Modeling cognitive and emotional processes: A novel neural network architecture

Neural Networks

Volumn 23, Issue 10, 2010, Pages 1155-1163

  Khashman, Adnan ^a  

^a NEAR EAST UNIVERSITY   (Turkey)

Author keywords

Back propagation; Dorsal and ventral neurons; Emotion and cognition; Emotional neural networks; Face recognition

Indexed keywords

COMPUTATIONAL MODEL; DORSAL AND VENTRAL NEURONS; EMOTION AND COGNITION; EMOTIONAL INFORMATION; EMOTIONAL NEURAL NETWORKS; HIDDEN LAYERS; HUMAN PERCEPTION; LOCAL FEATURE; MACHINE-LEARNING; NATURAL INTELLIGENCE; NOVEL NEURAL NETWORK; RECOGNITION RATES; VISUAL STIMULUS;

BACKPROPAGATION; BEHAVIORAL RESEARCH; COGNITIVE SYSTEMS; DATA PROCESSING; DECISION MAKING; FACE RECOGNITION; LEARNING ALGORITHMS; NETWORK ARCHITECTURE; NETWORK LAYERS;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COGNITION; CONTROLLED STUDY; DATA BASE; DECISION MAKING; EMOTION; IMAGE PROCESSING; INFORMATION PROCESSING; LEARNING ALGORITHM; NERVE CELL NETWORK; PRIORITY JOURNAL; VISUAL MEMORY; VISUAL STIMULATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COGNITION; EMOTIONS; FACIAL EXPRESSION; HUMANS; MODELS, NEUROLOGICAL; NERVE NET; NEURONS; PATTERN RECOGNITION, AUTOMATED; PATTERN RECOGNITION, VISUAL; RECOGNITION (PSYCHOLOGY);

EID: 78149495493     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2010.07.004     Document Type: Article

References (55)

1. Abu Maria K., Abu Zitar R. Emotional agents: a modelling and an application. Information and Software Technology 2007, 49:695-716.
2. AT & T (2009). Laboratories Cambridge. The ORL database of faces. Available: [Online]. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html.
3. Bates J. The role of emotion in believable agents. Communications of the ACM 1994, 37(7):122-125.
4. Belhumeur P.N., Hespanha J.P., Kriegman D.J. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 1997, 19(7):711-720.
5. Blangero A., Coello Y., Striemer C., Rossetti Y., Danckert J., Pisella L. Dorsal and ventral stream interactions: evidence from optic ataxia. Symposium I: illusions in action: what have illusory contexts told us about the neural control of action?. Brain and Cognition 2008, 67:S2-S3.
6. Canamero D. Designing emotions for activity selection in autonomous agents. Emotions in humans and artifacts 2003, 115-148. MIT Press, Cambridge, MA. R. Trappl, P. Petta, S. Payr (Eds.).
7. Canamero L. Emotion understanding from the perspective of autonomous robots research. Neural Networks 2005, 18(4):445-455.
8. Chokshi, K., Panchev, C., Wermter, S., & Taylor, J. G. (2004). Knowing what and where: a computational model for visual attention. In Proceedings of the IEEE international joint conference on neural networks (pp. 519-524).
9. Coutinho, E., & Cangelosi, A. (2007). Emotion and embodiment in cognitive agents: from instincts to music. In Proceedings of the IEEE international conference on integration of knowledge intensive multi-agent systems (pp. 133-138).
10. Coutinho, E., Miranda, E. R., & Cangelosi, A. (2005). Towards a model for embodied emotions. In C. Bento, A. Cardoso, & G. Dias (Eds.), In Proceedings of the Portugese conference on artificial intelligence (pp. 54-63).
11. Doya K. Meta-learning and neuro-modulation. Neural Networks 2002, 15(4):495-506.
12. Drevets W.C., Raichle M.E. Reciprocal suppression of regional cerebral blood flow during emotional versus higher cognitive processes: implications for interactions between emotion and cognition. Cognition & Emotion 1998, 12(3):353-385.
13. El-Nasr M.S., Yen J., Ioerger T.R. FLAME-fuzzy logic adaptive model of emotions. Autonomous Agents and Multi-Agent Systems 2000, 3(3):219-257.
14. Fragopanagos N., Taylor J.G. Modelling the interaction of attention and emotion. Neurocomputing 2006, 69(16-18):1977-1983.
15. Gnadt W., Grossberg S. SOVEREIGN: an autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal. Neural Networks 2008, 21:699-758.
16. Gobbini M.I., Haxby J.V. Neural systems for recognition of familiar faces. Neuropsychologia 2007, 45(1):32-41.
17. Gratch, J. (2000). Modelling the interplay between emotion and decision making. In Proceedings of the 9th conference on computer generated forces and behavioral representation (pp. 1-11).
18. Grossberg S., Gutowski W.E. Neural dynamics of decision making under risk: affective balance and cognitiveemotional interactions. Psychological Review 1987, 94(3):300-318.
19. Grossberg S., Merrill J.W.L. A neural-network model of adaptively timed reinforcement learning and hippocampal dynamics. Cognitive Brain Research 1992, 1(1):3-38.
20. Grossberg S., Seidman D. Neural dynamics of autistic behaviors: cognitive, emotional, and timing substrates. Psychological Review 2006, 113(3):483-525.
21. He X., Yan S., Hu Y., Niyogi P., Zhang H.J. Face recognition using Laplacian faces. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005, 27(3):328-340.
22. Josephs I.E. A psychological analysis of a psychological phenomenon: the dialogical construction of meaning. Social Science Information 2000, 39(1):115-129.
23. Khashman, A. (2006). Face recognition using neural networks and pattern averaging. In J. Wang, Z. Yi, J.M. Zurada, B.L. Lu, & H. Yin (Eds.), In Advances in neural networks. Chengdu, China (pp. 98-103).
24. Khashman A. A modified back propagation learning algorithm with added emotional coefficients. IEEE Transactions on Neural Networks 2008, 19(11):1896-1909.
25. Khashman A. Application of an emotional neural network to facial recognition. Neural Computing and Applications 2009, 18(4):309-320.
26. Khashman A. Blood cell identification using emotional neural networks. Journal of Information Science and Engineering 2009, 25(6):1737-1751.
27. Khashman A. Emotional system for military target identification. Proceedings of NATO research and technology organisation symposium on information management-exploitation 2009, 19-1-19-12. Information Systems & Technology Panel, Stockholm, Sweden.
28. Kort, B., Reilly, R., & Picard, R. W. (2001). An affective model of interplay between emotions and learning: reengineering educational pedagogy-building a learning companion. In T. Okamoto, R. Hartley, & J.P. Klus (Eds.), In Proceedings of the IEEE international conference on advanced learning technologies (pp. 43-46).
29. Koshizen, T., & Tsujino, H. (2001). To compute learning target location by form and motion attentive visuomotor control system. In Proceedings of the IEEE international joint conference on neural networks (pp. 890-895).
30. Kwak K.C., Pedrycz W. Face recognition using an enhanced independent component analysis approach. IEEE Transactions on Neural Networks 2007, 18(2):530-541.
31. Lamme V.A., Super H., Spekreijse H. Feedforward, horizontal, and feedback processing in the visual cortex. Current Opinion in Neurobiology 1998, 8(4):529-535.
32. Levine D.S. Neural network modelling of emotion. Physics of Life Reviews 2007, 4(1):37-63.
33. Li, G., Zhang, J., Wang, Y., & Freeman, W. J. (2006). Face recognition using a neural network simulating olfactory systems. In J. Wang, Z. Yi, J.M. Zurada, & H. Yin (Eds.), In Advances in neural networks. Chengdu, China (pp. 93-97).
34. Litt A., Eliasmith C., Thagard P. Neural affective decision theory: choices, brains, and emotions. Cognitive Systems Research 2008, 9:252-273.
35. Martinez A.M., Kak A.C. PCA versus LDA. IEEE Transactions on Pattern Analysis and Machine Intelligence 2001, 23(2):228-233.
36. Martinez-Miranda J., Aldea A. Emotions in human and artificial intelligence. Computers in Human Behavior 2005, 21:323-341.
37. Mériau K., Wartenburger I., Kazzer P., Prehn K., Lammers C.H., van der Meer E., et al. A neural network reflecting individual differences in cognitive processing of emotions during perceptual decision making. NeuroImage 2006, 33:1016-1027.
38. Mitchell R.L.C., Elliott R., Barry M., Cruttenden A., Woodruff P.W.R. The neural response to emotional prosody, as revealed by functional magnetic resonance imaging. Neuropsychologia 2003, 41:1410-1421.
39. Morey R.A., Petty C.M., Cooper D.A., LaBar K.S., McCarthy G. Neural systems for executive and emotional processing are modulated by symptoms of posttraumatic stress disorder in Iraq war veterans. Psychiatry Research: Neuroimaging 2008, 162:59-72.
40. Perlovsky L.I. Toward physics of the mind: concepts, emotions, consciousness, and symbols. Physics of Life Reviews 2006, 3(1):23-55.
41. Perlovsky, L. I. (2006b). Integrated emotions, cognition, and language. In Proceedings of the IEEE international joint conference on neural networks (pp. 1570-1575).
42. Perlovsky L. Language and emotions: emotional Sapir-Whorf hypothesis. Neural Networks 2009, 22:518-526.
43. Perlovsky L. Language and cognition. Neural Networks 2009, 22:247-257.
44. Pessoa L. On the relationship between emotion and cognition. Nature Review Neuroscience 2008, 9(1):48-58.
45. Poel, M., den Akker, R., Nijholt, A., & van Kesteren, A. J. (2002). Learning emotions in virtual environments. In R. Trappl (Eds.), In Proceedings of the sixteenth European meeting on cybernetics and system research (pp. 751-756).
46. Poggio, T. (2007). Neuroscience: new insights for AI? In N. Zhong, J.M. Liu, Y.Y. Yao, J.L. Wu, S.F. Lu, & K.C. Li (Eds.), In Web intelligence meets brain informatics. Beijing, China (pp. 32-35).
47. Prinz J.J. Gut reactions-a perceptual theory of emotion 2004, Oxford University Press, Oxford.
48. Rumelhart D., Hinton G.E., Williams R.J. Learning internal representations by error propagation. Parallel distributed processing: explorations in the microstructure of cognition 1986, 318-362. MIT Press, Cambridge, MA. D. Rumelhart, J. McClelland (Eds.).
49. Taylor J.G., Scherer K., Cowie R. Emotion and brain: understanding emotions and modelling their recognition. Neural Networks 2005, 18(4):313-316.
50. Taylor S.F., Liberzon I. Neural correlates of emotion regulation in psychopathology. Trends in Cognitive Sciences 2007, 11(10):413-418.
51. Turk, M. A., & Pentland, A. P. (1991). Face recognition using eigenfaces. In IEEE Proceedings of the conference on computer vision and pattern recognition(pp. 586-591).
52. Ushida, H., Hirayama, Y., & Nakajima, H. (1998). Emotion model for life-like agent and its evaluation. In Proceedings of the 15th national conference on artificial intelligence and the 10th conference on innovative applications of artificial intelligence (pp. 62-69).
53. Xu, P., & Wang, T. (2007). Emotion in decision making under uncertainty and cognitive control: a computational framework. In IEEE Proceedings of the 3rd international conference on natural computation. vol. 2 (pp. 149-154).
54. Zhou, W., Pu, X., & Zheng, Z. (2006). Parts-based holistic face recognition with RBF neural networks. In J. Wang, Z. Yi, J.M. Zurada, B.L. Lu, & H. Yin (Eds.), In Advances in neural networks. Chengdu, China (pp. 110-115).
55. Ziemke T., Lowe R. On the role of emotion in embodied cognitive architectures: from organisms to robots. Cognitive Computation 2009, 1(1):104-117.