Related papers: Task-dependent fractal patterns of information pro…
Brain decoding algorithms form an important part of the arsenal of analysis tools available to neuroscientists, allowing for a more detailed study of the kind of information represented in patterns of cortical activity. While most current…
Functional magnetic resonance imaging (fMRI) is a neuroimaging technique known for its ability to capture brain activity non-invasively and at fine spatial resolution (2-3mm). Cortical surface fMRI (cs-fMRI) is a recent development of fMRI…
The human brain has been studied at multiple scales, from neurons, circuits, areas with well defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed…
Decoding speech from brain activity has typically relied on limited neural recordings collected during short and highly controlled experiments. Here, we introduce a framework to leverage week-long intracranial and audio recordings from…
Physiological signals can potentially be applied as objective measures to understand the behavior and engagement of users interacting with information access systems. However, the signals are highly sensitive, and many controls are required…
We analyze the complex networks associated with brain electrical activity. Multichannel EEG measurements are first processed to obtain 3D voxel activations using the tomographic algorithm LORETA. Then, the correlation of the current…
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…
Functional connectivity refers to the temporal statistical relationship between spatially distinct brain regions and is usually inferred from the time series coherence/correlation in brain activity between regions of interest. In human…
Real-world scene perception is typically studied in the laboratory using static picture viewing with restrained head position. Consequently, the transfer of results obtained in this paradigm to real-word scenarios has been questioned. The…
It has become increasingly popular to study the brain as a network due to the realization that functionality cannot be explained exclusively by independent activation of specialized regions. Instead, across a large spectrum of behaviors,…
Visual working memory (VWM) allows us to actively store, update and manipulate visual information surrounding us. While the underlying neural mechanisms of VWM remain unclear, contralateral delay activity (CDA), a sustained negativity over…
Many studies have discussed the difference in brain activity related to encoding and retrieval of working memory (WM) tasks. However, it remains unclear if there is a change in brain activation associated with re-encoding. The main…
Brain decoding, understood as the process of mapping brain activities to the stimuli that generated them, has been an active research area in the last years. In the case of language stimuli, recent studies have shown that it is possible to…
Human learning is a complex process in which future behavior is altered via the reorganization of brain activity and connectivity. It remains unknown whether activity and connectivity differentially reorganize during learning, and, if so,…
In recent years,the application of deep learning in task functional Magnetic Resonance Imaging (tfMRI) decoding has led to significant advancements. However,most studies remain constrained by assumption of temporal stationarity in neural…
An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand the relationship between functional fluctuation and human cognition/behavior using a data-driven approach. To…
Emotion recognition is a critical component of affective computing. Training accurate machine learning models for emotion recognition typically requires a large amount of labeled data. Due to the subtleness and complexity of emotions,…
Working memory (WM) is a mechanism that temporarily stores and manipulates information in service of behavioral goals and is a highly dynamic process. Previous studies have considered decoding WM load using EEG but have not investigated the…
In the past three decades, neuroimaging has provided important insights into structure-function relationships in the human brain. Recently, however, the methods for analyzing functional magnetic resonance imaging (fMRI) data have come under…
Human brains exhibit highly organized multiscale neurophysiological dynamics. Understanding those dynamic changes and the neuronal networks involved is critical for understanding how the brain functions in health and disease. Functional…