{"paper_id":"36151363-f733-4d5c-8f8e-fba3f5a73fdb","body_text":"Journal of Obstetrics and Gynaecology\nISSN: 0144-3615 (Print) 1364-6893 (Online) Journal homepage: www.tandfonline.com/journals/ijog20\nBrain functional connectivity changes on fMRI\nin patients with chronic pelvic pain treated with\nthe Neuro Emotional Technique: a randomised\ncontrolled trial\nDaniel A. Monti, Faezeh Vedaei, Anna Tobia, Emily Navarreto, Chloe Hriso,\nReneita Ross, Rohit Raja, Nancy Wintering, George P. Zabrecky, Feroze\nMohamed & Andrew B. Newberg\nTo cite this article: Daniel A. Monti, Faezeh Vedaei, Anna Tobia, Emily Navarreto, Chloe Hriso,\nReneita Ross, Rohit Raja, Nancy Wintering, George P. Zabrecky, Feroze Mohamed & Andrew B.\nNewberg (2025) Brain functional connectivity changes on fMRI in patients with chronic pelvic\npain treated with the Neuro Emotional Technique: a randomised controlled trial, Journal of\nObstetrics and Gynaecology, 45:1, 2472767, DOI: 10.1080/01443615.2025.2472767\nTo link to this article:  https://doi.org/10.1080/01443615.2025.2472767\n© 2025 The Author(s). Published by Informa\nUK Limited, trading as Taylor & Francis\nGroup\nView supplementary material \nPublished online: 14 Mar 2025.\n Submit your article to this journal \nArticle views: 4780\n View related articles \nView Crossmark data\n Citing articles: 2 View citing articles \nFull Terms & Conditions of access and use can be found at\nhttps://www.tandfonline.com/action/journalInformation?journalCode=ijog20\n\nGynaecoloGy\nJournal of obstetrics and GynaecoloGy\n2025, Vol. 45, no . 1, 2472767\nBrain functional connectivity changes on fMRI in patients with chronic pelvic \npain treated with the Neuro Emotional Technique: a randomised controlled \ntrial\nDaniel a. Monti a, Faezeh Vedaei, a nna Tobia a, emily navarreto a, chloe Hriso a, Reneita Ross b, Rohit Raja c, \nnancy Wintering a, George P . Zabrecky a, Feroze Mohamed c and a ndrew B. newberg a,c\nadepartment of i ntegrative Medicine and nutritional s ciences, Marcus i nstitute of i ntegrative Health, t homas Jefferson university, Philadelphia, \nPennsylvania, usa; bdepartment obstetrics and Gynecology, t homas Jefferson university, Philadelphia, Pennsylvania, usa; cdepartment of \nr adiology, t homas Jefferson university, Philadelphia, Pennsylvania, usa\nABSTRACT\nBackground: chronic pelvic pain is a substantial clinical challenge that profoundly impacts quality of life \nfor many women. The neuro emotional Technique (ne T) is a novel mind-body intervention designed to \nattenuate emotional arousal of distressing thoughts and pain. This study evaluated functional connectivity \nchanges in key areas of the brain in patients with chronic pelvic pain receiving the ne T intervention. The \ngoal was to assess whether the ne T intervention was associated with functional connectivity (Fc ) \nchanges in the brain related to reductions in emotional distress and pain, particularly in the limbic areas, \nsensory/pain regions, and cerebellum.\nMethods: This is a prospectively designed study that included twenty-six patients with a diagnosis of \nchronic pelvic pain who were randomised to either the neT intervention or a waitlist control. To evaluate \nthe primary outcome of neurophysiological effects, all participants received resting state functional blood \noxygen level dependent (BolD) magnetic resonance imaging (rs-fMRI) before and after the neT \nintervention or waitlist control period. Pain, mood, anxiety, and quality of life also were assessed.\nResults: c ompared to the control group, the ne T group demonstrated significant improvements in pain \ninterference and pain intensity, and in emotional measures such anxiety and depression. Functional \nconnectivity in the ne T group compared to controls, was significantly decreased in the amygdala, \ncerebellum, and postcentral gyrus. There were also significant correlations between Fc changes and \nchanges in clinical measures.\nConclusions: This study is an initial step towards describing a neurological signature of reducing \nemotional distress in women with chronic pelvic pain. Specifically, Fc changes between the cerebellum \nand the amygdala and sensory areas appears to be associated with a reduction in pain and the effects \nof that pain. Future, larger clinical trials are warranted to further evaluate these mechanisms and ne T as \na potential therapeutic intervention in patients with chronic pelvic pain.\nPLAIN LANGUAGE SUMMARY\nchronic pelvic pain is a serious problem that can make everyday activities like sitting, driving, and even \nintimate moments very difficult. chronic pain can also lead to feelings of anxiety and depression, which \ncan make the pain feel worse. The neuro emotional Technique (ne T) is a type of therapy focusing on \nemotional distress, often a big part of chronic pain that lowers quality of life. This study looked at \nwhether ne T could help people with chronic pelvic pain by reducing their pain, lowering emotional \ndistress, and improving how their brain handles pain. The results showed that people who had neT felt \nless anxious and depressed. They also had changes in the parts of their brain that deal with pain and \nemotions, and were linked to less pain and better emotional coping. This study suggests that ne T might \nbe a helpful treatment for people dealing with chronic pelvic pain.\nIntroduction\nchronic pelvic pain ( cPP) in women is a well-known but \npoorly understood phenomenon. It affects approximately one \nquarter of all women worldwide and is usually treated by \ngynecological specialists ( a hangari 2014). cPP arises from \nseveral aetiologies, most commonly endometriosis, pudendal \nneuralgia, high tone pelvic floor dysfunction, and interstitial \ncystitis, with endometriosis one of the most common of these \nconditions (Raimondo et  al. 2023). The resultant cPP can be \nseverely limiting and debilitating, affecting basic life activities \nsuch as sitting, driving, exercise, and importantly, sexual \n© 2025 t he a uthor(s). Published by i nforma uK limited, trading as taylor & f rancis Group\nCONTACT a ndrew b. newberg  andrew.newberg@jefferson.edu  t homas Jefferson university, 789 east lancaster a venue, suite 110, Villanova, P a 19085, usa.\n supplemental data for this article can be accessed online at https://doi.org/10.1080/01443615.2025.2472767.\nt his article has been corrected with minor changes. t hese changes do not impact the academic content of the article.\nhttps://doi.org/10.1080/01443615.2025.2472767\nt his is an o pen a ccess article distributed under the terms of the c reative c ommons a ttribution license ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, \ndistribution, and reproduction in any medium, provided the original work is properly cited. t he terms on which this article has been published allow the posting of the a ccepted \nManuscript in a repository by the author(s) or with their consent.\nARTICLE HISTORY\nReceived 10 July 2024\na ccepted 22 February \n2025\nKEYWORDS\na mygdala functional \nconnectivity; cerebellar \nfunctional connectivity; \nchronic pelvic pain; \nemotional trauma; \nfunctional magnetic \nresonance imaging; \nneuro emotional \nTechnique\n\n2 D. a. MonTI e T al.\nfunction ( acoG Practice Bulletin 2020). c ommon to cPP are \nemotional symptoms of anxiety and depression, or physical \nor sexual abuse (Meltzer-Brody et  al. 2007).\nPain is a process that is mediated by the nervous system \nthrough changes that occur both peripherally and centrally \n(c ervero et  al. 1994). Using neuroimaging tools, researchers \nhave begun exploring cnS changes induced by pain and the \neffects of various pain therapies ( a dler et  al. 1997, Kupers \net  al. 2000). observations, including those from our group, \nhave identified alterations in the brain’s pain matrix during \nchronic pain and its modulation through pharmacological \nand non-pharmacological therapies (newberg et  al. 2011, \nStøttrup et al. 2023). Key regions implicated in the pain matrix \ninclude the thalamus, amygdala, sensory areas, prefrontal cor -\ntex, and cerebellum. chronic pain also involves changes in \nthe insular cortex and frontal lobes ( yang et  al. 2024). Specific \npain conditions, such as cPP , are associated with disruptions \nin the salience network, anterior cingulate gyrus, and sensory \nregions (Kutch et  al. 2017). Functional connectivity (Fc ) in \nthese networks is typically heightened, intensifying the inter -\nplay between pain and emotional responses (Martucci et  al. \n2015, a s-Sanie et  al. 2016).\nPatients with chronic pain frequently seek non-pharmacological \nand non-surgical management of their symptoms, with overall \nlimited effectiveness (Urits et  al. 2021). This study explores a \nnovel intervention, the neuro emotional Technique (neT), previ-\nously shown to modulate autonomic nervous system function \nand affect emotional connectivity pathways in the brain that \noverlap with pain perception. The intervention combines emo -\ntional, cognitive, and motor processing in a standardised format \ndesigned to help patients reduce their psychophysiological reac-\ntivity to distressing memories, thoughts, and perceptions, includ-\ning those related to pain. We have previously reported on brain \nresponses to the ne T intervention in distressed cancer patients. \nUtilising functional magnetic resonance imaging (fMRI) signifi -\ncant changes in the brain’s reactivity to distressing stimuli were \ndemonstrated (Monti et  al. 2017, 2018), as well as changes in Fc, \nincluding areas that overlap with pain regulation. Specifically, we \nhave found changes in the amygdala, cerebellum, and prefrontal \ncortex associated with the neT intervention.\nGiven the overlap between the brain areas previously \nobserved to be affected by ne T and those involved with chronic \npain, we wanted to assess whether ne T might have a clinical \nimpact on patients with cPP . Given that chronic pain is often \nassociated with heightened Fc in networks linking sensory, cer -\nebellar, and emotional regions, we hypothesised that the inter -\nvention would result in decreased Fc between these regions. \nFurthermore, these reductions in connectivity were anticipated \nto be associated with improvements in pain and emotional \nsymptoms in the treatment group. Thus, our primary outcome \nwas the change in Fc based on MRI data, and the secondary \noutcomes were the self-reported clinical measures of pain per -\nception and emotional status (e.g. anxiety and depression).\nMethods\nParticipants\nThe study was a prospectively designed study. Subjects \nenrolled were adult females with cPP of at least 3 months in \nduration. The specific cause of the pelvic pain was not exclu -\nsionary, but potential participants were excluded if they had \npelvic surgery or any stimulators implanted. Patients were \nexcluded if they had any history of significant and active \nmedical or neurological conditions. Patients were excluded if \nthey had any other major mental disorder or were actively \nparticipating in another emotional therapy. They were allowed \nto continue current treatments for their pelvic pain as long as \nthere were no substantive changes in the three months prior \nto enrolling in the study.\nPatients were recruited through the Department of \nobstetrics and Gynaecology and from posted advertisements \nat the Sidney Kimmel c ancer c entre at Thomas Jefferson \nUniversity. This study was also posted on clinicaltrials.gov \n(nc T03233594). a s an initial screening, potential participants \nwere asked to describe their pain on a scale from 0 to 10 \nwith 10 being the worst pain imaginable, and had to have a \nscore of 7 or higher. This cut-off is at a level considered \nsevere enough to significantly interfere with daily functioning \nwhich would establish the diagnosis of the patients and opti -\nmise the ability to evaluate the effect of the ne T intervention \n(Wolpe 1973, Boonstra et  al. 2016).\na total of 26 participants met the full criteria for participa -\ntion in the study ( Figure 1  and Table 1), a number consistent \nwith our prior study of ne T in cancer patients which showed \nsignificant findings in Fc (Monti et  al. 2018). The subjects \nwere randomised using a permuted block design into two \nparallel groups (IBM SPSS Statistics) that were not significantly \ndifferent. The randomisation was performed by the one of \nthe investigators ( aBn) and provided to the study coordinator \nwho placed subjects into their respective treatment arms \nupon enrolment. Thirteen subjects were assigned to the ne T \nintervention group (average age of 43.0 ± 15.7 years) and thir -\nteen were assigned to the waitlist control condition (average \nage of 42.8 ± 13.6 years). The mean BMI for the ne T group was \n22.5 ± 3.9 and for the control group was 26.9 ± 6.6. Patients \nhad four potential diagnoses – endometriosis, pudendal neu -\nralgia, high tone pelvic floor dysfunction, and interstitial cys -\ntitis. once enrolled, subjects received a battery of psychological \nand pain measures (see below) and the initial MRI scan with \nrs-fMRI.\nEthical approval\nThis study was approved (17D.163) by the Institutional Review \nBoard of Thomas Jefferson University. a ll procedures per -\nformed in this study involving human participants were in \naccordance with the ethical standards of the Institutional \nReview Board of Thomas Jefferson University and with the \n1964 Helsinki declaration. Participating women signed an \ninformed consent form at the first study visit.\nNET intervention\nThe ne T intervention consisted of five sessions which were \napproximately one hour in length, typically one per week. a ll \nsessions were led by a ne T-certified, licenced psychologist \n(aT). o ur previous work suggests that five sessions usually are \nsufficient for the intervention to address the distress of a \n\nBRaIn  FUnc TIon  cHanGeS In  cHR onIc  Pel VIc  PaIn  TReaTeD WITH ne T 3\ngiven situation (Monti et  al. 2017). The focus of the sessions \nwas on the subjective experience of the pain and its distress -\ning effects on all dimensions of life. During the desensitisa -\ntion aspect of the protocol, while thinking about the \ndistressing aspects of the pain experience and the cognitions \nand emotions associated with it, participants were asked to \ndo simple breathing exercises. The intervention integrates the \nuse of acupressure points on the wrists that are thought to \ncorrelate with specific emotional qualities in the Traditional \nchinese Medicine system. Targeted acupressure has shown \npromise for relieving stress and anxiety ( cho et  al. 2021). The \nfocus of the ne T sessions was on the experience of chronic \npain with an emphasis on stress-related aspects of the pain. \nIn summary, the ne T protocol for this study targeted the \nemotions, cognitions, energy, and autonomic activation \nrelated to stressful aspects of the pain experience.\nThe participants underwent the same battery of clinical \nand fMRI evaluations after the ne T intervention that they \nunderwent prior to the intervention. The participants who \nwere placed in the waitlist control group continued usual \ncare for the cPP between the two scans, and all were offered \nthe opportunity to undergo the ne T intervention after the \nstudy period. The waitlist period with standard care is also \nused to try to balance the patient’s expectation of therapeu -\ntic improvement since it is not clear what would be an ade -\nquate placebo condition that would match the elements of \nne T without providing a specific therapeutic benefit.\nFigure 1.  consort flow sheet diagram of the study participants.\nTable 1. d emographics for the two study groups.\ndemographic data\nc ontrol net\nMean ± sd Mean ± sd\nage 42.8 ± 13.6 43.0 ± 15.7\nbody mass index 26.9 ± 6.6 22.5 ± 3.9\ndiagnoses ic-5; eM-2; Ht -4; Pn-8 ic-4; eM-5; Ht -5; Pn-6\nback depression inventory 15.9 ± 12.9 13.6 ± 11.0\nPhysical function 16.2 ± 3.7 16.5 ± 3.9\nic = i nterstitial cystitis; eM = endometriosis; Ht = High tone pelvic floor dys -\nfunction; Pn = Pudendal neuralgia; sd = s tandard deviation.\n\n4 D. a. MonTI e T al.\nPsychological assessments\na ll assessments were conducted in the same office environ -\nment and were collected and managed using the computer \nbased ReDc ap electronic data capture tools hosted at yale \nUniversity (Harris et  al. 2009, 2019), so that the assessor is not \ninvolved in acquiring this data. a ll participants completed the \nBeck Depression Index (Beck et  al. 1961), Spielberger State \nTrait a nxiety Index Spielberger 1983), and PR oMIS ( c ella et  al. \n2010, a mtmann et  al. 2010) which is a clinical scale that eval -\nuates physical function, anxiety, depression, fatigue, sleep \nquality, pain interference, and pain intensity.\nfMRI Imaging protocol\nResting-state fMRI data was obtained using the similar pro -\ntocol as we have used in prior studies (Monti et  al. 2018, \nVedaei et  al. 2021). Briefly, all patients were scanned using \na 3 T Siemens Biograph mMR Pe T-MR scanner with a \n32-channel head coil. Initially, an anatomical T1-image was \nobtained for all subjects to check for any radiological find -\nings of brain abnormality or injury, and for further segmen -\ntation and registration steps during data pre-processing.\nnext, a resting state BolD scan was collected using an e cho \nPlanar Imaging (ePI) sequence to examine intrinsic Fc of the \nbrain regions. The following imaging parameters were used: \nFoV = 23.6 cm; voxel size = 3 × 3 × 4 mm3; TR = 2.0 s; Te = 30 ms; \nslice thickness = 4 mm; number of slices = 34; number of volumes \n= 180; and acquisition time = 366 s. During rs-fMRI, the subjects \nwere instructed to close their eyes, keep their heads still, and \nrest quietly without thinking about anything.\nData processing\nMRI processing was performed in a manner similar to our prior \nstudies evaluating Fc with ne T (Monti et  al. 2018, Vedaei et  al. \n2021). a ll rs-fMRI data were preprocessed using Data Processing \n& a nalysis for Resting-State Brain Imaging (DPaBI, V5.1_201201; \nhttp://rfmri.org/dpabi) based on Statistical Parametric Mapping \n(SPM12; http://www.fil.ion.ucl.ac.uk/spm) running on M aTlaB \nR2020b (The Maths Works, Inc., natick, M a, USa ). The \npre-processing steps are summarised here and are similar to \nour prior studies of the ne T. each individual T1-weighted struc-\ntural image was co-registered to the mean of the realigned ePI \nimages. a fter this step, all resting-state data were spatially nor -\nmalised to the ePI template in Montreal neurological Institute \n(MnI) space with a resampling voxel size of 3 × 3 × 3 mm. \nc orrection for head motion was applied (Vedaei et  al. 2022). \nThen, signal from white matter and cerebrospinal fluid were \nregressed out and filtered with a temporal band-pass of 0.01–\n0.08 Hz to reduce the effects of low-frequency drifts and \nhigh-frequency respiratory and cardiac noise.\nFunctional connectivity analysis\nSeed-based voxel-wise Fc analysis was carried out after \nband-pass filtering of 0.01–0.08 Hz. The seed regions were cre -\nated as a spherical 5-mm region of interest (R oI) around the \ncentre of mass coordinates. The seeds used included the follow-\ning that were based on prior studies of the ne T as well as \nregions expected to be involved with chronic pain (Monti et  al. \n2018): a mygdala, a nterior cingulate, c erebellum c rus, \ncerebellum, Hippocampus, Insula, Postcentral, Precentral, \nSupplementary motor area; all left and right sides. Fc was mea -\nsured using Pearson’s correlation coefficient between time series \nof the seeds and the rest of the time series in the gray matter \narea. For standardisation purpose, a Fisher’s z-transform was \napplied to change Fc to Z values and standardised Fc maps \nwere obtained. These converted z-score maps of Fc are referred \nto as the Pearson correlation coefficient maps (Vedaei et al. 2022).\nStatistical analysis\nStatistical analyses are performed in an automated manner \nwith the subjects separated by groups. o ur primary outcome \nwas the change in Fc based on MRI data, and the secondary \noutcomes were the self-reported clinical measures of pain \nperception and emotional status (e.g. anxiety and depres -\nsion). a nalysis of covariance ( ancoV a ) analysis was executed \nto estimate group-by-time interaction between treatment and \ncontrol groups and baseline and follow-up scans. Gaussian \nRandom Field (GRF) was applied for correction of multiple \ncomparison with p-value voxel < 0.05 and the minimum clus -\nter size was defined 200 voxels. The motion parameters and \nage were used as covariates.\nPartial correlation analysis was conducted to estimate the \ncorrelation between the neuropsychological scores and the \nrs-fMRI metrics, controlling for age and gender as the covari -\nates. The clusters showing significant differences from \nancoV a analysis were selected as regions of interest (R oIs). \nThe mean of Fc was extracted over the mask of R oIs. \nSpearman’s rank correlation coefficients between the mean \nvalues of seed-based Fc and neurophysiological scores were \ngenerated for all the patients within the nutrition and the \ncontrol groups. The linear correlation being considered signif -\nicant if p value was less than 0.05.\nFor the secondary outcomes related to clinical and psycho -\nlogical measures, a paired t-test was used to compare within \ngroup differences between the pre and post evaluation time \npoints, and a repeated measures anoV a was used to deter -\nmine the group vs time differences (IBM SPSS Statistics).\nResults\nClinical results\nThe clinical data demonstrated significant improvements in the \nneT group between the pre and post time points in specific \nmeasures related to anxiety, depression, fatigue, pain percep -\ntion, and pain interference (Table 2). The results with (*) indicate \nsignificant difference between the ne T and control group.\nFunctional connectivity results\nThere were significant changes observed in Fc in the ne T \ngroup compared to the control group between the pre and \n\nBRaIn  FUnc TIon  cHanGeS In  cHR onIc  Pel VIc  PaIn  TReaTeD WITH ne T 5\npost scan conditions. These are shown in Table 3  with repre -\nsentative examples shown in Figure 2( a –e).\nCorrelational analysis\nThe correlation between changes of resting-state Fc (in the \nsignificant clusters found from ancoV a ) was measured with \nchanges of clinical scores ( Table 4).\nDiscussion\nThis study evaluated brain Fc in patients with cPP who \nreceived ne T to address both the pain itself as well as the \ndistressing emotional elements of pain that may contrib -\nute to suffering. The results suggest that the ne T inter -\nvention was clinically useful in patients with cPP , with \nspecific improvements in pain intensity, pain interference, \ndepression, and anxiety symptoms. clinical improvement \nwas associated with Fc changes in both affective and pain \nregions of the brain. This data is an important step in \nunderstanding the mechanism of treatment effect when \naddressing the emotional distress associated with \nchronic pain.\nThere were a number of significant changes observed in \npatients treated with the ne T intervention compared to \ncontrols including cerebellar regions, post-central sensory \nTable 2. d ifferences in clinical measures in the net and waitlist control group showing significant improvements in the net group with * representing significance \nbetween the net and control groups.\nneuropsychological tests\nc ontrol net\nbaseline f ollow-up\nGroup p-value\nbaseline f ollow-up\nGroup p-valueMean ± sd Mean ± sd Mean ± sd Mean ± sd\nstate trait anxiety inventory\nstate anxiety 44.5 ± 11.0 45.6 ± 8.7 0.362 40.7 ± 9.0 38.1 ± 8.2 0.180\ntrait anxiety 49.8 ± 7.5 50.0 ± 8.1 0.468 46.0 ± 8.2 42.5 ± 5.4 0.045\nback depression inventory 15.9 ± 12.9 17.2 ± 11.2 0.174 13.6 ± 11.0 8.8 ± 8.5 0.032*\nProMis -29\nPhysical function 16.2 ± 3.7 15.4 ± 4.2 0.130 16.5 ± 3.9 16.3 ± 5.0 0.349\na nxiety 9.76 ± 2.8 15.4 ± 2.8 0.169 10.0 ± 4.5 7.9 ± 3.2 0.015*\ndepression 9.7 ± 4.4 10.2 ± 4.5 0.200 7.1 ± 3.5 6.2 ± 3.0 0.080\nf atigue 12.5 ± 3.6 13.4 ± 4.3 0.198 14.1 ± 3.7 10.6 ± 4.0 0.002*\nsleep quality 11.6 ± 3.1 11.4 ± 3.6 0.390 11.2 ± 4.4 9.9 ± 4.2 0.152\nPain interference 14.3 ± 4.2 12.3 ± 5.3 0.030 12.1 ± 4.6 9.8 ± 5.8 0.021\nPain intensity 5.7 ± 2.4 5.4 ± 2.5 0.183 6.5 ± 1.9 5.2 ± 2.4 0.005*\nAbbreviations: sd: s tandard d eviation; net : neuroemotional technique.\nTable 3. ancoV a analysis, interaction effect (group-by-time) showing the functional connectivity that was significantly different between \nthe pre and post scans when the net group was compared to the control group.\nseed brain region Voxels Peak Mni coordinates f score (peak value)\nc erebellum c rus r Postcentral r 435 39 − 24 39 16.57\nc erebellum c rus r c alcarine r 207 15 − 75 9 14.08\nc erebellum l Postcentral r 882 51 − 21 60 21.25\nc erebellum l Postcentral l 641 −54 − 27 57 16.99\nc erebellum r Postcentral r 959 42 − 21 45 19.57\nc erebellum r Postcentral l 391 −54 − 27 57 12.20\na mygdala l c ingulate_Mid r 422 −21 − 24 81 15.56\na mygdala l f rontal_inf_t ri l 280 −36 30 15 14.63\na mygdala l Parietal_inf l 204 −60 − 42 39 9.43\na mygdala r f rontal_sup_Medial r 325 6 39 45 15.14\na mygdala r supraMarginal r 287 42 − 39 42 22.77\na mygdala r c ingulate_Mid l 248 −15 − 54 36 13.18\na mygdala r Precentral l 239 −57 − 3 42 14.27\na mygdala r temporal_Pole_sup r 221 60 12 − 9 16.07\na mygdala r Precentral r 212 54 3 24 18.11\na nterior c ingulate l Parietal_inf r 271 36 − 48 54 10.76\na nterior c ingulate r Precuneus l 211 −12 − 51 42 17.17\nHippocampus l f rontal_sup l 324 −21 45 36 13.15\ninsula l f rontal_inf_t ri l 272 −54 15 39 13.15\ninsula l Precuneus l 258 −15 − 54 36 24.13\nPostcentral l c erebellum l 459 −30 − 63 − 27 19.67\nPostcentral r c erebellum l 1848 −30 − 63 − 27 24.71\nPrecentral l temporal_sup r 398 57 0 − 9 18.84\nPrecentral l Putamen l 379 −18 12 9 24.97\nPrecentral l acc_pre l 260 −3 39 6 24.04\nPrecentral l temporal_Mid l 255 −54 − 21 − 6 14.20\nPrecentral r f rontal_sup r 239 18 48 48 12.29\nPrecentral r Pallidum l 205 −21 − 3 −3 12.60\nsupplementary Motor a rea l Putamen l 288 −21 − 3 3 15.07\nsupplementary Motor a rea r f rontal_inf_t ri l 283 −48 27 15 13.82\nt he values are Grf corrected for a voxel p < 0.05, minimum cluster size of 200 voxels, and corrected for motion parameters and age.\nAbbreviations: l: l eft; r: r ight; i nf: i nferior; sup: superior; Mid: Middle; f rontal_inf_t ri: i nferior frontal gyrus, triangular part; acc: \na nterior c ingulate c ortex; Mni: Montreal neurological i nstitute.\n\n6 D. a. MonTI e T al.\nregions, the amygdala, the cingulate gyrus, as well as sev -\neral frontal regions. The decreased Fc from the ne T inter -\nvention among several motor and pre-motor regions, \nparticularly with several dopaminergic areas and the fron -\ntal regions, may explain some of the clinical effects seen. \no ther studies have revealed heightened connectivity in \nthese regions in chronic pain patients ( c oppieters et  al. \n2021; Dorado et  al. 2024). Therefore, reducing this connec -\ntivity, could arguably be associated with decreased pain \nperception. In addition, studies of placebo interventions \nFigure 2.   (a–e) r epresentative figures of the findings in the table 2  are provided below showing areas that had significant differences in functional connectivity \nbetween the pre and post scans in the net and waitlist control group. ( a bbreviations: l: l eft; r: r ight; i nf: i nferior; sup: superior; Mid: Middle; f rontal_inf_tri: \ninferior frontal gyrus, triangular part; acc: a nterior c ingulate c ortex).\n\nBRaIn  FUnc TIon  cHanGeS In  cHR onIc  Pel VIc  PaIn  TReaTeD WITH ne T 7\nhave typically revealed increased Fc ( a shar et al . 2024). \nThus, the present findings seem more specific for the ne T \nintervention.\nfMRI studies have revealed that the motor cortex is acti -\nvated in response to painful stimuli (Peyron et  al. 2000). For \nexample, when subjects are exposed to noxious heat or elec -\ntrical shocks, regions within the motor cortex, including the \nsupplementary motor area (SM a ) and premotor cortex (PMc ), \nshow increased activity (Peyron et  al. 2007). Beyond activa -\ntion, the motor cortex also has been shown to modulate pain \nperception (eccleston and c rombez 1999). Motor imagery, the \nmental simulation of movement without actual execution, \ncan reduce pain perception (Moseley and Flor 2012). The \nmotor cortex is connected to descending pain modulation \npathways that inhibit pain signals at the spinal cord level \n(Fields 2004). Reducing the connectivity between the motor \ncortex and these regions, as found in the present study, may \nallow the inhibitory pathways to function more actively \nreducing the pain signals.\nThis study also implicates the cerebellum with the ther -\napeutic effects of ne T. This is consistent with our prior \nstudy of ne T in distressed cancer patients where it was \ndemonstrated that the cerebellum appears to play an \nimportant role in the modulation of negative or traumatic \nemotions. The potential role of the cerebellum in modu -\nlating emotions and autonomic reactivity has been sup -\nported by clinical and neuroimaging data (Stoodley and \nSchmahmann 2009, 2010).\nRelevant to the present study, prior fMRI studies show \nthat negative emotional stimuli activate the cerebellum, pos -\nterior cingulate, and fusiform gyrus (Park et  al . 2010, \nSchraa-Tam et  al. 2012). The mechanism is based in part on \nFigure 2.  c ontinued.\n\n8 D. a. MonTI e T al.\nhow regions of the cerebellum are activated by negative or \naversive stimuli independent of regulation of motor or auto -\nnomic processes (Utz et  al. 2015). The vermis appears to be \ninvolved in forming emotional memories including how \nmemories are acquired (Supple and Kapp 1993), how they \nare stored and retrieved (Sacchetti et  al. 2007), and how \nthey dissipate (Dempesy et al . 1983). o f particular relevance \nto the present study, Fc between the cerebellum and emo -\ntional regions such as the insula has been correlated with \nmore intense pain in patients with endometriosis (Szabo \net  al. 2022). Thus, reducing such connections may help \nreduce the overall salience of the pain signals, and also \nenable more effective modulation of pain pathways via \ninhibitory processes.\nUsing MRI techniques similar to the current study, studies \nhave found functional coherence between the cerebellum \nand amygdala, hippocampus, hypothalamus, insula, and ante -\nrior cingulate ( a llen et  al. 2005, Seeley et  al. 2007, Sang et  al. \n2012). The ne T intervention may be of particular value in \nhelping people regulate negative emotions and associated \nmemories because the mechanism of action of this technique \nlikely affects motor, emotional, and sensory processing.\nThis relationship is further exemplified by correlations \nbetween the change in Fc in the aforementioned brain \nareas and changes on various clinical measures. Fc between \nthe amygdala and frontal regions was associated with \nimprovements in pain intensity along with improvements \nin various measures of negative emotions. The change in \nnegative emotions was also correlated with Fc changes \nbetween the amygdala and cingulate gyrus, frontal lobe \nincluding the precentral region, and parietal lobe struc -\ntures. The Fc between the frontal lobes and both the insula \nand hippocampus were similarly correlated with improve -\nments in negative emotions. Thus, ne T appears to be asso -\nciated with widespread changes in Fc in a number of brain \nareas that support pain perception, motor function, and \nemotional processing.\nRegarding limitations, the current study was exploratory \nand the sample size will need to be expanded to confirm the \nclinical and Fc changes observed in these patients. Future, \nlarger studies should include an analysis of covariables such \nas age, duration of chronic pain, gender, and other factors. \nWe used a waitlist control group, however, the next level of \ninvestigation should include an active control group that \naccounts for attention and therapeutic time to mitigate \nexpectation effects.\nThe results of this study represent the first investigation \ninto both the Fc changes and clinical effects of neuro \nemotional Technique (ne T) in patients with cPP . The findings \nsuggest that a short course of ne T not only alters brain Fc \nFigure 2.  c ontinued.\n\nBRaIn  FUnc TIon  cHanGeS In  cHR onIc  Pel VIc  PaIn  TReaTeD WITH ne T 9\nbut that these changes are directly associated with improve -\nments in clinical symptoms. a practical implication of this \nresearch is that ne T may serve as a valuable therapeutic \nintervention, particularly because it targets emotional distress, \nwhich is a common contributor to chronic pain conditions. \nThis initial study is encouraging and emphasises the need for \nlarger scale clinical and neurophysiological trials of this poten -\ntially important therapeutic approach for patients with cPP . \na n important goal would be to corroborate the present find -\nings and establish the generalisability of the ne T intervention \nin this patient population.\nAuthor contributions\na ll authors meet the IcMJe criteria for authorship.\nDisclosure statement\na ll authors have no conflict of interest to declare.\nFunding\nThis study was funded by a grant from the Marcus Foundation. \nTable 4.  Pearson correlation analysis results between clinical measures and structures found to have significant changes in functional connectivity (interaction \neffect (group*time), showing the correlations that were significantly different between the pre and post scans when the net group was compared to the control \ngroup.\nseed brain region clinical test Pearson’s r p-Value\na mygdala l c ingulate_Mid r state a nxiety 0.752 0.012\na mygdala l c ingulate_Mid r depression 0.797 0.006\na mygdala l c ingulate_Mid r a nxiety 0.666 0.035\na mygdala l f rontal_inf_t ri l state a nxiety 0.784 0.007\na mygdala l f rontal_inf_t ri l f atigue 0.683 0.030\na mygdala l f rontal_inf_t ri l sleep Quality 0.865 0.001\na mygdala l f rontal_inf_t ri l Pain i ntensity 0.720 0.019\na mygdala l Parietal_inf l state a nxiety 0.826 0.003\na mygdala l Parietal_inf l trait a nxiety 0.666 0.036\na mygdala l Parietal_inf l sleep Quality 0.793 0.006\na mygdala r f rontal_sup_Medial r trait a nxiety 0.690 0.027\na mygdala r f rontal_sup_Medial r depression 0.636 0.048\na mygdala r f rontal_sup_Medial r f atigue 0.732 0.016\na mygdala r f rontal_sup_Medial r a nxiety 0.643 0.045\na mygdala r supraMarginal r state a nxiety 0.792 0.006\na mygdala r supraMarginal r depression 0.772 0.009\na mygdala r supraMarginal r f atigue 0.688 0.028\na mygdala r supraMarginal r a nxiety 0.779 0.008\na mygdala r c ingulate_Mid l trait a nxiety 0.709 0.022\na mygdala r c ingulate_Mid l f atigue 0.746 0.013\na mygdala r c ingulate_Mid l a nxiety 0.787 0.007\na mygdala r Precentral l state a nxiety 0.838 0.002\na mygdala r Precentral l trait a nxiety 0.656 0.039\na mygdala r Precentral l depression 0.694 0.026\na mygdala r Precentral l f atigue 0.696 0.026\na mygdala r Precentral l a nxiety 0.673 0.033\na mygdala r Precentral l sleep Quality 0.745 0.013\na mygdala r temporal_Pole_sup r depression 0.717 0.020\na mygdala r temporal_Pole_sup r a nxiety 0.640 0.460\na mygdala r Precentral r state a nxiety 0.761 0.011\na mygdala r Precentral r trait a nxiety 0.689 0.027\na mygdala r Precentral r depression 0.680 0.030\na mygdala r Precentral r depression 0.773 0.009\nc erebellum c rus r c alcarine r Pain i nterference 0.637 0.048\nc erebellum r Postcentral r depression 0.768 0.010\nHippocampus l f rontal_sup l depression 0.717 0.020\ninsula l inf f ront l state a nxiety 0.852 0.002\ninsula l inf f ront l trait a nxiety 0.697 0.025\ninsula l inf f ront l depression 0.728 0.017\ninsula l inf f ront l depression 0.860 0.001\ninsula l inf f ront l a nxiety 0.712 0.021\ninsula l inf f ront l sleep Quality 0.666 0.035\ninsula l Precuneus l depression 0.664 0.036\ninsula l Precuneus l a nger 0.677 0.031\nPrecentral r Pallidum l state a nxiety 0.706 0.023\nPrecentral r Pallidum l trait a nxiety 0.692 0.027\nPrecentral r Pallidum l depression 0.767 0.010\nsuppl Motor a rea l Putamen l trait a nxiety 0.770 0.009\nsuppl Motor a rea l Putamen l depression 0.759 0.011\nsuppl Motor a rea l Putamen l f atigue 0.639 0.047\nsuppl Motor a rea l Putamen l a nxiety 0.733 0.016\nsuppl Motor a rea r inf f ront l state a nxiety 0.648 0.043\nsuppl Motor a rea r inf f ront l trait a nxiety 0.704 0.023\nsuppl Motor a rea r inf f ront l depression 0.670 0.034\nt he values are Grf corrected for a voxel p < 0.05, a minimum cluster size of 200 voxels, and corrected for motion parameters, and age.\nAbbreviations: l: l eft; r: r ight; i nf: i nferior; sup: superior; Mid: Middle; f rontal_inf_t ri: i nferior frontal gyrus, triangular part.\n\n10 D. a. 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