Ceramic-Based Multisite Electrode Arrays for Chronic Single-Neuron Recording

2004 ◽  
Vol 51 (4) ◽  
pp. 647-656 ◽  
Author(s):  
K.A. Moxon ◽  
S. Leiser ◽  
G.A. Gerhardt ◽  
K.A. Barbee ◽  
J.K. Chapin
Cortex ◽  
2014 ◽  
Vol 60 ◽  
pp. 3-9 ◽  
Author(s):  
Elisa Frisaldi ◽  
Elisa Carlino ◽  
Michele Lanotte ◽  
Leonardo Lopiano ◽  
Fabrizio Benedetti

2020 ◽  
Author(s):  
Zijun Sun ◽  
Thomas C. Südhof

AbstractBackgroundCa2+-imaging is a powerful tool to measure neuronal dynamics and network activity. To monitor network-level changes in cultured neurons, neuronal activity is often evoked by electrical or optogenetic stimulation and assessed using multi-electrode arrays or sophisticated imaging. Although such approaches allow detailed network analyses, multi-electrode arrays lack single-cell precision, whereas optical physiology generally requires advanced instrumentation.New MethodHere we developed a simple, stimulation-free protocol with associated Matlab algorithms that enables scalable analyses of network activity in cultured human and mouse neurons. The approach allows analysis of overall networks and single-neuron dynamics, and is amenable to scale-up for screening purposes.ResultsWe validated the protocol by assessing human neurons with a heterozygous conditional deletion of Munc18-1, and mouse neurons with a homozygous conditional deletion of neurexins. The approach described here enabled identification of differential changes in these mutant neurons at the network level and of the amplitude and frequency of calcium peaks at the single-neuron level. These results demonstrate the utility of the approach.Comparison with existing methodCompared with current imaging platforms, our method is simple, scalable, and easy to implement. It enables quantification of more detailed parameters than multi-electrode arrays, but does not have the resolution and depth of more sophisticated yet labour-intensive analysis methods, such as electrophysiology.ConclusionThis method is scalable for a rapid assessment of neuronal function in culture, and can be applied to both human and mouse neurons. Thus, the method can serve as a basis for phenotypical analysis of mutations and for drug discovery efforts.


2003 ◽  
Vol 89 (3) ◽  
pp. 1503-1518 ◽  
Author(s):  
Vassilis Raos ◽  
Gianfranco Franchi ◽  
Vittorio Gallese ◽  
Leonardo Fogassi

The somatotopy of the lateral part of dorsal premotor area F2 has been studied by means of intracortical microstimulation and single neuron recording. The results show that most of this sector of F2 is excitable with low-intensity currents (3–40 μA) and that intracortical microstimulation evokes forelimb and trunk movements. Both proximal and distal forelimb movements are evoked in similar percentages. The proximal and distal forelimb representations partially overlap. However, proximal movements tend to be located more medially (laterally to the superior precentral dimple), whereas distal movements tend to be located more laterally (medially to the spur of the arcuate sulcus). The somatotopic organization demonstrated with microstimulation is confirmed by the similar somatotopic organization of active movements and of somatosensory properties revealed by single-neuron recording. The excitability and somatotopic organization of the lateral part of area F2 are discussed in relation to previous electrophysiological and anatomical findings. The involvement of the distal forelimb representation of area F2 in programming and controlling reaching to grasp movements is suggested.


2009 ◽  
Vol 101 (4) ◽  
pp. 2186-2193 ◽  
Author(s):  
Sam Behseta ◽  
Tamara Berdyyeva ◽  
Carl R. Olson ◽  
Robert E. Kass

When correlation is measured in the presence of noise, its value is decreased. In single-neuron recording experiments, for example, the correlation of selectivity indices in a pair of tasks may be assessed across neurons, but, because the number of trials is limited, the measured index values for each neuron will be noisy. This attenuates the correlation. A correction for such attenuation was proposed by Spearman more than 100 yr ago, and more recent work has shown how confidence intervals may be constructed to supplement the correction. In this paper, we propose an alternative Bayesian correction. A simulation study shows that this approach can be far superior to Spearman's, both in accuracy of the correction and in coverage of the resulting confidence intervals. We demonstrate the usefulness of this technology by applying it to a set of data obtained from the frontal cortex of a macaque monkey while performing serial order and variable reward saccade tasks. There the correction results in a substantial increase in the correlation across neurons in the two tasks.


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