Samuel Garcia

Learning-dependent neurogenesis in the olfactory bulb determines long-term olfactory memory

Inhibitory interneurons of the olfactory bulb are subjected to permanent adult neurogenesis. Their number is modulated by learning, suggesting that they could play a role in plastic changes of the bulbar network associated with olfactory memory. Adult male C57BL/6 mice were trained in an associative olfactory task, and we analyzed long‐term retention of the task 5, 30, and 90 d post‐training. In parallel, we assessed the fate of these newborn cells, mapped their distribution in the olfactory bulb and measured their functional implication using the immediate early gene Zif268. In a second set of experiments, we pharmacologically modulated glutamatergic transmission and using the same behavioral task assessed the consequences on memory retention and neurogenesis. Finally, by local infusion of an antimitotic drug, we selectively blocked neurogenesis during acquisition of the task and looked at the effects on memory retention. First we demonstrated that retrieval of an associative olfactory task recruits the newborn neurons in odor‐specific areas of the olfactory bulb selected to survive during acquisition of the task and that it does this in a manner that depends on the strength of learning. We then demonstrated that acquisition is not dependent on neurogenesis if long‐term retention of the task is abolished by blocking neurogenesis. Adult‐born neurons are thus involved in changes in the neural representation of an odor; this underlies long‐term olfactory memory as the strength of learning is linked to the duration of this memory. Neurogenesis thus plays a crucial role in long‐term olfactory memory.—Sultan, S., Mandairon, N., Kermen, F., Garcia, S., Sacquet, J., Didier, A. Learning‐dependent neurogenesis in the olfactory bulb determines long‐term olfactory memory. FASEB J. 24, 2355–2363 (2010). www.fasebj.org

Modulation of Spontaneous and Odorant-Evoked Activity of Rat Olfactory Sensory Neurons by Two Anorectic Peptides, Insulin and Leptin

In mammals, the sense of smell is modulated by the status of satiety, which is mainly signaled by blood-circulating peptide hormones. However, the underlying mechanisms linking olfaction and food intake are poorly understood. Here we investigated the effects of two anorectic peptides, insulin and leptin, on the functional properties of olfactory sensory neurons (OSNs). Using patch-clamp recordings, we analyzed the spontaneous activity of rat OSNs in an in vitro intact epithelium preparation. Bath perfusion of insulin and leptin significantly increased the spontaneous firing frequency in 91.7% (n = 24) and 75.0% (n = 24) of the cells, respectively. When the activity was electrically evoked, both peptides shortened the latency to the first action potential by approximately 25% and decreased the interspike intervals by approximately 13%. While insulin and leptin enhanced the electrical excitability of OSNs in the absence of odorants, they surprisingly reduced the odorant-induced activity in the olfactory epithelium. Insulin and leptin decreased the peak amplitudes of isoamyl acetate-induced electroolfactogram (EOG) signals to 46 and 38%, respectively. When measured in individual cells by patch-clamp recordings, insulin and leptin decreased odorant-induced transduction currents and receptor potentials. Therefore by increasing the spontaneous activity but reducing the odorant-induced activity of OSNs, an elevated insulin and leptin level (such as after a meal) may result in a decreased global signal-to-noise ratio in the olfactory epithelium, which matches the smell ability to the satiety status.

OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework

Progress in experimental tools and design is allowing the acquisition of increasingly large datasets. Storage, manipulation and efficient analyses of such large amounts of data is now a primary issue. We present OpenElectrophy, an electrophysiological data- and analysis-sharing framework developed to fill this niche. It stores all experiment data and meta-data in a single central MySQL database, and provides a graphic user interface to visualize and explore the data, and a library of functions for user analysis scripting in Python. It implements multiple spike-sorting methods, and oscillation detection based on the ridge extraction methods due to Roux et al. (2007). OpenElectrophy is open source and is freely available for download at http://neuralensemble.org/trac/OpenElectrophy.

A wavelet-based method for local phase extraction from a multi-frequency oscillatory signal

One of the challenges in analyzing neuronal activity is to correlate discrete signal, such as action potentials with a signal having a continuous waveform such as oscillating local field potentials (LFPs). Studies in several systems have shown that some aspects of information coding involve characteristics that intertwine both signals. An action potential is a fast transitory phenomenon that occurs at high frequencies whereas a LFP is a low frequency phenomenon. The study of correlations between these signals requires a good estimation of both instantaneous phase and instantaneous frequency. To extract the instantaneous phase, common techniques rely on the Hilbert transform performed on a filtered signal, which discards temporal information. Therefore, time-frequency methods are best fitted for non-stationary signals, since they preserve both time and frequency information. We propose a new algorithmic procedure that uses wavelet transform and ridge extraction for signals that contain one or more oscillatory frequencies and whose oscillatory frequencies may shift as a function of time. This procedure provides estimates of phase, frequency and temporal features. It can be automated, produces manageable amounts of data and allows human supervision. Because of such advantages, this method is particularly suitable for analyzing synchronization between LFPs and unitary events.

The Way an Odor Is Experienced during Aversive Conditioning Determines the Extent of the Network Recruited during Retrieval: A Multisite Electrophysiological Study in Rats

Recent findings have revealed the importance of orthonasal and retronasal olfaction in food memory, especially in conditioned odor aversion (COA); however, little is known about the dynamics of the cerebral circuit involved in the recognition of an odor as a toxic food signal and whether the activated network depends on the way (orthonasal vs retronasal) the odor was first experienced. In this study, we mapped the modulations of odor-induced oscillatory activities through COA learning using multisite recordings of local field potentials in behaving rats. During conditioning, orthonasal odor alone or associated with ingested odor was paired with immediate illness. For all animals, COA retrieval was assessed by orthonasal smelling only. Both types of conditioning induced similarly strong COA. Results pointed out (1) a predictive correlation between the emergence of powerful beta (15–40 Hz) activity and the behavioral expression of COA and (2) a differential network distribution of this beta activity according to the way the animals were exposed to the odor during conditioning. Indeed, for both types of conditioning, the aversive behavior was predicted by the emergence of a strong beta oscillatory activity in response to the odor in the olfactory bulb, piriform cortex, orbitofrontal cortex, and basolateral amygdala. This network was selectively extended to the infralimbic and insular cortices when the odor was ingested during acquisition. These differential networks could participate in different food odor memory; these results are discussed in line with recent behavioral results that indicate that COA can be formed over long odor-illness delays only if the odor is ingested.

The RUB Cage: Respiration–Ultrasonic Vocalizations–Behavior Acquisition Setup for Assessing Emotional Memory in Rats

In animals, emotional memory is classically assessed through pavlovian fear conditioning in which a neutral novel stimulus (conditioned stimulus) is paired with an aversive unconditioned stimulus. After conditioning, the conditioned stimulus elicits a fear response characterized by a wide range of behavioral and physiological responses. Despite the existence of this large repertoire of responses, freezing behavior is often the sole parameter used for quantifying fear response, thus limiting emotional memory appraisal to this unique index. Interestingly, respiratory changes and ultrasonic vocalizations (USV) can occur during fear response, yet very few studies investigated the link between these different parameters and freezing. The aim of the present study was to design an experimental setup allowing the simultaneous recording of respiration, USV, and behavior (RUB cage), and the offline synchronization of the collected data for fine-grain second by second analysis. The setup consisted of a customized plethysmograph for respiration monitoring, equipped with a microphone capturing USV, and with four video cameras for behavior recording. In addition, the bottom of the plethysmograph was equipped with a shock-floor allowing foot-shock delivery, and the top received tubing for odor presentations. Using this experimental setup we first described the characteristics of respiration and USV in different behaviors and emotional states. Then we monitored these parameters during contextual fear conditioning and showed that they bring complementary information about the animals anxiety state and the strength of aversive memory. The present setup may be valuable in providing a clearer appraisal of the physiological and behavioral changes that occur during acquisition as well as retrieval of emotional memory.

Respiration-gated formation of gamma and beta neural assemblies in the mammalian olfactory bulb.

A growing body of data suggests that information coding can be achieved not only by varying neuronal firing rate, but also by varying spike timing relative to network oscillations. In the olfactory bulb (OB) of a freely breathing anaesthetized mammal, odorant stimulation induces prominent oscillatory local field potential (LFP) activity in the beta (10–35 Hz) and gamma (40–80 Hz) ranges, which alternate during a respiratory cycle. At the same time, mitral/tufted (M/T) cells display respiration‐modulated spiking patterns. Using simultaneous recordings of M/T unitary activities and LFP activity, we conducted an analysis of the temporal relationships between M/T cell spiking activity and both OB beta and gamma oscillations. We observed that M/T cells display a respiratory pattern that pre‐tunes instantaneous frequencies to a gamma or beta regime. Consequently, M/T cell spikes become phase‐locked to either gamma or beta LFP oscillations according to their frequency range and respiratory pattern. Our results suggest that slow respiratory dynamics pre‐tune M/T cells to a preferential fast rhythm (beta or gamma) such that a spike–LFP coupling might occur when units and oscillation frequencies are in a compatible range. This double‐coupling process might define two complementary beta‐ and gamma‐neuronal assemblies along the course of a respiratory cycle.

Neo: an object model for handling electrophysiology data in multiple formats

Neuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data would improve interoperability and facilitate data-sharing. To that end, we propose here a language-independent object model, named “Neo,” suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language. In addition to representing electrophysiology data in memory for the purposes of analysis and visualization, the Python implementation provides a set of input/output (IO) modules for reading/writing the data from/to a variety of commonly used file formats. Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB. Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation. For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualization. Software for neurophysiology data analysis and visualization built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in neurophysiology.

A Physiological Increase of Insulin in the Olfactory Bulb Decreases Detection of a Learned Aversive Odor and Abolishes Food Odor-Induced Sniffing Behavior in Rats

Insulin is involved in multiple regulatory mechanisms, including body weight and food intake, and plays a critical role in metabolic disorders such as obesity and diabetes. An increasing body of evidence indicates that insulin is also involved in the modulation of olfactory function. The olfactory bulb (OB) contains the highest level of insulin and insulin receptors (IRs) in the brain. However, a role for insulin in odor detection and sniffing behavior remains to be elucidated. Using a behavioral paradigm based on conditioned olfactory aversion (COA) to isoamyl-acetate odor, we demonstrated that an intracerebroventricular (ICV) injection of 14 mU insulin acutely decreased olfactory detection of fasted rats to the level observed in satiated animals. In addition, whereas fasted animals demonstrated an increase in respiratory frequency upon food odor detection, this effect was absent in fasted animals receiving a 14 mU insulin ICV injection as well as in satiated animals. In parallel, we showed that the OB and plasma insulin levels were increased in satiated rats compared to fasted rats, and that a 14 mU insulin ICV injection elevated the OB insulin level of fasted rats to that of satiated rats. We further quantified insulin receptors (IRs) distribution and showed that IRs are preferentially expressed in the caudal and lateral parts of the main OB, with the highest labeling found in the mitral cells, the main OB projection neurons. Together, these data suggest that insulin acts on the OB network to modulate olfactory processing and demonstrate that olfactory function is under the control of signals involved in energy homeostasis regulation and feeding behaviors.

Odor vapor pressure and quality modulate local field potential oscillatory patterns in the olfactory bulb of the anesthetized rat.

A central question in chemical senses is the way that odorant molecules are represented in the brain. To date, many studies, when taken together, suggest that structural features of the molecules are represented through a spatio‐temporal pattern of activation in the olfactory bulb (OB), in both glomerular and mitral cell layers. Mitral/tufted cells interact with a large population of inhibitory interneurons resulting in a temporal patterning of bulbar local field potential (LFP) activity. We investigated the possibility that molecular features could determine the temporal pattern of LFP oscillatory activity in the OB. For this purpose, we recorded the LFPs in the OB of urethane‐anesthetized, freely breathing rats in response to series of aliphatic odorants varying subtly in carbon‐chain length or functional group. In concordance with our previous reports, we found that odors evoked oscillatory activity in the LFP signal in both the beta and gamma frequency bands. Analysis of LFP oscillations revealed that, although molecular features have almost no influence on the intrinsic characteristics of LFP oscillations, they influence the temporal patterning of bulbar oscillations. Alcohol family odors rarely evoke gamma oscillations, whereas ester family odors rather induce oscillatory patterns showing beta/gamma alternation. Moreover, for molecules with the same functional group, the probability of gamma occurrence is correlated to the vapor pressure of the odor. The significance of the relation between odorant features and oscillatory regimes along with their functional relevance are discussed.