Insect olfactory memory in time and space

Recent studies using functional optical imaging have revealed that cellular memory traces form in different areas of the insect brain after olfactory classical conditioning. These traces are revealed as increased calcium signals or synaptic release from defined neurons, and include a short-lived trace that forms immediately after conditioning in antennal lobe projection neurons, an early trace in dopaminergic neurons, and a medium-term trace in dorsal paired medial neurons. New molecular genetic tools have revealed that for normal behavioral memory performance, synaptic transmission from the mushroom body neurons is required only during retrieval, whereas synaptic transmission from dopaminergic neurons is required at the time of acquisition and synaptic transmission from dorsal paired medial neurons is required during the consolidation period. Such experimental results are helping to identify the types of neurons that participate in olfactory learning and when their participation is required. Olfactory learning often occurs alongside crossmodal interactions of sensory information from other modalities. Recent studies have revealed complex interactions between the olfactory and the visual senses that can occur during olfactory learning, including the facilitation of learning about subthreshold olfactory stimuli due to training with concurrent visual stimuli.     

Neural coding for the retrieval of multiple memory patterns

We investigate the retrieval dynamics in a feature-based semantic memory model, in which the features are coded by neurons of the Hindmarsh-Rose type in the chaotic regime. We consider the retrieval process as consisting of the synchronized firing activity of the neurons coding for the same memory pattern. The retrieval dynamics is investigated for multiple patterns, with particular attention to the case of overlapping memories. In this case, we hypothesize a dynamical nontransitive mechanism based on synchronization, that allows for a shared feature to participate in multiple memory representations. The problem of the choice of a cognitive plausible time-scale for the retrieval analysis is investigated by analyzing the information that can be inferred from finite-time analyses. Different types of indicators are proposed in order to evaluate the temporal dynamics of the neurons engaged in the retrieval process. We interpret the simulation results as suggestive of a role for chaotic dynamics in allowing for flexible composition of elementary meaningful units in memory representations.     

Extinction antagonizes olfactory memory at the subcellular level

Memory loss occurs by diverse mechanisms, as different time constants of performance decrement and sensitivities to experimental manipulations suggest. While the phenomena of memory decay, interference, and extinction are well established behaviorally, little is known about them at the circuit or molecular level. In Drosophila, odorant memories lasting up to 3 hr can be localized to mushroom body Kenyon cells, a single neuronal level in the olfactory pathway. The plasticity underlying this memory trace can be induced without Kenyon cell synaptic output. Experimental extinction, i.e., presentation of the conditioned stimulus without the reinforcer, reduces memory performance and does so at the same circuit level as memory formation. Thus, unreinforced presentation of learned odorants antagonizes intracellularly the signaling cascade underlying memory formation.     

Canopy photosynthesis modulates soil respiration in a temperate semi-arid shrubland at multiple timescales

Plant and Soil - Plant growth-promoting bacteria of the genus Bacillus are known to solubilize phosphates and enhance plant growth in many plant species. We explored the effects of the inoculation...     

Spike-based population coding and working memory

Compelling behavioral evidence suggests that humans can make optimal decisions despite the uncertainty inherent in perceptual or motor tasks. A key question in neuroscience is how populations of spiking neurons can implement such probabilistic computations. In this article, we develop a comprehensive framework for optimal, spike-based sensory integration and working memory in a dynamic environment. We propose that probability distributions are inferred spike-per-spike in recurrently connected networks of integrate-and-fire neurons. As a result, these networks can combine sensory cues optimally, track the state of a time-varying stimulus and memorize accumulated evidence over periods much longer than the time constant of single neurons. Importantly, we propose that population responses and persistent working memory states represent entire probability distributions and not only single stimulus values. These memories are reflected by sustained, asynchronous patterns of activity which make relevant information available to downstream neurons within their short time window of integration. Model neurons act as predictive encoders, only firing spikes which account for new information that has not yet been signaled. Thus, spike times signal deterministically a prediction error, contrary to rate codes in which spike times are considered to be random samples of an underlying firing rate. As a consequence of this coding scheme, a multitude of spike patterns can reliably encode the same information. This results in weakly correlated, Poisson-like spike trains that are sensitive to initial conditions but robust to even high levels of external neural noise. This spike train variability reproduces the one observed in cortical sensory spike trains, but cannot be equated to noise. On the contrary, it is a consequence of optimal spike-based inference. In contrast, we show that rate-based models perform poorly when implemented with stochastically spiking neurons.     

Modeling peripheral olfactory coding in Drosophila larvae

The Drosophila larva possesses just 21 unique and identifiable pairs of olfactory sensory neurons (OSNs), enabling investigation of the contribution of individual OSN classes to the peripheral olfactory code. We combined electrophysiological and computational modeling to explore the nature of the peripheral olfactory code in situ. We recorded firing responses of 19/21 OSNs to a panel of 19 odors. This was achieved by creating larvae expressing just one functioning class of odorant receptor, and hence OSN. Odor response profiles of each OSN class were highly specific and unique. However many OSN-odor pairs yielded variable responses, some of which were statistically indistinguishable from background activity. We used these electrophysiological data, incorporating both responses and spontaneous firing activity, to develop a bayesian decoding model of olfactory processing. The model was able to accurately predict odor identity from raw OSN responses; prediction accuracy ranged from 12%-77% (mean for all odors 45.2%) but was always significantly above chance (5.6%). However, there was no correlation between prediction accuracy for a given odor and the strength of responses of wild-type larvae to the same odor in a behavioral assay. We also used the model to predict the ability of the code to discriminate between pairs of odors. Some of these predictions were supported in a behavioral discrimination (masking) assay but others were not. We conclude that our model of the peripheral code represents basic features of odor detection and discrimination, yielding insights into the information available to higher processing structures in the brain.     

Interhemispheric olfactory circuit and the memory beyond

In mammals, olfactory sensory neurons project their axons exclusively to the ipsilateral olfactory bulb. It remains unclear how odor information interacts between the two hemispheres of the brain. In this issue of Neuron, Yan et al. describe the precise interbulbar connection through the anterior olfactory nucleus pars externa (AONpE), which links contralateral isotypic olfactory columns.     

Strong single-fiber sensory inputs to olfactory cortex: implications for olfactory coding

Olfactory information is first encoded in a combinatorial fashion by olfactory bulb glomeruli, which individually represent distinct chemical features of odors. This information is then transmitted to piriform (olfactory) cortex, via axons of olfactory bulb mitral and tufted (M/T) cells, where it is presumed to form the odor percept. However, mechanisms governing the integration of sensory information in mammalian olfactory cortex are unclear. Here we show that single M/T cells can make powerful connections with cortical pyramidal cells, and coincident input from few M/T cells is sufficient to elicit spike output. These findings suggest that odor coding is broad and distributed in olfactory cortex.     

Behavioral analysis of olfactory coding and computation in rodents

Behavioral analysis is essential to understand how the olfactory system transforms chemosensory signals into information that can be used to guide actions. Recent studies in rodents have begun to address the behavioral relevance of putative olfactory codes and computations including spatial maps, oscillatory synchrony, and evolving temporal codes. To date, these studies have failed to find support for a role of any of these mechanisms in odor discrimination. Progress calls for experiments using precise psychophysical methods in conjunction with neural recording or perturbation, in addition to ethologically minded exploration of more complex forms of odor-guided behavior.     

Significance of glomerular compartmentalization for olfactory coding.

This paper deals with the dendritic signal processing by mitral cells in the olfactory bulb and its meaning for olfactory coding. The output signals of olfactory receptor neurones are sent to the olfactory bulb where they converge onto the secondary neurones, the mitral cells. On a short time scale, the connectivity between receptor and mitral cells can be assumed to be constant, whereas on a longer time scale, when considering the ongoing de- and regeneration, it is necessary to model the synaptical weights between receptor and mitral cells as variables. In a first approach we used Hebb's rule to this end and presumed that a mitral cell can be represented by one compartment only. In this case, and with a sequence of realistically modeled receptor activity signals, the synaptical weights of all mitral cells converged to the same point though every mitral cell had initial weights different from those of any other mitral cell. This means that a mitral cell, when modeled as one compartment, does not become sensitive to any particular odor quality. A similar lack of quality tuning turned out to occur when one-compartment mitral cells were connected among each other by laterally inhibiting interneurones. We therefore took into account the glomerular fine structure of mitral cell dendrites, assuming electrotonically decoupled dendritic subbranches. This feature together with local inhibitory circuitry at the subbranches led to a fundamentally different type of synaptical convergence pattern. In this case, mitral cells developed differential sensitivities for different odors. Mitral cells have thus to be regarded as multicompartment cells, and local, non-Hebbian learning rules for their afferent synapses are necessary to achieve a reasonable map of odors upon mitral cell activities.     

Intensity versus identity coding in an olfactory system

We examined the encoding and decoding of odor identity and intensity by neurons in the antennal lobe and the mushroom body, first and second relays, respectively, of the locust olfactory system. Increased odor concentration led to changes in the firing patterns of individual antennal lobe projection neurons (PNs), similar to those caused by changes in odor identity, thus potentially confounding representations for identity and concentration. However, when these time-varying responses were examined across many PNs, concentration-specific patterns clustered by identity, resolving the apparent confound. This is because PN ensemble representations changed relatively continuously over a range of concentrations of each odorant. The PNs' targets in the mushroom body-Kenyon cells (KCs)-had sparse identity-specific responses with diverse degrees of concentration invariance. The tuning of KCs to identity and concentration and the patterning of their responses are consistent with piecewise decoding of their PN inputs over oscillation-cycle length epochs.     

Odor and molecular vibration: Neural coding of olfactory information

Starting from an established correlation between specific molecular vibration patterns and the olfactory responses of organisms, a method is described by which equivalently specific patterns of neural excitation may be identified electrophysiologically. A molecular mechanism for the interaction is proposed which also takes into account such related matters as olfactory thresholds, and the possibility of both “specialist” and “generalist” receptors.     

Ultraconserved elements anchor thousands of genetic markers spanning multiple evolutionary timescales

Although massively parallel sequencing has facilitated large-scale DNA sequencing, comparisons among distantly related species rely upon small portions of the genome that are easily aligned. Methods are needed to efficiently obtain comparable DNA fragments prior to massively parallel sequencing, particularly for biologists working with non-model organisms. We introduce a new class of molecular marker, anchored by ultraconserved genomic elements (UCEs), that universally enable target enrichment and sequencing of thousands of orthologous loci across species separated by hundreds of millions of years of evolution. Our analyses here focus on use of UCE markers in Amniota because UCEs and phylogenetic relationships are well-known in some amniotes. We perform an in silico experiment to demonstrate that sequence flanking 2030 UCEs contains information sufficient to enable unambiguous recovery of the established primate phylogeny. We extend this experiment by performing an in vitro enrichment of 2386 UCE-anchored loci from nine, non-model avian species. We then use alignments of 854 of these loci to unambiguously recover the established evolutionary relationships within and among three ancient bird lineages. Because many organismal lineages have UCEs, this type of genetic marker and the analytical framework we outline can be applied across the tree of life, potentially reshaping our understanding of phylogeny at many taxonomic levels.     

Primary motor cortex reports efferent control of vibrissa motion on multiple timescales

Exploratory whisking in rat is an example of self-generated movement on multiple timescales, from slow variations in the envelope of whisking to the rapid sequence of muscle contractions during?a single whisk cycle. We find that, as a population, spike trains of single units in primary vibrissa motor cortex report the absolute angle of vibrissa position. This representation persists after sensory nerve transection, indicating an efferent source. About two-thirds of the units are modulated by slow variations in the envelope of whisking, while relatively few units report rapid changes in position within the whisk cycle. The combined results from this study and past measurements, which show that primary sensory cortex codes the whisking envelope as?a motor copy signal, imply that signals present in both sensory and motor cortices are necessary to compute angular coordinates based on vibrissa touch.     

Prospective and retrospective memory coding in the hippocampus

The effect of memory on hippocampal neuronal activity was assessed as rats performed a spatial task that was impaired by fornix lesions. The influences of current location, recently entered places, and places about to be entered were compared. Three new findings emerged. (1) Current, retrospective, and prospective coding were common and recorded simultaneously in neural ensembles. (2) The origin of journeys influenced firing even when rats made detours, showing that recent memory could modulate neuronal activity more than spatial trajectory. (3) Diminished retrospective coding and, more markedly, reduced prospective coding in error trials suggested that the neuronal signal was important for task performance. The population of hippocampal neurons thus encoded information about the recent past, the present, and the imminent future, consistent with a neuronal mechanism for episodic memory.