28 research outputs found

    Sensory Coding by Cerebellar Mossy Fibres through Inhibition-Driven Phase Resetting and Synchronisation

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    Temporal coding of spike-times using oscillatory mechanisms allied to spike-time dependent plasticity could represent a powerful mechanism for neuronal communication. However, it is unclear how temporal coding is constructed at the single neuronal level. Here we investigate a novel class of highly regular, metronome-like neurones in the rat brainstem which form a major source of cerebellar afferents. Stimulation of sensory inputs evoked brief periods of inhibition that interrupted the regular firing of these cells leading to phase-shifted spike-time advancements and delays. Alongside phase-shifting, metronome cells also behaved as band-pass filters during rhythmic sensory stimulation, with maximal spike-stimulus synchronisation at frequencies close to the idiosyncratic firing frequency of each neurone. Phase-shifting and band-pass filtering serve to temporally align ensembles of metronome cells, leading to sustained volleys of near-coincident spike-times, thereby transmitting synchronised sensory information to downstream targets in the cerebellar cortex

    Oscillatory activity in the medial prefrontal cortex and nucleus accumbens correlates with impulsivity and reward outcome.

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    Actions expressed prematurely without regard for their consequences are considered impulsive. Such behaviour is governed by a network of brain regions including the prefrontal cortex (PFC) and nucleus accumbens (NAcb) and is prevalent in disorders including attention deficit hyperactivity disorder (ADHD) and drug addiction. However, little is known of the relationship between neural activity in these regions and specific forms of impulsive behaviour. In the present study we investigated local field potential (LFP) oscillations in distinct sub-regions of the PFC and NAcb on a 5-choice serial reaction time task (5-CSRTT), which measures sustained, spatially-divided visual attention and action restraint. The main findings show that power in gamma frequency (50-60 Hz) LFP oscillations transiently increases in the PFC and NAcb during both the anticipation of a cue signalling the spatial location of a nose-poke response and again following correct responses. Gamma oscillations were coupled to low-frequency delta oscillations in both regions; this coupling strengthened specifically when an error response was made. Theta (7-9 Hz) LFP power in the PFC and NAcb increased during the waiting period and was also related to response outcome. Additionally, both gamma and theta power were significantly affected by upcoming premature responses as rats waited for the visual cue to respond. In a subgroup of rats showing persistently high levels of impulsivity we found that impulsivity was associated with increased error signals following a nose-poke response, as well as reduced signals of previous trial outcome during the waiting period. Collectively, these in-vivo neurophysiological findings further implicate the PFC and NAcb in anticipatory impulsive responses and provide evidence that abnormalities in the encoding of rewarding outcomes may underlie trait-like impulsive behaviour.RCUK, Wellcome, OtherThis is the final version of the article. It first appeared at http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0111300

    A Wireless Multi-Channel Recording System for Freely Behaving Mice and Rats

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    To understand the neural basis of behavior, it is necessary to record brain activity in freely moving animals. Advances in implantable multi-electrode array technology have enabled researchers to record the activity of neuronal ensembles from multiple brain regions. The full potential of this approach is currently limited by reliance on cable tethers, with bundles of wires connecting the implanted electrodes to the data acquisition system while impeding the natural behavior of the animal. To overcome these limitations, here we introduce a multi-channel wireless headstage system designed for small animals such as rats and mice. A variety of single unit and local field potential signals were recorded from the dorsal striatum and substantia nigra in mice and the ventral striatum and prefrontal cortex simultaneously in rats. This wireless system could be interfaced with commercially available data acquisition systems, and the signals obtained were comparable in quality to those acquired using cable tethers. On account of its small size, light weight, and rechargeable battery, this wireless headstage system is suitable for studying the neural basis of natural behavior, eliminating the need for wires, commutators, and other limitations associated with traditional tethered recording systems

    Probabilistic identification of cerebellar cortical neurones across species.

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    Despite our fine-grain anatomical knowledge of the cerebellar cortex, electrophysiological studies of circuit information processing over the last fifty years have been hampered by the difficulty of reliably assigning signals to identified cell types. We approached this problem by assessing the spontaneous activity signatures of identified cerebellar cortical neurones. A range of statistics describing firing frequency and irregularity were then used, individually and in combination, to build Gaussian Process Classifiers (GPC) leading to a probabilistic classification of each neurone type and the computation of equi-probable decision boundaries between cell classes. Firing frequency statistics were useful for separating Purkinje cells from granular layer units, whilst firing irregularity measures proved most useful for distinguishing cells within granular layer cell classes. Considered as single statistics, we achieved classification accuracies of 72.5% and 92.7% for granular layer and molecular layer units respectively. Combining statistics to form twin-variate GPC models substantially improved classification accuracies with the combination of mean spike frequency and log-interval entropy offering classification accuracies of 92.7% and 99.2% for our molecular and granular layer models, respectively. A cross-species comparison was performed, using data drawn from anaesthetised mice and decerebrate cats, where our models offered 80% and 100% classification accuracy. We then used our models to assess non-identified data from awake monkeys and rabbits in order to highlight subsets of neurones with the greatest degree of similarity to identified cell classes. In this way, our GPC-based approach for tentatively identifying neurones from their spontaneous activity signatures, in the absence of an established ground-truth, nonetheless affords the experimenter a statistically robust means of grouping cells with properties matching known cell classes. Our approach therefore may have broad application to a variety of future cerebellar cortical investigations, particularly in awake animals where opportunities for definitive cell identification are limited

    An intra-cerebral drug delivery system for freely moving animals

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    Abstract Microinfusions of drugs directly into the central nervous system of awake animals represent a widely used means of unravelling brain functions related to behaviour. However, current approaches generally use tethered liquid infusion systems and a syringe pump to deliver drugs into the brain, which often interfere with behaviour. We address this shortfall with a miniaturised electronically-controlled drug delivery system (20×17.5×5 mm 3 ) designed to be skull-mounted in rats. The device features a micropump connected to two 8-mm-long silicon microprobes with a cross section of 250×250 μm 2 and integrated fluid microchannels. Using an external electronic control unit, the device allows infusion of 16 metered doses (0.25 μL each, 8 per silicon shaft). Each dosage requires 3.375 Ws of electrical power making the device additionally compatible with state-of-the-art wireless headstages. A dosage precision of 0.25±0.01 μL was determined in vitro before in vivo tests were carried out in awake rats. No passive leakage from the loaded devices into the brain could be detected using methylene blue dye. Finally, the device was used to investigate the effects of the NMDA-receptor antagonist 3-((R)-2-Carboxypiperazin-4-yl)-propyl-1-phosphonic acid, (R)-CPP, administered directly into the prefrontal cortex of rats during performance on a task to assess visual attention and impulsivity. In agreement with previous findings using conventional tethered infusion systems, acute (R)-CPP administration produced a marked increase in impulsivity

    Multichannel Silicon Probes for Awake Hippocampal Recordings in Large Animals

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    Decoding laminar information across deep brain structures and cortical regions is necessary in order to understand the neuronal ensembles that represent cognition and memory. Large animal models are essential for translational research due to their gyrencephalic neuroanatomy and significant white matter composition. A lack of long-length probes with appropriate stiffness allowing penetration to deeper structures with minimal damage to the neural interface is one of the major technical limitations to applying the approaches currently utilized in lower order animals to large animals. We therefore tested the performance of multichannel silicon probes of various solutions and designs that were developed specifically for large animal electrophysiology. Neurophysiological signals from dorsal hippocampus were recorded in chronically implanted awake behaving Yucatan pigs. Single units and local field potentials were analyzed to evaluate performance of given silicon probes over time. EDGE-style probes had the highest yields during intra-hippocampal recordings in pigs, making them the most suitable for chronic implantations and awake behavioral experimentation. In addition, the cross-sectional area of silicon probes was found to be a crucial determinant of silicon probe performance over time, potentially due to reduction of damage to the neural interface. Novel 64-channel EDGE-style probes tested acutely produced an optimal single unit separation and a denser sampling of the laminar structure, identifying these research silicon probes as potential candidates for chronic implantations. This study provides an analysis of multichannel silicon probes designed for large animal electrophysiology of deep laminar brain structures, and suggests that current designs are reaching the physical thresholds necessary for long-term (∼1 month) recordings with single-unit resolution

    ProbeInterface: A Unified Framework for Probe Handling in Extracellular Electrophysiology

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    International audienceRecording neuronal activity with penetrating extracellular multi-channel electrode arrays, more commonly known as neural probes, is one of the most widespread approaches to probe neuronal activity. Despite a plethora of available extracellular probe designs, the time-consuming process of mapping of electrode channel order and relative geometries, as required by spike-sorting software is invariably left to the end-user. Consequently, this manual process is prone to mis-mapping mistakes, which in turn lead to undesirable spike-sorting errors and inefficiencies. Here, we introduce ProbeInterface , an open-source project that aims to unify neural probe metadata descriptions by removing the manual step of probe mapping prior to spike-sorting for the analysis of extracellular neural recordings. ProbeInterface is first of all a Python API, which enables users to create and visualize probes and probe groups at any required complexity level. Second, ProbeInterface facilitates the generation of comprehensive wiring description in a reproducible fashion for any specific data-acquisition setup, which usually involves the use of a recording probe, a headstage, adapters, and an acquisition system. Third, we collaborate with probe manufacturers to compile an open library of available probes, which can be downloaded at run time using our Python API. Finally, with ProbeInterface we define a file format for probe handling which includes all necessary information for a FAIR probe description and is compatible with and complementary to other open standards in neuroscience

    Probabilistic Identification of Cerebellar Cortical Neurones across Species

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    Despite our fine-grain anatomical knowledge of the cerebellar cortex, electrophysiological studies of circuit information processing over the last fifty years have been hampered by the difficulty of reliably assigning signals to identified cell types. We approached this problem by assessing the spontaneous activity signatures of identified cerebellar cortical neurones. A range of statistics describing firing frequency and irregularity were then used, individually and in combination, to build Gaussian Process Classifiers (GPC) leading to a probabilistic classification of each neurone type and the computation of equi-probable decision boundaries between cell classes. Firing frequency statistics were useful for separating Purkinje cells from granular layer units, whilst firing irregularity measures proved most useful for distinguishing cells within granular layer cell classes. Considered as single statistics, we achieved classification accuracies of 72.5% and 92.7% for granular layer and molecular layer units respectively. Combining statistics to form twin-variate GPC models substantially improved classification accuracies with the combination of mean spike frequency and log-interval entropy offering classification accuracies of 92.7% and 99.2% for our molecular and granular layer models, respectively. A cross-species comparison was performed, using data drawn from anaesthetised mice and decerebrate cats, where our models offered 80% and 100% classification accuracy. We then used our models to assess non-identified data from awake monkeys and rabbits in order to highlight subsets of neurones with the greatest degree of similarity to identified cell classes. In this way, our GPC-based approach for tentatively identifying neurones from their spontaneous activity signatures, in the absence of an established ground-truth, nonetheless affords the experimenter a statistically robust means of grouping cells with properties matching known cell classes. Our approach therefore may have broad application to a variety of future cerebellar cortical investigations, particularly in awake animals where opportunities for definitive cell identification are limited.status: publishe
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