Slow cortical potentials (SCPs) are gradual voltage shifts in the electroencephalogram (EEG). SCPs are characterized by low-frequency oscillations, typically below 1 Hz. These oscillations are distinct from other brain rhythms, such as delta (1-4 Hz) and spindle (7-14 Hz). SCPs have been observed to occur at approximately 0.3 Hz, and their depolarizing-hyperpolarizing components have been extensively analyzed.
These potentials are crucial indicators of cortical excitability and are associated with various cognitive and motor processes. This report explores the frequency range of SCP activity, its underlying generators, its significance in brain function, and recent findings related to its role in psychological and medical disorders, sleep, and performance.
The following 19-channel BioTrace+/NeXus-32 display of 0.1-1 Hz SCP activity © John S. Anderson.
Slow Cortical Potential Generators
Several neural mechanisms and structures within the brain generate SCPs. The generation of SCPs is primarily cortical, as evidenced by their persistence even after extensive thalamic destruction and corpus callosum transection, indicating that the thalamus is not essential for their genesis (Steriade, Nuñez, & Amzica, 1993). SCPs have been identified in cortical neurons, the thalamus, and glial cells. Cortical neurons in layers II to VI generate slow oscillations when the thalamus is removed or when cortical tissue is studied in vitro (in an artificial environment) or in vivo (within a living organism). Thalamic reticular neurons exhibit similar slow spontaneous oscillations when studied in vitro, and synchronized intracortical oscillations may depend on a corticothalamic network that targets these thalamic neurons.
Cortical Neurons
SCPs are primarily generated by the synchronized activity of large populations of cortical neurons. The slow shifts in membrane potential are thought to reflect changes in the overall excitability of cortical networks (Birbaumer et al., 1990). Neuron graphic © SciePro/Shutterstock.com.
Thalamocortical Interactions
Interactions between the thalamus and cortex also play a significant role in generating SCPs. Through its relay and integrative functions, the thalamus modulates cortical excitability and contributes to the slow potential changes observed in SCPs (Lopes da Silva, 1991). Thalamocortical graphic © Netter.
Glial Cells
Emerging evidence suggests that glial cells, particularly astrocytes, may influence SCPs by modulating the extracellular environment and supporting neuronal function (Amzica & Steriade, 2002).
Glial cells generate slow SCPs when they burn sugar, producing negatively charged bicarbonate ions. Unlike EEG rhythms like delta, SCPs do not summate dendritic potentials. SCPs are associated with glial cells and gap junctions. Glial cells chemically communicate among themselves and with neurons. The slow oscillations of glial cells may influence the timing of neuronal firing through their control of potassium ion outflow (Steriade, 2005). Astrocyte graphic © Kateryna Kon/Shutterstock.com.
"The concept of a unified corticothalamic network that generates diverse types of brain rhythms grouped by the cortical slow oscillation is supported by EEG studies in humans" (Mölle et al., 2002).
The Meaning of SCP EEG Activity
SCPs indicate shifts in cortical excitability and are associated with various functional states of the brain. Surface-negative SCPs reflect synchronized depolarization of neuronal assemblies, indicating increased cortical activity. Surface-positive SCPs correspond to decreased cortical excitation, often involving inhibitory processes (Hinterberger et al., 2003). The negative SCPs detected at the scalp during neuronal depolarization may seem counterintuitive at first.
When neurons are activated, their cell bodies become more positive internally due to the influx of positive ions. This leaves the immediate extracellular space around the neuron more negative. The negative charge in the extracellular space is conducted through brain tissue, cerebrospinal fluid, skull, and scalp. EEG electrodes on the scalp detect this conducted negative potential, resulting in a negative deflection on the EEG trace.
This phenomenon is often referred to as paradoxical negativity in EEG literature (Birbaumer et al., 1990). It's important to note that what we record on the scalp is not a direct measure of neuronal membrane potential, but rather the result of complex electrical field propagation through various tissues (Elbert et al., 1980). Paradoxical positivity occurs when neurons are hyperpolarized. This relationship is crucial in understanding the neurophysiological mechanisms underlying SCPs (Birbaumer et al., 1990). This paradoxical negativity graphic (Brienza & Mecarelli, 2019) is available under the license CC BY 3.0.
Caption: Schematic drawing of the scalp EEG registering negative (A) and positive (B) deflections elicited from summated EPSPs and IPSPs derived from pooled pyramidal cells. Cells releasing glutamate and GABA provide excitatory and inhibitory superficial and deep synaptic connections, resulting in an electrophysiological sink or source. EEG = electroencephalography; EPSPs = excitatory postsynaptic potentials; GABA = gamma-aminobutyric acid; IPSPs = inhibitory postsynaptic potentials. Figure courtesy of Anteneh Feyissa M.D. and Mayo Clinic.
Caton (1875) observed that the cortex's direct current baseline becomes negative whenever it is more active. The voltage gradients range from 150-200 μV. Underlying "tone" or valence factors determine the firing characteristics of neurons within a network. When SCPs are more positive, cortical neurons fire less due to hyperpolarization. When SCPs are more negative, firing increases due to depolarization.
SCPs participate in cognitive processes such as attention, preparation, and intention. Negative SCP shifts are often linked to increased cortical excitability and readiness to respond, while positive shifts are associated with decreased excitability and relaxation (Birbaumer et al., 1990). Some types of SCPs are event-related. These include the Bereitschaftspotenial (BP or so-called readiness potential), contingent negative variation (CNV), and stimulus-preceding negativity (SPN). These represent slow negative waves related to anticipating a stimulus or preparing for a movement (Brunia et al., 2012). The BP occurs before the execution of a self-paced movement. CNV occurs when a preparatory stimulus foretells the imminent presentation of a stimulus that requires a response. SPN occurs after a movement when waiting for a stimulus that will provide feedback about the accuracy of the movement.
The slow rhythm of SCPs is often combined with delta oscillations, and these rhythms are phase-locked, suggesting a close interaction between different frequency bands in the brain's electrical activity (Steriade, Nuñez, & Amzica, 1993).
SCPs play a crucial role in motor preparation and execution. The readiness potential (Bereitschaftspotential), a type of SCP, precedes voluntary movements and reflects the planning and initiation of motor actions.
SCPs are also associated with emotional and motivational states. Negative SCPs can indicate increased arousal and emotional engagement, whereas positive SCPs can reflect relaxation and disengagement (Hinterberger et al., 2004).
Psychological and Medical Disorders
SCPs have been extensively studied in various psychological and medical conditions.
Attention-Deficit/Hyperactivity Disorder (ADHD)
Individuals with ADHD often exhibit abnormal SCP patterns, with a reduced ability to generate negative SCP shifts. Neurofeedback training targeting SCPs has shown promise in improving attention and reducing hyperactivity in these individuals (Heinrich et al., 2004).
Epilepsy
SCP neurofeedback has been explored as a treatment for epilepsy. Training individuals to increase positive SCP shifts can reduce cortical excitability and decrease the frequency of seizures (Rockstroh et al., 1993).
Parkinson's Disease
Studies have shown that patients with Parkinson's disease (PD) exhibit abnormal SCP patterns, particularly during motor tasks (Brittain & Brown, 2014). These abnormalities include altered amplitude and timing of SCPs, associated with the impaired initiation and execution of voluntary movements seen in PD.
Research has shown that during non-rapid eye movement (NREM) sleep, cortico-basal slow wave delta activity increases, while beta activity decreases. Deep brain stimulation (DBS) further modulates this altered activity, enhancing cortical delta activity and reducing alpha and low beta power. These findings suggest that SCPs and their interaction with other brain rhythms are significantly altered in PD, contributing to sleep dysfunction and spontaneous awakenings (Anjum et al., 2023).
SCPs are used to monitor the effects of therapeutic interventions, such as deep brain stimulation (DBS), on cortical function in PD patients.
Slow cortical potential (SCP) neurofeedback has shown potential efficacy as a complementary treatment for Parkinson's disease (PD). SCP neurofeedback aims to train individuals to self-regulate their brain activity, particularly focusing on slow cortical potentials associated with motor control.
Research suggests that SCP neurofeedback can improve motor function in PD patients (Kober & Wood, 2014). Some studies have reported that participants undergoing SCP neurofeedback training demonstrated better control over motor symptoms, such as tremors and rigidity, and experienced enhanced overall motor performance. Additionally, SCP neurofeedback has been associated with improvements in non-motor symptoms, including mood and cognitive function, which are often affected in PD.
While promising, the current evidence is based on a limited number of studies with small sample sizes. More extensive and rigorous clinical trials are needed to establish SCP neurofeedback's long-term efficacy and generalizability for Parkinson's disease.
Depression
SCP abnormalities are observed in depression, with patients often showing reduced amplitude of SCP shifts. Neurofeedback interventions aiming to normalize SCP patterns have shown potential in alleviating depressive symptoms (Strehl et al., 2017).
Sleep
SCPs play a role in sleep regulation and quality.
Sleep Onset and Maintenance
SCPs are involved in the transition from wakefulness to sleep. Positive SCP shifts are associated with sleep initiation and maintaining sleep stability (Sterman, 1996).
Sleep Disorders
SCPs are closely linked to sleep rhythms, particularly during NREM sleep (Anjum et al., 2023). The slow oscillations of SCPs facilitate the synchronization of neuronal activity, which is essential for the restorative functions of sleep. In PD, the suppression of slow waves and the increase in subcortical beta activity before spontaneous awakenings highlight the critical role of SCPs in maintaining sleep stability and quality.
Abnormal SCP patterns have been linked to sleep disorders such as insomnia. Neurofeedback training targeting SCPs can improve sleep onset latency and enhance overall sleep quality (Hoedlmoser et al., 2008).
Performance
Enhancing SCP activity through neurofeedback training has improved performance in various cognitive and motor tasks.
Cognitive Performance
SCP training can enhance cognitive performance, including attention, memory, and executive function. This is likely due to the improved cortical excitability and better regulation of cognitive states (Vernon et al., 2003).
Motor Performance
SCP neurofeedback has been shown to improve motor performance, particularly in tasks requiring precise timing and coordination. This enhancement is attributed to the role of SCPs in motor preparation and execution (Gruzelier et al., 2014).
Training SCP
Various approaches to training slow cortical shifts have been applied. Early research (Birbaumer, 1990; Birbaumer, 1999) showed a correlation between cortical negativity and reaction time, signal detection, and short-term memory. This was identified primarily through evoked and event-related potential (EP, ERP) research, which led to a focus on the event-related potential in developing training paradigms for research and clinical interventions. Protocols involved presenting clients/participants with sequences of 8-second trials, training both positive and negative shifts in the cortical gradient by providing visual and/or auditory feedback showing such shifts in real-time. When the goal was greater cortical positivity, more positive shift trials were provided, and the opposite was true when cortical negativity was desired. Additional transfer trials were included that asked the individual to produce a shift but did not provide visual or auditory feedback to test the level of skill acquisition. This approach was the primary paradigm during the early years of SCP research (Strehl, 2009).
Other clinicians and researchers, including Susan and Siegfried Othmer and Mark Smith, addressed these slow gradient shifts with training called variously Infra-Low Frequency Neurofeedback (Othmer, 2020) and Infraslow Neurofeedback (Smith, 2013).
Post-traumatic stress, anxiety, and other characteristics of excessive cortical activation and excitability have been addressed by training to increase overall cortical positivity, using a 4-channel/location approach that rewards a gradual shift in the cortical gradient by providing proportional audio feedback reflecting directional shifts in the gradient. This has resulted in several client self-reports of an altered state experience characterized by a marked decrease in cognitive activity while retaining awareness. The positive shift in cortical gradient appears to correspond with a reduction in conscious thought while allowing a sense of self-awareness to remain (multiple clinical observations shared with John Anderson).
Conclusion
Slow cortical potentials (SCPs) are characterized by low-frequency oscillations in the EEG, typically below 1 Hz, with significant depolarizing-hyperpolarizing components. These potentials, occurring at approximately 0.3 Hz, are crucial indicators of cortical excitability and are associated with various cognitive and motor processes. Generated by cortical neurons, thalamocortical interactions, and glial cells, SCPs reflect shifts in cortical excitability linked to attention, motor preparation, and emotional states. Negative SCP shifts indicate increased excitability and readiness to respond, while positive shifts are associated with relaxation and decreased excitability. SCPs play roles in psychological and medical disorders like ADHD, epilepsy, and depression, and are vital in sleep regulation and performance enhancement. SCP neurofeedback shows promise in improving symptoms and cognitive functions in various conditions.
Glossary
amplitude: the height of a wave, indicating the strength or intensity of a signal.
astrocytes: a type of glial cell in the brain supporting neuronal function and modulating the extracellular environment.
basal ganglia: a group of nuclei in the brain that controls voluntary motor movements, procedural learning, and routine behaviors.
cognitive performance: the efficiency of cognitive functions such as attention, memory, and executive function.
contingent negative variation (CNV): a slow cortical potential shift between a warning stimulus and an imperative stimulus requiring a motor response. It reflects the anticipation and preparation for a motor act and involves brain regions such as the prefrontal cortex and supplementary motor area. CNV is used to study cognitive processes like attention, expectation, and motor preparation.
cortical negativity: a state where the cortical surface exhibits a negative electrical potential.
cortical neurons:Â nerve cells in the cortex responsible for generating and transmitting electrical impulses.
cortical positivity: a state where the cortical surface exhibits a positive electrical potential.
deep brain stimulation (DBS): a neurosurgical procedure involving the implantation of electrodes in specific brain areas to modulate neuronal activity.
depolarization: a reduction in membrane potential, making the inside of a cell less negative relative to the outside.
electroencephalogram (EEG): a test used to evaluate the electrical activity in the brain.
excitability: the ability of neurons to respond to stimuli and generate action potentials.
glial cells: non-neuronal cells in the central nervous system that process information and support and protect neurons.
hyperpolarization: an increase in membrane potential, making the inside of a cell more negative relative to the outside.
motor control: the process by which humans and animals use their brains and muscles to perform movements.
paradoxical negativity: in the context of SCPs, it refers to surface-negative EEG shifts when neurons are depolarized due to volume conduction of negative potentials from the extracellular space to the scalp.
paradoxical positivity: in the context of SCPs, it refers to surface-positive EEG shifts when neurons are hyperpolarized due to volume conduction of positive potentials from the extracellular space to the scalp.
Parkinson's disease (PD): a progressive neurodegenerative disorder characterized primarily by motor symptoms such as tremor, rigidity, bradykinesia (slowness of movement), and postural instability.
readiness potential: a slow cortical potential that precedes voluntary movements, reflecting the planning and initiation of motor actions.
slow cortical potentials (SCPs): gradual voltage shifts in the EEG characterized by low-frequency oscillations, typically below 1 Hz.
stimulus-preceding negativity (SPN): a slow negative potential shift observed before a stimulus that signals important or relevant information, such as feedback or a reward. SPN reflects anticipatory attention and affective processes involving regions like the insula and orbitofrontal cortex. SPN is associated with emotional and cognitive anticipation. surface-negative: a negative SCP shift typically associated with increased cortical excitability and response readiness.
surface-positive: a positive SCP shift typically associated with decreased cortical excitability and relaxation.
synchronization: the coordination of neuronal activity across different regions of the brain.
thalamocortical interactions: interactions between the thalamus and cortex that play a significant role in generating SCPs.
voltage: the electrical potential difference between two points.
References
Amzica, F., & Steriade, M. (2002). The functional significance of K-complexes. Sleep Medicine Reviews, 6(2), 139–149. https://doi.org/10.1053/smrv.2001.0181
Anjum, M., Smyth, C., Dijk, D., Starr, P., Denison, T., & Little, S. (2023). Multi-night cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings at high-temporal resolution in Parkinson’s disease. Research Square. https://doi.org/10.21203/rs.3.rs-3484527/v1
Birbaumer, N. (1999). Slow cortical potentials: Plasticity, operant control, and behavioral effects. The Neuroscientist, 5, 74–78. https://doi.org/10.1177/1073858499005002
Birbaumer, N., Elbert, T., Canavan, A. G., & Rockstroh, B. (1990). Slow potentials of the cerebral cortex and behavior. Physiological Reviews, 70(1), 1–41. https://doi.org/10.1152/physrev.1990.70.1.1
Brienza, M., & Mecarelli, O. (2019). Neurophysiological basis of EEG. In O. Mecarelli (Ed.), Clinical electroencephalography (pp. 25-45). Springer. https://doi.org/10.1007/978-3-030-04573-9_2
Brunia, C. H. M., van Boxtel, G. J. M., & Böcker, B. E. (2012). Negative slow waves as indices of anticipation: The Bereitschaftspotential, the Contingent Negative Variation, and the Stimulus-Preceding Negativity. In E. S. Kappenman & S. J. Luck (eds.), The Oxford handbook of Event-Related Potential components (pp. 190-208). Oxford Academic. https://doi.org/10.1093/oxfordhb/9780195374148.013.0108
Caton, R. (1875). The electric currents of the brain. British Medical Journal, 2, 278.
Elbert, T., Rockstroh, B., Lutzenberger, W., & Birbaumer, N. (1980). Biofeedback of slow cortical potentials. I. Electroencephalography and Clinical Neurophysiology, 48(3), 293-301. https://doi.org/10.1016/0013-4694(80)90265-5
Heinrich, H., Gevensleben, H., Freisleder, F. J., Moll, G. H., & Rothenberger, A. (2004). Training of slow cortical potentials in attention-deficit/hyperactivity disorder: Evidence for positive behavioral and neurophysiological effects. Biological Psychiatry, 55(7), 772–775. https://doi.org/10.1016/j.biopsych.2003.11.013
Hinterberger, T., Veit, R., Wilhelm, B., Weiskopf, N., Vatine, J. J., & Birbaumer, N. (2005). Neuronal mechanisms underlying control of a brain-computer interface. The European Journal of Neuroscience, 21(11), 3169–3181. https://doi.org/10.1111/j.1460-9568.2005.04092.x
Hoedlmoser, K., Pecherstorfer, T., Gruber, G., Anderer, P., Doppelmayr, M., Klimesch, W., & Schabus, M. (2008). Instrumental conditioning of human sensorimotor rhythm (12-15 Hz) and its impact on sleep as well as declarative learning. Sleep, 31(10), 1401–1408.
Kalia, L. V., & Lang, A. E. (2015). Parkinson's disease. Lancet (London, England), 386(9996), 896–912. https://doi.org/10.1016/S0140-6736(14)61393-3
Lopes da Silva, F. (1991). Neural mechanisms underlying brain waves: from neural membranes to networks. Electroencephalography and Clinical Neurophysiology, 79(2), 81–93. https://doi.org/10.1016/0013-4694(91)90044-5
Mölle, M., Marshall, L., Gais, S., & Born, J. (2002). Grouping of spindle activity during slow oscillations in human non-rapid eye movement sleep. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 22(24), 10941–10947. https://doi.org/10.1523/JNEUROSCI.22-24-10941.2002
Othmer, S., & Othmer, S. (2020). Toward a theory of infra-low frequency neurofeedback. In H. W. Kirk (Ed.), Restoring the brain. Routledge, eBook ISBN 9780429275760
Rockstroh, B., Elbert, T., Birbaumer, N., Wolf, P., Düchting-Röth, A., Reker, M., Daum, I., Lutzenberger, W., & Dichgans, J. (1993). Cortical self-regulation in patients with epilepsies. Epilepsy Research, 14(1), 63–72. https://doi.org/10.1016/0920-1211(93)90075-i
Shibasaki, H., & Hallett, M. (2006). What is the Bereitschaftspotential? Clinical Neurophysiology, 117(11), 2341-2356. https://doi.org/10.1016/j.clinph.2006.04.025
Smith, M. L. (2013). Infra-slow fluctuation training; On the down-low in neuromodulation. NeuroConnections.
Steriade, M., Nuñez, A., & Amzica, F. (1993). Intracellular analysis of relations between the slow (< 1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 13(8), 3266–3283. https://doi.org/10.1523/JNEUROSCI.13-08-03266.1993
Sterman M. B. (1996). Physiological origins and functional correlates of EEG rhythmic activities: Implications for self-regulation. Biofeedback and Self-regulation, 21(1), 3–33. https://doi.org/10.1007/BF02214147
Strehl, U. (2009). Slow cortical potentials neurofeedback. Journal of Neurotherapy, 13(2), 117–126. https://doi.org/10.1080/10874200902885936
Strehl, U., Aggensteiner, P., Wachtlin, D., Brandeis, D., Albrecht, B., 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., Millenet, S., Pniewski, B., … 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, 135. https://doi.org/10.3389/fnhum.2017.00135
Vernon, D., Egner, T., Cooper, N., Compton, T., Neilands, C., Sheri, A., & Gruzelier, J. (2003). The effect of training distinct neurofeedback protocols on aspects of cognitive performance. International Journal of Psychophysiology: Official Journal of the International Organization of Psychophysiology, 47(1), 75–85. https://doi.org/10.1016/s0167-8760(02)00091-0
Comments