The following is a list of articles and monographs useful to the philosophy of neuroscience. Click on a topic title to view references on that topic.





  • Bechtel, William and R. C. Richardson (1993), Discovering Complexity: Decomposition And Localization As Strategies in Scientific Research. Princeton, NJ: Princeton University Press.

  • Bechtel, William, and Adele Abrahamsen (2005), "Explanation: A Mechanistic Alternative", Studies in History and Philosophy of the Biological and Biomedical Sciences 36: 421-441.

  • Bennett, M. R., and P. M. S. Hacker (2003), Philosophical Foundations of Neuroscience. Malden, MA: Blackwell.

  • Bogen, James (2005), "Regularities and Causality; Generalizations and Causal Explanations", Studies in History and Philosophy of Biological and Biomedical Studies 36: 397-420.

  • Craver, Carl F. (2007), Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience. New York, NY: Oxford University Press.

  • Craver, Carl F. and Lindley Darden (2001), "Discovering Mechanisms in Neurobiology: The Case of Spatial Memory", in P.K. Machamer, R. Grush, P. McLaughlin (eds.), Theory And Method in The Neurosciences. Pittsburgh, PA: University of Pittsburgh Press, 112-137.

  • Cummins, R. (1975), "Functional Analysis", Journal of Philosophy 72:741-765.

  • Cummins, R. (1983), The Nature of Psychological Explanation. Cambridge, MA: MIT Press.

  • Hohwy, J., and C. Frith (2004), "Can Neuroscience Explain Consciousness?", Journal of Consciousness Studies 11(7-8): 180-198.

  • Hohwy, J., and C. Frith (2004), "Studies of the Neural Correlates of Consciousness Can Do Better, But Are On the Right Track", Journal of Consciousness Studies 11(1): 45-51.

  • Nadel, L., and J. O'Keefe (1974), "The Hippocampus in Pieces And Patches: An Essay on Modes of Explanation in Physiological Psychology", in R. Bellairs and E.G. Gray (eds.), Essays on The Nervous System: A Festschrift For Prof J.Z. Young. Oxford: Clarendon Press, 367-390.

  • Rosenberg, A. (2001), "How Is Biological Explanation Possible?", British Journal for the Philosophy of Science 52: 735-760.

  • Schaffner, Kenneth F. (1993), Discovery and Explanation in Biology And Medicine. Chicago: University of Chicago Press.

  • Skarda, S. (1986), "Explaining Behavior: Bringing the Brain Back In". Inquiry 29: 187-201.

  • Von Eckardt, B. and Jeffrey S. Poland (2004), "Mechanism and Explanation in Cognitive Neuroscience". Philosophy of Science 71: 972.Bennett, M. R., and P. M. S. Hacker (2003), Philosophical Foundations of Neuroscience. Malden, MA: Blackwell.



  • Butler, K. (1994), "Neural Constraints in Cognitive Science", Minds and Machines 4: 129-62.

  • Craver, Carl F. (1998), Neural Mechanisms: On the Structure, Function, and Development of Theories in Neurobiology. Ph.D. Dissertation. Pittsburgh, PA: University of Pittsburgh.

  • Craver, Carl F. (2002), "Structures of Scientific Theories", in P. K. Machamer and M. Silberstein (eds.), The Blackwell Guide To The Philosophy of Science. Malden, MA: Blackwell Publishers.

  • Rosenberg, A. (1985), The Structure of Biological Science. Cambridge: Cambridge University Press.

  • Weber, Marcel (2005), Philosophy of Experimental Biology. Cambridge: Cambridge University Press.



  • Bechtel, William (1983), "A Bridge Between Cognitive Science and Neuroscience: The Functional Architecture of Mind", Philosophical Studies 44: 319-30.

  • Bechtel, William (1995), "Biological and Social Constraints on Cognitive Processes: The Need for Dynamical interactions Between Levels of Organization", Canadian Journal of Philosophy Supplement 20: 133-164.

  • Craver, Carl F. (2002), "Interlevel Experiments and Multilevel Mechanisms in the Neuroscience of Memory", Philosophy of Science 69 Supplement: S83-S97.

  • Craver, Carl F. (2001), "Role Functions, Mechanisms and Hierarchy", Philosophy of Science 68: 31-55.

  • Mundale, Jennifer and William Bechtel (1996), "integrating Neuroscience, Psychology, and Evolutionary Biology through a Teleological Conception of Function", Minds and Machines 6: 481-505.

  • Sanes, Joshua R. and J. W. Lichtman (1999), "Can Molecules Explain Long-Term Potentiation?" Nature Neuroscience 2: 597-604.

  • Wilson, Robert A. and Carl F. Craver (forthcoming), "Realization", in Paul Thagard (ed.), Handbook of the Philosophy of Psychology and Cognitive Science. Kluwer Academic Publishers.

  • Wimsatt, William (1994), "The Ontology of Complex Systems: Levels of Organization, Perspectives, and Causal Thickets", Canadian Journal of Philosophy Supplement 20: 207-274.



  • Bechtel, William (1984), "Reconceptualizations and interfield connections: The discovery of the link between vitamins and coenzymes", Philosophy of Science 51: S48-S58.

  • Bechtel, William (1986), "The nature of cross-disciplinary research", In William Bechtel (ed.), Integrating Scientific Discliplines. Dordrecht: Martinus Nijhoff, 3-52.

  • Bechtel, William (2002), "Aligning Multiple Research Techniques in Cognitive Neuroscience: Why Is It Important?", Philosophy of Science 69: S48-S58.

  • Craver, Carl F. (2005), "Beyond Reduction: Mechanisms, Multifield Integration, and the Unity of Science", Studies in History and Philosophy of Biological and Biomedical Sciences 36: 373-396.

  • Darden, L., and Carl F. Craver (2002), "Strategies in the Interfield Discovery of the Mechanism of Protein Synthesis", Studies in History and Philosophy of Biological and Biomedical Sciences 33: 1-28.

  • Manier, E. (1986), "Problems in the development of cognitive neuroscience: Effective communication between scientific domains", Philosophy of Science Association 1: 183-97.

  • Mundale, J. and William Bechtel (1996), "Integrating neuroscience, psychology, and evolutionary biology through a teleological conception of function", Minds and Machines 6: 481-505.



  • Barlow, Horace B. (1972), "Single units and sensation: A neuron doctrine for perceptual psychology?", Perception 1: 371-394.

  • Bickle, John (1998), Psychoneural reduction: The new wave. Cambridge, MA: MIT Press.

  • Bickle, John (2003), Philosophy of neuroscience: A ruthlessly reductive approach. Kluwer Academic Publishers.

  • Chalmers, David, and Frank Jackson (2001), "Conceptual analysis and reductive explanation", Philosophical Review 110: 315-360.

  • Chemero, Anthony, and Charles Heyser (2006), "Object Exploration and a Problem with Reductionism", Synthese 147(3): 403-423.

  • Churchland, Patricia S. (1982), "Mind-brain reduction: New light from philosophy of science", Neuroscience 7: 1041-1047.

  • Churchland, Paul M. (1981), "Eliminative materialism and the propositional attitudes", Journal of Philosophy 78: 67-90.

  • Craver, Carl F. (2003), "The making of a memory mechanism", Journal of the History of Biology 36: 153-195.

  • Craver, Carl F. (2005), "Beyond Reduction: Mechanisms, Multifield Integration, and the Unity of Neuroscience", Studies in History and Philosophy of Biological and Biomedical Studies, 36: 373-397.

  • Hatfield, G. (1988), "Neurophilosophy meets psychology: Reduction, autonomy, and empirical constraints", Cognitive Neuropsychology 5: 723-46.

  • Machamer, Peter and Jacqueline Sullivan (2001), "Leveling Reduction", University of Pittsburgh Philosophy of Science Archive, http://philsci-archive.pitt.edu/archive/00000386/

  • Sanes, Joshua R. and J. W. Lichtman (1999), "Can molecules explain long-term potentiation?" Nature Neuroscience 2: 597-604.

  • van Eck, Dingmar, Huib Looren De Jong, and Maurice K. D. Schouten (2006), "Evaluating New Wave Reductionism: The Case of Vision", British Journal for the Philosophy of Science 57(1): 167-196.



  • Bechtel, William (2001), "Cognitive Neuroscience: Relating Neural Mechanisms and Cognition", in P. Machamer, P. McLaughlin and R. Grush (eds.), Philosophic Reflections on the Methods of Neuroscience. Pittsburgh, PA: University of Pittsburgh Press.

  • Bogen, James (2003), "Analyzing Causality: The Opposite of Counterfactual is Factual", University of Pittsburgh Philosophy of Science Archive.

  • Bogen, James (forthcoming), "Regularities and causality: Generalizations and causal explanations", Studies in the History and Philosophy of Biology and the Biomedical Sciences.

  • Craver, Carl F. (2003), "The making of a memory mechanism", Journal of the History of Biology 36: 153-195.

  • Craver, Carl F. and Lindley Darden (2001), "Discovering mechanisms in neurobiology: the case of spatial memory", in P.K. Machamer, R. Grush, P. McLaughlin (eds.), Theory and method in the neurosciences. Pittsburgh, PA: University of Pittsburgh Press, 112-137.

  • Dowe, Phillip (2004), "Causes are physically connected to their effects: Why preventers and omissions are not causes", in C. Hitchcock (ed.), Contemporary Debates in Philosophy of Science. Oxford: Blackwell Publishers.

  • Eells, E. (1991), Probabilistic Causality. Cambridge: Cambridge University Press.

  • Machamer, Peter K., Lindley Darden, and Carl F. Craver (2000), "Thinking about mechanisms", Philosophy of Science 57: 1-25.

  • Shafer, Jonathan (2004), "Causes need not be physically connected to their effects: The case for negative causation", in C. Hitchcock (ed.), Contemporary Debates in Philosophy of Science. Oxford: Blackwell Publishing.

  • Sperry, Roger T. (1976), "Mental phenomena as causal determinants in brain function", in Gordon G. Globus, Grover Maxwell, and Irwin Savodnik (eds.), Consciousness and the Brain. New York: Plenum, 163-177.

  • Von Eckardt, B. and Jeffrey S. Poland (2005), "Mechanism and explanation in cognitive neuroscience", Philosophy of Science 71 :972.



  • Bechtel, William and Robert C. Richardson (1993), Discovering Complexity: Decomposition and Localization as Strategies in Scientific Research. Princeton, NJ: Princeton University Press.

  • Brett, M., I. S. Johnsrude, and A.M. Owen (2002), "The Problem of Functional Localization in the Human Brain", Nature Reviews Neuroscience 3: 243-249.

  • Dunn, J.C., and K. Kirsner (1988), "Discovering functionally independent mental processes: The principle of reversed association", Psychological Review 95: 91-101.

  • Glymour, Clark (1994), "On the methods of cognitive neuropsychology", British Journal for the Philosophy of Science 45: 815-845.

  • Shallice, T. (1988), From Neuropsychology to Mental Structure. Cambridge: Cambridge University Press.



  • Ashby, W. R. (1950), "The Stability of a Randomly Assembled Nerve-Network", Electroencephalography and Clinical Neurophysiology 2: 471-82.

  • Balcazar, J. L. (1997), "Computational Power of Neural Networks: A Characterization in Terms of Kolmogorov Complexity", IEEE Transactions on Information Theory 43(4): 1175-1183.

  • Barron, A. R. (1993), "Universal Approximation Bounds for Superpositions of a Sigmoidal Function", IEEE Transactions on Information Theory 39(3): 930-945.

  • Beurle, R. L. (1956), "Properties of a Mass of Cells Capable of Regenerating Pulse", Philosophical Transactions of the Royal Society of London B240: 55-94.

  • Brindley, G. S. (1967), "The Classification of Modifiable Synapses and the Use in Models for Conditioning", Proceedings of the Royal Society of London B168: 361-76.

  • Chen, T. and H. Chen (1993), "Approximations of Continuous Functionals by Neural Networks with Application to Dynamic Systems", IEEE Transactions on Neural Networks 4(6): 910-918.

  • Chen, T. and H. Chen (1995), "Approximation Capability to Functions of Several Variables, Nonlinear Functionals, and Operators by Radial Basis Function Neural Networks", IEEE Transactions on Neural Networks 6 (4): 903-910.

  • Chen, T. et al. (1995), "Approximation Capability in C(R^n) by Multilayer Feedforward Networks and Related Problems", IEEE Transactions on Neural Networks 6 (1): 25-30.

  • Cherniak, C. (1994), "Philosophy and Computational Neuroanatomy", Philosophical Studies 73: 89-107.

  • Churchland, Patricia S., and Terry J. Sejnowski (1992), The Computational Brain. Cambridge, MA: MIT Press.

  • Cowan, J. D. (1965), "The Problem of Organismic Reliability", Progress in Brain Research 17: 9-63.

  • Cowan, J. D. (1968), "Statistical Mechanics of Nervous Nets", in E. R. Caianiello (ed.), Neural Networks. Berlin: Springer.

  • Cowan, J. D. (1990), "Neural Networks: The Early Days", in D. S. Touretzky (ed.), Advances in Neural Information Processing Systems 2. San Mateo, CA: Morgan Kaufman.

  • Cowan, J. D. (1990), "Von Neumann and Neural Networks", in J. Gilmm, J. Impagliazzo and I. Singer (eds.), The Legacy of Jon von Neumann. Providence, RI: American Mathematical Society.

  • Cragg, B. G. and H. N. V. Temperley (1954), "The Organisation of Neurones: A Cooperative Analogy", Electroencephalography and Clinical Neurophysiology 6: 85-92.

  • Cragg, B. G. and H. N. V. Temperley (1955), "Memory: The Analogy with Ferromagnetic Hysteresis", Brain 78: 304-16.

  • Cybenko, G. (1989), "Approximation by Superpositions of a Sigmoidal Function", Mathematics of Control, Signals, and Systems 2: 303-314.

  • Ermentrout, G.B. and J. D. Cowan (1979), "A Mathematical Theory of Visual Hallucination Patterns", Biological Cybernetics 34: 137-50.

  • Ermentrout, G.B. and J. D. Cowan (1979), "Temporal Oscillations in Neural Networks", Journal of Mathematical Biology 7: 265-80.

  • Estevez, Pablo A. and Yoichi Okabe (2004), "On the Computational Power of Max-Min Propagation Neural Networks", Neural Processing Letters 19(1): 11-23.

  • Gallant, A.R. and H. White (1988), "There Exists a Neural Network That Does Not Make Avoidable Mistakes", IEEE International Conference on Neural Networks Volume 1. San Diego, CA: SOS Printing, 657-664.

  • Girosi, F. and T. Poggio (1990), "Networks and the Best Approximation Property", Biological Cybernetics 63(3): 169-76.

  • Graubard, S. (ed.) (1988), The Artificial Intelligence Debate: False Starts, Real Foundations Cambridge, MA: MIT Press.

  • Hartley, R. and H. Szu (1987), "A Comparison of the Computational Power of Neural Network Models", in Proceedings of the IEEE First International Conference on Neural Networks, San Diego New York: IEEE Press, 15-22.

  • Hecht-Nielsen, R. (1987)," Kolmogorov's Mapping Neural Network Mapping Existence Theorem", Proceedings of the IEEE International Conference on Neural Networks Volume 2: 11-13.

  • Hopfield, J .J. and D. W. Tank (1985), "Neural Computation and Constraint Satisfaction Problems and the Traveling Salesman", Biological Cybernetics 55: 141-52.

  • Hornik, K., M. Stinchcombe, and H. White (1989), "Multilayer Feedforward Networks are Universal Approximators", Neural Networks 2: 359-66.

  • Kent, E. (1981), The Brains of Men and Machines. Peterborough, NH: BYTE/McGraw-Hill.

  • Kilian, J. and Hava T. Siegelmann (1993), "On the Power of Sigmoid Neural Networks", Proceedings of the Sixtieth ACM Workshop on Computational Learning Theory New York: Association for Computing Machinery, 137-43.

  • Kirkpatrick, S., C. D. Gelatt Jr., and M. P. Vecchi (1983), "Optimization by Simulated Annealing", Science 229: 671-79.

  • Kleene, S. C. (1956), "Representation of Events in Nerve Nets and Finite Automata", in Claude E. Shannon and John McCarthy (eds.), Automata Studies. Princeton, NJ: Princeton University Press.

  • Levelt, Wilemm. (1990), "Are Multilayer Feedforward Networks Effectively Turing Machines?" Psychological Research 52(2-3): 153-7.

  • Maass, W. (2000), "Neural Computation with Winner-Take-All as the Only Nonlinear Operation", Advances in Neural Information Processing Systems 12: 293-99.

  • Maass, W. (2000), "On the Computational Power of Winner-Take-All", Neural Computation 12(11): 2519-2535.

  • Machlup, F. and U. Mansfield (eds.) (1983), The Study of Information: Interdisciplinary Messages. New York: Wiley.

  • Maiorov, V. A. and Pinkus (1999), "Lower Bounds for Approximation by MLP Neural Networks", Neurocomputing 25: 81-91.

  • McCulloch, W. S. and Walter H. Pitts (1943), "A Logical Calculus of the Ideas Immanent in Nervous Activity", Bulletin of Mathematical Biophysics 7: 115-133.

  • Mhaskar, H. N. (1993), "Approximation Properties of a Multilayered Feedforward Artificial Neural Network", Advances in Computational Mathematics 1(1): 61-80.

  • Oliveira, Wilson R. et al. (2002), "Turing's Analysis of Computation and Artificial Neural Networks", Journal of Intelligent and Fuzzy Systems 13: 85-98.

  • Orponen, P. (1994), "Computational Complexity of Neural Networks: A Survey", Nordic Journal of Computing 1: 94-110.

  • Orponen, P. (1996), "The Computational Power of Discrete Hopfield Nets with Hidden Units", Neural Computation 8: 403-415.

  • Rosenblatt, Frank (1958), "The Perceptron, A Probabilistic Model for Information Storage and Organization in the Brain", Psychological Review 62: 386-408.

  • Rosenblatt, Frank (1961), Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms Washington DC: Spartan Books.

  • Ruck, D. W. et al. (1990), "The Multilayer Perceptron as an Approximation to a Bayes Optimal Discriminant Function", IEEE Transactions on Neural Networks 1(4): 296-98.

  • Rumelhart, D. E., G. E. Hinton, G. E., and R. J. Williams (1986), "Learning Representations by Back-propagating Errors", Nature 323: 533-36.

  • Siegelmann, Hava T. (1999), Neural Networks and Analog Computation: Beyond the Turing Limit Boston: Birkhauser.

  • Siegelmann, Hava T. et al. (1997), "Computational Capabilities of Recurrent NARX Neural Networks", IEEE Transactions on Systems, Man, and Cybernetics 27(2): 208-215.

  • Siegelmann, Hava and E. Sontag (1992), "On the Computational Power of Neural Nets", Proceedings of the Fifth ACM Workshop on Computational Learning Theory, 440-49.

  • Sima, J. and P. Orponen (2003), "General-Purpose Computation with Neural Networks: A Survey of Complexity Theoretic Results", Neural Computation 15(12): 2727-78.

  • Sima, J. et al. (2000), "On the Computational Complexity of Binary and Analog Symmetric Hopfield Nets", Neural Computation 12: 2965-2989.

  • Siu, K. et al. (1995), Discrete Neural Computation: a Theoretical Foundation Englewood Cliffs, NJ: Prentice Hall, Inc.

  • Steinbuch, K. (1961), "Die Lernmatrix", Kybernetik 1: 36-45.

  • Stinchcombe, M. and H. White (1989), "Universal Approximation Using Feedforward Networks with Non-Sigmoid Hidden Layer Activation Functions", International Joint Conference on Neural Networks 1: 613-617.

  • Stinchcombe, M. and H. White (1990), "Approximating and Learning Unknown Mappings Using Multilayer Feedforward Networks with Bounded Weights", International Joint Conference on Neural Networks 3: 7-16.

  • Sun, G.Z. et al. (1991), "Turing Equivalence of Neural Networks with Second Order Connection Weights". Seattle International Joint Conference on Neural Networks 2: 357-362.

  • Valentine, E. (1989), "Neural Nets: From Hartley and Hebb to Hinton", Journal of Mathematical Psychology 33: 348-57.

  • Wasserman, P. (1989), Neural Computing: Theory and Practice. New York: Van Nostrand Reinhold.

  • Wolpert, David H. and Bruce J. MacLennan (1993), "A Computational Universal Field Computer That is Purely Linear", Working Papers 93-09-056, Santa Fe Institute.Cowan, J. D. (1968), "Statistical Mechanics of Nervous Nets", in E. R. Caianiello (ed.), Neural Networks. Berlin: Springer.

  • van der Velde, Frank (1993), "Is the Brain an Effective Turing Machine or a Finite-state Machine?" Psychological Research 55(1): 71-79.



  • Andrewes, D. (2003). Double dissociation and the benefit of experience. Cortex, 39, 158-160.

  • Baddeley, A. (2003). Double dissociations: not magic, but still useful. Cortex, 39, 129-131.

  • Van Orden, G.C., Pennington, B.F., & Stone, G.O. (2001). What do double dissociations prove? Cognitive Science, 25, 111-172.



  • Bechtel, William (in press). The epistemology of evidence in cognitive neuroscience. In R. Skipper Jr., C. Allen, R. A. Ankeny, C. F. Craver, L. Darden, G. Mikkelson, and R. Richardson (eds.), Philosophy and the Life Sciences: A Reader. Cambridge, MA: MIT Press.

  • Bechtel, W. and Stufflebeam, R. (2001) Epistemic issues in procuring evidence about the brain: The importance of research instruments and techniques. In W. Bechtel et al. (Eds.), Philosophy and the neurosciences: A reader. Oxford: Basil Blackwell pp. 55-81.

  • Bogen, James (2002). Epistemological Custard Pies from Functional Brain Imaging. Philosophy of Science 69: S59–S71.

  • Bogen, James (2001). Functional Image Evidence: Some Epistemic Hot Spots. In P. Machamer, R. Grush, and P. McLaughlin (eds.), Theory and Method in Neuroscience. Pittsburgh, PA: University of Pittsburgh Press. 173-199.

  • Bub, J. & Bub, D. (1988). On the methodology of single-case studies in cognitive neuropsychology. Cognitive Neuropsychology, 5, 565-582.

  • Bub, J. (1994). Testing models of cognition through the analysis of brain-damaged performance. British Journal of the Philosophy of Science, 45, 837-855.

  • Carmazza, A. (1986). On drawing inferences about the structure of normal cognitive systems from the analysis of patterns of impaired performance: The case for single-patient studies. Brain and Cognition, 5, 41-66.

  • Cook, T. & Campbell, D. (1979). Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin.

  • Craver, Carl F. (2002). Interlevel experiments and multilevel mechanisms in the neuroscience of memory. Philosophy of Science 69 Supplement: S83-S97.

  • Culp, Sylvia (1995). Objectivity in Experimental Inquiry: Breaking Data-Technique Circles. Philosophy of Science 62.3: 438-458.

  • Glymour, Clark (1994). On the methods of cognitive neuropsychology. British Journal for the Philosophy of Science 45: 815-845.

  • Kosslyn, Stephen M. (1999). If neuroimaging is the answer, what is the question? Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 354: 1283-1294.

  • Weber, Marcel (2005). Philosophy of Experimental Biology. Cambridge: Cambridge University Press.



    Anderson, Karen E. et al. (2005). Functional imaging. Textbook of traumatic brain injury. Ed. Jonathan M. Silver et al. Washington, DC, US: American Psychiatric Publishing, Inc. pp. 107-133.

  • Avison, Malcolm J. (2002). Functional Brain Mapping - What Is It Good For? Absolutely Nothing? (Comments on The New Phrenology, by William R. Uttal). Brain & Mind, 3 (3): 367-373.

  • Beaulieu, Anne. (2003). Brains, Maps and the New Territory of Psychology. Theory & Psychology, 13 (4): 561-568.

  • Bechtel, William. (2002). Decomposing the mind-brain: A long-term pursuit. Brain & Mind, 3 (2): 229-242.

  • Billingsley-Marshall, Rebecca L. et al. (2004). Reliability and validity of functional neuroimaging techniques for identifying language-critical areas in children and adults. Developmental Neuropsychology, 26 (2): 541-563.

  • Borsook, David and Becerra, Lino. (2005). Functional imaging of pain and analgesia-A valid diagnostic tool? Pain, 117 (3): 247-250.

  • Brett, Matthew et al. (2002). The problem of functional localization in the human brain. Nature Reviews Neuroscience, 3 (3): 243-249.

  • Bub, Daniel N. (2000). Methodological issues confronting PET and fMRI studies of cognitive function: With special reference to Human Brain Function. Cognitive Neuropsychology, 17 (5): 467-484.

  • Cacace, A.T. et al. (2000). Principles of functional magnetic resonance imaging: application to auditory neuroscience. Journal of the American Academy of Audiology, 11 (5): 239-272.

  • Chatterjee, Anjan. (2005). A Madness to the Methods in Cognitive Neuroscience? Journal of Cognitive Neuroscience, 17 (6): 847-849.

  • Demonet, J.F. et al. (1996). PET studies of phonological processing: A critical reply to Poeppel. Brain and Language, 55 (3): 352-379.

  • Eden, Guinevere F. and Zeffiro, Thomas A. (1996). PET and fMRI in the detection of task-related brain activity: Implications for the study of brain development. Developmental neuroimaging: Mapping the development of brain and behavior. Ed. Robert W. Thatcher et al. San Diego, CA, US: Academic Press, Inc. pp. 77-90.

  • Evans, Jonathan J. et al. (2004). Research Digest: Brain imaging and neuropsychology: Scope, limitations, and implications for degeneracy in neural systems. Neuropsychological Rehabilitation, 14 (4): 473-476.

  • Fellows, Lesley K. et al. (2005). Method Matters: An Empirical Study of Impact in Cognitive Neuroscience. Journal of Cognitive Neuroscience, 17 (6): 850-858.

  • Fiez, Julie A. and Petersen, Steven E. (1993). PET as part of an interdisciplinary approach to understanding processes involved in reading. Psychological Science, 4 (5): 287-293.

  • George, Mark S. et al. (2000). Neuroimaging approaches to the study of emotion. The neuropsychology of emotion. Ed. Joan C. Borod. New York, NY, US: Oxford University Press. pp. 106-134.

  • Gracely, Richard H. (2003). Is seeing believing? Functional imaging of hysterical anesthesia. Neurology, 60 (9): 1410-1411.

  • Haier, Richard J. (2001). PET studies of learning and individual differences. Mechanisms of cognitive development: Behavioral and neural perspectives. Ed. James L. McClelland and Robert S. Siegler. Mahwah, NJ, US: Lawrence Erlbaum Associates, Publishers. pp. 123-145.

  • Heeger, David J. and Ress, David. (2002). What does fMRI tell us about neuronal activity? Nature Reviews Neuroscience, 3 (2): 142-151.

  • Humphreys, Glyn W. and Price, Cathy J. (2001). Cognitive neuropsychology and functional brain imaging: Implications for functional and anatomical models of cognition. Acta Psychologica, 107 (1-3): 119-153.

  • Hunton, D.L. et al. (1996). An assessment of functional-anatomical variability in neuroimaging studies. Human Brain Mapping, 4 (2): 122-139.

  • Jackson, Grace E. (2006). A curious consensus: "Brain scans prove disease?" Ethical Human Psychology and Psychiatry, 8 (1): 55-60.

  • Johnsrude, Ingrid S. et al. (2002). Functional Imaging of the Auditory System: The Use of Positron Emission Tomography. Audiology & Neuro-Otology, 7 (5): 251-276.

  • Lee, Lucy et al. (2003). The Functional Brain Connectivity Workshop: report and commentary. Network-Computation in Neural Systems, 14 (2): R1-15.

  • Lloyd, Dan. (2002). Studying the mind from the inside out. Brain & Mind, 3 (2): 243-259.

  • Morrish, Paul K. (2003). How valid is dopamine transporter imaging as a surrogate marker in research trials in Parkinson's disease? Movement Disorders, 18 (Suppl 7): S63-70.

  • Nadeau, Sephen E. and Crosson, Bruce. (1995). A guide to the functional imaging of cognitive processes. Neuropsychiatry, Neuropsychology, & Behavioral Neurology, 8 (3): 143-162.

  • Nair, Dinesh G. (2005). About being BOLD. Brain Research - Brain Research Reviews, 50 (2): 229-243.

  • Patterson, James C. II and Kotrla, Kathryn J. (2002). Functional neuroimaging in psychiatry. The American psychiatric publishing textbook of neuropsychiatry and clinical neurosciences (4th ed.). Ed. Stuart C. Yudofsky and Robert E. Hales. Washington, DC, US: American Psychiatric Publishing, Inc. pp. 285-321.

  • Perani, Daniela and Cappa, Stefano F. (1999). Neuroimaging methods in neuropsychology. Handbook of clinical and experimental neuropsychology. Ed. Gianfranco Denes and Luigi Pizzamiglio. Hove, England: Psychology Press/Erlbaum (UK) Taylor & Francis. pp. 69-94.

  • Petersen, Steven E. (1995). Functional neuroimaging in brain areas involved in language. Neuroscience, memory, and language. Ed. Richard D. Broadwell. Washington, DC, US: US Government Printing Office. pp. 109-116.

  • Peterson, Bradley S. (2003). Conceptual, methodological, and statistical challenges in brain imaging studies of developmentally based psychopathologies. Development & Psychopathology, 15 (3): 811-832.

  • Poeppel, David. (1996). A critical review of PET studies of phonological processing. Brain and Language, 55 (3): 317-351.

  • Poeppel, David. (1996). Some remaining questions about studying phonological processing with PET: Response to Demonet, Fiez, Paulesu, Petersen, and Zatorre (1996). Brain and Language, 55 (3): 380-385.

  • Price, Cathy J. and Friston, Karl J. (2002). Functional imaging studies of neuropsychological patients: Applications and limitations. Neurocase, 8 (5): 345-354.

  • Raichle, Marcus E. (1994). Images of the mind: Studies with modern imaging techniques. Annual Review of Psychology, 45: 333-356.

  • Raichle, Marcus E. (1994). Images of the human mind. Neuropsychopharmacology, 10 (Suppl 3): S28-33.

  • Raichle, Marcus E. (1997). Functional brain imaging and verbal behavior. Neural-network models of cognition: Biobehavioral foundations. Ed. John W. Donahoe and Vivian Packard Dorsel. Amsterdam, Netherlands: North-Holland/Elsevier Science Publishers. pp. 438-454.

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