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Objective: To evaluate progressive white matter (WM) degeneration in ALS. Methods: Sixty-six patients with ALS and 43 healthy controls were enrolled in a prospective, longitudinal, multicentre study in the Canadian ALS Neuroimaging Consortium (CALSNIC). Participants underwent a harmonized neuroimaging protocol across 4 centres including diffusion tensor imaging (DTI) for assessment of WM integrity. Three visits were accompanied by clinical assessments of disability (ALSFRS-R) and upper motor neuron (UMN) function. Voxel-wise whole brain and quantitative tractwise DTI assessments were done at baseline and longitudinally. Correction for site variance incorporated data from healthy controls and from healthy volunteers that underwent the DTI protocol at each centre. Results: ALS patients had a mean progressive decline in fractional anisotropy (FA) of the corticospinal tract (CST) and frontal lobes. Tractwise analysis revealed reduced FA in the CST, corticopontine/corticorubral and corticostriatal tracts. CST FA correlated with UMN function and frontal lobe FA with the ALSFRS-R. A progressive decline in CST FA correlated with a decline in the ALSFRS-R and worsening UMN signs. Patients with fast vs slow progression had a greater reduction in FA of the CST and upper frontal lobe. Conclusions: Progressive WM degeneration in ALS is most prominent in the CST and frontal lobes, and to a lesser degree in the corticopontine/corticorubral tracts and the corticostriatal pathways. With the use of a harmonized imaging protocol and incorporation of analytical methods to address site-related variances, this study is an important milestone towards developing DTI biomarkers for cerebral degeneration in ALS.

Alzheimer's disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/.

Example code for the multivariate template creation process used for Myelin imaging in the central nervous system: Comparison of multi-echo T2 relaxation and steady-state approaches

Segmentation of sub-cortical structures from MRI scans is of interest in many neurological diagnoses. Indian Brain Segmentation Dataset (IBSD) consists of high-quality 1.5T T1w MRI data of 114 subjects generated under fixed imaging protocol along with corresponding manual annotation data of 14 sub-cortical structures done by expert radiologists. The number of MR scans in the dataset consists of an approximately equal number of male and female subjects belonging to a young age group (20-30 years). This data has been used to create a template for the young Indian population [1]. This dataset can also be utilized for variety of tasks such as segmenting structures of interest, aligning/ registering images, etc, using traditional methods as well as Deep Learning approaches since it has adequate quantity of high quality data.

Entrainment of neural oscillations on multiple time scales is important for the perception of speech. Musical rhythms, and in particular the perception of a regular beat in musical rhythms, is also likely to rely on entrainment of neural oscillations. One recently proposed approach to studying beat perception in the context of neural entrainment and resonance (the “frequency-tagging” approach) has received an enthusiastic response from the scientific community. A specific version of the approach involves comparing frequency-domain representations of acoustic rhythm stimuli to the frequency-domain representations of neural responses to those rhythms (measured by electroencephalography, EEG). The relative amplitudes at specific EEG frequencies are compared to the relative amplitudes at the same stimulus frequencies, and enhancements at beat-related frequencies in the EEG signal are interpreted as reflecting an internal representation of the beat. Here, we show that frequency-domain representations of rhythms are sensitive to the acoustic features of the tones making up the rhythms (tone duration, onset/offset ramp duration); in fact, relative amplitudes at beat-related frequencies can be completely reversed by manipulating tone acoustics. Crucially, we show that changes to these acoustic tone features, and in turn changes to the frequency-domain representations of rhythms, do not affect beat perception. Instead, beat perception depends on the pattern of onsets (i.e., whether a rhythm has a simple or complex metrical structure). Moreover, we show that beat perception can differ for rhythms that have numerically identical frequency-domain representations. Thus, frequency-domain representations of rhythms are dissociable from beat perception. For this reason, we suggest caution in interpreting direct comparisons of rhythms and brain signals in the frequency domain. Instead, we suggest that combining EEG measurements of neural signals with creative behavioral paradigms is of more benefit to our understanding of beat perception. single participant behavioral data files.mat files for single participants. README.txt file in each zipped folder describes columnsdryad_data.zip

Juveniles of the cooperatively-breeding cichlid fish Neolamprologus pulcher either consistently provide help in form of alloparental egg care ('cleaners') or consistently abstain from helping ('non-cleaners'). These phenotypes are not based on heritable genetic differences. Instead they arise during ontogeny, which should lead to differences in brain structure or physiology, a currently untested prediction. We compared brain gene expression profiles of cleaners and non-cleaners in two experimental conditions, a helping opportunity and a control condition. We aimed to identify (i) expression differences between cleaners and non-cleaners in the control, (ii) changes in gene expression induced by the opportunity, and (iii) differences in plasticity of gene expression between cleaners and non-cleaners. Control cleaners and non-cleaners differed in the expression of a single gene, irx2, which regulates neural differentiation. During the opportunity, cleaners and non-cleaners had three up-regulated genes in common, which were implicated in neuroplasticity, hormonal signalling, and cell proliferation. Thus, the stimulus in the opportunity was sufficiently salient. Cleaners also showed higher expression of seven additional genes that were unique to the opportunity. One of these cleaner-specific genes is implicated in neuropeptide metabolism, indicating that this process is associated with cleaning performance. This suggests that the two types employed different pathways to integrate social information, preparing them for accelerated reaction to future opportunities. Interestingly, three developmental genes were down-regulated between the control and the opportunity in cleaners only. Our results indicate that the two behavioural types responded differently to the helping opportunity, and that only cleaners responded by down-regulating developmental genes. Read count matrix and treatment information on individualsRead count matrix from RNA-seq experiment of two distinct helper types in the cooperatively breeding cichlid fish Neolamprologus pulcher. 48 individuals in a 2x2 full-factorial design of cleaners and non-cleaners in control and opportunity. 38,2425 genes expressed in the telencephalon 45 min after the onset of the cooperation opportunity.data_Kasper_cichlid_helping_transcriptome.xlsx

Objectives: Degenerative cervical myelopathy (DCM) involves extrinsic spinal cord compression causing tissue injury and neurological dysfunction. Asymptomatic spinal cord compression (ASCC) is more common but its significance is poorly defined. This study investigates if: 1) ASCC can be automatically diagnosed using spinal cord shape analysis; 2) multiparametric quantitative MRI can detect similar spinal cord tissue injury as previously observed in DCM. Design: Prospective observational longitudinal cohort study. Setting: Single centre, tertiary care and research institution. Participants: 40 neurologically intact subjects (19 female, 21 male) divided into groups with and without ASCC. Interventions: None. Outcome Measures: Clinical assessments: modified Japanese Orthopedic Association (mJOA) score and physical examination. 3T MRI assessments: automated morphometric analysis compared with consensus ratings of spinal cord compression, and measures of tissue injury: cross-sectional area (CSA), diffusion fractional anisotropy (FA), magnetization transfer ratio (MTR), and T2-weighted imaging white to grey matter signal intensity ratio (T2WI WM/GM) extracted from rostral (C1-3), caudal (C6-7), and maximally compressed levels (MCL). Results: ASCC was present in 20/40 subjects. Diagnosis with automated shape analysis showed area under the curve > 97%. Five MRI metrics showed differences suggestive of tissue injury in ASCC compared with uncompressed subjects (p<0.05), while a composite of all 10 measures (average of z scores) showed highly significant differences (p=0.002). At follow-up (median 21 months), two ASCC subjects developed DCM. Conclusions: ASCC appears to be common and can be accurately and objectively diagnosed with automated morphometric analysis. Quantitative MRI appears to detect subclinical tissue injury in ASCC prior to the onset of neurological symptoms and signs. These findings require further validation, but offer the intriguing possibility of pre-symptomatic diagnosis and treatment of DCM and other spinal pathologies. Registration: Not registered. Demographic, morphometric, and quantitative MRI dataData includes anonymized subject ID, presence of spinal cord compression, age, sex, follow-up mJOA score, spinal cord morphometric parameters of compression ratio, solidity, and relative rotation, measured at C2-3, C3-4, C4-5, C5-6, and C6-7, and quantitative MRI measures of cross sectional area, magnetization transfer ratio, fractional anisotropy, and T2*-weighted white matter to grey matter signal intensity ratio, measured at rostral (C1-3), maximally compressed level, and caudal (C6-7) levels.qMRI_subclinical_tissue_injury_public_data.xlsx

HIGHLIGHTS AxonPacking: Open-source software for simulating white matter microstructure.Validation on a theoretical disk packing problem.Reproducible and stable for various densities and diameter distributions.Can be used to study interplay between myelin/fiber density and restricted fraction.Quantitative Magnetic Resonance Imaging (MRI) can provide parameters that describe white matter microstructure, such as the fiber volume fraction (FVF), the myelin volume fraction (MVF) or the axon volume fraction (AVF) via the fraction of restricted water (fr). While already being used for clinical application, the complex interplay between these parameters requires thorough validation via simulations. These simulations required a realistic, controlled and adaptable model of the white matter axons with the surrounding myelin sheath. While there already exist useful algorithms to perform this task, none of them combine optimisation of axon packing, presence of myelin sheath and availability as free and open source software. Here, we introduce a novel disk packing algorithm that addresses these issues. The performance of the algorithm is tested in term of reproducibility over 50 runs, resulting density, and stability over iterations. This tool was then used to derive multiple values of FVF and to study the impact of this parameter on fr and MVF in light of the known microstructure based on histology sample. The standard deviation of the axon density over runs was lower than 10−3 and the expected hexagonal packing for monodisperse disks was obtained with a density close to the optimal density (obtained: 0.892, theoretical: 0.907). Using an FVF ranging within [0.58, 0.82] and a mean inter-axon gap ranging within [0.1, 1.1] μm, MVF ranged within [0.32, 0.44] and fr ranged within [0.39, 0.71], which is consistent with the histology. The proposed algorithm is implemented in the open-source software AxonPacking (https://github.com/neuropoly/axonpacking) and can be useful for validating diffusion models as well as for enabling researchers to study the interplay between microstructure parameters when evaluating qMRI methods.