Central processing of sensory information in electric fish

Summary Comparative studies of neural mechanisms underlying the perception of natural stimulus patterns and the control of adaptive behavioral responses have revealed organizational principles that are shared by a wide spectrum of animals. Mechanisms of perception and motor control are commonly executed in a distributed network of neurons that lack pontifical elements. Individual neurons even at an organizational level as high as the optic tectum may still have very general response characteristics, and the recruitment of individual neurons reveals little about the nature of the stimulus situation outside. Only the joint evaluation of messages from large populations of such neurons yields unambiguous pictures of the outside world. Stimulus variables are commonly mapped continuously within a stratum of neurons so that their variation over time can be monitored by mechanisms similar to motion detection in a retina. The ordered representation of a stimulus variable within an array of broadly tuned elements allows for a degree of stimulus resolution that by far exceeds that of individual elements in the array. Neural systems are burdened by their evolutionary history and suffer from imperfections that are overcome by a patchwork of compensations. The existence of multiple neuronal representations of sensory information and multiple circuits for the control of behavioral responses should provide the necessary freedom for evolutionary tinkering and the invention of new designs.     

Lack of homogeneity of receptive fields of visual neurons in the cortical area 18 of the cat

The receptive fields of complex neurons within area 18 of the cerebral cortex of the cat were determined by a computer-assisted method using a moving light bar substantially shorter than the long diameter of the receptive field as a visual stimulus. The visual cells repeatedly generated nerve impulses when the stimulus crossed well-defined active points within their receptive fields. Outside of these active points, the cells remained silent. It is suggested that the receptive fields are formed by a discontinuous accumulation of such active points. When the electrical activities of two neighbouring visual neurons are recorded simultaneously, their active points do not coincide. In addition, some active points were located outside the most prominent excitatory part of the receptive field of the studied cells. Individual visual cells typically differ in the number and distribution of active points. Since these cells best respond to a stimulus moving in a certain direction, it is suggested that they may act as direction of movement and/or velocity detectors. Alternate firing of a number of neighboring cells connected to a distributed pattern of peripheral receptors may form a system which is able to code for velocity and direction of the moving stimulus.     

The transmission of coded information over neuronal systems exemplified by the motor rhythmic dominant

Functional organization of neurons in rabbit's sensorimotor cortex was studied before and within several days after formation of the rhythmical dominant focus. Functional reorganization of neurons in cortical microareas took place during actualization of the dominant. The number of functional interneuronal relations within neuronal pairs of a certain type could be increased in comparison with the control values and decreased within pairs of another type. As a result, the total percent of the interneuronal correlations in cortical microareas in the control animals and rabbits with the acting dominant was approximately equal. The total percent of correlations between neurons of the adjacent cortical areas during the actualization of the dominant was significantly higher than in the control due to increased number of correlations with participation of small and medium-sized neurons. A possibility of information circulation about the "stimulus image" in the closed chain of neurons was exemplified by the real micronetwork. The data suggest the reverberation of encoded information between adjacent microareas of the sensorimotor cortex within several days after application of the stimulus, which has formed the excitation focus.     

Dynamic integration of reward and stimulus information in perceptual decision-making

In perceptual decision-making, ideal decision-makers should bias their choices toward alternatives associated with larger rewards, and the extent of the bias should decrease as stimulus sensitivity increases. When responses must be made at different times after stimulus onset, stimulus sensitivity grows with time from zero to a final asymptotic level. Are decision makers able to produce responses that are more biased if they are made soon after stimulus onset, but less biased if they are made after more evidence has been accumulated? If so, how close to optimal can they come in doing this, and how might their performance be achieved mechanistically? We report an experiment in which the payoff for each alternative is indicated before stimulus onset. Processing time is controlled by a “go” cue occurring at different times post stimulus onset, requiring a response within msec. Reward bias does start high when processing time is short and decreases as sensitivity increases, leveling off at a non-zero value. However, the degree of bias is sub-optimal for shorter processing times. We present a mechanistic account of participants'' performance within the framework of the leaky competing accumulator model [1], in which accumulators for each alternative accumulate noisy information subject to leakage and mutual inhibition. The leveling off of accuracy is attributed to mutual inhibition between the accumulators, allowing the accumulator that gathers the most evidence early in a trial to suppress the alternative. Three ways reward might affect decision making in this framework are considered. One of the three, in which reward affects the starting point of the evidence accumulation process, is consistent with the qualitative pattern of the observed reward bias effect, while the other two are not. Incorporating this assumption into the leaky competing accumulator model, we are able to provide close quantitative fits to individual participant data.     

Interacting roles of attention and visual salience in V4

Attention increases the contrast gain of V4 neurons, causing them to respond to an attended stimulus as though its contrast had increased. When multiple stimuli appear within a neuron's receptive field (RF), the neuron responds primarily to the attended stimulus. This suggests that cortical cells may be "hard wired" to respond preferentially to the highest-contrast stimulus in their RF, and neural systems for attention capitalize on this mechanism by dynamically increasing the effective contrast of the stimulus that is task relevant. To test this, we varied the relative contrast of two stimuli within the recorded neurons' RFs, while the monkeys attended away to another location. Increasing the physical contrast of one stimulus caused V4 neurons to respond preferentially to that stimulus and reduced their responses to competing stimuli. When attention was directed to the lower-contrast stimulus, it partially overcame the influence of a competing, higher-contrast stimulus.     

Competition in the temporal domain among neural activities phase-locked to subthreshold oscillations

 In the presence of a subthreshold membrane oscillation, analog information may be encoded in the timing of spike generation phase-locked to the oscillation. With this spike timing neural code, a competitive network of inhibitory spiking neurons was shown to achieve a novel timing mechanism of neural activity selection: the neurons had higher probabilities of becoming winners if they were stimulated earlier in each oscillatory cycle. Here the timing mechanism and its robustness are studied both numerically and analytically, and the conditions to yield a given number of winners (the inhibitory neurons that remain active after the competition) are investigated. The analysis revealed that activity selection with a small number of winners is ensured for broad ranges of values of the parameters such as the strength and time constant of inhibition. In particular, the number of winners is almost unchanged for various timing differences between stimuli to different neurons. This implies that the timing mechanism is useful for such biological information processing as requires perception of a relatively small number of significant stimulus components. Received: 24 January 1996 / Accepted in revised form: 24 July 1996     

Microevolution of neuroendocrine mechanisms regulating reproductive timing in Peromyscus leucopus

A key question in the evolution of life history and in evolutionary physiology asks how reproductive and other life-history traits evolve. Genetic variation in reproductive control systems may exist in many elements of the complex inputs that can affect the hypothalamic-pituitary-gonadal (HPG) or reproductive axis. Such variation could include numbers and other traits of secretory cells, the amount and pattern of chemical message released, transport and clearance mechanisms, and the number and other traits of receptor cells. Selection lines created from a natural population of white-footed mice (Peromyscus leucopus) that contains substantial genetic variation in reproductive inhibition in response to short winter daylength (SD) have been used to examine neuroendocrine variation in reproductive timing. We hypothesized that natural genetic variation would be most likely to occur in the inputs to GnRH neurons and/or in GnRH neurons themselves, but not in elements of the photoperiodic pathway that would have pleiotropic effects on nonreproductive functions as well as on reproductive functions. Significant genetic variation has been found in the GnRH neuronal system. The number of GnRH neurons immunoreactive to an antibody to mature GnRH peptide under conditions maximizing detection of stained neurons was significantly heritable in an unselected control (C) line. Furthermore, a selection line that suppresses reproduction in SD (photoperiod responsive, R) had fewer IR-GnRH neurons than a selection line that maintains reproduction in SD (photoperiod nonresponsive, NR). This supports the hypothesis that genetic variation in characteristics of GnRH neurons themselves may be responsible for the observed phenotypic variation in reproduction in SD. The R and NR lines differ genetically in food intake and iodo-melatonin receptor binding, as well as in other characteristics. The latter findings are consistent with the hypothesis that genetic variation occurs in the nutritional and hormonal inputs to GnRH neurons. Genetic variation also exists in the phenotypic plasticity of responses to two combinations of treatments, (1) food and photoperiod, and (2) photoperiod and age, indicating genetic variation in individual norms of reaction within this population. Overall, the apparent multiple sources of genetic variation within this population suggest that there may be multiple alternative combinations of alleles for both the R and NR phenotypes. If that interpretation is correct, we suggest that this offers some support for the evolutionary "potential" hypothesis and is inconsistent with the evolutionary "constraint" and "symmorphosis" hypotheses for the evolution of complex neuroendocrine pathways.     

Population coding of visual stimuli by cortical neurons tuned to more than one dimension

Neurons in the visual cortex are typically selective to a number of stimulus dimensions. Thus, there is a basic ambiguity in relating the response level of a single neuron to the stimulus values. It is shown that a multi-dimensional stimulus may be coded reliably by an ensemble of neurons, using a weighted average population coding model. Each neurons' contribution to the population signal for each dimension is the product of its response magnitude and its preferred value for that dimension. The sum of the products was normalized by the sum of the ensemble responses. Simulation results show that the representation accuracy increases as the square root of the number of units irrespective of the number of dimensions. Comparison of a specific 2D case of this population code for orientation and spatial frequency to behavioral discrimination levels yields that 10³–10⁴ neurons are needed to reach psychophysical performance. Introduction of each additional dimension requires about 1.7 times the number of neurons in the ensemble to reach the same level of accuracy. This result suggests that neurons may be selective for only 3 to 5 dimensions. It also provides another rationale for the existence of parallel processing streams in vision.     

BOTTLENOSE DOLPHINS CAN GENERALIZE RULES and DEVELOP ABSTRACT CONCEPTS

Abstract: Generalization of a rule is demonstrated if the rule governs a class of problem, and the subject, after successful experience with a limited number of problems, can apply the governing rule to new problems within that class. We show that the bottlenose dolphin ( Tursiops truncatus ) is capable of such generalization for classes of problems requiting the matching of one of two alternative stimuli to a "sample" stimulus to which the animal had been previously exposed, regardless of the sensory domain used: vision, passive listening, or active echolocation. We also show this generalization capability in a related class of problem requiring a judgment of whether a single "probe" stimulus is the same as, or different from, a stimulus or stimuli previously presented. Further, one dolphin was shown capable of developing a true abstract concept of same/different through its ability to categorize pairs of simultaneously presented objects as identical or not. The suggestion that such generalization ability of dolphins may be in question because of so-called exclusion effects is shown to be not tenable when the whole body of available data is considered.     

<Emphasis Type="BoldItalic">In vivo</Emphasis> conditions influence the coding of stimulus features by bursts of action potentials

The functional role of burst firing (i.e. the firing of packets of action potentials followed by quiescence) in sensory processing is still under debate. Should bursts be considered as unitary events that signal the presence of a particular feature in the sensory environment or is information about stimulus attributes contained within their temporal structure? We compared the coding of stimulus attributes by bursts in vivo and in vitro of electrosensory pyramidal neurons in weakly electric fish by computing correlations between burst and stimulus attributes. Our results show that, while these correlations were strong in magnitude and significant in vitro, they were actually much weaker in magnitude if at all significant in vivo. We used a mathematical model of pyramidal neuron activity in vivo and showed that such a model could reproduce the correlations seen in vitro, thereby suggesting that differences in burst coding were not due to differences in bursting seen in vivo and in vitro. We next tested whether variability in the baseline (i.e. without stimulation) activity of ELL pyramidal neurons could account for these differences. To do so, we injected noise into our model whose intensity was calibrated to mimic baseline activity variability as quantified by the coefficient of variation. We found that this noise caused significant decreases in the magnitude of correlations between burst and stimulus attributes and could account for differences between in vitro and in vivo conditions. We then tested this prediction experimentally by directly injecting noise in vitro through the recording electrode. Our results show that this caused a lowering in magnitude of the correlations between burst and stimulus attributes in vitro and gave rise to values that were quantitatively similar to those seen under in vivo conditions. While it is expected that noise in the form of baseline activity variability will lower correlations between burst and stimulus attributes, our results show that such variability can account for differences seen in vivo. Thus, the high variability seen under in vivo conditions has profound consequences on the coding of information by bursts in ELL pyramidal neurons. In particular, our results support the viewpoint that bursts serve as a detector of particular stimulus features but do not carry detailed information about such features in their structure.     

Voltage-dependent burst-to-tonic switching of thalamic cell activity: an in vitro study

The electroresponsiveness of mammalian thalamic neurons was studied in a slice preparation of the guinea pig diencephalon. Although the morphology of the cells varied, their electroresponsive properties were the same. Stimulation of thalamic cells at a membrane potential more negative than--60 mV produced burst responses and stimulation of more depolarized levels produced tonic firing of fast spikes. The burst response is generated by an inactivating Ca++-conductance. It is seen as a slow Ca++-spike which in turn triggers fast Na+-spikes. The Ca++-conductance is deinactivated by hyperpolarization beyond--60 mV. The membranes of thalamic neurons contain a number of other conductances including a Ca++-dependent K+-conductance producing spike afterhyperpolarization and a non-inactivating Na+-conductance which plays an important role during tonic activity of the cells. The early part of a response to a long-lasting stimulus given at rest or at a hyperpolarized level is dominated by the burst and thus is is independent of the stimulus amplitude. During the late part of such a response the firing rate is highly dependent of the stimulus intensity. Current-frequency plots for the first inter-spike intervals after the burst during long stimuli are upward convex, but after "steady-state" is reached the plots are almost linear.     

Comparative strategies in the investigation of neural networks.

Comparative studies on nervous systems, though infrequently undertaken for the purpose of comparison, have yielded some important generalities about the formats of nervous networks, and about the cell biology of certain neural types. In the first category, it is clear that convergent evolutionary processes arrived at very similar networks to accomplish reciprocal and lateral inhibition, and load-compensation in "resistance reflexes." A newer general network format is described, command-derived inhibition, in which the central nervous elements controlling a rapid movement deliver presynaptic inhibition to the terminals of sensory neurons that carry reafferent excitation from the movement. It is argued that such circuits occur in several groups of animals, and that they include as a special class the efferent inhibitory neurons innervating acoustico-lateralis receptors in vertebrates. The properties of circuit elements that now seem to constitute useful generalizations include size principle (the inverse relationship between size and excitability in a variety of neurons), and the late differentiation of sensory neurons, failure to decussate, and their inability to mediate inhibition. Many other generalities have emerged, only to fall; one conclusion from such searches is that many supposedly "basic" properties of cell types or neural circuits are in fact not phylogenetically conservative, however much the physiologist may expect them to be.     

Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks

We discuss numerical methods for simulating large-scale, integrate-and-fire (I&F) neuronal networks. Important elements in our numerical methods are (i) a neurophysiologically inspired integrating factor which casts the solution as a numerically tractable integral equation, and allows us to obtain stable and accurate individual neuronal trajectories (i.e., voltage and conductance time-courses) even when the I&F neuronal equations are stiff, such as in strongly fluctuating, high-conductance states; (ii) an iterated process of spike-spike corrections within groups of strongly coupled neurons to account for spike-spike interactions within a single large numerical time-step; and (iii) a clustering procedure of firing events in the network to take advantage of localized architectures, such as spatial scales of strong local interactions, which are often present in large-scale computational models—for example, those of the primary visual cortex. (We note that the spike-spike corrections in our methods are more involved than the correction of single neuron spike-time via a polynomial interpolation as in the modified Runge-Kutta methods commonly used in simulations of I&F neuronal networks.) Our methods can evolve networks with relatively strong local interactions in an asymptotically optimal way such that each neuron fires approximately once in operations, where N is the number of neurons in the system. We note that quantifications used in computational modeling are often statistical, since measurements in a real experiment to characterize physiological systems are typically statistical, such as firing rate, interspike interval distributions, and spike-triggered voltage distributions. We emphasize that it takes much less computational effort to resolve statistical properties of certain I&F neuronal networks than to fully resolve trajectories of each and every neuron within the system. For networks operating in realistic dynamical regimes, such as strongly fluctuating, high-conductance states, our methods are designed to achieve statistical accuracy when very large time-steps are used. Moreover, our methods can also achieve trajectory-wise accuracy when small time-steps are used. Action Editor: Nicolas Brunel     

Simultaneous detection of neuropeptides and messenger RNA in the magnocellular hypothalamo-neurohypophysial system by a combination of non-radioactive in situ hybridization histochemistry and immunohistochemistry

A protocol was developed combining non-radioactive in situ hybridization histochemistry with enzyme based immunohistochemistry, detect the expression of mRNA in phenotypically defined neurons. Freefloating brain sections were hybridized with the oligonucleotide probes which have been 3-end labelled with biotin-11-dUTP. The hybridized probe was visualized by a combined avidin-biotin bridge method, anti-avidin immunohistochemistry, and horseradish peroxidase detection using diaminobenzidine as a substrate. The in situ hybridization step yielded a very stable reaction product enabling subsequent immunohistochemical reactions using horseradish peroxidase and benzidine dihydrochloride as a chromogen. Magnocellular neurons of the hypothalamo-neurophypophysial system synthesize either vasopressin or oxytocin; water deprivation and chronic saline ingestion are potent stimuli for the expression of both of the genes encoding these neuropeptides. A number of other neuropeptides with putative transmitter action are synthesized in magnocellular neurons during such stimulation. Experiments were performed to explore whether neuropeptide Y immunoreactivity is present within magnocellular vasopressin mRNA-expressing neurons of the hypothalamo-neurophypophysial system. The results clearly demonstrated that neuropeptide Y-immunoreactive elements were present within a number of magnocellular vasopressin mRNA-containing cells. In addition, immunohistochemical detection of the neuropeptides ocytocin and cholecystokinin was carried out on sections hybridized non-radioactively for vasopressin; as expected vasopressin mRNA did not co-exist with cholecystokinin, whereas a few oxytocin immunoreactive neurons in osmotically stimulated animals also contained vasopressin mRNA. The developed method makes possible the immunohistochemical detection of intracellular antigens with concomitant detection of intracellular mRNA.     

Light-induced activation of distinct modulatory neurons triggers appetitive or aversive learning in Drosophila larvae

During classical conditioning, a positive or negative value is assigned to a previously neutral stimulus, thereby changing its significance for behavior. If an odor is associated with a negative stimulus, it can become repulsive. Conversely, an odor associated with a reward can become attractive. By using Drosophila larvae as a model system with minimal brain complexity, we address the question of which neurons attribute these values to odor stimuli. In insects, dopaminergic neurons are required for aversive learning, whereas octopaminergic neurons are necessary and sufficient for appetitive learning. However, it remains unclear whether two independent neuronal populations are sufficient to mediate such antagonistic values. We report the use of transgenically expressed channelrhodopsin-2, a light-activated cation channel, as a tool for optophysiological stimulation of genetically defined neuronal populations in Drosophila larvae. We demonstrate that distinct neuronal populations can be activated simply by illuminating the animals with blue light. Light-induced activation of dopaminergic neurons paired with an odor stimulus induces aversive memory formation, whereas activation of octopaminergic/tyraminergic neurons induces appetitive memory formation. These findings demonstrate that antagonistic modulatory subsystems are sufficient to substitute for aversive and appetitive reinforcement during classical conditioning.     

Frequency-dependent response of SI RA-class neurons to vibrotactile stimulation of the receptive field

Three types of experiment were carried out on anesthetized monkeys and cats. In the first, spike discharge activity of rapidly adapting (RA) SI neurons was recorded extracellularly during the application of different frequencies of vibrotactile stimulation to the receptive field (RF). The second used the same stimulus conditions to study the response of RA-I (RA) cutaneous mechanoreceptive afferents. The third used optical intrinsic signal (OIS) imaging and extracellular neurophysiological recording methods together, in the same sessions, to evaluate the relationship between the SI optical and RA neuron spike train responses to low- vs high-frequency stimulation of the same skin site. RA afferent entrainment was high at all frequencies of stimulation. In contrast, SI RA neuron entrainment was much lower on average, and was strongly frequency-dependent, declining in near-linear fashion from 6 to 200 Hz. Even at 200 Hz, however, unambiguous frequencyfollowing responses were present in the spike train activity of some SI RA neurons. These entrainment results support the "periodicity hypothesis" of Mountcastle et al. ( J Neurophysiol 32: 452-484, 1969) that the capacity to discriminate stimulus frequency over the range 5-50 Hz is attributable to the ability of SI RA pyramidal neurons to discharge action potentials in consistent temporal relationship to stimulus motion, and raise the possibility that perceptual frequency discriminative capacity at frequencies between 50 and 200 Hz might be accounted for in the same way. An increase in vibrotactile stimulus frequency within the range 6-200 Hz consistently resulted in an increase in RA afferent mean spike firing rate (M FR). SI RA neuron M FR also increased as frequency increased between 6 and 50 Hz, but declined as stimulus frequency was increased over the range 50-200 Hz. At stimulus frequencies > 100 Hz, and at positions in the RF other than the receptive field center (RF center ), SI RA neuron MFR declined sharply within 0.5-2s of stimulus onset and rebounded transiently upon stimulus termination. In contrast, when the stimulus was applied to the RF center, MFR increased with increasing frequency and tended to remain well maintained throughout the period of high-frequency stimulation. The evidence obtained in "combined" OIS imaging and extracellular microelectrode recording experiments suggests that SI RA neurons with an RF center that corresponds to the stimulated skin site occupy small foci within the much larger SI region activated by same-site cutaneous flutter stimulation, while for the RA neurons located elsewhere in the large SI region activated by a flutter stimulus, the stimulus site and RF center are different.     

Semantic associations between signs and numerical categories in the prefrontal cortex

The utilization of symbols such as words and numbers as mental tools endows humans with unrivalled cognitive flexibility. In the number domain, a fundamental first step for the acquisition of numerical symbols is the semantic association of signs with cardinalities. We explored the primitives of such a semantic mapping process by recording single-cell activity in the monkey prefrontal and parietal cortices, brain structures critically involved in numerical cognition. Monkeys were trained to associate visual shapes with varying numbers of items in a matching task. After this long-term learning process, we found that the responses of many prefrontal neurons to the visual shapes reflected the associated numerical value in a behaviorally relevant way. In contrast, such association neurons were rarely found in the parietal lobe. These findings suggest a cardinal role of the prefrontal cortex in establishing semantic associations between signs and abstract categories, a cognitive precursor that may ultimately give rise to symbolic thinking in linguistic humans.     

Recurrent networks of submucous neurons controlling intestinal secretion: a modeling study

Secretomotor neurons, immunoreactive for vasoactive intestinal peptide (VIP), are important in controlling chloride secretion in the small intestine. These neurons form functional synapses with other submucosal VIP neurons and transmit via slow excitatory postsynaptic potentials (EPSPs). Thus they form a recurrent network with positive feedback. Intrinsic sensory neurons within the submucosa are also likely to form recurrent networks with positive feedback, provide substantial output to VIP neurons, and receive input from VIP neurons. If positive feedback within recurrent networks is sufficiently large, then neurons in the network respond to even small stimuli by firing at their maximum possible rate, even after the stimulus is removed. However, it is not clear whether such a mechanism operates within the recurrent networks of submucous neurons. We investigated this question by performing computer simulations of realistic models of VIP and intrinsic sensory neuron networks. In the expected range of electrophysiological properties, we found that activity in the VIP neuron network decayed slowly after cessation of a stimulus, indicating that positive feedback is not strong enough to support the uncontrolled firing state. The addition of intrinsic sensory neurons produced a low stable firing rate consistent with the common finding that basal secretory activity is, in part, neurogenic. Changing electrophysiological properties enables these recurrent networks to support the uncontrolled firing state, which may have implications with hypersecretion in the presence of enterotoxins such as cholera-toxin.