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2004


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On the variability of manual spike sorting

Wood, F., Black, M. J., Vargas-Irwin, C., Fellows, M., Donoghue, J. P.

IEEE Trans. Biomedical Engineering, 51(6):912-918, June 2004 (article)

pdf pdf from publisher [BibTex]

2004

pdf pdf from publisher [BibTex]


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Modeling and decoding motor cortical activity using a switching Kalman filter

Wu, W., Black, M. J., Mumford, D., Gao, Y., Bienenstock, E., Donoghue, J. P.

IEEE Trans. Biomedical Engineering, 51(6):933-942, June 2004 (article)

Abstract
We present a switching Kalman filter model for the real-time inference of hand kinematics from a population of motor cortical neurons. Firing rates are modeled as a Gaussian mixture where the mean of each Gaussian component is a linear function of hand kinematics. A “hidden state” models the probability of each mixture component and evolves over time in a Markov chain. The model generalizes previous encoding and decoding methods, addresses the non-Gaussian nature of firing rates, and can cope with crudely sorted neural data common in on-line prosthetic applications.

pdf pdf from publisher [BibTex]

pdf pdf from publisher [BibTex]


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Development of neural motor prostheses for humans

Donoghue, J., Nurmikko, A., Friehs, G., Black, M.

In Advances in Clinical Neurophysiology, (Editors: Hallett, M. and Phillips, L.H. and Schomer, D.L. and Massey, J.M.), Supplements to Clinical Neurophysiology Vol. 57, 2004 (incollection)

pdf [BibTex]

pdf [BibTex]

1999


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Artscience Sciencart

Black, M. J., Levy, D., PamelaZ,

In Art and Innovation: The Xerox PARC Artist-in-Residence Program, pages: 244-300, (Editors: Harris, C.), MIT-Press, 1999 (incollection)

Abstract
One of the effects of the PARC Artist In Residence (PAIR) program has been to expose the strong connections between scientists and artists. Both do what they do because they need to do it. They are often called upon to justify their work in order to be allowed to continue to do it. They need to justify it to funders, to sponsoring institutions, corporations, the government, the public. They publish papers, teach workshops, and write grants touting the educational or health benefits of what they do. All of these things are to some extent valid, but the fact of the matter is: artists and scientists do their work because they are driven to do it. They need to explore and create.

This chapter attempts to give a flavor of one multi-way "PAIRing" between performance artist PamelaZ and two PARC researchers, Michael Black and David Levy. The three of us paired up because we found each other interesting. We chose each other. While most artists in the program are paired with a single researcher Pamela jokingly calls herself a bigamist for choosing two PAIR "husbands" with different backgrounds and interests.

There are no "rules" to the PAIR program; no one told us what to do with our time. Despite this we all had a sense that we needed to produce something tangible during Pamela's year-long residency. In fact, Pamela kept extending her residency because she did not feel as though we had actually made anything concrete. The interesting thing was that all along we were having great conversations, some of which Pamela recorded. What we did not see at the time was that it was these conversations between artists and scientists that are at the heart of the PAIR program and that these conversations were changing the way we thought about our own work and the relationships between science and art.

To give these conversations their due, and to allow the reader into our PAIR interactions, we include two of our many conversations in this chapter.

[BibTex]

1999

[BibTex]


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Parameterized modeling and recognition of activities

Yacoob, Y., Black, M. J.

Computer Vision and Image Understanding, 73(2):232-247, 1999 (article)

Abstract
In this paper we consider a class of human activities—atomic activities—which can be represented as a set of measurements over a finite temporal window (e.g., the motion of human body parts during a walking cycle) and which has a relatively small space of variations in performance. A new approach for modeling and recognition of atomic activities that employs principal component analysis and analytical global transformations is proposed. The modeling of sets of exemplar instances of activities that are similar in duration and involve similar body part motions is achieved by parameterizing their representation using principal component analysis. The recognition of variants of modeled activities is achieved by searching the space of admissible parameterized transformations that these activities can undergo. This formulation iteratively refines the recognition of the class to which the observed activity belongs and the transformation parameters that relate it to the model in its class. We provide several experiments on recognition of articulated and deformable human motions from image motion parameters.

pdf pdf from publisher DOI [BibTex]

pdf pdf from publisher DOI [BibTex]


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Image segmentation using robust mixture models

Black, M. J., Jepson, A. D.

US Pat. 5,802,203, June 1995 (patent)

pdf on-line at USPTO [BibTex]