Effect of juvenile hormone on short-term olfactory memory in young honeybees (Apis mellifera).

Reliable retention of olfactory learning following a 1-trial classical conditioning of the proboscis extension reflex (PER) is not achieved in honeybees until they are 6-7 days old. Here we show that treatment of newly emerged honeybees with juvenile hormone (JH) has a profound effect on the maturation of short-term olfactory memory. JH-treated individuals display excellent short-term (1 h) memory of associative learning at times as early as 3 days of age and perform consistently better than untreated bees for at least the first week of their lives. By contrast, the retention of long-term (24 h) memory following a 3-trial conditioning of the PER is not significantly improved in JH-treated bees. Our study also shows that experience and (or) chemosensory activation are not essential to improve learning performance in olfactory tasks. The lack of accelerated development of long-term retention of olfactory memories in JH-treated honeybees is discussed in the context of neural circuits suspected to mediate memory formation and retrieval in the honeybee brain.     

药物成瘾及成瘾记忆的研究现状

本文在介绍药物成瘾与学习和记忆密切相关的神经回路及共同分子机制的基础上,围绕学习和记忆在药物成瘾中的作用,综述了关联性学习与复吸,关联性学习与敏化,异常关联性学习与强迫性用药行为,关联性学习及成瘾记忆与成瘾,多重记忆系统与成瘾的发生发展等方面的研究进展,并强调了突触可塑性及成瘾记忆在药物成瘾中的重要性。在此基础上提出：作为慢性脑病的药物成瘾的形成过程的重要特征是它包含着信息的特殊学习类型。药物成瘾与依赖于多巴胺的关联性学习紊乱有密切关系。海马可能在成瘾中扮演重要角色。     

Sequence learning recodes cortical representations instead of strengthening initial ones

We contrast two computational models of sequence learning. The associative learner posits that learning proceeds by strengthening existing association weights. Alternatively, recoding posits that learning creates new and more efficient representations of the learned sequences. Importantly, both models propose that humans act as optimal learners but capture different statistics of the stimuli in their internal model. Furthermore, these models make dissociable predictions as to how learning changes the neural representation of sequences. We tested these predictions by using fMRI to extract neural activity patterns from the dorsal visual processing stream during a sequence recall task. We observed that only the recoding account can explain the similarity of neural activity patterns, suggesting that participants recode the learned sequences using chunks. We show that associative learning can theoretically store only very limited number of overlapping sequences, such as common in ecological working memory tasks, and hence an efficient learner should recode initial sequence representations.     

The Role of non-NMDA-Receptors in the Process of Associative Learning in the Honeybee Apis mellifera

Pharmacological parameters of non-NMDA-receptors and their participation in the associative learning in the honeybee Apis mellifera L. have been studied using the method of conditional reflexes and pharmacological analysis. The effect of 1-amino-3-hydroxy-5-methyl, 4-isoxazolprpionate (AMPA), kainate, domoate, antagonist of AMPA-receptors NS-257 HCl and modulator of AMPA-receptors cyclothiazide was studied on retention of the elaborated conditional reflex in short- and long-term memory. It was shown that AMPA-receptors, but not kainate receptors, are involved in the process of formation of short-term memory and are characterized by pharmacological profile similar with that in molluscs. Coactivation of AMPA- and NMDA-receptors is considered as one of possible mechanisms of formation of short-term memory in the honeybee.     

A hierarchical neural network model for associative memory

A hierarchical neural network model with feedback interconnections, which has the function of associative memory and the ability to recognize patterns, is proposed. The model consists of a hierarchical multi-layered network to which efferent connections are added, so as to make positive feedback loops in pairs with afferent connections. The cell-layer at the initial stage of the network is the input layer which receives the stimulus input and at the same time works as an output layer for associative recall. The deepest layer is the output layer for pattern-recognition. Pattern-recognition is performed hierarchically by integrating information by converging afferent paths in the network. For the purpose of associative recall, the integrated information is again distributed to lower-order cells by diverging efferent paths. These two operations progress simultaneously in the network. If a fragment of a training pattern is presented to the network which has completed its self-organization, the entire pattern will gradually be recalled in the initial layer. If a stimulus consisting of a number of training patterns superposed is presented, one pattern gradually becomes predominant in the recalled output after competition between the patterns, and the others disappear. At about the same time when the recalled pattern reaches a steady state in he initial layer, in the deepest layer of the network, a response is elicited from the cell corresponding to the category of the finally-recalled pattern. Once a steady state has been reached, the response of the network is automatically extinguished by inhibitory signals from a steadiness-detecting cell. If the same stimulus is still presented after inhibition, a response for another pattern, formerly suppressed, will now appear, because the cells of the network have adaptation characteristics which makes the same response unlikely to recur. Since inhibition occurs repeatedly, the superposed input patterns are recalled one by one in turn.     

A review of cell assemblies

Since the cell assembly (CA) was hypothesised, it has gained substantial support and is believed to be the neural basis of psychological concepts. A CA is a relatively small set of connected neurons, that through neural firing can sustain activation without stimulus from outside the CA, and is formed by learning. Extensive evidence from multiple single unit recording and other techniques provides support for the existence of CAs that have these properties, and that their neurons also spike with some degree of synchrony. Since the evidence is so broad and deep, the review concludes that CAs are all but certain. A model of CAs is introduced that is informal, but is broad enough to include, e.g. synfire chains, without including, e.g. holographic reduced representation. CAs are found in most cortical areas and in some sub-cortical areas, they are involved in psychological tasks including categorisation, short-term memory and long-term memory, and are central to other tasks including working memory. There is currently insufficient evidence to conclude that CAs are the neural basis of all concepts. A range of models have been used to simulate CA behaviour including associative memory and more process- oriented tasks such as natural language parsing. Questions involving CAs, e.g. memory persistence, CAs’ complex interactions with brain waves and learning, remain unanswered. CA research involves a wide range of disciplines including biology and psychology, and this paper reviews literature directly related to the CA, providing a basis of discussion for this interdisciplinary community on this important topic. Hopefully, this discussion will lead to more formal and accurate models of CAs that are better linked to neuropsychological data.     

Network, cellular and molecular mechanisms of plasticity in simple nervous systems

In the present study we will try to single out several principles of the nervous system functioning essential for describing mechanisms of learning and memory basing on our own experimental investigation of cellular mechanisms of memory in the nervous system of gastropod molluscs and literature data: main changes in functioning due to learning occur in effectivity of synaptic inputs and in the intrinsic properties of postsynaptic neurons; due to learning some synaptic inputs of neurons selectively change its effectivity due to pre- and postsynaptic changes, but the induction of plasticity always starts in postsynapse, maintaining of long-term memory in postsynapse is also shown; reinforcement is not related to activity of the neural chain receptor-sensory neuron-interneuron-motoneuron-effector; reinforcement is mediated via activity of modulatory neurons, and in some cases can be exerted by a single neuron; activity of modulatory neurons is necessary for development of plastic modifications of behavior (including associative), but is not needed for recall of conditioned responses. At the same time, the modulatory neurons (in fact they constitute a neural reinforcement system) are necessary for recall of context associative memory; changes due to learning occur at least in two independent loci in the nervous system. A possibility for erasure of memory with participation of nitroxide is experimentally and theoretically based.     

The spatiotemporal learning rule and its efficiency in separating spatiotemporal patterns

The hippocampus plays an important role in the course of establishing long-term memory, i.e., to make short-term memory of spatially and temporally associated input information. In 1996 (Tsukada et al. 1996), the spatiotemporal learning rule was proposed based on differences observed in hippocampal long-term potentiation (LTP) induced by various spatiotemporal pattern stimuli. One essential point of this learning rule is that the change of synaptic weight depends on both spatial coincidence and the temporal summation of input pulses. We applied this rule to a single-layered neural network and compared its ability to separate spatiotemporal patterns with that of other rules, including the Hebbian learning rule and its extended rules. The simulated results showed that the spatiotemporal learning rule had the highest efficiency in discriminating spatiotemporal pattern sequences, while the Hebbian learning rule (including its extended rules) was sensitive to differences in spatial patterns.     

Lateralization and unilateral transfer of spatial memory in marsh tits

Summary The results reported in this paper demonstrate lateralization and transfer of spatial memory processing in an adult, food-storig bird. The technique of monocular occlusion was used to investigate lateralization and memory transfer in food-storing marsh tits (Parus palustris) for two tasks, food-storing and one-trial associative learning, which rely on one-trial learning for the spatial location of hidden food items. In the food-storing task, marsh tits had to return to the sites where they had previously stored a seed; in the one-trial associative learning task, the birds had to return to sites where they had been allowed to eat some, but not all, of a piece of peanut. For both spatial memory tasks, it was demonstrated that although the visual systems fed by both eyes are involved in short-term storage, the right eye system is associated with long-term storage, and that memories are transferred from the left to the right eye system between 3 and 24 h after memory formation.     

DNA methylation mediates the discriminatory power of associative long-term memory in honeybees

Memory is created by several interlinked processes in the brain, some of which require long-term gene regulation. Epigenetic mechanisms are likely candidates for regulating memory-related genes. Among these, DNA methylation is known to be a long lasting genomic mark and may be involved in the establishment of long-term memory. Here we demonstrate that DNA methyltransferases, which induce and maintain DNA methylation, are involved in a particular aspect of associative long-term memory formation in honeybees, but are not required for short-term memory formation. While long-term memory strength itself was not affected by blocking DNA methyltransferases, odor specificity of the memory (memory discriminatory power) was. Conversely, perceptual discriminatory power was normal. These results suggest that different genetic pathways are involved in mediating the strength and discriminatory power of associative odor memories and provide, to our knowledge, the first indication that DNA methyltransferases are involved in stimulus-specific associative long-term memory formation.     

Synaptic conditions for auto-associative memory storage and pattern completion in Jensen et al.’s model of hippocampal area CA3

Jensen et al. (Learn Memory 3(2–3):243–256, 1996b) proposed an auto-associative memory model using an integrated short-term memory (STM) and long-term memory (LTM) spiking neural network. Their model requires that distinct pyramidal cells encoding different STM patterns are fired in different high-frequency gamma subcycles within each low-frequency theta oscillation. Auto-associative LTM is formed by modifying the recurrent synaptic efficacy between pyramidal cells. In order to store auto-associative LTM correctly, the recurrent synaptic efficacy must be bounded. The synaptic efficacy must be upper bounded to prevent re-firing of pyramidal cells in subsequent gamma subcycles. If cells encoding one memory item were to re-fire synchronously with other cells encoding another item in subsequent gamma subcycle, LTM stored via modifiable recurrent synapses would be corrupted. The synaptic efficacy must also be lower bounded so that memory pattern completion can be performed correctly. This paper uses the original model by Jensen et al. as the basis to illustrate the following points. Firstly, the importance of coordinated long-term memory (LTM) synaptic modification. Secondly, the use of a generic mathematical formulation (spiking response model) that can theoretically extend the results to other spiking network utilizing threshold-fire spiking neuron model. Thirdly, the interaction of long-term and short-term memory networks that possibly explains the asymmetric distribution of spike density in theta cycle through the merger of STM patterns with interaction of LTM network.     

Associative Memory and Segmentation in an Oscillatory Neural Model of the Olfactory Bulb

We discuss the first few stages of olfactory processing in the framework of a layered neural network. Its central component is an oscillatory associative memory, describing the external plexiform layer, that consists of inhibitory and excitatory neurons with dendrodendritic interactions. We explore the computational properties of this neural network and point out its possible functional role in the olfactory bulb. When receiving a complex input that is composed of several odors, the network segments it into its components. This is done in two stages. First, multiple odor input is preprocessed in the glomerular layer via a decorrelation mechanism that relies on temporal independence of odor sources. Second, as the recall process of a pattern consists of associative convergence to an oscillatory attractor, multiple inputs are identified by alternate dominance of memory patterns during different sniff cycles. This could explain how quick analysis of mixed odors is subserved by the rapid sniffing behavior of highly olfactory animals. When one of the odors is much stronger than the rest, the network converges onto it, thus displaying odor masking.     

Learning in honeybees: from molecules to behaviour

Studies in a variety of organisms as diverse as molluscs, insects, birds and mammals have shown that memories can exist in a variety of temporal domains ranging from short-term memories in the range of minutes to long-term memories lasting a lifetime. While transient covalent modifications of proteins underlie short-term memory, the formation of long-term memory requires gene expression and protein synthesis. Different intracellular signalling cascades have been implicated in distinct aspects of learning and memory formation. Little is known however, about how learning in intact animals is related to the modulation of these signalling cascades and how this contributes to distinct neuronal and behavioural changes in vivo. Associative learning in the honeybee provides the opportunity to study processes of memory formation by analysing its progression through different phases, across levels of behaviour, neural circuits, and cellular signalling pathways. The findings reveal evidence that various cellular signalling pathways in the neuronal circuit of distinct brain areas play a role in different processes during learning and memory formation.     

主动联想记忆神经网络模型

在信息编码能提高联想记忆的存贮能力和脑内存在主动活动机制的启发下,提出一个主动联想记忆模型。模型包括两个神经网络,其一为输入和输出网络,另一个为在学习时期能自主产生兴奋模式的主动网络。两个网络的神经元之间有突触联系。由于自主产生的兴奋模式与输入无关,并可能接近于相互正交,因此,本模型有较高的存贮能力。初步分析和计算机仿真证明：本模型确有比通常联想记忆模型高的存贮能力,特别是在输入模式间有高度相关情况下、最后,对提出的模型与双向自联想记忆和光学全息存贮机制的关系作了讨论。     

A self-organizing neural network with a function of associative memory: Feedback-type cognitron

Previously, one of the authors proposed a new hypothesis on the organization of synaptic connections, and constructed a model of self-organizing multi-layered neural network cognitron (Fukushima, 1975). the cognitron consists of a number of neural layers with similar structure connected in a cascade one after another. We have modified the structure of the cognitron, and have developed a new network having an ability of associative memory. The new network, named a feedback-type cognitron, has not only the feedforward connections as in the conventional cognitron, but also modifiable feedback connections from the last-layer cells to the front-layer ones. This network has been simulated on a digital computer. If several stimulus patterns are repeatedly presented to the network, the interconnections between the cells are gradually organized. The feedback connections, as well as the conventional feedforward ones, are self-organized depending on the characteristies of the externally presented stimulus patterns. After adequate number of stimulus presentations, each cell usually acquires the selective responsiveness to one of the stimulus patterns which have been frequently given. That is, every different stimulus pattern becomes to elicit an individual response to the network. After the completion of the self-organization, several stimulus patterns are presented to the network, and the responses are observed. Once a stimulus is given to the network, the signal keeps circulating in the network even after cutting off the stimulus, and the response gradually changes. Even though an imperfect or an ambiguous pattern is presented, the response usually converges to one of the patterns which have been frequently given during the process of self-organization. In some cases, however, a new pattern which has never been presented before, emerges. It is seen that this feedback-type cognitron has characteristics quite similar to some functions of the brain, such as the associative recall of memory, or the creation of a new idea by intuition.     

Backward signal from medial temporal lobe in neural circuit reorganization of primate inferotemporal cortex

Neuropsychological theories proposed a critical role of the interaction between the medial temporal lobe and neocortex in the formation of long-term memory for facts and events, which has often been tested by learning of a series of paired words or figures in humans. We identify neural mechanisms of this long-term memory formation process by single-unit recording and molecular biological methods in an animal model of visual pair-association task in monkeys. In our previous studies, we found a group of neurons that manifested selective responses to both of the paired associates (pair-coding neuron) in the anterior inferior temporal (IT) cortex. It provides strong evidence that single IT neurons acquire the response-selectivity through associative learning, and suggests that the reorganized neural circuits for the pair-coding neurons serve as the memory engram of the pair-association learning. In this article, we investigated further mechanisms of the neural circuit reorganization. First, we tested the role of the backward connections from the medial temporal lobe to IT cortex. lbotenic acid was injected unilaterally into the entorhinal and perirhinal cortex which provided massive backward projections ipsilaterally to IT cortex. We found that the limbic lesion disrupted the associative code of the IT neurons between the paired associates, without impairing the visual response to each stimulus. Second, we ask why the limbic-neocortical interactions are so important. We hypothesize that limbic neurons would undergo rapid modification of synaptic connectivity and provide backward signals that guide reorganization of neocortical neural circuits. We then investigated the molecular basis of such rapid synaptic modifiability by detecting the expression of immediate-early genes. We found strong expression of zif268 during the learning of a new set of paired associates, most intensively in area 36 of the perirhinal cortex. All these results with visual pair-association task support our hypothesis, and demonstrate that the ‘consolidation’ process, which was first proposed on the basis of clinico-psychological evidence, can now be examined in the primate with neurophysiolocical and molecular biological approaches.     

Modeling neural mechanisms of vertebrate habituation: Locus specificity and pattern discrimination

A critical problem in neurobiology is to explain how the central nervous system coordinates pattern discrimination and locus specificity in learning. This problem is investigated in anuran amphibians who demonstrate both locus specificity and pattern discrimination in visual habituation. A neural mechanism is proposed whereby neural circuitry for pattern discrimination is shared by a spatial memory system. Such learning processes are argued to occur in the medial pallium (MP), the anuran's homolog of mammalian hippocampus. Necessary mapping from the shared network to spatial memory is set up by a mechanism that forms topographical connections, with desired orientation determined by activity gradient in presynaptic and postsynaptic layers. The model of MP is tested on both locus and stimulus specific habituation, which involve short-term as well as long-term synaptic plasticity. Successful modeling yields a set of predictions concerning MP organization and learning properties.     

The octopus vertical lobe modulates short-term learning rate and uses LTP to acquire long-term memory

Analyzing the processes and neuronal circuitry involved in complex behaviors in phylogenetically remote species can help us understand the evolution and function of these systems. Cephalopods, with their vertebrate-like behaviors but much simpler brains, are ideal for such an analysis. The vertical lobe (VL) of Octopus vulgaris is a pivotal brain station in its learning and memory system. To examine the organization of the learning and memory circuitry and to test whether the LTP that we discovered in the VL is involved in behavioral learning, we tetanized the VL to induce a global synaptic enhancement of the VL pathway. The effects of tetanization on learning and memory of a passive avoidance task were compared to those of transecting the same pathway. Tetanization accelerated and transection slowed short-term learning to avoid attacking a negatively reinforced object. However, both treatments impaired long-term recall the next day. Our results suggest that the learning and memory system in the octopus, as in mammals [9], is separated into short- and long-term memory sites. In the octopus, the two memory sites are not independent; the VL, which mediates long-term memory acquisition through LTP, also modulates the circuitry controlling behavior and short-term learning.     

Neural Population-Level Memory Traces in the Mouse Hippocampus

One of the fundamental goals in neurosciences is to elucidate the formation and retrieval of brain''s associative memory traces in real-time. Here, we describe real-time neural ensemble transient dynamics in the mouse hippocampal CA1 region and demonstrate their relationships with behavioral performances during both learning and recall. We employed the classic trace fear conditioning paradigm involving a neutral tone followed by a mild foot-shock 20 seconds later. Our large-scale recording and decoding methods revealed that conditioned tone responses and tone-shock association patterns were not present in CA1 during the first pairing, but emerged quickly after multiple pairings. These encoding patterns showed increased immediate-replay, correlating tightly with increased immediate-freezing during learning. Moreover, during contextual recall, these patterns reappeared in tandem six-to-fourteen times per minute, again correlating tightly with behavioral recall. Upon traced tone recall, while various fear memories were retrieved, the shock traces exhibited a unique recall-peak around the 20-second trace interval, further signifying the memory of time for the expected shock. Therefore, our study has revealed various real-time associative memory traces during learning and recall in CA1, and demonstrates that real-time memory traces can be decoded on a moment-to-moment basis over any single trial.     

A model of localized iconic memory, replicable and associative, using time sharing and 3 neuronal communication modes

A model is proposed for the functioning of an iconic memory involving several layers of neurones. A small group of neurones in one layer project their terminations over the terminations of a single neurone of the superior layer. According to the communication mode (emission or reception), a neurone in one layer can memorize the state of the terminations of a neurone of the superior layer, or impose on the latter the state of its own terminations. In the comparison mode, an emitting neurone compares its state to another emitting neurone and, in case of sufficient similarity, switches to the reception mode (associative recall). The first layer, corresponding to short-term memory, communicates with the cells involved in the representation of the perceived image. This model makes possible the establishment of a correspondence between a percept and a neurone, the replication of memorized configurations, the restructuration of memory and, starting with a percept or a memorized item, the integral associative recall of all similar memorized items.