Breathe to Relax updated with Self-Association Task

In my prior post Extending Antidepressant Effects of Ketamine with an Implicit Self-Association Task I referenced a study that observed a prolonging of ketamine’s antidepressant effects following an “automated self-association training” task. I developed a similar verbal self-association task and published it at https://cdn.coltongrubbs.com/asat/.

This verbal self-association task, although functional, has some clear limitations, including a “boring” and bland user interface and a mundane, repetitive task. I sought a way to implement the verbal self-association task in a more engaging and practical manner.

As a result, I have updated my app Breathe to Relax: Guided Breathing App to include verbal self-association during guided breathing exercises. The previous version would also display positive words, such as “Smile” and “Happy”. But when you listen to auditory affirmations, you don’t simply hear positive words, but also “I am” or “you are“. This way, you learn to associate the positive word with your self overtime. Now, Breathe to Relax will display “I” before the onset of each positive word. And it displays “I” for as little as 15ms (implicit/unconscious) up to 750ms (explicit/conscious).

Breathe to Relax combines the verbal self-association task with engaging guided breathing exercises accompanied by detailed animated backgrounds, relaxing background audio, numerous breathing methods, vocal affirmations, and full user customization. It is entirely free to download, with no advertisements or in-app purchases.

3D Neurofeedback Application

By combining neurofeedbacklab with Unity game engine, I created a 3D neurofeedback application that streams EEG data from a Muse 2 commercial EEG headset and outputs real-time feedback to a 3D application.

The intensity and volume of the fire corresponds to brain oscillations within the theta (3.5-6.5Hz) frequency range at AF7. This frequency range and location was selected based upon findings in the study Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation – PMC (nih.gov). It is thought that frontal theta oscillations are inversely correlated with default mode network (DMN) activation and that increasing these oscillations may improve focused-attention meditation.

Although a viable proof-of-concept, neurofeedback has a long way to go (in my opinion) before it is ready for widespread adaptation among everyday people. My primary concern about neurofeedback is an overemphasis on select frequencies and less emphasis on the actual task participants engage in during neurofeedback. In the video above, the real-time feedback of the fire may help train frontal theta oscillations and even increase baseline frontal theta activity with practice. However, how this transfers to real-world improvements in cognition and well-being is still a significant point of controversary. The training of focused-attention meditation is promising in that it may improve cognition by orchestrating domain-general cognitive and attentional networks within the brain.

A more practice application of neurofeedback may be facilitating application of emotion regulation strategies. If these strategies can be taught and even improved upon with practice, the use of neurofeedback could help people learn how to better regulate their emotional state, which may have significant real-world consequences in emotional health and well-being.

Special thanks to Arnaud Delorme for development of neurofeedbacklab, and my friend Kevin for helping me develop the Unity application.

Extending Antidepressant Effects of Ketamine with an Implicit Self-Association Task

Therapeutic Ketamine continues to rise in popularity for treatment of treatment-resistant depression. Recently published articles such as Smiling faces might help the drug ketamine keep depression at bay highlight the importance of environmental intervention following ketamine administration to enhance and/or prolong the antidepressant effects of ketamine.

These articles are based upon a recently published study A Novel, Brief, Fully Automated Intervention to Extend the Antidepressant Effect of a Single Ketamine Infusion: A Randomized Clinical Trial

Reviewing the articles supplementary material covering the intervention used in the study reveals important features, including:

  1. Two of the three tasks participants partook in did not involve photos or smiling faces at all. They involved words only.
  2. The final task that did involve photos always included a picture of the participant. Specifically, a picture of the participant was displayed momentarily before a picture of a random individual with a positive or neutral face was presented. In some trials, a picture of a random face was even followed by a negative face.

As a student of cognitive psychology, I believe a photo of the participant being presented was an essential ingredient to the study (although I cannot know for certain without conducting a separate experiment). The photo used for each participant was highly controlled for as well, with a specific angle, distance, and all with a neutral expression. Looking at smiling faces alone may provoke an acute positive response, but the long-term effects are likely mediated by associating positive faces with one’s self. In other words, changing beliefs we have about ourselves.

I have developed a website employing similar methodology used in the studies first two tasks. It is a self-association training task that may help you change how you think about your self. It should take no more than ten minutes. It only involves briefly displaying words, no images at all.

Here’s the website: https://cdn.coltongrubbs.com/asat/

No data or results are recorded. The server I host on may save your IP address temporarily, like every other website ever, but I can’t even access it. This is purely to serve as a potentially helpful tool for those looking to extend therapeutic ketamine’s effects.

It’s designed to be as simple as possible and works on desktops and mobile devices (you may need to rotate your device into landscape mode for it to display correctly).

Creating ERPs in ERPLAB with Muse EEG Data

This tutorial covers importing EEG data recorded from the Muse headset during an oddball task and using EEGLAB and ERPLAB to filter data and extract event-related potentials revealing the P300 component.

Download the data: https://cdn.coltongrubbs.com/EEG/muse_erp_tutorial_data.xdf

Download the bins: https://cdn.coltongrubbs.com/EEG/oddball_bins.txt

Download the filter: https://cdn.coltongrubbs.com/EEG/SteveLucksFilter.bfil

Brain Stimulator: Visual, Haptic, and Auditory Brainwave Entrainment

The use of brainwave entrainment has increased in popularity following recent articles such as Sensory-Evoked 40-Hz Gamma Oscillation Improves Sleep and Daily Living Activities in Alzheimer’s Disease Patients.

Brain waves are oscillating electrical voltages in the brain that can be recorded from electrical activity on the scalp using electroencephalography (EEG) technology. The most widely recognized brain waves are gamma, beta, alpha, theta, and delta. Frequencies of brainwaves are associated with different states of arousal, emotion, thought, and more. For example, low-frequency delta waves are present during deeper stages of sleep, whereas higher frequency beta waves are most salient during states of arousal.

Brain Stimulator is an Android app I developed that generates rhythms of stimuli to synchronize brainwaves to a specified frequency. For example: By flashing a light 40 times per second (40Hz), 40Hz gamma brainwave activity is enhanced, especially in regions that process visual information. Thus, brainwaves synchronize, or “entrain”, with the flashing light stimulus.

By utilizing hardware on your mobile device, Brain Stimulator can entrain your brainwaves to a specified frequency.

Do not use brain stimulator if you have a history of seizures, epilepsy, or are sensitive to flashing lights/colors. Please read the full terms of service before using this application: https://mindextension.online/terms-of-service/