Clinical trial NCT05732649: Improving Visual Perception and Visuo-motor Learning With Neurofeedback of Brain Network Interaction.
Official title: Improving Visual Perception and Visuo-motor Learning With Neurofeedback of Brain Network Interaction.
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Healthy
Lead sponsor: Insel Gruppe AG, University Hospital Bern
Sponsor class: OTHER
Collaborators: name: University of Bern
First posted: 2023-02-17
Enrollment: 65
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: FACTORIAL
Intervention model description: In Experiment 1, to disentangle which is the neurofeedback modality that most efficiently modulates brain connectivity, the investigators will compare auditory, tactile, or both modalities in a within subject design.

In Experiment 2, to investigate whether enhanced brain connectivity at visual areas through real-time neurofeedback can boost visuo-motor learning, the investigators will compare Group A (active) to Group B (first control) and C (second control) in a between subjects design.
Primary purpose: TREATMENT

Brief summary: Neuroscience has long focused on understanding brain activity during task performance. As a result, current training methods aim to maximize brain activation during a trained task. However, new evidence shows that this may not be an efficient way to go. Human subjects achieve maximum performance only when the brain network is in a state of high spontaneous interaction and communication between brain regions before training or, in other words, in a state of high "network communication." In this case, minimal effort is required during the task. This requires new learning strategies aimed at inducing higher network communication prior to task execution. The investigators have previously shown that healthy people can learn to increase network communication of motor areas (i.e., the areas that control movement) when they receive real-time feedback on their current activity, which is known as neurofeedback. In neurofeedback, subjects receive continuous feedback about the state of their brain activity in a present moment. Through this feedback, they can learn to change their own brain activity.

The aim of the present study is to validate neurofeedback as a new treatment approach for inducing high network communication at rest (i.e., when participants are not engaged in a task), and to test whether this heightened network communication can enhance visual perception and motor learning.

Detailed description: As the investigators have seen in a pilot study, participants are unable to improve the network communication of visual brain regions (i.e., regions that process light stimuli) through neurofeedback when the feedback is perceived with the eyes. Therefore, the goal of Experiment 1 is to find an alternative form of feedback through which participants can efficiently increase network communication. Specifically, participants will receive neurofeedback in the form of a sound, a vibration on the skin, or both. For neurofeedback as sound, the investigators will use relaxing sounds which have previously been found to enhance network communication. For neurofeedback as vibration, electrical or vibrotactile stimulators will stimulate both hands and feet, as previous research has found a positive effect on brain network communication. The sensory stimulation intensity will be modulated based on the current level of network communication between the target brain area and the rest of the brain. Thus, greater communication leads to reduced feedback intensity. The idea is that subjects learn to maintain states of high communication without sensory feedback. Subjects will receive the instruction to lower the feedback level without indication of any particular strategy of mental imagery, as the investigators have previously observed that no specific mental imagery task is able to enhance alpha-band FC without feedback. Finally, to explore effects on the behavioral level, the investigators will additionally assess visual perception at the beginning and at the end of each session, similarly as in a previous study.

In Experiment 2, the neurofeedback modality from Experiment 1 is adopted to test whether increasing network communication through neurofeedback can lead to improved visuo-motor learning. Visuo-motor learning will be measured with the mirror-drawing task because the investigators have evidence for feasibility from a previous study and because it represents a good model for re-learning as needed in clinics.

In both experiments, participants will undergo magnetic resonance imaging (MRI). This MRI will increase the precision of neurofeedback.

Eligibility criteria: Inclusion Criteria:

* Signed informed consent
* Age at least 18 years old
* Normal or corrected-to-normal vision
* No neurological or psychiatric diseases
* No regular consumption of benzodiazepines or neuroleptics

Exclusion Criteria:

* Any surgical intervention to the brain
* Drug or alcohol abuse
* Presence of non-MRI safe metal in the body

Primary outcomes:
measure: Changes in network communication
timeFrame: Alpha-band FC will be measured using EEG for 10 minutes (min) before neurofeedback, for ca. 20 min during neurofeedback, and for 10 min after neurofeedback.
Secondary outcomes:
measure: Visual perception
timeFrame: The visual perception task will be given at the start of each session. Then, after 10 min EEG, ca. 20 min neurofeedback, and 10 min EEG the task will be repeated.
measure: Visuo-motor learning
timeFrame: A pre-test of 5 min in the mirror-drawing task will be obtained after 10 min EEG and 20 min neurofeedback. Then, after 20 min of training in the task, a post-test of 5 min will be taken.
Other outcomes:
Locations:
city: Bern
country: Switzerland
facility: Division of Neurorehabilitation, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
Study officials:
affiliation: Division of Neurorehabilitation, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
name: Adrian Guggisberg, Prof. Dr.
role: PRINCIPAL_INVESTIGATOR
References:
citation: Guggisberg AG, Honma SM, Findlay AM, Dalal SS, Kirsch HE, Berger MS, Nagarajan SS. Mapping functional connectivity in patients with brain lesions. Ann Neurol. 2008 Feb;63(2):193-203. doi: 10.1002/ana.21224.
citation: Guggisberg AG, Dalal SS, Zumer JM, Wong DD, Dubovik S, Michel CM, Schnider A. Localization of cortico-peripheral coherence with electroencephalography. Neuroimage. 2011 Aug 15;57(4):1348-57. doi: 10.1016/j.neuroimage.2011.05.076. Epub 2011 Jun 7.
citation: Dubovik S, Pignat JM, Ptak R, Aboulafia T, Allet L, Gillabert N, Magnin C, Albert F, Momjian-Mayor I, Nahum L, Lascano AM, Michel CM, Schnider A, Guggisberg AG. The behavioral significance of coherent resting-state oscillations after stroke. Neuroimage. 2012 May 15;61(1):249-57. doi: 10.1016/j.neuroimage.2012.03.024. Epub 2012 Mar 13.
citation: Paszkiel S, Dobrakowski P, Lysiak A. The Impact of Different Sounds on Stress Level in the Context of EEG, Cardiac Measures and Subjective Stress Level: A Pilot Study. Brain Sci. 2020 Oct 13;10(10):728. doi: 10.3390/brainsci10100728.
citation: Freyer F, Reinacher M, Nolte G, Dinse HR, Ritter P. Repetitive tactile stimulation changes resting-state functional connectivity-implications for treatment of sensorimotor decline. Front Hum Neurosci. 2012 May 23;6:144. doi: 10.3389/fnhum.2012.00144. eCollection 2012.
citation: Mottaz A, Solca M, Magnin C, Corbet T, Schnider A, Guggisberg AG. Neurofeedback training of alpha-band coherence enhances motor performance. Clin Neurophysiol. 2015 Sep;126(9):1754-60. doi: 10.1016/j.clinph.2014.11.023. Epub 2014 Dec 6.
citation: Allaman L, Mottaz A, Guggisberg AG. Disrupted resting-state EEG alpha-band interactions as a novel marker for the severity of visual field deficits after brain lesion. Clin Neurophysiol. 2021 Sep;132(9):2101-2109. doi: 10.1016/j.clinph.2021.05.029. Epub 2021 Jun 28.
citation: Manuel AL, Guggisberg AG, Theze R, Turri F, Schnider A. Resting-state connectivity predicts visuo-motor skill learning. Neuroimage. 2018 Aug 1;176:446-453. doi: 10.1016/j.neuroimage.2018.05.003. Epub 2018 May 4.
citation: Allaman L, Mottaz A, Kleinschmidt A, Guggisberg AG. Spontaneous Network Coupling Enables Efficient Task Performance without Local Task-Induced Activations. J Neurosci. 2020 Dec 9;40(50):9663-9675. doi: 10.1523/JNEUROSCI.1166-20.2020. Epub 2020 Nov 6.