Occupational therapist Dr. Jean A. Ayres was one of the first to bring attention to sensory processing’s role in everyday function. Ayres described sensory integration as a behavioral response to sensory input and “explored the association between sensory processing and the behavior of children with learning, developmental, emotional, and other disabilities” [1
] (p. 136). Since Ayres’ theory in 1963, there have been many others who have further developed her theory to make advancements in the understanding of sensory processing. Occupational therapist Winnie Dunn created one of the most recognized models of sensory processing called Dunn’s Four Quadrant Model of Sensory Processing. Dunn’s Four Quadrant Model of Sensory Processing is based on two constructs: neurological thresholds and behavioral response. The neurological threshold construct refers to the threshold for response to a sensory stimulus and is described as ranging on a continuum from low to high. Individuals with low sensory thresholds may be quick to notice and respond to stimuli because their systems are easily activated by sensory stimuli. Individuals with high thresholds may not be as responsive, so they may miss stimuli that others respond to. Dunn suggests that neural regulation occurs as a balance of excitation and inhibition which creates thresholds for response. Each person has unique thresholds for responding to sensory information. Thresholds may not be the same for all sensory modalities. The second construct, behavioral response, also exists on a continuum based upon whether people have passive or active strategies in response to their environments. Though individuals with passive tendencies may internally respond to stimuli, they might not take action to change their environments, whereas at the active end of the continuum, individuals may tend to actively control the type and amount of sensory input in their environments [2
]. Dunn theorized that these constructs may be influenced by both genetic and environmental factors [2
These two constructs serve as axes that cross to form quadrants making Dunn’s Four Quadrant Model of Sensory Processing [3
]. The top, left quadrant arises from a combination of high neural thresholds and passive responding strategies. This is called low registration. The top, right quadrant is called Sensory Seeking with a pattern of high thresholds and active responding strategies. The bottom, left quadrant is the sensory sensitivity category with low thresholds and passive responding strategies. The bottom, right quadrant is a pattern with low thresholds and active responding strategies, referred to as sensory avoiding [1
Disruption in an individual’s sensory processing ability can affect engagement in occupations of daily life [6
]. As Brown and Dunn state, “areas of concern emerge only when a person’s sensory processing pattern seems incompatible with his or her desired or necessary life activity choices” [7
] (p. 5). This is when sensory processing becomes a concern of occupational therapy. According to the Sensory Processing Disorder Foundation [9
], the term Sensory Processing Disorder (SPD) is used to describe a condition in which a person encounters problems with his/her daily occupations due to how he/ she processes and responds to sensory information. The American Psychological Association’s review committee for the Diagnostic and Statistical Manual of Mental Disorders did not include SPD in the fifth edition because they judged that there was insufficient evidence supporting it as a stand-alone disorder [10
]. Currently SPD has been recognized as a distinct disorder by Diagnostic Classification: Zero to Three: Diagnostic Classification of Mental Health in Developmental Disorders in Infancy and Early Childhood [12
] and the Diagnostic Manual for Infancy and Early Childhood [10
]. Standardized assessments of sensory processing, such as Dunn’s Sensory Profile [14
], demonstrate normal distribution in scores. This allows clinicians to interpret scores falling outside of the first and second standard deviation as likely and probable indicators of SPD. Measured this way, SPD has been found to be present in a conservative estimate of 5% of the general population [15
] and is associated with a variety of diagnoses, including attention deficit hyperactivity disorder, Fragile X syndrome, autism spectrum disorders, developmental disability [16
], dysfunctional elimination syndrome [17
], and major affective disorders such as depression [18
Dunn and Brown [2
] conducted studies to compare children with and without disabilities according to Dunn’s model. Using factor analysis, they found that some typically developing children had similar sensory modulation patterns that could be observed in children with various disabilities. Similarly, Kinnealy, Koenig, and Smith [20
] found that healthy adults with Sensory Profile scores indicative of low thresholds reported lower quality of life indicators on the Short Form-36 Health Survey [21
]. Together, this provides evidence that intense sensory processing patterns are not exclusive to people diagnosed with disabilities. The focus of intervention should not be on the disability, or lack thereof, but instead on how the person functions in his/her environment given his/her intense sensory processing patterns [2
]. Engel-Yeger, Serafini, and colleagues [18
] found patterns of association between distinct characteristics of major affective disorders (such as depression, anxiety, irritability, impulsivity, alexithymia, and hopelessness) with scores indicative of extreme sensory processing patterns with Dunn’s model. They suggest that sensory processing patterns may be trait markers, which allows tailoring of intervention.
As part of a study of the construct validity of the Adult/Adolescent Sensory Profile, Brown, and colleagues [3
] used the physiological measure of skin conductance to examine response and habituation to stimuli as a proxy for the construct of neurological threshold. The researchers delivered a repeated auditory stimulus to participants while measuring skin conductance. Results indicated that people with sensory sensitivity and sensory avoiding patterns were more responsive, as measured by changes in skin conductance, than people with low registration and sensory seeking patterns. They also found that people with sensory sensitivity and sensory seeking patterns took more trials to habituate to the stimuli than people with the sensation avoiding and low registration patterns [3
]. As the Dunn’s model is widely used in clinical settings for assessment, client education, and intervention planning, it is important that its underlying constructs are tested. One way to validate a model is to compare its constructs to external measurements that are similarly described.
Dunn’s behavior response axis describes individuals’ characteristic actions taken in response to sensory stimulation. The language in which it is described is reminiscent of the personality characteristic of introversion/extraversion, which reflects how individuals’ respond to social stimulation. Psychologist Eysenck [21
] developed a four-quadrant personality model, which described introversion/extroversion on a horizontal axis and neuroticism on a vertical axis [23
]. He described individuals who seek stimulation due to a low arousal level as extraverts, and individuals who avoid stimulation due to naturally high arousal levels as introverts [24
]. Neuroticism was viewed on a continuum from low neuroticism describing individuals whose emotions fluctuate very little and high neuroticism describing individuals whose emotions fluctuate greatly [24
]. Sato [23
] created the Eysenck Personality Questionnaire-Brief Version based on the Eysenck Personality Questionnaire-Short Version, one of several versions based on Eysenck’s personality theories and original personality questionnaire. The EPQ-BV measures the two main personality traits from Eysenck’s theory: introversion/extraversion and neuroticism [24
The similarities in the verbiage of Dunn’s behavioral response aspect of sensory processing and the introversion/extraversion aspects of Eysenck’s personality model warrant exploration of whether the latter can be used to validate the former. Sato, in his revision of the Eysenck Personality Questionnaire to create a brief version, summarized the Eysenck’s research on the personality dimensions of introversion and extroversion:
“Compared to introverted individuals, extraverted individuals naturally have a lower arousal level. This makes extraverted individuals seek stimulation to raise their arousal level. In contrast, the naturally high arousal level of introverted individuals makes them avoid stimulation as much as possible. This is considered to be why introverts tend to like quiet activities while extraverts tend to like stimulating activities” [24
] (p. 106)
What Sato termed “arousal level
” in his summary, Eysenck [25
] may be interpreted as referring to “sensory threshold
” (p. 100). Dunn describes sensory processing differences similarly to Eysenck’s ideas on introversion and extraversion:
“Young children with high ‘sensory’ thresholds would respond to very few stimuli, while young children with low thresholds would respond to many stimuli. On the other end of the continuum, young children can respond to counteract their thresholds, these children might either try to exert excessive energy seeking stimuli to try to meet high thresholds or exert energy to avoid triggering low thresholds.” [4
] (p. 27)
Both authors refer to sensory thresholds and the way in which individuals respond to sensory information in similar manners; leading to the possibility that what Eysenck refers to as the continuum between introversion and extraversion may be the same construct as what Dunn refers to as behavioral regulation based on sensory threshold.
The description of the threshold axis invokes neurological processing of sensory stimuli. Physiological measurements of sensory responses may be useful in assessing this axis. Sensory gating, a process related to modulation, is associated with functions of attention, processing speed, and working memory [26
]. This is a neural process by which the brain responds to stimuli and filters out extraneous information. This is often measured by encephalography studies. Electroencephalography (EEG) records electrical brain activity through electrodes placed on the scalp. Event related potentials (ERPs) are obtained by giving a sensory stimulus multiple times and averaging the EEG segments surrounding the event [27
]. Changes in the magnitude of ERPs in response to repeated stimuli are indicative of the brain’s modulation of sensory stimulation, called gating. Many studies use an ERP called the P50 as their measure of sensory gating. The P50 is a positive going wave which generally occurs in the cortex 40–90 milliseconds after the stimulus. It is thought that the amplitude of P50 may reflect the degree of neural processing afforded to the stimulus. The amount of sensory gating that occurs for a pair of stimuli is represented as a ratio that is measured by dividing the peak amplitude of the P50 of the second stimulus as a proportion of the peak amplitude of the P50 of the first stimulus. The first stimulus is generally referred to as ‘conditioning’
and the second stimulus is the ‘test’
, thus the ratio is called a T/C ratio. A smaller T/C ratio is indicative that sensory gating has occurred [26
Davies and Gavin used EEG to test the diagnostic validity of sensory processing disorder. In 2007, Davies and Gavin tested the hypothesis that behavioral dysfunction in children with sensory processing disorders is related to dysfunction in brain function. To do this, they used the P50 gating paradigm with children with SPD, as verified by Dunn’s Sensory Profile, and typically developing children. Children with SPD showed less sensory gating (mean T/C ratio of 0.77 ± 0.42) than typically developed children (mean 0.58 ± 0.31, p
< 0.05). This suggests that children with SPD may have less ability to filter out extraneous sensory input. In addition, children with SPD were either hyper-responsive or hypo-responsive to the stimulus. In a cross-sectional analysis, the researchers factored in maturation as a variable in sensory processing. Results indicated that gating was not improved in older children with SPD as it was in older typically developing children [28
]. A subsequent study by Davies, Chang, and Gavin [26
] reports that children with SPD showed disorganized patterns of brain activity in response to both intensity and frequency of stimuli compared to typically developed peers.
Dunn’s model has clinical utility, and the associated standardized assessment has strong psychometrics. In this study, we examined the constructs that underlie the model, behavioral response and threshold. We tested the hypotheses that these axes of the model, as measured by the sensory profile, are ordinal ranges and that variation along the ranges is consistent with variation in external measures of characteristics that may also reflect sensory processing as described by Dunn. To begin, we converted raw scores of the Adult/Adolescent sensory profile to axis scores. To assess whether axis scores were consistent with the clinical presentation of Sensory Profile results, we compared the derived scores and quadrants to the raw and normative scores of the sensory profile. Next, we compared variation in behavioral response and threshold with variation in introversion/extraversion axis of Eysenck’s personality model [23
], respectively. Finally, we compared variation in threshold to variation in somatosensory event related potentials and sensory gating.
Dunn’s four-quadrant model of sensory processing has clinical utility [2
], and the associated standardized assessment has strong psychometrics. Here we examined the axis constructs that underlie the model, behavioral response and threshold, assessing them for scaling and relation to other traits. The findings suggest that behavioral response axis of Dunn’s model may not reflect a construct with ordinal range, suggesting that behavior response patterns may not reflect a spectrum of characteristic styles. Quadrant scores may reflect individuals’ most common response strategies, but across settings, they may use varieties of strategies, creating blur in scores on the axis. This may empower clinicians to take a top-down approach of teaching clients coping strategies that will help them deal with any sensory environment without beginning with bottom-up intervention strategies that change endogenous behavior response patterns.
Though passive and active behavior response patterns are described with language similar to Eysenck’s concepts of introversion and extraversion [24
], there was no difference in I/E scores for participants with passive and active BR patterns. This suggests the concepts are distinct from one another; that Dunn’s model of may distinctly describe individuals’ behavior responses to sensory stimuli transmitted through the nervous system’s afferent systems, irrespective of their style of social engagement Although individuals assign meaning to sensory stimuli according to past experiences and current context [31
], their behavior response may reflect momentary intention to tolerate, reduce, or intensify sensory stimulation. Further research is needed to explore the differences and similarities between behavior regulation and introversion/extraversion.
The threshold axis of Dunn’s model may reflect an ordinal range, with calculated threshold scores reflecting sensory processing patterns on a spectrum from low to high. This may suggest that threshold is a personal, endogenous characteristic. This may lend support for clinical interventions for individuals who are challenged by having a low or high threshold to employ bottom-up methods such as sensory integration therapy [32
] where changes in threshold may result and translate into improved function.
In our findings, neither the amplitude of somatosensory evoked event related potentials and nor their gating differed by participants categorization using sensory profile scores or calculated threshold scores. This may suggest that in healthy, typical adults, the brain’s reaction to activation of a somatosensory pathway is not a direct correlate of Dunn’s concept of threshold. It may be that somatosensory processing in well-developed, healthy central nervous systems does not have much inter-individual variation that would create a range of SERP amplitude and gating. Our findings do not, however, rule out the use of EEG to detect immature or problematic sensory processing. Davies and colleagues (Davies & Gavin, 2007; Davies, Chang, & Gavin, 2010; Davies, Change, Gavin, 2009) demonstrated differences in sensory gating in children with clinically documented sensory processing disorders. Further research is needed to establish biomarkers and describe neurological underpinnings of sensory processing.
This study lends support to Dunn’s four-quadrant model as a conception of sensory processing patterns Though the behavior response axis did not show ordinal scaling, inspection of Figure 1
A reveals that axis scores for participants passive response patterns were negative and those for participants with active response patterns were positive, suggesting distinctions between them. The threshold axis did present as a scale ranging from low to high. When calculated axes scores were plotted, the derived quadrant had high consistency with the quadrant in which participants had their highest raw score. Together, this may support the idea that individuals have a characteristic sensory processing pattern arising from the interaction of behavior response and threshold. This may support development of quadrant-specific interventions.
Participants represent a convenience sample. We recruited in the Midwest on a college campus and public/community locations via flyers and word of mouth. Flyers included a photograph of an individual wearing the EEG cap and referenced “sensory processing”. Individuals who chose to respond to recruiting may represent a different segment of society. We had few participants who were categorized as having either passive behavior regulation or low threshold patterns of processing. Perhaps individuals who typically employ passive behavior regulation are less likely to initiate research participation. It is also possible that individuals with low threshold judged the research procedures to be aversive. These possibilities may account for underrepresentation of these patterns in our sample. Conversely, these patterns may be uncommon in healthy, typical adults. In any case, not having a full range of response patterns may limit our ability to observe differences and trends in our data. Future research should include participants with broader ranges of sensory processing patterns. This may require research procedures to be modified to lower barriers to enrollment and enhance participant comfort. Researchers may want to specifically advertise their studies toward individuals who consider themselves to have passive behavior response and/or low threshold processing patterns. Inclusion of clinical populations, such as individuals with affective disorders or those with diagnosed sensory processing disorders, may extend the range of scores and allow patterns and trends to emerge from the analyses conducted here. In order to detect a large effect size, the one-way ANOVA needs an estimated sample size of 112 [33
], which we had for the active BR and high T categories but fell far short of for the passive BR and low T categories.
Out of our sample of 138 participants for whom we had EEG data, only 38 and 74 had P50 waves of at least 0.5 µV for analysis of baseline and gating responses, respectively. This likely reflects use of a low intensity MNS. The MNS was well below the motor threshold in order to maximize participant comfort and compliance, as well as make the stimulus more similar to tactile stimulation rather than proprioceptive input, painful stimulus, or an electrical impulse in the median nerve. However, the intensity of MNS has been suggested to not have an influence on gating [34
]. Still, in future studies, researchers may wish to use a more robust MNS stimulus or event related potentials evoked via other sensory modalities.
These limitations may have led to Type 2 errors, perhaps reflecting poor power to detect differences that would support they hypotheses. Therefore, we do not feel that the non-significant findings are not sufficient grounds for dismissing the axes constructs of Dunn’s model.