Locality and low-dimensions in the prediction of natural experience from fMRI

Functional Magnetic Resonance Imaging (fMRI) provides dynamical access into the complex functioning of the human brain, detailing the hemodynamic activity of thousands of voxels during hundreds of sequential time points. One approach towards illuminating the connection between fMRI and cognitive function is through decoding; how do the time series of voxel activities combine to provide information about internal and external experience? Here we seek models of fMRI decoding which are balanced between the simplicity of their interpretation and the effectiveness of their prediction. We use signals from a subject immersed in virtual reality to compare global and local methods of prediction applying both linear and nonlinear techniques of dimensionality reduction. We find that the prediction of complex stimuli is remarkably low-dimensional, saturating with less than 100 features. In particular, we build effective models based on the decorrelated components of cognitive activity in the classically-defined Brodmann areas. For some of the stimuli, the top predictive areas were surprisingly transparent, including Wernicke's area for verbal instructions, visual cortex for facial and body features, and visual-temporal regions for velocity. Direct sensory experience resulted in the most robust predictions, with the highest correlation ($c \sim 0.8$) between the predicted and experienced time series of verbal instructions. Techniques based on non-linear dimensionality reduction (Laplacian eigenmaps) performed similarly. The interpretability and relative simplicity of our approach provides a conceptual basis upon which to build more sophisticated techniques for fMRI decoding and offers a window into cognitive function during dynamic, natural experience.Comment: To appear in: Advances in Neural Information Processing Systems 20, Scholkopf B., Platt J. and Hofmann T. (Editors), MIT Press, 200

Inter-Subject Synchronization of Prefrontal Cortex Hemodynamic Activity During Natural Viewing

Hemodynamic activity in occipital, temporal, and parietal cortical areas were recently shown to correlate across subjects during viewing of a 30-minute movie clip. However, most of the frontal cortex lacked between-subject correlations. Here we presented 12 healthy naïve volunteers with the first 72 minutes of a movie (“Crash”, 2005, Lions Gate Films) outside of the fMRI scanner to involve the subjects in the plot of the movie, followed by presentation of the last 36 minutes during fMRI scanning. We observed significant between-subjects correlation of fMRI activity in especially right hemisphere frontal cortical areas, in addition to the correlation of activity in temporal, occipital, and parietal areas. It is possible that this resulted from the subjects following the plot of the movie and being emotionally engaged in the movie during fMRI scanning. We further show that probabilistic independent component analysis (ICA) reveals meaningful activations in individual subjects during natural viewing

Functional network connectivity and topology during naturalistic stimulus is altered in first-episode psychosis

Background: Psychotic disorders have been suggested to derive from dysfunctional integration of signaling between brain regions. Earlier studies have found several changes in functional network synchronization as well as altered network topology in patients with psychotic disorders. However, studies have used mainly resting-state that makes it more difficult to link functional alterations to any specific stimulus or experience. We set out to examine functional connectivity as well as graph (topological) measures and their association to symptoms in first-episode psychosis patients during movie viewing. Our goal was to understand whole-brain functional dynamics of complex naturalistic information processing in psychosis and changes in brain functional organization related to symptoms. Methods: 71 first-episode psychosis patients and 57 control subjects watched scenes from the movie Alice in Wonderland during 3 T fMRI. We compared functional connectivity and graph measures indicating integration, segregation and centrality between groups, and examined the association between topology and symptom scores in the patient group. Results: We identified a subnetwork with predominantly decreased links of functional connectivity in firstepisode psychosis patients. The subnetwork was mainly comprised of nodes of and links between the cinguloopercular, sensorimotor and default-mode networks. In topological measures, we observed between-group differences in properties of centrality. Conclusions: Functional brain networks are affected during naturalistic information processing already in the early stages of psychosis, concentrated in salience- and cognitive control-related hubs and subnetworks. Understanding these aberrant dynamics could add to better targeted cognitive and behavioral interventions in the early stages of psychotic disorders.Peer reviewe

Functional Subdivision of Group-ICA Results of fMRI Data Collected during Cinema Viewing

Independent component analysis (ICA) can unravel functional brain networks from functional magnetic resonance imaging (fMRI) data. The number of the estimated components affects both the spatial pattern of the identified networks and their time-course estimates. Here group-ICA was applied at four dimensionalities (10, 20, 40, and 58 components) to fMRI data collected from 15 subjects who viewed a 15-min silent film (“At land” by Maya Deren). We focused on the dorsal attention network, the default-mode network, and the sensorimotor network. The lowest dimensionalities demonstrated most prominent activity within the dorsal attention network, combined with the visual areas, and in the default-mode network; the sensorimotor network only appeared with ICA comprising at least 20 components. The results suggest that even very low-dimensional ICA can unravel the most prominent functionally-connected brain networks. However, increasing the number of components gives a more detailed picture and functionally feasible subdivision of the major networks. These results improve our understanding of the hierarchical subdivision of brain networks during viewing of a movie that provides continuous stimulation embedded in an attention-directing narrative.Peer reviewe

Differentiation between Vergence and Saccadic Functional Activity within the Human Frontal Eye Fields and Midbrain Revealed through fMRI

Eye movement research has traditionally studied solely saccade and/or vergence eye movements by isolating these systems within a laboratory setting. While the neural correlates of saccadic eye movements are established, few studies have quantified the functional activity of vergence eye movements using fMRI. This study mapped the neural substrates of vergence eye movements and compared them to saccades to elucidate the spatial commonality and differentiation between these systems.The stimulus was presented in a block design where the 'off' stimulus was a sustained fixation and the 'on' stimulus was random vergence or saccadic eye movements. Data were collected with a 3T scanner. A general linear model (GLM) was used in conjunction with cluster size to determine significantly active regions. A paired t-test of the GLM beta weight coefficients was computed between the saccade and vergence functional activities to test the hypothesis that vergence and saccadic stimulation would have spatial differentiation in addition to shared neural substrates.Segregated functional activation was observed within the frontal eye fields where a portion of the functional activity from the vergence task was located anterior to the saccadic functional activity (z>2.3; p<0.03). An area within the midbrain was significantly correlated with the experimental design for the vergence but not the saccade data set. Similar functional activation was observed within the following regions of interest: the supplementary eye field, dorsolateral prefrontal cortex, ventral lateral prefrontal cortex, lateral intraparietal area, cuneus, precuneus, anterior and posterior cingulates, and cerebellar vermis. The functional activity from these regions was not different between the vergence and saccade data sets assessed by analyzing the beta weights of the paired t-test (p>0.2).Functional MRI can elucidate the differences between the vergence and saccade neural substrates within the frontal eye fields and midbrain

Temporal and Spatial Independent Component Analysis for fMRI Data Sets Embedded in the AnalyzeFMRI R Package

For statistical analysis of functional magnetic resonance imaging (fMRI) data sets, we propose a data-driven approach based on independent component analysis (ICA) implemented in a new version of the AnalyzeFMRI R package. For fMRI data sets, spatial dimension being much greater than temporal dimension, spatial ICA is the computationally tractable approach generally proposed. However, for some neuroscientific applications, temporal independence of source signals can be assumed and temporal ICA becomes then an attractive exploratory technique. In this work, we use a classical linear algebra result ensuring the tractability of temporal ICA. We report several experiments on synthetic data and real MRI data sets that demonstrate the potential interest of our R package

Non-linear ICA Analysis of Resting-State fMRI in Mild Cognitive Impairment

Compared to linear independent component analysis (ICA), non-linear ICA is more suitable for the decomposition of mixed components. Existing studies of functional magnetic resonance imaging (fMRI) data by using linear ICA assume that the brain's mixed signals, which are caused by the activity of brain, are formed through the linear combination of source signals. But the application of the non-linear combination of source signals is more suitable for the mixed signals of brain. For this reason, we investigated statistical differences in resting state networks (RSNs) on 32 healthy controls (HC) and 38 mild cognitive impairment (MCI) patients using post-nonlinear ICA. Post-nonlinear ICA is one of the non-linear ICA methods. Firstly, the fMRI data of all subjects was preprocessed. The second step was to extract independent components (ICs) of fMRI data of all subjects. In the third step, we calculated the correlation coefficient between ICs and RSN templates, and selected ICs of the largest spatial correlation coefficient. The ICs represent the corresponding RSNs. After finding out the eight RSNs of MCI group and HC group, one sample t-tests were performed. Finally, in order to compare the differences of RSNs between MCI and HC groups, the two-sample t-tests were carried out. We found that the functional connectivity (FC) of RSNs in MCI patients was abnormal. Compared with HC, MCI patients showed the increased and decreased FC in default mode network (DMN), central executive network (CEN), dorsal attention network (DAN), somato-motor network (SMN), visual network(VN), MCI patients displayed the specifically decreased FC in auditory network (AN), self-referential network (SRN). The FC of core network (CN) did not reveal significant group difference. The results indicate that the abnormal FC in RSNs is selective in MCI patients

Listening to an Audio Drama Activates Two Processing Networks, One for All Sounds, Another Exclusively for Speech

Peer reviewe

Mapping inter-subject and inter-regional brain connectivity during free viewing of novel natural scenes

Traditional functional magnetic resonance imaging (fMRI) studies have used controlled tasks such as finger tapping to isolate function in distinct cortical. Recent studies have examined the mechanisms involved during natural conditions by asking subjects to freely view the presentation of a movie. The objective of our study was to further observe the extent to which similarities are present between subjects during natural vision. It was hypothesized that there would be a linear relationship between the percentage of region-specific overlap, which is the percent of the anatomical region of interest which contains spatial activation exhibited by all six subjects, and corresponding temporal correlation values between subjects from those regions. In this study, a controlled experiment was conducted in which all the subjects viewed a movie clip from the 2005 thriller Redeye for the first time during the tMRI scan. Spatial and temporal correlations were examined during a forty minute movie clip in which subjects casually viewed the stimulus. Significant spatial overlap between the six scanned subjects was observed in many regions during the viewing of the forty minute stimulus and this overlap was considerably lower during the second ten minute viewing. Temporal correlation values as high as 0.8 were observed between subjects during the viewing of the forty minute clip. Interregional correlation was also examined within subjects. The use of a movie clip allowed for the activation of a numerous functional regions in a single duration to identify similarity in cortical activation during a complex stimulus both spatially and temporally