Three classes of neurons form synapses in the anten-nal lobe of Drosophila, the insect counterpart of the vertebrate olfactory bulb: olfactory receptor neurons, projection neurons, and inhibitory local interneurons. We have targeted a genetically encoded optical re-porter of synaptic transmission to each of these classes of neurons and visualized population re-sponses to natural odors. The activation of an odor-specific ensemble of olfactory receptor neurons leads to the activation of a symmetric ensemble of projection neurons across the glomerular synaptic relay. Virtually all excited glomeruli receive inhibitory input from local interneurons. The extent, odor specificity, and partly interglomerular origin of this input suggest that inhibitory circuits assemble combinatorially during odor presentations. These circuits may serve as dynamic templates that extract higher order features from afferent activity patterns.

s underlying odor-specific slow temporal University of California, San Diego patterning. In a recent theoretical study, it was shown La Jolla, California 92093 that heteroclinic structures in the phase space of a dy- 5 Department of Biology namical system representing the antennal lobe network University of California, San Diego can underlie patterns of PN activity that resemble those La Jolla, California 92093 observed in vivo (Laurent et al., 2001). The specific mechanisms underlying these slow temporal structures, however, remain unknown. This issue is explored here. Summary The dynamical properties of a network consisting of interacting excitatory and inhibitory neurons depend, in Locust antennal lobe (AL) projection neurons (PNs) part at least, on the dynamics of synaptic transmission respond to olfactory stimuli with sequences of depo- between its elements. Previous pharmacological experi- larizing and hyp

We discuss the first few stages of olfactory processing in the framework of a compartmental neural network. Our model consists of inhibitory and excitatory formal neurons with dendrodendritic interactions. We explore the computational properties of this neural network, and point out its possible functional role in the olfactory bulb. We show that in a noisy background the network functions as an associative memory, in spite of the fact that the network operates in an oscillatory mode. 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 decomposed via a decorrelation mechanism that relies on the temporal independence of odor information originating from spatially distant sources. Secondly, as the recall process of one pattern consists of associative convergence to an oscillatory attractor, multiple inputs are identified by alternate dominance of memory patterns during dif...

Magnetic resonance imaging (MRI) has rapidly become an important tool in clinical medicine and biological research. Its functional variant (functional magnetic resonance imaging; fMRI) is currently the most widely used method for brain mapping and studying the neural basis of human cognition. While the method is widespread, there is insuf � cient knowledge of the physiological basis of the fMRI signal to interpret the data con � dently with respect to neural activity. This paper reviews the basic principles of MRI and fMRI, and subsequently discusses in some detail the relationship between the blood-oxygenlevel-dependent (BOLD) fMRI signal and the neural activity elicited during sensory stimulation. To examine this relationship, we conducted the � rst simultaneous intracortical recordings of neural signals and BOLD responses. Depending on the temporal characteristics of the stimulus, a moderate to strong correlation was found between the neural activity measured with microelectrodes and the BOLD signal averaged over a small area around the microelectrode tips. However, the BOLD signal had signi � cantly higher variability than the neural activity, indicating that human fMRI combined with traditional statistical methods underestimates the reliability of the neuronal activity. To understand the relative contribution of several types of neuronal signals to the haemodynamic response, we compared local � eld potentials (LFPs), single- and multi-unit activity (MUA) with high spatio-temporal fMRI responses recorded simultaneously in monkey visual cortex. At recording sites characterized by transient responses, only the LFP signal was signi � cantly correlated with the haemodynamic response. Furthermore, the LFPs had the largest magnitude signal and linear systems analysis showed that the LFPs were better than the MUAs at predicting the fMRI responses. These � ndings, together with an analysis of the neural signals, indicate that the BOLD signal primarily measures the input and processing of neuronal information within a region and not the output signal transmitted to other brain regions.

coding dimension emerges if the set of contributing neurons changes in time over the period of stimulation in a stimulus-specific manner. In olfactory systems, slow temporal patterns of excitation and inhibition have long been observed in the olfactory bulbs of amphibians

GABAergic inhibition via local interneurons may play a role in enhancing spike timing precision in principal cells, since it tends to eliminate the influence of initial conditions. However, both the number and the timing of inhibitory synaptic events may be variable across repeated trials. How does this variability affect the spike timing precision in principal neurons? In this paper, we derive an analytical expression for the spike output jitter as a function of the variability of the received inhibition. This study predicts that variable inhibition is especially tolerated as the number of inhibitory cells is large, which is consistent with experimental data from early olfactory systems (antennal lobe for insects, olfactory bulb for vertebrates). 1

The external plexiform layer is where the interactions between the mitral (excitatory) and granule (inhibitory) cells of the olfactory bulb (OB) take place. Two outstanding features of these interactions are that they are dendrodendritic, and that there seem to be none between excitatory cells. The latter are the ones that are usually accreditted with the role of forming Hebbian cell assemblies. Hence it would seem that this structure lacks the necessary ingredients for an associative memory system. In this paper we show that in spite of these two properties this system can serve as an associative memory. Our model incorporates the essential anatomical characteristics of the OB. The memories in our system, defined by Hebbian mitral assemblies, are activated via the interactions with the inhibitory granule cells. The nonlinearity is introduced in our model via a sigmoid function that describes neurotransmitter release in reciprocal dendrodendritic synapses. The capacity (maximal number ...

We discuss the problem of segmentation in pattern recognition. We adopt the model and the general approach in the landmark paper by Wang, Buhmann and von der Malsburg (Neural Computation, (1990), 2, 94--106), and expand their model in a number of ways. We review their solution to the segmentation problem in associative memory, which consists in feature binding being expressed by synchrony relations between oscillators or populations of neurons. We extend the model by introducing a law of synaptic change, which allows the network to learn by structuring itself in response to stimuli with relevant features. We discuss the problem of interference between pattern completion and the learning of new memories. We also propose a form of multiplexing of input information taking advantage of the time-structure of the neurons' response. It is based on the assessment of analog as well as of binary properties of the stimuli and provides for an enhancement of the network's processing capacity. The relevance of the results for biological systems is pointed out. # 2000 Elsevier Science Ltd. All rights reserved.

This paper presents a model of a network of integrate-and-fire neurons with time delay weights, capable of invariant spatio-temporal pattern recognition. Spatio-temporal patterns are formed by spikes according to the encoding principle that the phase shifts of the spikes encode the input stimulus intensity which corresponds to the concentration of constituent molecules of an odor. We applied the Hopfield's phase shift encoding principle at the output level for spatio-temporal pattern recognition: Firing of an output neuron indicates that corresponding odor is recognized and phase shift of its firing encodes the concentration of the recognized odor. The temporal structure of the model provides the base for the modeling of higher level tasks, where temporal correlation is involved, such as feature binding and segmentation, object recognition, etc.

A mushroom body extrinsic neuron, the Pe1 neuron, connects the peduncle of the mushroom body (MB) with two areas of the protocerebrum in the honeybee brain, the lateral protocerebral lobe (LPL) and the ring neuropil around the �-lobe. Each side of the bee brain contains only one Pe1 neuron. Using a combination of intracellular recording and neuroanatomical techniques we analyzed its properties of integrative processing of the different sensory modalities. The Pe1 neuron responds to visual, mechanosensory, and olfactory stimuli. The responses are broadly tuned, consisting of a sustained increase of spike frequency to the onset and offset of light flashes, to horizontal and vertical movements of extended objects, to mechanical stimuli applied to the antennae or mouth parts, and to all olfactory stimuli tested (29 chemicals). These multisensory properties are reflected in its dendritic organization. Serial reconstructions of intracellularly stained Pe1 neurons using confocal microscopy reveal that the Pe1 neuron arborizes throughout all layers of MB peduncle with finger-like, vertically oriented dendrites. The peduncle of the MB is formed by the axons of Kenyon cells, whose dendritic inputs are organized in modality-specific subcompartments of the calyx region. The peduncular arborization indicates that the Pe1 neuron receives input 3 Corresponding author. from Kenyon cells of all calycal subcompartments. Because the Pe1 neuron changes its odor responses transiently as a consequence of olfactory learning, we hypothesize that the multimodal response properties might have a role in memory consolidation and help to establish contextual references in the long-term trace.