Attention Training for Long COVID

(LongCovAtten Trial)

Overseen by Elliot Roth, MD

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Shirley Ryan AbilityLab

Disqualifiers: Neurological conditions, Severe depression, others

No Placebo Group

Trial Summary

What is the purpose of this trial?

This study is to find out if the Attention Processing Training program is a potential treatment for brain fog symptoms, reported by people with Long-Covid. Also investigating the feasibility of completing this program virtually.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It might be best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment Attention Training and Multimodal Affect Recognition Training (MMART) combined with Attention Training for Long COVID?

Research shows that Attention Training Technique (ATT) can improve attention control and flexibility, which may help with attention issues in Long COVID. Additionally, training in emotion regulation has been shown to enhance psychological well-being and resilience, suggesting potential benefits for emotional and cognitive challenges faced by Long COVID patients. ^{1 2 3 4 5}

Is Attention Training safe for humans?

Attention Training, including techniques like the Attention Training Technique (ATT) and Online Contingent Attention Training (OCAT), has been studied in healthy participants and those with conditions like depression and anxiety. These studies suggest that the training is generally safe, as no adverse effects were reported in the research. ^{2 3 5 6 7}

How does the Attention Training treatment for Long COVID differ from other treatments?

The Attention Training treatment for Long COVID is unique because it combines Multimodal Affect Recognition Training (MMART) with attention strategies to help patients recognize and interpret emotions from different sources, like audio and visual cues. This approach is novel as it focuses on improving cognitive and emotional processing, which is not typically addressed by standard treatments for Long COVID. ^{8 9 10 11 12}

Research Team

Shira Cohen-Zimerman, PhD

Principal Investigator

Shirley Ryan AbilityLab

Elliot Roth, MD

Principal Investigator

Shirley Ryan AbilityLab

Eligibility Criteria

This trial is for adults aged 18-65 who have had COVID-19 and are experiencing 'brain fog' that affects daily life. Participants must have attentional deficits, be able to use a keyboard, consent independently, and communicate in English. Those with severe depression, recent chemotherapy or radiation treatment, active substance abuse, or certain pre-existing neurological conditions cannot join.

Inclusion Criteria

I have attention issues confirmed by specific tests.

I've had memory or thinking problems since getting COVID-19.

I am between 18 and 65 years old.

Exclusion Criteria

I have been diagnosed with severe depression.

I have had chemotherapy or radiation in the past 6 months.

Active substance abuse

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive either the Attention Training or Music Program intervention for 4 weeks

4 weeks

Hybrid model: in-person, remote, and independent sessions

Follow-up

Participants are monitored for changes in attention test scores and completion of study tasks

2 years

Optional Attention Training

Participants in the Delayed Attention Training group have the option to complete the Attention Training after initial assessments

4 weeks

Treatment Details

Interventions

• Attention Training (Behavioural Intervention)

Trial Overview The study tests if an Attention Processing Training program can help improve the brain fog symptoms associated with Long-Covid. It also examines whether this training can be effectively completed online.

Participant Groups

Group I: Music Program Experimental Treatment 1 Intervention

This group will receive an enhanced music experience. They will listen to pre determined music for 30 minutes per day, 5 days a week, for 4 weeks (10 hours total over 4 weeks). This will be delivered in a hybrid model that will combine, in person, remote, and independent sessions, similar to the Attention Training group. Once they complete the music program, they will have the option to complete the Attention Training.

Group II: Attention Training Experimental Treatment 1 Intervention

The computer based APT-3 intervention will be delivered in a hybrid model that will combine in-person therapy sessions at Shirley Ryan AbilityLab and practice sessions which will be completed remotely. The dosing of each intervention training will be 30 minutes per day, 5 days a week, for 4 weeks (10 hours total over 4 weeks). The difficulty of the tasks in both interventions will increase progressively as the participants improve in their skills. APT-3 treatment will be administered by a trained and certified speech-language pathologist.

Group III: Delayed Attention Training Active Control 1 Intervention

This group will not be provided any program for the initial 4 weeks. After they complete the week 5 assessments, they will have the option to complete the Attention Training.

Who Is Running the Clinical Trial?

Shirley Ryan AbilityLab

Lead Sponsor

Trials

212

Recruited

17,900+

Dr. Pablo Celnik

Shirley Ryan AbilityLab

Chief Executive Officer since 2023

MD from University of Buenos Aires Faculty of Medical Sciences

Dr. James Sliwa

Shirley Ryan AbilityLab

Chief Medical Officer since 2021

DO

Findings from Research

Neurofeedback training using real-time fMRI allowed 15 healthy participants to learn to control the activity levels between the sustained attention network (SAN) and the default-mode network (DMN), leading to improved self-regulation of attention.

While participants showed some improvement in sustained attention after training, the effects were temporary and similar to practice effects, indicating that further research is needed to establish the long-term efficacy of this non-invasive attention training method.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Network-based fMRI-neurofeedback training of sustained attention. Pamplona, GSP., Heldner, J., Langner, R., et al.[2021]

A 20-day training program focused on emotional working memory significantly improved the efficiency of the brain's frontoparietal network, which is crucial for both working memory and affective cognitive control.

Participants who underwent this emotional working memory training showed enhanced emotion regulation abilities compared to those who received placebo training, indicating that this approach could be beneficial in clinical and occupational settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Training the emotional brain: improving affective control through emotional working memory training. Schweizer, S., Grahn, J., Hampshire, A., et al.[2023]

The Attention Training Technique (ATT) significantly improved attentional performance in healthy participants, as evidenced by faster reaction times in tasks like dichotic listening and attentional bias after both two and four doses of ATT.

These results suggest that ATT enhances attentional flexibility, which could potentially benefit individuals with psychiatric disorders such as depression and anxiety, making it a promising therapeutic tool.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Shifting Instead of Drifting - Improving Attentional Performance by Means of the Attention Training Technique. Barth, V., Heitland, I., Kruger, THC., et al.[2023]

A pilot intervention training military veterans in emotion regulation strategies (Focused Attention and Cognitive Reappraisal) over 5-8 weeks showed significant improvements in psychological well-being, including enhanced working memory and self-efficacy.

Neuroimaging results indicated that the training led to changes in brain connectivity, suggesting that resilience and emotional well-being can be developed through targeted training, with observable effects on brain function.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Cultivating Affective Resilience: Proof-of-Principle Evidence of Translational Benefits From a Novel Cognitive-Emotional Training Intervention. Dolcos, S., Hu, Y., Williams, C., et al.[2021]

Intensive working memory (WM) training can lead to improvements in cognitive functions beyond the training task, including gains in fluid intelligence, as shown in a study with 45 participants.

Training with emotional material specifically enhances the ability to control emotional information, indicating that the type of material used in brain-training is crucial for achieving transferable cognitive benefits.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Extending brain-training to the affective domain: increasing cognitive and affective executive control through emotional working memory training. Schweizer, S., Hampshire, A., Dalgleish, T.[2022]

Selective attention to positive information can help regulate emotions, suggesting that attention is a valuable tool for improving emotional experiences.

Training in attentional regulation, particularly through meditative practices, has shown promise in enhancing emotional well-being, indicating that attention can be developed as a skill for better emotion management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Fixing our focus: training attention to regulate emotion. Wadlinger, HA., Isaacowitz, DM.[2022]

The novel online contingent attention training (OCAT) was tested in two studies involving 64 undergraduates and 58 individuals during stressful periods, showing significant improvements in attention towards negative information and interpretation biases compared to a sham-control group.

Participants who underwent OCAT experienced reductions in rumination and anxiety symptoms, indicating that this training may effectively enhance emotion regulation and help individuals cope with major stressors.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Online Contingent Attention Training (OCAT): transfer effects to cognitive biases, rumination, and anxiety symptoms from two proof-of-principle studies. Blanco, I., Boemo, T., Martin-Garcia, O., et al.[2023]

The proposed visual attention convolutional neural network (VACNN) significantly improves speech emotion recognition (SER) performance across different datasets, achieving overall accuracies of 83.33% for RAVDESS, 86.92% for EmoDB, and 75.00% for SAVEE.

By utilizing a bag of visual words (BOVW) to enhance feature extraction, the VACNN method outperformed existing state-of-the-art cross-corpus SER approaches by 7.73% on RAVDESS, 15.12% on EmoDB, and 2.34% on SAVEE, demonstrating its effectiveness in generalizing across different emotional speech datasets.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Fusing Visual Attention CNN and Bag of Visual Words for Cross-Corpus Speech Emotion Recognition. Seo, M., Kim, M.[2021]

The proposed dyadic fusion network improves emotion recognition in communication by using an attention mechanism to efficiently fuse different types of data, achieving 3.8%-7.5% higher accuracy than previous models on the IEMOCAP and MELD datasets.

By transforming the annotation process into a regression problem, the model effectively addresses label disagreements, leading to more accurate emotion predictions and better utilization of the available data.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mutual Correlation Attentive Factors in Dyadic Fusion Networks for Speech Emotion Recognition. Gu, Y., Lyu, X., Sun, W., et al.[2020]

The proposed hierarchical multimodal architecture effectively classifies sentiment and emotion from both text and audio data, addressing challenges in feature extraction and modality interaction.

This model outperforms existing state-of-the-art methods on published datasets and provides visual interpretability through synchronized attention across modalities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multimodal Affective Analysis Using Hierarchical Attention Strategy with Word-Level Alignment. Gu, Y., Yang, K., Fu, S., et al.[2023]

The study presents a comprehensive audio-visual dataset of 7,442 clips featuring emotional expressions from 91 actors, which allows for the analysis of how emotions are conveyed through both facial and vocal cues.

Recognition of emotions is highest when both audio and visual cues are combined (63.6%), with visual-only recognition being more effective than audio-only, highlighting the importance of multi-modal cues in accurately perceiving emotions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset. Cao, H., Cooper, DG., Keutmann, MK., et al.[2020]

The study successfully combined facial video, audio, and lexical features to create more accurate affect estimators during conversations, significantly outperforming the baseline method in recognizing emotional states.

Using a particle filtering approach to integrate these modalities resulted in a correlation performance of 0.344 and 0.280 for continuous and word-level affect recognition, respectively, indicating a robust method for estimating emotions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering. Savran, A., Cao, H., Shah, M., et al.[2021]

References

1. United States pubmed.ncbi.nlm.nih.gov

Network-based fMRI-neurofeedback training of sustained attention. [2021]

2. United States pubmed.ncbi.nlm.nih.gov

Training the emotional brain: improving affective control through emotional working memory training. [2023]

3. Switzerland pubmed.ncbi.nlm.nih.gov

Shifting Instead of Drifting - Improving Attentional Performance by Means of the Attention Training Technique. [2023]

4. Switzerland pubmed.ncbi.nlm.nih.gov

Cultivating Affective Resilience: Proof-of-Principle Evidence of Translational Benefits From a Novel Cognitive-Emotional Training Intervention. [2021]

5. United States pubmed.ncbi.nlm.nih.gov

Extending brain-training to the affective domain: increasing cognitive and affective executive control through emotional working memory training. [2022]

6. United States pubmed.ncbi.nlm.nih.gov

Fixing our focus: training attention to regulate emotion. [2022]

7. England pubmed.ncbi.nlm.nih.gov

Online Contingent Attention Training (OCAT): transfer effects to cognitive biases, rumination, and anxiety symptoms from two proof-of-principle studies. [2023]

8. Switzerland pubmed.ncbi.nlm.nih.gov

Fusing Visual Attention CNN and Bag of Visual Words for Cross-Corpus Speech Emotion Recognition. [2021]

9. United States pubmed.ncbi.nlm.nih.gov

Mutual Correlation Attentive Factors in Dyadic Fusion Networks for Speech Emotion Recognition. [2020]

10. United States pubmed.ncbi.nlm.nih.gov

Multimodal Affective Analysis Using Hierarchical Attention Strategy with Word-Level Alignment. [2023]

11. United States pubmed.ncbi.nlm.nih.gov

CREMA-D: Crowd-sourced Emotional Multimodal Actors Dataset. [2020]

12. United States pubmed.ncbi.nlm.nih.gov

Combining Video, Audio and Lexical Indicators of Affect in Spontaneous Conversation via Particle Filtering. [2021]