Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment

In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment

Executive Functions and Prefrontal Cortex: A Matter of Persistence?

Executive function is thought to originates from the dynamics of frontal cortical networks. We examined the dynamic properties of the blood oxygen level dependent time-series measured with functional MRI (fMRI) within the prefrontal cortex (PFC) to test the hypothesis that temporally persistent neural activity underlies performance in three tasks of executive function. A numerical estimate of signal persistence, the Hurst exponent, postulated to represent the coherent firing of cortical networks, was determined and correlated with task performance. Increasing persistence in the lateral PFC was shown to correlate with improved performance during an n-back task. Conversely, we observed a correlation between persistence and increasing commission error – indicating a failure to inhibit a prepotent response – during a Go/No-Go task. We propose that persistence within the PFC reflects dynamic network formation and these findings underline the importance of frequency analysis of fMRI time-series in the study of executive functions

Fractal analysis of resting state functional connectivity of the brain

A variety of resting state neuroimaging data tend to exhibit fractal behavior where its power spectrum follows power-law scaling. Resting state functional connectivity is significantly influenced by fractal behavior which may not directly originate from neuronal population activities of the brain. To describe the fractal behavior, we adopted the fractionally integrated process (FIP) model instead of the fractional Gaussian noise (FGN) since the FIP model covers more general aspects of fractality than the FGN model. We also introduce a novel concept called the nonfractal connectivity which is defined as the correlation of short memory independent of fractal behavior, and compared it with the fractal connectivity which is an asymptotic wavelet correlation. We propose several wavelet-based estimators of fractal connectivity and nonfractal connectivity for a multivariate fractionally integrated noise (mFIN). The performance of these estimators was evaluated through simulation studies and the analyses of resting state functional MRI data of the rat brain.Comment: The 2012 International Joint Conference on Neural Network

Multifractal and entropy analysis of resting-state electroencephalography reveals spatial organization in local dynamic functional connectivity

Functional connectivity of the brain fluctuates even in resting-state condition. It has been reported recently that fluctuations of global functional network topology and those of individual connections between brain regions expressed multifractal scaling. To expand on these findings, in this study we investigated if multifractality was indeed an inherent property of dynamic functional connectivity (DFC) on the regional level as well. Furthermore, we explored if local DFC showed region-specific differences in its multifractal and entropy-related features. DFC analyses were performed on 62-channel, resting-state electroencephalography recordings of twelve young, healthy subjects. Surrogate data testing verified the true multifractal nature of regional DFC that could be attributed to the presumed nonlinear nature of the underlying processes. Moreover, we found a characteristic spatial distribution of local connectivity dynamics, in that frontal and occipital regions showed stronger long-range correlation and higher degree of multifractality, whereas the highest values of entropy were found over the central and temporal regions. The revealed topology reflected well the underlying resting-state network organization of the brain. The presented results and the proposed analysis framework could improve our understanding on how resting-state brain activity is spatio-temporally organized and may provide potential biomarkers for future clinical research

Microstructures And Nanomechanical Properties Of The Bakken Shale

The focus of this thesis is to study the pore structures along with mechanical properties of the shale rocks from the Bakken Formation. The pore structures that are obtained from the SEM image analysis method showed that total surface porosity of the studied samples is less than 12% and that organic porosity is not the main contributor to total porosity for the samples analyzed. Clay minerals and feldspar have a positive influence on porosity while quartz, pyrite, and TOC has a negative impact. The results from the multifractal theory and lacunarity methods based on the segmented SEM images indicated that pores distribution and size in Bakken shale are heterogeneous. Regarding gas adsorption analysis, the results showed that all range of pore sizes: micro (\u3c2 nm), meso (2-50 nm) and macro-pores (\u3e50 nm) exist in the Bakken shale samples. Meso-pores and macro-pores are the main contributors to the porosity for these samples. In comparison with the Middle Bakken, samples from the Upper and Lower Bakken exhibited more micro pore volumes. The deconvolution of the pore distribution function from the combination of N2 and CO2 adsorption results proved that five typical pore size families exist in the Bakken shale samples: one micro-pore, one macro-pore and three meso-pore size clusters. In order to analyze the heterogeneity of the pore structures from gas adsorption, multifractal method was applied to analyze adsorption isotherms (CO2 and N2). The results explained that the generalized dimensions derived from CO2 and the N2 adsorption isotherms decrease as q increases, demonstrating a multifractal behavior. Samples from the Middle Bakken demonstrated the smallest average H value and largest average α10-- α10+ for micropores while samples from the Upper Bakken depicted the highest average α10-- α10+ for the meso-macropores. This indicated that the Middle Bakken and the Upper Bakken have the largest micropore and meso-macropore heterogeneity, respectively. The impact of rock composition on pore structures showed that organic matter could increase the micropore connectivity and reduce micropore heterogeneity. This study was followed by mechanical analysis of shale samples from the Bakken. Statistical grid nanoindentation method was applied to analyze mechanical properties of the Bakken. Then the Mori-Tanaka scheme was carried out to homogenize the elastic properties of the samples and upscale the nanoindentation data to the macroscale. The discrepancy between the macro-mechanical modulus from the homogenization and unconfined compression test was less than 15% which was found acceptable. The creep analysis of the samples describes that minerals with various mechanical properties exhibit different creep behavior. Under the same constant load and time conditions, the creep displacement of hard minerals would be smaller than the soft ones. On the contrary, the changes in mechanical properties (storage modulus, loss modulus, complex modulus, and hardness) of hard minerals are larger than soft minerals. The results from curve fitting led us to conclude that the changes in creep displacement, storage modulus, complex modulus and hardness with respect to the creep time would follow a logarithmic function

Interplay between functional connectivity and scale-free dynamics in intrinsic fMRI networks

International audienceStudies employing functional connectivity-type analyses have established that sponta-neous fluctuations in functional magnetic resonance imaging (fMRI) signals are orga-nized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univari-ate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest fre-quencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional Rev.#1, Q