• Neuroinformatics
• Natural Sciences and Engineering Research Council of Canada close

Abstract Sex hormones estrogen (EST) and progesterone (PROG) have received increased attention for their important physiological action outside of reproduction. While studies have shown that EST and PROG have significant impacts on brain function, their impact on the cerebrovascular system in humans remains largely unknown. To address this, we used a multi‐modal magnetic resonance imaging (MRI) approach to investigate the link between serum hormones in the follicular phase and luteal phase of the menstrual cycle (MC) with measures of cerebrovascular function (cerebral blood flow [CBF]) and structure (intracranial artery diameter). Fourteen naturally cycling women were recruited and assessed at two‐time points of their MC. CBF was derived from pseudo‐continuous arterial spin labeling while diameters of the internal carotid and basilar artery was assessed using time of flight magnetic resonance angiography, blood samples were performed after the MRI. Results show that PROG and EST had opposing and spatially distinct effects on CBF: PROG correlated negatively with CBF in anterior brain regions (r = −.86, p < .01), while EST correlations were positive, yet weak and most prominent in posterior areas (r = .78, p < .01). No significant correlations between either hormone or intracranial artery diameter were observed. These results show that EST and PROG have opposing and regionally distinct effects on CBF and that this relationship is likely not due to interactions with large intracranial arteries. Considering that CBF in healthy women appears tightly linked to their current hormonal state, future studies should consider assessing MC‐related hormone fluctuations in the design of functional MRI studies in this population. Using multi‐modal magnetic resonance imaging (MRI) we investigated the influence of serum hormones on cerebrovascular function and structure in naturally cycling, non‐pregnant women. We observed that progesterone has a strong negative correlation with CBF while estrogen had a weak positive association with CBF that was independent of large artery structure. These results highlight the impact that menstrual cycle‐related hormone fluctuations have on the female brain.

International audience; Cephalopods are radically different from any other invertebrate. Their molluscan heritage, innovative nervous system, and specialized behaviors create a unique blend of characteristics that are sometimes reminiscent of vertebrate features. For example, despite differences in the organization and development of their nervous systems, both vertebrates and cephalopods use many of the same neurotransmitters. One neurotransmitter, histamine (HA), has been well studied in both vertebrates and invertebrates, including molluscs. While HA was previously suggested to be present in the cephalopod central nervous system (CNS), Scaros, Croll, and Baratte only recently described the localization of HA in the olfactory system of the cuttlefish Sepia officinalis. Here, we describe the location of HA using an anti‐HA antibody and a probe for histidine decarboxylase (HDC), a synthetic enzyme for HA. We extended previous descriptions of HA in the olfactory organ, nerve, and lobe, and describe HDC staining in the same regions. We found HDC‐positive cell populations throughout the CNS, including the optic gland and the peduncle, optic, dorso‐lateral, basal, subvertical, frontal, magnocellular, and buccal lobes. The distribution of HA in the olfactory system of S. officinalis is similar to the presence of HA in the chemosensory organs of gastropods but is different than the sensory systems in vertebrates or arthropods. However, HA's widespread abundance throughout the rest of the CNS of Sepia is a similarity shared with gastropods, vertebrates, and arthropods. Its widespread use with differing functions across Animalia provokes questions regarding the evolutionary history and adaptability of HA as a transmitter.

Abstract. In the context of epilepsy monitoring, electroencephalography (EEG) remains the modality of choice. Functional near-infrared spectroscopy (fNIRS) is a relatively innovative modality that cannot only characterize hemodynamic profiles of seizures but also allow for long-term recordings. We employ deep learning methods to investigate the benefits of integrating fNIRS measures for seizure detection. We designed a deep recurrent neural network with long short-term memory units and subsequently validated it using the CHBMIT scalp EEG database—a compendium of 896 h of surface EEG seizure recordings. After validating our network using EEG, fNIRS, and multimodal data comprising a corpus of 89 seizures from 40 refractory epileptic patients was used as model input to evaluate the integration of fNIRS measures. Following heuristic hyperparameter optimization, multimodal EEG-fNIRS data provide superior performance metrics (sensitivity and specificity of 89.7% and 95.5%, respectively) in a seizure detection task, with low generalization errors and loss. False detection rates are generally low, with 11.8% and 5.6% for EEG and multimodal data, respectively. Employing multimodal neuroimaging, particularly EEG-fNIRS, in epileptic patients, can enhance seizure detection performance. Furthermore, the neural network model proposed and characterized herein offers a promising framework for future multimodal investigations in seizure detection and prediction.

A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications.

Additional file 1. Supplementary methods.

International audience; Background: Evidence suggests that individuals with psychopathy display difficulties to adapt their behavior in accordance with the demands of the environment and show altered performance monitoring. However, studies investigating electrophysiological markers of error monitoring (e.g., the error-related negativity (ERN) and the error-positivity (Pe)) in this population reported mixed results. To explain discrepancies observed between studies, we hypothesized that psychopathy dimensions influence electrophysiological outcomes and we predicted that individuals with impulsive-antisocial features would display abnormal ERN compared to individuals with interpersonal-affective features. Methods: Based on the PRISMA guidelines, we conducted a systematic review and meta-analysis of studies investigating ERN and Pe components in individuals with psychopathy compared to controls. A factorial analysis was undertaken to investigate the role of psychopathy dimensions on ERN. Results: Among the 206 retrieved studies, 15 were included in the meta- analysis. Individuals with psychopathy (n = 817) showed a reduced ERN (Cohen's d = 0.18) and Pe amplitude (d = -0.22) compared to control. The factorial analysis indicates a dissociation regarding the dimensional construct of psychopathy. The impulsive-antisocial dimension was linked to reduced ERN amplitude (d = 0.22) whereas the interpersonal-affective dimension was related to increased ERN amplitude compare to controls (d = -0.17). Conclusion: Individuals with psychopathy displayed abnormal ERN and Pe amplitudes following error commission. In addition, models reported that individuals with psychopathic traits relating more specifically to the interpersonal-affective dimension shows efficient error-monitoring systems and increased ERN component while those with marked impulsive-antisocial dimension displayed decreased ERN and altered performance monitoring.

Objective To objectively quantify how cerebral volume loss could assist with clinical diagnosis and clinical trial design in the behavioural variant of frontotemporal dementia (bvFTD). Methods We applied deformation-based morphometric analyses with robust registration to precisely quantify the magnitude and pattern of atrophy in patients with bvFTD as compared to cognitively normal controls (CNCs), to assess the progression of atrophy over one year follow up and to generate clinical trial sample size estimates to detect differences for the structures most sensitive to change. This study included 203 subjects - 70 bvFTD and 133 CNCs - with a total of 482 timepoints from the Frontotemporal Lobar Degeneration Neuroimaging Initiative. Results Deformation based morphometry (DBM) revealed significant atrophy in the frontal lobes, insula, medial and anterior temporal regions bilaterally in bvFTD subjects compared to controls with outstanding subcortical involvement. We provide detailed information on regional changes per year. In both cross-sectional analysis and over a one-year follow-up period, ventricle expansion was the most prominent differentiator of bvFTD from controls and a sensitive marker of disease progression. Conclusions Automated measurement of ventricular expansion is a sensitive and reliable marker of disease progression in bvFTD to be used in clinical trials for potential disease modifying drugs, as well as possibly to implement in clinical practice. Ventricular expansion measured with DBM provides the lowest published estimated sample size for clinical trial design to detect significant differences over one and two years. Highlights • The expected atrophy was shown in the frontal lobes and anterior temporal regions. • Subcortical structures were notably affected in our bvFTD cohort. • Ventricles and sulci within frontotemporal regions were larger in the bvFTD cohort. • Ventricles and sulci showed significant enlargement and over a one-year period. • Ventricular expansion was the most prominent differentiator of bvFTD from controls.

AbstractDocosahexaenoic acid (DHA) is important for brain function, and can be obtained directly from the diet or synthesized in the body from α-linolenic acid (ALA). Debate exists as to whether DHA synthesized from ALA can provide sufficient DHA for the adult brain, as measures of DHA synthesis from ingested ALA are typically <1% of the oral ALA dose. However, the primary fate of orally administered ALA is β-oxidation and long-term storage in adipose tissue, suggesting that DHA synthesis measures involving oral ALA tracer ingestion may underestimate total DHA synthesis. There is also evidence that DHA synthesized from ALA can meet brain DHA requirements, as animals fed ALA-only diets have brain DHA concentrations similar to DHA-fed animals, and the brain DHA requirement is estimated to be only 2.4–3.8mg/day in humans. This review summarizes evidence that DHA synthesis from ALA can provide sufficient DHA for the adult brain by examining work in humans and animals involving estimates of DHA synthesis and brain DHA requirements. Also, an update on methods to measure DHA synthesis in humans is presented highlighting a novel approach involving steady-state infusion of stable isotope-labeled ALA that bypasses several limitations of oral tracer ingestion. It is shown that this method produces estimates of DHA synthesis that are at least 3-fold higher than brain uptake rates in rats.

Abstract We examined lexical stress processing in English-French bilinguals. Auditory mismatch negativity (MMN) responses were recorded in response to English and French pseudowords, whose primary stress occurred either on a language-consistent “usual” or language-inconsistent “unusual” syllable. In most conditions, the pseudowords elicited two consecutive MMNs, and somewhat surprisingly, these MMNs were not systematically modulated by bilingual experience. This suggests that it is possible to achieve native-like pre-attentive processing of lexical stress, even in a language that one has not learned since birth.

There is accumulating evidence from behavioral, neurophysiological, and neuroimaging studies that the acquisition of motor skills involves both perceptual and motor learning. Perceptual learning alters movements, motor learning, and motor networks of the brain. Motor learning changes perceptual function and the sensory circuits of the brain. Here, we review studies of both human limb movement and speech that indicate that plasticity in sensory and motor systems is reciprocally linked. Taken together, this points to an approach to motor learning in which perceptual learning and sensory plasticity have a fundamental role.