OpenElectrophy: An Electrophysiological Data- and Analysis-Sharing Framework

Project, toolkit, and database of neuroinformatics ecosystem: A summary of previous studies on "Frontiers in Neuroinformatics"

In the field of neuroscience, the core of the cohort study project consists of collection, analysis, and sharing of multi-modal data. Recent years have witnessed a host of efficient and high-quality toolkits published and employed to improve the quality of multi-modal data in the cohort study. In turn, gleaning answers to relevant questions from such a conglomeration of studies is a time-consuming task for cohort researchers. As part of our efforts to tackle this problem, we propose a hierarchical neuroscience knowledge base that consists of projects/organizations, multi-modal databases, and toolkits, so as to facilitate researchers' answer searching process. We first classified studies conducted for the topic "Frontiers in Neuroinformatics" according to the multi-modal data life cycle, and from these studies, information objects as projects/organizations, multi-modal databases, and toolkits have been extracted. Then, we map these information objects into our proposed knowledge base framework. A Python-based query tool has also been developed in tandem for quicker access to the knowledge base, (accessible at https://github.com/Romantic-Pumpkin/PDT_fninf). Finally, based on the constructed knowledge base, we discussed some key research issues and underlying trends in different stages of the multi-modal data life cycle.

Encoding Model for Continuous Motion-sensitive Neurons in the Intermediate and Deep Layers of the Pigeon Optic Tectum

The intermediate and deep layers of the optic tectum (OT) contain neurons that are sensitive to small continuously moving targets. The sensitivity of these neurons to continuously moving targets suggests directed energy accumulation in the dendrite field of these neurons. Considering that the activation of a single dendrite can induce somatic spikes in vitro, we suggest the mechanism underlying the sequential probability activation of soma. The simulation model of these neurons constructed in combination with the above assumptions qualitatively reproduces the response characteristics of neurons to multi-sized stimuli and continuous sensitivity stimuli observed in physiological experiments. We used the characteristics of continuous motion-sensitive neurons that prefer long-lasting motion and single dendrite activation to induce somatic spikes as the entry point to construct the neuron encoding model. This model will enhance our understanding of the information-processing mechanism of the OT area of bird neurons in perceiving weak targets, and has important theoretical and practical significance for the construction of new brain-like algorithms.

SCA7 Mouse Cerebellar Pathology Reveals Preferential Downregulation of Key Purkinje Cell-Identity Genes and Shared Disease Signature with SCA1 and SCA2

Spinocerebellar ataxia type 7 (SCA7) is an inherited neurodegenerative disease mainly characterized by motor incoordination because of progressive cerebellar degeneration. SCA7 is caused by polyglutamine expansion in ATXN7, a subunit of the transcriptional coactivator SAGA, which harbors histone modification activities. Polyglutamine expansions in specific proteins are also responsible for SCA1-SCA3, SCA6, and SCA17; however, the converging and diverging pathomechanisms remain poorly understood. Using a new SCA7 knock-in mouse, SCA7140Q/5Q, we analyzed gene expression in the cerebellum and assigned gene deregulation to specific cell types using published datasets. Gene deregulation affects all cerebellar cell types, although at variable degree, and correlates with alterations of SAGA-dependent epigenetic marks. Purkinje cells (PCs) are by far the most affected neurons and show reduced expression of 83 cell-type identity genes, including these critical for their spontaneous firing activity and synaptic functions. PC gene downregulation precedes morphologic alterations, pacemaker dysfunction, and motor incoordination. Strikingly, most PC genes downregulated in SCA7 have also decreased expression in SCA1 and SCA2 mice, revealing converging pathomechanisms and a common disease signature involving cGMP-PKG and phosphatidylinositol signaling pathways and LTD. Our study thus points out molecular targets for therapeutic development, which may prove beneficial for several SCAs. Furthermore, we show that SCA7140Q/5Q males and females exhibit the major disease features observed in patients, including cerebellar damage, cerebral atrophy, peripheral nerves pathology, and photoreceptor dystrophy, which account for progressive impairment of behavior, motor, and visual functions. SCA7140Q/5Q mice represent an accurate model for the investigation of different aspects of SCA7 pathogenesis.SIGNIFICANCE STATEMENT Spinocerebellar ataxia 7 (SCA7) is one of the several forms of inherited SCAs characterized by cerebellar degeneration because of polyglutamine expansion in specific proteins. The ATXN7 involved in SCA7 is a subunit of SAGA transcriptional coactivator complex. To understand the pathomechanisms of SCA7, we determined the cell type-specific gene deregulation in SCA7 mouse cerebellum. We found that the Purkinje cells are the most affected cerebellar cell type and show downregulation of a large subset of neuronal identity genes, critical for their spontaneous firing and synaptic functions. Strikingly, the same Purkinje cell genes are downregulated in mouse models of two other SCAs. Thus, our work reveals a disease signature shared among several SCAs and uncovers potential molecular targets for their treatment.

SpikeInterface, a unified framework for spike sorting

Much development has been directed toward improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this paper, we provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.

OPETH: Open Source Solution for Real-Time Peri-Event Time Histogram Based on Open Ephys

Single cell electrophysiology remains one of the most widely used approaches of systems neuroscience. Decisions made by the experimenter during electrophysiology recording largely determine recording quality, duration of the project and value of the collected data. Therefore, online feedback aiding these decisions can lower monetary and time investment, and substantially speed up projects as well as allow novel studies otherwise not possible due to prohibitively low throughput. Real-time feedback is especially important in studies that involve optogenetic cell type identification by enabling a systematic search for neurons of interest. However, such tools are scarce and limited to costly commercial systems with high degree of specialization, which hitherto prevented wide-ranging benefits for the community. To address this, we present an open-source tool that enables online feedback during electrophysiology experiments and provides a Python interface for the widely used Open Ephys open source data acquisition system. Specifically, our software allows flexible online visualization of spike alignment to external events, called the online peri-event time histogram (OPETH). These external events, conveyed by digital logic signals, may indicate photostimulation time stamps for in vivo optogenetic cell type identification or the times of behaviorally relevant events during in vivo behavioral neurophysiology experiments. Therefore, OPETH allows real-time identification of genetically defined neuron types or behaviorally responsive populations. By allowing "hunting" for neurons of interest, OPETH significantly reduces experiment time and thus increases the efficiency of experiments that combine in vivo electrophysiology with behavior or optogenetic tagging of neurons.

High beta rhythm amplitude in olfactory learning signs a well-consolidated and non-flexible behavioral state

Beta rhythm (15-30 Hz) is a major candidate underlying long-range communication in the brain. In olfactory tasks, beta activity is strongly modulated by learning but its condition of expression and the network(s) responsible for its generation are unclear. Here we analyzed the emergence of beta activity in local field potentials recorded from olfactory, sensorimotor and limbic structures of rats performing an olfactory task. Rats performed successively simple discrimination, rule transfer, memory recall tests and contingency reversal. Beta rhythm amplitude progressively increased over learning in most recorded areas. Beta amplitude reduced to baseline when new odors were introduced, but remained high during memory recall. Intra-session analysis showed that even expert rats required several trials to reach a good performance level, with beta rhythm amplitude increasing in parallel. Notably, at the beginning of the reversal task, beta amplitude remained high while performance was low and, in all tested animals, beta amplitude decreased before rats were able to learn the new contingencies. Connectivity analysis showed that beta activity was highly coherent between all structures where it was expressed. Overall, our results suggest that beta rhythm is expressed in a highly coherent network when context learning - including both odors and reward - is consolidated and signals behavioral inflexibility.

Differential Coding Strategies in Glutamatergic and GABAergic Neurons in the Medial Cerebellar Nucleus

The cerebellum drives motor coordination and sequencing of actions at the millisecond timescale through adaptive control of cerebellar nuclear output. Cerebellar nuclei integrate high-frequency information from both the cerebellar cortex and the two main excitatory inputs of the cerebellum: the mossy fibers and the climbing fiber collaterals. However, how nuclear cells process rate and timing of inputs carried by these inputs is still debated. Here, we investigate the influence of the cerebellar cortical output, the Purkinje cells, on identified cerebellar nuclei neurons in vivo in male mice. Using transgenic mice expressing Channelrhodopsin2 specifically in Purkinje cells and tetrode recordings in the medial nucleus, we identified two main groups of neurons based on the waveform of their action potentials. These two groups of neurons coincide with glutamatergic and GABAergic neurons identified by optotagging after Chrimson expression in VGLUT2-cre and GAD-cre mice, respectively. The glutamatergic-like neurons fire at high rate and respond to both rate and timing of Purkinje cell population inputs, whereas GABAergic-like neurons only respond to the mean population firing rate of Purkinje cells at high frequencies. Moreover, synchronous activation of Purkinje cells can entrain the glutamatergic-like, but not the GABAergic-like, cells over a wide range of frequencies. Our results suggest that the downstream effect of synchronous and rhythmic Purkinje cell discharges depends on the type of cerebellar nuclei neurons targeted.SIGNIFICANCE STATEMENT Motor coordination and skilled movements are driven by the permanent discharge of neurons from the cerebellar nuclei that communicate cerebellar computation to other brain areas. Here, we set out to study how specific subtypes of cerebellar nuclear neurons of the medial nucleus are controlled by Purkinje cells, the sole output of the cerebellar cortex. We could isolate different subtypes of nuclear cell that differentially encode Purkinje cell inhibition. Purkinje cell stimulation entrains glutamatergic projection cells at their firing frequency, whereas GABAergic neurons are only inhibited. These differential coding strategies may favor temporal precision of cerebellar excitatory outputs associated with specific features of movement control while setting the global level of cerebellar activity through inhibition via rate coding mechanisms.

Adaptive quantization of local field potentials for wireless implants in freely moving animals: an open-source neural recording device

OBJECTIVE

Modern neuroscience research requires electrophysiological recording of local field potentials (LFPs) in moving animals. Wireless transmission has the advantage of removing the wires between the animal and the recording equipment but is hampered by the large number of data to be sent at a relatively high rate.

APPROACH

To reduce transmission bandwidth, we propose an encoder/decoder scheme based on adaptive non-uniform quantization. Our algorithm uses the current transmitted codeword to adapt the quantization intervals to changing statistics in LFP signals. It is thus backward adaptive and does not require the sending of side information. The computational complexity is low and similar at the encoder and decoder sides. These features allow for real-time signal recovery and facilitate hardware implementation with low-cost commercial microcontrollers.

MAIN RESULTS

As proof-of-concept, we developed an open-source neural recording device called NeRD. The NeRD prototype digitally transmits eight channels encoded at 10 kHz with 2 bits per sample. It occupies a volume of 2  ×  2  ×  2 cm³ and weighs 8 g with a small battery allowing for 2 h 40 min of autonomy. The power dissipation is 59.4 mW for a communication range of 8 m and transmission losses below 0.1%. The small weight and low power consumption offer the possibility of mounting the entire device on the head of a rodent without resorting to a separate head-stage and battery backpack. The NeRD prototype is validated in recording LFPs in freely moving rats at 2 bits per sample while maintaining an acceptable signal-to-noise ratio (>30 dB) over a range of noisy channels.

SIGNIFICANCE

Adaptive quantization in neural implants allows for lower transmission bandwidths while retaining high signal fidelity and preserving fundamental frequencies in LFPs.

Comparing Open-Source Toolboxes for Processing and Analysis of Spike and Local Field Potentials Data

Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific research. Today there exist many open-source toolboxes for spike and LFP data analysis implementing various functionality. Here we aim to provide a practical guidance for neuroscientists in the choice of an open-source toolbox best satisfying their needs. We overview major open-source toolboxes for spike and LFP data analysis as well as toolboxes with tools for connectivity analysis, dimensionality reduction and generalized linear modeling. We focus on comparing toolboxes functionality, statistical and visualization tools, documentation and support quality. To give a better insight, we compare and illustrate functionality of the toolboxes on open-access dataset or simulated data and make corresponding MATLAB scripts publicly available.

Opto nongenetics inhibition of neuronal firing

Optogenetics is based on the selective expression of exogenous opsins by neurons allowing experimental control of their electrical activity using visible light. The interpretation of the results of optogenetic experiments is based on the assumption that light stimulation selectively acts on those neurons expressing the exogenous opsins without perturbing the activity of naive ones. Here, we report that light stimulation, of wavelengths and power in the range of those normally used in optogenetic experiments, consistently reduces the firing activity of naive Mitral Cells (MCs) and Tufted Neurons in the olfactory bulb as well as in Medium Spiny Neurons (MSNs) in the striatum. No such effect was observed for cerebellar Purkinje and hippocampal CA1 neurons. The effects on MC firing appear to be mainly due to a light-induced increase in tissue temperature, between 0.1 and 0.4°C, associated with the generation of a hyperpolarizing current and a modification of action potential (AP) shape. Therefore, light in the visible range can affect neuronal physiology in a cell-specific manner. Beside the implications for optogenetic studies, our results pave the way to investigating the use of visible light for therapeutic purposes in pathologies associated with neuronal hyperexcitability.

Modulation of olfactory-driven behavior by metabolic signals: role of the piriform cortex

Olfaction is one of the major sensory modalities that regulates food consumption and is in turn regulated by the feeding state. Given that the olfactory bulb has been shown to be a metabolic sensor, we explored whether the anterior piriform cortex (aPCtx)-a higher olfactory cortical processing area-had the same capacity. Using immunocytochemical approaches, we report the localization of Kv1.3 channel, glucose transporter type 4, and the insulin receptor in the lateral olfactory tract and Layers II and III of the aPCtx. In current-clamped superficial pyramidal (SP) cells, we report the presence of two populations of SP cells: glucose responsive and non-glucose responsive. Using varied glucose concentrations and a glycolysis inhibitor, we found that insulin modulation of the instantaneous and spike firing frequency are both glucose dependent and require glucose metabolism. Using a plethysmograph to record sniffing frequency, rats microinjected with insulin failed to discriminate ratiometric enantiomers; considered a difficult task. Microinjection of glucose prevented discrimination of odorants of different chain-lengths, whereas injection of margatoxin increased the rate of habituation to repeated odor stimulation and enhanced discrimination. These data suggest that metabolic signaling pathways that are present in the aPCtx are capable of neuronal modulation and changing complex olfactory behaviors in higher olfactory centers.

Short-Term Plasticity Combines with Excitation-Inhibition Balance to Expand Cerebellar Purkinje Cell Dynamic Range

The balance between excitation (E) and inhibition (I) in neuronal networks controls the firing rate of principal cells through simple network organization, such as feedforward inhibitory circuits. Here, we demonstrate in male mice, that at the granule cell (GrC)-molecular layer interneuron (MLI)-Purkinje cell (PC) pathway of the cerebellar cortex, E/I balance is dynamically controlled by short-term dynamics during bursts of stimuli, shaping cerebellar output. Using a combination of electrophysiological recordings, optogenetic stimulation, and modeling, we describe the wide range of bidirectional changes in PC discharge triggered by GrC bursts, from robust excitation to complete inhibition. At high frequency (200 Hz), increasing the number of pulses in a burst (from 3 to 7) can switch a net inhibition of PC to a net excitation. Measurements of EPSCs and IPSCs during bursts and modeling showed that this feature can be explained by the interplay between short-term dynamics of the GrC-MLI-PC pathway and E/I balance impinging on PC. Our findings demonstrate that PC firing rate is highly sensitive to the duration of GrC bursts, which may define a temporal-to-rate code transformation in the cerebellar cortex.SIGNIFICANCE STATEMENT Sensorimotor information processing in the cerebellar cortex leads to the occurrence of a sequence of synaptic excitation and inhibition in Purkinje cells. Granule cells convey direct excitatory inputs and indirect inhibitory inputs to the Purkinje cells, through molecular layer interneurons, forming a feedforward inhibitory pathway. Using electrophysiological recordings, optogenetic stimulation, and mathematical modeling, we found that presynaptic short-term dynamics affect the balance between synaptic excitation and inhibition on Purkinje cells during high-frequency bursts and can reverse the sign of granule cell influence on Purkinje cell discharge when burst duration increases. We conclude that short-term dynamics may play an important role in transforming the duration of sensory inputs arriving on cerebellar granule cells into cerebellar cortical output firing rate.

A Bit-Encoding Based New Data Structure for Time and Memory Efficient Handling of Spike Times in an Electrophysiological Setup

Recent neuroscientific and technical developments of brain machine interfaces have put increasing demands on neuroinformatic databases and data handling software, especially when managing data in real time from large numbers of neurons. Extrapolating these developments we here set out to construct a scalable software architecture that would enable near-future massive parallel recording, organization and analysis of neurophysiological data on a standard computer. To this end we combined, for the first time in the present context, bit-encoding of spike data with a specific communication format for real time transfer and storage of neuronal data, synchronized by a common time base across all unit sources. We demonstrate that our architecture can simultaneously handle data from more than one million neurons and provide, in real time (< 25 ms), feedback based on analysis of previously recorded data. In addition to managing recordings from very large numbers of neurons in real time, it also has the capacity to handle the extensive periods of recording time necessary in certain scientific and clinical applications. Furthermore, the bit-encoding proposed has the additional advantage of allowing an extremely fast analysis of spatiotemporal spike patterns in a large number of neurons. Thus, we conclude that this architecture is well suited to support current and near-future Brain Machine Interface requirements.

NeoAnalysis: a Python-based toolbox for quick electrophysiological data processing and analysis

Background

In a typical electrophysiological experiment, especially one that includes studying animal behavior, the data collected normally contain spikes, local field potentials, behavioral responses and other associated data. In order to obtain informative results, the data must be analyzed simultaneously with the experimental settings. However, most open-source toolboxes currently available for data analysis were developed to handle only a portion of the data and did not take into account the sorting of experimental conditions. Additionally, these toolboxes require that the input data be in a specific format, which can be inconvenient to users. Therefore, the development of a highly integrated toolbox that can process multiple types of data regardless of input data format and perform basic analysis for general electrophysiological experiments is incredibly useful.

Results

Here, we report the development of a Python based open-source toolbox, referred to as NeoAnalysis, to be used for quick electrophysiological data processing and analysis. The toolbox can import data from different data acquisition systems regardless of their formats and automatically combine different types of data into a single file with a standardized format. In cases where additional spike sorting is needed, NeoAnalysis provides a module to perform efficient offline sorting with a user-friendly interface. Then, NeoAnalysis can perform regular analog signal processing, spike train, and local field potentials analysis, behavioral response (e.g. saccade) detection and extraction, with several options available for data plotting and statistics. Particularly, it can automatically generate sorted results without requiring users to manually sort data beforehand. In addition, NeoAnalysis can organize all of the relevant data into an informative table on a trial-by-trial basis for data visualization. Finally, NeoAnalysis supports analysis at the population level.

Conclusions

With the multitude of general-purpose functions provided by NeoAnalysis, users can easily obtain publication-quality figures without writing complex codes. NeoAnalysis is a powerful and valuable toolbox for users doing electrophysiological experiments.

Electronic supplementary material

The online version of this article (10.1186/s12938-017-0419-7) contains supplementary material, which is available to authorized users.

Understanding pup affective state through ethologically significant ultrasonic vocalization frequency

Throughout life, rats emit ultrasonic vocalizations (USV) when confronted with an aversive situation. However, the conditions classically used to elicit USV vary greatly with the animal's age (isolation from the dam in infancy, versus nociceptive stimulation in adults). The present study is the first to characterize USV responses to the same aversive event throughout development. Specifically, infant, juvenile and adult rats were presented with mild foot-shocks and their USV frequency, duration, and relationship with respiration and behavior were compared. In juvenile and adult rats, a single class of USV is observed with an age-dependent main frequency and duration (30 kHz/400 ms in juveniles, 22 kHz/900 ms in adults). In contrast, infant rat USV were split into two classes with specific relationships with respiration and behavior: 40 kHz/300 ms and 66 kHz/21 ms. Next, we questioned if these infant USV were also emitted in a more naturalistic context by exposing pups to interactions with the mother treating them roughly. This treatment enhanced 40-kHz USV while leaving 66-kHz USV unchanged suggesting that the use of USV goes far beyond a signal studied in terms of amount of emission, and can inform us about some aspects of the infant's affective state.

In vivo beta and gamma subthreshold oscillations in rat mitral cells: origin and gating by respiratory dynamics

In mammals, olfactory bulb (OB) dynamics are paced by slow and fast oscillatory rhythms at multiple levels: local field potential, spike discharge, and/or membrane potential oscillations. Interactions between these levels have been well studied for the slow rhythm linked to animal respiration. However, less is known regarding rhythms in the fast beta (10-35 Hz) and gamma (35-100 Hz) frequency ranges, particularly at the membrane potential level. Using a combination of intracellular and extracellular recordings in the OB of freely breathing rats, we show that beta and gamma subthreshold oscillations (STOs) coexist intracellularly and are related to extracellular local field potential (LFP) oscillations in the same frequency range. However, they are differentially affected by changes in cell excitability and by odor stimulation. This leads us to suggest that beta and gamma STOs may rely on distinct mechanisms: gamma STOs would mainly depend on mitral cell intrinsic resonance, while beta STOs could be mainly driven by synaptic activity. In a second study, we find that STO occurrence and timing are constrained by the influence of the slow respiratory rhythm on mitral and tufted cells. First, respiratory-driven excitation seems to favor gamma STOs, while respiratory-driven inhibition favors beta STOs. Second, the respiratory rhythm is needed at the subthreshold level to lock gamma and beta STOs in similar phases as their LFP counterparts and to favor the correlation between STO frequency and spike discharge. Overall, this study helps us to understand how the interaction between slow and fast rhythms at all levels of OB dynamics shapes its functional output. NEW & NOTEWORTHY In the mammalian olfactory bulb of a freely breathing anesthetized rat, we show that both beta and gamma membrane potential fast oscillation ranges exist in the same mitral and tufted (M/T) cell. Importantly, our results suggest they have different origins and that their interaction with the slow subthreshold oscillation (respiratory rhythm) is a key mechanism to organize their dynamics, favoring their functional implication in olfactory bulb information processing.

PRANAS: A New Platform for Retinal Analysis and Simulation

The retina encodes visual scenes by trains of action potentials that are sent to the brain via the optic nerve. In this paper, we describe a new free access user-end software allowing to better understand this coding. It is called PRANAS (https://pranas.inria.fr), standing for Platform for Retinal ANalysis And Simulation. PRANAS targets neuroscientists and modelers by providing a unique set of retina-related tools. PRANAS integrates a retina simulator allowing large scale simulations while keeping a strong biological plausibility and a toolbox for the analysis of spike train population statistics. The statistical method (entropy maximization under constraints) takes into account both spatial and temporal correlations as constraints, allowing to analyze the effects of memory on statistics. PRANAS also integrates a tool computing and representing in 3D (time-space) receptive fields. All these tools are accessible through a friendly graphical user interface. The most CPU-costly of them have been implemented to run in parallel.

Experimental assessment of the safety and potential efficacy of high irradiance photostimulation of brain tissues

Optogenetics is widely used in fundamental neuroscience. Its potential clinical translation for brain neuromodulation requires a careful assessment of the safety and efficacy of repeated, sustained optical stimulation of large volumes of brain tissues. This study was performed in rats and not in non-human primates for ethical reasons. We studied the spatial distribution of light, potential damage, and non-physiological effects in vivo, in anesthetized rat brains, on large brain volumes, following repeated high irradiance photo-stimulation. We generated 2D irradiance and temperature increase surface maps based on recordings taken during optical stimulation using irradiance and temporal parameters representative of common optogenetics experiments. Irradiances of 100 to 600 mW/mm2 with 5 ms pulses at 20, 40, and 60 Hz were applied during 90 s. In vivo electrophysiological recordings and post-mortem histological analyses showed that high power light stimulation had no obvious phototoxic effects and did not trigger non-physiological functional activation. This study demonstrates the ability to illuminate cortical layers to a depth of several millimeters using pulsed red light without detrimental thermal damages.

Odor-Induced Neuronal Rhythms in the Olfactory Bulb Are Profoundly Modified in ob/ob Obese Mice

Leptin, the product of the Ob(Lep) gene, is a peptide hormone that plays a major role in maintaining the balance between food intake and energy expenditure. In the brain, leptin receptors are expressed by hypothalamic cells but also in the olfactory bulb, the first central structure coding for odors, suggesting a precise function of this hormone in odor-evoked activities. Although olfaction plays a key role in feeding behavior, the ability of the olfactory bulb to integrate the energy-related signal leptin is still missing. Therefore, we studied the fate of odor-induced activity in the olfactory bulb in the genetic context of leptin deficiency using the obese ob/ob mice. By means of an odor discrimination task with concomitant local field potential recordings, we showed that ob/ob mice perform better than wild-type (WT) mice in the early stage of the task. This behavioral gain of function was associated in parallel with profound changes in neuronal oscillations in the olfactory bulb. The distribution of the peaks in the gamma frequency range was shifted toward higher frequencies in ob/ob mice compared to WT mice before learning. More notably, beta oscillatory activity, which has been shown previously to be correlated with olfactory discrimination learning, was longer and stronger in expert ob/ob mice after learning. Since oscillations in the olfactory bulb emerge from mitral to granule cell interactions, our results suggest that cellular dynamics in the olfactory bulb are deeply modified in ob/ob mice in the context of olfactory learning.

Significance of sniffing pattern during the acquisition of an olfactory discrimination task

Active sampling of olfactory environment consists of sniffing in rodents. The importance of sniffing dynamics is well established at the neuronal and behavioral levels. Patterns of sniffing have been shown to be modulated by the physicochemical properties of odorants, particularly concentration and sorption. Sniffing is also heavily impacted by higher processing related to the behavioral context, emotion and attentional demand. However, how the pattern of sniffing evolves over the course of learning of an experimental olfactory conditioning is still poorly understood. We tested this question by monitoring sniffing activity, using a whole-body plethysmograph, on rats performing a two-alternative choice odor discrimination task. We followed sniff variations at different learning stages (naïve, well-trained, expert). We found that during the acquisition of an odor discrimination task, rats acquired a global sniffing pattern, independent of the odor pair used. This pattern consists of a longer sampling duration, a higher sniffing frequency, and a larger amplitude. In parallel, subtle differences of sniffing between the two odors of a pair were also observed. This sniffing behavior was not only associated with a better and faster acquisition of the discrimination task but was also transferred to other odor sets and refined after a long-term pause so as to reduce the sampling duration and maintain a specific sniffing frequency. Our results provide additional arguments that sniffing is a complex sensorimotor act that is strongly affected by olfactory learning.

Neurophysiological analytics for all! Free open-source software tools for documenting, analyzing, visualizing, and sharing using electronic notebooks

Neurophysiology requires an extensive workflow of information analysis routines, which often includes incompatible proprietary software, introducing limitations based on financial costs, transfer of data between platforms, and the ability to share. An ecosystem of free open-source software exists to fill these gaps, including thousands of analysis and plotting packages written in Python and R, which can be implemented in a sharable and reproducible format, such as the Jupyter electronic notebook. This tool chain can largely replace current routines by importing data, producing analyses, and generating publication-quality graphics. An electronic notebook like Jupyter allows these analyses, along with documentation of procedures, to display locally or remotely in an internet browser, which can be saved as an HTML, PDF, or other file format for sharing with team members and the scientific community. The present report illustrates these methods using data from electrophysiological recordings of the musk shrew vagus-a model system to investigate gut-brain communication, for example, in cancer chemotherapy-induced emesis. We show methods for spike sorting (including statistical validation), spike train analysis, and analysis of compound action potentials in notebooks. Raw data and code are available from notebooks in data supplements or from an executable online version, which replicates all analyses without installing software-an implementation of reproducible research. This demonstrates the promise of combining disparate analyses into one platform, along with the ease of sharing this work. In an age of diverse, high-throughput computational workflows, this methodology can increase efficiency, transparency, and the collaborative potential of neurophysiological research.

Stereotyped spatial patterns of functional synaptic connectivity in the cerebellar cortex

Motor coordination is supported by an array of highly organized heterogeneous modules in the cerebellum. How incoming sensorimotor information is channeled and communicated between these anatomical modules is still poorly understood. In this study, we used transgenic mice expressing GFP in specific subsets of Purkinje cells that allowed us to target a given set of cerebellar modules. Combining in vitro recordings and photostimulation, we identified stereotyped patterns of functional synaptic organization between the granule cell layer and its main targets, the Purkinje cells, Golgi cells and molecular layer interneurons. Each type of connection displayed position-specific patterns of granule cell synaptic inputs that do not strictly match with anatomical boundaries but connect distant cortical modules. Although these patterns can be adjusted by activity-dependent processes, they were found to be consistent and predictable between animals. Our results highlight the operational rules underlying communication between modules in the cerebellar cortex.

Processing of motion stimuli by cells in the optic tectum of chickens

The ability to detect motion is crucial for the survival of animals. In the avian optic tectum, motion-sensitive output neurons in the stratum griseum centrale have large dendritic fields and receive direct retinal input at their distal dendrites (bottlebrush endings). It has been hypothesized that the activation of each ending elicits a burst in the neuron. Thus, an object moving across the receptive field would lead to a fixed number of bursts, independent of movement speed. However, experimental confirmation of this hypothesis is still missing. We measured the response of tectal neurons to moving stimuli in vivo and found that in 'fast-bursting' units (~500 Hz within burst), the number of bursts was independent of stimulus speed. These results indicate that the number of bursts might indeed be related to the sequential activation of the bottlebrush endings by visual stimuli.

Afterhyperpolarization (AHP) regulates the frequency and timing of action potentials in the mitral cells of the olfactory bulb: role of olfactory experience

Afterhyperpolarization (AHP) is a principal feedback mechanism in the control of the frequency and patterning of neuronal firing. In principal projection neurons of the olfactory bulb, the mitral cells (MCs), the AHP is produced by three separate components: classical potassium-mediated hyperpolarization, and the excitatory and inhibitory components, which are generated by the recurrent dendrodendritic synaptic transmission. Precise spike timing is involved in olfactory coding and learning, as well as in the appearance of population oscillatory activity. However, the contribution of the AHP and its components to these processes remains unknown. In this study, we demonstrate that the AHP is developed with the MC firing frequency and is dominated by the potassium component. We also show that recurrent synaptic transmission significantly modifies MC AHP and that the strength of the hyperpolarization produced by the AHP in the few milliseconds preceding the action potential (AP) emission determines MC firing frequency and AP timing. Moreover, we show that the AHP area is larger in younger animals, possibly owing to increased Ca²⁺ influx during MC firing. Finally, we show that olfactory experience selectively reduces the early component of the MC AHP (under 25 msec), thus producing a modification of the AP timing limited to the higher firing frequency. On the basis of these results, we propose that the AHP, and its susceptibility to be selectively modulated by the recurrent synaptic transmission and olfactory experience, participate in odor coding and learning by modifying the frequency and pattern of MC firing.

Excitation of tuberoinfundibular dopamine neurons by oxytocin: crosstalk in the control of lactation

Milk production in the nursing mother is induced by the hormone prolactin. Its release from the anterior pituitary is generally under tonic inhibition by neuroendocrine tuberoinfundibular dopamine (TIDA) neurons of the arcuate nucleus. Successful nursing, however, requires not only production but also ejection of breast milk. This function is supported by the hormone oxytocin. Here we explored the possibility that interaction between these functionally complementary hormones is mediated by TIDA neurons. First, whole-cell patch-clamp recordings were performed on prepubertal male rat hypothalamic slices, where TIDA neurons can be identified by a robust and rhythmic membrane potential oscillation. Oxytocin induced a switch of this rhythmic activity to tonic discharge through a depolarization involving direct actions on TIDA neurons. The depolarization is sensitive to blockade of the oxytocin receptor and is mediated by a voltage-dependent inward current. This inward current has two components: a canonical transient receptor potential-like conductance in the low-voltage range, and in the high-voltage range, a Ca(2+)-dependent component. Finally, whole-cell and loose-patch recordings were also performed on slices from virgin and lactating female rats to evaluate the relevance of these findings for nursing. In these preparations, oxytocin was found to excite TIDA neurons, identified by their expression of tyrosine hydroxylase. These findings suggest that oxytocin can modulate prolactin secretion by exciting TIDA neurons, and that this may serve as a feedforward inhibition of prolactin release.

Semantic framework for mapping object-oriented model to semantic web languages

The article deals with and discusses two main approaches in building semantic structures for electrophysiological metadata. It is the use of conventional data structures, repositories, and programming languages on one hand and the use of formal representations of ontologies, known from knowledge representation, such as description logics or semantic web languages on the other hand. Although knowledge engineering offers languages supporting richer semantic means of expression and technological advanced approaches, conventional data structures and repositories are still popular among developers, administrators and users because of their simplicity, overall intelligibility, and lower demands on technical equipment. The choice of conventional data resources and repositories, however, raises the question of how and where to add semantics that cannot be naturally expressed using them. As one of the possible solutions, this semantics can be added into the structures of the programming language that accesses and processes the underlying data. To support this idea we introduced a software prototype that enables its users to add semantically richer expressions into a Java object-oriented code. This approach does not burden users with additional demands on programming environment since reflective Java annotations were used as an entry for these expressions. Moreover, additional semantics need not to be written by the programmer directly to the code, but it can be collected from non-programmers using a graphic user interface. The mapping that allows the transformation of the semantically enriched Java code into the Semantic Web language OWL was proposed and implemented in a library named the Semantic Framework. This approach was validated by the integration of the Semantic Framework in the EEG/ERP Portal and by the subsequent registration of the EEG/ERP Portal in the Neuroscience Information Framework.

AnyWave: a cross-platform and modular software for visualizing and processing electrophysiological signals

BACKGROUND

The importance of digital signal processing in clinical neurophysiology is growing steadily, involving clinical researchers and methodologists. There is a need for crossing the gap between these communities by providing efficient delivery of newly designed algorithms to end users. We have developed such a tool which both visualizes and processes data and, additionally, acts as a software development platform.

NEW METHOD

AnyWave was designed to run on all common operating systems. It provides access to a variety of data formats and it employs high fidelity visualization techniques. It also allows using external tools as plug-ins, which can be developed in languages including C++, MATLAB and Python.

RESULTS

In the current version, plug-ins allow computation of connectivity graphs (non-linear correlation h2) and time-frequency representation (Morlet wavelets). The software is freely available under the LGPL3 license.

COMPARISON WITH EXISTING METHODS

AnyWave is designed as an open, highly extensible solution, with an architecture that permits rapid delivery of new techniques to end users.

CONCLUSIONS

We have developed AnyWave software as an efficient neurophysiological data visualizer able to integrate state of the art techniques. AnyWave offers an interface well suited to the needs of clinical research and an architecture designed for integrating new tools. We expect this software to strengthen the collaboration between clinical neurophysiologists and researchers in biomedical engineering and signal processing.

Neural correlates of task switching in prefrontal cortex and primary auditory cortex in a novel stimulus selection task for rodents

Animals can selectively respond to a target sound despite simultaneous distractors, just as humans can respond to one voice at a crowded cocktail party. To investigate the underlying neural mechanisms, we recorded single-unit activity in primary auditory cortex (A1) and medial prefrontal cortex (mPFC) of rats selectively responding to a target sound from a mixture. We found that prestimulus activity in mPFC encoded the selection rule-which sound from the mixture the rat should select. Moreover, electrically disrupting mPFC significantly impaired performance. Surprisingly, prestimulus activity in A1 also encoded selection rule, a cognitive variable typically considered the domain of prefrontal regions. Prestimulus changes correlated with stimulus-evoked changes, but stimulus tuning was not strongly affected. We suggest a model in which anticipatory activation of a specific network of neurons underlies the selection of a sound from a mixture, giving rise to robust and widespread rule encoding in both brain regions.

Two distinct olfactory bulb sublaminar networks involved in gamma and beta oscillation generation: a CSD study in the anesthetized rat

A prominent feature of olfactory bulb (OB) dynamics is the expression of characteristic local field potential (LFP) rhythms, including a slow respiration-related rhythm and two fast alternating oscillatory rhythms, beta (15-30 Hz) and gamma (40-90 Hz). All of these rhythms are implicated in olfactory coding. Fast oscillatory rhythms are known to involve the mitral-granule cell loop. Although the underlying mechanisms of gamma oscillation have been studied, the origin of beta oscillation remains poorly understood. Whether these two different rhythms share the same underlying mechanism is unknown. This study uses a quantitative and detailed current-source density (CSD) analysis combined with multi-unit activity (MUA) recordings to shed light on this question in freely breathing anesthetized rats. In particular, we show that gamma oscillation generation involves mainly the upper half of the external plexiform layer (EPL) and superficial areas of granule cell layer (GRL). In contrast, the generation of beta oscillation involves the lower part of the EPL and deep granule cells. This differential involvement of sublaminar networks is neither dependent on odor quality nor on the precise frequency of the fast oscillation under study. Overall, this study demonstrates a functional sublaminar organization of the rat OB, which is supported by previous anatomical findings.

Investigating local and long-range neuronal network dynamics by simultaneous optogenetics, reverse microdialysis and silicon probe recordings in vivo

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Optogenetics and microdialysis can be successfully combined.

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How to manipulate circuits of spontaneous and evoked activities with drugs and lights?

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Thalamic control of delta waves and sleep spindles.

Background

The advent of optogenetics has given neuroscientists the opportunity to excite or inhibit neuronal population activity with high temporal resolution and cellular selectivity. Thus, when combined with recordings of neuronal ensemble activity in freely moving animals optogenetics can provide an unprecedented snapshot of the contribution of neuronal assemblies to (patho)physiological conditions in vivo. Still, the combination of optogenetic and silicone probe (or tetrode) recordings does not allow investigation of the role played by voltage- and transmitter-gated channels of the opsin-transfected neurons and/or other adjacent neurons in controlling neuronal activity.

New method and results

We demonstrate that optogenetics and silicone probe recordings can be combined with intracerebral reverse microdialysis for the long-term delivery of neuroactive drugs around the optic fiber and silicone probe. In particular, we show the effect of antagonists of T-type Ca²⁺ channels, hyperpolarization-activated cyclic nucleotide-gated channels and metabotropic glutamate receptors on silicone probe-recorded activity of the local opsin-transfected neurons in the ventrobasal thalamus, and demonstrate the changes that the block of these thalamic channels/receptors brings about in the network dynamics of distant somatotopic cortical neuronal ensembles.

Comparison with existing methods

This is the first demonstration of successfully combining optogenetics and neuronal ensemble recordings with reverse microdialysis. This combination of techniques overcomes some of the disadvantages that are associated with the use of intracerebral injection of a drug-containing solution at the site of laser activation.

Conclusions

The combination of reverse microdialysis, silicone probe recordings and optogenetics can unravel the short and long-term effects of specific transmitter- and voltage-gated channels on laser-modulated firing at the site of optogenetic stimulation and the actions that these manipulations exert on distant neuronal populations.

Sniff adjustment in an odor discrimination task in the rat: analytical or synthetic strategy?

A growing body of evidence suggests that sniffing is not only the mode of delivery for odorant molecules but also contributes to olfactory perception. However, the precise role of sniffing variations remains unknown. The zonation hypothesis suggests that animals use sniffing variations to optimize the deposition of odorant molecules on the most receptive areas of the olfactory epithelium (OE). Sniffing would thus depend on the physicochemical properties of odorants, particularly their sorption. Rojas-Líbano and Kay (2012) tested this hypothesis and showed that rats used different sniff strategies when they had to target a high-sorption (HS) molecule or a low-sorption (LS) molecule in a binary mixture. Which sniffing strategy is used by rats when they are confronted to discrimination between two similarly sorbent odorants remains unanswered. Particularly, is sniffing adjusted independently for each odorant according to its sorption properties (analytical processing), or is sniffing adjusted based on the pairing context (synthetic processing)? We tested these hypotheses on rats performing a two-alternative choice discrimination of odorants with similar sorption properties. We recorded sniffing in a non-invasive manner using whole-body plethysmography during the behavioral task. We found that sniffing variations were not only a matter of odorant sorption properties and that the same odorant was sniffed differently depending on the odor pair in which it was presented. These results suggest that rather than being adjusted analytically, sniffing is instead adjusted synthetically and depends on the pair of odorants presented during the discrimination task. Our results show that sniffing is a specific sensorimotor act that depends on complex synthetic processes.

Insulin modulates network activity in olfactory bulb slices: impact on odour processing

Odour perception depends closely on nutritional status, in animals as in humans. Insulin, the principal anorectic hormone, appears to be one of the major candidates for ensuring the link between olfactory abilities and nutritional status, by modifying processing in the olfactory bulb (OB), one of its main central targets. The present study investigates whether and how insulin can act in OB, by evaluating its action on the main output neurons activities, mitral cells (MCs), in acute rat OB slices. Insulin was found to act at two OB network levels: (1) on MCs, by increasing their excitability, probably by inhibiting two voltage-gated potassium (K(+)) channels; (2) on interneurons by modifying the GABAergic and on glutamatergic synaptic activity impinging on MCs, mainly reducing them. Insulin also altered the olfactory nerve (ON)-evoked excitatory postsynaptic currents in 60% of MCs. Insulin decreased or increased the ON-evoked responses in equal proportion and the direction of its effect depended on the initial neuron ON-evoked firing rate. Indeed, insulin tended to decrease the high and to increase the low ON-evoked firing rates, thereby reducing inter-MC response firing variability. Therefore, the effects of insulin on the evoked firing rates were not carried out indiscriminately in the MC population. By constructing a mathematical model, the impact of insulin complex effects on OB was assessed at the population activity level. The model shows that the reduction of variability across cells could affect MC detection and discrimination abilities, mainly by decreasing and, less frequently, increasing them, depending on odour quality. Thus, as previously proposed, this differential action of insulin on MCs across odours would allow this hormone to put the olfactory function under feeding signal control, given the discerning valence of an odour as a function of nutritional status.

Stimfit: quantifying electrophysiological data with Python

Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals.

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.

ACQ4: an open-source software platform for data acquisition and analysis in neurophysiology research

The complexity of modern neurophysiology experiments requires specialized software to coordinate multiple acquisition devices and analyze the collected data. We have developed ACQ4, an open-source software platform for performing data acquisition and analysis in experimental neurophysiology. This software integrates the tasks of acquiring, managing, and analyzing experimental data. ACQ4 has been used primarily for standard patch-clamp electrophysiology, laser scanning photostimulation, multiphoton microscopy, intrinsic imaging, and calcium imaging. The system is highly modular, which facilitates the addition of new devices and functionality. The modules included with ACQ4 provide for rapid construction of acquisition protocols, live video display, and customizable analysis tools. Position-aware data collection allows automated construction of image mosaics and registration of images with 3-dimensional anatomical atlases. ACQ4 uses free and open-source tools including Python, NumPy/SciPy for numerical computation, PyQt for the user interface, and PyQtGraph for scientific graphics. Supported hardware includes cameras, patch clamp amplifiers, scanning mirrors, lasers, shutters, Pockels cells, motorized stages, and more. ACQ4 is available for download at http://www.acq4.org.

pySPACE-a signal processing and classification environment in Python

In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries.

Essential thalamic contribution to slow waves of natural sleep

Slow waves represent one of the prominent EEG signatures of non-rapid eye movement (non-REM) sleep and are thought to play an important role in the cellular and network plasticity that occurs during this behavioral state. These slow waves of natural sleep are currently considered to be exclusively generated by intrinsic and synaptic mechanisms within neocortical territories, although a role for the thalamus in this key physiological rhythm has been suggested but never demonstrated. Combining neuronal ensemble recordings, microdialysis, and optogenetics, here we show that the block of the thalamic output to the neocortex markedly (up to 50%) decreases the frequency of slow waves recorded during non-REM sleep in freely moving, naturally sleeping-waking rats. A smaller volume of thalamic inactivation than during sleep is required for observing similar effects on EEG slow waves recorded during anesthesia, a condition in which both bursts and single action potentials of thalamocortical neurons are almost exclusively dependent on T-type calcium channels. Thalamic inactivation more strongly reduces spindles than slow waves during both anesthesia and natural sleep. Moreover, selective excitation of thalamocortical neurons strongly entrains EEG slow waves in a narrow frequency band (0.75-1.5 Hz) only when thalamic T-type calcium channels are functionally active. These results demonstrate that the thalamus finely tunes the frequency of slow waves during non-REM sleep and anesthesia, and thus provide the first conclusive evidence that a dynamic interplay of the neocortical and thalamic oscillators of slow waves is required for the full expression of this key physiological EEG rhythm.

Anesthetic regimes modulate the temporal dynamics of local field potential in the mouse olfactory bulb

Anesthetized preparations have been widely used to study odor-induced temporal dynamics in the olfactory bulb. Although numerous recent data of single-cell recording or imaging in the olfactory bulb have employed ketamine cocktails, their effects on networks activities are still poorly understood, and odor-induced oscillations of the local field potential have not been characterized under these anesthetics. Our study aimed at describing the impact of two ketamine cocktails on oscillations and comparing them to awake condition. Anesthesia was induced by injection of a cocktail of ketamine, an antagonist of the N-methyl-d-aspartate receptors, combined with one agonist of α2-adrenergic receptors, xylazine (low affinity) or medetomidine (high affinity). Spontaneous and odor-induced activities were examined in anesthetized and awake conditions, in the same mice chronically implanted with an electrode in the main olfactory bulb. The overall dynamic pattern of oscillations under the two ketamine cocktails resembles that of the awake state. Ongoing activity is characterized by gamma bursts (>60 Hz) locked on respiration and beta (15-40 Hz) power increases during odor stimulation. However, anesthesia decreases local field potential power and leads to a strong frequency shift of gamma oscillations from 60-90 Hz to 100-130 Hz. We conclude that similarities between oscillations in anesthetized and awake states make cocktails of ketamine with one α2-agonist suitable for the recordings of local field potential to study processing in the early stages of the olfactory system.

Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis

Spyke Viewer is an open source application designed to help researchers analyze data from electrophysiological recordings or neural simulations. It provides a graphical data browser and supports finding and selecting relevant subsets of the data. Users can interact with the selected data using an integrated Python console or plugins. Spyke Viewer includes plugins for several common visualizations and allows users to easily extend the program by writing their own plugins. New plugins are automatically integrated with the graphical interface. Additional plugins can be downloaded and shared on a dedicated website.

It's time to fear! Interval timing in odor fear conditioning in rats

Time perception is crucial to goal attainment in humans and other animals, and interval timing also guides fundamental animal behaviors. Accumulating evidence has made it clear that in associative learning, temporal relations between events are encoded, and a few studies suggest this temporal learning occurs very rapidly. Most of these studies, however, have used methodologies that do not permit investigating the emergence of this temporal learning. In the present study we monitored respiration, ultrasonic vocalization (USV) and freezing behavior in rats in order to perform fine-grain analysis of fear responses during odor fear conditioning. In this paradigm an initially neutral odor (the conditioned stimulus, CS) predicted the arrival of an aversive unconditioned stimulus (US, footshock) at a fixed 20-s time interval. We first investigated the development of a temporal pattern of responding related to CS-US interval duration. The data showed that during acquisition with odor-shock pairings, a temporal response pattern of respiration rate was observed. Changing the CS-US interval duration from 20-s to 30-s resulted in a shift of the temporal response pattern appropriate to the new duration thus demonstrating that the pattern reflected the learning of the CS-US interval. A temporal pattern was also observed during a retention test 24 h later for both respiration and freezing measures, suggesting that the animals had stored the interval duration in long-term memory. We then investigated the role of intra-amygdalar dopaminergic transmission in interval timing. For this purpose, the D1 dopaminergic receptors antagonist SCH23390 was infused in the basolateral amygdala before conditioning. This resulted in an alteration of timing behavior, as reflected in differential temporal patterns between groups observed in a 24 h retention test off drug. The present data suggest that D1 receptor dopaminergic transmission within the amygdala is involved in temporal processing.

Why am I lost without dopamine? Effects of 6-OHDA lesion on the encoding of reward and decision process in CA3

There is growing evidence that Parkinson's disease, generally characterized by motor symptoms, also causes cognitive impairment such as spatial disorientation. The hippocampus is a critical structure for spatial navigation and receives sparse but comprehensive dopamine (DA) innervation. DA loss is known to be the cause of Parkinson's disease and therefore it has been hypothesized that the associated spatial disorientation could result from hippocampal dysfunction. Because DA is involved in the prediction of reward expectation, it is possible to infer that spatial disorientation in DA depleted subjects results from the loss of the ability to detect the rewarding features within the environment. Amongst hippocampal formation subdivisions, CA3 properties such as the high liability of its place fields make it a serious candidate for interfacing DA reward system and spatial information encoding. We addressed this issue using multiple electrode recordings of CA3 in normal and dopamine depleted rats performing a spatial learning in a Y-maze. Our data confirm that DA is essential to spatial learning as its depletion results in spatial impairments. The present work also shows that CA3 involvement in the detection of spatial feature contextual significance is under DA control. Finally, it also shows that CA3 contributes to the decision making processes of navigation tasks. The data also reveal a lateralization effect of DA depletion underlined by neural correlates.

Mapping of the receptive fields in the optic tectum of chicken (Gallus gallus) using sparse noise

The optic tectum plays a key role in visual processing in birds. While the input from the retina is topographic in the superficial layers, the deep layers project to the thalamic nucleus rotundus in a functional topographical manner. Although the receptive fields of tectal neurons in birds have been mapped before, a high resolution description of the white and black subfields of the receptive fields of tectal neurons is not available. We measured the receptive fields of neurons in the different layers of the tectum of anesthetized chickens with black and white stimuli that were flashed on a grey background in fast progression. Our results show that neurons in the deep layers of the optic tectum tend to respond stronger to black stimuli compared to white stimuli. In addition, the receptive field sizes are larger when measured using black stimuli than with white stimuli. While the black subfield was significantly larger than the white subfield for the intermediate and deep layers, no significant effects were found for the superficial layers. Finally, we investigated the optimal stimulus size in a subset of the neurons and found that these cells respond best to small white stimuli and to large black stimuli. In the majority of the cases the response was stronger to a large black bar than to a small white bar. We propose that such a stronger response to black stimuli might be advantageous for the detection of darker objects against the brighter sky.

Modulations of EEG beta power during planning and execution of grasping movements

Although beta oscillations (≈ 13–35 Hz) are often considered as a sensorimotor rhythm, their functional role remains debated. In particular, the modulations of beta power during preparation and execution of complex movements in different contexts were barely investigated. Here, we analysed the beta oscillations recorded with electroencephalography (EEG) in a precued grasping task in which we manipulated two critical parameters: the grip type (precision vs. side grip) and the force (high vs. low force) required to pull an object along a horizontal axis. A cue was presented 3 s before a GO signal and provided full, partial or no information about the two movement parameters. We measured beta power over the centro-parietal areas during movement preparation and execution as well as during object hold. We explored the modulations of power in relation to the amount and type of prior information provided by the cue. We also investigated how beta power was affected by the grip and force parameters.

We observed an increase in beta power around the cue onset followed by a decrease during movement preparation and execution. These modulations were followed by a transient power increase during object hold. This pattern of modulations did not differ between the 4 movement types (2 grips ×2 forces). However, the amount and type of prior information provided by the cue had a significant effect on the beta power during the preparatory delay. We discuss how these results fit with current hypotheses on the functional role of beta oscillations.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

Background

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue.

Results

Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms.

Conclusions

This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.

Faster, deeper, better: the impact of sniffing modulation on bulbar olfactory processing

A key feature of mammalian olfactory perception is that sensory input is intimately related to respiration. Different authors have considered respiratory dynamics not only as a simple vector for odor molecules but also as an integral part of olfactory perception. Thus, rats adapt their sniffing strategy, both in frequency and flow rate, when performing odor-related tasks. The question of how frequency and flow rate jointly impact the spatio-temporal representation of odor in the olfactory bulb (OB) has not yet been answered. In the present paper, we addressed this question using a simulated nasal airflow protocol on anesthetized rats combined with voltage-sensitive dye imaging (VSDi) of odor-evoked OB glomerular maps. Glomerular responses displayed a tonic component during odor stimulation with a superimposed phasic component phase-locked to the sampling pattern. We showed that a high sniffing frequency (10 Hz) retained the ability to shape OB activity and that the tonic and phasic components of the VSDi responses were dependent on flow rate and inspiration volume, respectively. Both sniffing parameters jointly affected OB responses to odor such that the reduced activity level induced by a frequency increase was compensated by an increased flow rate.

An interdisciplinary learning experience in neuro-optics

How can a Ph.D. student initially trained as a biologist take part in the development of a multineuronal recording method that requires cross interaction between physics, neurobiology and mathematics? Beyond student training in the laboratory, interdisciplinary research calls for a new style of academic training of young researchers. Here we present an innovative approach to graduate student academic training that fills the need for multidisciplinary knowledge and provides students, in addition, with a deeper understanding of the interdisciplinary approach to scientific research.