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GENERAL PROJECTSSpatial Navigation, Prosthetics, Neural Control of Cardiac Function |
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Spatial NavigationNumerous studies have shown that the hippocampus and adjacent cortical regions are essential for learning complex associations in animals ranging from rodents to humans. Very little is known about the neural correlates of that learning, however, and how sensory information is used to form these associations. In a collaboration with Emery Brown at MGH, we are therefore examining the relationship between patterns of neural firing and the behavioral changes that accompany learning in the hippocampus and adjacent cortical regions in the context of learning spatial environments. We designed a set of novel spatial tasks that rats can learn within one or two 20-minute sessions and we have been recording simultaneously from chronically implanted electrode arrays in the hippocampus, the entorhinal cortex (EC), and related neocortical regions while animals learn these tasks. The tasks are shown in Figure 15.
Figure 15. Familiar (1-3-7) and novel (1-3-6) configurations of T-maze task.. From Frank et al., 2004. The animal is pretrained before surgery on an alternation task in the familiar configuration, running continuously from arms 1 to 3 to 1 to 7 to 1 and so on until it achieves 80% correct performance, where each trial begins and ends in the home arm (arm 1). Once the animal has recovered from surgery and the electrodes have been advanced to the target brain regions, recordings are begun. On the first day of recording the animal runs on the familiar 1-3-1-7-1 task for 20 minutes and then, after a 20 minute rest period, the animal must learn the perform the same task with a new outside arm (eg. arm 7 is closed off and arm 6 is opened). The animal runs this new task for until it reaches 75% correct or until it has experienced the new environment three times, at which point the task for the second session is changed to include a new novel arm. This basic paradigm has spawned two distinct projects to date, described below. Plasticity in Novel Environments. It is well-established that the hippocampus is essential for learning complex spatial relationships, but little is known about how hippocampal neural activity changes as animals learn about a novel environment. In a recent project, we studied the formation of new place representations in rats by examining the changes in place-specific firing of neurons in the CA1 region of the hippocampus and the relationship between these changes and behavioral change across multiple days of exposure to novel places (Frank et al., 2004). We found that although some neurons maintain their place representation in the novel environment (such as that in Figure 16C), many neurons showed very rapid changes on the first day of exposure to the novel place, including many cases in which a previously silent neuron developed a place field over the course of a single pass through the environment, as shown in Figure 16D.
Figure 16. C, The place-related activity of a neuron that was active in the familiar configuration and maintained the same place field in the novel configuration. D, The place-related activity of a neuron recorded simultaneously from the same tetrode that was not active in the familiar configuration but developed a place field in the novel arm. Colorbar indicates the firing rate in Hz. From Frank et al., 2004. When we examined the formation of place representations in the novel arm, we found that although most neurons were active during the first traversal of the new place, many previously silent neurons developed place specific activity as the animal explored the novel arm. These findings extend previous observations from Hill (1978), who described 2 of 12 place cells as initially silent in a novel environment. We found place-specific activity could emerge in a particular neuron over as little as 5 sec comprising a single pass, even if there had been no spiking on previous passes. These findings are consistent We found that stable hippocampal place fields are not sufficient for an animal to treat a place as familiar. We hypothesize that neocortical, and perhaps subcortical, regions outside the hippocampus continue to distinguish between the novel and familiar places even after the hippocampal representation has formed and hippocampal plasticity has declined. These results provide support for the hypothesis that the hippocampus is specialized for rapid learning, and that other brain regions form representations more slowly. Thus, our findings suggest that although the hippocampus may form new memories quickly, using those memories to guide behavior also requires changes in other brain regions. The role of phase-locking between brain structures. The theta rhythm modulates activity in hippocampus and entorhinal cortex. In the CA1 region of hippocampus, the interaction between theta and place specificity leads to a temporal code wherein the phase of firing is related to the animal's position. We
Figure 17. a, Occupancy during the T-maze traversal over many trials (green dots), and for a single run from the top arm to the center (red dots). b, Power spectral density of the LFP signals from dEC (left) and CA1 (right), for a single electrode pair. Dashed line indicates the noise-floor. Both the position of the animal and local field potentials were recorded. Band-pass filtering was utilized to capture instantaneous amplitude and phase of the theta waves. Recording sites in dEC and CA1 exhibited strong power in the theta band, as shown in the right panel of Figure 17. The positive correlation between the power of theta waves in dEC and CA1 increased as the locomotive speed increased. More striking was the phase locking between the theta waves at the two loci. The degree of phase locking increased as the locomotive speed increased. This observation was statistically significant across all electrode pairs of all animals. Preliminary analysis suggests this strengthening of phase locking is not due to an increase in coupling between the two oscillators. Instead this is consistent with a model wherein external drive to dEC and CA1, perhaps from the medial septum, becomes more coherent at higher velocities to reduce systematic errors in registration between the two brain structures. Related Publications L. M. Frank, G. B. Stanley, and E. N. Brown. Hippocampal plasticity across multiple days of exposure to novel environments, J. Neurosci., 24: 7681-7689, 2004. PDF L. M. Frank, E. N. Brown, and G. B. Stanley. Hippocampal and cortical place cell plasticity: implications for episodic memory, submitted, 2006. J. R. Chen, L. M. Frank, E. N. Brown, G. B. Stanley. Theta waves in the hippcampus and the deep layer of the entorhinal cortex become more phase-locked with increasing locomotive speed, to be presented at SFN, Washington DC, 2005. PDF |
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ProstheticsHuman voice is the foundation of self-expression and vocal communication with others. Unfortunately, each year thousands of people undergo a laryngectomy, which is the surgical removal of the larynx for the treatment of cancer. Loss of the larynx results in an inability to produce normal speech and the need to breathe through a stoma (hole) in the neck. However, since the main articulators are still intact, a prosthetic device can be used to acoustically excite the vocal tract for production of alaryngeal speech. The majority of laryngectomy patients either use a tracheo-esophageal (TE) prosthesis, or an electrolarynx (EL). Use of the EL requires little training and produces intelligible speech, making it a popular voice aid. Multiple studies report that over half of the laryngectomy patients use an EL for verbal communication.
Figure 18. Processing stages of the EMG-EL processor: EMG signal is filtered and amplified, then rectified and smoothed to produce a slow envelope (top path) to modulate pitch, and a fast envelope (bottom path) to control on/off of the EL. From Goldstein et al., 2004. A major inconvenience in using a conventional hand-held EL device is that it requires the use of one hand. Before being able to speak or respond to a Related Publications E. A. Goldstein, J. T. Heaton, J. B. Kobler, G. B. Stanley, and R. E. Hillman. Design and implementation of a hands-free electrolarynx device controlled by neck strap muscle electromyographic activity, IEEE Trans. Biomed. Eng., 51:325-332, 2004. PDF |
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Neural Control of Cardiac Function - under construction
Related Publications G. B. Stanley, K. Poolla, and R. A. Siegel. Threshold modeling of autonomic control of heart rate variability, IEEE Trans. Biomed. Eng., 49(9):1147-1153, 2000. PDF G. Stanley, D. Verotta, N. Craft, R. A. Siegel, and J. B. Schwartz. Age effects on interrelationships between lung volume and heart rate during standing, Amer. J. Physiol., 42:H2128-H2134, 1997. PDF G. Stanley, D. Verotta, N. Craft, R. A. Siegel, and J. B. Schwartz. Age and autonomic effects on interrelationships between lung volume and heart rate, Amer. J. Physiol., 39:H1833-H1840, 1996. |
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