A neural network for processing olfactory-like stimuli

Several critical issues associated with the processing of olfactory stimuli in animals (but focusing on insects) are discussed with a view to designing a neural network which can process olfactory stimuli. This leads to the construction of a neural network that can learn and identify the quality (direction cosines) of an input vector or extract information from a sequence of correlated input vectors, where the latter corresponds to sampling a time varying olfactory stimulus (or other generically similar pattern recognition problems). The network is constructed around a discrete time content-addressable memory (CAM) module which basically satisfies the Hopfield equations with the addition of a unit time delay feedback. This modification improves the convergence properties of the network and is used to control a switch which activates the learning or template formation process when the input is “unknown”. The network dynamics are embedded within a sniff cycle which includes a larger time delay (i.e. an integert _s <1) that is also used to control the template formation switch. In addition, this time delay is used to modify the input into the CAM module so that the more dominant of two mingling odors or an odor increasing against a background of odors is more readily identified. The performance of the network is evaluated using Monte Carlo simulations and numerical results are presented.     

蜜蜂对复合气味中特征因素的选择性记忆巩固的研究

目的 蜜蜂天生具有丰富的嗅觉辨识能力,觅食、交配、导航以及社交活动均依赖其嗅觉系统,是研究嗅觉感知和学习记忆的行为及神经机制的理想模型。蜜蜂既能够将某个复合气味作为一个整体也可以将复合气味的各组成成分进行辨别和区分,但是在特征依赖的联合记忆中依据何种原则进行加工并存储到长期记忆还不清楚。方法 本文利用特征阳性（feature positive：AB+,B-）和特征阴性（feature negative：AB-,B+）的奖赏性嗅觉条件化,训练蜜蜂对复合气味和成分气味的辨别,并检测蜜蜂对复合气味（AB）、成分气味（B）以及特征气味（A）的中长时记忆（3 h）和长时记忆（24 h）。结果 在特征阳性的奖赏性嗅觉条件化中,蜜蜂对训练过的气味可以形成稳定的中长时和长时记忆,并且对复合气味中的特征气味的记忆与复合气味的记忆呈现高度相似。但在特征阴性的奖赏性嗅觉条件化中,蜜蜂虽能够在3 h和24 h对训练过的两种气味具有显著的伸喙反应差异,且对特征阴性的气味无显著反应,但对复合气味的反应随时间的推移而增加。结论 实验结果表明,蜜蜂选择性地将与奖赏信息联合出现的气味巩固到长时记忆中,但并未依据特征成分加工储存到长时记忆中。奖赏信息预示着食物源,与生存息息相关,表明对环境信息进行选择性的记忆巩固加工并储存可能是低等动物高效地编码生存相关信息的重要策略。     

An olfactory recognition model based on spatio-temporal encoding of odor quality in the olfactory bulb

In order to study the problem how the olfactory neural system processes the odorant molecular information for constructing the olfactory image of each object, we present a dynamic model of the olfactory bulb constructed on the basis of well-established experimental and theoretical results. The information relevant to a single odor, i.e. its constituent odorant molecules and their mixing ratios, are encoded into a spatio-temporal pattern of neural activity in the olfactory bulb, where the activity pattern corresponds to a limit cycle attractor in the mitral cell network. The spatio-temporal pattern consists of a temporal sequence of spatial firing patterns: each constituent molecule is encoded into a single spatial pattern, and the order of magnitude of the mixing ratio is encoded into the temporal sequence. The formation of a limit cycle attractor under the application of a novel odor is carried out based on the intensity-to-time-delay encoding scheme. The dynamic state of the olfactory bulb, which has learned many odors, becomes a randomly itinerant state in which the current firing state of the bulb itinerates randomly among limit cycle attractors corresponding to the learned odors. The recognition of an odor is generated by the dynamic transition in the network from the randomly itinerant state to a limit cycle attractor state relevant to the odor, where the transition is induced by the short-term synaptic changes made according to the Hebbian rule under the application of the odor stimulus. Received: 28 July 1997 / Accepted in revised form: 6 May 1998     

Neuronal circuits and computations: Pattern decorrelation in the olfactory bulb

Neuronal circuits in the olfactory bulb transform odor-evoked activity patterns across the input channels, the olfactory glomeruli, into distributed activity patterns across the output neurons, the mitral cells. One computation associated with this transformation is a decorrelation of activity patterns representing similar odors. Such a decorrelation has various benefits for the classification and storage of information by associative networks in higher brain areas. Experimental results from adult zebrafish show that pattern decorrelation involves a redistribution of activity across the population of mitral cells. These observations imply that pattern decorrelation cannot be explained by a global scaling mechanism but that it depends on interactions between distinct subsets of neurons in the network. This article reviews insights into the network mechanism underlying pattern decorrelation and discusses recent results that link pattern decorrelation in the olfactory bulb to odor discrimination behavior.     

Odor similarity does not influence the time needed for odor processing

The brain's link between perception and action involves several steps, which include stimulus transduction, neuronal coding of the stimulus, comparison to a memory template and choice of an appropriate behavioral response. All of these need time, and many studies report that the time needed to compare two stimuli correlates inversely with the perceived distance between them. We developed a behavioral assay in which we tested the time that a honeybee needs to discriminate between odors consisting of mixtures of two components, and included both very similar and very different stimuli spanning four log-concentration ranges. Bees learned to discriminate all odors, including very similar odors and the same odor at different concentrations. Even though discriminating two very similar odors appears to be a more difficult task than discriminating two very distinct substances, we found that the time needed to make a choice for or against an odor was independent of odor similarity. Our data suggest that, irrespective of the nature of the olfactory code, the bee olfactory system evaluates odor quality after a constant interval. This may ensure that odors are only assessed after the olfactory network has optimized its representation.     

Excitatory local interneurons enhance tuning of sensory information

Neurons in the insect antennal lobe represent odors as spatiotemporal patterns of activity that unfold over multiple time scales. As these patterns unspool they decrease the overlap between odor representations and thereby increase the ability of the olfactory system to discriminate odors. Using a realistic model of the insect antennal lobe we examined two competing components of this process -lateral excitation from local excitatory interneurons, and slow inhibition from local inhibitory interneurons. We found that lateral excitation amplified differences between representations of similar odors by recruiting projection neurons that did not receive direct input from olfactory receptors. However, this increased sensitivity also amplified noisy variations in input and compromised the ability of the system to respond reliably to multiple presentations of the same odor. Slow inhibition curtailed the spread of projection neuron activity and increased response reliability. These competing influences must be finely balanced in order to decorrelate odor representations.     

条件联想神经网络研究

在人脑的某些功能和神经系统中的突前抑制机制启发下,本文提出一个新型的神经网络模型——条件联想神经网络.模型是一个有突触前抑制的联想记忆神经网络.通过初步分析和计算机模拟,证明本模型具有一般联想记忆模型所未有的一些新的特性,如可以在不同条件下,对同一输入有不同的反应.对同一输入,在不同的条件下,又可以有相同的反应.这些特点将有助于人们对神经系统中信息处理过程的了解.此外,文中也指出可能实现本模型的神经结构.     

Cortical contributions to olfaction: plasticity and perception

In most sensory systems, the sensory cortex is the place where sensation approaches perception. As described in this review, olfaction is no different. The olfactory system includes both primary and higher order cortical regions. These cortical structures perform computations that take highly analytical afferent input and synthesize it into configural odor objects. Cortical plasticity plays an important role in this synthesis and may underlie olfactory perceptual learning. Olfactory cortex is also involved in odor memory and association of odors with multimodal input and contexts. Finally, the olfactory cortex serves as an important sensory gate, modulating information throughput based on recent experience and behavioral state.     

Innate attractiveness and associative learnability of odors can be dissociated in larval Drosophila

We investigate olfactory associative learning in larval Drosophila. A reciprocal training design is used, such that one group of animals receives a reward in the presence of odor X but not in the presence of odor Y (Train: X+ // Y), whereas another group is trained reciprocally (Train: X // Y+). After training, differences in odor preference between these reciprocally trained groups in a choice test (Test: X - Y) reflect associative learning. The current study, after showing which odor pairs can be used for such learning experiments, 1) introduces a one-odor version of such reciprocal paradigm that allows estimating the learnability of single odors. Regarding this reciprocal one-odor paradigm, we show that 2) paired presentations of an odor with a reward increase odor preference above baseline, whereas unpaired presentations of odor and reward decrease odor preference below baseline; this suggests that odors can become predictive either of reward or of reward absence. Furthermore, we show that 3) innate attractiveness and associative learnability can be dissociated. These data deepen our understanding of odor-reward learning in larval Drosophila on the behavioral level, and thus foster its neurogenetic analysis.     

A neural mechanism of hierarchical discrimination of odors in the olfactory cortex based on spatiotemporal encoding of odor information

We propose a neural mechanism for discrimination of different complex odors in the olfactory cortex based on the dynamical encoding scheme. Both constituent molecules of the odor and their mixing ratios are encoded simultaneously into a spatiotemporal activity pattern (limit cycle attractor) in the olfactory bulb [Hoshino O, Kashimori Y, Kambara T (1998) Biol Cybern 79:109–120]. We present a functional model of the olfactory cortex consisting of some dynamical mapping modules. Each dynamical map is represented by itinerancy among the limit cycle attractors. When a temporal sequence of spatial activity patterns corresponding to a complex odor is injected from the bulb to the network of the olfactory cortex, the neural activity state of each mapping module is fixed to a relevant spatial pattern injected. Recognition of an odor is accomplished by a combination of firing patterns fixed in all the mapping modules. The stronger the response strength of the component, the earlier the component is recognized. The hierarchical discrimination of an odor is made by recognizing the components in order of decreasing response strengths. Received: 28 November 1998 / Accepted in revised form: 17 December 1999     

Parallel odor processing by two anatomically distinct olfactory bulb target structures

The olfactory cortex encompasses several anatomically distinct regions each hypothesized to provide differential representation and processing of specific odors. Studies exploring whether or not the diversity of olfactory bulb input to olfactory cortices has functional meaning, however, are lacking. Here we tested whether two anatomically major olfactory cortical structures, the olfactory tubercle (OT) and piriform cortex (PCX), differ in their neural representation and processing dynamics of a small set of diverse odors by performing in vivo extracellular recordings from the OT and PCX of anesthetized mice. We found a wealth of similarities between structures, including odor-evoked response magnitudes, breadth of odor tuning, and odor-evoked firing latencies. In contrast, only few differences between structures were found, including spontaneous activity rates and odor signal-to-noise ratios. These results suggest that despite major anatomical differences in innervation by olfactory bulb mitral/tufted cells, the basic features of odor representation and processing, at least within this limited odor set, are similar within the OT and PCX. We predict that the olfactory code follows a distributed processing stream in transmitting behaviorally and perceptually-relevant information from low-level stations.     

Sparse Distributed Representation of Odors in a Large-scale Olfactory Bulb Circuit

In the olfactory bulb, lateral inhibition mediated by granule cells has been suggested to modulate the timing of mitral cell firing, thereby shaping the representation of input odorants. Current experimental techniques, however, do not enable a clear study of how the mitral-granule cell network sculpts odor inputs to represent odor information spatially and temporally. To address this critical step in the neural basis of odor recognition, we built a biophysical network model of mitral and granule cells, corresponding to 1/100th of the real system in the rat, and used direct experimental imaging data of glomeruli activated by various odors. The model allows the systematic investigation and generation of testable hypotheses of the functional mechanisms underlying odor representation in the olfactory bulb circuit. Specifically, we demonstrate that lateral inhibition emerges within the olfactory bulb network through recurrent dendrodendritic synapses when constrained by a range of balanced excitatory and inhibitory conductances. We find that the spatio-temporal dynamics of lateral inhibition plays a critical role in building the glomerular-related cell clusters observed in experiments, through the modulation of synaptic weights during odor training. Lateral inhibition also mediates the development of sparse and synchronized spiking patterns of mitral cells related to odor inputs within the network, with the frequency of these synchronized spiking patterns also modulated by the sniff cycle.     

Testing for Odor Discrimination and Habituation in Mice

This video demonstrates a technique to establish the presence of a normally functioning olfactory system in a mouse. The test helps determine whether the mouse can discriminate between non-social odors and social odors, whether the mouse habituates to a repeatedly presented odor, and whether the mouse demonstrates dishabituation when presented with a novel odor. Since many social behavior tests measure the experimental animal’s response to a familiar or novel mouse, false positives can be avoided by establishing that the animals can detect and discriminate between social odors. There are similar considerations in learning tests such as fear conditioning that use odor to create a novel environment or olfactory cues as an associative stimulus. Deficits in the olfactory system would impair the ability to distinguish between contexts and to form an association with an olfactory cue during fear conditioning. In the odor habitation/dishabituation test, the mouse is repeatedly presented with several odors. Each odor is presented three times for two minutes. The investigator records the sniffing time directed towards the odor as the measurement of olfactory responsiveness. A typical mouse shows a decrease in response to the odor over repeated presentations (habituation). The experimenter then presents a novel odor that elicits increased sniffing towards the new odor (dishabituation). After repeated presentation of the novel odor the animal again shows habituation. This protocol involves the presentation of water, two or more non-social odors, and two social odors. In addition to reducing experimental confounds, this test can provide information on the function of the olfactory systems of new knockout, knock-in, and conditional knockout mouse lines.     

Simple networks for spike-timing-based computation,with application to olfactory processing

Spike synchronization across neurons can be selective for the situation where neurons are driven at similar firing rates, a "many are equal" computation. This can be achieved in the absence of synaptic interactions between neurons, through phase locking to a common underlying oscillatory potential. Based on this principle, we instantiate an algorithm for robust odor recognition into a model network of spiking neurons whose main features are taken from known properties of biological olfactory systems. Here, recognition of odors is signaled by spike synchronization of specific subsets of "mitral cells." This synchronization is highly odor selective and invariant to a wide range of odor concentrations. It is also robust to the presence of strong distractor odors, thus allowing odor segmentation within complex olfactory scenes. Information about odors is encoded in both the identity of glomeruli activated above threshold (1 bit of information per glomerulus) and in the analog degree of activation of the glomeruli (approximately 3 bits per glomerulus).     

Slow breathing and emotions associated with odor-induced autobiographical memories

An important feature of olfactory perception is its dependence on respiratory activity. By inspiration, olfactory information ascends directly to olfactory-related limbic structures. Therefore, every breath with odor molecules activates these limbic areas associated with emotional experience and memory retrieval. We tested whether odors associated with autobiographical memories can trigger pleasant emotional experiences and whether respiration changes during stimulation with these odors. During presentation of odors related to autobiographical memories and control odors, we measured minute ventilation, tidal volume, respiratory frequency, O2 consumption, and end tidal CO2 concentration. Findings showed that autobiographical memory retrieval was associated with increasing tidal volume and decreasing respiratory frequency more than during presentation of control odors. Subjective feelings such as emotional arousal during retrieval of the memory, arousal level of the memory itself, or pleasantness and familiarity toward the odor evoked by autobiographical memory were more specific emotional responses compared with those related to control odors. In addition, high trait anxiety subjects responded with a stronger feeling of being taken back in time and had high arousal levels with tidal volume increases. We discussed assumptions regarding how deep and slow breathing is related to pleasantness and comfortableness of an autobiographical memory.     

Modeling the olfactory bulb and its neural oscillatory processings

The olfactory bulb of mammals aids in the discrimination of odors. A mathematical model based on the bulbar anatomy and electrophysiology is described. Simulations of the highly non-linear model produce a 35–60 Hz modulated activity which is coherent across the bulb. The decision states (for the odor information) in this system can be thought of as stable cycles, rather than point stable states typical of simpler neuro-computing models. Analysis shows that a group of coupled non-linear oscillators are responsible for the oscillatory activities. The output oscillation pattern of the bulb is determined by the odor input. The model provides a framework in which to understand the transform between odor input and the bulbar output to olfactory cortex. There is significant correspondence between the model behavior and observed electrophysiology.     

Synaptic learning rules and sparse coding in a model sensory system

Neural circuits exploit numerous strategies for encoding information. Although the functional significance of individual coding mechanisms has been investigated, ways in which multiple mechanisms interact and integrate are not well understood. The locust olfactory system, in which dense, transiently synchronized spike trains across ensembles of antenna lobe (AL) neurons are transformed into a sparse representation in the mushroom body (MB; a region associated with memory), provides a well-studied preparation for investigating the interaction of multiple coding mechanisms. Recordings made in vivo from the insect MB demonstrated highly specific responses to odors in Kenyon cells (KCs). Typically, only a few KCs from the recorded population of neurons responded reliably when a specific odor was presented. Different odors induced responses in different KCs. Here, we explored with a biologically plausible model the possibility that a form of plasticity may control and tune synaptic weights of inputs to the mushroom body to ensure the specificity of KCs' responses to familiar or meaningful odors. We found that plasticity at the synapses between the AL and the MB efficiently regulated the delicate tuning necessary to selectively filter the intense AL oscillatory output and condense it to a sparse representation in the MB. Activity-dependent plasticity drove the observed specificity, reliability, and expected persistence of odor representations, suggesting a role for plasticity in information processing and making a testable prediction about synaptic plasticity at AL-MB synapses.     

A model of stimulus-specific neural assemblies in the insect antennal lobe

It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.     

Odor recognition memory as a function of odor-naming performance

A series of experiments sought to clarify the relationship between odor naming and memory by manipulating odor label availability during a dual naming-memory task. Experiment 1 demonstrated that recognition memory and odor naming were both better when the naming task provided participants with odor label alternatives. Consistent and correct odor naming was associated with nearly perfect memory, whereas inconsistent or incorrect naming was associated with very weak memory if any at all. Experiment 2 showed that the availability of odor labels was effective at improving memory only if labels were available at both memory encoding and retrieval, suggesting that the labels were aiding memory by improving the identification of the odors. Odor naming was manipulated in Experiment 3 by varying the number of available labels from 4 to 16 during each odor-naming trial. As found in the previous experiments, naming and memory were strongly related in each of the labeling conditions. Experiment 4 showed that corrective naming feedback produced better memory performance but only when the feedback led to correct odor naming. It was concluded that perceptual processes related to matching olfactory input to acquired, multidimensional representations of odors play a critical role in both odor naming and episodic memory.     

The sniff as a unit of olfactory processing

Sniffing is a rhythmic motor process essential for the acquisition of olfactory information. Recent behavioral experiments show that using a single sniff rats can accurately discriminate between very similar odors and fail to improve their accuracy by taking multiple sniffs. This implies that each sniff has the potential to provide a complete snapshot of the local olfactory environment. The discrete and intermittent nature of sniffing has implications beyond the physical process of odor capture as it strongly shapes the flow of information into the olfactory system. We review electrophysiological studies-primarily from anesthetized rodents-demonstrating that olfactory neural responses are coupled to respiration. Hence, the "sniff cycle" might play a role in odor coding, by allowing the timing of spikes with respect to the phase of the respiration cycle to encode information about odor identity or concentration. We also discuss behavioral and physiological results indicating that sniffing can be dynamically coordinated with other rhythmic behaviors, such as whisking, as well as with rhythmic neural activity, such as hippocampal theta oscillations. Thus, the sniff cycle might also facilitate the coordination of the olfactory system with other brain areas. These converging lines of empirical data support the notion that each sniff is a unit of olfactory processing relevant for both neural coding and inter-areal coordination. Further electrophysiological recordings in behaving animals will be necessary to assess these proposals.