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All Publications


  • Crowding out Memetic Explanation PHILOSOPHY OF SCIENCE Cao, R. 2020; 87 (5): 1160–71

    View details for DOI 10.1086/710518

    View details for Web of Science ID 000599038100033

  • New Labels for Old Ideas: Predictive Processing and the Interpretation of Neural Signals REVIEW OF PHILOSOPHY AND PSYCHOLOGY Cao, R. 2020
  • Modest and immodest neural codes: Can there be modest codes? The Behavioral and brain sciences Cao, R. n., Rathkopf, C. n. 2019; 42: e221

    Abstract

    We argue that Brette's arguments, or some variation on them, work only against the immodest codes imputed by neuroscientists to the signals they study; they do not tell against "modest" codes, which may be learned by neurons themselves. Still, caution is warranted: modest neural codes likely lead to only modest explanatory gains.

    View details for DOI 10.1017/S0140525X19001420

    View details for PubMedID 31775923

  • COMPUTATIONAL EXPLANATIONS AND NEURAL CODING ROUTLEDGE HANDBOOK OF THE COMPUTATIONAL MIND Cao, R., Sprevak, M., Colombo, M. 2019: 283–96
  • Content in Simple Signalling Systems. The British journal for the philosophy of science Shea, N., Godfrey-Smith, P., Cao, R. 2018; 69 (4): 1009–35

    Abstract

    Our understanding of communication and its evolution has advanced significantly through the study of simple models involving interacting senders and receivers of signals. Many theorists have thought that the resources of mathematical information theory are all that are needed to capture the meaning or content that is being communicated in these systems. However, the way theorists routinely talk about the models implicitly draws on a conception of content that is richer than bare informational content, especially in contexts where false content is important. This article shows that this concept can be made precise by defining a notion of functional content that captures the degree to which different states of the world are involved in stabilizing senders' and receivers' use of a signal at equilibrium. A series of case studies is used to contrast functional content with informational content, and to illustrate the explanatory role and limitations of this definition of functional content. 1Introduction 2Modelling Framework 3Two Kinds of Content3.1Informational content3.2Functional content 4Cases4.1Case 1: Simplest case4.2Case 2: Partial pooling4.3Case 3: Bottleneck4.4Case 4: Partial common interest4.5Case 5: Deception4.6Case 6: A further problem arising from divergent interests 5Discussion Appendix.

    View details for PubMedID 30443051

  • Signaling in the Brain: In Search of Functional Units Cao, R. UNIV CHICAGO PRESS. 2014: 891–901

    View details for DOI 10.1086/677688

    View details for Web of Science ID 000345579400016

  • A teleosemantic approach to information in the brain BIOLOGY & PHILOSOPHY Cao, R. 2012; 27 (1): 49–71
  • The hemo-neural hypothesis: On the role of blood flow in information processing JOURNAL OF NEUROPHYSIOLOGY Moore, C. I., Cao, R. 2008; 99 (5): 2035–47

    Abstract

    Brain vasculature is a complex and interconnected network under tight regulatory control that exists in intimate communication with neurons and glia. Typically, hemodynamics are considered to exclusively serve as a metabolic support system. In contrast to this canonical view, we propose that hemodynamics also play a role in information processing through modulation of neural activity. Functional hyperemia, the basis of the functional MRI (fMRI) BOLD signal, is a localized influx of blood correlated with neural activity levels. Functional hyperemia is considered by many to be excessive from a metabolic standpoint, but may be appropriate if interpreted as having an activity-dependent neuro-modulatory function. Hemodynamics may impact neural activity through direct and indirect mechanisms. Direct mechanisms include delivery of diffusible blood-borne messengers and mechanical and thermal modulation of neural activity. Indirect mechanisms are proposed to act through hemodynamic modulation of astrocytes, which can in turn regulate neural activity. These hemo-neural mechanisms should alter the information processing capacity of active local neural networks. Here, we focus on analysis of neocortical sensory processing. We predict that hemodynamics alter the gain of local cortical circuits, modulating the detection and discrimination of sensory stimuli. This novel view of information processing-that includes hemodynamics as an active and significant participant-has implications for understanding neural representation and the construction of accurate brain models. There are also potential medical benefits of an improved understanding of the role of hemodynamics in neural processing, as it directly bears on interpretation of and potential treatment for stroke, dementia, and epilepsy.

    View details for DOI 10.1152/jn.01366.2006

    View details for Web of Science ID 000255811500001

    View details for PubMedID 17913979

    View details for PubMedCentralID PMC3655718