Three separate fMRI studies were conducted to study the neural dynamics of free decision formation. In Study 1, we first searched across the brain for spatiotemporal patterns that could predict the specific outcome and timing of free motor decisions to make a left or right button press (Soon et al., 2008). In Study 2, we replicated Study 1 using ultra-high field fMRI for improved temporal and spatial resolution to more accurately characterize the evolution of decision-predictive information in prefrontal cortex (Bode et al., 2011). In Study 3, to unequivocally dissociate high-level intentions from motor preparation and execution, we investigated the neural precursors of abstract intentions as participants spontaneously decided to perform either of two mental arithmetic tasks: addition or subtraction (Soon et al., 2013). Across the three studies, we consistently found that upcoming decisions could be predicted with ~60% accuracy from fine-grained spatial activation patterns occurring a few seconds before the decisions reached awareness, with very similar profiles for both motor and abstract intentions. The content and timing of the decisions appeared to be encoded in two functionally dissociable sets of regions: frontopolar and posterior cingulate/ precuneus cortex encoded the content but not the timing of the decisions, while the pre-supplementary motor area encoded the timing but not the content of the decisions. The choice-predictive regions in both motor and abstract decision tasks overlapped partially with the default mode network. High-resolution imaging in Study 2 further revealed that as the time-point of conscious decision approached, activity patterns in frontopolar cortex became increasingly stable with respect to the final choice.:Abstract 1
1. General Introduction 5
2. Study 1: Decoding the Unconscious Formation of Motor Intentions 21
3. Study 2: Temporal Stability of Neural Patterns Involved in Intention Formation 56
4. Study 3: Decoding the Unconscious Formation of Abstract Intentions 89
5. General Discussion 119
References 145
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:30275 |
| Date | 10 April 2017 |
| Creators | Soon, Chun Siong |
| Contributors | Haynes, John-Dylan, Goschke, Thomas, Technische Universität Dresden |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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