Neurofeedback for Peak Performance in Sports

Neurofeedback and the Pursuit of Peak Performance

Neurofeedback (NFB) is a form of biofeedback that enables individuals to observe and regulate their own brain activity in real time.

The technology serves multiple purposes, ranging from basic science investigations of brain function (Ros et al., 2013) to clinical interventions for health concerns (Thompson & Thompson, 2015) and the cultivation of peak performance (van Son et al., 2020).

Peak performance refers to the seemingly effortless functioning at the upper limit of one's ability, a state that athletes, musicians, surgeons, and other skilled professionals strive to reach.

Types of peak performance may involve motor performance in athletic or artistic endeavors, cognitive performance for tasks that demand mental effort, and emotional regulation during stressful activities. Parameters of interest across these areas include force, complexity, speed, coordination, endurance, recovery time, and flexibility.

An increasingly important application of neurofeedback is the use of its technologies to teach self-regulation of brain activity in the service of peak performance.

This post examines three recent articles that illuminate how neurofeedback can be applied to motor performance in sport. They support Larson and Sherlin's (2023) probably efficacious rating for neurofeedback in optimal performance.

First, a meta-analysis by Yu et al. (2025) synthesizes the overall evidence base across 21 controlled studies.

Second, a quantitative electroencephalographic (qEEG) study by Cheng et al. (2023) reveals the neural signatures that distinguish superior from inferior marksmen.

Third, an experimental neurofeedback intervention by Lo et al. (2025) demonstrates that training a specific brain rhythm can improve shooting accuracy in experienced athletes.

Systematic Review and Meta-Analysis of Neurofeedback for Motor Performance in Sport: Yu et al. (2025)

Elite athletic performance is often explained not only by physical skill but also by how efficiently the brain controls movement. In precision sports such as shooting, even tiny variations in attention, motor control, or neural processing can determine whether a shot hits the center of the target or misses entirely.

The theoretical framework guiding much of this research is the psychomotor efficiency hypothesis, which proposes that expert performers show more efficient brain activity during skilled movement.

In practical terms, this means the brain activates task-relevant processes while suppressing unnecessary or distracting neural activity.

This section reviews a comprehensive meta-analysis that tested the hypothesis across multiple sports and neurofeedback protocols.

The multinational Yu et al. (2025) research team, drawn from Taiwan, China, the United States, and Germany, searched the PubMed, Scopus, and Web of Science databases for articles published before 2025. Their inclusion criteria required healthy adult participants, an EEG neurofeedback intervention, measured motor performance outcomes, and a controlled experimental design.

Twenty-five studies met these criteria for qualitative review, and 21 of those could be included in the quantitative meta-analysis. These 21 studies collectively included 271 research participants.

The neurofeedback protocols in the reviewed studies frequently targeted one of four frequency bands: alpha (8 to 13 Hz), theta (4 to 7.5 Hz), the sensorimotor rhythm or SMR (12 to 15 Hz), or beta (15 to 30 Hz).

The sensorimotor rhythm is an EEG rhythm recorded over the motor strip of the cortex that is associated with motor stillness and focused readiness.

Training sites for neurofeedback were often at the 10-20 system electrode locations C3, Cz, C4, or Pz. Motor tasks in the selected studies included golf putting, rifle or pistol shooting, archery, dance, balance, and cycling endurance.

Main Findings of the Yu et al. (2025) Meta-Analysis

This section summarizes four key findings from the meta-analysis regarding overall effect size, the influence of study quality, the impact of athlete expertise, and the theoretical interpretation of results.

The meta-analysis found an overall moderate effect size for neurofeedback when all studies were taken into account. This result suggests that neurofeedback produces meaningful improvements in motor performance tasks compared to control conditions.

Studies that had better experimental designs, as assessed with the CRED-nf Checklist (Ros et al., 2020), showed statistically larger effects than less well-designed studies. The CRED-nf Checklist is a standardized tool for evaluating the reporting quality of neurofeedback experiments. Yu et al. (2025) interpreted this finding as evidence that better experimental design helps to make the effects of neurofeedback more apparent, rather than inflating them.

Yu et al. (2025) also identified a trend showing that novice athletes had larger effects than expert athletes, perhaps because of a ceiling effect that limited absolute improvements among those already performing at high levels. Findings were interpreted within a psychomotor efficiency model frequently used in sports neuroscience (Lu et al., 2025).

This model hypothesizes that sport performance is enhanced when there is reduced conscious effort to control motor skills, increased relaxation, greater efficiency in neural processing, and more automaticity of motor execution.

Methodological Limitations Identified by Yu et al. (2025)

Despite the encouraging overall result, the studies reviewed by Yu et al. (2025) were marked by several methodological limitations. Sample sizes were typically small, few studies used double-blind designs, and control conditions were inconsistent across experiments. Neurofeedback protocols were heterogeneous, and most interventions were short-term in duration. Researchers frequently failed to report important details such as participant self-regulation strategies, artifact correction methods, reinforcement schedules, the level of success participants achieved in regulating their EEG signal, and the correlation between EEG regulation success and changes in motor behavior.

Bottom Line from the Yu et al. (2025) Meta-Analysis

EEG neurofeedback shows moderate effect size evidence for improving sports motor performance, particularly in studies with stronger methodological design. However, the literature remains heterogeneous and methodologically uneven.

Future work should adopt standardized protocols and reporting practices such as the CRED-nf framework to strengthen the evidence base and allow more definitive conclusions.

Practical Insights for Neurofeedback and Motor Behavior in Sport

The findings from the Yu et al. (2025) meta-analysis carry practical implications for clinicians and sport psychologists considering neurofeedback for athletic training. This section presents two summary tables extracted from the reviewed studies, describes the most common training protocols, and discusses patterns in how different sports responded to neurofeedback.

The most frequently used neurofeedback protocol across the collection of studies was rewarding SMR while simultaneously inhibiting theta, a combination often employed in precision-skill sports such as putting and pistol shooting. SMR uptraining may help motor efficiency and consistency by reducing neural "noise," while theta downtraining may enhance sustained attention by reducing drowsiness and mind-wandering.

Most neurofeedback protocols used central or frontal electrode sites that are associated with motor control and attention. The following table summarizes the rationale for common electrode placements.

Neural Signatures of Superior Marksmanship: A qEEG Study by Cheng et al. (2023)

Neurofeedback can often be helpfully guided by the results of quantitative EEG (qEEG) assessment, a method that uses statistical analyses of recorded brainwave data to identify patterns of neural activity associated with specific cognitive or motor states.

Cheng et al. (2023) present a recent example of how qEEG can illuminate the brain dynamics underlying sport peak performance. This section describes their study of skilled marksmen, the specific EEG markers they examined, and the neural differences they found between superior and inferior shooters.

Researchers studying skilled athletes have focused on several specific EEG signals thought to reflect attention, motor planning, and interference control. Among the most commonly studied are frontal midline theta activity (an indicator of sustained attention originating from frontal brain regions), left temporal alpha activity (associated with verbal-analytical processing), the sensorimotor rhythm (linked to motor readiness and inhibition), and coherence between frontal and temporal brain regions (reflecting how strongly these areas communicate). Each of these signals may indicate how efficiently an athlete's brain organizes perception, cognition, and movement while preparing for action.

In sports that demand extreme precision, such as air pistol shooting, athletes must maintain steady posture, regulate breathing, stabilize attention, and control extremely fine motor movements during the final seconds before firing. These demands make shooting an ideal task for studying the neural processes underlying psychomotor efficiency. If superior performers truly operate with more efficient neural dynamics, their brain activity during preparation and aiming should differ measurably from that of less successful shooters.

How Cheng et al. (2023) Studied Neural Markers in Skilled Marksmen

Cheng et al. (2023) investigated the neural signatures that distinguish superior shooting performance from less successful performance among highly trained marksmen. Their goal was to determine whether differences in specific EEG markers corresponded to differences in shooting accuracy and motor stability.

The researchers specifically examined four EEG indicators associated with the psychomotor efficiency hypothesis: frontal midline theta, left temporal alpha activity, sensorimotor rhythm activity over the sensorimotor cortex, and coherence between frontal and temporal brain regions. Each marker represents different aspects of cognitive and motor control, including sustained attention, verbal-analytical processing, interference control, and conscious monitoring of movement.

The study recruited 35 right-handed skilled marksmen between the ages of 18 and 38, all of whom had substantial experience in precision shooting. Each shooter completed a controlled air pistol shooting task while brain activity was recorded using electroencephalography.

During the experiment, participants performed 30 shots while researchers monitored neural activity in the seconds leading up to the trigger pull. This period is particularly important because it involves intense focus and fine motor control as the athlete aligns the target and prepares to fire.

After the shooting session, participants were divided into two groups based on a median split of their shooting scores. Those with higher performance scores were classified as the superior group, while the remaining shooters formed the inferior group. Electroencephalographic data were then examined to determine whether the two groups differed in key neural markers during the preparation and aiming periods. The analysis focused on patterns of brain activity immediately before the trigger pull, when cognitive and motor processes are most tightly integrated.

What Cheng et al. (2023) Found: SMR, Coherence, and Psychomotor Efficiency

Cheng et al. (2023) found clear differences in neural activity between the superior and inferior marksmen.

One of the most important findings was that superior shooters exhibited higher sensorimotor rhythm activity during the preparation period before firing. This increased activity occurred from approximately three seconds before the shot until the trigger pull.

Sensorimotor rhythm activity was also associated with more stable movement across all participants: higher SMR power correlated with less jerking movement during the aiming phase.

This finding suggests that stronger SMR activity may support finer motor control and greater stability during precision tasks, consistent with the idea that increased SMR activity reflects reduced extraneous motor output.

Another important difference appeared in the coherence between frontal and left temporal brain regions. Coherence in this context refers to the degree of synchronization or communication between two brain areas. During successful shots that hit the bull's eye, superior shooters showed lower high alpha coherence between these regions than inferior shooters.

This pattern suggests reduced communication between motor planning areas and regions associated with verbal-analytical processing. Lower coherence in this network is interpreted as a sign of reduced conscious monitoring and verbal analysis during movement.

In other words, the superior performers appeared to rely less on deliberate thinking and more on automatic motor execution. This pattern aligns closely with the psychomotor efficiency hypothesis, which predicts that skilled athletes suppress unnecessary cognitive processing during performance.

Overall, the findings suggest that superior shooters demonstrate a combination of increased sensorimotor stability and reduced interference from unnecessary neural processing.

Training the Quiet Brain: An Experimental Neurofeedback Intervention for Pistol Shooting by Lo et al. (2025)

The qEEG findings from Cheng et al. (2023) and others have identified neural markers associated with expert performance, but a critical question remains: can these neural states be deliberately trained?

Lo et al. (2025) addressed this question by testing whether increasing the amplitude of left temporal alpha activity at the 10-20 electrode site T3 would improve accuracy among expert air pistol marksmen. This section describes the theoretical rationale, the experimental design, and the results of a six-week neurofeedback intervention.

The theoretical backdrop for the study is the psychomotor efficiency hypothesis, a framework proposing that elite performers execute complex actions with reduced and more selective neural processing. When motor skills become highly practiced, the brain ideally minimizes unnecessary cognitive activity, allowing movement planning and execution to occur with minimal interference.

In elite marksmen, previous electroencephalographic studies have repeatedly observed increased alpha oscillations over the left temporal cortex during the final seconds preceding a shot. Alpha activity is a brain rhythm typically cycling between 8 and 13 times per second that, in this context, is thought to reflect active inhibition of irrelevant cognitive processes, particularly verbal-analytical thinking that might disrupt automatic motor control.

The left temporal region is of particular interest because it is associated with language and analytic processing. If activity in this region decreases during performance, it may indicate that the athlete is not consciously analyzing the movement but rather relying on automated sensorimotor routines. This state aligns with the concept of "quiet eye" and automaticity in motor learning.

Neurofeedback offers a potential method to deliberately train this neural state by allowing individuals to observe and regulate their own brain activity in real-time.

Experimental Design and Procedure of Lo et al. (2025)

Twenty experienced air pistol shooters participated in the experiment. By focusing on skilled shooters rather than novices, the investigators attempted to study individuals already operating near the optimal range of motor coordination. This design choice increased the likelihood that subtle changes in neural regulation, rather than basic skill acquisition, would account for any performance improvements observed.

Marksmen were randomly assigned to either a neurofeedback-plus-shooting-skills-training group or a shooting-skills-training-only group. Lo et al. (2025) discuss the pros and cons of sham and active control groups, and explain their decision not to use either because of the risk of degraded performance with false feedback, as observed by Landers et al. (1991). Sham feedback refers to providing participants with signals that do not reflect their actual brain activity, a practice that can sometimes inadvertently impair skilled performance.

The study followed a three-phase design consisting of pretesting, a six-week intervention period, and post-testing. During pretest and posttest sessions, participants performed 40 shots at a standard 10-meter target while electroencephalographic signals were recorded from 30 scalp locations using the international 10-20 electrode system.

Particular attention was paid to temporal sites corresponding to the left and right temporal cortices. The researchers examined alpha activity in two sub-bands: low alpha, typically associated with general cortical arousal, and high alpha, which has been linked to task-specific attentional processes.

During the intervention phase, the neurofeedback group completed 16 training sessions over approximately six weeks. Each session included 15 trials lasting 30 seconds each.

For each trial, the participants were instructed to aim at a target while they received auditory feedback reflecting whether their alpha activity at the left temporal electrode site exceeded a personalized threshold. They were also instructed to hold the alpha activity above threshold for as long as possible.

This threshold was derived from the participant's best shots recorded during the pretest session. To analyze neural data, researchers focused on the final three seconds before the trigger pull, dividing this interval into three one-second segments.

Results of the Lo et al. (2025) Neurofeedback Intervention

The results indicated that neurofeedback training was associated with both neural and behavioral changes. Shooters who received neurofeedback demonstrated significantly greater improvement in shooting accuracy from pretest to posttest than those in the control group. Performance gains were evident across the training sessions and were largest by the final session of the intervention period.

A strong relationship also emerged between the duration of time participants maintained the targeted alpha state during training and their shooting scores. As participants became more proficient at sustaining the desired neural pattern, their performance accuracy tended to increase as well.

This dose-response relationship suggested that the neurofeedback protocol was not merely producing incidental changes but was tied directly to the behavioral outcome being measured.

Pearson correlation between the holding time of T3-alpha power and performance accuracy for the neurofeedback group.

The duration of alpha holding time also increased as neurofeedback training continued from the first to the sixteenth session, indicating progressive learning of the self-regulation skill.

Means and standard errors of holding time of T3-alpha power as a function of training sessions for the neurofeedback group.

Interestingly, the enhancement was not confined to the left temporal region that had been targeted during neurofeedback. Instead, elevated alpha power appeared bilaterally across both temporal cortices. This finding suggested that training one region may influence broader cortical networks involved in motor planning and attentional regulation.

Means and standard errors of performance accuracy for neurofeedback and control groups across 16 training sessions.

Strengths and Limitations of the Lo et al. (2025) Study

One strength of the study was its use of a theoretically grounded neurofeedback target. Rather than selecting an arbitrary EEG frequency, the researchers focused on a biomarker repeatedly associated with expert motor performance. This choice strengthened the interpretation that the intervention was aligned with known neural mechanisms of skilled behavior.

Another methodological advantage was the number of training sessions. Many earlier neurofeedback studies used only one or a few sessions, making it difficult to observe durable neural adaptations. The 16-session design allowed participants sufficient time to learn self-regulation strategies and potentially consolidate them through practice. The study also avoided using sham feedback for the control group, thereby preventing the risk of inadvertently impairing the performance of skilled participants.

At the same time, several limitations should be noted. The sample size was relatively small, which restricts statistical power and generalizability. The spatial resolution of EEG is also limited by volume conduction, a phenomenon in which electrical signals spread through brain tissue and skull so that activity recorded at one electrode may partly reflect signals from nearby cortical regions.

Consequently, interpreting left temporal alpha activity as a precise marker of verbal-analytical processes must be done cautiously. Additionally, the absence of changes in coherence measures weakens the claim that the intervention improved large-scale neural efficiency, and future studies using higher-resolution imaging techniques or more sophisticated connectivity analyses could clarify how neurofeedback influences broader brain networks.

Broader Impact and Implications of the Lo et al. (2025) Study

The study provides experimental evidence supporting the idea that neural states associated with expert performance can be deliberately trained.

By demonstrating that self-regulation of alpha oscillations corresponded with improved shooting accuracy, the findings suggest that neurofeedback can influence the neural mechanisms underlying precision motor skills. The results also reinforce the psychomotor efficiency hypothesis, as increased alpha power during the aiming period implies reduced cortical activation in temporal regions involved in analytical processing.

Beyond sports performance, the findings may have implications for professions that require fine motor precision under pressure, such as surgery, aviation, or law enforcement marksmanship. Training individuals to achieve efficient neural states could potentially enhance performance in these contexts as well.

At a broader scientific level, the work contributes to the growing literature exploring how brain oscillations regulate attention, motor planning, and cognitive control. It illustrates how neurofeedback can serve as both a training method and an experimental tool for probing causal relationships between neural dynamics and behavior.

Integrative Summary: Converging Evidence from Three Lines of Research

Taken together, these three studies paint a coherent and increasingly detailed picture of how neurofeedback relates to motor performance in sport. This final section synthesizes the take-away messages from the Yu et al. (2025) meta-analysis, the Cheng et al. (2023) qEEG study, and the Lo et al. (2025) neurofeedback experiment.

Key Messages from the Yu et al. (2025) Meta-Analysis

Yu et al. (2025) relate the effects of neurofeedback to psychomotor efficiency models in sports neuroscience, proposing that neurofeedback may enhance performance by promoting reduced conscious motor control, increased relaxation, efficient neural processing, and more automatic motor execution. These characteristics correspond to the automatic stage of motor learning and optimal performance states.

EEG neurofeedback shows moderate evidence for improving sports motor performance, particularly in studies with stronger methodological design. However, the literature remains heterogeneous and methodologically uneven, and future work should adopt standardized protocols and reporting practices such as the CRED-nf framework.

Key Messages from the Cheng et al. (2023) qEEG Study

The Cheng et al. (2023) study contributes to a growing body of research showing that elite athletic performance is linked to efficient neural processing rather than simply greater brain activation. In skilled marksmen, superior performance appears to depend on maintaining focused attention while minimizing interference from unnecessary cognitive processes. The findings provide empirical support for the psychomotor efficiency hypothesis and highlight specific neural markers that may reflect optimal performance states.

In particular, increased sensorimotor rhythm activity and reduced frontal-temporal coherence may indicate a mental state in which attention is stable and motor control is finely tuned.

The research also has practical implications for athlete training. Because EEG markers such as the sensorimotor rhythm can be targeted through neurofeedback training, the results may help guide the development of brain-based training methods aimed at improving performance in precision sports. More broadly, the study suggests that even among highly trained athletes, small differences in neural dynamics can influence success or failure in tasks that demand extreme precision.

Key Messages from the Lo et al. (2025) Neurofeedback Experiment

Neurofeedback training targeting alpha oscillations in the left temporal cortex can improve precision shooting performance in experienced athletes. Increased alpha power during the aiming period appears to reflect cortical quieting and reduced interference from verbal-analytical processes. Training one cortical region can influence activity across broader neural networks, as shown by bilateral increases in temporal alpha power.

Sustained practice over multiple neurofeedback sessions is likely necessary to produce meaningful neural and behavioral changes. The findings provide experimental support for the psychomotor efficiency hypothesis, suggesting that optimal motor performance depends on efficient rather than excessive brain activity.

Glossary

alpha activity: a pattern of brain waves in the frequency range of approximately 8–12 Hz commonly associated with relaxed but attentive mental states.

attentional control: a cognitive process referring to the ability to selectively focus on relevant stimuli while suppressing distractions, which is considered a key psychological factor influencing athletic performance.

beta band: a range of EEG frequencies typically between 13 and 30 Hz that is associated with alertness, active cognitive processing, and heightened cortical engagement.

biofeedback: a technique in which individuals receive real-time feedback about physiological signals, such as heart rate or brain activity, in order to learn voluntary control over those processes.

cerebral cortical arousal: a level of activation within the cerebral cortex reflecting the degree of neural engagement with cognitive or sensory processes.

coherence: a measure of synchronization between electrical signals recorded from different brain regions that reflects functional connectivity.

cortical arousal: a level of activation within the cerebral cortex that influences alertness, readiness for action, and information processing efficiency during cognitive or motor tasks.

effect size: a quantitative statistical measure that represents the magnitude of a relationship or difference observed in a study, commonly used in meta-analyses to compare results across multiple experiments.

electroencephalography (EEG): a noninvasive technique that records electrical activity from the brain using electrodes placed on the scalp.

Fast Fourier transformation: a mathematical algorithm used to convert a time domain signal such as EEG data into its component frequencies.

frontal midline theta: a pattern of brain activity in the 4–7 Hz range typically observed in frontal brain regions and associated with sustained attention and cognitive control.

heterogeneity: a statistical concept describing the degree of variability in effect sizes or outcomes among studies included in a systematic review or meta-analysis.

high alpha: a sub band of the alpha frequency range, typically around ten to thirteen hertz, often linked to task specific attentional processes.

low alpha: a sub band of the alpha frequency range, typically around eight to ten hertz, frequently associated with general cortical arousal or relaxation.

meta-analysis: a statistical technique that combines quantitative results from multiple independent studies to estimate an overall effect and identify patterns across research findings.

moderator: a variable that influences the strength or direction of the relationship between an intervention and its outcomes, such as training duration, participant characteristics, or neurofeedback protocol.

motor performance: the measurable execution of movement-related tasks, including accuracy, speed, coordination, and consistency, which are often evaluated in sports performance research.

neurofeedback: a form of biofeedback in which individuals receive real time information about their brain activity and learn to regulate it through operant conditioning.

neural efficiency: a concept proposing that skilled performers use fewer or more focused neural resources to perform tasks effectively.

performance outcome: a measurable indicator used to evaluate the effectiveness of an intervention, such as improvements in accuracy, reaction time, endurance, or sport-specific skill execution.

psychomotor efficiency hypothesis: a theory suggesting that expert motor performance involves selective activation of task relevant neural processes and suppression of task irrelevant processes.

publication bias: a systematic distortion in the scientific literature that occurs when studies with significant or positive findings are more likely to be published than studies with null or negative results.

randomized controlled trial (RCT): an experimental research design in which participants are randomly assigned to intervention or control groups to minimize bias and establish causal inference.

self-regulation: a psychological and neurophysiological capacity to consciously modulate internal states, including attention, emotion, and physiological responses, often targeted by neurofeedback training.

sensorimotor rhythm: a brain wave pattern in the 12–15 Hz range recorded over the sensorimotor cortex that is associated with motor control and focused attention.

spectral power: a measure of the magnitude of oscillatory activity within a specific frequency band of a signal such as an EEG recording.

systematic review: a structured synthesis of research studies that follows predefined methodological procedures to identify, evaluate, and summarize evidence on a specific topic.

T3 alpha: alpha frequency brain activity recorded over the left temporal region that has historically been associated with verbal analytical processing.

theta band: a frequency range of EEG activity typically between 4 and 7 Hz that is associated with drowsiness, memory processes, and certain attentional states.

training protocol: a structured set of procedures defining the parameters of an intervention, including electrode placement, frequency targets, feedback modality, session duration, and number of sessions.

References

Cheng, M. Y., Wang, C. H., Hung, T. M., & Chang, Y. K. (2023). QEEG markers of superior shooting performance in skilled marksmen: An investigation of cortical activity on the psychomotor efficiency hypothesis. Psychology of Sport and Exercise, 65, 102320. https://doi.org/10.1016/j.psychsport.2022.102320

Landers, D. M., Han, M., Salazar, W., Petruzzello, S. J., Kubitz, K. A., & Gannon, T. L. (1991). The influence of electrocortical biofeedback on performance in pre-elite archers. Medicine and Science in Sports and Exercise, 21(1), 123–129. https://doi.org/10.1249/00005768-199101000-00018

Lo, L.-C., Huang, C.-J., Hung, T.-M., Chang, Y.-K., & Kao, S.-C. (2025). The effect of left temporal EEG neurofeedback training on cerebral cortical activity and precision cognitive-motor performance. Research Quarterly for Exercise and Sport, 96(2), 486–496. https://doi.org/10.1080/02701367.2024.2441149

Larson, N. C., & Sherlin, L. (2023). Optimal performance. In I. Kazan, F. Shaffer, D. Moss, R. Lyle, & S. Rosenberg (Eds.). Evidence-based practice in biofeedback and neurofeedback (4th ed.). Association for Applied Psychophysiology and Biofeedback.

Lu, G., Zhang, C., Li, F., Wang, Y., & Zhao, X. (2025). Amateurs exhibit greater psychomotor efficiency than novices: Evidence from EEG during a visuomotor task. Frontiers in Psychology, 16, 1436549. https://doi.org/10.3389/fpsyg.2025.1436549

Ros, T., Baars, B. J., Lanius, R. A., & Vuilleumier, P. (2020). Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist). Brain, 143(6), 1674–1685. https://doi.org/10.1093/brain/awaa009 Ros, T., Théberge, J., Frewen, P. A., Kluetsch, R., Densmore, M., Calhoun, V. D., &

Lanius, R. A. (2013). Mind over chatter: Plastic up-regulation of the fMRI salience network after neurofeedback. NeuroImage, 65, 324–335. https://doi.org/10.1016/j.neuroimage.2012.09.046

Thompson, M., & Thompson, L. (2015). The neurofeedback book: An introduction to basic concepts in applied psychophysiology (2nd ed.). Association for Applied Psychophysiology and Biofeedback.

van Son, D., Wijsman, J., van Roon, A., van den Berg, M., & de Geus, E. J. C. (2020). EEG theta/beta ratio neurofeedback training in healthy females. Applied Psychophysiology and Biofeedback, 45(3), 195–210. https://doi.org/10.1007/s10484-020-09472-1

Yu, C.-L., Chen, H.-Y., Tsai, C.-L., Wang, C.-H., & Hung, T.-M. (2025). The effect of EEG neurofeedback training on sport performance: A systematic review and meta-analysis. Scandinavian Journal of Medicine & Science in Sports, 35, e70055. https://doi.org/10.1111/sms.70055

About the Author

Dr. John "Dusty" Raymond Davis is an adjunct lecturer in the Department of Psychiatry and Behavioural Neurosciences at McMaster University's Faculty of Health Sciences. His scholarly contributions include research on EEG changes in major depression and case studies on neurological conditions. ​

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