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

International audienceOne 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

Specific Entrainment of Mitral Cells during Gamma Oscillation in the Rat Olfactory Bulb

Local field potential (LFP) oscillations are often accompanied by synchronization of activity within a widespread cerebral area. Thus, the LFP and neuronal coherence appear to be the result of a common mechanism that underlies neuronal assembly formation. We used the olfactory bulb as a model to investigate: (1) the extent to which unitary dynamics and LFP oscillations can be correlated and (2) the precision with which a model of the hypothesized underlying mechanisms can accurately explain the experimental data. For this purpose, we analyzed simultaneous recordings of mitral cell (MC) activity and LFPs in anesthetized and freely breathing rats in response to odorant stimulation. Spike trains were found to be phase-locked to the gamma oscillation at specific firing rates and to form odor-specific temporal patterns. The use of a conductance-based MC model driven by an approximately balanced excitatory-inhibitory input conductance and a relatively small inhibitory conductance that oscillated at the gamma frequency allowed us to provide one explanation of the experimental data via a mode-locking mechanism. This work sheds light on the way network and intrinsic MC properties participate in the locking of MCs to the gamma oscillation in a realistic physiological context and may result in a particular time-locked assembly. Finally, we discuss how a self-synchronization process with such entrainment properties can explain, under experimental conditions: (1) why the gamma bursts emerge transiently with a maximal amplitude position relative to the stimulus time course; (2) why the oscillations are prominent at a specific gamma frequency; and (3) why the oscillation amplitude depends on specific stimulus properties. We also discuss information processing and functional consequences derived from this mechanism

Respiratory cycle as time basis: an improved method for averaging olfactory neural events.

International audienceIn the mammalian olfactory system, neural activity appears largely modulated by respiration. Accurate analysis of respiratory synchronized activity is precluded by the variability of the respiratory frequency from trial to trial. Thus, the use of respiratory cycle as the time basis for measuring cell responses was developed about 20 years ago. Nevertheless, averaging oscillatory component of the activity remains a challenge due to their rhythmic features. In this paper, we present a new respiratory monitoring setup based on the measurement of micropressure changes induced by nasal airflow in front of the nostril. Improvements provided by this new monitoring setup allows automatic processing of respiratory signals in order to extract each respiratory period (expiration and inspiration). The time component of these periods, which can differ from trial to trial, is converted into a phase component defined as [-pi, 0] and [0, pi] for inspiration and expiration, respectively. As opposed to time representation, the phase representation is common to all trials. Thus, this phase representation of the respiratory cycle is used as a normalized time basis permitting to collect results in a standardized data format across different animals and providing new tools to average oscillatory components of the activity

Fast and slow rhythms interactions in olfactory information representation in bulbar network

Une particularité de la modalité sensorielle olfactive est la nature complexe du stimulus chimique à représenter. Les cellules sensorielles de la cavité nasale sont sensibles aux traits physico-chimiques des molécules et transmettent cette information vers le bulbe olfactif, premier relais central de cette modalité. L’organisation des voies de projection vers le bulbe entraîne une spatialisation de l’activité dans cette structure, ce qui constitue un mode de représentation de l’information mais qui n’est pas suffisant à lui seul. Le bulbe olfactif est également marqué par des phénomènes dynamiques prépondérants. Tout d’abord le rythme respiratoire, qui organise temporellement le niveau d’activation de l’appareil sensoriel, ensuite les oscillations des potentiels de champs locaux, et enfin les oscillations sous-liminaires des potentiels de membrane des cellules. Ces éléments dynamiques pourraient être le support de la formation d’assemblées de neurones, sous-populations de cellules synchronisées transitoirement et permettant la représentation de l’information suivant un principe spatio-temporel. Les travaux présentés dans cette thèse sont basés sur l’enregistrement conjoint des activités unitaires des cellules du bulbe, des oscillations des potentiels de champs locaux et de la respiration en réponse à des stimulations olfactives. Nous montrons les relations existant entre les différents phénomènes dynamiques et comment ils permettent d’organiser l’activité des cellules pour aboutir à la formation d’assemblées de neurones fonctionnelles. Nous mettons particulièrement en évidence le rôle central de la respiration dans le fonctionnement intégré du bulbe olfactif.A striking feature of the olfactory sensory system is its ability to deal with a complex multi-dimensional chemical stimuli. Receptor cells in the nasal cavity are sensitive to specific features of molecules and transmit this information to the olfactory bulb, first relay for olfaction in the central nervous system. Due to the organization of projection pathways to the bulb, afferent information activates the structure in a topographical fashion ; although this may constitute a coding strategy for olfactory information it has proven insufficient, and other strategies must be investigated. Dynamic phenomenons are a preponderant feature of the olfactory bulb. The respiratory rhythm imposes a sinusoidal level of activation to the system, oscillations in local field potentials and subthreshold oscillations in neurons membrane potentials may interact and lead to the transient synchronization of sub-populations of neurons. This particular mechanism, designated as neural assemblies, is in theory a good candidate for the representation of olfactory information. The work presented here is based on conjoint recordings, in anesthetized animals, of unitary activities, oscillations in the LFP and respiration, in response to olfactory stimulation. We show the relationships existing between the various dynamic phenomenons, and hypothesize on their functional roles. We propose that a same mechanism may form different neural assemblies each assuming a specific functional role. The respiratory rhythm acts as a gating system, organizing the formation of successive yet different neural assemblies

Interactions entre rythmes rapides et rythmes lents dans la représentation de l’information olfactive dans le réseau bulbaire

A striking feature of the olfactory sensory system is its ability to deal with a complex multi-dimensional chemical stimuli. Receptor cells in the nasal cavity are sensitive to specific features of molecules and transmit this information to the olfactory bulb, first relay for olfaction in the central nervous system. Due to the organization of projection pathways to the bulb, afferent information activates the structure in a topographical fashion ; although this may constitute a coding strategy for olfactory information it has proven insufficient, and other strategies must be investigated. Dynamic phenomenons are a preponderant feature of the olfactory bulb. The respiratory rhythm imposes a sinusoidal level of activation to the system, oscillations in local field potentials and subthreshold oscillations in neurons membrane potentials may interact and lead to the transient synchronization of sub-populations of neurons. This particular mechanism, designated as neural assemblies, is in theory a good candidate for the representation of olfactory information. The work presented here is based on conjoint recordings, in anesthetized animals, of unitary activities, oscillations in the LFP and respiration, in response to olfactory stimulation. We show the relationships existing between the various dynamic phenomenons, and hypothesize on their functional roles. We propose that a same mechanism may form different neural assemblies each assuming a specific functional role. The respiratory rhythm acts as a gating system, organizing the formation of successive yet different neural assemblies.Une particularité de la modalité sensorielle olfactive est la nature complexe du stimulus chimique à représenter. Les cellules sensorielles de la cavité nasale sont sensibles aux traits physico-chimiques des molécules et transmettent cette information vers le bulbe olfactif, premier relais central de cette modalité. L’organisation des voies de projection vers le bulbe entraîne une spatialisation de l’activité dans cette structure, ce qui constitue un mode de représentation de l’information mais qui n’est pas suffisant à lui seul. Le bulbe olfactif est également marqué par des phénomènes dynamiques prépondérants. Tout d’abord le rythme respiratoire, qui organise temporellement le niveau d’activation de l’appareil sensoriel, ensuite les oscillations des potentiels de champs locaux, et enfin les oscillations sous-liminaires des potentiels de membrane des cellules. Ces éléments dynamiques pourraient être le support de la formation d’assemblées de neurones, sous-populations de cellules synchronisées transitoirement et permettant la représentation de l’information suivant un principe spatio-temporel. Les travaux présentés dans cette thèse sont basés sur l’enregistrement conjoint des activités unitaires des cellules du bulbe, des oscillations des potentiels de champs locaux et de la respiration en réponse à des stimulations olfactives. Nous montrons les relations existant entre les différents phénomènes dynamiques et comment ils permettent d’organiser l’activité des cellules pour aboutir à la formation d’assemblées de neurones fonctionnelles. Nous mettons particulièrement en évidence le rôle central de la respiration dans le fonctionnement intégré du bulbe olfactif

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

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Types of phase-locking.

<p>A) Classification principles. Spike phases (x-axis) are represented by grey ticks along the successive gamma cycles (y-axis) of a LFP burst. If the spike train has a regular number of spike at each cycle (here, 1 spike at each cycle, see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000551#s4" target="_blank">Methods</a> for details), and if the phase jitter is small enough (<0.5) (left panel) in comparison to the mean phase (<i>black boxes</i>), it is classified as a phase-locked pattern (here, a 1∶1 pattern). Otherwise (right panel), the spike train is classified as residual. B) Six examples of phase-locked spike trains. Along the top of each plot is indicated the type of pattern (q∶p types–3∶1, 2∶1, 1∶1, 2∶3, 1∶2, 1∶3–where q∶p indicates p spikes during q cycles) and its phase jitter. Phase-locked patterns account for 31% of all spike trains that last during the time of at least three LFP gamma cycles. C) Distributions of experimentally found (<i>grey</i>) and randomly generated (<i>black contours</i>) phase-locked pattern types. The majority of the patterns were 1∶1 in both distributions. D) Distribution of relative distances (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000551#s4" target="_blank">Methods</a>) from spike train phases to the closest pattern for the experimentally found (<i>grey</i>) and randomly generated (<i>black contours</i>) spike trains. <i>Dashed line</i> is the strict distance limit (0.33) under which the spike train can be considered for phase locking. Note the good agreement between experimentally found and randomly generated distance distributions. E) Distribution of phase jitter for experimentally found (grey) and randomly generated (black contours) spike trains for the respective phase-locked pattern type. The <i>dashed line</i> is the limit (0.5) under which the spike train is considered phase locked. Note that the area of experimentally found distributions under the limit was often larger than those of the randomly generated distributions, especially for the 1∶1 patterns (* indicate significant global statistical differences between both distributions, Kolmogorov Smirnov test, p<0.05).</p

Oscillatory inhibition at 60 Hz controls MC model firing rate and phase jitter.

<p>Ai) The firing rate (y-axis) of the MC model is plotted (<i>red</i>) in spikes per cycle (SpC) for a 60 Hz oscillation as a function of the excitatory conductance g_E (x-axis), while the cell is submitted to a constant inhibitory conductance g_I = 20 S/m². The firing rate was measured for two inhibitory oscillatory conductances (g_Io): 10% (<i>blue</i>) and 30% (<i>green</i>). Plateaus appear around 0.5 SpC <i>(a)</i>, 1 SpC <i>(b)</i>, 1.5 SpC <i>(c)</i>, 2 SpC <i>(d)</i> and 3 SpC <i>(e)</i> (see arrows). Aii): Same as in Ai, but under noisy conditions. The main plateaus remained after the addition of noise. B) Examples of spike patterns along four oscillation cycles plotted using the same conventions as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000551#pcbi-1000551-g003" target="_blank">Fig. 3</a>. They correspond to different g_E positions along the curves drawn in Ai, i.e., without noise (see small capital letters for correspondence). C) Phase jitter map according to g_E (x-axis) and g_Io (y-axis). Like in A) g_I = 20 S/m². Ci) Without noise, null-jitter zones (<i>black zones</i>) correspond to tongues 2∶1, 1∶1, 2∶3, 1∶2, and 1∶3 (indicated on the map). Colored zones represent the regime of non-locked spike trains with jitter >0.05 (see colored bar). Tongue width increases with g_Io. Tongues start at g_Io = 0 when the unforced neuron firing rate is 1, 1.5, 2, and 3 SpC (see the firing rate-x-axis below, which corresponds to the unforced frequency at a given excitatory input). Cii) Noisy conditions. Noise tended to degrade the phase-locking, but the tongue structures persisted.</p

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

International audienceA 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