Shared genetic architecture between schizophrenia and subcortical brain volumes implicates early neurodevelopmental processes and brain development in childhood.

Patients with schizophrenia have consistently shown brain volumetric abnormalities, implicating both etiological and pathological processes. However, the genetic relationship between schizophrenia and brain volumetric abnormalities remains poorly understood. Here, we applied novel statistical genetic approaches (MiXeR and conjunctional false discovery rate analysis) to investigate genetic overlap with mixed effect directions using independent genome-wide association studies of schizophrenia (n = 130,644) and brain volumetric phenotypes, including subcortical brain and intracranial volumes (n = 33,735). We found brain volumetric phenotypes share substantial genetic variants (74-96%) with schizophrenia, and observed 107 distinct shared loci with sign consistency in independent samples. Genes mapped by shared loci revealed (1) significant enrichment in neurodevelopmental biological processes, (2) three co-expression clusters with peak expression at the prenatal stage, and (3) genetically imputed thalamic expression of CRHR1 and ARL17A was associated with the thalamic volume as early as in childhood. Together, our findings provide evidence of shared genetic architecture between schizophrenia and brain volumetric phenotypes and suggest that altered early neurodevelopmental processes and brain development in childhood may be involved in schizophrenia development.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

A molecule-based genetic association approach implicates a range of voltage-gated calcium channels associated with schizophrenia.

Traditional genome-wide association studies (GWAS) have successfully detected genetic variants associated with schizophrenia. However, only a small fraction of heritability can be explained. Gene-set/pathway-based methods can overcome limitations arising from single nucleotide polymorphism (SNP)-based analysis, but most of them place constraints on size which may exclude highly specific and functional sets, like macromolecules. Voltage-gated calcium (Cav ) channels, belonging to macromolecules, are composed of several subunits whose encoding genes are located far away or even on different chromosomes. We combined information about such molecules with GWAS data to investigate how functional channels associated with schizophrenia. We defined a biologically meaningful SNP-set based on channel structure and performed an association study by using a validated method: SNP-set (sequence) kernel association test. We identified eight subtypes of Cav channels significantly associated with schizophrenia from a subsample of published data (N = 56,605), including the L-type channels (Cav 1.1, Cav 1.2, Cav 1.3), P-/Q-type Cav 2.1, N-type Cav 2.2, R-type Cav 2.3, T-type Cav 3.1, and Cav 3.3. Only genes from Cav 1.2 and Cav 3.3 have been implicated by the largest GWAS (N = 82,315). Each subtype of Cav channels showed relatively high chip heritability, proportional to the size of its constituent gene regions. The results suggest that abnormalities of Cav channels may play an important role in the pathophysiology of schizophrenia and these channels may represent appropriate drug targets for therapeutics. Analyzing subunit-encoding genes of a macromolecule in aggregate is a complementary way to identify more genetic variants of polygenic diseases. This study offers the potential of power for discovery the biological mechanisms of schizophrenia.

Structural growth trajectories and rates of change in the first 3 months of infant brain development.

IMPORTANCE: The very early postnatal period witnesses extraordinary rates of growth, but structural brain development in this period has largely not been explored longitudinally. Such assessment may be key in detecting and treating the earliest signs of neurodevelopmental disorders. OBJECTIVE: To assess structural growth trajectories and rates of change in the whole brain and regions of interest in infants during the first 3 months after birth. DESIGN, SETTING, AND PARTICIPANTS: Serial structural T1-weighted and/or T2-weighted magnetic resonance images were obtained for 211 time points from 87 healthy term-born or term-equivalent preterm-born infants, aged 2 to 90 days, between October 5, 2007, and June 12, 2013. MAIN OUTCOMES AND MEASURES: We segmented whole-brain and multiple subcortical regions of interest using a novel application of Bayesian-based methods. We modeled growth and rate of growth trajectories nonparametrically and assessed left-right asymmetries and sexual dimorphisms. RESULTS: Whole-brain volume at birth was approximately one-third of healthy elderly brain volume, and did not differ significantly between male and female infants (347 388 mm3 and 335 509 mm3, respectively, P = .12). The growth rate was approximately 1%/d, slowing to 0.4%/d by the end of the first 3 months, when the brain reached just more than half of elderly adult brain volume. Overall growth in the first 90 days was 64%. There was a significant age-by-sex effect leading to widening separation in brain sizes with age between male and female infants (with male infants growing faster than females by 200.4 mm3/d, SE = 67.2, P = .003). Longer gestation was associated with larger brain size (2215 mm3/d, SE = 284, P = 4×10-13). The expected brain size of an infant born one week earlier than average was 5% smaller than average; at 90 days it will not have caught up, being 2% smaller than average. The cerebellum grew at the highest rate, more than doubling in 90 days, and the hippocampus grew at the slowest rate, increasing by 47% in 90 days. There was left-right asymmetry in multiple regions of interest, particularly the lateral ventricles where the left was larger than the right by 462 mm3 on average (approximately 5% of lateral ventricular volume at 2 months). We calculated volume-by-age percentile plots for assessing individual development. CONCLUSIONS AND RELEVANCE: Normative trajectories for early postnatal brain structural development can be determined from magnetic resonance imaging and could be used to improve the detection of deviant maturational patterns indicative of neurodevelopmental disorders.

Basal ganglia atrophy in prodromal Huntington's disease is detectable over one year using automated segmentation.

Future clinical trials of neuroprotection in prodromal Huntington's (known as preHD) will require sensitive in vivo imaging biomarkers to track disease progression over the shortest period. Since basal ganglia atrophy is the most prominent structural characteristic of Huntington's pathology, systematic assessment of longitudinal subcortical atrophy holds great potential for future biomarker development. We studied 36 preHD and 22 age-matched controls using a novel method to quantify regional change from T(1) -weighted structural images acquired 1 year apart. We assessed cross-sectional volume differences and longitudinal volumetric change in 7 subcortical structures-the accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. At baseline, accumbens, caudate, pallidum, and putamen volumes were reduced in preHD versus controls (all P < .01). Longitudinally, atrophy was greater in preHD than controls in the caudate, pallidum, and putamen (all P < .01). Each structure showed a large between-group effect size, especially the pallidum where Cohen's d was 1.21. Using pallidal atrophy as a biomarker, we estimate that a hypothetical 1-year neuroprotection study would require only 35 preHD per arm to detect a 50% slowing in atrophy and only 138 preHD per arm to detect a 25% slowing in atrophy. The effect sizes calculated for preHD basal ganglia atrophy over 1 year are some of the largest reported to date. Consequently, this translates to strikingly small sample size estimates that will greatly facilitate any future neuroprotection study. This underscores the utility of this automatic image segmentation and longitudinal nonlinear registration method for upcoming studies of preHD and other neurodegenerative disorders.

Sequential temporo-fronto-temporal activation during monitoring of the auditory environment for temporal patterns.

Subjects detected rarely occurring shifts between two simple tone-patterns, in a paradigm that dissociated the effects of rarity from those of pitch, habituation, and attention. Whole-head magnetoencephalography suggested that rare attended pattern-shifts evoked activity first in the superior temporal plane (sTp, peak ~100 ms), then superior temporal sulcus (sTs, peak ~130 ms), then posteroventral prefrontal (pvpF, peak ~230 ms), and anterior temporal cortices (aT, peak ~370 ms). Activity was more prominent in the right hemisphere. After subtracting the effects of nonshift tones (balanced for pitch and habituation status), weak but consistent differential effects of pattern-shifts began in aT at 90-130 ms, spread to sTs and sTp at ∼130 ms, then pvpF, and finally returned to aT. Cingulate activity resembled prefrontal. Responses to pattern shifts were greatly attenuated when the same stimuli were ignored, suggesting that the initial superior temporal activity reflected an attention-related mismatch negativity. The prefrontal activity at ~230 ms corresponded in latency and task correlates with simultaneously recorded event-related potential components N2b and P3a; the subsequent temporal activity corresponded to the P3b. These results were confirmed in sensors specific for frontal or temporal cortex, and thus are independent of the inverse method used. Overall, these results suggest that auditory working memory for temporal patterns begins with detection of the pattern change by an interaction of anterior and superior temporal structures, followed by identification of the event and its consequences led by posteroventral prefrontal and cingulate cortices, and finally, definitive encoding of the event in anterior temporal areas.

Estimation of thalamocortical and intracortical network models from joint thalamic single-electrode and cortical laminar-electrode recordings in the rat barrel system.

A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population.

Subcortical and cerebellar atrophy in mesial temporal lobe epilepsy revealed by automatic segmentation.

PURPOSE: To determine the validity and utility of using automated subcortical segmentation to identify atrophy of the hippocampus and other subcortical and cerebellar structures in patients with mesial temporal lobe epilepsy (MTLE). METHODS: Volumetric MRIs were obtained on 21 patients with MTLE (11 right, 10 left) and 21 age- and gender-matched healthy controls. Labeling of subcortical and cerebellar structures was accomplished using automated reconstruction software (FreeSurfer). Multivariate analysis of covariance (MANCOVA) was used to explore group differences in intracranial-normalized, age-adjusted volumes and structural asymmetries. Step-wise discriminant function analysis was used to identify the linear combination of volumes that optimized classification of individual subjects. RESULTS: Results revealed the expected reduction in hippocampal volume on the side ipsilateral to the seizure focus, as well as bilateral reductions in thalamic and cerebellar gray matter volume. Analysis of structural asymmetries revealed significant asymmetry in the hippocampus and putamen in patients compared to controls. The discriminant function analysis revealed that patients with right and left MTLE were best distinguished from one another using a combination of subcortical volumes that included the right and left hippocampus and left thalamus (91-100% correct classification using cross-validation). DISCUSSION: Volumetric data obtained with automated segmentation of subcortical and cerebellar structures approximate data from previous studies based on manual tracings. Our data suggest that automated segmentation can provide a clinically useful means of evaluating the nature and extent of structural damage in patients with MTLE and may increase diagnostic classification of patients, especially when hippocampal atrophy is mild.

Vector-based spatial-temporal minimum L1-norm solution for MEG.

Minimum L1-norm solutions have been used by many investigators to analyze MEG responses because they provide high spatial resolution images. However, conventional minimum L1-norm approaches suffer from instability in spatial construction, and poor smoothness of the reconstructed source time-courses. Activity commonly "jumps" from one grid point to (usually) the neighboring grid points. Equivalently, the time-course of one specific grid point can show substantial "spiky-looking" discontinuity. In the present study, we present a new vector-based spatial-temporal analysis using a L1-minimum-norm (VESTAL). This approach is based on a principle of MEG physics: the magnetic waveforms in sensor-space are linear functions of the source time-courses in the imaging-space. Our computer simulations showed that VESTAL provides good reconstruction of the source amplitude and orientation, with high stability and resolution in both the spatial and temporal domains. "Spiky-looking" discontinuity was not observed in the source time-courses. Importantly, the simulations also showed that VESTAL can resolve sources that are 100% correlated. We then examined the performance of VESTAL in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguishes sources very spatially close to each other, including individual primary somatosensory areas (BA 1, 2, 3b), primary motor area (BA 4), and other regions in the somatosensory system (e.g., BA 5, 7, SII, SMA, and temporal-parietal junction) with high temporal stability and resolution. VESTAL's potential for obtaining information on source extent was also examined.

Distributed current estimates using cortical orientation constraints.

Distributed source models of magnetoencephalographic (MEG) and electroencephalographic (EEG) data employ dense distributions of current sources in a volume or on a surface. Previously, anatomical magnetic resonance imaging (MRI) data have been used to constrain locations and orientations based on cortical geometry extracted from anatomical MRI data. We extended this approach by first calculating cortical patch statistics (CPS), which for each patch corresponding to a current source location on the cortex comprise the area of the patch, the average normal direction, and the average deviation of the surface normal from its average. The patch areas were then incorporated in the forward model to yield estimates of the surface current density instead of dipole amplitudes at the current locations. The surface normal data were employed in a loose orientation constraint (LOC), which allows some variation of the current direction from the average normal. We employed this approach both in the l(2) minimum-norm estimates (MNE) and in the more focal l(1) minimum-norm solutions, the minimum-current estimate (MCE). Simulations in auditory and somatosensory areas with current dipoles and 10- or 20-mm diameter cortical patches as test sources showed that applying the LOC can increase localization accuracy. We also applied the method to in vivo auditory and somatosensory data.

Coupling of the cortical hemodynamic response to cortical and thalamic neuronal activity.

Accurate interpretation of functional MRI (fMRI) signals requires knowledge of the relationship between the hemodynamic response and the neuronal activity that underlies it. Here we address the question of coupling between pre- and postsynaptic neuronal activity and the hemodynamic response in rodent somatosensory (Barrel) cortex in response to single-whisker deflection. Using full-field multiwavelength optical imaging of hemoglobin oxygenation and electrophysiological recordings of spiking activity and local field potentials, we demonstrate that a point hemodynamic measure is influenced by neuronal activity across multiple cortical columns. We demonstrate that the hemodynamic response is a spatiotemporal convolution of the neuronal activation. Therefore, positive hemodynamic response in one cortical column might be explained by neuronal activity not only in that column but also in the neighboring columns. Thus, attempts at characterizing the neurovascular relationship based on point measurements of electrophysiology and hemodynamics may yield inconsistent results, depending on the spatial extent of neuronal activation. The finding that the hemodynamic signal observed at a given location is a function of electrophysiological activity over a broad spatial region helps explain a previously observed increase of local vascular response beyond the saturation of local neuronal activity. We also demonstrate that the oxy- and total-hemoglobin hemodynamic responses can be well approximated by space-time separable functions with an antagonistic center-surround spatial pattern extending over several millimeters. The surround "negative" hemodynamic activity did not correspond to observable changes in neuronal activity. The complex spatial integration of the hemodynamic response should be considered when interpreting fMRI data.

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain.

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl's gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions.

Tonotopic organization in human auditory cortex revealed by progressions of frequency sensitivity.

Functional neuroimaging experiments have revealed an organization of frequency-dependent responses in human auditory cortex suggestive of multiple tonotopically organized areas. Numerous studies have sampled cortical responses to isolated narrow-band stimuli, revealing multiple locations in auditory cortex at which the position of response varies systematically with frequency content. Because appropriate anatomical or functional grouping of these distinct frequency-dependent responses is uncertain, the number and location of tonotopic mappings within human auditory cortex remains unclear. Further, sampling does not address whether the observed mappings exhibit continuity as a function of position. This functional magnetic resonance imaging study used frequency-swept stimuli to identify progressions of frequency sensitivity across the cortical surface. The center-frequency of narrow-band, amplitude-modulated noise was slowly swept between 125 and 8,000 Hz. The latency of response relative to sweep onset was determined for each cortical surface location. Because frequency varied systematically with time, response latency indicated the frequency to which a location was maximally sensitive. Areas of cortex exhibiting a progressive change in response latency with position were considered tonotopically organized. There exist two main findings. First, six progressions of frequency sensitivity (i.e., tonotopic mappings) were repeatably observed in the superior temporal plane. Second, the locations of the higher- and lower-frequency endpoints of these progressions were approximately congruent with regions reported to be most responsive to discrete higher- and lower-frequency stimuli. Based on these findings and previous anatomical work, we propose a correspondence between these progressions and anatomically defined cortical areas, suggesting that five areas in human auditory cortex exhibit at least six tonotopic organizations.

In vivo tracing of major rat brain pathways using manganese-enhanced magnetic resonance imaging and three-dimensional digital atlasing.

The magnetic resonance imaging (MRI)-detectable T1 contrast agent manganese (Mn2+) has recently been introduced as a neural tracer in rodents, birds, and monkeys. We have tested to what extent this in vivo method is useful for three-dimensional (3-D) survey of connectivity patterns in the rat somatosensory system. A commonly available 3 T human clinical MRI scanner was used to trace neural pathways following focal injection of manganese chloride (MnCl2) in the somatosensory cortex. Six to 10 h after MnCl2 injection, we found significant signal enhancement in major projection systems, including corticocortical, corticostriatal, corticothalamic, corticotectal, corticopontine, and corticospinal pathways. To facilitate the assignment of anatomic localization to the observed Mn2+ signal enhancement, we registered the MRI data with a 3-D digital reconstruction of a stereotaxic rat brain atlas. Across-animal comparison using the digital model allowed demonstration of a corticothalamic 3-D topographic organization in agreement with previously published two-dimensional topographic schemes based on classical neural tracing data. We conclude that anterograde MnCl2/MRI tracing allows rapid analysis of topographic organization across multiple brain regions. The method allows a higher data throughput for 3-D studies of large-scale brain connectivity than conventional methods based on tissue sectioning.

Identifying regional activity associated with temporally separated components of working memory using event-related functional MRI.

This study describes the neural circuitry underlying temporally separated components of working memory (WM) performance-stimulus encoding, maintenance of information during a delay, and the response to a probe. While other studies have applied event-related fMRI to separate epochs of WM tasks, this study differs in that it employs a methodology that does not make any a priori assumptions about the shape of the hemodynamic response (HDR). This is important because no one model of the HDR is valid across the range of activated brain regions and stimulus types. Systematic modeling inaccuracies may lead to the misattribution of activity to adjacent events. Twelve healthy subjects performed a numerical version of the Sternberg Item Recognition Paradigm adapted for rapid presentation event-related fMRI. This paradigm emphasized maintenance rather than manipulative WM processes and used a subcapacity WM load. WM trials with different delay lengths were compared to fixation. The HDR of the entire WM trial for each trial type was estimated using a finite impulse response (FIR). Regional activity associated with the Encode, Delay, and Probe epochs was identified using contrasts that were based on the FIR estimates and by examining the HDRs. Each epoch was associated with a distinct but overlapping pattern of regional activity. Activation of the dorsolateral prefrontal cortex, thalamus, and basal ganglia was exclusively associated with the probe. This suggests that frontostriatal neural circuitry participates in selecting an appropriate response based on the contents of WM.