Predicting Decisions in Human Social Interactions Using Real-Time fMRI and Pattern Classification

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives

A proof-of-principle study of multi-site real-time functional imaging at 3T and 7T: Implementation and validation

Real-time functional Magnetic Resonance Imaging (rtfMRI) is used mainly for neurofeedback or for brain-computer interfaces (BCI). But multi-site rtfMRI could in fact help in the application of new interactive paradigms such as the monitoring of mutual information flow or the controlling of objects in shared virtual environments. For that reason, a previously developed framework that provided an integrated control and data analysis of rtfMRI experiments was extended to enable multi-site rtfMRI. Important new components included a data exchange platform for analyzing the data of both MR scanners independently and/or jointly. Information related to brain activation can be displayed separately or in a shared view. However, a signal calibration procedure had to be developed and integrated in order to permit the connecting of sites that had different hardware and to account for different inter-individual brain activation levels. The framework was successfully validated in a proof-of-principle study with twelve volunteers. Thus the overall concept, the calibration of grossly differing signals, and BCI functionality on each site proved to work as required. To model interactions between brains in real-time, more complex rules utilizing mutual activation patterns could easily be implemented to allow for new kinds of social fMRI experiments

Mapping fine-scale anatomy of gray matter, white matter, and trigeminal-root region applying spherical deconvolution to high-resolution 7-T diffusion MRI

OBJECTIVES: We assessed the use of high-resolution ultra-high-field diffusion magnetic resonance imaging (dMRI) to determine neuronal fiber orientation density functions (fODFs) throughout the human brain, including gray matter (GM), white matter (WM), and small intertwined structures in the cerebellopontine region. MATERIALS AND METHODS: We acquired 7-T whole-brain dMRI data of 23 volunteers with 1.4-mm isotropic resolution; fODFs were estimated using constrained spherical deconvolution. RESULTS:High-resolution fODFs enabled a detailed view of the intravoxel distributions of fiber populations in the whole brain. In the brainstem region, the fODF of the extra- and intrapontine parts of the trigeminus could be resolved. Intrapontine trigeminal fiber populations were crossed in a network-like fashion by fiber populations of the surrounding cerebellopontine tracts. In cortical GM, additional evidence was found that in parts of primary somatosensory cortex, fODFs seem to be oriented less perpendicular to the cortical surface than in GM of motor, premotor, and secondary somatosensory cortices. CONCLUSION: With 7-T MRI being introduced into clinical routine, high-resolution dMRI and derived measures such as fODFs can serve to characterize fine-scale anatomic structures as a prerequisite to detecting pathologies in GM and small or intertwined WM tracts

Decrease (blue) and increase (red) of gray matter volume in LDH patients relative to healthy controls.

<p>(<i>p</i><0.0001, uncorrected for multiple comparison, cluster threshold of 15 voxel) The group analysis showed decreased gray matter volumes in the right anterolateral prefrontal cortex (alPFC), the right middle temporal gyrus (MTG), the left premotor cortex (PMC), the right caudate nucleus (CN), and the lobule VIIa (Crus I) of the right cerebellum (LVIIa). Increases were found in the right dorsal anterior cingulate cortex (dACC), the left lateral precuneal region (PCu), the left fusiform gyrus (FusG), and the nucleus reticularis of the right brainstem at the level of the basal pons (nRet). Bilateral increases as well as decreases are shown in the orbitofrontal cortex (OFC). [Images are presented in neurological convention].</p

Significant gray and white matter changes in LDH patients relative to healthy controls.

<p>Significant gray and white matter changes in LDH patients relative to healthy controls.</p

Decrease of the white matter volume in LDH patients relative healthy controls.

<p>(<i>p</i><0.0001, uncorrected for multiple comparison, cluster threshold of 15 voxel) The group analysis showed decreased subcortical white matter volumes adjacent to the left prefrontal cortex (PFC), the right premotor cortex (PMC) and the anterior limb of the left internal capsule (IC). [Images are presented in neurological convention].</p