Neurocognitive mechanisms in compulsive sexual behavior disorder (2018) – Excerpts analyzing Prause et al., 2015

Link to PDF of full paper – Neurocognitive mechanisms in compulsive sexual behavior disorder (2018).

Excerpt analyzing Prause et al., 2015 (which is citation 87)

A study using EEG, conducted by Prause and colleagues, suggested that individuals who feel distressed about their pornography use, as compared to a control group who do not feel distress about their use of pornography, may require more/greater visual stimulation to evoke brain responses [87]. Hypersexual participants—individuals‘ experiencing problems regulating their viewing of sexual images’ (M=3.8 hours per week)—exhibited less neural activation (measured by late positive potential in the EEG signal) when exposed to sexual images than did the comparison group when exposed to the same images. Depending on the interpretation of sexual stimuli in this study (as a cue or reward; for more see Gola et al. [4]), the findings may support other observations indicating habituation effects in addictions [4]. In 2015, Banca and colleagues observed that men with CSB preferred novel sexual stimuli and demonstrated findings suggestive of habituation in the dACC when exposed repeatedly to the same images [88]. Results of the aforementioned studies suggest that frequent pornography use may decrease reward sensitivity, possibly leading to increased habituation and tolerance, thereby enhancing the need for greater stimulation to be sexually aroused. However, longitudinal studies are indicated to examine this possibility further. Taken together, neuroimaging research to date has provided initial support for the notion that CSB shares similarities with drug, gambling, and gaming addictions with respect to altered brain networks and processes, including sensitization and habituation.

COMMENTS: The authors of the current review agree with six other peer-reviewed papers (1, 2, 3, 4, 5, 6.): Lower EEG readings mean that subjects are paying less attention to the pictures. They were bored (habituated or desensitized). The lead author claims these results “debunk porn addiction”, but other researchers disagree with her over-the-top assertions. You have to ask yourself – “What legitimate scientist would claim that their lone anomalous study has debunked a well established field of study?”

  1. Prause N, Steele VR, Staley C, Sabatinelli D, Proudfit GH. Modulation of late positive potentials by sexual images in problem users and controls inconsistent with “porn addiction”. Biol Psychol. 2015;109:192-9.


October 2018, Current Sexual Health Reports


Purpose of review: The current review summarizes the latest findings concerning neurobiological mechanisms of compulsive sexual behavior disorder (CSBD)and provides recommendations for future research specific to the diagnostic classification of the condition.

Recent findings: To date, most neuroimaging research on compulsive sexual behavior has provided evidence of overlapping mechanisms underlying compulsive sexual behavior and non-sexual addictions. Compulsive sexual behavior is associated with altered functioning in brain regions and networks implicated in sensitization, habituation, impulse dyscontrol, and reward processing in patterns like substance, gambling, and gaming addictions. Key brain regions linked to CSB features include the frontal and temporal cortices, amygdala, and striatum, including the nucleus accumbens.

Summary: Despite much neuroscience research finding many similarities between CSBD and substance and behavioral addictions, the World Health Organization included CSBD in the ICD-11 as an impulse-control disorder. Although previous research has helped to highlight some underlying mechanisms of the condition, additional investigations are needed to fully understand this phenomenon and resolve classification issues surrounding CSBD.


Compulsive sexual behavior (CSB) is a debated topic that is also known as sexual addiction, hypersexuality, sexual dependence, sexual impulsivity, nymphomania, or out-of-control sexual behavior [1-27]. Although precise rates are unclear given limited epidemiological research, CSB is estimated to affect 3-6% of the adult population and is more common in men than women [28-32]. Due to the associated distress and impairment reported by men and women with CSB [4-6, 30, 33-38], the World Health Organization (WHO) has recommended including Compulsive Sexual Behavior Disorder(CSBD)in the forthcoming 11th edition of the International Classification of Diseases (6C72)[39]. This inclusion should help increase access to treatment for unserved populations, reduce stigma and shame associated with help-seeking, promote concerted research efforts, and increase international attention on this condition[40, 41].We acknowledge that over the last 20 years there have been varying definitions used to describe dysregulated sexual behaviors often characterized by excessive engagement in nonparaphilic sexual activities (e.g., frequent casual/anonymous sex, problematic use of pornography). For the current review, we will use the term CSB as an overarching term for describing problematic, excessive sexual behavior.

CSB has been conceptualized as an obsessive–compulsive-spectrum disorder, an impulse-control disorder, or addictive behavior [42, 43]. The symptoms of CSBD are like those proposed in 2010forthe DSM-5 diagnosis of hypersexual disorder [44]. Hypersexual disorder was ultimately excluded by American Psychiatric Association from DSM-5 for multiple reasons; the lack of neurobiological and genetic studies was among the most noted reasons [45, 46]. More recently, CSB has received considerable attention in both popular culture and social sciences, particularly given health disparities affecting at-risk and underserved groups. Despite the considerable increase in studies of CSB (including those studying “sexual addiction,” “hypersexuality,” “sexual compulsivity”), relatively little research has examined neural underpinnings of CSB [4, 36]. This article reviews neurobiological mechanisms of CSB and provides recommendations for future research, particularly as related to diagnostic classification of CSBD.

CSB as an Addictive Disorder

Brain regions involved in processing rewards are likely important for understanding the origins, formation, and maintenance of addictive behaviors [47]. Structures within a so-called ‘reward system’ are activated by potentially reinforcing stimuli, such as addictive drugs in addictions. A major neurotransmitter involved in processing rewards is dopamine, particularly within the mesolimbic pathway involving the ventral tegmental area (VTA) and its connections with the nucleus accumbens (NAc), as well as the amygdala, hippocampus, and prefrontal cortex [48]. Additional neurotransmitters and pathways are involved in processing rewards and pleasure, and these warrant considerations given that dopamine has been implicated to varying degrees in individual drug and behavioral addictions in humans [49-51].

According to the incentive salience theory, different brain mechanisms influence motivation to obtain reward (‘wanting’) and the actual hedonic experience of reward (‘liking’) [52]. Whereas ‘wanting’ may be closely related to dopaminergic neurotransmission in the ventral striatum (VStr) and orbitofrontal cortex, networks dedicated to creating wanting motivations and pleasurable feelings are more complex [49, 53, 54].

VStr reward-related reactivity has been studied in addictive disorders such as alcohol, cocaine, opioid use disorders, and gambling disorder[55-58]. Volkow and colleagues describe four important components of addiction: (1) sensitization involving cue reactivity and craving, (2) desensitization involving habituation, (3) hypofrontality, and (4) malfunctioning stress systems[59]. Thus far, research of CSB has largely focused on cue reactivity, craving, and habituation. The first neuroimaging studies of CSB were focused on examining potential  similarities between CSB and addictions, with a specific focus on the incentive salience theory that is based on preconscious neural sensitization related to changes in dopamine-related motivation systems[60]. In this model, repeated exposure to potentially addictive drugs may change brain cells and circuits that regulate the attribution of incentive salience to stimuli, which is a psychological process involved in motivated behavior. Because of this exposure, brain circuits may become hypersensitive (or sensitized), thereby contributing to the development of pathological levels of incentive salience for target substances and their associated cues. Pathological incentive motivation (‘wanting’) for drugs may last for years, even if drug use is discontinued. It may involve implicit (unconscious wanting) or explicit (conscious craving) processes. The incentive salience model has been proposed to potentially contribute to the development and maintenance of CSB [1, 2].

Data support the incentive salience model for CSB. For example, Voon and colleagues examined cue-induced activity in the dorsal anterior cingulate cortex (dACC) –Vstr –amygdala functional network [1].Men with CSB as compared to those without showed increased VStr, dACC, and amygdala responses to pornographic video clips. These findings in the context of the larger literature suggest that sex and drug-cue reactivity involve largely overlapping regions and networks[61, 62]. Men with CSB as compared to those without also reported higher wanting (subjective sexual desire) of pornography stimuli and lower liking which is consistent with an incentive salience theory[1]. Similarly, Mechelmans and colleagues found that men with CSB as compared to men without showed enhanced early attentional bias towards sexually explicit stimuli but not to neutral cues [2]. These findings suggest similarities in enhanced attentional bias observed in studies examining drug cues in addictions.

In 2015, Seok and Sohn found that among men with CSB as compared to those without, greater activity was observed in the dorsolateral prefrontal cortex (dlPFC), caudate, inferior supramarginal gyrus of the parietal lobe, dACC, and thalamus in response to sexual cues[63]. They also found that the severity of CSB symptoms was correlated with cue-induced activation of the dlPFC and thalamus. In 2016, Brand and colleagues observed greater activation of the VStr for preferred pornographic material as compared to non-preferred pornographic material among men with CSB and found that VStr activity was positively associated with self-reported symptoms of addictive use of Internet pornography (assessed by the short Internet Addiction Test modified for cybersex (s-IATsex) [64, 65].

Klucken and colleagues recently observed that participants with CSB as compared to participants without displayed greater activation of the amygdala during presentation of conditioned cues (colored squares) predicting erotic pictures (rewards) [66]. These results are like those from other studies examining amygdala activation among individuals with substance use disorders and men with CSB watching sexually explicit video clips [1, 67].Using EEG, Steele and colleagues observed a higher P300 amplitude to sexual images (when compared to neutral pictures) among individuals self-identified as having problems with CSB, resonating with prior research of processing visual drug cues in drug addiction [68, 69].

In 2017, Gola and colleagues published results of a study using functional magnetic resonance imaging (fMRI) to examine Vstr responses to erotic and monetary stimuli among men seeking treatment for CSB and men without CSB [6]. Participants were engaged in an incentive delay task[54, 70, 71] while undergoing fMRI scanning. During this task, they received erotic or monetary rewards preceded by predictive cues. Men with CSB differed from those without in VStr responses to cues predicting erotic pictures, but not in their responses to erotic pictures. Additionally, men with CSB versus without CSB showed greater VStr activation specifically for cues predicting erotic pictures and not for those predicting monetary rewards. Relative sensitivity to cues (predicting erotic pictures vs. monetary gains) was found to be related to an increased behavioral motivation for viewing erotic images (‘wanting’), intensity of CSB, amount of pornography used per week, and frequency of weekly masturbation. These findings suggest similarities between CSB and addictions, an important role for learned cues in CSB, and possible treatment approaches, particularly interventions focused on teaching skills to individuals to successfully cope with cravings/urges [72]. Furthermore, habituation may be revealed through decreased reward sensitivity to normally salient stimuli and may impact reward responses to sexual stimuli including pornography viewing and partnered sex [1, 68]. Habituation has also been implicated in substance and behavioral addictions [73-79].

In 2014, Kuhn and Gallinat observed decreased VStr reactivity in response to erotic pictures in a group of participants watching pornography frequently, when compared to participants watching pornography rarely[80].Decreased functional connectivity between the left dlPFC and right VStr was also observed. Impairment in fronto-striatal circuity has been related to inappropriate or disadvantageous behavioral choices irrespective of potential negative outcome and impaired regulation of craving in drug addiction [81, 82]. Individuals with CSBmay have reduced executive control when exposed to pornographic material [83, 84]. Kuhn and Gallinat also found that the gray matter volume of the right striatum(caudate nucleus), which has been implicated in approach-attachment behaviors and related to motivational states associated with romantic love, was negatively associated with duration of internet pornography viewing[80, 85, 86]. These findings raise the possibility that frequent use of pornography may decrease brain activation in response to sexual stimuli and increase habituation to sexual pictures although longitudinal studies are needed to exclude other possibilities.

A study using EEG, conducted by Prause and colleagues, suggested that individuals who feel distressed about their pornography use, as compared to a control group who do not feel distress about their use of pornography, may require more/greater visual stimulation to evoke brain responses [87]. Hypersexual participants—individuals‘ experiencing problems regulating their viewing of sexual images’ (M=3.8 hours per week)—exhibited less neural activation (measured by late positive potential in the EEG signal) when exposed to sexual images than did the comparison group when exposed to the same images. Depending on the interpretation of sexual stimuli in this study (as a cue or reward; for more see Gola et al. [4]), the findings may support other observations indicating habituation effects in addictions [4].In 2015, Banca and colleagues observed that men with CSB preferred novel sexual stimuli and demonstrated findings suggestive of habituation in the dACC when exposed repeatedly to the same images [88]. Results of the aforementioned studies suggest that frequent pornography use may decrease reward sensitivity, possibly leading to increased habituation and tolerance, thereby enhancing the need for greater stimulation to be sexually aroused. However, longitudinal studies are indicated to examine this possibility further. Taken together, neuroimaging research to date has provided initial support for the notion that CSB shares similarities with drug, gambling, and gaming addictions with respect to altered brain networks and processes, including sensitization and habituation.

CSB as an Impulse-Control Disorder?

The category of “Impulse-Control Disorders Not Elsewhere Classified” in DSM-IV was heterogeneous in nature and included multiple disorders that have since been re-classified as being addictive (gambling disorder) or obsessive-compulsive-related (trichotillomania) in DSM-5[89, 90]. The current category in the DSM-5 focuses on disruptive, impulse-control and conduct disorders, becoming more homogeneous in its focus by including kleptomania, pyromania, intermittent explosive disorder, oppositional defiant disorder, conduct disorder, and antisocial personality disorder[90]. The category of impulse-control disorders in the ICD-11includes these first three disorders and CSBD, raising questions regarding the most appropriate classification. Given this context, how CSBD relates to the transdiagnostic construct of impulsivity warrants additional consideration for classification as well as clinical purposes.

Impulsivity may be defined as a, “predisposition towards rapid, unplanned reactions to internal or external stimuli with diminished regard to the negative consequences to the impulsive individual or others” [91]. Impulsivity has been associated with hypersexuality [92]. Impulsivity is a multidimensional construct with different types (e.g., choice, response) that may have trait and state characteristics [93-97]. Different forms of impulsivity may be assessed via self-report or via tasks. They may correlate weakly or not all, even within the same form of impulsivity; importantly, they may relate differentially to clinical characteristics and outcomes [98]. Response impulsivity maybe measured by performance on inhibitory control tasks, such as the stop signal or Go/No-Go tasks, whereas choice impulsivity may be assessed through delay discounting tasks [94, 95, 99].

Data suggest differences between individuals with and without CSB on self-report and task-based measures of impulsivity [100-103]. Furthermore, impulsivity and craving seem to be associated with the severity of symptoms of dysregulated pornography use, such as loss of control [64, 104]. For instance, one study found interacting effects of levels of impulsivity measured by self-report and behavioral tasks with respect to cumulative influences on symptom severity of CSB [104].

Among treatment-seeking samples, 48% to 55% of people may exhibit high levels of generalized impulsivity on Barratt Impulsiveness Scale [105-107]. In contrast, other data suggest that some patients seeking treatment for CSB do not have other impulsive behaviors or comorbid addictions beyond their struggles with sexual behaviors which is consistent with findings from a large online survey of men and women suggesting relatively weak relations between impulsivity and some aspects of CSB (problematic pornography use) and stronger relations with others (hypersexuality) [108, 109]. Similarly, in a study using different measures of individuals with problematic pornography use(mean time of weekly pornography use = 287.87 minutes) and those without (mean time of weekly pornography use = 50.77 minutes) did not differ on self-reported (UPPS-P Scale) or task-based (Stop Signal Task)measures of impulsivity [110].Further, Reid and colleagues did not observe differences between individuals with CSB and healthy controls on neuropsychological tests of executive functioning (i.e., response inhibition, motor speed, selective attention, vigilance, cognitive flexibility, concept formation, set shifting),even after adjusting for cognitive ability in analyses [103]. Together, findings suggest that impulsivity may link most strongly to hypersexuality but not to specific forms of CSB like problematic pornography use. It raises questions about CSBD’s classification as an impulse-control disorder in the ICD-11 and highlights the need for precise assessments of different forms of CSB. This is particularly important since some research indicates that impulsivity and subdomains of impulse-control disorder differ on conceptual and pathophysiological level [93, 98, 111].

CSB as an Obsessive-Compulsive-Spectrum Disorder?

One condition (trichotillomania) classified as an impulse-control disorder in DSM-IV has been reclassified with obsessive-compulsive disorder (OCD) as an obsessive-compulsive and related disorder in DSM-5[90]. Other DSM-IV impulse-control disorders like gambling disorder exhibit significant differences from OCD, supporting their classification in separate categories [112]. Compulsivity is a transdiagnostic construct that involves, “the performance of repetitive and functionally impairing overt or covert behavior without adaptive function, performed in a stereotyped or habitual fashion, either according to rigid rules or as a means to avoid negative consequences”[93]. OCD exhibits high levels of compulsivity; however, so do substance addictions and behavioral addictions like gambling disorder [98]. Traditionally, compulsive and impulsive disorders were construed as lying along opposite ends of a spectrum; however, data suggest the constructs as being orthogonal with many disorders scoring high on measures of both impulsivity and compulsivity [93, 113]. Regarding CSB, sexual obsessions have also been described as time-consuming and interfering and may relate theoretically to OCD or to OCD-related features [114].

Recent studies assessing obsessive-compulsive features using the Obsessive-Compulsive Inventory –Revised (OCI-R) did not show elevations among individuals with CSB [6, 37, 115]. Similarly, a large online survey found aspects of compulsivity only weakly related to problematic pornography use[109]. Together, these findings do not show strong support for considering CSB as an obsessive-compulsive-related disorder. Neural features underlying compulsive behaviors have been described and overlap across multiple disorders [93]. Further studies using psychometrically validated and neuroimaging methods in larger clinical treatment seeking samples are needed to examine further how CSBD may relate to compulsivity and OCD.

Structural Neural Changes among CSB Individuals

Thus far, most neuroimaging studies have focused on functional alterations in individuals with CSB, and results suggest that CSB symptoms are linked to specific neural processes[1, 63, 80]. Although task-based studies have deepened our knowledge about regional activation and functional connectivity, additional approaches should be used.

White-or gray-matter measures have been studied in CSB [102, 116]. In 2009, Miner and colleagues found that individuals with CSB as compared to those without displayed higher superior frontal region mean diffusivity and exhibited poorer inhibitive control. In a study of men with and without CSB from 2016, greater left amygdala volume was observed in the CSB group and relatively reduced resting-state functional connectivity was observed between the amygdala and dlPFC [116]. Reduction of brain volumes in the temporal lobe, frontal lobe, hippocampus, and amygdala were found to be related to the symptoms of hypersexuality in patients with dementia or Parkinson’s disease [117, 118]. These seemingly opposing patterns of amygdala volume relating to CSB highlight the importance of considering co-occurring neuropsychiatric disorders in understanding the neurobiology of CSB.

In 2018, Seok and Sohn used voxel-based morphometry (VBM) and resting-state connectivity analysis to examine gray-matter and resting-state measures in CSB [119]. Men with CSB showed significant gray-matter reduction in the temporal gyrus. Left superior temporal gyrus (STG) volume was negatively correlated with the severity of CSB (i.e., Sexual Addiction Screening Test-Revised [SAST ] and Hypersexual Behavior Inventory [HBI] scores)[120, 121]. Additionally, altered left STG-left precuneus and left STG-right caudate connectivities were observed. Lastly, results revealed a significant negative correlation between severity of CSB and functional connectivity of the left STG to the right caudate nucleus.

While the neuroimaging studies of CSB have been illuminating, little is still known about alternations in brain structures and functional connectivity among CSB individuals, particularly from treatment studies or other longitudinal designs. Integration of findings from other domains (e.g., genetic and epigenetic) will also be important to consider in future studies. Additionally, findings directly comparing specific disorders and incorporating transdiagnostic measures will allow for collection of important information that could inform classification and intervention development efforts currently underway.

Conclusions and Recommendations

This article reviews scientific knowledge regarding neural mechanisms of CSB from three perspectives: addictive, impulse-control, and obsessive-compulsive. Several studies suggest relationships between CSB and increased sensitivity for erotic rewards or cues predicting these rewards, and others suggest that CSB is related to increased cue-conditioning for erotic stimuli [1, 6, 36, 64, 66]. Studies also suggest that CSB symptoms are associated with elevated anxiety [34, 37,122]. Although gaps exist in our understanding of CSB, multiple brain regions (including frontal, parietal and temporal cortices, amygdala, and striatum) have been linked to CSB and related features.

CSBD has been included in the current version oftheICD-11as an impulse-control disorder [39]. As described by the WHO, ‘Impulse-control disorders are characterized by the repeated failure to resist an impulse, drive, or urge to perform an act that is rewarding to the person, at least in the short-term, despite consequences such as longer-term harm either to the individual or to others, marked distress about the behaviour pattern, or significant impairment in personal, family, social, educational, occupational, or other important areas of functioning’ [39]. Current findings raise important questions regarding the classification of CSBD. Many disorders characterized by impaired impulse-control are classified elsewhere in the ICD-11 (for example, gambling, gaming, and substance-use disorders are classified as being addictive disorders) [123].

Currently, CSBD constitutes a heterogeneous disorder, and further refinement of CSBD criteria should distinguish between different subtypes, some of which may relate to the heterogeneity of sexual behaviors problematic for individuals [33, 108, 124]. Heterogeneity in CSBD may in part explain seeming discrepancies which are noticeable across studies. Although neuroimaging studies find multiple similarities between CSB and substance and behavioral addictions, additional research is needed to fully understand how neurocognition relates to the clinical characteristics of CSB, especially with respect to sexual behaviors subtypes. Multiple studies have focused exclusively on problematic use of pornography which may limit generalizability to other sexual behaviors. Further, inclusion/exclusion criteria for CSB research participants have varied across studies, also raising questions regarding generalizability and comparability across studies.

Future Directions

Several limitations should be noted with respect to current neuroimaging studies and be considered when planning future investigations (see Table 1). A primary limitation involves small sample sizes that are largely white, male, and heterosexual. More research is needed to recruit larger, ethnically diverse samples of men and women with CSB and individuals of different sexual identities and orientations. For example, no systematic scientific studies have investigated neurocognitive processes of CSB in women. Such studies are needed given data linking sexual impulsivity to greater psychopathology in women as compared to men and other data which suggest gender-related differences in clinical populations with CSB [25, 30]. As women and men with addictions may demonstrate different motivations (e.g., relating to negative versus positive reinforcement) for engaging in addictive behaviors and show differences in stress and drug-cue responsivity, future neurobiological studies should consider stress systems and related processes in gender-related investigations of CSBD given its current inclusion in the ICD-11 as a mental health disorder [125, 126].

Similarly, there is also a need to conduct systematic research focusing on ethnic and sexual minorities to clarify our understanding of CSB among these groups. Screening instruments for CSB have been mostly tested and validated on white European men. Moreover, current studies have focused predominantly on heterosexual men. More research examining clinical characteristics of CSB among gay and bisexual men and women is needed. Neurobiological research of specific groups (transgender, polyamorous, kink, other) and activities (pornography viewing, compulsive masturbation, casual anonymous sex, other) is also needed. Given such limitations, existing results should be interpreted cautiously.

Direct comparison of CSBD with other disorders (e.g., substance use, gambling, gaming, and other disorders)is needed, as is incorporation of other non-imaging modalities (e.g., genetic, epigenetic) and use of other imaging approaches. Techniques like positron emission tomography could also provide important insight into neurochemical underpinnings of CSBD.

The heterogeneity of CSB may also be clarified through careful assessment of clinical features that may be obtained in part from qualitative research like focus group ordiary assessment methods [37]. Such research could also provide insight into longitudinal questions like whether problematic pornography use may lead to sexual dysfunction, and integrating neurocognitive assessments into such studies could provide insight into neurobiological mechanisms. Further, as behavioral and pharmacological interventions are formally tested for their efficacies in treating CSBD, integration of neurocognitive assessments could help identify mechanisms of effective treatments for CSBD and potential biomarkers. This last point may be particularly important because the inclusion of CSBD in the ICD-11 will likely increase the number of individuals seeking treatment for CSBD. Specifically, the inclusion of CSBD in the ICD-11 should raise awareness in patients, providers, and others and potentially remove other barriers (e.g., reimbursement from insurance providers) that may currently exist for CSBD.

Analysis of “Modulation of late positive potentials by sexual images in problem users and controls inconsistent with ‘porn addiction’ (2015)”, by Liberos LLC/ SPAN lab


Because this EEG study reported greater porn use related to less brain activation to vanilla porn it is listed as supporting the hypothesis that chronic porn use down regulates sexual arousal. Put simply, the more frequent porn users were bored by static images of ho-hum porn (its findings parallel Kuhn & Gallinat., 2014). These findings are consistent with tolerance, a sign of addiction. Tolerance is defined as a person’s diminished response to a drug or stimulus that is the result of repeated use.

Ten peer-reviewed papers agree with YBOP’s assessment of Prause et al., 2015 (links are to excerpts addressing Prause et al.)

  1. Decreased LPP for sexual images in problematic pornography users may be consistent with addiction models. Everything depends on the model (Commentary on Prause et al., 2015)
  2. Neuroscience of Internet Pornography Addiction: A Review and Update (2015)
  3. Neurobiology of Compulsive Sexual Behavior: Emerging Science (2016)
  4. Should compulsive sexual behavior be considered an addiction? (2016)
  5. Is Internet Pornography Causing Sexual Dysfunctions? A Review with Clinical Reports (2016)
  6. Conscious and Non-Conscious Measures of Emotion: Do They Vary with Frequency of Pornography Use? (2017)
  7. Neurocognitive mechanisms in compulsive sexual behavior disorder (2018)
  8. Online Porn Addiction: What We Know and What We Don’t—A Systematic Review (2019)
  9. The Initiation and Development of Cybersex Addiction: Individual Vulnerability, Reinforcement Mechanism and Neural Mechanism (2019)
  10. Do Varying Levels of Exposure to Pornography and Violence Have an Effect on Non-Conscious Emotion in Men (2020)

Because frequent porn users had lower EEG readings than controls, lead author Nicole Prause claims her anomalous study falsifies the porn addiction model. Prause proclaimed that her EEG readings assessed “cue-reactivity” (sensitization), rather than habituation. Even if Prause were correct she conveniently ignores the gaping hole in her “falsification” assertion: Even if Prause et al. 2015 had found less cue-reactivity in frequent porn users, 25 other neurological studies have reported cue-reactivity or cravings (sensitization) in compulsive porn users: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25. Science doesn’t go with the lone anomalous study hampered by serious methodological flaws; science goes with the preponderance of evidence (unless you are agenda-driven).

Update: In this 2018 presentation Gary Wilson exposes the truth behind 5 questionable and misleading studies, including the two Nicole Prause EEG studies (Steele et al., 2013 and Prause et al., 2015): Porn Research: Fact or Fiction?

Update (April, 2019): In an attempt to silence YBOP’s criticism, a handful of authors formed a group to steal YBOP’s trademark (headed by Nicole Prause, and including Justin Lehmiller & David Ley). See this page for details: Aggressive Trademark Infringement Waged by Porn Addiction Deniers (

Update (Summer, 2019): On May 8, 2019 Donald Hilton, MD filed a defamation per se lawsuit against Nicole Prause & Liberos LLC. On July 24, 2019 Donald Hilton amended his defamation complaint to highlight (1) a malicious Texas Board of Medical Examiners complaint, (2) false accusations that Dr. Hilton had falsified his credentials, and (3) affidavits from 9 other Prause victims of similar harassment & defamation (John Adler, MD, Gary Wilson, Alexander Rhodes, Staci Sprout, LICSW, Linda Hatch, PhD, Bradley Green, PhD, Stefanie Carnes, PhD, Geoff Goodman, PhD, Laila Haddad.)

Update (October, 2019): On October 23, 2019 Alexander Rhodes (founder of reddit/nofap and filed a defamation lawsuit against Nicole R Prause and Liberos LLC. See the court docket here. See this page for three primary court documents filed by Rhodes: NoFap founder Alexander Rhodes defamation lawsuit against Nicole Prause / Liberos.


Hyperbole & Inaccurate Claims

As it was published July 2015, we will refer to this paper as Prause et al., 2015. Let’s start with the lead author’s hyperbole. Nicole Prause boldly claimed on her SPAN lab website that this solitary study “debunks porn addiction”:

What legitimate researcher would ever claim to have debunked an entire field of research and to refute all previous studies with a single EEG study?

In addition, Nicole Prause claimed her study contained 122 subjects (N). In reality, the study had only 55 subjects who were “experiencing problems regulating their viewing of sexual images”. The subjects were recruited from Pocatello Idaho, which is over 50% Mormon. The other 67 participants were controls.

In a second dubious claim, Prause et al., 2015 stated in both the abstract and in the body of the study:

These are the first functional physiological data of persons reporting Visual Sexual Stimuli regulation problems“.

This is clearly not the case, as the Cambridge fMRI study was published nearly a year earlier.

In a third claim Nicole Prause has consistently asserted that Prause et al., 2015 is “the largest neuroscience investigation of porn addiction ever conducted”. It should be noted that compared to brain scan studies, EEG studies are far less expensive per subject. It’s easy to gather a large group of “porn addicted” subjects if you don’t screen the subjects for porn addiction or any exclusionary condition (mental problems, addictions, psychotropic drug use, etc.). A few problems with Prause’s claim:

  1. It’s not a study on porn addiction if it has no porn addicts. This study, and 2 earlier Prause studies (Prause et al., 2013 & Steele et al., 2013), did not assess whether any of the subjects were porn addicts or not. Prause admitted in an interview that many of the subjects had little difficulty controlling use: they were not addicts. All of the subjects would have to have been confirmed porn addicts to permit a legitimate comparison with a group of non-porn addicts. In addition the Prause Studies did not screen subjects for mental disorders, compulsive behaviors, or other addictions. Four of the nine peer-reviewed critiques point out these fatal flaws: 2, 3, 4, 8.
  2. “HPA axis dysregulation in men with hypersexual disorder” (2015) could be considered the largest neuroscience-based study to date on “hypersexuals” (with 67 subjects in treatment for sex addiction, as compared to Prause’s 55 subjects who were upset about their porn use). The study assessed the brain’s response to stress by assessing a hormone release by the brain (ACTH), and a hormone controlled by the brain (cortisol). While this study was a published a few months after Prause et al., 2015, Nicole Prause continues to claim her EEG study as the largest.
  3. Brain Structure and Functional Connectivity Associated With Pornography Consumption: The Brain on Porn (2014) – Could be considered larger than Prause et al., 2015, because it had 64 subjects, and all were carefully screened for exclusionary items such as addictions, substance use, mental disorders, and medical & neurological disorders. The 3 Prause studies did not do this.

Prause et al., 2015 Assessed Brain Wave Activity

Prause et al., 2015 was an Electroencephalography or EEG study. EEG’s measure electrical activity, or brain waves, on the scalp. Although EEG technology has been around for 100 years, debate continues as to what actually causes brain waves, or what specific EEG readings really signify. As a consequence, experimental results may be interpreted in a variety of ways. Spikes in electrical activity are called amplitudes (below).

Researchers believe that certain EEG amplitudes (LPP, P3) may assess attention given to a particular stimulus, such as a picture. Put simply, greater amplitudes indicate the subject is paying greater attention to the visual stimulus presented in the experiment. In the Prause study the stimulus was a one-second exposure to a sexual photo. A few important points:

  1. Greater attention, and the corresponding EEG spike, cannot tell us if the person was sexually aroused or if they were repulsed. A higher spike may just as easily be caused by negative emotions, such as disgust or shock.
  2. Nor can an EEG spike tell us if the brain’s reward circuitry was activated or not. In contrast, other recent studies on porn users by Voon et al., 2014. and Kuhn & Gallinat 2014 used fMRI scanners to pinpoint structural changes and reward circuit activity.

In this study, Prause et al., 2015 compared the EEG activity of so called “porn addicts” (average 3.8 hours of porn/week) to controls (average 0.6 hours of porn/week). As expected, both “porn addicts” and controls had greater EEG activity (LPP amplitude) when viewing sexual photos. However, the amplitude was smaller for the “porn addicts.”

Prause et al., 2015 Actually Supports Porn Addiction

Expecting a greater amplitude for “porn addicts”, the authors stated,

This pattern appears different from substance addiction models.”

But does that really make sense? As a researcher friend says, in any study there are results…and there are the researcher’s interpretations. The results are pretty clear: Porn addicts paid less attention to photos of vanilla sex flashed on the screen for one second. This is no surprise to anyone who overconsumes today’s porn.

Prause’s findings of lower LPP amplitudes for “porn addicts” when compared to controls actually aligns with the addiction model, notwithstanding her interpretation that she has “debunked porn addiction.” Her finding indicates both desensitization (or habituation) and tolerance, which is the need for greater stimulation. Both are commonly seen in addicts, and, somewhat alarmingly, have also been recorded in heavy porn users who were not addicts (more below).

Key point: If porn use had no effect on Prause’s subjects, we would expect controls and “porn addicts” to have the same LPP amplitude in response to sexual photos. Instead, Prause’s so-called “porn addicts” had less brain activation (lower LPP) to still images of vanilla porn. I use quotation marks because Prause did not actually employ a screening instrument for internet pornography addicts, so we have no idea whether some, or any, of her subjects were porn addicts. For Prause’s claims of falsification and the resulting dubious headlines to be legitimate, all of Prause’s 55 subjects would have to have been actual porn addicts. Not some, not most, but every single subject. All signs point to a good number of the 55 Prause subjects being non-addicts

The subjects were recruited from Pocatello Idaho via online advertisements requesting people who were “experiencing problems regulating their viewing of sexual images”. Pocatello Idaho is over 50% Mormon, so many of the subjects may feel that any amount of porn use is a serious problem. In a serious methodological flaw, none of the subjects were screened for porn addiction. In another methodological flaw, the ad limited recruitment to participants who had problems with only “sexual images”. Since most compulsive porn users view streaming video clips, did this skew the participants even further?

Make no mistake, neither Steele et al., 2013 nor Prause et al., 2015 described these 55 subjects as porn addicts or compulsive porn users. The subjects only admitted to feeling “distressed” by their porn use. Confirming the mixed nature of her subjects, Prause admitted in 2013 interview that some of the 55 subjects experienced only minor problems (which means they were not porn addicts):

“This study only included people who reported problems, ranging from relatively minor to overwhelming problems, controlling their viewing of visual sexual stimuli.”

How can you debunk the porn addiction model if many of your “porn addicts” are not really porn addicts? You can’t.

The Prause et al. finding aligns perfectly with Kühn & Gallinat (2014), which found that more porn use correlated with less brain activation in heavy users (who were not addicts) when exposed to sexual photos (.530 seconds). Said the researchers:

“This is in line with the hypothesis that intense exposure to pornographic stimuli results in a downregulation of the natural neural response to sexual stimuli.”

Kühn & Gallinat also reported more porn use correlating with less reward circuit grey matter and disruption of the circuits involved with impulse control. In this article researcher Simone Kühn, said:

“That could mean that regular consumption of pornography more or less wears out your reward system.”

Kühn says existing psychological, scientific literature suggests consumers of porn will seek material with novel and more extreme sex games.

“That would fit perfectly the hypothesis that their reward systems need growing stimulation.”

Another EEG study found that greater porn use in women correlated with less brain activation to porn. Put simply, those who use more porn may need greater stimulation for the response level seen in lighter consumers, and photos of vanilla porn are unlikely to register as all that interesting. Less interest, equates to less attention, and lower EEG readings. End of story.

Prause et al., 2015 Concedes That Kühn & Gallinat 2014 May Be Right

In the discussion section, Prause et al, cited Kühn & Gallinat and offered it as a possible explanation for the lower LPP pattern. She was on the right track, and it’s too bad her interpretation then took a U-turn from her data. Perhaps Prause’s strong biases against porn addiction shaped her interpretations. Her former Twitter slogan suggests she may lack the impartiality required for scientific research:

“Studying why people choose to engage in sexual behaviors without invoking addiction nonsense”

Incidentally, the still images employed by both Kühn and Prause differed significantly from the 9-second “explicit” video clips used in the 2014 Cambridge fMRI study, which found similarities between porn addicts’ brains and those of drug addicts. Those researchers found greater reward center activity in porn addicts in response to the video clips, which is typical of addicts.

Internet porn studies and their interpretation are complicated by the fact that viewing pornographic images (stills or videos) is the addictive behavior, rather than solely a cue. By comparison, viewing images of vodka bottles is a cue for an alcoholic. While that cue may light up her brain more than a control’s brain, the alcoholic needs greater amounts of alcohol to get a buzz. The heavy porn users in the Kühn and Prause studies clearly needed greater stimulation (videos?) to exhibit their buzz. They didn’t respond normally to mere stills. This is evidence of tolerance (and underlying addiction-related brain changes).

Updates on Nicole Prause’s twitter slogan:

  1. UCLA did not renew Prause’s contract. She hasn’t been affiliated with any university since early 2015.
  2. In October, 2015 Prause’s original Twitter account is permanently suspended for harassment

In Her 2013 EEG Study and a Blog Post Prause States That LESS Brain Activation Would Indicate Habituation or Addiction

Prause claimed that her 2013 EEG study was the first time EEG readings were recorded for so-called “hypersexuals.” Since this was a “first” Prause admits it’s pure speculation as to whether “hypersexuals” should have higher or lower EEG readings than healthy controls:

“Given that this is the first time ERPs were recorded in hypersexuals, and literature on addiction (higher P300) and impulsivity (lower P300) suggest opposite predictions, the direction of the hypersexual effect was specified mainly on theoretical grounds.” [That is, without much basis at all.]

As explained here Prause’s 2013 EEG study had no control group, so it could not compare “porn addicts'” EEG readings to “non-addicts.” As a result, her 2013 study told us nothing about the EEG readings for either healthy individuals or “hypersexuals.” Let’s continue with Prause’s views from 2013:

“Therefore, individuals with high sexual desire could exhibit large P300 amplitude difference between sexual stimuli and neutral stimuli due to salience and emotional content of the stimuli. Alternatively, little or no P300 amplitude difference could be measured due to habituation to VSS.

In 2013, Prause said that porn addicts, when compared to controls, could exhibit:

  1. higher EEG readings due to cue-reactivity to images, or
  2. lower EEG readings due to habituation to porn (VSS).

Five months before her 2013 EEG study was published, Prause and David Ley teamed up to write this Psychology Today blog post about her upcoming study. In it they claim that “diminished electrical response” would indicate habituation or desensitization:

But, when EEG’s were administered to these individuals, as they viewed erotic stimuli, results were surprising, and not at all consistent with sex addiction theory. If viewing pornography actually was habituating (or desensitizing), like drugs are, then viewing pornography would have a diminished electrical response in the brain. In fact, in these results, there was no such response. Instead, the participants’ overall demonstrated increased electrical brain responses to the erotic imagery they were shown, just like the brains of “normal people”…

So, we have 2013 Prause saying “diminished electrical response” would indicate habituation or desensitization. Now, however, in 2015, when Prause found evidence of desensitization (common in addicts), she is telling us “diminished electrical response” debunks porn addiction. Huh?

In the intervening two years it took Prause to compare her same tired subject data with an actual control group, she has done a complete flip-flop. Now, she claims the evidence of desensitization that she found when she added the control group isn’t evidence of addiction (which she claimed in 2013 it would have been). Instead, once again, she insists she has “disproved addiction.” This is inconsistent and unscientific, and suggests that regardless of opposing findings, she will claim to have “disproven addiction.” In fact, unless 2015 Prause rejects the 2013 Prause study and blog post she would be obliged to “invoke addiction nonsense.”

By the way, the above excerpt –“participants’ overall demonstrated increased electrical brain responses to the erotic imagery” – is confusing. Of course it’s normal to have a greater response to sexual pictures than to neutral landscape pictures. However, Prause’s 2013 study had no control group, and it did not compare EEG readings of porn addicts to non-addicts. Once she added the control group, it was evident that arousal in response to erotic imagery is normal and the effect disappeared. Instead, her subjects turned out to be suffering from desensitization, an addiction process. In short, Prause’s 2013 results were meaningless (see below), while her 2015 headlines contradict everything she had previously stated. She claims to disprove addiction while discovering evidence of it.

Poor Methodology Once Again

1) As with Prause’s 2013 EEG study (Steele et al.), the subjects in this study were males, females and possibly “non-heterosexuals”. All evidence suggests Prause used the same subjects for her current study and her 2013 study: the number of females are identical (13) and the total numbers very close (52 vs. 55). If so, this current study also included 7 “non-heterosexuals”. This matters, because it violates standard procedure for addiction studies, in which researchers select homogeneous subjects in terms of age, gender, orientation, even similar IQ’s (plus a homogeneous control group) in order to avoid distortions caused by such differences. This is especially critical for studies like this one, which measured arousal to sexual images, as research confirms that men and women have significantly different brain responses to sexual images or films (Studies: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14). This flaw alone calls into question both of Prause’s studies.

2) Prause’s subjects were not pre-screened. Valid addiction brain studies screen out individuals with pre-existing conditions (depression, OCD, other addictions, etc.). This is the only way responsible researchers can draw conclusions about addiction. See the Cambridge Univeristy studies for an example of proper screening & methodology.

3) The two questionnaires Prause relied upon in both EEG studies to assess “porn addiction” are not validated to screen for internet porn use / addiction. The Sexual Compulsivity Scale (SCS) was created in 1995 to measure sexual behavior to help with AIDS-risk assessment, and specifically not validated for females. The SCS says:

“The scale has been should [shown?] to predict rates of sexual behaviors, numbers of sexual partners, practice of a variety of sexual behaviors, and histories of sexually transmitted diseases.”

Moreover, the SCS’s developer warns that this tool won’t show psychopathology in women,

“Associations between sexual compulsivity scores and other markers of psychopathology showed different patterns for men and women; sexual compulsivity was associated with indexes of psychopathology in men but not in women.”

Like the SCS, the second questionnaire (the CBSOB) has no questions about Internet porn use. It was designed to screen for “hypersexual” subjects, and out-of-control sexual behaviors – not strictly the overuse of sexually explicit materials on the internet.

A valid addiction “brain study” must:

  1. have homogenous subjects and controls,
  2. screen out other mental disorders and other addictions, and
  3. use validated questionnaires and interviews to assure the subjects are actually porn addicts.

Prause’s two EEG studies on porn users did none of these, yet she drew vast conclusions and published them widely.

Claims Must be Supported by The Data

Prause, by her own admission, rejects the concept of porn addiction, and believes that porn use can never cause problems. For example a quote from this recent Martin Daubney article about sex/porn addictions:

Dr Nicole Prause, principal investigator at the Sexual Psychophysiology and Affective Neuroscience (Span) Laboratory in Los Angeles, calls herself a “professional debunker” of sex addiction.

Such inherent biases may have led to several claims by Prause, which do not align with her experimental data.

The first example is her 2013 study “Sexual desire, not hypersexuality, is related to neurophysiological responses elicited by sexual images.” Five months before this study was published, Prause released it (only) to psychologist David Ley, who promptly blogged about it on Psychology Today, claiming that it proved pornography addiction didn’t exist. Such claims were not, in fact, supported by the study when published. The following excerpt is taken from this peer-reviewed critique of the study:

‘The single statistically significant finding says nothing about addiction. Furthermore, this significant finding is a negative correlation between P300 and desire for sex with a partner (r=−0.33), indicating that P300 amplitude is related to lower sexual desire; this directly contradicts the interpretation of P300 as high desire. There are no comparisons to other addict groups. There are no comparisons to control groups. The conclusions drawn by the researchers are a quantum leap from the data, which say nothing about whether people who report trouble regulating their viewing of sexual images have or do not have brain responses similar to cocaine or any other kinds of addicts.’

Just as in the current EEG study, Prause claimed her subjects’ brains did not respond like other addicts. In reality, her subjects had higher EEG (P300) readings when viewing sexual images – which is exactly what occurs when addicts view images related to their addiction. Commenting under the Psychology Today interview with Prause’s claims, senior psychology professor emeritus John A. Johnson said:

“My mind still boggles at the Prause claim that her subjects’ brains did not respond to sexual images like drug addicts’ brains respond to their drug, given that she reports higher P300 readings for the sexual images. Just like addicts who show P300 spikes when presented with their drug of choice. How could she draw a conclusion that is the opposite of the actual results? I think it could be due to her preconceptions–what she expected to find.”

This 2015 review of the neuroscience literature on pornography addiction went further:

The study was designed to examine the relationship between ERP amplitudes when viewing emotional and sexual images and questionnaire measures of hypersexuality and sexual desire. The authors concluded that the absence of correlations between scores on hypersexuality questionnaires and mean P300 amplitudes when viewing sexual images “fail to provide support for models of pathological hypersexuality” [303] (p. 10). However, the lack of correlations may be better explained by arguable flaws in the methodology. For example, this study used a heterogeneous subject pool (males and females, including 7 non-heterosexuals). Cue-reactivity studies comparing the brain response of addicts to healthy controls require homogenous subjects (same sex, similar ages) to have valid results. Specific to porn addiction studies, it’s well established that males and females differ appreciably in brain and autonomic responses to the identical visual sexual stimuli [304, 305, 306]. Additionally, two of the screening questionnaires have not been validated for addicted IP users, and the subjects were not screened for other manifestations of addiction or mood disorders.

Moreover, the conclusion listed in the abstract, “Implications for understanding hypersexuality as high desire, rather than disordered, are discussed” [303] (p. 1) seems out of place considering the study’s finding that P300 amplitude was negatively correlated with desire for sex with a partner. As explained in Hilton (2014), this finding “directly contradicts the interpretation of P300 as high desire” [307]. The Hilton analysis further suggests that the absence of a control group and the inability of EEG technology to discriminate between “high sexual desire” and “sexual compulsion” render the Steele et al. findings uninterpretable [307].

Finally, a significant finding of the paper (higher P300 amplitude to sexual images, relative to neutral pictures) is given minimal attention in the discussion section. This is unexpected, as a common finding with substance and internet addicts is an increased P300 amplitude relative to neutral stimuli when exposed to visual cues associated with their addiction [308]. In fact, Voon, et al. [262] devoted a section of their discussion analyzing this prior study’s P300 findings. Voon et al. provided the explanation of importance of P300 not provided in the Steele paper, particularly in regards to established addiction models, concluding,

“Thus, both dACC activity in the present CSB study and P300 activity reported in a previous CSB study[303] may reflect similar underlying processes of attentional capture. Similarly, both studies show a correlation between these measures with enhanced desire. Here we suggest that dACC activity correlates with desire, which may reflect an index of craving, but does not correlate with liking suggestive of on an incentive-salience model of addictions. [262]” (p. 7)

So while these authors [303] claimed that their study refuted the application of the addiction model to CSB, Voon et al. posited that these authors actually provided evidence supporting said model.

Bottom line: Eight peer-reviewed papers agree with our analysis of Steele et al., 2013 (Peer-reviewed critiques of Steele et al., 2013) The 2013 EEG study actually reported higher EEG readings (P300) when subjects were exposed to sexual photos. A higher P300 occurs when addicts are exposed to cues (such as images) related to their addiction. However, the study had no control group for comparison, which made the findings uninterpretable (as explained above this current study simply found a control group for the 2013 study). In addition, the study reported greater cue-reactivity for porn correlating to less desire for partnered sex. Put simply: The study found greater brain activation for porn and less desire for sex (but not less desire for masturbation). Not exactly what the headlines claimed about porn increasing sexual desire or sex addicts simply having higher libidos.

Similar to Prause’s current study, her second study from 2013 found significant differences between controls and “porn addicts” – “No Evidence of Emotion Dysregulation in “Hypersexuals” Reporting Their Emotions to a Sexual Film (2013).” As explained in this critique, the title hides the actual findings. In fact, “porn addicts” had less emotional response when compared to controls. This is not surprising as many porn addicts report numbed feelings and emotions. Prause justified the title by saying she expected “greater emotional response”, but provided no citation for her dubious “expectation.” A more accurate title would have been: “Subjects who have difficulty controlling their porn use show less emotional response to sexual films, probably due to habituation, a sign of addiction“. This finding aligns with Prause’s current EEG study and Kühn & Gallinat (2014), and indicates desensitization.

In Prause’s 2015 paper, “Viewing sexual stimuli associated with greater sexual responsiveness, not erectile dysfunction“, none of paper’s claims are supported by the data provided in the underlying studies. Two critiques, one by a lay person, and another by a medical doctor (peer-reviewed), describe the papers many discrepancies and dubious claims:

As noted in the above analyses, Prause did not measure sexual responsiveness, erections, or brain activation. Instead, porn users gave a number on a single question self-report of “sexual arousal” after viewing visual sexual stimuli. Those in the 2+ hours per week porn use had slightly higher scores after watching porn. This is what one would expect. This tells us nothing about their sexual arousal without porn or their sexual arousal with a partner. And it says nothing about erectile function. It’s hard to say what the title should be as Prause did not release the relevant data, but it appears that an accurate title might be “More porn use makes men hornier.”

Even more surprising, the scores for the young men (average age 23) in her paper indicated erectile dysfunction. Not only are we given no reason why these young men had ED, we are falsely told the men “reported relatively good erectile functioning”. We could go on and on about this paper.

In 2014, Prause openly teamed up with David Ley – author of The Myth of Sex Addiction, who has no background in the neuroscience of addiction or research – to produce a dubious review on the subject of porn addiction: “The Emperor Has No Clothes: A review of the “Pornography Addiction” model.” It is this review that the authors cite for the astonishing proposition that, “The Internet has [not] increased viewing of visual sexual stimuli.” Once again, virtually nothing in Ley & Prause “review” holds up to scrutiny, as this painfully detailed critique reveals: “The Emperor Has No Clothes: A Fractured Fairytale Posing As A Review.

Finally, it needs to be stated that former academic Nicole Prause has a long history of harassing authors, researchers, therapists, reporters and others who dare to report evidence of harms from internet porn use. She appears to be quite cozy with the pornography industry, as can be seen from this image of her (far right) on the red carpet of the X-Rated Critics Organization (XRCO) awards ceremony. (According to Wikipedia the XRCO Awards are given by the American X-Rated Critics Organization annually to people working in adult entertainment and it is the only adult industry awards show reserved exclusively for industry members.[1]). It also appears that Prause may have obtained porn performers as subjects through another porn industry interest group, the Free Speech Coalition. The FSC-obtained subjects were allegedly used in her hired-gun study on the heavily tainted and very commercial “Orgasmic Meditation” scheme (now being investigated by the FBI).Prause has also made unsupported claims about the results of her studies and her study’s methodologies. For much more documentation, see: Is Nicole Prause Influenced by the Porn Industry?

In Summary, the Three Prause Studies on Porn Users Align With the Cambridge studies and Kühn & Gallinat (2014).

1) Sexual Desire, not Hypersexuality, is Related to Neurophysiological Responses Elicited by Sexual Images (2013)

  • Aligns with the 23 other neurological studies on porn users and sex addicts that found cue-reactivity to porn or cravings (sensitization). In addition, the Prause study reported less sexual desire for a partner correlating with greater cue-reactivity. In a parallel finding, the first Cambridge study reported that 60% of subjects had difficulty achieving erections/arousal with real partners, yet could achieve erections with porn.

2) No Evidence of Emotion Dysregulation in “Hypersexuals” Reporting Their Emotions to a Sexual Film (2013)

3) Modulation of Late Positive Potentials by Sexual Images in Problem Users and Controls Inconsistent with “Porn Addiction” (2015)

  • Aligns with Kühn & Gallinat (2014) in that more porn use correlated to less brain activation in response to sexual photos.
  • Aligns perfectly with 2013 Prause who said that lower EEG amplitudes (compared to controls) would indicate habituation or desensitization.

Wouldn’t it be great if journalists and bloggers actually read studies, and conferred with addiction neuroscientists, before rubber stamping sexologists’ press releases or sound bites? Bottom line: All brain and neuropsychological studies published to date support the existence of porn addiction, including Prause’s.


Analysis of Prause et al. excerpted from “Neuroscience of Internet Pornography Addiction: A Review and Update, 2015:

Another EEG study involving three of the same authors was recently published [309]. Unfortunately, this new study suffered from many of the same methodological issues as the prior one [303]. For example, it used a heterogeneous subject pool, the researchers employed screening questionnaires that have not been validated for pathological internet pornography users, and the subjects were not screened for other manifestations of addiction or mood disorders.

In the new study, Prause et al. compared EEG activity of frequent viewers of Internet pornography with that of controls as they viewed both sexual and neutral images [309]. As expected, the LPP amplitude relative to neutral pictures increased for both groups, although the amplitude increase was smaller for the IPA subjects. Expecting a greater amplitude for frequent viewers of Internet pornography, the authors stated, “This pattern appears different from substance addiction models”.

While greater ERP amplitudes in response to addiction cues relative to neutral pictures is seen in substance addiction studies, the current finding is not unexpected, and aligns with the findings of Kühn and Gallinat [263], who found more use correlated with less brain activation in response to sexual images. In the discussion section, the authors cited Kühn and Gallinat and offered habituation as a valid explanation for the lower LPP pattern. A further explanation offered by Kühn and Gallinat, however, is that intense stimulation may have resulted in neuroplastic changes. Specifically, higher pornography use correlated with lower grey matter volume in the dorsal striatum, a region associated sexual arousal and motivation [265].

It’s important to note that the findings of Prause et al. were in the opposite direction of what they expected [309]. One might expect frequent viewers of Internet pornography and controls to have similar LPP amplitudes in response to brief exposure to sexual images if pathological consumption of Internet pornography had no effect. Instead, the unexpected finding of Prause et al. [309] suggests that frequent viewers of Internet pornography experience habituation to still images. One might logically parallel this to tolerance. In today’s world of high-speed Internet access, it is very likely that frequent consumers of Internet pornography users view sexual films and videos as opposed to still clips. Sexual films produce more physiological and subjective arousal than sexual images [310] and viewing sexual films results in less interest and sexual responsiveness to sexual images [311]. Taken together, the Prause et al., and Kühn and Gallinat studies lead to the reasonable conclusion that frequent viewers of internet pornography require greater visual stimulation to evoke brain responses comparable to healthy controls or moderate porn users.

In addition, the statement of Prause et al. [309] that, “These are the first functional physiological data of persons reporting VSS regulation problems” is problematic because it overlooks research published earlier [262,263]. Moreover, it is critical to note that one of the major challenges in assessing brain responses to cues in Internet pornography addicts is that viewing sexual stimuli is the addictive behavior. In contrast, cue-reactivity studies on cocaine addicts utilize pictures related to cocaine use (white lines on a mirror), rather than having subjects actually ingest cocaine. Since the viewing of sexual images and videos is the addictive behavior, future brain activation studies on Internet pornography users must take caution in both experimental design and interpretation of results. For example, in contrast to the one-second exposure to still images used by Prause et al. [309], Voon et al. chose explicit 9-second video clips in their cue reactivity paradigm to more closely match Internet porn stimuli [262]. Unlike the one-second exposure to still images (Prause et al. [309]), exposure to 9-second video clips evoked greater brain activation in heavy viewers of internet pornography than did one-second exposure to still images. It is further concerning that the authors referenced the Kühn and Gallinat study, released at the same time as the Voon study [262], yet they did not acknowledge the Voon et al. study anywhere in their paper despite its critical relevance.

A recovering porn-user summed the situation up here: