Mark Llewellyn Smith LCSW, BCN, QEEGD
Imagine for a moment your sessions with developmentally traumatized clients. What words come to mind? Challenging? Frustrating? Overwhelming? What if you had a tool that made each session more productive? What if this tool promoted less reactivity, more emotional stability, better sleep, and more flexibility in the way your client reacted to triggers to her past? All this is possible through an intervention that has been hiding in plain sight for the last 50 years called neurofeedback.
But saying neurofeedback helps with trauma is like saying medication helps with illness. Neurofeedback like medication is a big category with many different kinds of interventions. Most “traditional” neurofeedback approaches apply a conditioning paradigm to the client and after several sessions behavioral change begins to take place. Infraslow Neurofeedback Training (ISF) is especially helpful with trauma clients because it is an immediate state altering intervention. The effect is more rapid than other neurofeedback interventions. The client is moved from an uncomfortable affective state to a more focused and relaxed state in session. This is possible due to the behavioral impact of the Infraslow frequencies within the human cerebral cortex.
The infraslow frequencies, defined as < 0.1 Hertz, have been identified in neuroscience as a coordinating rhythm responsible for the organization of neuronal networks that play an integral role in many forms of human behavior. Recently evidence has accumulated that delineates a primary role for the Infraslow Rhythm and physiological systems that include the relationship between the heart and the brain, the coordination of the blood brain barrier, and information flow between the stomach and the brain (Bao et al., 2015; Grooms, 2015; Gudmand-Hoeyer, Timmermann, & Ottesen, 2014; Hashimoto et al., 2015; Hiltunen et al., 2014; Lecci et al., 2017; Tso et al., 2017; Zanatta et al., 2013). It should not be a surprise then that research has also confirmed the Infraslow band’s significance to the Autonomic Nervous System (ANS). This organ system has central significance to human behavior, especially trauma.
The central organ system of the ANS is directed by the Hypothalamus. The earliest exploration of Infraslow frequencies identified their behavioral centrality in the reaction to threat in animal research(Aladjalova, 1957). The Hypothalamus of rabbits slowed down in frequency but increased in amplitude as a response to “wounding.” More recent work has associated these slow processes with hormone concentrations related to the Hypothalamic-Pituitary-Adrenal axis (HPA) in humans. Since the HPA axis maintains basal and stress related homeostasis of the central nervous system, cardiovascular, metabolic, and immune functions; dysregulation of this axis is implicated in many behavioral, circulatory, endocrine/metabolic, and immune disorders. The HPA-axis coordinates the fight, flight or freeze response to threat in mammals. Researchers have noted the similarity of HPA hormone secretions to the Ultradian Rhythm of one to three times per hour (Gudmand-Hoeyer et al., 2014).
This corresponds with the so-called “minimal model” of the HPA-axis that considers the Ultradian Rhythm (Infraslow Rhythms associated with human behavior) an inherent element of the Autonomic Nervous System. In plain terms these slow rhythms are the organizing nexus of the HPA-axis/Autonomic Nervous System. These frequencies correspond to the lowest third of the training band in ISF neurofeedback. The ability to train these slow frequencies in neurofeedback has proven very useful in clinical populations whose salient dysregulation involves the HPA-axis. Operantly conditioning the fear response in PTSD, RAD, anxiety and depression is a useful tool for many of our clients, particularly those who cannot or will not use medication(M. L. Smith, 2013; M. L. Smith, Collura, Ferrara, & de Vries, 2014; M.L. Smith, Leiderman, & de Vries, 2017).
Recent work by Ledoux (LeDoux & Pine, 2017) suggests that the feelings of fear and anxiety are reactions to threat but are not created by it. That is, one can respond to threats in the environment without the feeling of fear or anxiety. This is how elite athletes are able to respond to potentially injurious activity with elegant athletic control that avoids the threat without the affect of anxiety or fear. Conversely, as all therapists are acutely aware, clients may experience fear or anxiety in the absence of an objective threat. This happens because the experience of anxiety and fear are mediated in
different brain circuits than the reaction to fear. There is not one “fear circuit” but in fact there are two. One regulates a physiological reaction to threat and the other determines the affective response. These systems can function independently from one another or in tandem. How they are coupled and decoupled explains “normal” from pathological behavior.
In clinical practice, we use Infraslow neurofeedback to calm the reactivity of the ANS so that traumatized clients are less vulnerable to triggers to their past trauma. But we are also able to help those clients who are Dysautonomic or Alexithymic to become aware of their emotions through the reintegration of limbic and sensory networks in cortex. More recent research has defined the Infraslow frequencies a the “superstructure” of the brain that regulate both the integration within and decoupling between concurrently active neuronal networks(Palva & Palva, 2012). We are able to optimize the interplay between the two fear circuits with the processes of the larger limbic and sensory networks. So for instance, a recent client was able to identify the slight facial flush, chilling hands, and butterflies in her stomach as the first stages of low level anxiety in a cue to her past trauma. This allowed her to function successfully in a high stress atmosphere. In the past, largely unaware of these early, subtle cues, she would only become aware of her developing response to threat as she succumbed to a panic attack.
Aladjalova, N. A. (1957). Infra-slow rhythmic oscillations of the steady potential of the cerebral cortex. Nature, 179(4567), 957-959.
Bao, Y., Pöppel, E., Wang, L., Lin, X., Yang, T., Avram, M., . . . Zhou, B. (2015). Synchronization as a biological, psychological and social mechanism to create common time: A theoretical frame and a single case study. PsyCh Journal, 4(4), 243-254. doi:10.1002/pchj.119
Grooms, J. K. (2015). Examining the relationship between BOLD fMRI and infraslow EEG signals in the resting human brain. (M.S. Masters), Georgia Institute of Technology.
Gudmand-Hoeyer, J., Timmermann, S., & Ottesen, J. T. (2014). Patient-specific modeling of the neuroendocrine HPA-axis and its relation to depression: Ultradian and circadian oscillations. Mathematical Biosciences(0). doi:https://dx.doi.org/10.1016/j.mbs.2014.07.013
Hashimoto, T., Kitajo, K., Kajihara, T., Ueno, K., Suzuki, C., Asamizuya, T., & Iriki, A. (2015). Neural correlates of electrointestinography: Insular activity modulated by signals recorded from the abdominal surface. Neuroscience, 289(0), 1-8. doi:https://dx.doi.org/10.1016/j.neuroscience.2014.12.057
Hiltunen, T., Kantola, J., Abou Elseoud, A., Lepola, P., Suominen, K., Starck, T., . . . Palva, J. M. (2014). Infra-Slow EEG Fluctuations Are Correlated with Resting-State Network Dynamics in fMRI. The Journal of Neuroscience, 34(2), 356-362. doi:10.1523/jneurosci.0276-13.2014
Lecci, S., Fernandez, L. M. J., Weber, F. D., Cardis, R., Chatton, J.-Y., Born, J., & Lüthi, A. (2017). Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep. Science Advances, 3(2). doi:10.1126/sciadv.1602026
LeDoux, J. E., & Pine, D. S. (2017). Using Neuroscience to Help Understand Fear and Anxiety: A Two-System Framework. American Journal of Psychiatry, 0(0), appi.ajp.2016.16030353. doi:doi:10.1176/appi.ajp.2016.16030353
Palva, J. M., & Palva, S. (2012). Infra-slow fluctuations in electrophysiological recordings, blood-oxygenation-level-dependent signals, and psychophysical time series. Neuroimage, 62(4), 2201-2211. doi:https://dx.doi.org/10.1016/j.neuroimage.2012.02.060
Smith, M. L. (2013). Infra-slow fluctuation training; On the down-low in neuromodulation. Neuroconnections, Fall.
Smith, M. L., Collura, T. F., Ferrara, J., & de Vries, J. (2014). Infra-slow fluctuation training in clinical practice: A technical history. NeuroRegulation, 1(2), 187-207. doi:doi:10.15540/nr.1.2.187
Smith, M. L., Leiderman, L., & de Vries, J. (2017). Infra-slow fluctuation (ISF) for autism spectrum disorders. In T. F. Collura & J. A. Frederick (Eds.), Handbook of clinical QEEG and neurotherapy.