Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations.

We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution in vivo MR imaging and detailed segmentations previously possible only in histological preparations. Here, we present and evaluate the first step of this initiative: a comprehensive dataset of two healthy male volunteers reconstructed to a 0.25 mm isotropic resolution for T1w, T2w, and DWI contrasts. Multiple high-resolution acquisitions were collected for each contrast and each participant, followed by averaging using symmetric group-wise normalisation (Advanced Normalisation Tools). The resulting image quality permits structural parcellations rivalling histology-based atlases, while maintaining the advantages of in vivo MRI. For example, components of the thalamus, hypothalamus, and hippocampus are often impossible to identify using standard MRI protocols-can be identified within the present data. Our data are virtually distortion free, fully 3D, and compatible with the existing in vivo Neuroimaging analysis tools. The dataset is suitable for teaching and is publicly available via our website (hba.neura.edu.au), which also provides data processing scripts. Instead of focusing on coordinates in an averaged brain space, our approach focuses on providing an example segmentation at great detail in the high-quality individual brain. This serves as an illustration on what features contrasts and relations can be used to interpret MRI datasets, in research, clinical, and education settings.

Cannabidiol as a Treatment for Neurobiological, Behavioral, and Psychological Symptoms in Early-Stage Dementia: A Double-Blind, Placebo-Controlled Clinical Trial Protocol.

Rationale: The slowing of disease progression in dementia in the early stages of diagnosis is paramount to improving the quality of life for those diagnosed and their support networks. Accumulating evidence suggests that CBD, a constituent of Cannabis sativa, is associated with neuroprotective, neuroendocrine, and psychotherapeutic effects, suggesting that it may be beneficial to dementia treatment. However, no published human study to date has examined this possibility. This trial aims to determine whether daily treatment with CBD over a 12-week period is associated with improved neurobiological, behavioral, and psychological outcomes in individuals living with early-stage dementia. Methods: Sixty participants with early-stage dementia will be recruited for a randomized, double-blind, placebo-controlled clinical trial. Participants will be randomized into either 99.9% pure CBD or placebo treatment conditions and administered two capsules per day for 12 weeks. Participants will commence a 200 mg/day dose for 2 weeks before escalating to 300 mg/day for the remaining 10 weeks. Neuroimaging and blood-based neuroendocrine profiles will be assessed at baseline and post-treatment. Psychological and behavioral symptoms will be assessed at baseline, 6 weeks, and post-treatment. Monitoring of health and side-effects will be conducted through weekly home visits. Discussion: This study is among the first to investigate the effects of isolated CBD in improving neuroanatomical and neuroendocrine changes, alongside psychological symptoms, during the early stages of dementia diagnosis. The outcomes of this trial have the capacity to inform a potential novel and accessible treatment approach for individuals living with early-stage dementia, and in turn, improve quality of life, prognoses, and treatment outcomes. Trial Registration: This trial has been registered with the Therapeutic Goods Administration (CT-2020-CTN-03849-1v2) and the Australian and New Zealand Clinical Trials Registry (ACTRN12621001364864).

Nature in motion: The tuning of the visual system to the spatiotemporal properties of natural scenes.

Natural scenes contain several statistical regularities despite their superficially diverse appearances (e.g., mountains, rainforests, deserts). First, they exhibit a unique distribution of luminance intensities decreasing across spatial frequency, known as the 1/fα amplitude spectrum (α ≈ 1). Additionally, natural scenes share consistent geometric properties, comprising similar densities of structure across multiple scales-a property classifying them as fractal (e.g., how the branching patterns of rivers and trees appear similar irrespective of scale). These two properties are intimately related and correlate strongly in natural scenes. However, research using thresholded noise images suggests that spatially, the human visual system is preferentially tuned to natural scene structure more so than 1/fα spectra. It is currently unclear whether this dependency on natural geometry extends to the temporal domain. We used a psychophysics task to measure discrimination sensitivity toward two types of synthetic noise movies: gray scale and thresholded (N = 60). Each movie type shared the same geometric properties (measured fractal D), but substantially differing spectral properties (measured α). In both space and time, we observe a characteristic dependency on stimulus structure across movie types, with sensitivity peaking for stimuli with natural geometry despite having altered 1/fα spectra. Although only measured behaviorally, our findings may imply that the neural processes underlying this tuning have developed to be sensitive to the most stable signal in our natural environment-structure (e.g., the structural properties of a tree are consistent from morning to night despite illumination changes across time points).

Correcting Susceptibility Artifacts of MRI Sensors in Brain Scanning: A 3D Anatomy-Guided Deep Learning Approach.

Echo planar imaging (EPI), a fast magnetic resonance imaging technique, is a powerful tool in functional neuroimaging studies. However, susceptibility artifacts, which cause misinterpretations of brain functions, are unavoidable distortions in EPI. This paper proposes an end-to-end deep learning framework, named TS-Net, for susceptibility artifact correction (SAC) in a pair of 3D EPI images with reversed phase-encoding directions. The proposed TS-Net comprises a deep convolutional network to predict a displacement field in three dimensions to overcome the limitation of existing methods, which only estimate the displacement field along the dominant-distortion direction. In the training phase, anatomical T1-weighted images are leveraged to regularize the correction, but they are not required during the inference phase to make TS-Net more flexible for general use. The experimental results show that TS-Net achieves favorable accuracy and speed trade-off when compared with the state-of-the-art SAC methods, i.e., TOPUP, TISAC, and S-Net. The fast inference speed (less than a second) of TS-Net makes real-time SAC during EPI image acquisition feasible and accelerates the medical image-processing pipelines.

Nice and slow: Measuring sensitivity and visual preference toward naturalistic stimuli varying in their amplitude spectra in space and time.

The 1/fα amplitude spectrum is a statistical property of natural scenes characterising a specific distribution of spatial and temporal frequencies and their associated luminance intensities. This property has been studied extensively in the spatial domain whereby sensitivity and visual preference overlap and peak for slopes within the natural range (α ≈ 1), but remains relatively less studied in the temporal domain. Here, we used a 4AFC task to measure sensitivity and a 2AFC task to measure visual preference and across a wide range of spatial (α = 0.25, 1.25, 2.25) and temporal (α = 0.25 to 2.50, step size: 0.25) slope conditions. Stimuli with a shallow temporal slope modulate rapidly (e.g. 0.25), whereas stimuli with a steep slope modulate slowly (e.g. 2.25). Interestingly, sensitivity and visual preference did not closely overlap. While the sensitivity of the visual system is highest for our stimulus with an intermediate modulation rate (1.25), which is most abundant in nature, the stimulus with the slowest modulation rate (2.25) was most preferred. It seems sensible for the visual system to be sensitive to spatiotemporal spectra that most commonly exist in nature (α ≈ 1). However, it is possible that preference might be related to what these properties signal in the natural world. Consider the cases of waves slowly vs. rapidly crashing on a beach or fast vs. slow animals. In both instances the slowest option is often the safest and preferential, suggesting that the temporal 1/fα amplitude spectrum provides additional information that may indicate preferred environmental conditions.

The impact of self-control training on neural responses following anger provocation.

Self-control training (SCT) is one way to enhance self-controlled behavior. We conducted a novel and exploratory functional magnetic resonance imaging experiment to examine how SCT affects neural responses in a situation that elicits a self-control response: anger provocation. Forty-five healthy young men and women completed two-weeks of SCT or a behavioral monitoring task and were then insulted during scanning. We found significant changes in functional activation and connectivity using a lenient error threshold, which were not observed using a stricter threshold. Activation in the posterior insula was greater for the control compared to the SCT group at post-provocation, trait aggression correlated with neural responses to SCT, and SCT was associated with specific amygdala-cortical connections. Neural changes occurred even though SCT did not affect participants' performance on an inhibition task, reports of trying to control their anger, or their experience of anger. This dissociation prevented clear interpretation about whether the neural changes were indicative of specific anger or anger control processes. Although replication with high-powered studies is needed, we provide evidence that SCT affects neural responses in the context of anger provocation.

Manipulating the structure of natural scenes using wavelets to study the functional architecture of perceptual hierarchies in the brain.

Functional neuroimaging experiments that employ naturalistic stimuli (natural scenes, films, spoken narratives) provide insights into cognitive function "in the wild". Natural stimuli typically possess crowded, spectrally dense, dynamic, and multimodal properties within a rich multiscale structure. However, when using natural stimuli, various challenges exist for creating parametric manipulations with tight experimental control. Here, we revisit the typical spectral composition and statistical dependences of natural scenes, which distinguish them from abstract stimuli. We then demonstrate how to selectively degrade subtle statistical dependences within specific spatial scales using the wavelet transform. Such manipulations leave basic features of the stimuli, such as luminance and contrast, intact. Using functional neuroimaging of human participants viewing degraded natural images, we demonstrate that cortical responses at different levels of the visual hierarchy are differentially sensitive to subtle statistical dependences in natural images. This demonstration supports the notion that perceptual systems in the brain are optimally tuned to the complex statistical properties of the natural world. The code to undertake these stimulus manipulations, and their natural extension to dynamic natural scenes (films), is freely available.

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images.

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.

Feasibility of functional magnetic resonance imaging of ocular dominance and orientation preference in primary visual cortex.

A recent hemodynamic model is extended and applied to simulate and explore the feasibility of detecting ocular dominance (OD) and orientation preference (OP) columns in primary visual cortex by means of functional magnetic resonance imaging (fMRI). The stimulation entails a short oriented bar stimulus being presented to one eye and mapped to cortical neurons with corresponding OD and OP selectivity. Activated neurons project via patchy connectivity to excite other neurons with similar OP in nearby visual fields located preferentially along the direction of stimulus orientation. The resulting blood oxygen level dependent (BOLD) response is estimated numerically via the model's spatiotemporal hemodynamic response function. The results are then used to explore the feasibility of detecting spatial OD-OP modulation, either directly measuring BOLD or by using Wiener deconvolution to filter the image and estimate the underlying neural activity. The effect of noise is also considered and it is estimated that direct detection can be robust for fMRI resolution of around 0.5 mm, whereas detection with Wiener deconvolution is possible at a broader range from 0.125 mm to 1 mm resolution. The detection of OD-OP features is strongly dependent on hemodynamic parameters, such as low velocity and high damping reduce response spreads and result in less blurring. The short-bar stimulus that gives the most detectable response is found to occur when neural projections are at 45 relative to the edge of local OD boundaries, which provides a constraint on the OD-OP architecture even when it is not fully resolved.

Fine-Grained Mapping of Cortical Somatotopies in Chronic Complex Regional Pain Syndrome.

It has long been thought that severe chronic pain conditions, such as complex regional pain syndrome (CRPS), are not only associated with, but even maintained by a reorganization of the somatotopic representation of the affected limb in primary somatosensory cortex (S1). This notion has driven treatments that aim to restore S1 representations in CRPS patients, such as sensory discrimination training and mirror therapy. However, this notion is based on both indirect and incomplete evidence obtained with imaging methods with low spatial resolution. Here, we used fMRI to characterize the S1 representation of the affected and unaffected hand in humans (of either sex) with unilateral CRPS. The cortical area, location, and geometry of the S1 representation of the CRPS hand were largely comparable with those of both the unaffected hand and healthy controls. We found no differential relation between affected versus unaffected hand map measures and clinical measures (pain severity, upper limb disability, disease duration). Thus, if any map reorganization occurs, it does not appear to be directly related to pain and disease severity. These findings compel us to reconsider the cortical mechanisms underlying CRPS and the rationale for interventions that aim to "restore" somatotopic representations to treat pain.SIGNIFICANCE STATEMENT This study shows that the spatial map of the fingers in somatosensory cortex is largely preserved in chronic complex regional pain syndrome (CRPS). These findings challenge the treatment rationale for restoring somatotopic representations in complex regional pain syndrome patients.

The neural correlates of alcohol-related aggression.

Alcohol intoxication is implicated in approximately half of all violent crimes. Over the past several decades, numerous theories have been proposed to account for the influence of alcohol on aggression. Nearly all of these theories imply that altered functioning in the prefrontal cortex is a proximal cause. In the present functional magnetic resonance imaging (fMRI) experiment, 50 healthy young men consumed either a low dose of alcohol or a placebo and completed an aggression paradigm against provocative and nonprovocative opponents. Provocation did not affect neural responses. However, relative to sober participants, during acts of aggression, intoxicated participants showed decreased activity in the prefrontal cortex, caudate, and ventral striatum, but heightened activation in the hippocampus. Among intoxicated participants, but not among sober participants, aggressive behavior was positively correlated with activation in the medial and dorsolateral prefrontal cortex. These results support theories that posit a role for prefrontal cortical dysfunction as an important factor in intoxicated aggression.

The tuning of human visual cortex to variations in the 1/fα amplitude spectra and fractal properties of synthetic noise images.

Natural scenes share a consistent distribution of energy across spatial frequencies (SF) known as the 1/fα amplitude spectrum (α≈0.8-1.5, mean 1.2). This distribution is scale-invariant, which is a fractal characteristic of natural scenes with statistically similar structure at different spatial scales. While the sensitivity of the visual system to the 1/f properties of natural scenes has been studied extensively using psychophysics, relatively little is known about the tuning of cortical responses to these properties. Here, we use fMRI and retinotopic mapping techniques to measure and analyze BOLD responses in early visual cortex (V1, V2, and V3) to synthetic noise images that vary in their 1/fα amplitude spectra (α=0.25 to 2.25, step size: 0.50) and contrast levels (10% and 30%) (Experiment 1). To compare the dependence of the BOLD response between the photometric (intensity based) and geometric (fractal) properties of our stimuli, in Experiment 2 we compared grayscale noise images to their binary (thresholded) counterparts, which contain only black and white regions. In both experiments, early visual cortex responded maximally to stimuli generated to have an input 1/f slope corresponding to natural 1/fα amplitude spectra, and lower BOLD responses were found for steeper or shallower 1/f slopes (peak modulation: 0.59% for 1.25 vs. 0.31% for 2.25). To control for changing receptive field sizes, responses were also analyzed across multiple eccentricity bands in cortical surface space. For most eccentricity bands, BOLD responses were maximal for natural 1/fα amplitude spectra, but importantly there was no difference in the BOLD response to grayscale stimuli and their corresponding thresholded counterparts. Since the thresholding of an image changes its measured 1/f slope (α) but not its fractal characteristics, this suggests that neuronal responses in early visual cortex are not strictly driven by spectral slope values (photometric properties) but rather their embedded geometric, fractal-like scaling properties.

The spatiotemporal hemodynamic response function for depth-dependent functional imaging of human cortex.

The gray matter of human cortex is characterized by depth-dependent differences in neuronal activity and connections (Shipp, 2007) as well as in the associated vasculature (Duvernoy et al., 1981). The resolution limit of functional magnetic resonance imaging (fMRI) measurements is now below a millimeter, promising the non-invasive measurement of these properties in awake and behaving humans (Muckli et al., 2015; Olman et al., 2012; Ress et al., 2007). To advance this endeavor, we present a detailed spatiotemporal hemodynamic response function (HRF) reconstructed through the use of high-resolution, submillimeter fMRI. We decomposed the HRF into directions tangential and perpendicular to the cortical surface and found that key spatial properties of the HRF change significantly with depth from the cortical surface. Notably, we found that the spatial spread of the HRF increases linearly from 4.8mm at the gray/white matter boundary to 6.6mm near the cortical surface. Using a hemodynamic model, we posit that this effect can be explained by the depth profile of the cortical vasculature, and as such, must be taken into account to properly estimate the underlying neuronal responses at different cortical depths.

High-resolution In Vivo Manual Segmentation Protocol for Human Hippocampal Subfields Using 3T Magnetic Resonance Imaging.

The human hippocampus has been broadly studied in the context of memory and normal brain function and its role in different neuropsychiatric disorders has been heavily studied. While many imaging studies treat the hippocampus as a single unitary neuroanatomical structure, it is, in fact, composed of several subfields that have a complex three-dimensional geometry. As such, it is known that these subfields perform specialized functions and are differentially affected through the course of different disease states. Magnetic resonance (MR) imaging can be used as a powerful tool to interrogate the morphology of the hippocampus and its subfields. Many groups use advanced imaging software and hardware (>3T) to image the subfields; however this type of technology may not be readily available in most research and clinical imaging centers. To address this need, this manuscript provides a detailed step-by-step protocol for segmenting the full anterior-posterior length of the hippocampus and its subfields: cornu ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus (DG), strata radiatum/lacunosum/moleculare (SR/SL/SM), and subiculum. This protocol has been applied to five subjects (3F, 2M; age 29-57, avg. 37). Protocol reliability is assessed by resegmenting either the right or left hippocampus of each subject and computing the overlap using the Dice's kappa metric. Mean Dice's kappa (range) across the five subjects are: whole hippocampus, 0.91 (0.90-0.92); CA1, 0.78 (0.77-0.79); CA2/CA3, 0.64 (0.56-0.73); CA4/dentate gyrus, 0.83 (0.81-0.85); strata radiatum/lacunosum/moleculare, 0.71 (0.68-0.73); and subiculum 0.75 (0.72-0.78). The segmentation protocol presented here provides other laboratories with a reliable method to study the hippocampus and hippocampal subfields in vivo using commonly available MR tools.

Future challenges for vection research: definitions, functional significance, measures, and neural bases.

This paper discusses four major challenges facing modern vection research. Challenge 1 (Defining Vection) outlines the different ways that vection has been defined in the literature and discusses their theoretical and experimental ramifications. The term vection is most often used to refer to visual illusions of self-motion induced in stationary observers (by moving, or simulating the motion of, the surrounding environment). However, vection is increasingly being used to also refer to non-visual illusions of self-motion, visually mediated self-motion perceptions, and even general subjective experiences (i.e., "feelings") of self-motion. The common thread in all of these definitions is the conscious subjective experience of self-motion. Thus, Challenge 2 (Significance of Vection) tackles the crucial issue of whether such conscious experiences actually serve functional roles during self-motion (e.g., in terms of controlling or guiding the self-motion). After more than 100 years of vection research there has been surprisingly little investigation into its functional significance. Challenge 3 (Vection Measures) discusses the difficulties with existing subjective self-report measures of vection (particularly in the context of contemporary research), and proposes several more objective measures of vection based on recent empirical findings. Finally, Challenge 4 (Neural Basis) reviews the recent neuroimaging literature examining the neural basis of vection and discusses the hurdles still facing these investigations.

Derivation of high-resolution MRI atlases of the human cerebellum at 3T and segmentation using multiple automatically generated templates.

The cerebellum has classically been linked to motor learning and coordination. However, there is renewed interest in the role of the cerebellum in non-motor functions such as cognition and in the context of different neuropsychiatric disorders. The contribution of neuroimaging studies to advancing understanding of cerebellar structure and function has been limited, partly due to the cerebellum being understudied as a result of contrast and resolution limitations of standard structural magnetic resonance images (MRI). These limitations inhibit proper visualization of the highly compact and detailed cerebellar foliations. In addition, there is a lack of robust algorithms that automatically and reliably identify the cerebellum and its subregions, further complicating the design of large-scale studies of the cerebellum. As such, automated segmentation of the cerebellar lobules would allow detailed population studies of the cerebellum and its subregions. In this manuscript, we describe a novel set of high-resolution in vivo atlases of the cerebellum developed by pairing MR imaging with a carefully validated manual segmentation protocol. Using these cerebellar atlases as inputs, we validate a novel automated segmentation algorithm that takes advantage of the neuroanatomical variability that exists in a given population under study in order to automatically identify the cerebellum, and its lobules. Our automatic segmentation results demonstrate good accuracy in the identification of all lobules (mean Kappa [κ]=0.731; range 0.40-0.89), and the entire cerebellum (mean κ=0.925; range 0.90-0.94) when compared to "gold-standard" manual segmentations. These results compare favorably in comparison to other publically available methods for automatic segmentation of the cerebellum. The completed cerebellar atlases are available freely online (http://imaging-genetics.camh.ca/cerebellum) and can be customized to the unique neuroanatomy of different subjects using the proposed segmentation pipeline (https://github.com/pipitone/MAGeTbrain).

A functional polymorphism of the MAOA gene is associated with neural responses to induced anger control.

Aggressiveness is highly heritable. Recent experimental work has linked individual differences in a functional polymorphism of the monoamine oxidase-A gene (MAOA) to anger-driven aggression. Other work has implicated the dorsal ACC (dACC) in cognitive-emotional control and the amygdala in emotional arousal. The present imaging genetics study investigated dACC and amygdala reactivity to induced anger control as a function of MAOA genotype. A research assistant asked 38 healthy male undergraduates to control their anger in response to an insult by a rude experimenter. Men with the low-expression allele showed increased dACC and amygdala activation after the insult, but men with the high-expression allele did not. Both dACC and amygdala activation independently mediated the relationship between MAOA genotype and self-reported anger control. Moreover, following the insult, men with the high-functioning allele showed functional decoupling between the amygdala and dACC, but men with the low-functioning allele did not. These results suggest that heightened dACC and amygdala activation and their connectivity are neuroaffective mechanisms underlying anger control in participants with the low-functioning allele of the MAOA gene.

A novel in vivo atlas of human hippocampal subfields using high-resolution 3 T magnetic resonance imaging.

The hippocampus is a neuroanatomical structure that has been widely studied in the context of learning, memory, stress, and neurodegeneration. Neuroanatomically, the hippocampus is subdivided into several subfields with intricate morphologies and complex three-dimensional relationships. Recent studies have demonstrated that the identification of different subfields is possible with high-resolution and -contrast image volumes acquired using ex vivo specimens in a small bore 9.4 T scanner and, more recently, in vivo, at 7 T. In these studies, the neuroanatomical definitions of boundaries between subfields are based upon salient differences in image contrast. Typically, the definition of subfields has not been possible using commonly available magnetic resonance (MR) scanners (i.e.: 1.5 or 3T) due to resolution and contrast limitations. To overcome the limited availability of post-mortem specimens and expertise in state-of-the-art high-field imaging, we propose a coupling of MR acquisition and detailed segmentation techniques that allow for the reliable identification of hippocampal anatomy (including subfields). High-resolution and -contrast T1- and T2-weighted image volumes were acquired from 5 volunteers (2 male; 3 female; age range: 29-57, avg. 37) using a clinical research-grade 3T scanner and have final super-sampled isotropic voxel dimensions of 0.3mm. We demonstrate that by using these acquisition techniques, our data results in contrast-to-noise ratios that compare well with high-resolution images acquired with long scan times using post-mortem data at higher field strengths. For the subfields, the cornus ammonis (CA) 1, CA2/CA3, CA4/dentate gyrus, stratum radiatum/stratum lacunosum/stratum moleculare, and subiculum were all labeled as separate structures. Hippocampal volumes are reported for each of the substructures and the hippocampus as a whole (range for hippocampus: 2456.72-3325.02 mm(3)). Intra-rater reliability of our manual segmentation protocol demonstrates high reliability for the whole hippocampus (mean Dice Kappa of 0.91; range 0.90-0.92) and for each of the subfields (range of Dice Kappas: 0.64-0.83). We demonstrate that our reliability is better than the Dice Kappas produced by simulating the following errors: a translation by a single voxel in all cardinal directions and 1% volumetric shrinkage and expansion. The completed hippocampal atlases are available freely online (info2.camh.net/kf-tigr/index.php/Hippocampus) and can be coupled with novel computational neuroanatomy techniques that will allow for them to be customized to the unique neuroanatomy of different subjects, and ultimately be utilized in different analysis pipelines.

Endogenous testosterone and cortisol modulate neural responses during induced anger control.

Research with violent offenders and delinquent adolescents suggests that endogenous testosterone concentrations have the strongest positive correlations with violence among men who have low concentrations of cortisol. The present study tested the hypothesis that testosterone and cortisol would similarly interact to determine neural activation in regions supporting self-regulation in response to anger provocation. Nineteen healthy Asian male participants were insulted and asked to control their anger during functional magnetic resonance imaging (fMRI). When cortisol levels were low, testosterone positively correlated with activation in the dorsolateral prefrontal cortex (dlPFC) and thalamus, but not when cortisol levels were high. During induced anger control, functional connectivity was increased between the amygdala and a top-down prefrontal cortical control network. Moreover, the amygdala-PFC connectivity was strongest among those high in testosterone and low in cortisol. This research highlights a possible neural mechanism by which testosterone and cortisol may influence anger control.