Neural processing of gustatory information in insular circuits

The insular cortex is the primary cortical site devoted to taste processing. A large body of evidence is available for how insular neurons respond to gustatory stimulation in both anesthetized and behaving animals. Most of the reports describe broadly tuned neurons that are involved in processing the chemosensory, physiological and psychological aspects of gustatory experience. However little is known about how these neural responses map onto insular circuits. Particularly mysterious is the functional role of the three subdivisions of the insular cortex: the granular, the dysgranular and the agranular insular cortices. In this article we review data on the organization of the local and long-distance circuits in the three subdivisions. The functional significance of these results is discussed in light of the latest electrophysiological data. A view of the insular cortex as a functionally integrated system devoted to processing gustatory, multimodal, cognitive and affective information is proposed.     

The state of gustatory neural coding

Debates on gustatory neural coding have been dominated by asmall number of fundamental issues since the inception of thefield in 1941. Three of these are discussed in this review:(1) are there basic tastes? (2) are there gustatory neuron types?(3) is the code for a taste read simultaneously across all participatingneurons (across-fiber patterning), or is it confined to a selectivechannel composed of cells of one type (labeled-line or channeling)?No conclusions are drawn regarding (1), primarily because auniversal definition of ‘basic tastes’ is lacking.It is concluded that gustatory neuron types are likely to existafter reviewing the issue from multiple perspectives and discoveringrecurring indications of neuron types from several. A firm conclusion,however, also awaits a widely accepted definition of what constitutesa neuron type. Issue (3) cannot yet be resolved for lack ofdefinitive data, specifically whether the discharges of inhibited,unresponsive, or weakly responsive cells add to (signal) ordetract from (noise) the neural code for a tastant.     

Odor and molecular vibration: Neural coding of olfactory information

Starting from an established correlation between specific molecular vibration patterns and the olfactory responses of organisms, a method is described by which equivalently specific patterns of neural excitation may be identified electrophysiologically. A molecular mechanism for the interaction is proposed which also takes into account such related matters as olfactory thresholds, and the possibility of both “specialist” and “generalist” receptors.     

Neural coding of natural stimuli: information at sub-millisecond resolution

Sensory information about the outside world is encoded by neurons in sequences of discrete, identical pulses termed action potentials or spikes. There is persistent controversy about the extent to which the precise timing of these spikes is relevant to the function of the brain. We revisit this issue, using the motion-sensitive neurons of the fly visual system as a test case. Our experimental methods allow us to deliver more nearly natural visual stimuli, comparable to those which flies encounter in free, acrobatic flight. New mathematical methods allow us to draw more reliable conclusions about the information content of neural responses even when the set of possible responses is very large. We find that significant amounts of visual information are represented by details of the spike train at millisecond and sub-millisecond precision, even though the sensory input has a correlation time of ~55 ms; different patterns of spike timing represent distinct motion trajectories, and the absolute timing of spikes points to particular features of these trajectories with high precision. Finally, the efficiency of our entropy estimator makes it possible to uncover features of neural coding relevant for natural visual stimuli: first, the system's information transmission rate varies with natural fluctuations in light intensity, resulting from varying cloud cover, such that marginal increases in information rate thus occur even when the individual photoreceptors are counting on the order of one million photons per second. Secondly, we see that the system exploits the relatively slow dynamics of the stimulus to remove coding redundancy and so generate a more efficient neural code.     

Neural coding of categories: information efficiency and optimal population codes

This paper deals with the analytical study of coding a discrete set of categories by a large assembly of neurons. We consider population coding schemes, which can also be seen as instances of exemplar models proposed in the literature to account for phenomena in the psychophysics of categorization. We quantify the coding efficiency by the mutual information between the set of categories and the neural code, and we characterize the properties of the most efficient codes, considering different regimes corresponding essentially to different signal-to-noise ratio. One main outcome is to find that, in a high signal-to-noise ratio limit, the Fisher information at the population level should be the greatest between categories, which is achieved by having many cells with the stimulus-discriminating parts (steepest slope) of their tuning curves placed in the transition regions between categories in stimulus space. We show that these properties are in good agreement with both psychophysical data and with the neurophysiology of the inferotemporal cortex in the monkey, a cortex area known to be specifically involved in classification tasks.     

Neural dynamics of envelope coding

We consider the processing of narrowband signals that modulate carrier waveforms in sensory systems. The tuning of sensory neurons to the carrier frequency results in a high sensitivity to the amplitude modulations of the carrier. Recent work has revealed how specialized circuitry can extract the lower-frequency modulation associated with the slow envelope of a narrowband signal, and send it to higher brain along with the full signal. This paper first summarizes the experimental evidence for this processing in the context of electroreception, where the narrowband signals arise in the context of social communication between the animals. It then examines the mechanism of this extraction by single neurons and neural populations, using intracellular recordings and new modeling results contrasting envelope extraction and stochastic resonance. Low noise and peri-threshold stimulation are necessary to obtain a firing pattern that shows high coherence with the envelope of the input. Further, the output must be fed through a slow synapse. Averaging networks are then considered for their ability to detect, using additional noise, signals with power in the envelope bandwidth. The circuitry that does support envelope extraction beyond the primary receptors is available in many areas of the brain including cortex. The mechanism of envelope extraction and its gating by noise and bias currents is thus accessible to non-carrier-based coding as well, as long as the input to the circuit is a narrowband signal. Novel results are also presented on a more biophysical model of the receptor population, showing that it can encode a narrowband signal, but not its envelope, as observed experimentally. The model is modified from previous models by stimulus reducing contrast in order to make it sufficiently linear to agree with the experimental data.     

Dynamical coding of sensory information with competitive networks.

Based on experiments with the locust olfactory system, we demonstrate that model sensory neural networks with lateral inhibition can generate stimulus specific identity-temporal patterns in the form of stimulus-dependent switching among small and dynamically changing neural ensembles (each ensemble being a group of synchronized projection neurons). Networks produce this switching mode of dynamical activity when lateral inhibitory connections are strongly non-symmetric. Such coding uses 'winner-less competitive' (WLC) dynamics. In contrast to the well known winner-take-all competitive (WTA) networks and Hopfield nets, winner-less competition represents sensory information dynamically. Such dynamics are reproducible, robust against intrinsic noise and sensitive to changes in the sensory input. We demonstrate the validity of sensory coding with WLC networks using two different formulations of the dynamics, namely the average and spiking dynamics of projection neurons (PN).     

Neural ensemble coding of satiety states

The motivation to start or terminate a meal involves the continual updating of information on current body status by central gustatory and reward systems. Previous electrophysiological and neuroimaging investigations revealed region-specific decreases in activity as the subject's state transitions from hunger to satiety. By implanting bundles of microelectrodes in the lateral hypothalamus, orbitofrontal cortex, insular cortex, and amygdala of hungry rats that voluntarily eat to satiety, we have measured the behavior of neuronal populations through the different phases of a complete feeding cycle (hunger-satiety-hunger). Our data show that while most satiety-sensitive units preferentially responded to a unique hunger phase within a cycle, neuronal populations integrated single-unit information in order to reflect the animal's motivational state across the entire cycle, with higher activity levels during the hunger phases. This distributed population code might constitute a neural mechanism underlying meal initiation under different metabolic states.     

Autocatalysis, information and coding

Autocatalytic self-construction in macromolecular systems requires the existence of a reflexive relationship between structural components and the functional operations they perform to synthesise themselves. The possibility of reflexivity depends on formal, semiotic features of the catalytic structure–function relationship, that is, the embedding of catalytic functions in the space of polymeric structures. Reflexivity is a semiotic property of some genetic sequences. Such sequences may serve as the basis for the evolution of coding as a result of autocatalytic self-organisation in a population of assignment catalysts. Autocatalytic selection is a mechanism whereby matter becomes differentiated in primitive biochemical systems. In the case of coding self-organisation, it corresponds to the creation of symbolic information. Prions are present-day entities whose replication through autocatalysis reflects aspects of biological semiotics less obvious than genetic coding.     

Neural representation of objects in space: a dual coding account.

I present evidence on the nature of object coding in the brain and discuss the implications of this coding for models of visual selective attention. Neuropsychological studies of task-based constraints on: (i) visual neglect; and (ii) reading and counting, reveal the existence of parallel forms of spatial representation for objects: within-object representations, where elements are coded as parts of objects, and between-object representations, where elements are coded as independent objects. Aside from these spatial codes for objects, however, the coding of visual space is limited. We are extremely poor at remembering small spatial displacements across eye movements, indicating (at best) impoverished coding of spatial position per se. Also, effects of element separation on spatial extinction can be eliminated by filling the space with an occluding object, indicating that spatial effects on visual selection are moderated by object coding. Overall, there are separate limits on visual processing reflecting: (i) the competition to code parts within objects; (ii) the small number of independent objects that can be coded in parallel; and (iii) task-based selection of whether within- or between-object codes determine behaviour. Between-object coding may be linked to the dorsal visual system while parallel coding of parts within objects takes place in the ventral system, although there may additionally be some dorsal involvement either when attention must be shifted within objects or when explicit spatial coding of parts is necessary for object identification.     

Neural coding in the chick cochlear nucleus

Physiological recordings were made from single units in the two divisions of the chick cochlear nucleus-nucleus angularis (NA) and nucleus magnocellularis (NM). Sound evoked responses were obtained in an effort to quantify functional differences between the two nuclei. In particular, it was of interest to determine if nucleus angularis and magnocellularis code for separate features of sound stimuli, such as temporal and intensity information. The principal findings are: 1. Spontaneous activity patterns in the two nuclei are very different. Neurons in nucleus angularis tend to have low spontaneous discharge rates while magnocellular units have high levels of spontaneous firing. 2. Frequency tuning curves recorded in both nuclei are similar in form, although the best thresholds of NA units are about 10 dB more sensitive than their NM counterparts across the entire frequency range. A wide spread of neural thresholds is evident in both NA and NM. 3. Large driven increases in discharge rate are seen in both NA and NM. Rate intensity functions from NM units are all monotonic, while a substantial percentage (22%) of NA units respond to increased sound level in a nonmonotonic fashion. 4. Most NA units with characteristic frequencies (CF) above 1000 Hz respond to sound stimuli at CF as 'choppers', while units with CF's below 1000 Hz are 'primary-like'. Several 'onset' units are also seen in NA. In contrast, all NM units show 'primary-like' response. 5. Units in both nuclei with CF's below 1000 Hz show strong neural phase-locking to stimuli at their CF. Above 1000 Hz, few NA units are phase-locked, while phase-locking in NM extends to 2000 Hz. 6. These results are discussed with reference to the hypothesis that NM initiates a neural pathway which codes temporal information while NA is involved primarily with intensity coding, similar in principle to the segregation of function seen in the cochlear nucleus of the barn owl (Sullivan and Konishi 1984).     

Neural correlations, population coding and computation

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.     

Disseminated storage of information with sequential coding

The paper demonstrates that it is possible to construct memory models where the information inserted is stored in disseminated form, using sequential coding, the changes in the units forming the models being determined by their geometrical connections and by the incoming stream of information. The models are shown to have large storage capacity and their efficiency can be made insensitive to loss of or damage to a large fraction of their units. The satisfactory verification by computer simulation of the analysis and results described in the present paper will be the subject of a future paper.     

Neural coding of behavioral relevance in parietal cortex

Flexible control of behavior requires the selective processing of task-relevant sensory information and the appropriate linkage of sensory input to action. A great deal of evidence suggests a central role for the parietal cortex in these functions. Recent results from neurophysiological studies in non-human primates and neuroimaging experiments in humans illuminate the importance of parietal cortex for attention, and suggest how parietal neurons might allow the dynamic representation of behaviorally relevant information.