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Background: Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in lowresource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people. Methods: T1- and T2-weighted structural MR images were obtained from a low- field (64mT) Hyperfine and high-field (3T) Siemens system in N = 70 individuals (mean age = 20.39 years, range 9--26 years). We tested two super-resolution approaches to improve image correspondence between images acquired at high- and low-field: (1) processing via a convolutional neural network ('SynthSR'), and (2) multi-orientation image averaging. We extracted brain region volumes, cortical thickness, and cortical surface area estimates. We used Pearson correlations to test the correspondence between these measures, and Steiger Z tests to compare the difference in correspondence between standard imaging and super-resolution approaches. Results: Single pairs of T1- and T2-weighted images acquired at low field showed high correspondence to high-field-strength images for estimates of total intracranial volume, surface area cortical volume, subcortical volume, and total brain volume (r range = 0.60--0.88). Correspondence was lower for cerebral white matter volume (r = 0.32, p = 0.007, q = 0.009) and non-significant for mean cortical thickness (r = -0.05, p = 0.664, q = 0.664). Processing images with SynthSR yielded significant improvements in correspondence for total brain volume, white matter volume, total surface area, subcortical volume, cortical volume, and total intracranial volume (r range = 0.85--0.97), with the exception of global mean cortical thickness (r = 0.14). An alternative multi-orientation image averaging approach improved correspondence for cerebral white matter and total brain volume. Processing with SynthSR also significantly improved correspondence across widespread regions for estimates of cortical volume, surface area and subcortical volume, as well as within isolated prefrontal and temporal regions for estimates of cortical thickness. Conclusion: Applying super-resolution approaches to low-field imaging improves regional brain volume and surface area accuracy in young people. Finer-scale brain measurements, such as cortical thickness, remain challenging with the limited resolution of low-field systems. [ABSTRACT FROM AUTHOR]

Objective: Epilepsy patients are often grouped together by clinical variables. Quantitative neuroimaging metrics can provide a data‐driven alternative for grouping of patients. In this work, we leverage ultra‐high‐field 7‐T structural magnetic resonance imaging (MRI) to characterize volumetric atrophy patterns across hippocampal subfields and thalamic nuclei in drug‐resistant focal epilepsy. Methods: Forty‐two drug‐resistant epilepsy patients and 13 controls with 7‐T structural neuroimaging were included in this study. We measured hippocampal subfield and thalamic nuclei volumetry, and applied an unsupervised machine learning algorithm, Latent Dirichlet Allocation (LDA), to estimate atrophy patterns across the hippocampal subfields and thalamic nuclei of patients. We studied the association between predefined clinical groups and the estimated atrophy patterns. Additionally, we used hierarchical clustering on the LDA factors to group patients in a data‐driven approach. Results: In patients with mesial temporal sclerosis (MTS), we found a significant decrease in volume across all ipsilateral hippocampal subfields (false discovery rate‐corrected p [pFDR] <.01) as well as in some ipsilateral (pFDR <.05) and contralateral (pFDR <.01) thalamic nuclei. In left temporal lobe epilepsy (L‐TLE) we saw ipsilateral hippocampal and some bilateral thalamic atrophy (pFDR <.05), whereas in right temporal lobe epilepsy (R‐TLE) extensive bilateral hippocampal and thalamic atrophy was observed (pFDR <.05). Atrophy factors demonstrated that our MTS cohort had two atrophy phenotypes: one that affected the ipsilateral hippocampus and one that affected the ipsilateral hippocampus and bilateral anterior thalamus. Atrophy factors demonstrated posterior thalamic atrophy in R‐TLE, whereas an anterior thalamic atrophy pattern was more common in L‐TLE. Finally, hierarchical clustering of atrophy patterns recapitulated clusters with homogeneous clinical properties. Significance: Leveraging 7‐T MRI, we demonstrate widespread hippocampal and thalamic atrophy in epilepsy. Through unsupervised machine learning, we demonstrate patterns of volumetric atrophy that vary depending on disease subtype. Incorporating these atrophy patterns into clinical practice could help better stratify patients to surgical treatments and specific device implantation strategies. [ABSTRACT FROM AUTHOR]

Objective: Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug‐resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. Methods: We created iEEG‐recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG‐recon in a containerized format that allows integration into clinical workflows. We propose a cloud‐based implementation of iEEG‐recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. Results: We used iEEG‐recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30‐min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG‐recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre‐ and postimplant T1‐MRI visual inspections. We also found that our use of ANTsPyNet deep learning‐based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. Significance: iEEG‐recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG‐recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide. [ABSTRACT FROM AUTHOR]

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations—leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD‐AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI. [ABSTRACT FROM AUTHOR]

In March 2022, the first ISMRM Workshop on Low‐Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low‐field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low‐field MRI within traditional radiology practices, other point‐of‐care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low‐field portable systems that are purpose‐built for clinical decision‐making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value. [ABSTRACT FROM AUTHOR]

Objective: Epilepsy surgery is an effective treatment for drug‐resistant patients. However, how different surgical approaches affect long‐term brain structure remains poorly characterized. Here, we present a semiautomated method for quantifying structural changes after epilepsy surgery and compare the remote structural effects of two approaches, anterior temporal lobectomy (ATL), and selective amygdalohippocampectomy (SAH). Methods: We studied 36 temporal lobe epilepsy patients who underwent resective surgery (ATL = 22, SAH = 14). All patients received same‐scanner MR imaging preoperatively and postoperatively (mean 2 years). To analyze postoperative structural changes, we segmented the resection zone and modified the Advanced Normalization Tools (ANTs) longitudinal cortical pipeline to account for resections. We compared global and regional annualized cortical thinning between surgical treatments. Results: Across procedures, there was significant cortical thinning in the ipsilateral insula, fusiform, pericalcarine, and several temporal lobe regions outside the resection zone as well as the contralateral hippocampus. Additionally, increased postoperative cortical thickness was seen in the supramarginal gyrus. Patients treated with ATL exhibited greater annualized cortical thinning compared with SAH cases (ATL: −0.08 ± 0.11 mm per year, SAH: −0.01 ± 0.02 mm per year, t = 2.99, P = 0.006). There were focal postoperative differences between the two treatment groups in the ipsilateral insula (P = 0.039, corrected). Annualized cortical thinning rates correlated with preoperative cortical thickness (r = 0.60, P < 0.001) and had weaker associations with age at surgery (r = −0.33, P = 0.051) and disease duration (r = −0.42, P = 0.058). Significance: Our evidence suggests that selective procedures are associated with less cortical thinning and that earlier surgical intervention may reduce long‐term impacts on brain structure. [ABSTRACT FROM AUTHOR]

Objective: Temporal lobe epilepsy (TLE) is the most common type of focal epilepsy. An increasingly identified subset of patients with TLE consists of those who show bilaterally independent temporal lobe seizures. The purpose of this study was to leverage network neuroscience to better understand the interictal whole brain network of bilateral TLE (BiTLE). Methods: In this study, using a multicenter resting state functional magnetic resonance imaging (rs‐fMRI) data set, we constructed whole‐brain functional networks of 19 patients with BiTLE, and compared them to those of 75 patients with unilateral TLE (UTLE). We quantified resting‐state, whole‐brain topological properties using metrics derived from network theory, including clustering coefficient, global efficiency, participation coefficient, and modularity. For each metric, we computed an average across all brain regions, and iterated this process across network densities. Curves of network density vs each network metric were compared between groups. Finally, we derived a combined metric, which we term the "integration‐segregation axis," by combining whole‐brain average clustering coefficient and global efficiency curves, and applying principal component analysis (PCA)–based dimensionality reduction. Results: Compared to UTLE, BiTLE had decreased global efficiency (p =.031), and decreased whole brain average participation coefficient across a range of network densities (p =.019). Modularity maximization yielded a larger number of smaller communities in BiTLE than in UTLE (p =.020). Differences in network properties separate BiTLE and UTLE along the integration‐segregation axis, with regions within the axis having a specificity of up to 0.87 for BiTLE. Along the integration‐segregation axis, UTLE patients with poor surgical outcomes were distributed in the same regions as BiTLE, and network metrics confirmed similar patterns of increased segregation in both BiTLE and poor outcome UTLE. Significance: Increased interictal whole‐brain network segregation, as measured by rs‐fMRI, is specific to BiTLE, as well as poor surgical outcome UTLE, and may assist in non‐invasively identifying this patient population prior to intracranial electroencephalography or device implantation. [ABSTRACT FROM AUTHOR]

Objective: Measuring cortico‐cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low‐frequency oscillations. Methods: We studied 11 patients who underwent CCEP mapping after stereo‐electroencephalography electrode implantation for surgical evaluation of drug‐resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15–50 ms post‐stimulation) and N2 (50–300 ms post‐stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure‐onset zone (SOZ) or interictal spike rates. Results: We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial‐level N1 amplitude with low‐frequency phase in the hippocampus, which did not localize the SOZ. Significance: These findings suggest that standard approaches for CCEP mapping, which involve computing a trial‐averaged response over a.2–1 Hz stimulation train, may be masking inter‐trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low‐frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase‐locked stimulation could have a role in localizing epileptogenic tissue. [ABSTRACT FROM AUTHOR]

Temporal lobe epilepsy (TLE) is one of the most common subtypes of focal epilepsy, with mesial temporal sclerosis (MTS) being a common radiological and histopathological finding. Accurate identification of MTS during presurgical evaluation confers an increased chance of good surgical outcome. Here we propose the use of glutamate‐weighted chemical exchange saturation transfer (GluCEST) magnetic resonance imaging (MRI) at 7 Tesla for mapping hippocampal glutamate distribution in epilepsy, allowing to differentiate lesional from non‐lesional mesial TLE. We demonstrate that a directional asymmetry index, which quantifies the relative difference between GluCEST contrast in hippocampi ipsilateral and contralateral to the seizure onset zone, can differentiate between sclerotic and non‐sclerotic hippocampi, even in instances where traditional presurgical MRI assessments did not provide evidence of sclerosis. Overall, our results suggest that hippocampal glutamate mapping through GluCEST imaging is a valuable addition to the presurgical epilepsy evaluation toolbox. [ABSTRACT FROM AUTHOR]

Modern MRI scanners have trended toward higher field strengths to maximize signal and resolution while minimizing scan time. However, high‐field devices remain expensive to install and operate, making them scarce outside of high‐income countries and major population centers. Low‐field strength scanners have drawn renewed academic, industry, and philanthropic interest due to advantages that could dramatically increase imaging access, including lower cost and portability. Nevertheless, low‐field MRI still faces inherent limitations in image quality that come with decreased signal. In this article, we review advantages and disadvantages of low‐field MRI scanners, describe hardware and software innovations that accentuate advantages and mitigate disadvantages, and consider clinical applications for a new generation of low‐field devices. In our review, we explore how these devices are being or could be used for high acuity brain imaging, outpatient neuroimaging, MRI‐guided procedures, pediatric imaging, and musculoskeletal imaging. Challenges for their successful clinical translation include selecting and validating appropriate use cases, integrating with standards of care in high resource settings, expanding options with actionable information in low resource settings, and facilitating health care providers and clinical practice in new ways. By embracing both the promise and challenges of low‐field MRI, clinicians and researchers have an opportunity to transform medical care for patients around the world. Level of Evidence: 5 Technical Efficacy: Stage 6 [ABSTRACT FROM AUTHOR]

Planning surgery for patients with medically refractory epilepsy often requires recording seizures using intracranial EEG. Quantitative measures derived from interictal intracranial EEG yield potentially appealing biomarkers to guide these surgical procedures; however, their utility is limited by the sparsity of electrode implantation as well as the normal confounds of spatiotemporally varying neural activity and connectivity. We propose that comparing intracranial EEG recordings to a normative atlas of intracranial EEG activity and connectivity can reliably map abnormal regions, identify targets for invasive treatment and increase our understanding of human epilepsy. Merging data from the Penn Epilepsy Center and a public database from the Montreal Neurological Institute, we aggregated interictal intracranial EEG retrospectively across 166 subjects comprising >5000 channels. For each channel, we calculated the normalized spectral power and coherence in each canonical frequency band. We constructed an intracranial EEG atlas by mapping the distribution of each feature across the brain and tested the atlas against data from novel patients by generating a z-score for each channel. We demonstrate that for seizure onset zones within the mesial temporal lobe, measures of connectivity abnormality provide greater distinguishing value than univariate measures of abnormal neural activity. We also find that patients with a longer diagnosis of epilepsy have greater abnormalities in connectivity. By integrating measures of both single-channel activity and inter-regional functional connectivity, we find a better accuracy in predicting the seizure onset zones versus normal brain (area under the curve = 0.77) compared with either group of features alone. We propose that aggregating normative intracranial EEG data across epilepsy centres into a normative atlas provides a rigorous, quantitative method to map epileptic networks and guide invasive therapy. We publicly share our data, infrastructure and methods, and propose an international framework for leveraging big data in surgical planning for refractory epilepsy. [ABSTRACT FROM AUTHOR]

Episodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. Evidence from functional neuroimaging and invasive recordings in humans suggest that reinstatement organizes our memories by time or content, yet the neural systems involved in reinstating these unique types of information remain unclear. Here, combining computational modeling and intracranial recordings from 69 epilepsy patients, we show that two cortical systems uniquely reinstate the semantic content and temporal context of previously studied items during free recall. Examining either the posterior medial or anterior temporal networks, we find that forward encoding models trained on the brain's response to the temporal and semantic attributes of items can predict the serial position and semantic category of unseen items. During memory recall, these models uniquely link reinstatement of temporal context and semantic content to these posterior and anterior networks, respectively. These findings demonstrate how specialized cortical systems enable the human brain to target specific memories. People can search for memories based on their content or context, defined as when and where they were formed. Here, the authors use direct brain recordings to provide evidence in line with the idea that separable neural systems retrieve these two types of information and predict whether recall is organized by time or content. [ABSTRACT FROM AUTHOR]

Epilepsy is among one of the most common neurologic disorders. The role of magnetic resonance imaging (MRI) in the diagnosis and management of patients with epilepsy is well established, and most patients with epilepsy are likely to undergo at least one or more MRI examinations in the course of their disease. Recent advances in high-field MRI have enabled high resolution in vivo visualization of small and intricate anatomic structures that are of great importance in the assessment of seizure disorders. Familiarity with normal anatomic variations is essential in the accurate diagnosis and image interpretation, as these variations may be mistaken for epileptogenic foci, leading to unnecessary follow-up imaging, or worse, unnecessary treatment. After a brief overview of normal imaging anatomy of the mesial temporal lobe, this article will review a few important common and uncommon anatomic variations, mimics, and pitfalls that may be encountered in the imaging evaluation of patients with epilepsy. [ABSTRACT FROM AUTHOR]

A case of a true dual-genotype IDH-mutant oligoastrocytoma with two different cell types within a single mass in a young woman is presented. Imaging findings of the left frontal infiltrating glioma predicted the two neoplastic components that were identified upon resection. Tissue examination demonstrated areas of tumor with contrasting histologic and molecular features, including specific IDH1, ATRX, TP53, TERT and CIC mutational profiles, consistent with oligodendroglioma and astrocytoma, respectively. The clinical and radiological course over 17 months from first diagnosis included three surgical resections with slow progression of the astrocytic component, and ultimately chemotherapy and radiation treatments were commenced. Reports of the clinical courses for these rare cases of dual-genotype oligoastrocytomas will inform therapy choices, to optimize benefit while minimizing side effects. The steadily increasing number of cases suggests that the neoplasm might be reconsidered as an official entity by the WHO. [ABSTRACT FROM AUTHOR]

Background and Purpose: This study's purpose is to correlate location and metabolic activity of developmental venous anomalies (DVAs) in epilepsy patients to the seizure focus as determined by ictal/interictal encephaloelectrogram (EEG).Methods: A retrospective search was performed for epilepsy patients with DVAs who underwent brain 18 F-fluorodeoxyglucose positron emission tomography (18 F-FDG-PET) and magnetic resonance imaging (MRI). MRI exams were analyzed to characterize DVA location and associated structural findings. MRI and PET images were co-registered and assessment of 18 F-FDG uptake in the DVA territory was performed. The electronic medical record was reviewed for each subject to determine seizure semiology and site of seizure focus by ictal/interictal EEG.Results: Twenty-eight DVAs in 25 patients were included. Twelve DVAs demonstrated regional metabolic abnormality on 18 F-FDG-PET. There was no significant correlation between DVA site and seizure focus on EEG. DVA location was concordant with EEG seizure focus in three subjects, and all three demonstrated hypometabolism on 18 F-FDG-PET. This significance remains indeterminate, as one of these DVAs was associated with cavernoma, which could serve as the true seizure focus, and one of the patients underwent resection of the DVA without decrease in seizure frequency. Furthermore, there was no statistically significant relationship between DVA metabolic activity and DVA-EEG lobar or laterality concordance.Conclusions: In this sample, there is no significant correlation between location of DVA and seizure focus, and hypometabolism within the DVA territory is not predictive of EEG/DVA co-localization. As use of 18 F-FDG-PET for evaluation of epilepsy increases, knowledge of this poor correlation is important to avoid diagnostic confusion and potentially unnecessary surgery in epilepsy patients. [ABSTRACT FROM AUTHOR]

Based on rodent models, researchers have theorized that the hippocampus supports episodic memory and navigation via the theta oscillation, a ~4–10 Hz rhythm that coordinates brainwide neural activity. However, recordings from humans have indicated that hippocampal theta oscillations are lower in frequency and less prevalent than in rodents, suggesting interspecies differences in theta’s function. To characterize human hippocampal theta, we examine the properties of theta oscillations throughout the anterior–posterior length of the hippocampus as neurosurgical subjects performed a virtual spatial navigation task. During virtual movement, we observe hippocampal oscillations at multiple frequencies from 2 to 14 Hz. The posterior hippocampus prominently displays oscillations at ~8-Hz and the precise frequency of these oscillations correlates with the speed of movement, implicating these signals in spatial navigation. We also observe slower ~3 Hz oscillations, but these signals are more prevalent in the anterior hippocampus and their frequency does not vary with movement speed. Our results converge with recent findings to suggest an updated view of human hippocampal electrophysiology. Rather than one hippocampal theta oscillation with a single general role, high- and low-frequency theta oscillations, respectively, may reflect spatial and non-spatial cognitive processes. [ABSTRACT FROM AUTHOR]

Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so. [ABSTRACT FROM AUTHOR]

How does the human brain's structural scaffold give rise to its intricate functional dynamics? This is a central question in translational neuroscience that is particularly relevant to epilepsy, a disorder affecting over 50 million subjects worldwide. Treatment for medication-resistant focal epilepsy is often structural-through surgery or laser ablation-but structural targets, particularly in patients without clear lesions, are largely based on functional mapping via intracranial EEG. Unfortunately, the relationship between structural and functional connectivity in the seizing brain is poorly understood. In this study, we quantify structure-function coupling, specifically between white matter connections and intracranial EEG, across pre-ictal and ictal periods in 45 seizures from nine patients with unilateral drug-resistant focal epilepsy. We use high angular resolution diffusion imaging (HARDI) tractography to construct structural connectivity networks and correlate these networks with time-varying broadband and frequency-specific functional networks derived from coregistered intracranial EEG. Across all frequency bands, we find significant increases in structure-function coupling from pre-ictal to ictal periods. We demonstrate that short-range structural connections are primarily responsible for this increase in coupling. Finally, we find that spatiotemporal patterns of structure-function coupling are highly stereotyped for each patient. These results suggest that seizures harness the underlying structural connectome as they propagate. Mapping the relationship between structural and functional connectivity in epilepsy may inform new therapies to halt seizure spread, and pave the way for targeted patient-specific interventions. [ABSTRACT FROM AUTHOR]

Mesial temporal lobe epilepsy (TLE) is a common neurological disorder affecting the hippocampus and surrounding medial temporal lobe (MTL). Although prior studies have analyzed whole‐brain network distortions in TLE patients, the functional network architecture of the MTL at the subregion level has not been examined. In this study, we utilized high‐resolution 7T T2‐weighted magnetic resonance imaging (MRI) and resting‐state BOLD‐fMRI to characterize volumetric asymmetry and functional network asymmetry of MTL subregions in unilateral medically refractory TLE patients and healthy controls. We subdivided the TLE group into mesial temporal sclerosis patients (TLE‐MTS) and MRI‐negative nonlesional patients (TLE‐NL). Using an automated multi‐atlas segmentation pipeline, we delineated 10 MTL subregions per hemisphere for each subject. We found significantly different patterns of volumetric asymmetry between the two groups, with TLE‐MTS exhibiting volumetric asymmetry corresponding to decreased volumes ipsilaterally in all hippocampal subfields, and TLE‐NL exhibiting no significant volumetric asymmetries other than a mild decrease in whole‐hippocampal volume ipsilaterally. We also found significantly different patterns of functional network asymmetry in the CA1 subfield and whole hippocampus, with TLE‐NL patients exhibiting asymmetry corresponding to increased connectivity ipsilaterally and TLE‐MTS patients exhibiting asymmetry corresponding to decreased connectivity ipsilaterally. Our findings provide initial evidence that functional neuroimaging‐based network properties within the MTL can distinguish between TLE subtypes. High‐resolution MRI has potential to improve localization of underlying brain network disruptions in TLE patients who are candidates for surgical resection. [ABSTRACT FROM AUTHOR]

Spontaneous internal carotid artery dissection occurs in patients of all ages, rarely presenting with hypoglossal nerve palsy. The characteristic imaging findings of internal carotid artery dissection and tongue denervation are reviewed in four patients. Recognition of internal carotid artery dissection is critical for appropriate treatment and to minimise the risk of thromboembolic–ischaemic complications. Radiologists must be aware of the radiological appearance of hypoglossal nerve palsy and maintain a high index of suspicion for internal carotid artery dissection when this finding is present. [ABSTRACT FROM AUTHOR]

ITK-SNAP is an interactive software tool for manual and semi-automatic segmentation of 3D medical images. This paper summarizes major new features added to ITK-SNAP over the last decade. The main focus of the paper is on new features that support semi-automatic segmentation of multi-modality imaging datasets, such as MRI scans acquired using different contrast mechanisms (e.g., T1, T2, FLAIR). The new functionality uses decision forest classifiers trained interactively by the user to transform multiple input image volumes into a foreground/background probability map; this map is then input as the data term to the active contour evolution algorithm, which yields regularized surface representations of the segmented objects of interest. The new functionality is evaluated in the context of high-grade and low-grade glioma segmentation by three expert neuroradiogists and a non-expert on a reference dataset from the MICCAI 2013 Multi-Modal Brain Tumor Segmentation Challenge (BRATS). The accuracy of semi-automatic segmentation is competitive with the top specialized brain tumor segmentation methods evaluated in the BRATS challenge, with most results obtained in ITK-SNAP being more accurate, relative to the BRATS reference manual segmentation, than the second-best performer in the BRATS challenge; and all results being more accurate than the fourth-best performer. Segmentation time is reduced over manual segmentation by 2.5 and 5 times, depending on the rater. Additional experiments in interactive placenta segmentation in 3D fetal ultrasound illustrate the generalizability of the new functionality to a different problem domain. [ABSTRACT FROM AUTHOR]

The entorhinal cortex contains a network of grid cells that play a fundamental part in the brain's spatial system, supporting tasks such as path integration and spatial memory. In rodents, grid cells are thought to rely on network theta oscillations, but such signals are not evident in all species, challenging our understanding of the physiological basis of the grid network. We analyzed intracranial recordings from neurosurgical patients during virtual navigation to identify oscillatory characteristics of the human entorhinal grid network. The power of entorhinal theta oscillations showed six-fold modulation according to the virtual heading during navigation, which is a hypothesized signature of grid representations. Furthermore, modulation strength correlated with spatial memory performance. These results demonstrate the connection between theta oscillations and the human entorhinal grid network and show that features of grid-like neuronal representations can be identified from population electrophysiological recordings. [ABSTRACT FROM AUTHOR]

The hippocampus plays a vital role in various aspects of cognition including both memory and spatial navigation. To understand electrophysiologically how the hippocampus supports these processes, we recorded intracranial electroencephalographic activity from 46 neurosurgical patients as they performed a spatial memory task. We measure signals from multiple brain regions, including both left and right hippocampi, and we use spectral analysis to identify oscillatory patterns related to memory encoding and navigation. We show that in the left but not right hippocampus, the amplitude of oscillations in the 1–3-Hz “low theta” band increases when viewing subsequently remembered object–location pairs. In contrast, in the right but not left hippocampus, low-theta activity increases during periods of navigation. The frequencies of these hippocampal signals are slower than task-related signals in the neocortex. These results suggest that the human brain includes multiple lateralized oscillatory networks that support different aspects of cognition. [ABSTRACT FROM AUTHOR]

Abstract: The ability to produce nanotherapeutics at large‐scale with high drug loading efficiency, high drug loading capacity, high stability, and high potency is critical for clinical translation. However, many nanoparticle‐based therapeutics under investigation suffer from complicated synthesis, poor reproducibility, low stability, and high cost. In this work, a simple method for preparing multifunctional nanoparticles is utilized that act as both a contrast agent for magnetic resonance imaging and a photosensitizer for photodynamic therapy for the treatment of cancer. In particular, the photosensitizer protoporphyrin IX (PpIX) is used to solubilize small nanoclusters of superparamagnetic iron oxide nanoparticles (SPIONs) without the use of any additional carrier materials. These nanoclusters are characterized with a high PpIX loading efficiency; a high loading capacity, stable behavior; high potency; and a synthetic approach that is amenable to large‐scale production. In vivo studies of photodynamic therapy (PDT) efficacy show that the PpIX‐coated SPION nanoclusters lead to a significant reduction in the growth rate of tumors in a syngeneic murine tumor model compared to both free PpIX and PpIX‐loaded poly(ethylene glycol)‐polycaprolactone micelles, even when injected at 1/8th the dose. These results suggest that the nanoclusters developed in this work can be a promising nanotherapeutic for clinical translation. [ABSTRACT FROM AUTHOR]

Direct electrical stimulation of the human brain can elicit sensory and motor perceptions as well as recall of memories. Stimulating higher order association areas of the lateral temporal cortex in particular was reported to activate visual and auditory memory representations of past experiences (Penfield and Perot, 1963). We hypothesized that this effect could be used to modulate memory processing. Recent attempts at memory enhancement in the human brain have been focused on the hippocampus and other mesial temporal lobe structures, with a few reports of memory improvement in small studies of individual brain regions. Here, we investigated the effect of stimulation in four brain regions known to support declarative memory: hippocampus, parahippocampal neocortex, prefrontal cortex and temporal cortex. Intracranial electrode recordings with stimulation were used to assess verbal memory performance in a group of 22 patients (nine males). We show enhanced performance with electrical stimulation in the lateral temporal cortex (paired t-test, P = 0.0067), but not in the other brain regions tested. This selective enhancement was observed both on the group level, and for two of the four individual subjects stimulated in the temporal cortex. This study shows that electrical stimulation in specific brain areas can enhance verbal memory performance in humans.awx373media15704855796001. [ABSTRACT FROM AUTHOR]

Environmental boundaries play a crucial role in spatial navigation and memory across a wide range of distantly-related species. In rodents, boundary representations have been identified at the single-cell level in the subiculum and entorhinal cortex of the hippocampal formation. While studies of hippocampal function and spatial behavior suggest that similar representations might exist in humans, boundary-related neural activity has not been identified electrophysiologically in humans until now. To address this gap in the literature, we analyzed intracranial recordings from the hippocampal formation of surgical epilepsy patients (of both sexes) while they performed a virtual spatial navigation task and compared the power in three frequency bands (1-4 Hz, 4-10 Hz, 30-90 Hz) for target locations near and far from the environmental boundaries. Our results suggest that encoding locations near boundaries elicited stronger theta oscillations than for target locations near the center of the environment and that this difference cannot be explained by variables such as trial length, speed, movement, or performance. These findings provide direct evidence of boundary-dependent neural activity localized in humans to the subiculum, the homologue of the hippocampal subregion in which most boundary cells are found in rodents, and indicate that this system can represent attended locations that rather than the position of one's own body. [ABSTRACT FROM AUTHOR]

Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction. [ABSTRACT FROM AUTHOR]

Abstract: Medial temporal lobe (MTL) subregions play integral roles in memory function and are differentially affected in various neurological and psychiatric disorders. The ability to structurally and functionally characterize these subregions may be important to understanding MTL physiology and diagnosing diseases involving the MTL. In this study, we characterized network architecture of the MTL in healthy subjects (n = 31) using both resting state functional MRI and MTL‐focused T2‐weighted structural MRI at 7 tesla. Ten MTL subregions per hemisphere, including hippocampal subfields and cortical regions of the parahippocampal gyrus, were segmented for each subject using a multi‐atlas algorithm. Both structural covariance matrices from correlations of subregion volumes across subjects, and functional connectivity matrices from correlations between subregion BOLD time series were generated. We found a moderate structural and strong functional inter‐hemispheric symmetry. Several bilateral hippocampal subregions (CA1, dentate gyrus, and subiculum) emerged as functional network hubs. We also observed that the structural and functional networks naturally separated into two modules closely corresponding to (a) bilateral hippocampal formations, and (b) bilateral extra‐hippocampal structures. Finally, we found a significant correlation in structural and functional connectivity (r = 0.25). Our findings represent a comprehensive analysis of network topology of the MTL at the subregion level. We share our data, methods, and findings as a reference for imaging methods and disease‐based research. [ABSTRACT FROM AUTHOR]

Behavioral and neurophysiological evidence suggests that the slow (≤1 Hz) oscillation (SO) during sleep plays a role in consolidating hippocampal (HIPP)-dependent memories. The effects of the SO on HIPP activity have been studied in rodents and cats both during natural sleep and during anesthetic administration titrated to mimic sleep-like slow rhythms. In this study, we sought to document these effects in primates. First, HIPP field potentials were recorded during ketamine-dexmedetomidine sedation and during natural sleep in three rhesus macaques. Sedation produced regionally-specific slow and gamma (∼40 Hz) oscillations with strong coupling between the SO phase and gamma amplitude. These same features were seen in slow-wave sleep (SWS), but the coupling was weaker and the coupled gamma oscillation had a higher frequency (∼70 Hz) during SWS. Second, electrical stimuli were delivered to HIPP afferents in the parahippocampal gyrus (PHG) during sedation to assess the effects of sleep-like SO on excitability. Gamma bursts after the peak of SO cycles corresponded to periods of increased gain of monosynaptic connections between the PHG and HIPP. However, the two PHG-HIPP connectivity gains during sedation were both substantially lower than when the animal was awake. We conclude that the SO is correlated with rhythmic excitation and inhibition of the PHG-HIPP network, modulating connectivity and gamma generators intrinsic to this network. Ketamine-dexmedetomidine sedation produces a similar effect, but with a decreased contribution of the PHG to HIPP activity and gamma generation. [ABSTRACT FROM AUTHOR]

Gamma frequency activity (30-150 Hz) is induced in cognitive tasks and is thought to reflect underlying neural processes. Gamma frequency activity can be recorded directly from the human brain using intracranial electrodes implanted in patients undergoing treatment for drug-resistant epilepsy. Previous studies have independently explored narrowband oscillations in the local field potential and broadband power increases. It is not clear, however, which processes contribute to human brain gamma frequency activity, or their dynamics and roles during memory processing. Here a large dataset of intracranial recordings obtained during encoding of words from 101 patients was used to detect, characterize and compare induced gamma frequency activity events. Individual bursts of gamma frequency activity were isolated in the time-frequency domain to determine their spectral features, including peak frequency, amplitude, frequency span, and duration. We found two distinct types of gamma frequency activity events that showed either narrowband or broadband frequency spans revealing characteristic spectral properties. Narrowband events, the predominant type, were induced by word presentations following an initial induction of broadband events, which were temporally separated and selectively correlated with evoked response potentials, suggesting that they reflect different neural activities and play different roles during memory encoding. The two gamma frequency activity types were differentially modulated during encoding of subsequently recalled and forgotten words. In conclusion, we found evidence for two distinct activity types induced in the gamma frequency range during cognitive processing. Separating these two gamma frequency activity components contributes to the current understanding of electrophysiological biomarkers, and may prove useful for emerging neurotechnologies targeting, mapping and modulating distinct neurophysiological processes in normal and epileptogenic brain. [ABSTRACT FROM AUTHOR]

Objectives Interictal epileptiform discharges ( IEDs) have been linked to memory impairment, but the spatial and temporal dynamics of this relationship remain elusive. In the present study, we aim to systematically characterize the brain areas and times at which IEDs affect memory. Methods Eighty epilepsy patients participated in a delayed free recall task while undergoing intracranial electroencephalography ( EEG) monitoring. We analyzed the locations and timing of IEDs relative to the behavioral data in order to measure their effects on memory. Results Overall IED rates did not correlate with task performance across subjects (r = 0.03, p = 0.8). However, at a finer temporal scale, within-subject memory was negatively affected by IEDs during the encoding and recall periods of the task but not during the rest and distractor periods (p < 0.01, p < 0.001, p = 0.3, and p = 0.8, respectively). The effects of IEDs during encoding and recall were stronger in the left hemisphere than in the right (p < 0.05). Of six brain areas analyzed, IEDs in the inferior-temporal, medial-temporal, and parietal areas significantly affected memory (false discovery rate < 0.05). Significance These findings reveal a network of brain areas sensitive to IEDs with key nodes in temporal as well as parietal lobes. They also demonstrate the time-dependent effects of IEDs in this network on memory. [ABSTRACT FROM AUTHOR]

ABSTRACT Human theta (4−8 Hz) activity in the medial temporal lobe correlates with memory formation; however, the precise role that theta plays in the memory system remains elusive (Hanslmayr and Staudigl, ). Recently, prestimulus theta activity has been associated with successful memory formation, although its specific cognitive role remains unknown (e.g., Fell et al., 2011). In this report, we demonstrate that prestimulus theta in the hippocampus indexes encoding that supports old-new recognition memory but not recall. These findings suggest that human hippocampal prestimulus theta may preferentially participate in the encoding of item information, as opposed to associative information. © 2014 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

The dsRNA-binding protein Staufen was the first RNA-binding protein proven to play a role in RNA localization in Drosophila. A mammalian homolog, Staufen1 (Stau1), has been implicated in dendritic RNA localization in neurons, translational control, and mRNA decay. However, the precise mechanisms by which it fulfills these specific roles are only partially understood. To determine its physiological functions, the murine Stau1 gene was disrupted by homologous recombination. Homozygous stau1tm1Apa mutant mice express a truncated Stau1 protein lacking the functional RNA-binding domain 3. The level of the truncated protein is significantly reduced. Cultured hippocampal neurons derived from stau1tm1Apa homozygous mice display deficits in dendritic delivery of Stau1-EYFP and β-actin mRNA-containing ribonucleoprotein particles (RNPs). Furthermore, these neurons have a significantly reduced dendritic tree and develop fewer synapses. Homozygous stau1tm1Apa mutant mice are viable and show no obvious deficits in development, fertility, health, overall brain morphology, and a variety of behavioral assays, e.g., hippocampus-dependent learning. However, we did detect deficits in locomotor activity. Our data suggest that Stau1 is crucial for synapse development in vitro but not critical for normal behavioral function. [ABSTRACT FROM AUTHOR]

Histone deacetylase (HDAC) inhibitors increase histone acetylation and enhance both memory and synaptic plasticity. The current model for the action of HDAC inhibitors assumes that they alter gene expression globally and thus affect memory processes in a nonspecific manner. Here, we show that the enhancement of hippocampus-dependent memory and hippocampal synaptic plasticity by HDAC inhibitors is mediated by the transcription factor cAMP response element-binding protein (CREB) and the recruitment of the transcriptional coactivator and histone acetyltransferase CREB-binding protein (CBP) via the CREB-binding domain of CBP. Furthermore, we show that the HDAC inhibitor trichostatin A does not globally alter gene expression but instead increases the expression of specific genes during memory consolidation. Our results suggest that HDAC inhibitors enhance memory processes by the activation of key genes regulated by the CREB:CBP transcriptional complex. [ABSTRACT FROM AUTHOR]

Synapse-specific local protein synthesis is thought to be important for neurodevelopment and plasticity and involves neuronal RNA binding proteins that regulate the transport and translation of dendritically localized transcripts. The best characterized of these RNA binding proteins is the fragile X mental retardation protein (FMRP). Mutations affecting the expression or function of FMRP cause fragile X syndrome in humans, and targeted deletion of the gene encoding FMRP results in developmental and behavioral alterations in mice. Translin is an RNA-binding protein that regulates mRNA transport and translation in mouse male germ cells and is proposed to play a similar role in neurons. Like FMRP, translin is present in neuronal dendrites, binds dendritically localized RNA, and associates with microtubules and motor proteins. We reported previously the production of viable homozygous translin knock-out mice, which demonstrate altered expression of multiple mRNA transcripts in the brain and mild motor impairments. Here, we report that translin knock-out mice also exhibit sex-specific differences in tests of learning and memory, locomotor activity, anxiety-related behavior, and sensorimotor gating, as well as handling-induced seizures and alterations in monoamine neurotransmitter levels in several forebrain regions. Similar behavioral and neurochemical alterations have been observed in mice lacking FMRP, suggesting that both proteins may act within the same neuronal systems and signaling pathways. Our results in mice indicate that mutations in translin may contribute to fragile X-like syndromes, mental retardation, attention deficit hyperactivity disorder, epilepsy, and autism spectrum disorders in humans. [ABSTRACT FROM AUTHOR]

Testis-brain RNA-binding protein (TB-RBP), the mouse orthologue of the human protein Translin, is a widely expressed and highly conserved protein with proposed functions in chromosomal translocations, mitotic cell division, and mRNA transport and storage. To better define the biological roles of TB-RBP, we generated mice lacking TB-RBP. Matings between heterozygotes gave rise to viable, apparently normal homozygous mutant mice at a normal Mendelian ratio. The TB-RBP-related and -interacting protein Translin-associated factor X was reduced to 50% normal levels in heterozygotes and was absent in TB-RBP-null animals. The null mice were 10 to 30% smaller than their wild-type or heterozygote littermates at birth and remained so to about 6 to 9 months of age, showed normal B- and T-cell development, and accumulated visceral fat. TB-RBP-null male mice were fertile and sired offspring but had abnormal seminiferous tubules and reduced sperm counts. Null female mice were subfertile and had reduced litter sizes. Microarray analysis of total brain RNA from null and wild-type mice revealed an altered gene expression profile with the up-regulation of 14 genes and the down-regulation of 217 genes out of 12,473 probe sets. Numerous neurotransmitter receptors and ion channels, including γ-aminobutyric acid A receptor α1 and glutamate receptor α3, were strongly down-regulated. Behavioral abnormalities were also seen. Compared to littermates, the TB-RBP-null mice appeared docile and exhibited reduced Rota-Rod performance. [ABSTRACT FROM AUTHOR]

Optimizing direct electrical stimulation for the treatment of neurological disease remains difficult due to an incomplete understanding of its physical propagation through brain tissue. Here, we use network control theory to predict how stimulation spreads through white matter to influence spatially distributed dynamics. We test the theory's predictions using a unique dataset comprising diffusion weighted imaging and electrocorticography in epilepsy patients undergoing grid stimulation. We find statistically significant shared variance between the predicted activity state transitions and the observed activity state transitions. We then use an optimal control framework to posit testable hypotheses regarding which brain states and structural properties will efficiently improve memory encoding when stimulated. Our work quantifies the role that white matter architecture plays in guiding the dynamics of direct electrical stimulation and offers empirical support for the utility of network control theory in explaining the brain's response to stimulation. • Tools from network control theory are extended to model empirical brain stimulation • A model of stimulation spreading along axon bundles predicts changes in activity • The model posits how brain activity and connectivity facilitate targeted stimulation Stiso et al. report evidence that network control theory can explain the propagation of electrical stimulation through the human brain and quantify how white matter connectivity is crucial for driving spatially distributed changes in activity. Furthermore, they use network control theory to predict stimulation outcome in specific cognitive contexts. [ABSTRACT FROM AUTHOR]

Photodynamic therapy (PDT) is an approved modality for the treatment of various types of maligancies and diseased states. However, most of the available photosensitizers (PS) are highly hydrophobic, which limits their solubility and dispersion in biological fluids and can lead to self-quenching and sub-optimal therapeutic efficacy. In this study, chlorin e6 (Ce6)-coated superparamagnetic iron oxide nanoparticle (SPION) nanoclusters (Ce6-SCs) were prepared via an oil-in-water emulsion. The physical-chemical properties of the Ce6-SCs were systematically evaluated. Dual-mode imaging and PDT was subsequently performed in tumor-bearing mice. Chlorin e6 is capable of solubilizing hydrophobic SPION into stable, water-soluble nanoclusters without the use of any additional amphiphiles or carriers. The method is reproducible and the Ce6-SCs are highly stable under physiological conditions. The Ce6-SCs have an average diameter of 92 nm and low polydispersity (average PDI < 0.2). Encapsulation efficiency of both Ce6 and SPION is ≈100%, and the total Ce6 payload can be as high as 56% of the total weight (Ce6 + Fe). The Ce6-SCs localize within tumors via enhanced permeability and retention and are detectable by magnetic resonance (MR) and optical imaging. With PDT, Ce6-SCs demonstrate high singlet oxygen generation and produce a significant delay in tumor growth in mice. [ABSTRACT FROM AUTHOR]