Cognitive neural prosthetics.
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Action Potentials↗
Biomedical subjects
B Pesaran
Publications and source records attributed to B Pesaran.
Cognitive neural prosthetics.
Research on neural prosthetics has focused largely on using activity related to hand trajectories recorded from motor cortical areas. An interesting question revolves around what other signals might be read out from the brain and used for neural prosthetic applications. Recent studies indicate that goals and expected value are among the high-level cognitive signals that can be used and will potentially enhance the ability of paralyzed patients to communicate with the outside world. Other new findings show that local field potentials provide an excellent source of information about the cognitive state of the subject and are much easier to record and maintain than spike activity. Finally, new movable probe technologies will enable recording electrodes to seek out automatically the best signals for decoding cognitive variables.
Animals↗
Magnetic resonance image-guided implantation of chronic recording electrodes in the macaque intraparietal sulcus.
The implantation of chronic recording electrodes in the brain has been shown to be a valuable method for simultaneously recording from many neurons. However, precise placement of these electrodes, crucial for successful recording, is challenging if the target area is not on the brain surface. Here we present a stereotaxic implantation procedure to chronically implant bundles of recording electrodes into macaque cortical sulci, employing magnetic resonance (MR) imaging to determine stereotaxic coordinates of target location and sulcus orientation. Using this method in four animals, we recorded simultaneously the spiking activity and the local field potential from the parietal reach region (PRR), located in the medial bank of the intraparietal sulcus (IPS), while the animal performed a reach movement task. Fifty percent of all electrodes recorded spiking activity during the first 2 post-operative months, indicating their placement within cortical gray matter. Chronic neural activity was similar to standard single electrode recordings in PRR, as reported previously. These results indicate that this MR image-guided implantation technique can provide sufficient placement accuracy in cortical sulci and subcortical structures. Moreover, this technique may be useful for future cortical prosthesis applications in humans that require implants within sulci.
Anesthesia, General↗
A procedure for an automated measurement of song similarity.
Assessment of vocal imitation requires a widely accepted way of describing and measuring any similarities between the song of a tutor and that of its pupil. Quantifying the similarity between two songs, however, can be difficult and fraught with subjective bias. We present a fully automated procedure that measures parametrically the similarity between songs. We tested its performance on a large database of zebra finch, Taeniopygia guttata, songs. The procedure uses an analytical framework of modern spectral analysis to characterize the acoustic structure of a song. This analysis provides a superior sound spectrogram that is then reduced to a set of simple acoustic features. Based on these features, the procedure detects similar sections between songs automatically. In addition, the procedure can be used to examine: (1) imitation accuracy across acoustic features; (2) song development; (3) the effect of brain lesions on specific song features; and (4) variability across different renditions of a song or a call produced by the same individual, across individuals and across populations. By making the procedure available we hope to promote the adoption of a standard, automated method for measuring similarity between songs or calls. Copyright 2000 The Association for the Study of Animal Behaviour.
Journal Article↗
Analysis of dynamic brain imaging data.
Modern imaging techniques for probing brain function, including functional magnetic resonance imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques for analysis and visualization of such imaging data to separate the signal from the noise and characterize the signal. The techniques developed fall into the general category of multivariate time series analysis, and in particular we extensively use the multitaper framework of spectral analysis. We develop specific protocols for the analysis of fMRI, optical imaging, and MEG data, and illustrate the techniques by applications to real data sets generated by these imaging modalities. In general, the analysis protocols involve two distinct stages: "noise" characterization and suppression, and "signal" characterization and visualization. An important general conclusion of our study is the utility of a frequency-based representation, with short, moving analysis windows to account for nonstationarity in the data. Of particular note are 1) the development of a decomposition technique (space-frequency singular value decomposition) that is shown to be a useful means of characterizing the image data, and 2) the development of an algorithm, based on multitaper methods, for the removal of approximately periodic physiological artifacts arising from cardiac and respiratory sources.
Brain↗
The role of nonlinear dynamics of the syrinx in the vocalizations of a songbird.
Birdsong is characterized by the modulation of sound properties over a wide image of timescales. Understanding the mechanisms by which the brain organizes this complex temporal behaviour is a central motivation in the study of the song control and learning system. Here we present evidence that, in addition to central neural control, a further level of temporal organization is provided by nonlinear oscillatory dynamics that are intrinsic to the avian vocal organ. A detailed temporal and spectral examination of song of the zebra finch (Taeniopygia guttata) reveals a class of rapid song modulations that are consistent with transitions in the dynamical state of the syrinx. Furthermore, in vitro experiments show that the syrinx can produce a sequence of oscillatory states that are both spectrally and temporally complex in response to the slow variation of respiratory or syringeal parameters. As a consequence, simple variations in a small number of neural signals can result in a complex acoustic sequence.
Animals↗
Visual stimuli induce waves of electrical activity in turtle cortex.
The computations involved in the processing of a visual scene invariably involve the interactions among neurons throughout all of visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334-337] support a view in which only synchronous (no phase lags) activity carries information about the visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by visual stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of approximately pi/2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during visual processing.
Animals↗