Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Brain Topography
Published in: Brain Topography 2/2015

01-03-2015 | Original Paper

Characterization of Post-traumatic Stress Disorder Using Resting-State fMRI with a Multi-level Parametric Classification Approach

Authors: Feng Liu, Bing Xie, Yifeng Wang, Wenbin Guo, Jean-Paul Fouche, Zhiliang Long, Wenqin Wang, Heng Chen, Meiling Li, Xujun Duan, Jiang Zhang, Mingguo Qiu, Huafu Chen

Published in: Brain Topography | Issue 2/2015

Login to get access

Abstract

Functional neuroimaging studies have found intra-regional activity and inter-regional connectivity alterations in patients with post-traumatic stress disorder (PTSD). However, the results of these studies are based on group-level statistics and therefore it is unclear whether PTSD can be discriminated at single-subject level, for instance using the machine learning approach. Here, we proposed a novel framework to identify PTSD using multi-level measures derived from resting-state functional MRI (fMRI). Specifically, three levels of measures were extracted as classification features: (1) regional amplitude of low-frequency fluctuations (univariate feature), which represents local spontaneous synchronous neural activity; (2) temporal functional connectivity (bivariate feature), which represents the extent of similarity of local activity between two regions, and (3) spatial functional connectivity (multivariate feature), which represents the extent of similarity of temporal correlation maps between two regions. Our method was evaluated on 20 PTSD patients and 20 demographically matched healthy controls. The experimental results showed that the features of each level could successfully discriminate PTSD patients from healthy controls. Furthermore, the combination of multi-level features using multi-kernel learning can further improve the classification performance. Specifically, the classification accuracy obtained by the proposed framework was 92.5 %, which was an increase of at least 5 and 17.5 % from the two-level and single-level feature based methods, respectively. Particularly, the limbic structure and prefrontal cortex provided the most discriminant features for classification, consistent with results reported in previous studies. Together, this study demonstrated for the first time that patients with PTSD can be identified at the individual level using resting-state fMRI data. The promising classification results indicated that this method may provide a complementary approach for improving the clinical diagnosis of PTSD.
Literature
Astur RS, St Germain SA, Tolin D, Ford J, Russell D, Stevens M (2006) Hippocampus function predicts severity of post-traumatic stress disorder. Cyberpsychol Behav 9:234–240CrossRefPubMed
Bing X, Ming-Guo Q, Ye Z, Jing-Na Z, Min L, Han C, Yu Z, Jia-Jia Z, Jian W, Wei C, Han-Jian D, Shao-Xiang Z (2013) Alterations in the cortical thickness and the amplitude of low-frequency fluctuation in patients with post-traumatic stress disorder. Brain Res 1490:225–232CrossRefPubMed
Biswal B, Zerrin Yetkin F, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar mri. Magn Reson Med 34:537–541CrossRefPubMed
Blake DD, Weathers FW, Nagy LM, Kaloupek DG, Gusman FD, Charney DS, Keane TM (1995) The development of a clinician-administered PTSD scale. J Trauma Stress 8:75–90CrossRefPubMed
Blanchard EB, Hickling EJ (2004) After the crash: psychological assessment and treatment of survivors of motor vehicle accidents. American Psychological Association, Washington, DCCrossRef
Braun K (2011) The prefrontal–limbic system: development, neuroanatomy, function, and implications for socioemotional development. Clin Perinatol 38:685–702CrossRefPubMed
Brown VM, LaBar KS, Haswell CC, Gold AL, McCarthy G, Morey RA (2014) Altered resting-state functional connectivity of basolateral and centromedial amygdala complexes in posttraumatic stress disorder. Neuropsychopharmacology 39:351–359PubMed
Bryant RA, Felmingham K, Kemp A, Das P, Hughes G, Peduto A, Williams L (2008) Amygdala and ventral anterior cingulate activation predicts treatment response to cognitive behaviour therapy for post-traumatic stress disorder. Psychol Med 38:555–561CrossRefPubMed
Catani M, Dell’acqua F, Thiebaut de Schotten M (2013) A revised limbic system model for memory, emotion and behaviour. Neurosci Biobehav Rev 37:1724–1737CrossRefPubMed
Chang C-C, Lin C-J (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol 2:27CrossRef
Chao LL, Lenoci M, Neylan TC (2012) Effects of post-traumatic stress disorder on occipital lobe function and structure. NeuroReport 23:412–419PubMed
Chao-Gan Y, Yu-Feng Z (2010) DPARSF: a MATLAB toolbox for “pipeline” data analysis of resting-state fMRI. Front Syst Neurosci 4:13PubMedCentralPubMed
Chen S, Li L, Xu B, Liu J (2009) Insular cortex involvement in declarative memory deficits in patients with post-traumatic stress disorder. BMC Psychiatry 9:39CrossRefPubMedCentralPubMed
Chossegros L, Hours M, Charnay P, Bernard M, Fort E, Boisson D, Sancho P-O, Yao SN, Laumon B (2011) Predictive factors of chronic post-traumatic stress disorder 6 months after a road traffic accident. Accid Anal Prev 43:471–477CrossRefPubMed
Cohen J, Cohen P, West SG, Aiken LS (2013) Applied multiple regression/correlation analysis for the behavioral sciences. Routledge, London
Croy I, Schellong J, Joraschky P, Hummel T (2010) PTSD, but not childhood maltreatment, modifies responses to unpleasant odors. Int J Psychophysiol 75:326–331CrossRefPubMed
Dai Z, Yan C, Wang Z, Wang J, Xia M, Li K, He Y (2012) Discriminative analysis of early Alzheimer’s disease using multi-modal imaging and multi-level characterization with multi-classifier (M3). Neuroimage 59:2187–2195CrossRefPubMed
Derogatis LR, Rickels K, Rock AF (1976) The SCL-90 and the MMPI: a step in the validation of a new self-report scale. Br J Psychiatry 128:280–289CrossRefPubMed
Ecker C, Marquand A, Mourao-Miranda J, Johnston P, Daly EM, Brammer MJ, Maltezos S, Murphy CM, Robertson D, Williams SC, Murphy DG (2010) Describing the brain in autism in five dimensions—magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. J Neurosci 30:10612–10623CrossRefPubMed
El Khoury-Malhame M, Reynaud E, Soriano A, Michael K, Salgado-Pineda P, Zendjidjian X, Gellato C, Eric F, Lefebvre MN, Rouby F, Samuelian JC, Anton JL, Blin O, Khalfa S (2011) Amygdala activity correlates with attentional bias in PTSD. Neuropsychologia 49:1969–1973CrossRefPubMed
Etkin A, Wager TD (2007) Functional neuroimaging of anxiety: a meta-analysis of emotional processing in PTSD, social anxiety disorder, and specific phobia. Am J Psychiatry 164:1476–1488CrossRefPubMedCentralPubMed
First MB, Spitzer RL, Gibbon M, Williams JB (1995) The structured clinical interview for DSM-III-R personality disorders (SCID-II). Part II: multi-site test–retest reliability study. J Pers Disord 9:92–104CrossRef
Fox MD, Snyder AZ, Vincent JL, Corbetta M, Van Essen DC, Raichle ME (2005) The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci USA 102:9673–9678CrossRefPubMedCentralPubMed
Fox MD, Corbetta M, Snyder AZ, Vincent JL, Raichle ME (2006) Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc Natl Acad Sci USA 103:10046–10051CrossRefPubMedCentralPubMed
Fox MD, Zhang D, Snyder AZ, Raichle ME (2009) The global signal and observed anticorrelated resting state brain networks. J Neurophysiol 101:3270–3283CrossRefPubMedCentralPubMed
Greicius M (2008) Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol 21:424–430CrossRefPubMed
Guo WB, Liu F, Xue ZM, Xu XJ, Wu RR, Ma CQ, Wooderson SC, Tan CL, Sun XL, Chen JD, Liu ZN, Xiao CQ, Chen HF, Zhao JP (2012) Alterations of the amplitude of low-frequency fluctuations in treatment-resistant and treatment-response depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 37:153–160CrossRefPubMed
Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182
Guyon I, Weston J, Barnhill S, Vapnik V (2002) Gene selection for cancer classification using support vector machines. Mach Learn 46:389–422CrossRef
Haller S, Lovblad KO, Giannakopoulos P, Van De Ville D (2014) Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends. Brain Topogr 27:329–337CrossRefPubMed
Hayasaka S, Laurienti PJ (2010) Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data. Neuroimage 50:499–508CrossRefPubMedCentralPubMed
He Y, Wang J, Wang L, Chen ZJ, Yan C, Yang H, Tang H, Zhu C, Gong Q, Zang Y, Evans AC (2009) Uncovering intrinsic modular organization of spontaneous brain activity in humans. PLoS One 4:e5226CrossRefPubMedCentralPubMed
Hinrichs C, Singh V, Xu G, Johnson S (2009) MKL for robust multi-modality AD classification. In: Yang G-Z, et al. (eds) Medical image computing and computer-assisted intervention—MICCAI 2009. Springer, Berlin, pp 786–794
Jatzko A, Schmitt A, Demirakca T, Weimer E, Braus DF (2006) Disturbance in the neural circuitry underlying positive emotional processing in post-traumatic stress disorder (PTSD). An fMRI study. Eur Arch Psychiatry Clin Neurosci 256:112–114CrossRefPubMed
Jin C, Qi R, Yin Y, Hu X, Duan L, Xu Q, Zhang Z, Zhong Y, Feng B, Xiang H, Gong Q, Liu Y, Lu G, Li L (2014) Abnormalities in whole-brain functional connectivity observed in treatment-naive post-traumatic stress disorder patients following an earthquake. Psychol Med 44:1927–1936
Kessler RC (2000) Posttraumatic stress disorder: the burden to the individual and to society. J Clin Psychiatry 61(Suppl 5):4–12 (discussion 13–14)PubMed
Kessler RC, Borges G, Walters EE (1999) Prevalence of and risk factors for lifetime suicide attempts in the National Comorbidity Survey. Arch Gen Psychiatry 56:617–626CrossRefPubMed
Lanius RA, Williamson PC, Boksman K, Densmore M, Gupta M, Neufeld RW, Gati JS, Menon RS (2002) Brain activation during script-driven imagery induced dissociative responses in PTSD: a functional magnetic resonance imaging investigation. Biol Psychiatry 52:305–311CrossRefPubMed
Lanius RA, Vermetten E, Loewenstein RJ, Brand B, Schmahl C, Bremner JD, Spiegel D (2010) Emotion modulation in PTSD: clinical and neurobiological evidence for a dissociative subtype. Am J Psychiatry 167:640–647CrossRefPubMedCentralPubMed
Lindemer ER, Salat DH, Leritz EC, McGlinchey RE, Milberg WP (2013) Reduced cortical thickness with increased lifetime burden of PTSD in OEF/OIF Veterans and the impact of comorbid TBI. Neuroimage Clin 2:601–611CrossRefPubMedCentralPubMed
Linnman C, Zeffiro TA, Pitman RK, Milad MR (2011) An fMRI study of unconditioned responses in post-traumatic stress disorder. Biol Mood Anxiety Disord 1:8CrossRefPubMedCentralPubMed
Liu F, Guo W, Yu D, Gao Q, Gao K, Xue Z, Du H, Zhang J, Tan C, Liu Z, Zhao J, Chen H (2012a) Classification of different therapeutic responses of major depressive disorder with multivariate pattern analysis method based on structural MR scans. PLoS One 7:e40968CrossRefPubMedCentralPubMed
Liu F, Hu M, Wang S, Guo W, Zhao J, Li J, Xun G, Long Z, Zhang J, Wang Y, Zeng L, Gao Q, Wooderson SC, Chen J, Chen H (2012b) Abnormal regional spontaneous neural activity in first-episode, treatment-naive patients with late-life depression: a resting-state fMRI study. Prog Neuropsychopharmacol Biol Psychiatry 39:326–331
Liu F, Guo W, Fouche JP, Wang Y, Wang W, Ding J, Zeng L, Qiu C, Gong Q, Zhang W, Chen H (2013a) Multivariate classification of social anxiety disorder using whole brain functional connectivity. Brain Struct Funct. doi:10.​1007/​s00429-013-0641-4
Liu F, Guo W, Liu L, Long Z, Ma C, Xue Z, Wang Y, Li J, Hu M, Zhang J, Du H, Zeng L, Liu Z, Wooderson SC, Tan C, Zhao J, Chen H (2013b) Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study. J Affect Disord 146:401–406CrossRefPubMed
Liu F, Suk H-I, Wee C-Y, Chen H, Shen D (2013c) High-order graph matching based feature selection for Alzheimer’s disease identification. In: Mori K, et al. (eds) Medical image computing and computer-assisted intervention—MICCAI 2013. Springer, Berlin, pp 311–318
Liu F, Wee CY, Chen H, Shen D (2014) Inter-modality relationship constrained multi-modality multi-task feature selection for Alzheimer’s disease and mild cognitive impairment identification. Neuroimage 84:466–475CrossRefPubMed
Long Z, Duan X, Xie B, Du H, Li R, Xu Q, Wei L, Zhang SX, Wu Y, Gao Q, Chen H (2013) Altered brain structural connectivity in post-traumatic stress disorder: a diffusion tensor imaging tractography study. J Affect Disord 150:798–806CrossRefPubMed
Margulies DS, Vincent JL, Kelly C, Lohmann G, Uddin LQ, Biswal BB, Villringer A, Castellanos FX, Milham MP, Petrides M (2009) Precuneus shares intrinsic functional architecture in humans and monkeys. Proc Natl Acad Sci USA 106:20069–20074CrossRefPubMedCentralPubMed
Mega MS, Cummings JL, Salloway S, Malloy P (1997) The limbic system: an anatomic, phylogenetic, and clinical perspective. J Neuropsychiatry Clin Neurosci 9:315CrossRefPubMed
Molina ME, Isoardi R, Prado MN, Bentolila S (2010) Basal cerebral glucose distribution in long-term post-traumatic stress disorder. World J Biol Psychiatry 11:493–501CrossRefPubMed
Morey RA, Petty CM, Cooper DA, Labar KS, McCarthy G (2008) Neural systems for executive and emotional processing are modulated by symptoms of posttraumatic stress disorder in Iraq War veterans. Psychiatry Res 162:59–72CrossRefPubMedCentralPubMed
Mourao-Miranda J, Reinders A, Rocha-Rego V, Lappin J, Rondina J, Morgan C, Morgan K, Fearon P, Jones P, Doody G (2012) Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. Psychol Med 42:1037CrossRefPubMedCentralPubMed
Murphy K, Birn RM, Handwerker DA, Jones TB, Bandettini PA (2009) The impact of global signal regression on resting state correlations: are anti-correlated networks introduced? Neuroimage 44:893–905CrossRefPubMedCentralPubMed
Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE (2012) Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:2142–2154CrossRefPubMedCentralPubMed
Qin LD, Wang Z, Sun YW, Wan JQ, Su SS, Zhou Y, Xu JR (2012) A preliminary study of alterations in default network connectivity in post-traumatic stress disorder patients following recent trauma. Brain Res 1484:50–56CrossRefPubMed
Rabinak CA, Angstadt M, Welsh RC, Kenndy AE, Lyubkin M, Martis B, Phan KL (2011) Altered amygdala resting-state functional connectivity in post-traumatic stress disorder. Front Psychiatry 2:62CrossRefPubMedCentralPubMed
Saad ZS, Gotts SJ, Murphy K, Chen G, Jo HJ, Martin A, Cox RW (2012) Trouble at rest: how correlation patterns and group differences become distorted after global signal regression. Brain Connect 2:25–32CrossRefPubMedCentralPubMed
Sato JR, Hoexter MQ, Fujita A, Rohde LA (2012) Evaluation of pattern recognition and feature extraction methods in ADHD prediction. Front Syst Neurosci 6:68CrossRefPubMedCentralPubMed
Satterthwaite TD, Wolf DH, Loughead J, Ruparel K, Elliott MA, Hakonarson H, Gur RC, Gur RE (2012) Impact of in-scanner head motion on multiple measures of functional connectivity: relevance for studies of neurodevelopment in youth. Neuroimage 60:623–632CrossRefPubMedCentralPubMed
Shaw ME, Moores KA, Clark RC, McFarlane AC, Strother SC, Bryant RA, Brown GC, Taylor JD (2009) Functional connectivity reveals inefficient working memory systems in post-traumatic stress disorder. Psychiatry Res 172:235–241CrossRefPubMed
Shin LM, Rauch SL, Pitman RK (2006) Amygdala, medial prefrontal cortex, and hippocampal function in PTSD. Ann N Y Acad Sci 1071:67–79CrossRefPubMed
Sokolova M, Japkowicz N, Szpakowicz S (2006) Beyond accuracy, F-score and ROC: a family of discriminant measures for performance evaluation. In: Sattar A, Kang BH (eds) Advances in artificial intelligence–AI 2006. Springer, Berlin, pp 1015–1021
Tuescher O, Protopopescu X, Pan H, Cloitre M, Butler T, Goldstein M, Root JC, Engelien A, Furman D, Silverman M, Yang Y, Gorman J, LeDoux J, Silbersweig D, Stern E (2011) Differential activity of subgenual cingulate and brainstem in panic disorder and PTSD. J Anxiety Disord 25:251–257CrossRefPubMedCentralPubMed
Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289CrossRefPubMed
Uddin LQ, Kelly AM, Biswal BB, Castellanos FX, Milham MP (2009) Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp 30:625–637CrossRefPubMed
van der Kolk BA (1989) Psychobiology of the trauma response. In: Lerer B, et al. (eds) New directions in affective disorders. Springer, Berlin, pp 443–446
Vincent JL, Patel GH, Fox MD, Snyder AZ, Baker JT, Van Essen DC, Zempel JM, Snyder LH, Corbetta M, Raichle ME (2007) Intrinsic functional architecture in the anaesthetized monkey brain. Nature 447:83–86CrossRefPubMed
Wang J, Wang L, Zang Y, Yang H, Tang H, Gong Q, Chen Z, Zhu C, He Y (2009) Parcellation-dependent small-world brain functional networks: a resting-state fMRI study. Hum Brain Mapp 30:1511–1523CrossRefPubMed
Wang J, Zuo X, Dai Z, Xia M, Zhao Z, Zhao X, Jia J, Han Y, He Y (2013) Disrupted functional brain connectome in individuals at risk for Alzheimer’s disease. Biol Psychiatry 73:472–481CrossRefPubMed
Wee CY, Yap PT, Zhang D, Wang L, Shen D (2014) Group-constrained sparse fMRI connectivity modeling for mild cognitive impairment identification. Brain Struct Funct 219:641–656CrossRefPubMed
Westman E, Aguilar C, Muehlboeck JS, Simmons A (2013) Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer’s disease and mild cognitive impairment. Brain Topogr 26:9–23CrossRefPubMedCentralPubMed
Yan X, Brown AD, Lazar M, Cressman VL, Henn-Haase C, Neylan TC, Shalev A, Wolkowitz OM, Hamilton SP, Yehuda R, Sodickson DK, Weiner MW, Marmar CR (2013) Spontaneous brain activity in combat related PTSD. Neurosci Lett 547:1–5CrossRefPubMed
Yehuda R, Flory JD (2007) Differentiating biological correlates of risk, PTSD, and resilience following trauma exposure. J Trauma Stress 20:435–447CrossRefPubMed
Yin Y, Jin C, Eyler LT, Jin H, Hu X, Duan L, Zheng H, Feng B, Huang X, Shan B, Gong Q, Li L (2012) Altered regional homogeneity in post-traumatic stress disorder: a resting-state functional magnetic resonance imaging study. Neurosci Bull 28:541–549CrossRefPubMed
Zalesky A, Fornito A, Harding IH, Cocchi L, Yucel M, Pantelis C, Bullmore ET (2010) Whole-brain anatomical networks: does the choice of nodes matter? Neuroimage 50:970–983CrossRefPubMed
Zang YF, He Y, Zhu CZ, Cao QJ, Sui MQ, Liang M, Tian LX, Jiang TZ, Wang YF (2007) Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev 29:83–91CrossRefPubMed
Zantvoord JB, Diehle J, Lindauer RJ (2013) Using neurobiological measures to predict and assess treatment outcome of psychotherapy in posttraumatic stress disorder: systematic review. Psychother Psychosom 82:142–151CrossRefPubMed
Zeng L-L, Shen H, Liu L, Wang L, Li B, Fang P, Zhou Z, Li Y, Hu D (2012) Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain 135:1498–1507CrossRefPubMed
Zeng L-L, Wang D, Fox MD, Sabuncu M, Hu D, Ge M, Buckner RL, Liu H (2014) Neurobiological basis of head motion in brain imaging. In: Proceedings of the national academy of sciences of the United States of America, vol 111, pp 6058–6062
Zuo XN, Di Martino A, Kelly C, Shehzad ZE, Gee DG, Klein DF, Castellanos FX, Biswal BB, Milham MP (2010) The oscillating brain: complex and reliable. Neuroimage 49:1432–1445CrossRefPubMedCentralPubMed
Metadata
Title
Characterization of Post-traumatic Stress Disorder Using Resting-State fMRI with a Multi-level Parametric Classification Approach
Authors
Feng Liu
Bing Xie
Yifeng Wang
Wenbin Guo
Jean-Paul Fouche
Zhiliang Long
Wenqin Wang
Heng Chen
Meiling Li
Xujun Duan
Jiang Zhang
Mingguo Qiu
Huafu Chen
Publication date
01-03-2015
Publisher
Springer US
Published in
Brain Topography / Issue 2/2015
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI
https://doi.org/10.1007/s10548-014-0386-2

Other articles of this Issue 2/2015

Brain Topography 2/2015 Go to the issue

Original Paper

Two Intrinsic Coupling Types for Resting-State Integration in the Human Brain

Original Paper

A Local Signature of LTP-Like Plasticity Induced by Repetitive Paired Associative Stimulation

Original Paper

Complex Motor–Cognitive Factors Processed in the Anterior Nucleus of the Thalamus: An Intracerebral Recording Study

Original Paper

Characterisation and Reduction of the EEG Artefact Caused by the Helium Cooling Pump in the MR Environment: Validation in Epilepsy Patient Data

Original Paper

Multimodal Sensory Feedback Associated with Motor Attempts Alters BOLD Responses to Paralyzed Hand Movement in Chronic Stroke Patients

Original Paper

Detecting Functional Hubs of Ictogenic Networks