Kynurenines increase MRS metabolites in basal ganglia and decrease resting-state connectivity in frontostriatal reward circuitry in depression

AbstractInflammation is associated with the development of anhedonia in major depression (MD), but the pathway by which inflammatory molecules gain access to the brain and lead to anhedonia is not clear. Molecules of the kynurenine pathway (KP), which is activated by inflammation, readily influx into the brain and generate end products that alter brain chemistry, disrupt circuit functioning, and result in the expression of inflammatory behaviors such as anhedonia. We examined the impact of plasma and CSF KP metabolites on brain chemistry and neural function using multimodal neuroimaging in 49 depressed subjects. We measured markers of glial dysfunction and distress including glutamate (Glu) and myo-inositol in the left basal ganglia using magnetic resonance spectroscopy (MRS); metrics of local activity coherence (regional homogeneity, ReHo) and functional connectivity from resting-state functional MRI measures; and anhedonia from the Inventory for Depressive Symptoms-Self Report Version (IDS-SR). Plasma kynurenine/tryptophan (KYN/TRP) ratio and cerebrospinal fluid (CSF) 3-hydroxykynurenine (3HK) were associated with increases in left basal ganglia myo-inositol. Plasma kynurenic acid (KYNA) and KYNA/QA were associated with decreases and quinolinic acid (QA) with increases in left basal ganglia Glu. Plasma and CSF KP were associated with decreases in ReHo in the basal ganglia and dorsomedial prefrontal regions (DMPFC) and impaired functional connectivity between these two regions. DMPFC-basal ganglia mediated the effect of plasma and CSF KP on anhedonia. These findings highlight the pathological impact of KP system dysregulation in mediating inflammatory behaviors such as anhedonia.

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Kynurenines Increase MRS Metabolites in Basal Ganglia and Decrease Resting State Connectivity in Frontostriatal Reward Circuitry in Depression

10.1101/2021.05.16.21257295 ◽

2021 ◽

Author(s):

Xiangchuan Chen ◽

Diana J Beltran ◽

Valeriya D Tsygankova ◽

Bobbi J Woolwine ◽

Trusharth Patel ◽

...

Keyword(s):

Depressive Symptoms ◽

Basal Ganglia ◽

Magnetic Resonance ◽

Functional Connectivity ◽

Resting State ◽

Animal Studies ◽

Brain Regions ◽

Kynurenine Pathway ◽

Resonance Spectroscopy ◽

The Brain

Inflammation is associated with depressive symptoms including anhedonia in patients with major depression. Nevertheless, the mechanisms by which peripheral inflammatory signals are communicated to the brain to influence central nervous system (CNS) function has yet to be fully elucidated. Based on laboratory animal studies, molecules of the kynurenine pathway (KP), which is activated by inflammation, can readily enter the brain, and generate metabolites that can alter neuronal and glial function, leading to behavioral changes. We therefore examined the relationship between KP metabolites in the plasma and cerebrospinal fluid (CSF) and brain chemistry and neural network function using multi-modal neuroimaging in 49 unmedicated, depressed subjects. CNS measures included 1) biochemical markers of glial dysfunction including glutamate (Glu) and myo-inositol (mI) in the left basal ganglia (LBG) using magnetic resonance spectroscopy (MRS); 2) local activity coherence (regional homogeneity, ReHo) and functional connectivity using resting-state functional magnetic resonance imaging; and 3) anhedonia from the Inventory for Depressive Symptoms-Self Reported. Plasma quinolinic acid (QA) was associated with increases and kynurenic acid (KYNA) and KYNA/QA with decreases in LBG Glu. Plasma kynurenine/tryptophan and CSF 3-hydroxy kynurenine (3HK) were associated with increases in LBG mI. Plasma and CSF KP were associated with decreases in ReHo in LBG and dorsomedial prefrontal cortex (DMPFC), and impaired functional connectivity between these two brain regions. DMPFC-BG connectivity mediated the effect of plasma and CSF KP metabolites on anhedonia. These findings highlight the contribution of KP metabolites to glial and neuronal dysfunction and ultimately behavior in depression.

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Measuring Glycolytic Activity with Hyperpolarized [2H7, U-13C6] D-Glucose in the Naive Mouse Brain under Different Anesthetic Conditions

Metabolites ◽

10.3390/metabo11070413 ◽

2021 ◽

Vol 11 (7) ◽

pp. 413

Author(s):

Emmanuelle Flatt ◽

Bernard Lanz ◽

Yves Pilloud ◽

Andrea Capozzi ◽

Mathilde Hauge Lerche ◽

...

Keyword(s):

Functional Connectivity ◽

Glucose Metabolism ◽

De Novo ◽

Cerebral Metabolism ◽

Resonance Spectroscopy ◽

Hyperpolarized 13C ◽

Glycolytic Activity ◽

The Difference ◽

The Impact ◽

The Brain

Glucose is the primary fuel for the brain; its metabolism is linked with cerebral function. Different magnetic resonance spectroscopy (MRS) techniques are available to assess glucose metabolism, providing complementary information. Our first aim was to investigate the difference between hyperpolarized 13C-glucose MRS and non-hyperpolarized 2H-glucose MRS to interrogate cerebral glycolysis. Isoflurane anesthesia is commonly employed in preclinical MRS, but it affects cerebral hemodynamics and functional connectivity. A combination of low doses of isoflurane and medetomidine is routinely used in rodent fMRI and shows similar functional connectivity, as in awake animals. As glucose metabolism is tightly linked to neuronal activity, our second aim was to assess the impact of these two anesthetic conditions on the cerebral metabolism of glucose. Brain metabolism of hyperpolarized 13C-glucose and 2H-glucose was monitored in two groups of mice in a 9.4 T MRI system. We found that the very different duration and temporal resolution of the two techniques enable highlighting the different aspects in glucose metabolism. We demonstrate (by numerical simulations) that hyperpolarized 13C-glucose reports on de novo lactate synthesis and is sensitive to CMRGlc. We show that variations in cerebral glucose metabolism, under different anesthesia, are reflected differently in hyperpolarized and non-hyperpolarized X-nuclei glucose MRS.

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A comparison of feature extraction methods for prediction of neuropsychological scores from functional connectivity data of stroke patients

Brain Informatics ◽

10.1186/s40708-021-00129-1 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Federico Calesella ◽

Alberto Testolin ◽

Michele De Filippo De Grazia ◽

Marco Zorzi

Keyword(s):

Feature Extraction ◽

Functional Connectivity ◽

Dimensionality Reduction ◽

Verbal Memory ◽

Resting State ◽

Component Analysis ◽

Model Complexity ◽

Stroke Patients ◽

Prediction Ability ◽

The Impact

AbstractMultivariate prediction of human behavior from resting state data is gaining increasing popularity in the neuroimaging community, with far-reaching translational implications in neurology and psychiatry. However, the high dimensionality of neuroimaging data increases the risk of overfitting, calling for the use of dimensionality reduction methods to build robust predictive models. In this work, we assess the ability of four well-known dimensionality reduction techniques to extract relevant features from resting state functional connectivity matrices of stroke patients, which are then used to build a predictive model of the associated deficits based on cross-validated regularized regression. In particular, we investigated the prediction ability over different neuropsychological scores referring to language, verbal memory, and spatial memory domains. Principal Component Analysis (PCA) and Independent Component Analysis (ICA) were the two best methods at extracting representative features, followed by Dictionary Learning (DL) and Non-Negative Matrix Factorization (NNMF). Consistent with these results, features extracted by PCA and ICA were found to be the best predictors of the neuropsychological scores across all the considered cognitive domains. For each feature extraction method, we also examined the impact of the regularization method, model complexity (in terms of number of features that entered in the model) and quality of the maps that display predictive edges in the resting state networks. We conclude that PCA-based models, especially when combined with L1 (LASSO) regularization, provide optimal balance between prediction accuracy, model complexity, and interpretability.

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The Brain Resting-State Functional Connectivity Underlying Violence Proneness: Is It a Reliable Marker for Neurocriminology? A Systematic Review

Behavioral Sciences ◽

10.3390/bs9010011 ◽

2019 ◽

Vol 9 (1) ◽

pp. 11 ◽

Cited By ~ 4

Author(s):

Ángel Romero-Martínez ◽

Macarena González ◽

Marisol Lila ◽

Enrique Gracia ◽

Luis Martí-Bonmatí ◽

...

Keyword(s):

Functional Connectivity ◽

Effective Treatment ◽

Resting State ◽

Brain Structures ◽

Prevention Programs ◽

Angular Gyrus ◽

Resting State Functional Connectivity ◽

Treatment And Prevention ◽

Reliable Marker ◽

The Brain

Introduction: There is growing scientific interest in understanding the biological mechanisms affecting and/or underlying violent behaviors in order to develop effective treatment and prevention programs. In recent years, neuroscientific research has tried to demonstrate whether the intrinsic activity within the brain at rest in the absence of any external stimulation (resting-state functional connectivity; RSFC) could be employed as a reliable marker for several cognitive abilities and personality traits that are important in behavior regulation, particularly, proneness to violence. Aims: This review aims to highlight the association between the RSFC among specific brain structures and the predisposition to experiencing anger and/or responding to stressful and distressing situations with anger in several populations. Methods: The scientific literature was reviewed following the PRISMA quality criteria for reviews, using the following digital databases: PubMed, PsycINFO, Psicodoc, and Dialnet. Results: The identification of 181 abstracts and retrieval of 34 full texts led to the inclusion of 17 papers. The results described in our study offer a better understanding of the brain networks that might explain the tendency to experience anger. The majority of the studies highlighted that diminished RSFC between the prefrontal cortex and the amygdala might make people prone to reactive violence, but that it is also necessary to contemplate additional cortical (i.e. insula, gyrus [angular, supramarginal, temporal, fusiform, superior, and middle frontal], anterior and posterior cingulated cortex) and subcortical brain structures (i.e. hippocampus, cerebellum, ventral striatum, and nucleus centralis superior) in order to explain a phenomenon as complex as violence. Moreover, we also described the neural pathways that might underlie proactive violence and feelings of revenge, highlighting the RSFC between the OFC, ventral striatal, angular gyrus, mid-occipital cortex, and cerebellum. Conclusions. The results from this synthesis and critical analysis of RSFC findings in several populations offer guidelines for future research and for developing a more accurate model of proneness to violence, in order to create effective treatment and prevention programs.

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Putative neural consequences of captivity for elephants and cetaceans

Reviews in the Neurosciences ◽

10.1515/revneuro-2021-0100 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Bob Jacobs ◽

Heather Rally ◽

Catherine Doyle ◽

Lester O’Brien ◽

Mackenzie Tennison ◽

...

Keyword(s):

Basal Ganglia ◽

Behavioral Health ◽

Negative Impact ◽

Well Being ◽

Present Review ◽

Large Mammals ◽

Impoverished Environment ◽

Neural Underpinnings ◽

The Impact ◽

The Brain

Abstract The present review assesses the potential neural impact of impoverished, captive environments on large-brained mammals, with a focus on elephants and cetaceans. These species share several characteristics, including being large, wide-ranging, long-lived, cognitively sophisticated, highly social, and large-brained mammals. Although the impact of the captive environment on physical and behavioral health has been well-documented, relatively little attention has been paid to the brain itself. Here, we explore the potential neural consequences of living in captive environments, with a focus on three levels: (1) The effects of environmental impoverishment/enrichment on the brain, emphasizing the negative neural consequences of the captive/impoverished environment; (2) the neural consequences of stress on the brain, with an emphasis on corticolimbic structures; and (3) the neural underpinnings of stereotypies, often observed in captive animals, underscoring dysregulation of the basal ganglia and associated circuitry. To this end, we provide a substantive hypothesis about the negative impact of captivity on the brains of large mammals (e.g., cetaceans and elephants) and how these neural consequences are related to documented evidence for compromised physical and psychological well-being.

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Computerized physical and cognitive training improves the functional architecture of the brain in adults with Down syndrome: A network science EEG study

Network Neuroscience ◽

10.1162/netn_a_00177 ◽

2020 ◽

pp. 1-21

Author(s):

Alexandra Anagnostopoulou ◽

Charis Styliadis ◽

Panagiotis Kartsidis ◽

Evangelia Romanopoulou ◽

Vasiliki Zilidou ◽

...

Keyword(s):

Down Syndrome ◽

Functional Connectivity ◽

Cognitive Training ◽

Resting State ◽

Network Architecture ◽

Right Hemisphere ◽

Random Network ◽

Brain Activity ◽

Hierarchical Organization ◽

The Brain

Understanding the neuroplastic capacity of people with Down syndrome (PwDS) can potentially reveal the causal relationship between aberrant brain organization and phenotypic characteristics. We used resting-state EEG recordings to identify how a neuroplasticity-triggering training protocol relates to changes in the functional connectivity of the brain’s intrinsic cortical networks. Brain activity of 12 PwDS before and after a 10-week protocol of combined physical and cognitive training was statistically compared to quantify changes in directed functional connectivity in conjunction with psychosomatometric assessments. PwDS showed increased connectivity within the left hemisphere and from left-to-right hemisphere, as well as increased physical and cognitive performance. Our findings reveal a strong adaptive neuroplastic reorganization as a result of the training that leads to a less-random network with a more pronounced hierarchical organization. Our results go beyond previous findings by indicating a transition to a healthier, more efficient, and flexible network architecture, with improved integration and segregation abilities in the brain of PwDS. Resting-state electrophysiological brain activity is used here for the first time to display meaningful relationships to underlying Down syndrome processes and outcomes of importance in a translational inquiry. This trial is registered with ClinicalTrials.gov Identifier NCT04390321.

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Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

10.1101/742833 ◽

2019 ◽

Author(s):

Milou Straathof ◽

Michel R.T. Sinke ◽

Theresia J.M. Roelofs ◽

Erwin L.A. Blezer ◽

R. Angela Sarabdjitsingh ◽

...

Keyword(s):

Functional Connectivity ◽

Structure Function ◽

Rat Brain ◽

Resting State ◽

Structural Connectivity ◽

Distinct Structure ◽

Macro Scale ◽

Function Relationship ◽

The Brain ◽

Meso Scale

AbstractAn improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in many disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional connectivity and macro-scale diffusion-based structural connectivity, but no correspondence between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Locally, strong functional connectivity was found in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Distinct structure-function relationships across the brain can explain the organization of networks and may underlie variations in the impact of structural damage on functional networks and behavior.

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Local GABA concentration is related to network-level resting functional connectivity

eLife ◽

10.7554/elife.01465 ◽

2014 ◽

Vol 3 ◽

Cited By ~ 86

Author(s):

Charlotte J Stagg ◽

Velicia Bachtiar ◽

Ugwechi Amadi ◽

Christel A Gudberg ◽

Andrei S Ilie ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Primary Motor Cortex ◽

Empirical Studies ◽

Network Connectivity ◽

Resting State Fmri ◽

Resonance Spectroscopy ◽

Resting State Networks ◽

Inhibitory Neurotransmitter ◽

Motor Network

Anatomically plausible networks of functionally inter-connected regions have been reliably demonstrated at rest, although the neurochemical basis of these ‘resting state networks’ is not well understood. In this study, we combined magnetic resonance spectroscopy (MRS) and resting state fMRI and demonstrated an inverse relationship between levels of the inhibitory neurotransmitter GABA within the primary motor cortex (M1) and the strength of functional connectivity across the resting motor network. This relationship was both neurochemically and anatomically specific. We then went on to show that anodal transcranial direct current stimulation (tDCS), an intervention previously shown to decrease GABA levels within M1, increased resting motor network connectivity. We therefore suggest that network-level functional connectivity within the motor system is related to the degree of inhibition in M1, a major node within the motor network, a finding in line with converging evidence from both simulation and empirical studies.

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Brain network dynamics correlate with personality traits

10.1101/702266 ◽

2019 ◽

Cited By ~ 1

Author(s):

Aya Kabbara ◽

Veronique Paban ◽

Arnaud Weill ◽

Julien Modolo ◽

Mahmoud Hassan

Keyword(s):

Functional Connectivity ◽

Personality Traits ◽

Resting State ◽

Brain Networks ◽

Neural Substrates ◽

Brain Network ◽

Functional Brain ◽

Human Connectome Project ◽

Functional Brain Networks ◽

The Brain

AbstractIntroductionIdentifying the neural substrates underlying the personality traits is a topic of great interest. On the other hand, it is now established that the brain is a dynamic networked system which can be studied using functional connectivity techniques. However, much of the current understanding of personality-related differences in functional connectivity has been obtained through the stationary analysis, which does not capture the complex dynamical properties of brain networks.ObjectiveIn this study, we aimed to evaluate the feasibility of using dynamic network measures to predict personality traits.MethodUsing the EEG/MEG source connectivity method combined with a sliding window approach, dynamic functional brain networks were reconstructed from two datasets: 1) Resting state EEG data acquired from 56 subjects. 2) Resting state MEG data provided from the Human Connectome Project. Then, several dynamic functional connectivity metrics were evaluated.ResultsSimilar observations were obtained by the two modalities (EEG and MEG) according to the neuroticism, which showed a negative correlation with the dynamic variability of resting state brain networks. In particular, a significant relationship between this personality trait and the dynamic variability of the temporal lobe regions was observed. Results also revealed that extraversion and openness are positively correlated with the dynamics of the brain networks.ConclusionThese findings highlight the importance of tracking the dynamics of functional brain networks to improve our understanding about the neural substrates of personality.

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