5-Min Science: The Role of Pacemaker Neurons in Networks Trained by Neurofeedback

Introduction: The Cellular Foundation of Brain Rhythms

Neurofeedback utilizes real-time brain signals to help individuals learn to regulate specific rhythms associated with executive functions, such as attention, sleep, and mood.

Early neurofeedback research focused on operant conditioning of scalp rhythms without specifying which timing mechanisms supported the observed frequencies. As physiology improved, training began to incorporate concepts such as state control, autonomic stability, respiratory pattern, and the influence of medication on membrane excitability. These developments provide a bridge between pacemaker physiology and the practical demands of contemporary neurofeedback.

A reliable source of those rhythms is a small class of cells called pacemaker neurons. These neurons can generate rhythmic bursts on their own, and their timing can recruit and coordinate surrounding networks. Their contribution varies with state, which is why the same circuit can appear sturdy in one context and fragile in another (Peña-Ortega, 2012; Ramirez, Tryba, & Peña, 2004; Sitaram et al., 2017).

Understanding the Unique Properties of Pacemaker Neurons

Most neurons fire because other neurons drive them. Pacemaker neurons are different. Thanks to intrinsic membrane properties, they cycle between quiet and active phases on their own, creating brief bursts of action potentials that can set the tempo for larger populations. When researchers silence ordinary synaptic communication in vitro, true pacemakers continue to burst, while follower neurons do not, indicating that the rhythm originates within the cell. Whether a neuron behaves like a pacemaker depends on the context and the presence of neuromodulators, rather than solely on its cell type (Peña-Ortega, 2012; Ramirez, Tryba, & Peña, 2004).

Pacemaker Contributions to Normal Brain Rhythms

Pacemakers help explain why familiar EEG rhythms emerge so reliably. In thalamocortical networks, timing cells participate in sleep spindles that occupy the sigma band, corresponding to a frequency range of approximately 11 to 16 Hz. Converging evidence in animals identifies specific thalamic mechanisms that enable these spindles, linking pacemaker activity to a rhythm often targeted in sleep-related training (Astori et al., 2011; Peña-Ortega, 2012).

In the hippocampal system, fast-firing neurons in the medial septum can generate theta, a 4 to 8 Hz rhythm important for navigation and memory (Hangya et al., 2009; Varga et al., 2008). Hippocampus graphic © Kateryna Kon/Shutterstock.com.

In the neocortex, a subset of pyramidal neurons that burst intrinsically can help organize gamma activity, a rhythm above about 30 Hz that supports attention and sensory processing (Cunningham et al., 2004). Pyramidal neuron graphic © Kateryna Kon/Shutterstock.com.

Breathing illustrates state dependence in a clinically intuitive way: the brainstem network that generates inspiration contains multiple pacemaker populations, and different pools contribute under ordinary conditions versus during physiological stress. That shift helps explain why respiratory rhythm can be robust in one context yet brittle in another (Peña‑Ortega, 2012; Ramirez, Tryba, & Peña, 2004).

Clinical Consequences When Pacemaker Timing Becomes Disrupted

If a network leans too heavily on a particular pacemaker mechanism, symptoms can emerge. In absence epilepsy, thalamic bursting during wakefulness correlates with spike-and-wave activity, and compounds that damp the responsible thalamic timing circuitry reduce seizures in animal models, tying pacemaker features to clinical effects (Astori et al., 2011; Tringham et al., 2012). John S. Anderson illustrated a 3-per-second absence seizure.

Tshilidzi Marwala uploaded this spike-and-wave illustration to ResearchGate.

In Parkinson's disease, neurons in the subthalamic nucleus can exhibit an overly bursting mode. Dialing down the burst-supporting mechanisms or applying deep brain stimulation normalizes these patterns and improves movement in both preclinical and clinical studies (Benazzouz et al., 1996; Tai et al., 2011). Substantia nigra graphic © Kateryna Kon/Shutterstock.com.

Human tissue studies from pediatric epilepsy surgery show that intrinsically bursting neurons exist in the neocortex and are altered near seizure foci, linking cellular bursting to clinical electrophysiology (Marcuccilli et al., 2010; Tryba et al., 2011).

Across systems, reviews emphasize that pacemaker contributions shift with behavioral state and neuromodulators so that the same anatomy can support very different dynamics (Peña‑Ortega, 2012; Ramirez, Tryba, & Peña, 2004).

The Flexible Nature of Pacemaker Timing

Pacemaker behavior is adjustable rather than fixed. Intrinsic currents power rhythmic bursting, and brain chemicals can strengthen or weaken that engine. In the mammalian breathing network, endogenous serotonin is required for regular bursting in one pacemaker subtype, and the peptide substance P enhances the regularity of bursting. These studies demonstrate how neuromodulators influence the number of active pacemaker neurons and the strength of their bursts, which, in turn, affect a network's ability to generate stable rhythms (Peña & Ramirez, 2002; Peña & Ramirez, 2004; Ramirez, Tryba, & Peña, 2004).

Clinical Applications for Neurofeedback Practice

Three principles help translate this physiology into practice. First, align targets with plausible pacemaker substrates. Training near the sigma band, where sleep spindles reside, interacts with thalamic timing cells; therefore, medications that alter thalamic bursting can change how readily a person increases spindles during training (Astori et al., 2011; Tringham et al., 2012).

Second, expect state dependence. Theta-range training engages septum-hippocampus circuits in which septal pacemakers act as leaders; differences in arousal and context help explain person-to-person variability (Hangya et al., 2009; Ramirez, Tryba, & Peña, 2004; Varga et al., 2008).

Third, recognize that gamma-band protocols may depend on the excitability of intrinsically bursting cortical neurons; drugs that reduce the steady inward drive that supports bursting can blunt gamma increases, which may be helpful in epilepsy but may dampen response to gamma-upregulation aims (Cunningham et al., 2004; Stafstrom, 2007; Taverna et al., 1998).

Practical Recommendations for Session Management

State

Standardize state across sessions. Drowsiness, caffeine, sedatives, acute stress, and changes in breathing pattern each shift the neuromodulators that govern pacemaker excitability; maintaining these factors steady makes the pacemaker's contribution to a target rhythm more predictable (Peña-Ortega, 2012; Ramirez, Tryba, & Peña, 2004; Sitaram et al., 2017). State shapes reward sensitivity and signal-to-noise ratios in cortical recordings. When autonomic arousal is high, cortical rhythms often show elevated broadband activity, which can mask amplitude changes in the trained band. Establishing a stable preparatory routine that standardizes breathing, posture, and attentional stance improves the reliability of learning curves.

Medication

Many common agents alter intrinsic membrane currents relevant to bursting, including persistent sodium currents, T-type calcium currents, and HCN-mediated pacing. The practical implication is that medication changes can shift the apparent ease or difficulty of frequency training. Assess the stability of medication throughout the training period. Adjust expectations when agents that influence cortical excitability, sleep architecture, or autonomic activation are present. Agents that affect thalamic or cortical bursting can influence frequency training in the sigma, alpha, or gamma bands (Astori et al., 2011; Stafstrom, 2007; Tringham et al., 2012).

Breathing

Breathing-related oscillations couple to cortical rhythms through vagal and brainstem pathways. When the respiratory network shifts to a stress-driven pattern, the pacemaker hierarchy reorganizes, and cortical oscillations can become less predictable.

Breathwork pairs well with many protocols, but remember that respiratory circuits recruit different pacemaker sets under low oxygen levels. Paced breathing exercises can help maintain comfort and alertness rather than stress (Peña-Ortega, 2012; Ramirez, Tryba, & Peña, 2004). Consistent breathing depth and pace before and during feedback sessions help to stabilize the milieu in which pacemaker-driven rhythms operate.

Artifacts

Practical challenges often arise not from neural mechanisms but from artifacts that mimic rhythmic activity. Pacemaker-driven rhythms can be subtle, whereas muscle tension, respiration-induced movement, and electrode drift can produce misleading periodicity. Maintaining a clean impedance, minimizing facial and jaw tension, and monitoring respiratory-induced artifacts help prevent the misattribution of non-neural periodic signals to pacemaker-linked rhythms.

Protocol Design

For sigma or sensorimotor ranges, quiet attentional engagement and low muscle tension are crucial. For theta-related protocols, arousal must be kept sufficiently stable to avoid drifting into drowsiness, where theta reflects state change rather than controlled modulation. For gamma-oriented work, high-frequency activity is particularly vulnerable to muscle contamination. Training should therefore include careful calibration periods and real-time artifact suppression to ensure that observed changes reflect genuine pacemaker-supported cortical activity.

Summary and Integration

Pacemaker neurons are the brain's timekeepers. They help start, stabilize, and synchronize rhythms that underlie sleep, attention, memory, breathing, and movement. Their influence is flexible, as neuromodulators and network context can modulate pacemaker contributions. When these dynamics are exaggerated or suppressed, disorders can emerge.

Neurofeedback targets the very rhythms that pacemakers scaffold, so mapping targets to pacemaker-rich circuits, controlling participant state, and coordinating with medication plans can make training safer and more effective (Peña‑Ortega, 2012; Ramirez, Tryba, & Peña, 2004; Sitaram et al., 2017). Any rhythm targeted during neurofeedback sits atop a network of interacting excitatory, inhibitory, and neuromodulatory processes. Pacemaker neurons contribute intrinsic timing, but trainability ultimately depends on the global balance of arousal, autonomic tone, and respiratory state.

Key Takeaways

1. Pacemaker neurons can set a beat on their own and help networks switch from quiet to active states.
   

2. Their contribution to any rhythm depends on state, which is why standardizing arousal, breathing, and recent substance use helps training.
   

3. Sigma, theta, and gamma protocols interact with circuits containing identifiable timing cells, so the effects of medication on these cells can alter trainability.
   

4. In epilepsy and Parkinsonism, abnormal bursting helps explain symptoms and why some rhythms resist change.
   

5. Using this physiology to select targets and shape session conditions should improve outcomes.

Glossary

absence epilepsy: a generalized epilepsy marked by brief lapses of awareness with abrupt onset and offset, typically accompanied by a 3 Hz spike and wave pattern on electroencephalography. alpha rhythm: a brain rhythm near 8 to 12 Hz that is prominent over occipital areas during relaxed wakefulness.

arousal: a global state of alertness that influences neural excitability. artifact: a non-neural signal contaminating physiological recordings. autonomic tone: the balance of sympathetic and parasympathetic activity that shapes physiological state. bursting: a neuronal firing pattern in which action potentials occur in short clusters separated by intervals of relative quiescence.

central pattern generator: a network that produces rhythmic output without requiring rhythmic input, as in breathing or walking.

deep brain stimulation: a neurosurgical therapy that delivers electrical pulses to specific brain regions to normalize abnormal activity.

electroencephalography: a method that records scalp electrical activity from the brain to estimate rhythmic patterns.

frequency training: neurofeedback protocols to increase or decrease power in specific frequency bands.

gamma oscillation: a brain rhythm above about 30 Hz associated with attention and sensory processing.

HCN channel: a hyperpolarization-activated channel that can contribute to pacemaking.

hippocampus: a brain structure important for memory and navigation that participates in theta rhythms.

medial septum: a basal forebrain region that helps pace hippocampal theta through fast‑firing inhibitory neurons.

membrane current: ionic flow through channels that determines firing patterns.

neocortex: the layered outer surface of the brain that supports perception, thought, and voluntary movement.

network: an interconnected set of neurons whose synaptic interactions generate collective activity patterns that can support behaviorally relevant rhythms.

neurofeedback: a training method that uses real‑time brain signals to help individuals learn voluntary control of neural activity.

neuromodulator: a chemical that shifts neuronal responsiveness and network state.

oscillation: a repeated rise and fall in a signal’s amplitude over time, such as a brain rhythm.

pacemaker neuron: a neuron that can generate rhythmic bursts without needing rhythmic input from other neurons.

Parkinson’s disease: a progressive neurodegenerative disorder characterized by bradykinesia, rigidity, rest tremor, and postural instability, associated with degeneration of nigrostriatal dopamine neurons and dysregulated basal ganglia circuits.

pyramidal neurons: a class of excitatory projection neurons with pyramid‑shaped cell bodies and a prominent apical dendrite, predominant in the cerebral cortex and hippocampus.

reinforcement: increasing the probability of an operant behavior when a discriminative stimulus is present. sensorimotor rhythm: a rhythm around 12 to 15 Hz recorded over the central scalp that relates to quiet motor readiness.

sigma band: a frequency band around 11 to 16 Hz that contains sleep spindles during stage 2 non‑REM sleep.

spike‑and‑wave activity: a repetitive electroencephalographic pattern in which brief spikes are followed by slower waves at a regular frequency, classically around 3 Hz in typical absence seizures.

state dependence: variation in neural patterns due to changes in internal or external conditions. substance P: a neuropeptide that enhances neuronal excitability by acting on specific G-protein–coupled receptors

subthalamic nucleus: a glutamatergic structure of the basal ganglia located below the thalamus that modulates motor output and is a common target for deep brain stimulation in Parkinson’s disease.

synchrony: the temporal alignment of neuronal firing or oscillations across cells or regions that produces coordinated activity.

state: the moment‑to‑moment operating condition of a neural circuit determined by arousal level, neuromodulators, the current balance of inhibition and excitation, metabolic and oxygenation status, medications, and recent activity; it governs whether pacemaker neurons express intrinsic bursting and which pacemaker subgroup sets the rhythm.

T-type calcium current: a low-threshold, transient calcium influx that promotes rhythmic burst firing in specific neurons. theta rhythm: a 4 to 8 Hz brain rhythm linked to memory, navigation, and drowsiness.

References

Astori, S., Wimmer, R. D., Prosser, H. M., Corti, C., Corsi, M., Liaudet, N., Volterra, A., Franken, P., Adelman, J. P., & Lüthi, A. (2011). The Cav3.3 calcium channel is the major sleep spindle pacemaker in thalamus. Proceedings of the National Academy of Sciences of the United States of America, 108(33), 13823–13828. https://doi.org/10.1073/pnas.1105115108

Benazzouz, A., Boraud, T., Féger, J., Burbaud, P., Bioulac, B., & Gross, C. (1996). Alleviation of experimental hemiparkinsonism by high‑frequency stimulation of the subthalamic nucleus in primates: A comparison with L‑Dopa treatment. Movement Disorders, 11(6), 627–632. https://doi.org/10.1002/mds.870110606

Cunningham, M. O., Whittington, M. A., Bibbig, A., Roopun, A., LeBeau, F. E. N., Vogt, A., Monyer, H., Buhl, E. H., & Traub, R. D. (2004). A role for fast rhythmic bursting neurons in cortical gamma oscillations in vitro. Proceedings of the National Academy of Sciences of the United States of America, 101(18), 7152–7157. https://doi.org/10.1073/pnas.0402060101

Hangya, B., Borhegyi, Z., Szilágyi, N., Freund, T. F., & Varga, V. (2009). GABAergic neurons of the medial septum lead the hippocampal network during theta activity. Journal of Neuroscience, 29(25), 8094–8102. https://doi.org/10.1523/JNEUROSCI.5665-08.2009

Marcuccilli, C. J., Tryba, A. K., van Drongelen, W., Koch, H., Viemari, J.‑C., Peña‑Ortega, F., Doren, E. L., Pytel, P., Chevalier, M., Mrejeru, A., Kohrman, M. H., Lasky, R. E., Lew, S. M., Frim, D. M., & Ramirez, J.‑M. (2010). Neuronal bursting properties in focal and parafocal regions in pediatric neocortical epilepsy stratified by histology. Journal of Clinical Neurophysiology, 27(6), 387–397. https://doi.org/10.1097/WNP.0b013e3181fe06d8

Peña, F., & Ramirez, J. M. (2002). Endogenous activation of serotonin‑2A receptors is required for respiratory rhythm generation in vitro. Journal of Neuroscience, 22(24), 11055–11064. https://doi.org/10.1523/JNEUROSCI.22-24-11055.2002

Peña, F., & Ramirez, J. M. (2004). Substance P‑mediated modulation of pacemaker properties in the mammalian respiratory network. Journal of Neuroscience, 24(34), 7549–7556. https://doi.org/10.1523/JNEUROSCI.1871-04.2004

Peña‑Ortega, F. (2012). Pacemaker neurons and neuronal networks in health and disease. In Advances in Clinical Neurophysiology (Chapter 6). InTech. https://doi.org/10.5772/50264

Ramirez, J.‑M., Tryba, A. K., & Peña, F. (2004). Pacemaker neurons and neuronal networks: An integrative view. Current Opinion in Neurobiology, 14(6), 665–674. https://doi.org/10.1016/j.conb.2004.10.011

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

Stafstrom, C. E. (2007). Persistent sodium current and its role in epilepsy. Epilepsy Currents, 7(1), 15–22. https://doi.org/10.1111/j.1535-7511.2007.00156.x

Tai, C.‑H., Yang, Y.‑C., Pan, M.‑K., Huang, C.‑S., & Kuo, C.‑C. (2011). Modulation of subthalamic T‑type Ca2+ channels remedies locomotor deficits in a rat model of Parkinson disease. Journal of Clinical Investigation, 121(8), 3289–3305. https://doi.org/10.1172/JCI46482

Taverna, S., Mantegazza, M., Franceschetti, S., & Avanzini, G. (1998). Valproate selectively reduces the persistent fraction of Na+ current in neocortical neurons. Epilepsy Research, 32(1–2), 304–308. https://doi.org/10.1016/S0920-1211(98)00060-6

Tringham, E., Powell, K. L., Cain, S. M., Kuplast, K., Mezeyova, J., Weerapura, M., Eduljee, C., Jiang, X., Smith, P., Morrison, J.‑L., Jones, N. C., Braine, E., Rind, G., Fee‑Maki, M., Parker, D., Pajouhesh, H., Parmar, M., O’Brien, T. J., & Snutch, T. P. (2012). T‑type calcium channel blockers that attenuate thalamic burst firing and suppress absence seizures. Science Translational Medicine, 4(121), 121ra19. https://doi.org/10.1126/scitranslmed.3003120

Tryba, A. K., Kaczorowski, C. C., Ben‑Mabrouk, F., Elsen, F. P., Lew, S. M., & Marcuccilli, C. J. (2011). Rhythmic intrinsic bursting neurons in human neocortex obtained from pediatric patients with epilepsy. European Journal of Neuroscience, 34(1), 31–44. https://doi.org/10.1111/j.1460-9568.2011.07746.x

Varga, V., Hangya, B., Kránitz, K., Ludányi, A., Zemankovics, R., Katona, I., Shigemoto, R., Freund, T. F., & Borhegyi, Z. (2008). The presence of pacemaker HCN channels identifies theta rhythmic GABAergic neurons in the medial septum. Journal of Physiology, 586(16), 3893–3915. https://doi.org/10.1113/jphysiol.2008.155242

About the Author

Fred Shaffer earned his PhD in Psychology from Oklahoma State University. He earned BCIA certifications in Biofeedback and HRV Biofeedback. Fred is an Allen Fellow and Professor of Psychology at Truman State University, where has has taught for 50 years. He is a Biological Psychologist who consults and lectures in heart rate variability biofeedback, Physiological Psychology, and Psychopharmacology. Fred helped to edit Evidence-Based Practice in Biofeedback and Neurofeedback (3rd and 4th eds.) and helped to maintain BCIA's certification programs.

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