Skip to main content

Artificial Neural Network Analysis and ERP in Intimate Partner Violence

  • Chapter
  • First Online:

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 69))

Abstract

The aim of this work is to analyze, through artificial neural network models, cortical pattern of women with Intimate Partner Violence (IPV) to investigate representative models of sensitization or habituation to the emotional stimulus in IPV. We investigate the ability of high emotional impact images, during a recognition task, analyzing the electroencephalogram data and event related potentials. Neural network analysis highlights an impairment in IPV group in cortical arousal, during the emotional recognition task. The alteration of this capacity has obvious repercussions on people’s lives, because it involves chronic difficulties in interpersonal relationships.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Romero-Martinez, A., Lila, M., Conchell, R., Gonzalez-Bono, E., Maya-Albiol, L.: Immunoglobulin a response to acute stress in intimate partner violence perpetrators: the role of anger expression-out and testosterone. Biol. Psychol. 96, 66–71 (2014)

    Google Scholar 

  2. Romero-Martinez, A., Lila, M., Williams, R., Gonzalez-Bono, E., Moya-Albiol, L.: Skin conductance rises in preparation and recovery to psychosocial stress and its relationship with impulsivity and testosterone in intimate partner violence perpetrators. Int. J. Psychophysiol. 329–333 (2013)

    Google Scholar 

  3. Wong, J.Y.-H., Fong, D.Y.T., Lai, V., Tiwari, A.: Bridging intimate partner violence and the human brain: a literature review. Trauma Violence Abuse 15, 22–33 (2014)

    Article  Google Scholar 

  4. Almli, L., Fani, N., Ressler, K., Smith, A.: Genetic approaches to understanding post-traumatic stress disorder. Int. J. Neuropsychopharmacol. 355–370 (2014)

    Google Scholar 

  5. Harvey, G., Bryant, R., Dang, S.: Autobiographical memory in acute stress disorder. J. Consul. Clin. Psychol. 500–506 (1998)

    Google Scholar 

  6. Vasterling, J., Duke, L., Brailey, K., Constans, J., Allain Jr., A., Sutker, P.: Attention, learning, and memory performance and intellectual resources in Vietnam veterans; PTSD and no disorder comparations. Neuropsychology 16, 5–14 (2002)

    Article  Google Scholar 

  7. Wheeler, M., Buckner, R.: Functional-anatomic correlates of remembering and Knowing. Neuroimage 1337–1349 (2004)

    Google Scholar 

  8. Nemeroff, C., Sherin, J.: Post traumatic stress disorder: the neurobiological impact of psychological trauma. Dialogues Clin. Neurosci. 13(3), 263–278 (2011)

    Google Scholar 

  9. Luck, S.: An Introduction to the Event-Related Potential Technique, pp. 1–357. The MIT Press (2005)

    Google Scholar 

  10. Vogel, E.K., Luck, S.J.: The visual N1 component as an index of a discrimination process. Psychophysiology 37, 190–203 (2000)

    Article  Google Scholar 

  11. Karl, A., Malta, L., Maercker, A.: Meta-analytic review of event-related potential studies in post-traumatic stress disorder. Biol. Psychol. 71, 123–147 (2006)

    Article  Google Scholar 

  12. Invitto, S., Mignozzi, A., Quarta, M., Sammarco, S., Nicolardi, G., de Tommaso, M.; Intimate partner violence and emotional face recognition. In: Psychophysiology-SPR 54th Annual Meeting Society of Psychophysiological Research, at Atlanta, 2014, Wiley Online Library

    Google Scholar 

  13. Kemperman, C.J.F.: Helsinki declaration. The Lancet (1982)

    Google Scholar 

  14. Invitto, S., Faggiano, C., Sammarco, S., De Luca, V., De Paolis, L.: Haptic, virtual interaction and motor imagery: entertainment tools and psychophysiological testing. Sensors 16(3), 394 (2016)

    Article  Google Scholar 

  15. Ahsen, M.E., Singh, N.K., Boren, T., Vidyasagar, M., White, M.A.: A new feature selection algorithm for two-class classification problems and application to endometrial cancer. In: 51st IEEE Annual Conference on Decision and Control (CDC), Maui, Hawaii, USA, pp. 2976–2982. IEEE (2012)

    Google Scholar 

  16. Menolascina, F., Tommasi, S., Paradiso, A., Cortellino, M., Bevilacqua, V., Mastronardi, G.: Novel data mining techniques in aCGH based breast cancer subtypes profiling: the biological perspective. In IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology, 2007, CIBCB’07, pp. 9–16. IEEE (2007)

    Google Scholar 

  17. Scolaro, G.R., De Azevedo, F.M.: Classification of epileptiform events in raw EEG signals using neural classifier. In: 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT), vol. 5, pp. 368–372. IEEE (2010)

    Google Scholar 

  18. Bevilacqua, V., Mastronardi, G., Menolascina, F., Pannarale, P., Pedone, A.: A novel multi-objective genetic algorithm approach to artificial neural network topology optimisation: the breast cancer classification problem. In: International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada, pp. 1958–1965. IEEE (2006)

    Google Scholar 

  19. Bevilacqua, V., Cassano, F., Mininno, E., Iacca, G.: Optimizing feed-forward neural network topology by multi-objective evolutionary algorithms: a comparative study on biomedical datasets. In: Advances in Artificial Life, Evolutionary Computation and Systems Chemistry, pp. 53–64. Springer International Publishing (2015)

    Google Scholar 

  20. Sovierzoski, M.A., Argoud, F.I.M., de Azevedo, F.M.: Evaluation of ANN classifiers during supervised training with roc analysis and cross validation. In: International Conference on BMEI, vol. 1, pp. 274–278. IEEE (2008)

    Google Scholar 

  21. Kimble, M., Kaloupek, D., Kaufman, M.: Stimulus novelty differentially affects attentional allocation in PTSD. Biol. Psychiatry 880–890 (2000)

    Google Scholar 

  22. Javanbakht, A., Liberzon, I., Amirsadri, A., Gjini, K., Boutros, N.: Event-relates potential studies of post-traumatic stress disorder: a critical review and synthesis. Biol. Mood Anxiety Disord. 1–5 (2011)

    Google Scholar 

  23. Karl, A., Schaefer, M., Malta, L., Dorfel, D., Rohlender, N., Werner, A.: A meta-analysis of structural brain abnormalities in PTSD. Neurosci. Biobehav. Rev. 1004–1031 (2006)

    Google Scholar 

  24. Kimble, M., Frueh, B., Marks, L.: Dose the modified Stroop effect exist in PTSD? Evidence from dissertation abstract and the peer reviewed literature. J. Anxiety Disord. 23(5), 650–655 (2009)

    Article  Google Scholar 

  25. Kimble, M., Fleming, K., Bandy, C., Kim, J., Zambetti, A.: Eye tracking and visual attention to threating stimuli in veterans of the Iraq war. J. Anxiety Disord. 24, 293–299 (2010)

    Google Scholar 

Download references

Acknowledgements

‘Università del Salento — ‘5 for Thousand Research Fund’.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Sara Invitto or Vitoantonio Bevilacqua .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Invitto, S. et al. (2018). Artificial Neural Network Analysis and ERP in Intimate Partner Violence. In: Esposito, A., Faudez-Zanuy, M., Morabito, F., Pasero, E. (eds) Multidisciplinary Approaches to Neural Computing. Smart Innovation, Systems and Technologies, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-319-56904-8_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-56904-8_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56903-1

  • Online ISBN: 978-3-319-56904-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics