweet, sour, salty, and bitter) is conveyed in the PbN of awake, freely licking rats, with a focus on how this information is transformed from the incoming NTS signals. Awake rats with electrodes in the PbN had free access to a lick spout that delivered taste stimuli (5 consecutive licks; 100 mM NaCl, 10 mM citric acid, 0.01 mM quinine HCl, or 100 mM sucrose and water) or water (as a rinse) on a variable-ratio schedule. To assess temporal coding, a family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. PbN neurons ( n = 49) were generally broadly tuned across taste qualities with variable response latencies. Some PbN neurons were quiescent during lick bouts, and others, some taste responsive, showed time-locked firing to the lick pattern. Compared with NTS neurons, spike timing played a larger role in signaling taste in the first 2 s of the response, contributing significantly in 78% (38/49) of PbN cells compared with 45% of NTS cells. Also, information from temporal coding increased at a faster rate as the response unfolded over time in PbN compared with NTS. Collectively, these data suggest that taste-related information from NTS converges in the PbN to enable a subset of PbN cells to carry a larger information load.

Download Full-text

Temporal coding of taste in the parabrachial nucleus of the pons of the rat

Journal of Neurophysiology ◽

10.1152/jn.00836.2010 ◽

2011 ◽

Vol 105 (4) ◽

pp. 1889-1896 ◽

Cited By ~ 17

Author(s):

Andrew M. Rosen ◽

Jonathan D. Victor ◽

Patricia M. Di Lorenzo

Keyword(s):

Time Course ◽

Temporal Dynamics ◽

Spike Timing ◽

Temporal Coding ◽

Taste Quality ◽

Spike Count ◽

Parabrachial Nucleus ◽

Similar Proportion ◽

Temporal Characteristics ◽

Temporal Precision

Recent studies have provided evidence that temporal coding contributes significantly to encoding taste stimuli at the first central relay for taste, the nucleus of the solitary tract (NTS). However, it is not known whether this coding mechanism is also used at the next synapse in the central taste pathway, the parabrachial nucleus of the pons (PbN). In the present study, electrophysiological responses to taste stimuli (sucrose, NaCl, HCl, and quinine) were recorded from 44 cells in the PbN of anesthetized rats. In 29 cells, the contribution of the temporal characteristics of the response to the discrimination of various taste qualities was assessed. A family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. Results showed that spike timing in 14 PbN cells (48%) conveyed a significant amount of information about taste quality, beyond what could be conveyed by spike count alone. In another 14 cells (48%), the rate envelope (time course) of the response contributed significantly more information than spike count alone. Across cells there was a significant correlation ( r = 0.51; P < 0.01) between breadth of tuning and the proportion of information conveyed by temporal dynamics. Comparison with previous data from the NTS (Di Lorenzo PM and Victor JD. J Neurophysiol 90: 1418–31, 2003 and J Neurophysiol 97: 1857–1861, 2007) showed that temporal coding in the NTS occurred in a similar proportion of cells and contributed a similar fraction of the total information at the same average level of temporal precision, even though trial-to-trial variability was higher in the PbN than in the NTS. These data suggest that information about taste quality conveyed by the temporal characteristics of evoked responses is transmitted with high fidelity from the NTS to the PbN.

Download Full-text

Temporal Coding of Intensity of NaCl and HCl in the Nucleus of the Solitary Tract of the Rat

Journal of Neurophysiology ◽

10.1152/jn.00539.2010 ◽

2011 ◽

Vol 105 (2) ◽

pp. 697-711 ◽

Cited By ~ 18

Author(s):

Jen-Yung Chen ◽

Jonathan D. Victor ◽

Patricia M. Di Lorenzo

Keyword(s):

Single Cells ◽

Temporal Structure ◽

Relative Size ◽

Spike Timing ◽

Temporal Coding ◽

Spike Count ◽

Scaling Analysis ◽

Solitary Tract ◽

Stimulus Quality ◽

Temporal Characteristics

Sensory neurons are generally tuned to a subset of stimulus qualities within their sensory domain and manifest this tuning by the relative size of their responses to stimuli of equal intensity. However, response size alone cannot unambiguously signal stimulus quality, since response size also depends on stimulus intensity. Thus a common problem faced by sensory systems is that response size (e.g., spike count) confounds stimulus quality and intensity. Here, using the gustatory system as a model, we asked whether temporal firing characteristics could disambiguate these axes. To address this question, we recorded taste responses of single neurons in the nucleus of the solitary tract (NTS, the first central gustatory relay) in anesthetized rats to a range of concentrations of NaCl and HCl and their binary mixtures. To assess the contribution of the temporal characteristics of the response to discrimination among tastants, a family of metrics that quantifies the similarity of two spike trains in terms of spike count and spike timing was used. Results showed that the spike count produced by different taste qualities and different concentrations overlapped in most cells, implying that information conveyed by spike count is imprecise. Multidimensional scaling analysis of taste responses using similarity of temporal characteristics showed that different taste qualities, intensities, and mixtures formed distinct clusters in this “temporal coding” taste space and were arranged in a logical order. Thus the temporal structure of taste responses in single cells in the NTS can simultaneously convey information about both taste quality and intensity.

Download Full-text

Variability in Responses and Temporal Coding of Tastants of Similar Quality in the Nucleus of the Solitary Tract of the Rat

Journal of Neurophysiology ◽

10.1152/jn.00920.2007 ◽

2008 ◽

Vol 99 (2) ◽

pp. 644-655 ◽

Cited By ~ 30

Author(s):

Andre T. Roussin ◽

Jonathan D. Victor ◽

Jen-Yung Chen ◽

Patricia M. Di Lorenzo

Keyword(s):

Single Cells ◽

Spike Timing ◽

Temporal Coding ◽

Spike Count ◽

Chemical Compositions ◽

Similar Response ◽

Theoretic Approach ◽

Solitary Tract ◽

Electrophysiological Responses ◽

Information Theoretic Approach

In the nucleus of the solitary tract (NTS), electrophysiological responses to taste stimuli representing four basic taste qualities (sweet, sour, salty, or bitter) can often be discriminated by spike count, although in units for which the number of spikes is variable across identical stimulus presentations, spike timing (i.e., temporal coding) can also support reliable discrimination. The present study examined the contribution of spike count and spike timing to the discrimination of stimuli that evoke the same taste quality but are of different chemical composition. Responses to between 3 and 21 repeated presentations of two pairs of quality-matched tastants were recorded from 38 single cells in the NTS of urethane-anesthetized rats. Temporal coding was assessed in 24 cells, most of which were tested with salty and sour tastants, using an information-theoretic approach. Within a given cell, responses to tastants of similar quality were generally closer in magnitude than responses to dissimilar tastants; however, tastants of similar quality often reversed their order of effectiveness across replicate sets of trials. Typically, discrimination between tastants of dissimilar qualities could be made by spike count. Responses to tastants of similar quality typically evoked more similar response magnitudes but were more frequently, and to a proportionally greater degree, distinguishable based on temporal information. Results showed that nearly every taste-responsive NTS cell has the capacity to generate temporal features in evoked spike trains that can be used to distinguish between stimuli of different qualities and chemical compositions.

Download Full-text

Taste Response Variability and Temporal Coding in the Nucleus of the Solitary Tract of the Rat

Journal of Neurophysiology ◽

10.1152/jn.00177.2003 ◽

2003 ◽

Vol 90 (3) ◽

pp. 1418-1431 ◽

Cited By ~ 88

Author(s):

Patricia M. Di Lorenzo ◽

Jonathan D. Victor

Keyword(s):

Response Rate ◽

Single Cells ◽

Temporal Structure ◽

Spike Timing ◽

Temporal Coding ◽

Potential Contribution ◽

Theoretic Approach ◽

Solitary Tract ◽

Stimulus Response ◽

Information Theoretic Approach

Theories of taste coding in the brain stem have been based on the idea that taste responses are integrated over time without regard to the temporal structure of the taste-evoked spike train. In the present experiment, the reliability of response rate across stimulus repetitions and the potential contribution of temporal coding to the discrimination of taste stimuli was examined. Taste stimuli representing the four basic taste qualities were presented repeatedly, and electrophysiological responses were recorded from single cells in the nucleus of the solitary tract (NTS) of anesthetized rats. Blocks of the four tastants were repeated for as long as the cell remained isolated. Nineteen cells were recorded with between 8 and 27 repetitions of each stimulus. Response magnitude to a given tastant varied widely within some NTS cells. This impacted the determination of both the breadth of tuning and best stimulus for a given cell. The contribution of spike timing and the pattern of interspike intervals to discrimination of taste stimuli was evaluated by an information-theoretic approach based on two families of metrics. Spike timing significantly contributed to the discrimination of taste qualities in 10 of 19 (53%) cells. This contribution was especially notable during the initial 2 s of the response. Those cells that showed the most variable firing rates in response to repetition of taste stimuli tended to show the largest contribution of temporal coding. These results suggest that, in addition to response rate, the temporal parameters of responses may convey information about taste stimuli in the NTS.

Download Full-text

Cholecystokinin-, galanin-, and corticotropin-releasing factor-like immunoreactive projections from the nucleus of the solitary tract to the parabrachial nucleus in the rat

The Journal of Comparative Neurology ◽

10.1002/cne.902930405 ◽

1990 ◽

Vol 293 (4) ◽

pp. 581-598 ◽

Cited By ~ 142

Author(s):

Horst Herbert ◽

Clifford B. Saper

Keyword(s):

Corticotropin Releasing Factor ◽

Parabrachial Nucleus ◽

Solitary Tract

Download Full-text

Cortical Representation of Auditory Space: Information-Bearing Features of Spike Patterns

Journal of Neurophysiology ◽

10.1152/jn.00491.2001 ◽

2002 ◽

Vol 87 (4) ◽

pp. 1749-1762 ◽

Cited By ~ 115

Author(s):

Shigeto Furukawa ◽

John C. Middlebrooks

Keyword(s):

Sound Source ◽

Neuronal Response ◽

Source Location ◽

Spike Timing ◽

Spike Count ◽

Cortical Representation ◽

Auditory Space ◽

Transmitted Information ◽

Related Information ◽

Spike Patterns

Previous studies have demonstrated that the spike patterns of cortical neurons vary systematically as a function of sound-source location such that the response of a single neuron can signal the location of a sound source throughout 360° of azimuth. The present study examined specific features of spike patterns that might transmit information related to sound-source location. Analysis was based on responses of well-isolated single units recorded from cortical area A2 in α-chloralose-anesthetized cats. Stimuli were 80-ms noise bursts presented from loudspeakers in the horizontal plane; source azimuths ranged through 360° in 20° steps. Spike patterns were averaged across samples of eight trials. A competitive artificial neural network (ANN) identified sound-source locations by recognizing spike patterns; the ANN was trained using the learning vector quantization learning rule. The information about stimulus location that was transmitted by spike patterns was computed from joint stimulus-response probability matrices. Spike patterns were manipulated in various ways to isolate particular features. Full-spike patterns, which contained all spike-count information and spike timing with 100-μs precision, transmitted the most stimulus-related information. Transmitted information was sensitive to disruption of spike timing on a scale of more than ∼4 ms and was reduced by an average of ∼35% when spike-timing information was obliterated entirely. In a condition in which all but the first spike in each pattern were eliminated, transmitted information decreased by an average of only ∼11%. In many cases, that condition showed essentially no loss of transmitted information. Three unidimensional features were extracted from spike patterns. Of those features, spike latency transmitted ∼60% more information than that transmitted either by spike count or by a measure of latency dispersion. Information transmission by spike patterns recorded on single trials was substantially reduced compared with the information transmitted by averages of eight trials. In a comparison of averaged and nonaveraged responses, however, the information transmitted by latencies was reduced by only ∼29%, whereas information transmitted by spike counts was reduced by 79%. Spike counts clearly are sensitive to sound-source location and could transmit information about sound-source locations. Nevertheless, the present results demonstrate that the timing of the first poststimulus spike carries a substantial amount, probably the majority, of the location-related information present in spike patterns. The results indicate that any complete model of the cortical representation of auditory space must incorporate the temporal characteristics of neuronal response patterns.

Download Full-text

Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier

Sensors ◽

10.3390/s20020500 ◽

2020 ◽

Vol 20 (2) ◽

pp. 500 ◽

Cited By ~ 3

Author(s):

Sergey A. Lobov ◽

Andrey V. Chernyshov ◽

Nadia P. Krilova ◽

Maxim O. Shamshin ◽

Victor B. Kazantsev

Keyword(s):

Supervised Learning ◽

Hebbian Learning ◽

Back Propagation ◽

Spike Timing ◽

Temporal Coding ◽

Competitive Learning ◽

Neuron Activity ◽

Synaptic Competition ◽

Rate Coding ◽

Emg Patterns

One of the modern trends in the design of human–machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporal-rate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pair-based and triplet-based spike timing-dependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the so-called forgetting function that is dependent on neuron activity. We show that coherent use of the triplet-based STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the “winner takes all” principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multi-layer perceptron learned by back propagation of an error algorithm.

Download Full-text

Exact Event-Driven Implementation for Recurrent Networks of Stochastic Perfect Integrate-and-Fire Neurons

Neural Computation ◽

10.1162/neco_a_00346 ◽

2012 ◽

Vol 24 (12) ◽

pp. 3145-3180 ◽

Cited By ~ 2

Author(s):

Thibaud Taillefumier ◽

Jonathan Touboul ◽

Marcelo Magnasco

Keyword(s):

Intrinsic Noise ◽

Spike Timing ◽

Temporal Coding ◽

Recurrent Networks ◽

Neural Noise ◽

Integrate And Fire ◽

Discretization Schemes ◽

Event Driven ◽

Random Variability

In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks’ dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.

Download Full-text