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Find video protocols related to scientific articles indexed in Pubmed.
Independent components of neural activity carry information on individual populations.
PLoS ONE
PUBLISHED: 08-25-2014
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Local field potential (LFP), the low-frequency part of the potential recorded extracellularly in the brain, reflects neural activity at the population level. The interpretation of LFP is complicated because it can mix activity from remote cells, on the order of millimeters from the electrode. To understand better the relation between the recordings and the local activity of cells we used a large-scale network thalamocortical model to compute simultaneous LFP, transmembrane currents, and spiking activity. We used this model to study the information contained in independent components obtained from the reconstructed Current Source Density (CSD), which smooths transmembrane currents, decomposed further with Independent Component Analysis (ICA). We found that the three most robust components matched well the activity of two dominating cell populations: superior pyramidal cells in layer 2/3 (rhythmic spiking) and tufted pyramids from layer 5 (intrinsically bursting). The pyramidal population from layer 2/3 could not be well described as a product of spatial profile and temporal activation, but by a sum of two such products which we recovered in two of the ICA components in our analysis, which correspond to the two first principal components of PCA decomposition of layer 2/3 population activity. At low noise one more cell population could be discerned but it is unlikely that it could be recovered in experiment given typical noise ranges.
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Frequency dependence of signal power and spatial reach of the local field potential.
PLoS Comput. Biol.
PUBLISHED: 07-01-2013
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Despite its century-old use, the interpretation of local field potentials (LFPs), the low-frequency part of electrical signals recorded in the brain, is still debated. In cortex the LFP appears to mainly stem from transmembrane neuronal currents following synaptic input, and obvious questions regarding the locality of the LFP are: What is the size of the signal-generating region, i.e., the spatial reach, around a recording contact? How far does the LFP signal extend outside a synaptically activated neuronal population? And how do the answers depend on the temporal frequency of the LFP signal? Experimental inquiries have given conflicting results, and we here pursue a modeling approach based on a well-established biophysical forward-modeling scheme incorporating detailed reconstructed neuronal morphologies in precise calculations of population LFPs including thousands of neurons. The two key factors determining the frequency dependence of LFP are the spatial decay of the single-neuron LFP contribution and the conversion of synaptic input correlations into correlations between single-neuron LFP contributions. Both factors are seen to give low-pass filtering of the LFP signal power. For uncorrelated input only the first factor is relevant, and here a modest reduction (<50%) in the spatial reach is observed for higher frequencies (>100 Hz) compared to the near-DC ([Formula: see text]) value of about [Formula: see text]. Much larger frequency-dependent effects are seen when populations of pyramidal neurons receive correlated and spatially asymmetric inputs: the low-frequency ([Formula: see text]) LFP power can here be an order of magnitude or more larger than at 60 Hz. Moreover, the low-frequency LFP components have larger spatial reach and extend further outside the active population than high-frequency components. Further, the spatial LFP profiles for such populations typically span the full vertical extent of the dendrites of neurons in the population. Our numerical findings are backed up by an intuitive simplified model for the generation of population LFP.
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Inverse current source density method in two dimensions: inferring neural activation from multielectrode recordings.
Neuroinformatics
PUBLISHED: 03-17-2011
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The recent development of large multielectrode recording arrays has made it affordable for an increasing number of laboratories to record from multiple brain regions simultaneously. The development of analytical tools for array data, however, lags behind these technological advances in hardware. In this paper, we present a method based on forward modeling for estimating current source density from electrophysiological signals recorded on a two-dimensional grid using multi-electrode rectangular arrays. This new method, which we call two-dimensional inverse Current Source Density (iCSD 2D), is based upon and extends our previous one- and three-dimensional techniques. We test several variants of our method, both on surrogate data generated from a collection of Gaussian sources, and on model data from a population of layer 5 neocortical pyramidal neurons. We also apply the method to experimental data from the rat subiculum. The main advantages of the proposed method are the explicit specification of its assumptions, the possibility to include system-specific information as it becomes available, the ability to estimate CSD at the grid boundaries, and lower reconstruction errors when compared to the traditional approach. These features make iCSD 2D a substantial improvement over the approaches used so far and a powerful new tool for the analysis of multielectrode array data. We also provide a free GUI-based MATLAB toolbox to analyze and visualize our test data as well as user datasets.
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Differential effects produced by ketamine on oscillatory activity recorded in the rat hippocampus, dorsal striatum and nucleus accumbens.
J. Psychopharmacol. (Oxford)
PUBLISHED: 04-22-2010
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Previously, we showed that NMDA antagonists enhance high-frequency oscillations (130-180?Hz) in the nucleus accumbens. However, whether NMDA antagonists can enhance high-frequency oscillations in other brain regions remains unclear. Here, we used monopolar, bipolar and inverse current source density techniques to examine oscillatory activity in the hippocampus, a region known to generate spontaneous ripples (?200?Hz), its surrounding tissue, and the dorsal striatum, neuroanatomically related to the nucleus accumbens. In monopolar recordings, ketamine-induced increases in the power of high-frequency oscillations were detected in all structures, although the power was always substantially larger in the nucleus accumbens. In bipolar recordings, considered to remove common-mode input, high-frequency oscillations associated with ketamine injection were not present in the regions we investigated outside the nucleus accumbens. In line with this, inverse current source density showed the greatest changes in current to occur in the vicinity of the nucleus accumbens and a monopolar structure of the generator. We found little spatial localisation of ketamine high-frequency oscillations in other areas. In contrast, sharp-wave ripples, which were well localized to the hippocampus, occurred less frequently after ketamine. Notably, we also found ketamine produced small, but significant, changes in the power of 30-90?Hz gamma oscillations (an increase in the hippocampus and a decrease in the nucleus accumbens).
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.