Abstract
Deep brain stimulation is an effective therapy for Parkinson's disease (PD) that has enabled microelectrode recordings from single-unit cells in the sub-thalamic nucleus (STN) of the basal ganglia. This rare data is important to develop detailed characterizations of spiking activity to understand the pathophysiology of PD. Despite the point process nature of neuronal spiking activity, point process (PP) methods are not used to analyze these recordings. Therefore, we develop PP models using the generalized linear method to characterize spiking activity in 28 STN neurons in 7 PD patients executing a two-step motor task. In the first step of the task, patients could anticipate visual go cues and moved once prompted. In the second step of the task, go cues had a 50% chance of appearing. If cues failed to appear, movements were self-initiated. The point process models provide an accurate summary of pathological characteristics under different cued conditions such as bursting, 10-30Hz oscillations, and fluctuations in directional tuning. In particular, the models show that when cues can be anticipated or when patients self-initiate movements (in both cases an internal motor plan is formed prior to movement), pathological neural characteristics are suppressed. In contrast, when cues cannot be anticipated and later appear, there is no suppression of pathological neural characteristics. Consequently, movements deteriorate.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 |
| Pages | 7716-7722 |
| Number of pages | 7 |
| DOIs | |
| State | Published - Dec 1 2009 |
| Externally published | Yes |
| Event | 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China Duration: Dec 15 2009 → Dec 18 2009 |
Other
| Other | 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 |
|---|---|
| Country | China |
| City | Shanghai |
| Period | 12/15/09 → 12/18/09 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization
Cite this
Using point process models to determine the impact of visual cues on basal ganglia activity and behavior of Parkinson's patients. / Sarma, Sridevi V.; Eden, Uri T.; Cheng, Ming L.; Williams, Ziv; Eskandar, Emad N.; Brown, Emery N.
Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. 2009. p. 7716-7722 5399938.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Using point process models to determine the impact of visual cues on basal ganglia activity and behavior of Parkinson's patients
AU - Sarma, Sridevi V.
AU - Eden, Uri T.
AU - Cheng, Ming L.
AU - Williams, Ziv
AU - Eskandar, Emad N.
AU - Brown, Emery N.
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Deep brain stimulation is an effective therapy for Parkinson's disease (PD) that has enabled microelectrode recordings from single-unit cells in the sub-thalamic nucleus (STN) of the basal ganglia. This rare data is important to develop detailed characterizations of spiking activity to understand the pathophysiology of PD. Despite the point process nature of neuronal spiking activity, point process (PP) methods are not used to analyze these recordings. Therefore, we develop PP models using the generalized linear method to characterize spiking activity in 28 STN neurons in 7 PD patients executing a two-step motor task. In the first step of the task, patients could anticipate visual go cues and moved once prompted. In the second step of the task, go cues had a 50% chance of appearing. If cues failed to appear, movements were self-initiated. The point process models provide an accurate summary of pathological characteristics under different cued conditions such as bursting, 10-30Hz oscillations, and fluctuations in directional tuning. In particular, the models show that when cues can be anticipated or when patients self-initiate movements (in both cases an internal motor plan is formed prior to movement), pathological neural characteristics are suppressed. In contrast, when cues cannot be anticipated and later appear, there is no suppression of pathological neural characteristics. Consequently, movements deteriorate.
AB - Deep brain stimulation is an effective therapy for Parkinson's disease (PD) that has enabled microelectrode recordings from single-unit cells in the sub-thalamic nucleus (STN) of the basal ganglia. This rare data is important to develop detailed characterizations of spiking activity to understand the pathophysiology of PD. Despite the point process nature of neuronal spiking activity, point process (PP) methods are not used to analyze these recordings. Therefore, we develop PP models using the generalized linear method to characterize spiking activity in 28 STN neurons in 7 PD patients executing a two-step motor task. In the first step of the task, patients could anticipate visual go cues and moved once prompted. In the second step of the task, go cues had a 50% chance of appearing. If cues failed to appear, movements were self-initiated. The point process models provide an accurate summary of pathological characteristics under different cued conditions such as bursting, 10-30Hz oscillations, and fluctuations in directional tuning. In particular, the models show that when cues can be anticipated or when patients self-initiate movements (in both cases an internal motor plan is formed prior to movement), pathological neural characteristics are suppressed. In contrast, when cues cannot be anticipated and later appear, there is no suppression of pathological neural characteristics. Consequently, movements deteriorate.
UR - http://www.scopus.com/inward/record.url?scp=77950819938&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77950819938&partnerID=8YFLogxK
U2 - 10.1109/CDC.2009.5399938
DO - 10.1109/CDC.2009.5399938
M3 - Conference contribution
SN - 9781424438716
SP - 7716
EP - 7722
BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
ER -