The Biological Basis of Attention & Concentration


Raymond Deck III
Clinical Psychology, Saybrook University
Psy3015: Cognition and Affect in Human Behavior
Dr. Melissa Oleshansky
June 15, 2023

The Biological Basis of Attention & Concentration

Attention-deficit hyperactivity disorder (ADHD) is the single most researched psychological malady. More research literature is published each year regarding ADHD than any other entry in the Diagnostic and Statistical Manual (DSM) (Barkley R. A., 2015). And yet, there are still sharp differences of opinion about not only the biological basis of attentional deficit but how many different flavors of subtypes should be recognized by the medical community (Barkley R. , 2013). Much of the research regards ways to replace the need for or diminish the side effects of the most common pharmacological intervention for attentional challenges—prescription methamphetamine stimulants (Alexander, 2021). And while many environmental causes have been effectively ruled out as causes of ADHD, there is not broad agreement on the nature of the neurological condition that creates this cluster of symptoms. This paper will explore three competing theories of the case, propose a mental model and non-pharmacological treatment strategy to harmonize them into a unified understanding of the brain’s capacity for attention.

Defining Attention & Concentration

Attention and concentration are related cognitive functions, but they differ in their specific definitions and implications. Attention is generally understood to refer to the cognitive process of selectively focusing on one aspect of the environment while ignoring or filtering out other things (Barkley R. A., 2015). It is about focusing cognitive resources on relevant stimuli and processing them. Attention can be either voluntary (top-down) or reflexive (bottom-up). Top-down attention refers to when attention is directed by goals or expectations, such as when you are looking for a friend in a crowded room. Bottom-up attention, on the other hand, is driven by the properties of the stimuli themselves, such as when a loud noise or bright flash captures your attention. Concentration, also known as sustained attention, is the ability to maintain attention on a task over an extended period of time. It is a form of attention but implies a longer-term, more focused, and persistent form of attention. It’s the cognitive process that enables sustained focused on a task without getting distracted (Barkley R. A., 2018).

So, while both attention and concentration involve focusing cognitive resources, attention is more about selecting stimuli to process, and can be driven by either the stimuli themselves or by goals and expectations, whereas concentration is about maintaining that focus over a period of time, especially in the face of potential distractions.

Jha (2021) offers a metaphor to help explain the differences. If we imagine the brain’s focus as a sort of light, it has a spotlight mode in which attention is directed narrowly at a chosen point of focus. This spotlight is attention. The brain also has a floodlight mode in which it maintains broad situational awareness without judiciously filtering stimuli, almost seeking interruption. It is the floodlight mode that we engage while driving, cycling through several important sets of data including the traffic ahead, the instrumental panel, the mirrors, and the sound and feel of the car itself. Using this metaphor, attention is the spotlight, concentration is the spotlight locked into the ‘on’ position, and there is not a common parlance to describe the floodlight mode which is a cognitive process of monitoring multiple shifting sets, despite most people recognizing it as a condition distinct from narrowly focused attention.

Attention disorders are experienced differently by those who live with them from loved ones. Loved ones, commonly parents and teachers, experience attentional disorders as a failure to exercise this attention-directing equipment (Dang et al., 2007) while those who live with an attentional disorder have described their experience as having missing or faulty equipment (Bussing et al., 2011) as a failure of this system in one form or another. Either the spotlight portion of the brain’s attention structure is broken, the lock for the spotlight mode is broken, or the switch itself is faulty in some way.

This spotlight/floodlight metaphor may prove a useful theoretical framework for exploring the biological basis of the brain’s attention system, the function of the relevant neurological structures, and the mechanism of action for various treatments. 

Literature Review: Causes of Attentional Deficits

There is a long and fruitless history of research to explain attentional deficits in various environmental factors. Television watching (Thapar et al., 2013), deficiencies in polyunsaturated fatty acids, consumption of sugar (Barkley R. A., 2013), zinc & magnesium deficiencies (Sinn, 2008), and consumption of food dyes (Schab & Trinh, 2004) have all been effectively ruled out as causes. There is considerable (though not conclusive) evidence that genetics play is significant role in attentional disorders. A genome-wide association study (GWAS) is a type of quantitative study that seeks to correlate genome patterns with expressed traits to identify the location in the genome relevant to the trait in question (Ferneandez et al., 2017). Several studies of this type have been attempted regarding attention deficits. But for a multi-factor condition like attention deficit hyperactivity disorder (ADHD) and other forms of attentional impairment, an enormous sample size would be required to clear the threshold for statistical significance and none of the individual attempts have managed to do so. But a meta-analysis of all prior GWAS research into ADHD did clear the threshold and found five locations of interest in the human genetic code (Demontis et al., 2018).

Neuroanatomy of Attention: 3 Theories

The mid-brain and prefrontal cortex have been the focus of research regarding the biological basis of attention and concentration (Curatolo et al., 2010) with special focus on the midbrain structures of the thalamus and hypothalamus with a more recent vein of research considering the state of the prefrontal cortex as a downstream impact of brain-wide arousal.

With the vagus nerve terminating in the mid-brain, the nearby structures effectively serve as the mind-body connection and act as a sort of master switch, determining the overall state for the rest of the brain (Moini & Piran, 2020). Specifically, the thalamus is often described as the « relay station » of the brain because it transmits sensory and motor signals to the cerebral cortex. Almost all sensory information (except for the sense of smell) passes through the thalamus before reaching higher brain centers where it is interpreted. This includes visual, auditory, somatosensory (touch), and gustatory (taste) information. This positions it to act as a sort of stimulus gate or filter, effectively narrowing or broadening the focus of attention as needed. The hypothalamus, thus named because it is both physically below and earlier in the signal chain from the thalamus, is a small region at the base of the brain that plays a crucial role in many important functions, including releasing hormones and regulating body temperature, hunger, thirst, sleep, mood, and sex drive. It serves as a link between the endocrine system and the nervous system via the pituitary gland and is vital for maintaining the body’s homeostasis. For example, when dehydrated, the hypothalamus sends a signal to release antidiuretic hormone (ADH) to conserve water in the body. It would be an oversimplification to say that the thalamus filters stimuli that a person is consciously aware of, and the hypothalamus filters stimuli which the brain is unconsciously aware of, but such a distinction is directionally correct if not precisely so. The famous-among-humanistic-psychologists text A General Theory of Love (Lewis et al., 2000) theorized that these structures and their role in regulating the limbic system were essential in the formation of human relationships, a theory which has been explored and expanded on since under the name interpersonal neurobiology. Polyvagal theory, the work of Steve Porges (2017), is an expanded application of this thinking to consider the limbic system’s involvement in many other human states and activities including mood and attention.

Paul Swingle: Theta-beta ratio in the mid brain

Building further on the work of these scholars, Paul Swingle has hypothesized that that the function of these structures correlates with the relative amplitude of various brainwave frequencies, and has documented his success in treating attentional deficits with neurofeedback by training the brain to produce the desired amounts of the target brainwave frequencies (Swingle, 2015). Specifically, the upper end of the beta frequency range—often called hi-beta, between 20 and 30hz—correlates with broad situational awareness and general arousal while the bottom end of the beta frequency range—often called lo-beta, between 15–20hz—is associated with narrow focused attention. While the Theta frequency range—3.5–7.5hz—is associated with daydreaming, fantasizing, drowsiness, and semi-wakefulness (Soutar & Longo, 2011). Using a Qualitative Electroencephalogram (QEEG), Swingle measures the relative amplitude of these frequencies and uses the resulting ratio—called theta-beta ratio (TBR)—as a proxy for attention. When theta and hi-beta are low relative to lo-beta, the subject’s attention is constricted onto a narrow point of focus. When hi-beta is elevated, the brain is configured for broad situational awareness, tracking multiple rapidly changing sets. Elevated theta in the midbrain is suggestive of fatigue or sluggishness. Swingle—and many other practitioners replicating his approach—then uses neurofeedback training to teach his client’s brains to apply the correct level of stimulus filter for the situation. The desired state us typically a TBR of between twice and three times as much lo-beta as theta and hi-beta, denoting the ability to enter and sustain deep concentration on cue (Soutar & Longo, 2011).

Thompsons: Surplus alpha in the prefrontal cortex

More recently, neurofeedback practitioners have noticed surplus alpha frequency (8–12hz) brainwaves in clients who present for help with attentional challenges (Thompson & Thompson, 2015). Many of these clinicians were using Swingle’s TBR approach and seeing success for many (but not all of) their clients with it (Jalali & Sho’ouri, 2021). The Thompsons (2015) hypothesized that surplus alpha in the prefrontal cortex is a sort of residual effect of sustained limbic arousal. In other words, if the brain is on high alert for an extended period of time and is in need of a rest & recovery cycle, the prefrontal cortex (where most conscious thought occurs) is flooded with a slow frequency activity like alpha and theta creating a state of drowsiness. But the Thompsons theorized that for some of their clients this condition is not residual and can manifest as slow reaction time, inability to decide, inability to complete a thought. They found success in treating this condition with a similar neurofeedback approach but targeting different locations and frequencies.

I observe a similarity between the Thompsons (2015) clinical observations and Sluggish Cognitive Tempo (SCT), a condition not included in the Diagnostic Statistical Manual (DSM), but which many attention/concentration researchers believe to be distinct from either of the ADHD variants (Barkley R. A., 2018). Sometimes called Concentration Deficit Disorder, SCT is typified by compulsive mind wandering in a way that ADHD is typified by hyperactivity and inattention. Though it cooccurs 50 percent of the time with the inattentive subtype of ADHD, it has been differentiated form it by several large diagnostic studies (Barkley R. , 2013).

Jha: Faulty switch

Jha (2021), the scholar who provided the fruitful spotlight metaphor, proposes a third neurological explanation for symptoms of attentional deficit: faulty switch. In her view, attentional symptoms are most often caused by a failure of the switching mechanism between the two gross states—broad situational awareness and narrow focused attention—and relief from ADHD symptoms can be found by systematically training the brain to move from one condition to the other on cue. The training method described in her book is a particular form of mindfulness practice—a technique that has proven effective in treating ADHD among adults and adolescents (Zylowska & Mitchell, 2021)—which is informed by her research to improve this mental muscle or capacity for switching states.

If true, this expression of ADHD would be especially difficult to detect using a point-in-time assessment like the QEEG, which would at some moments show a pronounced TBR pattern and at other times reveal none. To detect the “faulty switch” expression of attention deficit, the diagnostic best practice of multi-modal, multi-setting, multi-reporter data becomes especially important (Sparrow & Erhardt, 2014). Similar to a check engine light that goes off whenever the car is taken to the mechanic, given that the neurological state of concern is intermittent, accurate diagnostics would require catching the client in a specific state.

Toward Integration: Harmonizing These 3 Theories

These three theories for the neurological basis for attentional deficits: TBR pattern in the mid-brain from Swingle (2015), surplus alpha in the prefrontal cortex from the Thompsons (2015), and the diminished capacity for switching between states from Jha (2021)—correlate well to the three widely understood attentional deficit symptom clusters: ADHD-hyperactivity, ADHD-inattention, and SCT. The hyperactive subtype of ADHD is a highly externalized and physical symptom cluster, including an intolerance for physical stillness and a quickly shifting target of focus. This expression is consistent with elevated hi-beta frequency activity throughout the brain, particularly in the mid-brain where the thalamus would be overwhelmed by stimuli and unable to serve its gating function. SCT is the opposite presentation in many ways, with internalizing behavior like compulsive mind wandering and delayed reaction time caused by surplus slow wave activity in the prefrontal cortex and mid-brain. In this presentation, the thalamus is not overwhelmed by the volume stimuli but instead lulled into inactivity by the slow wave activity in that region of the brain. While the inattentive subtype is often imagined as an internalized condition in comparison to the hyperactive subtype, but in effect it splits the difference between it and SCT. It may be possible to organize these conditions (and the undiscussed neurotypical alternative) into a matrix with the two spectra being attention and concentration.


This approach to the full range of attention and concentration deficits offers a way to harmonize these three theories and neurofeedback offers a way to treat each presentation differently. Swingle’s approach would likely be effective for the hyperactive subtype, The Thompsons’ for sluggish cognitive tempo and alpha-driven inattention, and a modified Swingle would be effective as a technological aid in Jha’s approach to the faulty switch hypothesis. But rather than relying solely on symptom scales like many primary care providers do when diagnosing ADHD (Chan et al., 2005), the QEEG offers clinicians the chance to look for the nexus of expressed traits and the underlying brain state and tune an intervention—whether neurofeedback (Jalali & Sho’ouri, 2021), pharmacological (Alexander, 2021), or otherwise (Zylowska & Mitchell, 2021)—to the specific neurological presentation of each individual.

Opportunity for Future Research

The mental model proposed in this paper is theoretical but would be testable especially given the size and diversity of QEEG data available in various research databases. The trick would be gaining access to the corresponding symptom scales to enable regression analysis to identify the power factor of various brain traits as correlates to symptom clusters. Research questions I would bring to a normative database of QEEG brain scans might include:

  1. To what extent does hyperactivity symptoms correlate to surplus hi-beta in the midbrain?
  2. To what extent do SCT symptoms correlate to surplus alpha in the midbrain?
  3. To what extent does mid-brain TBR correlate to inattention symptoms?

By asking these questions of the data, a better understanding of the neurological processes underlying attentional deficits may open new pathways for treatment of both ADHD and SCT.


I hope the future of research about ADHD and SCT focuses more on the underlying neurological and biological patterns that produce these symptom clusters in an attempt to harmonized the lab-based QEEG research with the clinical observations that have been made by neurofeedback practitioners. Each of the prevailing theories derives from skilled practitioners approaching the same situation with different tools and different goals. I hope we can integrate these perspectives into a cohesive understanding of human attention.


Alexander, S. (2021, January 25). Know Your Amphetamines. Astral Codex Ten:

Barkley, R. (2013). Distinguishing sluggish cognitive tempo from ADHD in children and adolescents: Executive functioning, impairment, and comorbidity. Journal of Clinical Child & Adolescent Psychology, 42(2), 161-173.

Barkley, R. (2018). Psychological Assessment of Children with ADHD. In R. Barkley, Attention-Deficit Hyperactivity Disorder (pp. 455-474). New York, NY: Guilford Press.

Barkley, R. A. (2013). Taking charge of ADHD: The complete, authoritative guide for parents. New York, NY: Guilford Press.

Barkley, R. A. (2015). History of ADHD. In R. A. Barkley, Attention-Deficit Hyperactivity Disorder (pp. 3-50). New York, NY: Guilford Press.

Barkley, R. A. (2018). Concentration Deficit Disorder (Sluggish Cognative Tempo). In R. A. Barkley, Attention Deficit Hyperactivity Disorder: A handbook for diagnosis & treatment (pp. 435-454). New York, NY: Guilford Press.

Bussing, R., Koro-Ljungberg, M., Noguchi, K., Mason, D., Mayerson, G., & Garvan, C. (2011). Willingness to use ADHD treatments: A mixed methods study of perceptions. Social Science & Medicine, 66(1), 92-100.

Chan, E., Hopkins, M., Perrin, J., Herrerias, C., & Homer, C. (2005). Diagnostic Practices for Attention Deficit Hyperactivity Disorder: A National Survey of Primary Care Physicians. Ambulatory Pediatrics, 201-208.

Curatolo, P., D’Agati, E., & Moavero, R. (2010). The neurobiological basis of ADHD. Italian Journal of Pediatrics.

Dang, M., Warrington, D., Tung, T., Baker, D., & Pan, R. (2007). A School-Based Approach to Early Identification and Management of Students with ADHD. The Journal of School Nursing.

Demontis, D., Walters, R., Martin, J., Mattheisen, M., Als, T., & Agerbo, E. (2018). Discovery of the first genome-wide significant risk loci for ADHD. Nature Gentics, 1(4), 63-75.

Ferneandez, T., Gupta, A., & Hoffman, E. (2017). Assessing risk: gene discovery. In A. Martin, F. Volkmar, & M. Bloch, Lewis’s Child and Adolescent Psychiatry: A Comprehensive Textbook (pp. 246-261). Philadephia, PA: Wolters Kluwer Health.

Jalali, P., & Sho’ouri, N. (2021). Neurofeedback Training Protocol Based on Selecting Distinctive Features to Treat or Reduce ADHD Symptoms. Clinical EEG Neuroscience, 414-421.

Jha, A. (2021). Peak Mind. New York, NY: HarperOne.

Lewis, T., Amini, F., & Lannon, R. (2000). A General Theory of Love. Vintage Books.

Moini, J., & Piran, P. (2020). Functional and Clinical Neuroanatomy. Cambridge, MA: Academic Press.

Porges, S. W. (2017). The Polyvagal Theory. New York: W. W. Norton & Company.

Schab, D. W., & Trinh, N.-H. (2004). Do artificial food colors promote hyperactivity in children with hyperactive syndromes? A meta-analysis of double-blind placebo-controlled trials. Journal of Developmental & Behavioral Pediatrics, 423-234.

Sinn, N. (2008). Nutritional and dietary influences on attention deficit hyperactivity disorder. Nutritional Review, 558-568.

Soutar, R., & Longo. (2011). Doing Neurofeedback. San Francisco: ISNR Research Foundation.

Sparrow, E., & Erhardt, D. (2014). Essentials of ADHD Assessment for Children and Adolescents. Hoboken, NJ: John Wiley & Sons.

Swingle, P. G. (2015). Adding Neurotherapy to Your Practice. New York, NY: Springer.

Thapar, A., Cooper, M., Eyre, O., & Langley, K. (2013). What have we learnt about the causes of ADHD? Journal of Child Psychology and Psychiatry.

Thompson, M., & Thompson, L. (2015). The Neurofeedback Book. Toronto: The Association for Applied Psychophysiology & Biofeedback.

Zylowska, L., & Mitchell, J. (2021). Mindfulness for Adult ADHD. New York, NY: Guildford Press.