Neuronal ensemble dynamics in associative learning

Associative learning restructures the activity of numerous neurons distributed across cortical and subcortical regions. Individual neurons change the rate or timing of spiking patterns in response to environmental stimuli as they become associated with salient outcomes. Recent large–scale activity monitoring in rodents has uncovered that these learning-related changes occur concertedly across groups of neurons within and between brain regions. These changes yield neuronal representations of learned associations in three types of ensemble dynamics: ensemble firing rates, multineuron coactivity, and sequential activity. Here, I review some of the most robust demonstrations of these dynamics in the rodent neocortex and hippocampus and discuss their potential function in memory encoding, consolidation, and retrieval.     

Serial order learning in associative formation

Serial order learning was investigated in rats by delivering food to two spatially distinct feeders. All rats received three food pellets in feeder A delivered 10 min into the session. Three additional pellets were then delivered in feeder B after 20s, in Group Short (S), or 150 s, in Group Long (L). The rats in Group S learned the A-B association better than the rats in Group L. Of more interest, however, was that the rats in Group S showed more anticipatory responding to feeder A, suggesting subjects had better learned that feeder A delivered food "first". Implications for classical conditioning and serial order learning are considered.     

Studying behavioural variation in salmonids from an ecological perspective: observations questions methodological considerations

Salmonid fish are an ecologically important and extensively studied group of fish which concern many interest groups in our society. The aim of this paper is to discuss and suggest solutions to the multifaceted problems associated with studying behavioural variation in salmonids, with focus on designing behavioural studies that are ecologically relevant. Many of the general problems and solutions discussed can be applied to other animals as well. First, the importance of asking clear questions when conceiving behavioural studies is addressed, using Tinbergen’s four questions and associated theories as stepping stones towards generating testable hypotheses about behavioural variation. We then address a range of methodological challenges encountered when attempting to study behavioural variation in salmonids and suggest solutions to overcome these problems. A range of approaches is discussed, from highly controllable laboratory experiments to monitoring studies of behaviour in the wild. The importance of combining lab- and field approaches to evaluate the ecological relevance of behavioural variation is highlighted. Finally, we suggest a general framework using a multi-faceted research approach to address questions about the behavioural ecology of salmonids (and other animals) so that knowledge can progress, and the ecological relevance of behavioural studies can be validated.     

Landmark learning: An illustration of associative search

In a previous paper we defined the associative search problem and presented a system capable of solving it under certain conditions. In this paper we interpret a spatial learning problem as an associative search task and describe the behavior of an adaptive network capable of solving it. This example shows how naturally the associative search problem can arise and permits the search, association, and generalization properties of the adaptive network to bee clearly illustrated.     

Dusky damselfish Stegastes fuscus relational learning: evidences from associative and spatial tasks

This study investigated the ability of the dusky damselfish Stegastes fuscus to associate conditioned and unconditioned stimuli (single CS–US) and to find a specific place in a clueless ambiece (spatial learning). After tested for colour preference and showing no specific colour attractively, the fish were trained to associate a colour cue with a stimulus fish (conspecific). Fish were then challenged to locate the exact place where the stimulus fish was presented. Stegastes fuscus spent most time close to the zone where stimulus was presented, even without obvious marks for orientation. The results confirm that S. fuscus show single CS–US learning and suggest the fish ability for spatial orientation. Stegastes fuscus appears to use multiple senses (sight and lateral line) for cues association and recall, and appear to perform relational learning similar to mammals. These data suggest the importance of cognitive skill for reef fishes that may have contributed to their establishment and evolutionary success in such complex environment.     

Impaired associative learning in schizophrenia: behavioral and computational studies

Associative learning is a central building block of human cognition and in large part depends on mechanisms of synaptic plasticity, memory capacity and fronto–hippocampal interactions. A disorder like schizophrenia is thought to be characterized by altered plasticity, and impaired frontal and hippocampal function. Understanding the expression of this dysfunction through appropriate experimental studies, and understanding the processes that may give rise to impaired behavior through biologically plausible computational models will help clarify the nature of these deficits. We present a preliminary computational model designed to capture learning dynamics in healthy control and schizophrenia subjects. Experimental data was collected on a spatial-object paired-associate learning task. The task evinces classic patterns of negatively accelerated learning in both healthy control subjects and patients, with patients demonstrating lower rates of learning than controls. Our rudimentary computational model of the task was based on biologically plausible assumptions, including the separation of dorsal/spatial and ventral/object visual streams, implementation of rules of learning, the explicit parameterization of learning rates (a plausible surrogate for synaptic plasticity), and learning capacity (a plausible surrogate for memory capacity). Reductions in learning dynamics in schizophrenia were well-modeled by reductions in learning rate and learning capacity. The synergy between experimental research and a detailed computational model of performance provides a framework within which to infer plausible biological bases of impaired learning dynamics in schizophrenia.     

Neurophysiological changes and dynamics of bound calcium during the development of associative learning in Helix lucorum

Neurophysiological effects and the dynamics of the content of bound calcium (Ca-b) in command neurons (LP1 and RP1) of defensive behavior during food aversion conditioning are studied inHelix lucorum. In the case of associative learning, there arises in these cells both a response to the conditioned stimulus and a nonspecific facilitation of the reactions to sensory stimuli that is characteristic for the state of sensitization. A response to the presentation of a conditioned stimulus is detected approximately 30 min after the development of long-term sensitization. The use of three or more paired stimuli reveals the characteristic dynamics of the level of Ca-b, which correlates with the neurophysiological effects and differs from the changes in Ca-b content during the development of "pure" sensitization. It is thought that the command neuron of defense behavior exhibits inHelix differences of the molecular-cellular mechanisms lying at the basis of the development of associative learning and sensitization.P. K. Anokhin Institute of Normal Physiology, Russian Academy of Sciences, Moscow. I. P. Pavlov Institute of Physiology, Russian Academy of Sciences, St. Petersburg. Translated from Neirofiziologiya, Vol. 24, No. 6, pp. 691–701, November–December, 1992.     

Immune response inhibits associative learning in insects

In vertebrates, it is well established that there are many intricate interactions between the immune system and the nervous system, and vice versa. Regarding insects, until now little has been known about the link between these two systems. Here, we present behavioural evidence indicating a link between the immune system and the nervous system in insects. We show that otherwise non-infected honeybees whose immune systems are challenged by a non-pathogenic immunogenic elicitor lipopolysaccharide (LPS) have reduced abilities to associate an odour with sugar reward in a classical conditioning paradigm. The cost of an immune response therefore not only affects survival of the host, as previously shown, but also everyday behaviour and memory formation.     

One-trial associative odor learning in neonatal mice

Behavior genetics studies in mice demand efficient training protocols for rapid phenotypic screening. However, the capacity of neonatal mice to form and retain associative memories has been difficult to study due to their limited sensorimotor capacities. The present study describes a method for robust, naturalistic associative learning in neonatal mice as young as 3 days old. After removal of the dam from the home cage for 2 h, preweanling CD-1 mice of ages 3, 5, and 10 days postnatal were conditioned to associate an arbitrary odorant with the suckling and milk delivery that ensued upon her return to the home cage. After a second maternal deprivation, neonates were tested on their acquired preference for that odorant. Neonates exhibited a learned preference for the conditioned odorant over a novel control odorant. No learning was observed without deprivation, that is, when the dam was removed only briefly for scenting. One-trial learning sufficed to show clear preferences for the conditioned odorant, although repeated training (three sessions over 8 days) significantly increased the expression of preference. The development of neonatal associative learning protocols requiring minimal human intervention is important for the behavioral phenotyping of mutant and transgenic strains, particularly those modeling developmental disorders.     

Scaling from mycelial growth to infection dynamics: a reaction diffusion approach

Numerous models have been proposed for the dynamics of fungal growth, and also for the dynamics of infection. Few models, however, have combined the mechanistic interpretation of mycelial growth with epidemiological models for the transmission of infection. Many of the mechanistic models seek to include considerable biological detail, which necessarily leads to a proliferation of state variables and parameters. Including such models within an epidemiological framework makes interpretation of underpinning processes difficult. A simple reaction diffusion model for the growth and spread of fungal mycelium is introduced and analysed, scaling from the small-scale parameters for mycelial dynamics to the large-scale properties of the colony. By coupling the output to a parsimonious epidemiological model for the dynamics of primary infection, we analyse the sensitivity of the probability of successful infection of a host to the colony dynamics associated with local bulking-up, extension, growth and nutrient consumption by the mycelium. In particular we identify optimal trade-offs in bulking-up versus dispersal in controlling infection dynamics.     

Beyond origami: using behavioural observations as a strategy to improve trap design

In contrast to ad hoc methods of developing traps for pest monitoring systems, a systematic approach using direct observation of animals allowed a greater understanding of the reasons why trap catch was significantly different in traps of basically similar design. The information gained using this approach could then be used to guide the further development of the trap. The same feature on two related designs of cockroach trap was varied: the slope of the ramp leading into the trap was either 60°, 30°, or 0°. The 30° ramp version of both traps caught significantly more Blattella germanica (L.) (Dictyoptera: Blattellidae). The 60° and 0° ramp versions both caught equal, lower, numbers but observation showed that these net catches were achieved by quite different means; few insects entered over the 60° ramps but none escaped, whereas all entered over the 0° ramps but half escaped. Similar approaches could be applied to other insect-trap systems.     

Associative search network: A reinforcement learning associative memory

An associative memory system is presented which does not require a teacher to provide the desired associations. For each input key it conducts a search for the output pattern which optimizes an external payoff or reinforcement signal. The associative search network (ASN) combines pattern recognition and function optimization capabilities in a simple and effective way. We define the associative search problem, discuss conditions under which the associative search network is capable of solving it, and present results from computer simulations. The synthesis of sensory-motor control surfaces is discussed as an example of the associative search problem.     

Simple minds: a qualified defence of associative learning

Using cooperation in chimpanzees as a case study, this article argues that research on animal minds needs to steer a course between 'association-blindness'-the failure to consider associative learning as a candidate explanation for complex behaviour-and 'simple-mindedness'-the assumption that associative explanations trump more cognitive hypotheses. Association-blindness is challenged by the evidence that associative learning occurs in a wide range of taxa and functional contexts, and is a major force guiding the development of complex human behaviour. Furthermore, contrary to a common view, association-blindness is not entailed by the rejection of behaviourism. Simple-mindedness is founded on Morgan's canon, a methodological principle recommending 'lower' over 'higher' explanations for animal behaviour. Studies in the history and philosophy of science show that Morgan failed to offer an adequate justification for his canon, and subsequent attempts to justify the canon using evolutionary arguments and appeals to simplicity have not been successful. The weaknesses of association-blindness and simple-mindedness imply that there are no short-cuts to finding out about animal minds. To decide between associative and yet more cognitive explanations for animal behaviour, we have to spell them out in sufficient detail to allow differential predictions, and to test these predictions through observation and experiment.     

Picophytoplankton dynamics in the equatorial Pacific: diel cycling from flow-cytometer observations

The French JGOFS cruise FLUPAC was conducted in October–November 1994 in the western and central equatorial Pacific Ocean. During a 7-day time series at 150 °W, in addition to conventional sampling (four times per day from discrete depths between 0 and 150 m), a high frequency (hourly) experiment was performed by continuously pumping water at 5 m below the surface over 24 h. Flow cytometric measurements allowed us to recognise and to follow separately the two major components of equatorial picophytoplankton, the Prochlorococcus and the picoeukaryotes. The hourly surface experiment confirmed the synchrony of Prochlorococcus cell division and showed that picoeukaryotes exhibited a similar behaviour. The main consequence is that the maximum potential growth rate of picophytoplankton is one doubling per day for both cell groups. The vertical profiles indicated that the diel cycling extends throughout the surface layer for both algal groups. The cells were observed to divide daily from late afternoon to the middle of the night, and then to disappear, probably as a result of grazing. In the surface layer, variations of abundance allowed us to estimate a growth rate of about 0.6 day¹. Mean cell light scattering parFS as measured by the cytometer indicated a decrease in cell size concurrent with cell division and an increase during the photosynthetic growth phase.     

Optimising synaptic learning rules in linear associative memories

Associative matrix memories with real-valued synapses have been studied in many incarnations. We consider how the signal/noise ratio for associations depends on the form of the learning rule, and we show that a covariance rule is optimal. Two other rules, which have been suggested in the neurobiology literature, are asymptotically optimal in the limit of sparse coding. The results appear to contradict a line of reasoning particularly prevalent in the physics community. It turns out that the apparent conflict is due to the adoption of different underlying models. Ironically, they perform identically at their co-incident optima. We give details of the mathematical results, and discuss some other possible derivations and definitions of the signal/noise ratio.     

Input coding in animal and human associative learning

Two appetitive conditioning experiments with rats investigated whether the degree of generalization between a compound and its component parts is fixed or variable. Both experiments used a two-stage transfer design. In Stage 1, the elemental groups learned that a compound and its component parts signaled the same outcome (i.e. C+, D+, CD+), whereas the configural groups learned that a compound and its component parts signaled different outcomes (i.e. C+, D+, CD-, where '+' is pellets and '-' is no pellets). In Stage 2, the rats were tested for reductions in generalization. Experiment 1 found no evidence that past configural learning reduced generalization when a new set of alike-treated A and B elements were presented in compound for the first time. Experiment 2 found no evidence that past configural learning reduced generalization when the stimuli of Stage 1 were presented in a new C-, D-, CD+ relation. In contrast to findings with humans, these results suggest that past experience plays a minor role in how stimuli are encoded in animal conditioning.