Functional connectivity measures for the prediction of motor learning ability

Functional connectivity measures for the prediction of motor learning ability - TAP-PREDICT

Status

Active, not recruiting

Phases

Unknown

Study type

Interventional

Source

DRKS

Registry ID

DRKS00015158

Enrollment

Registered

2018-07-31

Start date

2018-08-24

Completion date

Unknown

Last updated

2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

U50.0

Interventions

Group 1: 50 healthy volunteers Before and after learning the 10-Finger Tipping System (1 week program with 2x30 minutes training sessions per day), a functional MRI is performed (including Resting sta

Eligibility

Sex/Gender

All

Age

18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Healthy adult between the ages of 18 and 80 years without previous knowledge in the 10 finger writing system

Exclusion criteria

Exclusion criteria: Contraindications for MRI Measurements, experiences with the 10 Finger writing system

Design outcomes

Primary

Measure	Time frame
Predicting long-term learning success through short-term connectivity changes in the brain during a 12-minute motor learning task. The connectivity changes are calculated as the difference between two resting state measurements taken before and after the short-term learning paradigm. The long-term learning success is measured by the speed and error rate in the final test as well as the learning rate over time in the 10-finger writing system. The primary endpoint is thus the predictive value of the difference of the functional connectivity in the motor system before. after the Sequence Learning task on the long-term learning success.	—

Measure

Time frame

Predicting long-term learning success through short-term connectivity changes in the brain during a 12-minute motor learning task. The connectivity changes are calculated as the difference between two resting state measurements taken before and after the short-term learning paradigm. The long-term learning success is measured by the speed and error rate in the final test as well as the learning rate over time in the 10-finger writing system. The primary endpoint is thus the predictive value of the difference of the functional connectivity in the motor system before. after the Sequence Learning task on the long-term learning success.

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Secondary

Measure	Time frame
• Correlation of long-term learning success with short-term behavioral learning success • Correlation of long-term learning success with age • Correlation of long-term learning success with microvascular changes measured as vascular resistance index in duplex and white matter lesions on MRI • Identification of target regions in the sensorimotor network with high and low predictive value for long-term learning ability • Correlation of long-term learning success with the BrainAge score of structural imaging • Correlation of long-term learning success with structural changes between longitudinal measurements • Correlation of long-term learning success with functional connectivity changes in the sensorimotor network between longitudinal measurements over one week • Correlation of long-term learning success with connectivity changes in the MEG	—

Measure

Time frame

• Correlation of long-term learning success with short-term behavioral learning success • Correlation of long-term learning success with age • Correlation of long-term learning success with microvascular changes measured as vascular resistance index in duplex and white matter lesions on MRI • Identification of target regions in the sensorimotor network with high and low predictive value for long-term learning ability • Correlation of long-term learning success with the BrainAge score of structural imaging • Correlation of long-term learning success with structural changes between longitudinal measurements • Correlation of long-term learning success with functional connectivity changes in the sensorimotor network between longitudinal measurements over one week • Correlation of long-term learning success with connectivity changes in the MEG

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Countries

Germany

Contacts

Public ContactChristiane Dahms

Jena, Universitätsklinik, Abteilung für Neurologie

christiane.dahms@med.uni-jena.de03641 9323450

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026