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How Predictable are “Spontaneous Decisions” and “Hidden Intentions”? Comparing Classification Results Based on Previous Responses with Multivariate Pattern Analysis of fMRI BOLD Signals

By Martin Lages and Katarzyna Jaworska


In two replication studies we examined response bias and dependencies in voluntary decisions. We trained a linear classifier to predict “spontaneous decisions” and in the second study “hidden intentions” from responses in preceding trials and achieved comparable prediction accuracies as reported for multivariate pattern classification based on voxel activities in frontopolar cortex. We discuss implications of our findings and suggest ways to improve classification analyses of fMRI BOLD signals that may help to reduce effects of response dependencies between trials

Topics: Psychology
Publisher: Frontiers Research Foundation
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Provided by: PubMed Central
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    1. (2010). A critique of multi-voxel pattern analysis,”
    2. (1960). Response-tendencies in attempts to generate random binary series. A m .J .P s y c h o l .73,
    3. (2011). Tracking the unconscious generation of free decisions using ultra-high field fMRI.
    4. (2009). How green is the grass on the other side? Frontopolar cortex and the evidence in favor of alternative courses of action.
    5. (2008). The what, when, whether model of intentionalaction.Neuroscientist 14,
    6. (2001). Brain regions involved in prospective memory as determined by positron emission tomography.
    7. (2000). The frontopolar cortex and human cognition: evidence for a rostrocaudal hierarchical organization within the human prefrontal cortex.
    8. (2001). Rostrolateral prefrontal cortex involvement in relational integration during reasoning.
    9. (2007). Making up the Mind: How the Brain Creates our Mental World.
    10. (2008). Human volition: towards neuroscience of will.
    11. (2010). Statistical learning analysis in neuroscience: aiming for transparency.
    12. (2008). Brain reading using full brain support vector machines for object recognition: there is no“face” identification area.
    13. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex.
    14. (2007). Reading hidden intentions in the human brain.
    15. (2009). Is free will an illusion?
    16. (2004). Probability effects on theneuralcorrelatesof retrievalsuccess: an fMRI study.
    17. (2000). The role of the dorsolateral prefrontal cortex in random number generation: a study with positron emission tomography.
    18. (2007). A tutorial on kernel methods for categorization.
    19. (2007). Anteriorprefrontalfunctionandthe limits of human decision-making.
    20. (2009). Circular analysis in systems neuroscience: the dangers of double dipping.
    21. (2009). Dissociating what and when of intentional actions.
    22. (1999). Algebraic Decomposition on of Individual Choice Behavior. Materialien aus der Bildungsforschung’No.63.Berlin:MaxPlanck Institute for Human Development.
    23. (2002). Ear decomposition for pair comparison data.
    24. (2006). Visual long-term memory for spatial frequency?
    25. (1998). Spatial frequency discrimination: visual long-term memory or criterionsetting?VisionRes.38,557–572.
    26. (2010). A criterion setting theory of discrimination learning that accounts for anisotropies and context effects.
    27. Attention to intention.
    28. (2000). Prefrontal cortex and episodic memory retrieval mode.
    29. (2004). Preparing for action: inferences from CNV and LRP.
    30. andPearl,D.K.(1983).Timeof conscious intention to act in relation to onset of cerebral activity (readinesspotential). The unconscious initiation of a freely voluntary act.
    31. (1967). On the Kolmogorov–Smirnov test for normality with mean and variance unknown.
    32. (1986). Response Times. Their Role in Inferring Elementary Mental Organization.
    33. andFrith,C.D.(2007).Law,responsibility, and the brain.
    34. (2009). Machine learning classifiers and fMRI: a tutorial overview.
    35. (2004). Anterior prefrontal cortex: insights into function from anatomy and neuroimaging.
    36. (2011). Prediction of decisions from noise in the brain before the evidence is provided.
    37. (2008). Unconsciousdeterminantsoffreedecisions in the human brain.
    38. (2012). 6Lages and Jaworska How predictable are voluntary decisions?
    39. (2010). Sensory integration across modalities: how kinaesthesia integrates with vision in visual orientation discrimination.
    40. (2011). paper pending published: 06
    41. (2012)Howpredictableare“spontaneous decisions” and “hidden intentions”? Comparing classification results based on previous responses with multivariate pattern analysis of fMRI BOLD signals.
    42. (2012). and Jaworska How predictable are voluntary decisions?

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