Dissociated Emergent Response System and Fine-Processing System in Human Neural Network and a Heuristic Neural Architecture for Autonomous Humanoid Robots

The current study investigated the functional connectivity of the primary sensory system with resting state fMRI and applied such knowledge into the design of the neural architecture of autonomous humanoid robots. Correlation and Granger causality analysis was utilized to reveal the functional connectivity patterns. Dissociation was found among the primary sensory system, in that the olfactory cortex and the somatosensory cortex were strongly connected to the amygdala whereas the visual cortex and the auditory cortex were strongly connected with the frontal cortex. The posterior cingulate cortex and the anterior cingulate cortex were found to maintain constant communication with the primary sensory system, the frontal cortex, and the amygdala. Such neural architecture inspired the design of dissociated emergent response system and fine-processing system in autonomous humanoid robots, with separate processing units and another consolidation center to coordinate the two systems. Such design can help autonomous robots to detect and respond quickly to danger, so as to maintain their sustainability and independence.

[1]  G. Kramer Auditory Scene Analysis: The Perceptual Organization of Sound by Albert Bregman (review) , 2016 .

[2]  M. Torrens Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[3]  C. Olson,et al.  Functional heterogeneity in cingulate cortex: the anterior executive and posterior evaluative regions. , 1992, Cerebral cortex.

[4]  B. Vogt,et al.  Contributions of anterior cingulate cortex to behaviour. , 1995, Brain : a journal of neurology.

[5]  M. Lowe,et al.  Functional Connectivity in Single and Multislice Echoplanar Imaging Using Resting-State Fluctuations , 1998, NeuroImage.

[6]  Stephen M. Smith,et al.  fMRI resting state networks define distinct modes of long-distance interactions in the human brain , 2006, NeuroImage.

[7]  B. Miller,et al.  Neurodegenerative Diseases Target Large-Scale Human Brain Networks , 2009, Neuron.

[8]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[9]  Bharat B. Biswal,et al.  Functionally Related Correlation in the Noise , 2000 .

[10]  C. Granger Investigating causal relations by econometric models and cross-spectral methods , 1969 .

[11]  Nicholas L. Cassimatis,et al.  A Cognitive Substrate for Achieving Human-Level Intelligence , 2006, AI Mag..

[12]  Cynthia Breazeal,et al.  Emotion and sociable humanoid robots , 2003, Int. J. Hum. Comput. Stud..

[13]  S Lehéricy,et al.  The visual word form area: spatial and temporal characterization of an initial stage of reading in normal subjects and posterior split-brain patients. , 2000, Brain : a journal of neurology.

[14]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[15]  R. Malach,et al.  The topography of high-order human object areas , 2002, Trends in Cognitive Sciences.

[16]  Barry Horwitz,et al.  The elusive concept of brain connectivity , 2003, NeuroImage.

[17]  V. Calhoun,et al.  Changes in the interaction of resting‐state neural networks from adolescence to adulthood , 2009, Human brain mapping.

[18]  R. Brooks,et al.  The cog project: building a humanoid robot , 1999 .

[19]  Cameron S. Carter,et al.  Conflict and Cognitive Control in the Brain , 2006 .

[20]  Yoshitaka Nakajima,et al.  Auditory Scene Analysis: The Perceptual Organization of Sound Albert S. Bregman , 1992 .

[21]  J. Cohen,et al.  Dissociating the role of the dorsolateral prefrontal and anterior cingulate cortex in cognitive control. , 2000, Science.

[22]  Stefan Schaal,et al.  Is imitation learning the route to humanoid robots? , 1999, Trends in Cognitive Sciences.

[23]  M. Posner,et al.  Cognitive and emotional influences in anterior cingulate cortex , 2000, Trends in Cognitive Sciences.

[24]  Illah R. Nourbakhsh,et al.  A survey of socially interactive robots , 2003, Robotics Auton. Syst..

[25]  S. Pinker,et al.  Visual cognition : An introduction * , 1989 .

[26]  Michael Davis,et al.  The role of the amygdala in fear and anxiety. , 1992, Annual review of neuroscience.

[27]  N. Kanwisher,et al.  The Fusiform Face Area: A Module in Human Extrastriate Cortex Specialized for Face Perception , 1997, The Journal of Neuroscience.

[28]  C. Carter,et al.  Anterior cingulate cortex and conflict detection: An update of theory and data , 2007, Cognitive, affective & behavioral neuroscience.

[29]  Leslie G. Ungerleider,et al.  Transient and sustained activity in a distributed neural system for human working memory , 1997, Nature.

[30]  R. Adolphs,et al.  Fear and the human amygdala , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[31]  M. Raichle,et al.  The anterior cingulate cortex mediates processing selection in the Stroop attentional conflict paradigm. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Sabine Kastner,et al.  Neuroscience: Unconscious networking , 2007, Nature.

[33]  L CassimatisNicholas A cognitive substrate for achieving human-level intelligence , 2006 .

[34]  Brian Scassellati,et al.  Theory of Mind for a Humanoid Robot , 2002, Auton. Robots.

[35]  H. Barlow Vision: A computational investigation into the human representation and processing of visual information: David Marr. San Francisco: W. H. Freeman, 1982. pp. xvi + 397 , 1983 .

[36]  K. Holyoak,et al.  A System for Relational Reasoning in Human Prefrontal Cortex , 1999 .

[37]  S. Bressler,et al.  Granger Causality: Basic Theory and Application to Neuroscience , 2006, q-bio/0608035.

[38]  Vinod Menon,et al.  Functional connectivity in the resting brain: A network analysis of the default mode hypothesis , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[39]  M. Jeannerod,et al.  Ways of Seeing: The Scope and Limits of Visual Cognition , 2003 .

[40]  V. Haughton,et al.  Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data. , 2001, AJNR. American journal of neuroradiology.

[41]  R. Malach,et al.  Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[42]  M. Greicius,et al.  Resting-state functional connectivity reflects structural connectivity in the default mode network. , 2009, Cerebral cortex.

[43]  R. Fisher FREQUENCY DISTRIBUTION OF THE VALUES OF THE CORRELATION COEFFIENTS IN SAMPLES FROM AN INDEFINITELY LARGE POPU;ATION , 1915 .

[44]  Jie Cui,et al.  2008 Special Issue: BSMART: A Matlab/C toolbox for analysis of multichannel neural time series , 2008 .

[45]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[46]  M. Buonocore,et al.  Posterior cingulate cortex activation by emotional words: fMRI evidence from a valence decision task , 2003, Human brain mapping.

[47]  Anil K. Seth,et al.  A MATLAB toolbox for Granger causal connectivity analysis , 2010, Journal of Neuroscience Methods.

[48]  Rodney A. Brooks,et al.  Prospects for Human Level Intelligence for Humanoid Robots , 1998 .

[49]  Karl J. Friston Functional and effective connectivity in neuroimaging: A synthesis , 1994 .

[50]  Arthur C. Graesser,et al.  Is it an Agent, or Just a Program?: A Taxonomy for Autonomous Agents , 1996, ATAL.

[51]  H. Simon,et al.  The shape of automation for men and management , 1965 .