scholarly journals Bayesian Correction for Attenuation of Correlation in Multi-Trial Spike Count Data

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.

2020 ◽  
Author(s):  
Lukas Röseler ◽  
Daniel Wolf ◽  
Johannes Leder ◽  
Astrid Schütz

We argue that the test-retest reliability coefficient, which is the correlation between a measurement and a repeated measurement using the same diagnostic instrument in the same sample (sometimes referred to as repeatability or falsely referred to as stability), is by itself not an appropriate measure of the reliability of the diagnostic instrument or of the stability of the construct in question. In combination with an actual coefficient of reliability such as Cronbach’s alpha, the test-retest reliability coefficient can be used to estimate and compare the stabilities of constructs using a procedure based on the correction for attenuation. However, results from a simulation study showed that classically constructed confidence intervals for the estimator exhibit under-coverage and thus cannot be interpreted correctly.


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.


Author(s):  
Dankmar Böhning ◽  
Herwig Friedl

AbstractEstimating the size of a hard-to-count population is a challenging matter. In particular, when only few observations of the population to be estimated are available. The matter gets even more complex when one-inflation occurs. This situation is illustrated with the help of two examples: the size of a dice snake population in Graz (Austria) and the number of flare stars in the Pleiades. The paper discusses how one-inflation can be easily handled in likelihood approaches and also discusses how variances and confidence intervals can be obtained by means of a semi-parametric bootstrap. A Bayesian approach is mentioned as well and all approaches result in similar estimates of the hidden size of the population. Finally, a simulation study is provided which shows that the unconditional likelihood approach as well as the Bayesian approach using Jeffreys’ prior perform favorable.


1998 ◽  
Vol 21 (4) ◽  
pp. 529-530
Author(s):  
Barry J. Sessle

This commentary focusses on MacNeilage's arguments and evidence that the development of cerebral cortical controls over cyclic ingestive movements has provided substrates for the evolution of speech production. It outlines evidence from experimental approaches using cortical stimulation, inactivation, and single neuron recording in primates that lateral frontal cortical regions are indeed crucial for the generation and guidance of cyclic orofacial movements.


2021 ◽  
pp. 263208432199622
Author(s):  
Tim Mathes ◽  
Oliver Kuss

Background Meta-analysis of systematically reviewed studies on interventions is the cornerstone of evidence based medicine. In the following, we will introduce the common-beta beta-binomial (BB) model for meta-analysis with binary outcomes and elucidate its equivalence to panel count data models. Methods We present a variation of the standard “common-rho” BB (BBST model) for meta-analysis, namely a “common-beta” BB model. This model has an interesting connection to fixed-effect negative binomial regression models (FE-NegBin) for panel count data. Using this equivalence, it is possible to estimate an extension of the FE-NegBin with an additional multiplicative overdispersion term (RE-NegBin), while preserving a closed form likelihood. An advantage due to the connection to econometric models is, that the models can be easily implemented because “standard” statistical software for panel count data can be used. We illustrate the methods with two real-world example datasets. Furthermore, we show the results of a small-scale simulation study that compares the new models to the BBST. The input parameters of the simulation were informed by actually performed meta-analysis. Results In both example data sets, the NegBin, in particular the RE-NegBin showed a smaller effect and had narrower 95%-confidence intervals. In our simulation study, median bias was negligible for all methods, but the upper quartile for median bias suggested that BBST is most affected by positive bias. Regarding coverage probability, BBST and the RE-NegBin model outperformed the FE-NegBin model. Conclusion For meta-analyses with binary outcomes, the considered common-beta BB models may be valuable extensions to the family of BB models.


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