Quantifying Self-Regulation: Neuroevolutionary Insights From Precuneus Alpha Modulation via LORETA Neurofeedback

Authors

  • Rex L Cannon Currents, LLC

DOI:

https://doi.org/10.15540/nr.12.2.154

Keywords:

self-regulation, LORETA neurofeedback, emotional equilibrium, Homeostasis, behavioral equilibrium, precuneus, alpha oscillations, neuroplasticity, volumetric studies, neuroevolutionary dynamics

Abstract

Self-regulation (SR) is a vital neurobehavioral capacity orchestrating behavior, physiological equilibrium, and emotional resilience through corticothalamic networks spanning the cortex and thalamus. This study formalizes SR as SR = behavioral equilibrium (BE) / (homeostasis [H] + emotional equilibrium [EE]), where BE captures adaptive responses, H denotes physiological stability, and EE reflects affective harmony, positioning neurofeedback (NFB) as a leading intervention. NFB, encompassing LORETA neurofeedback (LNFB) targeting precuneus alpha and real-time fMRI neurofeedback (rt-fMRI-NFB) modulating blood-oxygen-level-dependent (BOLD) signals, enhances corticothalamic modulation across educational, correctional, clinical, pediatric, and ADHD contexts. Evidence from diverse cohorts validates NFB’s efficacy, with LNFB improving BE (CPT-3,
p < .008) and rt-fMRI-NFB stabilizing EE (BOLD, p < .01), supported by long-term gains in children (Strehl et al., 2017) and adults (Rance et al., 2018). The back-to-front brain focus, rooted in precuneus primacy (~2 Mya), contrasts with historical frontal emphasis post-Phineas Gage. As noted in experimental findings, surface NFB training boosts neural connectivity. Pre- and postprotocols are rare due to subjective reliance, resistance to objective tracking, and resource limits (Hofmann & Smits, 2008). NFB’s standardized protocols (EEG
ICC = .87–.92, BOLD consistency) inspire volumetric MRI studies, advancing SR science across the lifespan.

Author Biography

Rex L Cannon, Currents, LLC

usa

References

Arnone, D., McKie, S., Elliott, R., Thomas, E. J., Downey, D., Juhasz, G., Williams, S. R., Deakin, J. F., & Anderson, I. M. (2012). Increased amygdala responses to sad but not fearful faces in major depression: Relation to mood state and pharmacological treatment. The American Journal of Psychiatry, 169(8), 841–850. https://doi.org/10.1176/appi.ajp.2012.11121774

Bandura, A. (1977). Social learning theory. Prentice Hall.

Bruner, E. (2004). Geometric morphometrics and paleoneurology: Brain shape evolution in the genus Homo. Journal of Human Evolution, 47(5), 279–303. https://doi.org/10.1016/j.jhevol.2004.03.009

Cannon, R. (2014). Parietal foci for attention deficit/hyperactivity disorder: Targets for LORETA neurofeedback with outcomes. Biofeedback, 42(2), 47–57. https://doi.org/10.5298/1081-5937-42.2.01

Cannon, W. B. (1932). The wisdom of the body. W. W. Norton & Company.

Cannon, R. L., Baldwin, D. R., Diloreto, D. J., Phillips, S. T., Shaw, T. L., & Levy, J. J. (2014). LORETA neurofeedback in the precuneus: Operant conditioning in basic mechanisms of self-regulation. Clinical EEG and Neuroscience, 45(4), 238–248. https://doi.org/10.1177/1550059413512796

Cannon, R. L., Baldwin, D. R., Shaw, T. L., Diloreto, D. J., Phillips, S. M., Scruggs, A. M., & Riehl, T. C. (2012). Reliability of quantitative EEG (qEEG) measures and LORETA current source density at 30 days. Neuroscience Letters, 518(1), 27–31. https://doi.org/10.1016/j.neulet.2012.04.035

Cannon, R., & Lubar, J. (2011). Long-term effects of neurofeedback training in anterior cingulate cortex: A short follow-up report. Journal of Neurotherapy, 15(2), 130–150. https://doi.org/10.1080/10874208.2011.570694

Cannon, R., Mills, C., Geroux, M. J., Zhart, L. A., Boluyt, K., Webber, R., & Cook, D. (2025). LORETA neurofeedback at precuneus: A standard approach for use in incarcerated populations with substance use problems. NeuroRegulation. [Unpublished manuscript].

Cannon, R. L., Strunk, W., Carroll, S., & Carroll, S. (2018). LORETA neurofeedback at precuneus in 3-year-old female with intrauterine drug exposure. NeuroRegulation, 5(2), 75–82. https://doi.org/10.15540/nr.5.2.75

Cannon, R., Tedder, J., & Millsaps, K. (2023). LORETA neurofeedback in the educational setting: A standard protocol to improve learning and self-regulation as a method for student success in post-COVID recovery. In Proceedings of the 2023 ISNR Annual Conference: Keynote and Plenary Presentations, 10(4), 260–270. https://doi.org/10.15540/nr.10.4.260

Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: A review of its functional anatomy and behavioural correlates. Brain, 129(3), 564–583. https://doi.org/10.1093/brain/awl004

deBettencourt, M. T., Cohen, J. D., Lee, R. F., Norman, K. A., & Turk-Browne, N. B. (2015). Closed-loop training of attention with real-time brain imaging. Journal of Neuroscience, 18(3), 470–475. https://doi.org/10.1038/nn.3940

Dunbar, R. I. M. (1998). The social brain hypothesis. Evolutionary Anthropology: Issues, News, and Reviews, 6(5), 178–190. https://doi.org/10.1002/(SICI)1520-6505(1998)6:5<178::AID-EVAN5>3.0.CO;2-8

Fournier, J. C., DeRubeis, R. J., Hollon, S. D., Dimidjian, S., Amsterdam, J. D., Shelton, R. C., & Fawcett, J. (2010). Antidepressant drug effects and depression severity: A patient-level meta-analysis. Journal of the American Medical Association, 303(1), 47–53. https://doi.org/10.1001/jama.2009.1943

Fox, K. C. R., Zakarauskas, P., Dixon, M., Ellamil, M., Thompson, E., & Christoff, K. (2012). Meditation experience predicts introspective accuracy. PLoS ONE, 7(9), Article e45370. https://doi.org/10.1371/journal.pone.0045370

Ghaziri, J., Tucholka, A., Larue, V., Blanchette-Sylvestre, M., Reyburn, G., Gilbert, G., Lévesque, J., & Beauregard, M. (2013). Neurofeedback training induces changes in white and gray matter. Clinical EEG and Neuroscience, 44(4), 265–272. https://doi.org/10.1177/1550059413476031

Hofmann, S. G., & Smits, J. A. J. (2008). Cognitive-behavioral therapy for adult anxiety disorders: A meta-analysis of randomized placebo-controlled trials. Journal of Clinical Psychiatry, 69(4), 621–632. https://doi.org/10.4088/JCP.v69n0415

Hölzel, B. K., Carmody, J., Vangel, M., Congleton, C., Yerramsetti, S. M., Gard, T., & Lazar, S. W. (2011). Mindfulness practice leads to increases in regional brain gray matter density. Psychiatry Research: Neuroimaging, 191(1), 36–43. https://doi.org/10.1016/j.pscychresns.2010.08.006

Johnston, S. J., Boehm, S. G., Healy, D., Goebel, R., & Linden, D. E. J. (2010). Neurofeedback: A promising tool for the self-regulation of emotion networks. NeuroImage, 49(1), 1068–1072. https://doi.org/10.1016/j.neuroimage.2009.07.056

Lam, S.-L., Criaud, M., Lukito, S., Westwood, S. J., Agbedjro, D., Kowalczyk, O. S., Curran, S., Barret, N., Abbott, C., Liang, H., Simonoff, E., Barker, G. J., Giampietro, V., & Rubia, K. (2022). Double-blind, sham-controlled randomized trial testing the efficacy of fMRI neurofeedback on clinical and cognitive measures in children with ADHD. American Journal of Psychiatry, 179(12), 947–958. https://doi.org/10.1176/appi.ajp.21100999

Li, L., Wang, Y., Zeng, Y., Hou, S., Huang, G., Zhang, L., Yan, N., Ren, L., & Zhang, Z. (2021). Multimodal neuroimaging predictors of learning performance of sensorimotor rhythm up-regulation neurofeedback. Frontiers in Neuroscience, 15, Article 699999. https://doi.org/10.3389/fnins.2021.699999

Marins, T., Rodrigues, E. C., Bortolini, T., Melo, B., Moll, J., & Tovar-Moll, F. (2019). Structural and functional connectivity changes in response to short-term neurofeedback training with motor imagery. NeuroImage, 194, 283–290. https://doi.org/10.1016/j.neuroimage.2019.03.027

Menon, V., & Uddin, L. Q. (2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure and Function, 214(5–6), 655–667. https://doi.org/10.1007/s00429-010-0262-0

Nunez, P. L., & Srinivasan, R. (2006). Electric fields of the brain: The neurophysics of EEG (2nd ed.). Oxford University Press.

Peniston, E. G., & Kulkosky, P. J. (1989). Alpha-theta brainwave training and beta-endorphin levels in alcoholics. Alcoholism: Clinical and Experimental Research, 13(2), 271–279. https://doi.org/10.1111/j.1530-0277.1989.tb00325.x

Porges, S. W. (1995). Orienting in a defensive world: Mammalian modifications of our evolutionary heritage. A polyvagal theory. Psychophysiology, 32(4), 301–318. https://doi.org/10.1111/j.1469-8986.1995.tb01213.x

Rance, M., Walsh, C., Sukhodolsky, D. G., Pittman, B., Qiu, M., Kichuk, S. A., Wasylink, S., Koller, W. N., Bloch, M., Gruner, P., Scheinost, D., Pittenger, C., & Hampson, M. (2018). Time course of clinical change following neurofeedback. NeuroImage, 181, 807–813. https://doi.org/10.1016/j.neuroimage.2018.05.001

Saj, A., Pierce, J. E., Ronchi, R., Ros, T., Thomasson, M., Bernati, T., Van De Ville, D., Serino, A., & Vuilleumier, P. (2021). Real-time fMRI and EEG neurofeedback: A perspective on applications for the rehabilitation of spatial neglect. Annals of Physical and Rehabilitation Medicine, 64(5), Article 101561. https://doi.org/10.1016/j.rehab.2021.101561

Sitaram, R., Ros, T., Stoeckel, L., Haller, S., Scharnowski, F., Lewis-Peacock, J., Weiskopf, N., Blefari, M. L., Rana, M., Oblak, E., Birbaumer, N., & Sulzer, J. (2017). Closed-loop brain training: The science of neurofeedback. Nature Reviews Neuroscience, 18(2), 86–100. https://doi.org/10.1038/nrn.2016.164

Stahl, S. M. (2000). Essential psychopharmacology: Neuroscientific basis and practical applications (2nd ed.). Cambridge University Press.

Sterman, M. B., & Friar, L. (1972). Suppression of seizures in an epileptic following sensorimotor EEG biofeedback training. Electroencephalography and Clinical Neurophysiology, 33(1), 89–95. https://doi.org/10.1016/0013-4694(72)90028-4

Strehl, U., Aggensteiner, P., Wachtlin, D., Brandeis, D., Albrecht, B., Arns, M., Arana, M., Bach, C., Banaschewski, T., Bogen, T., Flaig-Röhr, A., Freitag, C. M., Fuchsenberger, Y., Gest, S., Gevensleben, H., Herde, L., Hohmann, S., Legenbauer, T., Marx, A.-M., … Holtmann, M. (2017). Neurofeedback of slow cortical potentials in children with attention-deficit/hyperactivity disorder: A multicenter randomized trial controlling for unspecific effects. Frontiers in Human Neuroscience, 11, Article 135. https://doi.org/10.3389/fnhum.2017.00135

Suh, J. S., Minuzzi, L., Raamana, P. R., Davis, A., Hall, G. B., Harris, J., Hassel, S., Zamyadi, M., Arnott, S. R., Alders, G. L., Sassi, R. B., Milev, R., Lam, R. W., MacQueen, G. M., Strother, S. C., Kennedy, S. H., & Frey, B. N. (2020). An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report. NeuroImage: Clinical, 25, Article 102178. https://doi.org/10.1016/j.nicl.2020.102178

Thibault, R. T., MacPherson, A., Lifshitz, M., Roth, R. R., & Raz, A. (2016). Neurofeedback with fMRI: A critical systematic review. NeuroImage, 172, 786–807. https://doi.org/10.1016/j.neuroimage.2017.12.071

Van Doren, J., Arns, M., Heinrich, H., Vollebregt, M. A., Strehl, U., & Loo, S. K. (2019). Sustained effects of neurofeedback in ADHD: A systematic review and meta-analysis. European Child & Adolescent Psychiatry, 28(3), 293–305. https://doi.org/10.1007/s00787-018-1121-4

Yuan, S., Wu, H., Wu, Y., Xu, H., Yu, J., Zhong, Y., Zhang, N., Li, J., Xu, Q., & Wang, C. (2022). Neural effects of cognitive behavioral therapy in psychiatric disorders: A systematic review and activation likelihood estimation meta-analysis. Frontiers in Psychology, 13, Article 853804. https://doi.org/10.3389/fpsyg.2022.853804

Young, K. D., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., & Bodurka, J. (2014). Real-time fMRI neurofeedback training of the amygdala activity in patients with major depressive disorder. PLoS ONE, 9(2), Article e88785. https://doi.org/10.1371/journal.pone.0088785

Zilles, K., Armstrong, E., Schleicher, A., & Kretschmann, H.-J. (1988). The human pattern of gyrification in the cerebral cortex. Anatomy and Embryology, 179(2), 173–179. https://doi.org/10.1007/BF00304699

Zotev, V., Phillips, R., Yuan, H., Misaki, M., & Bodurka, J. (2014). Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback. NeuroImage, 85(Pt 3), 985–995. https://doi.org/10.1016/j.neuroimage.2013.04.126

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Published

2025-06-27

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