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The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input., (Copyright © 2021. Published by Elsevier Inc.)

The relationship between anatomic and resting state functional connectivity of large-scale brain networks is a major focus of current research. In previous work, we introduced a model based on eigen decomposition of the Laplacian which predicts the functional network from the structural network in healthy brains. In this work, we apply the eigen decomposition model to two types of epilepsy; temporal lobe epilepsy associated with mesial temporal sclerosis, and MRI-normal temporal lobe epilepsy. Our findings show that the eigen relationship between function and structure holds for patients with temporal lobe epilepsy as well as normal individuals. These results suggest that the brain under TLE conditions reconfigures and rewires the fine-scale connectivity (a process which the model parameters are putatively sensitive to), in order to achieve the necessary structure-function relationship., (Copyright © 2020. Published by Elsevier Inc.)

How structural connectivity (SC) gives rise to functional connectivity (FC) is not fully understood. Here we mathematically derive a simple relationship between SC measured from diffusion tensor imaging, and FC from resting state fMRI. We establish that SC and FC are related via (structural) Laplacian spectra, whereby FC and SC share eigenvectors and their eigenvalues are exponentially related. This gives, for the first time, a simple and analytical relationship between the graph spectra of structural and functional networks. Laplacian eigenvectors are shown to be good predictors of functional eigenvectors and networks based on independent component analysis of functional time series. A small number of Laplacian eigenmodes are shown to be sufficient to reconstruct FC matrices, serving as basis functions. This approach is fast, and requires no time-consuming simulations. It was tested on two empirical SC/FC datasets, and was found to significantly outperform generative model simulations of coupled neural masses., (Copyright © 2018. Published by Elsevier Inc.)

Septal nuclei, located in basal forebrain, are strongly connected with hippocampi and important in learning and memory, but have received limited research attention in human MRI studies. While probabilistic maps for estimating septal volume on MRI are now available, they have not been independently validated against manual tracing of MRI, typically considered the gold standard for delineating brain structures. We developed a protocol for manual tracing of the human septal region on MRI based on examination of neuroanatomical specimens. We applied this tracing protocol to T1 MRI scans (n=86) from subjects with temporal epilepsy and healthy controls to measure septal volume. To assess the inter-rater reliability of the protocol, a second tracer used the same protocol on 20 scans that were randomly selected from the 72 healthy controls. In addition to measuring septal volume, maximum septal thickness between the ventricles was measured and recorded. The same scans (n=86) were also analyzed using septal probabilistic maps and DARTEL toolbox in SPM. Results show that our manual tracing algorithm is reliable, and that septal volume measurements obtained via manual and automated methods correlate significantly with each other (p<.001). Both manual and automated methods detected significantly enlarged septal nuclei in patients with temporal lobe epilepsy in accord with a proposed compensatory neuroplastic process related to the strong connections between septal nuclei and hippocampi. Septal thickness, which was simple to measure with excellent inter-rater reliability, correlated well with both manual and automated septal volume, suggesting it could serve as an easy-to-measure surrogate for septal volume in future studies. Our results call attention to the important though understudied human septal region, confirm its enlargement in temporal lobe epilepsy, and provide a reliable new manual delineation protocol that will facilitate continued study of this critical region., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Intracranial electrode arrays are routinely used in the pre-surgical evaluation of patients with medically refractory epilepsy, and recordings from these electrodes have been increasingly employed in human cognitive neurophysiology due to their high spatial and temporal resolution. For both researchers and clinicians, it is critical to localize electrode positions relative to the subject-specific neuroanatomy. In many centers, a post-implantation MRI is utilized for electrode detection because of its higher sensitivity for surgical complications and the absence of radiation. However, magnetic susceptibility artifacts surrounding each electrode prohibit unambiguous detection of individual electrodes, especially those that are embedded within dense grid arrays. Here, we present an efficient method to accurately localize intracranial electrode arrays based on pre- and post-implantation MR images that incorporates array geometry and the individual's cortical surface. Electrodes are directly visualized relative to the underlying gyral anatomy of the reconstructed cortical surface of individual patients. Validation of this approach shows high spatial accuracy of the localized electrode positions (mean of 0.96 mm ± 0.81 mm for 271 electrodes across 8 patients). Minimal user input, short processing time, and utilization of radiation-free imaging are strong incentives to incorporate quantitatively accurate localization of intracranial electrode arrays with MRI for research and clinical purposes. Co-registration to a standard brain atlas further allows inter-subject comparisons and relation of intracranial EEG findings to the larger body of neuroimaging literature., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, 'N') and words that repeated (old, 'O'). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs. O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs. O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350 to 450 ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal., (Copyright 2010 Elsevier Inc. All rights reserved.)

Accurate pronunciation of phonetically irregular words (exception words) requires prior exposure to unique relationships between orthographic and phonemic features. Whether such word knowledge is accompanied by structural variation in areas associated with orthographic-to-phonemic transformations has not been investigated. We used high-resolution MRI to determine whether performance on a visual word-reading test composed of phonetically irregular words, the Wechsler Test of Adult Reading (WTAR), is associated with regional variations in cortical structure. A sample of 60 right-handed, neurologically intact individuals were administered the WTAR and underwent 3T volumetric MRI. Using quantitative, surface-based image analysis, cortical thickness was estimated at each vertex on the cortical mantle and correlated with WTAR scores while controlling for age. Higher scores on the WTAR were associated with thicker cortex in bilateral anterior superior temporal gyrus, bilateral angular gyrus/posterior superior temporal gyrus, and left hemisphere intraparietal sulcus. Higher scores were also associated with thinner cortex in left hemisphere posterior fusiform gyrus and central sulcus, bilateral inferior frontal gyrus, and right hemisphere lingual gyrus and supramarginal gyrus. These results suggest that the ability to correctly pronounce phonetically irregular words is associated with structural variations in cortical areas that are commonly activated in functional neuroimaging studies of word reading, including areas associated with grapheme-to-phonemic conversion., (Copyright 2010 Elsevier Inc. All rights reserved.)