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Related Concept Videos

Long-term Potentiation01:35

Long-term Potentiation

Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre- and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Long-term Potentiation01:25

Long-term Potentiation

Long-term potentiation, or LTP, is one of the ways by which synaptic plasticity—changes in the strength of chemical synapses—can occur in the brain. LTP is the process of synaptic strengthening that occurs over time between pre and postsynaptic neuronal connections. The synaptic strengthening of LTP works in opposition to the synaptic weakening of long-term depression (LTD) and together are the main mechanisms that underlie learning and memory.
Hebbian LTP
LTP can occur when presynaptic neurons...

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Related Experiment Video

Updated: Jun 17, 2026

Controlling Parkinson's Disease With Adaptive Deep Brain Stimulation
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Prospective Connectomic-Based Deep Brain Stimulation Programming for Parkinson's Disease.

Kevin Hines1, Angela M Noecker2, Anneke M Frankemolle-Gilbert2

  • 1Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania, USA.

Movement Disorders : Official Journal of the Movement Disorder Society
|October 21, 2024
PubMed
Summary
This summary is machine-generated.

Automated connectomic programming (ACP) offers a safe and feasible method for deep brain stimulation (DBS). This novel approach shows promise for improving motor function in Parkinson's disease patients.

Keywords:
Parkinson's diseaseautomated programmingconnectomedeep brain stimulationnetwork

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Area of Science:

  • Neurology
  • Biomedical Engineering
  • Computational Neuroscience

Background:

  • Deep brain stimulation (DBS) efficacy depends on precise lead placement and optimized stimulation parameters.
  • Current DBS programming methods, like monopolar review, are time-consuming for patients and clinicians.

Purpose of the Study:

  • To evaluate the safety and feasibility of automated connectomic DBS programming (ACP).
  • To assess ACP's ability to recruit specific white matter pathways for improved DBS therapy.

Main Methods:

  • Developed patient-specific connectomic DBS models.
  • Utilized a driving-force model to analyze 2400 DBS settings for pathway recruitment.
  • Employed optimization algorithms to maximize therapeutic pathway recruitment and minimize side-effect pathways.
  • Compared ACP-derived settings with standard clinical settings in 13 subjects.

Main Results:

  • Automated connectomic programming (ACP) was tolerated by all patients without adverse effects.
  • In the reprogramming cohort, 3 patients preferred ACP settings, and 1 found them comparable to their current program.
  • The initial ACP cohort demonstrated an average motor improvement of 43.5% on the Unified Parkinson's Disease Rating Scale Part III.

Conclusions:

  • Automated connectomic programming (ACP) is clinically safe and feasible for deep brain stimulation.
  • ACP shows potential for motor improvement in Parkinson's disease, with further optimization possible.
  • Larger studies are needed to refine ACP algorithms and confirm its clinical benefits.