Improving Dysregulated Neural Networks With EEG-neurofeedback
- Conditions
- Chronic PainPtsd
- Interventions
- Device: Neurofeedback
- Registration Number
- NCT06587919
- Lead Sponsor
- University of Southern Denmark
- Brief Summary
Comorbid PTSD in the context of chronic pain rehabilitation is a major problem. The lack of effective and efficient methods that can be integrated into current practice is needed. The current recommended treatments for PTSD leave room for supplementary approaches to achieve symptom reduction. PTSD is characterized by specific alterations of neural activity, and the DMN is known to be involved in this. Neurofeedback is the most current approach to altering neural activity patterns towards a norm pattern found in healthy subjects.
The aim of the present study is to assess whether EEG neurofeedback compared to an active control group receiving EEG sham neurofeedback is effective in alleviating PTSD symptoms and pain intensity in patients with chronic pain and comorbid PTSD after MVCs.
- Detailed Description
Prevalence and current treatment of PTSD PTSD is a debilitating mental health disorder arising from exposure to traumatic events such as war, motor vehicle accidents, crimes, and other events, threatening the lives of oneself or others involved (American Psychiatric Association, 2013).
The current recommended treatments for PTSD victims consist of psychotherapies and pharmacological interventions (NICE, 2005). Although 60% of PTSD patients experience improvements from a variety of trauma-focused cognitive behavior therapies (Bradley et al., 2005), and pharmacotherapies (Ipser et al., 2006), as many as 40% of PTSD patients do not experience symptom relief from existent therapies. Thus, the development of novel treatment alternatives is needed.
Injuries related to motor vehicle crashes (MVC) are one of the major causes of morbidity and mortality in the Western world (Peden et al., 2004). While physical injury and pain are the primary symptoms after MVC, between 20-40% also experience severe posttraumatic stress disorder symptoms (Craig et al., 2016). What is less known is that psychological distress is higher among those who have sustained a minor injury, such as whiplash injury, compared to more severe injuries, such as spinal cord injury. In particular PTSD symptoms such as hyperarousal are common after MVCs and an important mechanism in the development of chronic pain and disability after MVCs (Buitenhuis et al., 2006; Sterling et al., 2012; Ravn et al., 2018). With the mutual maintenance theory (Sharp \& Harvey, 2001), it is suggested that pain and PTSD are mutually maintaining conditions. Indeed, PTSD is highly prevalent in the context of chronic pain rehabilitation of victims of MVCs with about 20% experiencing severe PTSD symptoms (Siqveland et al., 2017). Those with high levels of PTSD symptoms are known to experience higher levels of pain, disability, and distress. Unfortunately, targeting PTSD in pain rehabilitation is uncommon and the few existing trials that have tried to target comorbid PTSD and pain have not been sufficiently effective in alleviating pain and PTSD symptoms (Andersen et al., 2017; Andersen et al., 2020; Andersen et al., 2021). Treatment resistance may be due to dysregulated brain networks that are not sufficiently targeted with traditional psychotherapeutic approaches.
A novel and promising method to target PTSD is source-localized EEG neurofeedback in that this method targets specific neural regions; thus, the treatment can be tailored to the individual patient's symptoms. As the treatment is entirely noninvasive and low-cost, the potential and the feasibility that the neurofeedback method can be employed broadly and that patients can train in between treatment sessions is considerable.
Here, we propose an investigation of the potential of standardized weighted Low-Resolution Tomography EEG neurofeedback training in treatment of comorbid PTSD in chronic pain. Our proposed study investigates the neural mechanisms hypothesized to be involved in neurofeedback training for PTSD patients. By testing, if such training can alter activity in specific target neural regions related to PTSD symptoms in our patient group, the goal is to evaluate the technique as a supplement to current therapies. We compare the active EEG neurofeedback treatment with a placebo control condition receiving sham EEG neurofeedback.
Neurofeedback In its most basic form, neurofeedback is a non-invasive technique, in which a person is trained to regulate his/her own neural activity. For psychological symptoms which are linked to dysregulated neural activity, neurofeedback may offer symptom alleviation by teaching patients to regulate relevant activity patterns themselves (Hammond, 2011). By rewarding the person whenever the neural activity changes in a desired direction, the activity can be regulated or modulated. The pivotal mechanism is thus operant conditioning: A desired change in neural activity is followed by a rewarding stimulus as positive reinforcement. This reward may be appetitive to the patient, or, the reward may be in the form of a signal notifying that the training criterion is met, which in itself may be rewarding for a patient seeking symptom alleviation (Hammond, 2011; Thatcher et al., 2015).
Since the 1990s, a number of studies have reported positive treatment outcomes for neurofeedback in psychiatric disorders (Kluetsch et al., 2014; Othmer \& Othmer, 2009; Schoenberg \& David, 2014; Simkin et al., 2014) establishing the value of neurofeedback interventions within mainstream psychiatry. Our proposed study aims at systematically registering the mechanisms involved in neurofeedback when applied to patients with comorbid PTSD and chronic pain. By doing so, we aim at furthering our understanding of the neural structures involved in posttraumatic stress symptoms and chronic pain and how neurofeedback may alter their activity patterns. This knowledge will enable the design of a specific and optimized neurofeedback training protocol for patients with PTSD and chronic pain after MVCs.
In recent decades, large-scale studies of EEG in healthy subjects across all ages and genders have been conducted to create knowledge on the characteristics of the human EEG. Such data have been processed and stored in databases making a wide range of EEG parameters available as norm data (Thatcher et al., 2003). EEG in a patient can thus be analyzed in terms of deviations from such norms. Deviations along some EEG parameters, which may be hypothesized to be involved in the targeted symptoms, can then be trained via neurofeedback to achieve greater congruence with relevant EEG parameters in healthy subjects (Thatcher et al., 2015).
Traditional neurofeedback uses one or two electrodes on the head to increase or decrease activity within a particular frequency band. Standardized Weighted Low Resolution Electromagnetic Tomography (swLORETA) is a mathematical technique to analyze the three-dimensional distribution of intracortical brain electrical activity based on surface EEG recordings. The computation enables imaging of real-time brainwave activity with a spatial resolution of less than one cubic centimeter as it divides the brain into over 12,000 voxels or pieces; this provides localization similar to that of fMRI while preserving the faster temporal resolutions of EEG (Thatcher, 2011, 2013). Thus, while traditional neurofeedback protocols typically utilize one or two electrode sites to train diffuse brainwave frequencies near the outer surface of the brain, source localized NF can more directly target specific brain regions even deeper within the cortex (Krigbaum \& Wigton, 2014; Thatcher et al., 2020). It can also target multiple Brodmann areas simultaneously as well as give feedback on connectivity or communication between different neural sources (coherence and phase relations), enabling the option to train specific neural networks.
In combination, state-of-the-art neurofeedback offers training in deviating neural activity towards a norm mean recorded in healthy subjects, specifically targeting anatomical regions involved in symptoms (Thatcher et al., 2015).
Altered neurocircuitry in PTSD Due to the nature of the diagnostic criteria (American Psychiatric Association, 2013), PTSD is a heterogeneous disorder with symptom levels varying across symptom clusters (Bryant et al., 2015; Galatzer-Levy \& Bryant, 2013). However, a key observation is changes in hyperarousal (Staples et al., 2020) as well as self-referential processing, which refers to information relevant to oneself and is an essential component in cognitive processing (Cox et al., 2014; Foa et al., 1999; Schore and Schore, 2003). Furthermore, PTSD patients may report changes in somatic self-reference and self-perception (Foa et al., 1999).
In recent years, neuroscientific research has shown that many psychiatric disorders can be understood as disturbances within, or, in the relation between three basic, large brain networks (Broyd et al., 2009). The default mode network (DMN) (Raichle et al., 2001), the salience network (SN) (Seeley et al., 2007), and the central executive networks (CEN) (Monsell, 2003) are concerned with self-referential processing, with external, task-related processing and with executive functions respectively (Menon, 2011). Changes in the functioning or connectivity within one network propagate to the remaining two.
Symptoms of disturbed self-referential processing in PTSD have been linked to changes in DMN connectivity (Bluhm et al., 2009; Cisler et al., 2014; Kluetsch et al., 2014; Lanius et al., 2010, 2015). Changes in DMN may further be accompanied by an increase in SN activity, resulting in hyperarousal/heightened threat perception, and a decrease in CEN activity (Patel et al., 2012). Recently, PTSD symptomatology has been shown to be predicted by the level of DMN disturbance (Lanius et al., 2010). Alterations in DMN activity and connectivity are thus strong candidates for neural correlates to altered self-referential processing in PTSD and the symptoms associated with this. Based on this knowledge, a restoration of normal activity in the DMN through neurofeedback has been suggested as a viable supplement to current treatments (Kluetsch et al., 2014; Lanius et al., 2015).
Alterations in DMN activity have also been found in acute and chronic pain states (Alshelz et al., 2017), which may reflect underlying alterations in attentional processes associated with the presence of pain itself as it has been reported that chronic pain patients also display significant attention and mental flexibility deficits. In fact, multiple studies have reported significant changes in DMN function in many chronic pain conditions (Baliki et al., 2008; Baliki et al., 2014; Letzen et al., 2013; Napadow et al., 2012; Tagliazucchi et al., 2010). It has been suggested that the strength of the functional connections between brain regions within the DMN in chronic pain subjects relates to pain rumination, which is a measure of an individual's continuous focus on pain and its potential negative outcomes (Kucyi et al., 2014).
Recruitment & Eligibility
- Status
- ENROLLING_BY_INVITATION
- Sex
- All
- Target Recruitment
- 63
- has finished treatment at Smertecenter Syd.
- is still experiencing pain of more than 4 on the Numeric Ranking Scale (NRS).
- has been exposed to an adverse event that causes continued arousal according to the International Trauma Questionnaire.
- Participants with known neurological disorders will be excluded from participation.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- PARALLEL
- Arm && Interventions
Group Intervention Description Real EEG-NF Neurofeedback 10 EEG based neurofeedback sessions modulating the activity of the default mode network. Sham EEG-NF Neurofeedback 10 sessions of neurofeedback another person's EEG.
- Primary Outcome Measures
Name Time Method Pain intensity rating Before every nf-session and six months after the last session. Average pain intensity during the last day and current pain intensity before beginning the neurofeedback session, will be assessed on an 11-point numeric rating scale (NRS) ranging from 0 (no pain) to 10 (worst imaginable pain)
EEG-power in alpha band Before the first nf-session and after the last session (roughly six weeks later) 37-channel EEG will be recorded, the alpha power seems to indicate cortical activity.
- Secondary Outcome Measures
Name Time Method General QoL Assessed before first nf-session, after five weeks and after seven months. World Health Organization Quality of Life (WHOQOL)-Brief contains questions about how the subject feels in their everyday life, most answers are given on a five-point scale with 1 being worst/least and 5 being best/most.
Trial Locations
- Locations (1)
University of Southern Denmark
🇩🇰Odense, Denmark