Concept

Pramipexole

Related publications (8)

The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...

EPFL2020

Purpose of review Mild cognitive impairment (MCI) is a comorbid factor in Parkinson's disease. The aim of this review is to examine the recent neuroimaging findings in the search for Parkinson's disease MCI (PD-MCI) biomarkers to gain insight on whether MC ...

Lippincott, Williams & Wilkins2015

, ,

Mitochondria are highly dynamic, multifunctional organelles. Aside from their major role in energy metabolism, they are also crucial for many cellular processes including neurotransmission, synaptic maintenance, calcium homeostasis, cell death, and neurona ...

2012

Time-dependent alterations of peripheral immune parameters after nigrostriatal dopamine depletion in a rat model of Parkinson's disease

Raphaël Doenlen

Dysfunction of the central dopaminergic system is associated with neurodegenerative disorders and mental illnesses such as Parkinson's disease and schizophrenia. Patients suffering from these diseases were reported to exhibit altered immune functions compa ...

2009

The ability of the central nervous system to form motor memories, a process contributing to motor learning and skill acquisition, decreases with age. Dopaminergic activity, one of the mechanisms implicated in memory formation, experiences a similar decline ...

Wiley-Blackwell2005

Gene transfer techniques for the delivery of GDNF in Parkinson's disease

Patrick Aebischer

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor disturbances caused by an alteration of the dopaminergic nigrostriatal system. Current symptomatic treatments for PD include dopaminergic drug administration, deep brain stimul ...

2000

Adaptive tracking of linear time-variant systems by extended RLS algorithms

Ali H. Sayed

We exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms of the extended RLS algorithm are considered: one pertaining to a system identif ...

Institute of Electrical and Electronics Engineers1997

In this paper we exploit the one-to-one correspondences between the recursive least-squares (RLS) and Kalman variables to formulate extended forms of the RLS algorithm. Two particular forms are considered, one pertaining to a system identification problem ...

1995

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