Biology subjects

Gruetter, R.

Publications and source records attributed to Gruetter, R..

6 recordsLinked to original sources

bioRxiv2020

Deletion of Crtc1 leads to hippocampal neuroenergetic impairments associated with depressive-like behavior

Mood disorders (MD) are a major burden on society as their biology remains poorly understood, challenging both diagnosis and therapy. Among many observed biological dysfunctions, homeostatic dysregulation, such as metabolic syndrome (MeS), shows considerable comorbidity with MD. Recently, CREB-regulated transcription coactivator 1 (CRTC1), a regulator of brain metabolism, was proposed as a promising factor to understand this relationship. Searching for imaging biomarkers and associating them with pathophysiological mechanisms using preclinical models, can provide significant insight into these complex psychiatric diseases and help the development of personalized healthcare. Here, we used neuroimaging technologies to show that deletion of Crtc1 in mice leads to an imaging fingerprint of hippocampal metabolic impairment related to depressive-like behavior. By identifying the underlying molecular/physiological origin, we could assign an energy-boosting mood-stabilizing treatment, ebselen, which rescued behavior and neuroimaging markers. Finally, our results point towards the GABAergic system as a potential therapeutic target for behavioral dysfunctions related to metabolic disorders. This study provides new insights on Crtc1s and MeSs relationship to MD and establishes depression-related markers with clinical potential.

neuroscience↗

bioRxiv2020

EEG and fMRI connectomes are reliably related: a simultaneous EEG-fMRI study from 1.5T to 7T

Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation (fMRI) and neurophysiological recordings (EEG) are indirectly coupled. The electrophysiological and BOLD signal can map the underlying functional connectivity structure at the whole brain scale at different timescales. Previous work demonstrated a moderate but significant correlation between resting-state functional connectivity of both modalities, however there is a wide range of technical setups to measure simultaneous EEG-fMRI and the reliability of those measures between different setups remains unknown. This is true notably with respect to different magnetic field strengths (low and high field) and different spatial sampling of EEG (medium to high-density electrode coverage). Here, we investigated the reproducibility of the bimodal EEG-fMRI functional connectome in the most comprehensive resting-state simultaneous EEG-fMRI dataset compiled to date including a total of 72 subjects from four different imaging centers. Data was acquired from 1.5T, 3T and 7T scanners with simultaneously recorded EEG using 64 or 256 electrodes. We demonstrate that the whole-brain monomodal connectivity reproducibly correlates across different datasets and that a moderate crossmodal correlation between EEG and fMRI connectivity of r{approx}0.3 can be reproducibly extracted in low- and high-field scanners. The crossmodal correlation was strongest in the EEG-{beta} frequency band but exists across all frequency bands. Both homotopic and within intrinsic connectivity network (ICN) connections contributed the most to the crossmodal relationship. This study confirms, using a considerably diverse range of recording setups, that simultaneous EEG-fMRI offers a consistent estimate of multimodal functional connectomes in healthy subjects that are dominantly linked through a functional core of ICNs across spanning across the different timescales measured by EEG and fMRI. This opens new avenues for estimating the dynamics of brain function and provides a better understanding of interactions between EEG and fMRI measures. This observed level of reproducibility also defines a baseline for the study of alterations of this coupling in pathological conditions and their role as potential clinical markers.

neuroscience↗

bioRxiv2020

Spatio-temporal alterations in functional connectivity and white matter microstructure resulting from glucose hypometabolism in a rat model of sporadic Alzheimer's disease

Brain glucose hypometabolism has been singled out as an important contributor and possibly main trigger to Alzheimers disease (AD). Intracerebroventricular injections of streptozotocin (icv-STZ) cause brain glucose hypometabolism without systemic diabetes. Here, a first-time longitudinal study of brain glucose metabolism, functional connectivity and white matter microstructure was performed in icv-STZ rats using PET and MRI. Histological markers of pathology were tested at an advanced stage of disease. STZ rats exhibited altered functional connectivity and intra-axonal damage and demyelination in brain regions typical of AD, in a temporal pattern of acute injury, transient recovery/compensation and chronic degeneration. In the context of sustained glucose hypometabolism, these nonmonotonic trends - also reported in behavioral studies of this animal model as well as in human AD - suggest a compensatory mechanism, possibly recruiting ketone bodies, that allows a partial and temporary repair of brain structure and function. The early acute phase could thus become a valuable therapeutic window to strengthen the recovery phase and prevent or delay chronic degeneration, to be considered both in preclinical and clinical studies of AD. In conclusion, this work reveals the consequences of brain insulin resistance on structure and function, highlights signature nonmonotonic trajectories in their evolution and proposes potent MRI-derived biomarkers translatable to human AD and diabetic populations.

neuroscience↗

bioRxiv2019

Metabolic signature in nucleus accumbens for anti-depressant-like effects of acetyl-L-carnitine: An in vivo 1H-magnetic resonance spectroscopy study at 14 T

BackgroundEmerging evidence suggests that hierarchical status may provide vulnerability to develop stress-induced depression. Energy metabolism in the nucleus accumbens (NAc) was recently related to hierarchical status and vulnerability to develop depression-like behavior. Acetyl-L-carnitine (LAC), a mitochondria-boosting supplement, has shown promising antidepressant-like effects opening promising therapeutic strategies for restoring energy balance in depressed patients. Here, we investigated the metabolic impact in the NAc of antidepressant LAC treatment in chronically stressed mice.\n\nMethodMice were characterized for emotional behaviors and social rank. They were then exposed to chronic restraint stress (CRS) for 21 days and subsequently tested in a social behavior (SB) test. A group of mice was also given LAC supplementation during the 7 last CRS days. Mice were then tested in the SB and forced swim tests (FST) and scanned in vivo using 1H-magnetic resonance spectroscopy (1H-MRS) to quantitatively assess the NAc neurochemical profile.\n\nResultsDominant, but not subordinate, mice showed behavioral vulnerability to CRS. In the NAc, dominant mice showed reduced levels of several energy-related metabolites. LAC treatment counteracted stress-induced behavioral changes in dominant mice, and normalized levels of taurine, phosphocreatine, glutamine and phosphocholine in the NAc. No major accumbal metabolic changes were observed in subordinate mice.\n\nConclusionHigh social rank is confirmed as a vulnerability factor to develop chronic stress-induced depressive-like behaviors. We reveal a metabolic signature in the NAc for the antidepressant-like effects of LAC in vulnerable mice, characterized by restoration of stress-induced alterations in neuroenergetics and lipid function.

neuroscience↗

bioRxiv2018

Nucleus accumbens neurochemistry in human anxiety: A 7T 1H-MRS study

Individual differences in anxiety provide a differential predisposition to develop neuropsychiatric disorders. The neurochemical underpinnings of anxiety remain elusive, particularly in deep structures, such as the nucleus accumbens (NAc) whose involvement in anxiety is being increasingly recognized. We examined the associations between the neurochemical profile of human NAc metabolites involved in neural excitation and inhibition and inter-individual variation in temperamental and situational anxiety. Twenty-seven healthy 20-30 years-old human males were phenotyped with questionnaires for state and trait anxiety (State-Trait Anxiety Inventory, STAI), social anxiety (Liebowitz Social Anxiety Scale), depression (Beck Depression Inventory, BDI) and fatigue (Mental and Physical State Energy and Fatigue Scales, SEF). Using proton magnetic resonance spectroscopy (1H-MRS) at 7 Tesla (7T), we measured metabolite levels for glutamate, glutamine, GABA and taurine in the NAc with. Salivary cortisol was also measured. Strikingly, trait anxiety was negatively associated with NAc taurine content. Perceived situational stress was negatively associated with NAc GABA, while positively with the Glu/GABA ratio. These findings were specific, as no correlation was observed between NAc taurine or GABA and other phenotypic variables examined (i.e., state anxiety, social anxiety, depression, or cortisol), except for a negative correlation between taurine and state physical fatigue. This first 7T study of NAc neurochemistry shows relevant metabolite associations with individual variation in anxiety traits and situational stress and state anxiety measurements. The novel identified association between NAc taurine levels and trait anxiety may pave the way for clinical studies aimed at identifying new treatments for anxiety and related disorders.

neuroscience↗

bioRxiv2018

Capturing the spatiotemporal dynamics of task-initiated thoughts with combined EEG and fMRI

When at rest, our mind wanders from thought to thought in distinct mental states. Despite the marked importance of ongoing mental processes, it is challenging to capture and relate these states to specific cognitive contents. In this work, we employed ultra-high field functional magnetic resonance imaging (fMRI) and high-density electroencephalography (EEG) to study the ongoing thoughts of participants instructed to retrieve self-relevant past episodes for periods of 20s. These task-initiated, participant-driven activity patterns were compared to a distinct condition where participants performed serial mental arithmetic operations, thereby shifting from self-related to self-unrelated thoughts. BOLD activity mapping revealed selective activity changes in temporal, parietal and occipital areas (\"posterior hot zone\"), evincing their role in integrating the re-experienced past events into conscious representations during memory retrieval. Functional connectivity analysis showed that these regions were organized in two major subparts of the default mode network, previously associated to \"scene-reconstruction\" and \"self-experience\" subsystems. EEG microstate analysis allowed studying these participant-driven thoughts in the millisecond range by determining the temporal dynamics of brief periods of stable scalp potential fields. This analysis revealed selective modulation of occurrence and duration of specific microstates in both conditions. EEG source analysis revealed similar spatial distributions between the sources of these microstates and the regions identified with fMRI. These findings support growing evidence that specific fMRI networks can be captured with EEG as repeatedly occurring, integrated brief periods of synchronized neuronal activity, lasting only fractions of seconds.\n\nSignificanceWe investigated the spatiotemporal dynamics of large-scale brain networks related to specific conscious thoughts. We demonstrate here that instructing participants to direct their thoughts to either episodic autobiographic memory or to mental arithmetic modulates distinct networks both in terms of highly spatially-specific BOLD signal oscillations as well as fast sub-second dynamics of EEG microstates. The combined findings from the two modalities evince a clear link between hemodynamic and electrophysiological signatures of spontaneous brain activity by the occurrence of thoughts that last for fractions of seconds, repeatedly appearing over time as integrated coherent activities of specific large-scale networks.

neuroscience↗