Cognitive Functions as Revealed by Imaging of the Human Brain


Functional neuroimaging techniques allow neuroscientists to map the processes of perception, cognition, memory, and action onto the human brain. The core techniques used in current research either measure neuronal activity directly (e.g., electroencephalography, magnetoencephalography) or measure aspects of brain metabolism that provide indirect measures of neuronal activity (e.g., functional magnetic resonance imaging, positron emission tomography). Each technique presents a distinct set of strengths and limitations; some have superior ability to localize processing within the brain (spatial resolution), while others have better capability for evaluating the timing of processing (temporal resolution). As these techniques have matured, they have been applied to an increasingly diverse range of research questions. This chapter highlights some key advances associated with functional neuroimaging, with a focus on research that studies higher cognition and decision making. The chapter ends with speculations about the future directions for functional neuroimaging research, including the roles these techniques will play within neuroscience.


Depression Europe Schizophrenia Radioactive Isotope Caffeine 

Further Reading

  1. De Martino B, Kumaran D, Seymour B, Dolan RJ (2006) Frames, biases, and rational decision-making in the human brain. Science 313:684–687PubMedCrossRefGoogle Scholar
  2. Dolan RJ (2008) Neuroimaging of cognition: past, present, and future. Neuron 60:496–502PubMedCrossRefGoogle Scholar
  3. Gianaros PJ, Manuck SB, Sheu LK, Kuan DCH, Votruba-Drzal E, Craig AE, Hariri AR (2010) Parental education predicts corticostriatal functionality in adulthood. Cereb Cortex 21:896–910PubMedCrossRefGoogle Scholar
  4. Glimcher PW, Camerer C, Poldrack R, Fehr E (2008) Neuroeconomics: decision making and the brain. Academic, New YorkGoogle Scholar
  5. Gratton G, Fabiani M (2001) Shedding light on brain function: the event-related optical signal. Trends Cogn Sci 5:357–363PubMedCrossRefGoogle Scholar
  6. Huettel SA, Stowe CJ, Gordon EM, Warner BT, Platt ML (2006) Neural signatures of economic preferences for risk and ambiguity. Neuron 49:765–775PubMedCrossRefGoogle Scholar
  7. Huettel SA, Song AW, McCarthy G (2009) Functional magnetic resonance imaging, 2nd edn. Sinauer, SunderlandGoogle Scholar
  8. Kable JW, Glimcher PW (2007) The neural correlates of subjective value during intertemporal choice. Nat Neurosci 10:1625–1633PubMedCrossRefGoogle Scholar
  9. Knutson B, Fong GW, Adams CS, Hommer D (2001) Dissociation of reward anticipation versus outcome with event-related FMRI. Neuroreport 12:3683–3687PubMedCrossRefGoogle Scholar
  10. Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A (2001) Neurophysiological investigation of the basis of the fMRI signal. Nature 412:128–130CrossRefGoogle Scholar
  11. Luck SJ (2005) An introduction to the event-related potential technique. MIT Press, Cambridge, MAGoogle Scholar
  12. McClure SM, Laibson DI, Loewenstein G, Cohen JD (2004) Separate neural systems value immediate and delayed monetary rewards. Science 306:503–507PubMedCrossRefGoogle Scholar
  13. Purves D, Brannon EM, Cabeza R, Huettel SA, LaBar KS, Platt ML, Woldorff MG (2008) Principles of cognitive neuroscience. Sinauer, SunderlandGoogle Scholar
  14. Schultz W, Dayan P, Montague PR (1997) A neural substrate of prediction and reward. Science 275:1593–1599PubMedCrossRefGoogle Scholar
  15. Sharot T, Riccardi AM, Raio CM, Phelps EA (2007) Neural mechanisms mediating optimism bias. Nature 450:102–105PubMedCrossRefGoogle Scholar
  16. Venkatraman V, Huettel SA, Chuah LYM, Payne JW, Chee MWL (2011) Sleep deprivation biases the neural mechanisms underlying economic preferences. J Neurosci 31:3712–3718PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2013

Authors and Affiliations

  1. 1.Center for Cognitive NeuroscienceDuke UniversityDurhamUSA

Personalised recommendations