Recent advances in philosophical thinking about consciousness, such as cognitive phenomenology and mereological analysis, provide a framework that facilitates using computational models to explore issues surrounding the nature of consciousness. Here we suggest that, in particular, studying the computational mechanisms of working memory and its cognitive control is highly likely to identify computational correlates of consciousness and thereby lead to a deeper understanding of the nature of consciousness. We describe our recent computational models of human working memory and propose that three computational correlates of consciousness follow from the results of this work: itinerant attractor sequences, top-down gating, and very fast weight changes. Our current investigation is focused on evaluating whether these three correlates are sufficient to create more complex working memory models that encompass compositionality and basic causal inference. We conclude that computational models of working memory are likely to be a fruitful approach to advancing our understanding of consciousness in general and in determining the long-term potential for development of an artificial consciousness specifically.
Cleeremans, Axel. “Computational Correlates of Consciousness”. Progress in Brain Research, 150 (2005), 81-98.
Cleeremans, Axel, Timmermans, Bert, Pasquali, Antoine. “Consciousness and Metarepresentation: A Computational Sketch”. Neural Networks, 20 (2007), 1032-1039.
Connor, Dustin, Shanahan, Murray. “A Computational Model of a Global Neuronal Workspace with Stochastic Connections”. Neural Networks, 23 (2010), 1139-1154.
Courtney, Susan, Petit, Laurent, Haxby, James and Ungerleider, Leslie. “The Role of Prefrontal Cortex in Working Memory: Examining the Contents of Consciousness”. Philosophical Transactions of the Royal Society of London B, 353 (1998), 1819-1828.
Cowan, Nelson, Elliott, Emily, Saults, J. Scott, Morey, Candice, Mattox, Sam, Hismjatullina, Anna, Conway, Andrew. “On the Capacity of Attention: Its Estimation and Its Role in Working Memory and Cognitive Aptitudes”. Cognitive Psychology, 51 (2005), 42-100.
Crick, Francis. The Astonishing Hypothesis, NY: Charles Scribner’s Sons, 1994.
Davis, Greg, Katz, Garrett, Soranzo, Daniel, Costanzo, Michelle, Reinhard, Matthew, Gentili, Rodolphe, Reggia, James. “A Neurocomputational Model of Increased Saccade Latency and BOLD Changes in Posttraumatic Stress Disorder”, submitted, 2019.
Dehaene, Stanislas, Naccache, Lionel. “Towards a Cognitive Neuroscience of Consciousness”. Cognition, 79 (2001), 1-37.
Fekete, Tomer, Edelman, Shimon. “Towards a Computational Theory of Experience”. Consciousness and Cognition, 20 (2011), 807-827.
Frank, Michael, Loughry, Bryan and O’Reilly, Randall. “Interactions Between Frontal Cortex and Basal Ganglia in Working Memory: A Computational Model”. Cognitive, Affective and Behavioral Neuroscience, 1 (2001), 137-160.
Garrett, Brian. “What the History of Vitalism Teaches Us about Consciousness and the ‘Hard Problem’.” Philosophy and Phenomenological Research, 72 (2006), 616-628.
Goodfellow, Ian, Bengio, Yoshua and Courville, Aaron. Deep Learning, NY: MIT Press, 2016.
Haikonen, Pentti. Consciousness and Robot Sentience, Singapore: World Scientific, 2019.
Jorba, Marta, Vincente, Agustin. “Cognitive Phenomenology, Access to Contents, and Inner Speech. Journal of Consciousness Studies, 21:9-10 (2014), 74-99.
Katz, Garrett, Davis, Greg, Gentili, Rodolphe, Reggia, James. “A Programmable Neural Virtual Machine Based on a Fast Store-Erase Learning Rule”. Neural Networks, 119 (2019), 10-30.
Katz, Garrett, Huang, Di-Wei, Hauge, Theresa, Gentili, Rodolphe and Reggia, James. “A Novel Parsimonious Cause-Effect Reasoning Algorithm for Robot Imitation and Plan Recognition”. IEEE Transactions on Cognition and Developmental Systems, 10 (2018), 177-193.
Katz, Garrett, Reggia, James. “Using Directional Fibers to Locate Fixed Points of Recurrent Neural Networks”. IEEE Transaction on Neural Networks and Learning Systems, 29 (2018), 3636-3646.
Lara, Antonio and Wallis, Jonathan. “The Role of Prefrontal Cortex in Working Memory: A Mini Review”. Frontiers in Systems Neuroscience. Retrieved from https://doi.org/10.3389/fnsys.2015.00173. Accessed December 18, 2015.
McDermott, Drew. “Artificial Intelligence and Consciousness.” In Cambridge Handbook of Consciousness, edited by M. Moscovitch and E. Thompson, 117-150, Cambridge: Cambridge University Press, 2007.
McGinn, Colin. Can We Solve the Mind-Brain Problem? Mind, 98 (1989), 349-366.
Metzinger, Thomas. Neural Correlates of Consciousness, NY: MIT Press, 2000.
Mongillo, Gianluigi, Barak, Omri and Tsodyks, Mish. “Synaptic Theory of Working Memory”. Science, 319 (2008), 1543-1346.
Munkhdali, Tsenduren and Trischler, Adam. “Metalearning with Hebbian Fast Weights”. Retrieved from arXiv: 1807.05076v1, 2018.
Nagel, Thomas. “What is it Like to be a Bat?” Philosophical Review, 4 (1974), 435-450.
Pascanu, Razvan and Jaeger, Herbert. “A Neurodynamical Model for Working Memory”. Neural Networks, 24 (2011), 199-207.
Perlis, Don and Brody, Justin. “Operationalizing Consciousness”. AAAI Spring Symposium, Stanford CA, 2019.
Persuh, Marjan, LaRock, Eric and Berger, Jacob. “Working Memory and Consciousness: The Current State of Play”. Frontiers in Human Neuroscience. Retrieved from https://doi.org/10.3389/fnhum.2018.00078. Accessed March 2018.
Prentner, Robert. “Process Metaphysics of Consciousness”. Open Philosophy, 2 (2018) 3-13.
Prinz, Jesse. The Conscious Brain, Oxford: Oxford University Press, 2012.
Reggia, James. “The Rise of Machine Consciousness”. Neural Networks, 44 (2013), 112-131.
Reggia, James, Monner, Derek, Sylvester, Jared. “The Computational Explanatory Gap”. Journal of Consciousness Studies, 21:9 (2014), 153-178.
Regis, Ed. What is Life?, NY: Farber, Strauss and Giroux, 2008.
Sherman, S. Murray, Guillery, R. Exploring the Thalamus and its Role in Cortical Function, NY: MIT Press, 2006.
Singer, Wolf. “Dynamic Formation of Functional Networks by Synchronization”. Neuron, 69 (2011), 191-193.
Squire, Larry and Dede, Adam. “Conscious and Unconscious Memory Systems”. Cold Spring Harbor Perspectives in Biology, 7 (2015). Retrieved from DOI:10.1101/cshperspect.a021667.
Sylvester, Jared, Reggia, James, Weems, Scott, Bunting, Michael. “Controlling Working Memory with Learned Instructions”. Neural Networks, 41 (2013), 23-38.
Sylvester, Jared, Reggia, James. “Engineering Neural Systems for High-Level Problem Solving”. Neural Networks, 79 (2016), 37-52.
Takeno, Junichi. Creation of a Conscious Robot, Singapore: Pan Stanford, 2013.
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