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- Emery N. Brown, Riccardo Barbieri, Valérie Ventura, Robert E. Kass, Loren M. Frank
- Neural Computation
- 2002

Measuring agreement between a statistical model and a spike train data series, that is, evaluating goodness of fit, is crucial for establishing the model's validity prior to using it to make inferences about a particular neural system. Assessing goodness-of-fit is a challenging problem for point process neural spike train models, especially for… (More)

- B ILARIA DMATTEO, CHRISTOPHER R. GENOVESE, ROBERT E. KASS
- 2002

We describe a Bayesian method, for fitting curves to data drawn from an exponential family, that uses splines for which the number and locations of knots are free parameters. The method uses reversible-jump Markov chain Monte Carlo to change the knot configurations and a locality heuristic to speed up mixing. For nonnormal models, we approximate the… (More)

- A E Brockwell, A L Rojas, R E Kass
- Journal of neurophysiology
- 2004

The population vector (PV) algorithm and optimal linear estimation (OLE) have been used to reconstruct movement by combining signals from multiple neurons in the motor cortex. While these linear methods are effective, recursive Bayesian decoding schemes, which are nonlinear, can be more powerful when probability model assumptions are satisfied. We have… (More)

- Emery N Brown, Robert E Kass, Partha P Mitra
- Nature neuroscience
- 2004

Multiple electrodes are now a standard tool in neuroscience research that make it possible to study the simultaneous activity of several neurons in a given brain region or across different regions. The data from multi-electrode studies present important analysis challenges that must be resolved for optimal use of these neurophysiological measurements to… (More)

In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null is one-half. Although there has been much discussion of… (More)

- Beata Jarosiewicz, Steven M Chase, George W Fraser, Meel Velliste, Robert E Kass, Andrew B Schwartz
- Proceedings of the National Academy of Sciences…
- 2008

Efforts to study the neural correlates of learning are hampered by the size of the network in which learning occurs. To understand the importance of learning-related changes in a network of neurons, it is necessary to understand how the network acts as a whole to generate behavior. Here we introduce a paradigm in which the output of a cortical network can… (More)

- Garrick L Wallstrom, Robert E Kass, Anita Miller, Jeffrey F Cohn, Nathan A Fox
- International journal of psychophysiology…
- 2004

A variety of procedures have been proposed to correct ocular artifacts in the electroencephalogram (EEG), including methods based on regression, principal components analysis (PCA) and independent component analysis (ICA). The current study compared these three methods, and it evaluated a modified regression approach using Bayesian adaptive regression… (More)

- Robert E Kass, Valérie Ventura, Emery N Brown
- Journal of neurophysiology
- 2005

Analysis of data from neurophysiological investigations can be challenging. Particularly when experiments involve dynamics of neuronal response, scientific inference can become subtle and some statistical methods may make much more efficient use of the data than others. This article reviews well-established statistical principles, which provide useful… (More)

- Robert E. Kass, Valérie Ventura
- Neural Computation
- 2001

Poisson processes usually provide adequate descriptions of the irregularity in neuron spike times after pooling the data across large numbers of trials, as is done in constructing the peristimulus time histogram. When probabilities are needed to describe the behavior of neurons within individual trials, however, Poisson process models are often inadequate.… (More)

- Steven M. Chase, Andrew B. Schwartz, Robert E. Kass
- Neural Networks
- 2009

The activity of dozens of simultaneously recorded neurons can be used to control the movement of a robotic arm or a cursor on a computer screen. This motor neural prosthetic technology has spurred an increased interest in the algorithms by which motor intention can be inferred. The simplest of these algorithms is the population vector algorithm (PVA), where… (More)