Neurobiological Properties Research Articles

Childhood Trauma, Emotional Awareness, and Neural Correlates of Long-Term Nicotine Smoking

Temporal dynamic measures provide insight into the neurobiological properties of nicotine use. It is critical to determine whether brain-based measures are associated with substance use risk factors, such as childhood trauma-related emotion dysregulation. To assess temporal dynamic differences based on smoking status and examine the associations between childhood trauma, alexithymia, nicotine smoking, and default mode network (DMN) states. This cross-sectional study was conducted in the Baltimore, Maryland, area at the National Institute on Drug Abuse. Participants included individuals aged 18 to 65 years who smoked nicotine long term and matched controls with no co-occurring substance use or psychiatric disorders. Participants were enrolled from August 8, 2013, to August 9, 2022. Analysis was conducted from August 2022 to July 2023. Long-term nicotine smoking. The main outcome was temporal dynamic differences based on smoking status. Coactivation pattern analysis was conducted based on 16-minute resting-state functional magnetic resonance imaging; total time in, persistence of, and frequency of transitions into states were evaluated. The associations between childhood trauma (Childhood Trauma Questionnaire), alexithymia (20-item Toronto Alexithymia Scale), and DMN temporal dynamics were assessed. The sample included 204 participants (102 individuals who smoked nicotine and 102 control individuals) with a mean (SD) age of 37.53 (10.64) years (109 [53.4%] male). Compared with controls, individuals who smoked nicotine spent more time in the frontoinsular DMN (FI-DMN) state (mean difference, 25.63 seconds; 95% CI, 8.05-43.20 seconds; η2p = 0.04; P = .004 after Bonferroni correction). In those who smoked nicotine, greater alexithymia was associated with less time spent in the FI-DMN state (r, -0.26; 95% CI, -0.44 to -0.07; P = .007). In a moderated mediation analysis, alexithymia mediated the association between childhood trauma and time spent in the FI-DMN state only in individuals who smoked nicotine (c' = -0.24; 95% CI, -0.58 to -0.03; P = .02). Compared with controls, individuals who smoked nicotine spent more time in the FI-DMN state. Among those who smoked nicotine, childhood trauma-related alexithymia was associated with less time spent in the FI-DMN state, indicating that considering trauma-related factors may reveal alternative neurobiological underpinnings of substance use. These data may aid in reconciling contradictory findings in prior literature regarding the role of FI-DMN regions in substance use.

Hippocampal microstructure, but not macrostructure, mediates age differences in episodic memory.

Separate unimodal magnetic resonance imaging (MRI) literatures have shown that hippocampal gray matter macrostructure (volume) and microstructure (diffusion) decline with age and relate to episodic memory performance, with multimodal MRI studies reporting that episodic memory may be better explained by a combination of these metrics. However, these effects are often assessed independent of age or only within older adults and therefore do not address whether these distinct modalities explain variance in (i.e, mediate) the effect of age on episodic memory. Here, we simultaneously examined the unique and joint contribution of hippocampal volume and diffusion to age-related differences in episodic memory in 83 younger and 61 older adults who underwent a T1- and diffusion-weighted MRI and completed the Rey Auditory Verbal Learning Test. As expected, older age was significantly related to smaller volume and higher diffusion (intracellular, dispersion, and free) in bilateral hippocampus and to worse episodic memory performance (immediate and delayed free recall, recognition). Structural equation modelling revealed that the age-memory relationship was significantly mediated by hippocampal diffusion, but not volume. A non-significant influential indirect effect further revealed that the structural metrics did not jointly mediate the age-memory relationship. Together, these findings indicate that hippocampal microstructure uniquely contributes to age-related differences in episodic memory and suggest that volume and diffusion capture distinct neurobiological properties of hippocampal gray matter.

An Overview of the Neurotrophic and Neuroprotective Properties of the Psychoactive Drug Lithium as an Autophagy Modulator in Neurodegenerative Conditions.

For both short-term and long-term treatment of bipolar disorder, lithium is a prototypical mood stabilizer. Lithium's neuroprotective properties were revealed by cumulative translational research, which opened the door to reforming the chemical as a treatment for neurodegenerative illnesses. The control of homeostatic systems such as oxidative stress, autophagy, apoptosis, mitochondrial function, and inflammation underlies lithium's neuroprotective characteristics. The fact that lithium inhibits the enzymes inositol monophosphatase (IMPase) and glycogen synthase kinase (GSK)-3 may be the cause of the various intracellular reactions. In this article, we review lithium's neurobiological properties, as demonstrated by its neurotrophic and neuroprotective capabilities, as well as translational studies in cells in culture and in animal models of Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), Prion disease, amyotrophic lateral sclerosis (ALS), ischemic stroke, and neuronal ceroid lipofuscinosis (NCL), discussing the justification for the drug's use in the treatment of these neurodegenerative disorders.

Neural Representation of Donating Time and Money.

Volunteering and charitable donations are two common forms of prosocial behavior, yet it is unclear whether these other-benefitting behaviors are supported by the same or different neurobiological mechanisms. During an fMRI task, 40 participants (20 female-identifying; age: mean = 18.92 years, range = 18.32-19.92 years) contributed their time (in minutes) and money (in dollars) to a variety of local charities. With the maximum amount of time and money that participants could spend on these charities, they did not differentially donate their time and money. At the neural level, donating time and money both showed activations in brain regions involved in cognitive control (e.g., dorsolateral PFC) and affective processing (e.g., dorsal anterior cingulate cortex), but donating time recruited regions involved in reward valuation (e.g., ventral striatum) and mentalizing (e.g., temporal pole) to a greater extent than donating money. Further, the precuneus, which is also a region involved in mentalizing, more strongly tracked the varying amount of money than time donated, suggesting that the precuneus may be more sensitive to the increasing magnitude of a nonsocial exchange (e.g., donating money is a financial exchange) than a social exchange (e.g., donating time is an interpersonal exchange). Our findings elucidate shared as well as distinct neurobiological properties of two prosocial behaviors, which have implications for how humans share different resources to positively impact their community.SIGNIFICANCE STATEMENT Prosocial behaviors broadly characterize how humans act to benefit others. Various prosocial behaviors, such as volunteering and charitable donations, share the goal of positively contributing to community. Our study identifies brain regions that may serve as ubiquitous neurobiological markers of community-based prosocial behaviors. Despite this shared goal, our study also shows that the human brain responds to donating time and money in diverging ways, such that brain regions associated with processing emotional reward and thinking about others are more strongly recruited for donating time than for money. Therefore, our study sheds light on how different personal resources, such as one's time and money, within a prosocial context are represented in the brain.

Mapping high-grade glioma immune infiltration to 5-ALA fluorescence levels: TCGA data computation, classical histology, and digital image analysis.

Resection of high-grade gliomas has been considerably improved by 5-aminolevulinic acid (5-ALA). However, not all neurobiological properties of 5-ALA are fully understood. Specifically, potential differences in immune infiltration have not been conclusively examined, despite recent reports that immune cells might play a role. Thus, we here provide a systematic mapping of immune infiltration of different 5-ALA fluorescence levels. Tumor-associated macrophages (CD68, CD163), cytotoxic T cells (CD8), and regulatory T cells (FoxP3) were quantified via three methods. First, data from The Cancer Genome Atlas (TCGA) of 172 patients was examined for correlations between 5-ALA fluorescence-related mRNA expression signatures and immune markers. Second, as classical histology, 508 stained slides from 39 high-grade glioma patients were analysed semi-quantitatively by two independent reviewers, generating 1016 data points. Third, digital image analysis was performed with automated scanning and algorithm-based cell quantification. TCGA mRNA data from 172 patients showed a direct, significant correlation between 5-ALA signatures and immune markers (p < 0.001). However, we were not able to confirm this finding in the here studied initial set of 39 patient histologies where we found a comparable immune infiltration in different fluorescence levels. Digital image analysis correlated excellently with standard histology. With mapping the immune infiltration pattern of different 5-ALA categories, we are adding fundamental basic insights to the field of 5-ALA and glioma biology. The observation that a significant correlation in TCGA data did not fully translate to detectable differences in immune infiltration in first histology data warrants further investigation in larger cohorts.

Neuropharmacological computational analysis of longitudinal electroencephalograms in clozapine-treated patients with schizophrenia using hierarchical dynamic causal modeling

The hierarchical characteristics of the brain are prominent in the pharmacological treatment of psychiatric diseases, primarily targeting cellular receptors that extend upward to intrinsic connectivity within a region, interregional connectivity, and, consequently, clinical observations such as an electroencephalogram (EEG). To understand the long-term effects of neuropharmacological intervention on neurobiological properties at different hierarchical levels, we explored long-term changes in neurobiological parameters of an N-methyl-D-aspartate canonical microcircuit model (CMM-NMDA) in the default mode network (DMN) and auditory hallucination network (AHN) using dynamic causal modeling of longitudinal EEG in clozapine-treated patients with schizophrenia. The neurobiological properties of the CMM-NMDA model associated with symptom improvement in schizophrenia were found across hierarchical levels, from a reduced membrane capacity of the deep pyramidal cell and intrinsic connectivity with the inhibitory population in DMN and intrinsic and extrinsic connectivity in AHN. The medication duration mainly affects the intrinsic connectivity and NMDA time constant in DMN. Virtual perturbation analysis specified the contribution of each parameter to the cross-spectral density (CSD) of the EEG, particularly intrinsic connectivity and membrane capacitances for CSD frequency shifts and progression. It further reveals that excitatory and inhibitory connectivity complements frequency-specific CSD changes, notably the alpha frequency band in DMN. Positive and negative synergistic interactions exist between neurobiological properties primarily within the same region in patients treated with clozapine. The current study shows how computational neuropharmacology helps explore the multiscale link between neurobiological properties and clinical observations and understand the long-term mechanism of neuropharmacological intervention reflected in clinical EEG.

Urethane provides an unparalleled anaesthetic model for natural sleep: Commentary on Mondino et al., 2022.

Urethane provides an unparalleled anaesthetic model for natural sleep: Commentary on Mondino et al., 2022.

Using The Wire in medical education

The television series The Wire originally aired on June 2, 2002 with the pilot episode titled “The Target”. The opening scene depicts a discussion between Baltimore detective Jimmy McNulty and a witness to the murder of a teenager named Omar Betts, otherwise known as “Snot Boogie”. The witness goes into detail about the murder, describing how Snot would join a weekly back-alley dice game and would rob from the cash pot when the bets grew sufficiently large. This occurred until one day a newcomer entered the game and shot and killed Snot for stealing the money. Perplexed, McNulty asked why regulars would allow Snot Boogie to join the game each week knowing that in advance he would rob it. To this the witness responds “Got to. It's America man.” Childhood maltreatment and its role in the development of pain and psychopathologyChildhood maltreatment represents a form of trauma capable of altering fundamental neurobiological properties and negatively impacting neurodevelopmental processes. An outcome of childhood maltreatment is the emergence of psychopathology, which might become evident during childhood or adolescence, but might also project into adulthood. In this Review, we propose a biobehavioural framework in which childhood maltreatment and the associated aberrant neurobiological mechanisms and behavioural processes additionally lead to the onset of altered pain processing and, ultimately, the existence of pain syndromes. Full-Text PDF

Hippocampal cholinergic receptors and the mTOR participation in fear-motivated inhibitory avoidance extinction memory

Evidence has demonstrated the hippocampal cholinergic system and the mammalian target of rapamycin (mTOR) participation during the memory formation of aversive events. This study assessed the role of these systems in the hippocampus for the extinction memory process by submitting male Wistar rats to fear-motivated step-down inhibitory avoidance (IA). The post-extinction session administration of the nicotinic and muscarinic cholinergic receptor antagonists, mecamylamine and scopolamine, respectively, both at doses of 2 µg/µl/side, and rapamycin, an mTOR inhibitor (0.02 µg/µl/side), into the CA1 region of the dorsal hippocampus, impaired the IA extinction memory. Furthermore, the nicotinic and muscarinic cholinergic receptor agonists, nicotine and muscarine, respectively, had a dose-dependent effect on the IA extinction memory when administered intra-CA1, immediately after the extinction session. Nicotine (0.6 µg/µl/side) and muscarine (0.02 µg/µl/side), respectively, had no effect, while the higher doses (6 and 2 µg/µl/side, respectively) impaired the IA extinction memory. Interestingly, the co-administration of muscarine at the lower dose blocked the impairment that was induced by rapamycin. This effect was not observed when nicotine at the lower dose was co-administered. These results have demonstrated the participation of the cholinergic receptors and mTOR in the hippocampus for IA extinction, and that the cholinergic agonists had a dose-dependent effect on the IA extinction memory. This study provides insights related to the behavioural aspects and the neurobiological properties underlying the early stage of fear-motivated IA extinction memory consolidation and suggests that there is hippocampal muscarinic receptor participation independent of mTOR in this memory process.

The Rise and Fall of Slow Wave Tides: Vacillations in Coupled Slow Wave/Spindle Pairing Shift the Composition of Slow Wave Activity in Accordance With Depth of Sleep.

Slow wave activity (SWA) during sleep is associated with synaptic regulation and memory processing functions. Each cycle of non-rapid-eye-movement (NREM) sleep demonstrates a waxing and waning amount of SWA during the transitions between stages N2 and N3 sleep, and the deeper N3 sleep is associated with an increased density of SWA. Further, SWA is an amalgam of different types of slow waves, each identifiable by their temporal coupling to spindle subtypes with distinct physiological features. The objectives of this study were to better understand the neurobiological properties that distinguish different slow wave and spindle subtypes, and to examine the composition of SWA across cycles of NREM sleep. We further sought to explore changes in the composition of NREM cycles that occur among aging adults. To address these goals, we analyzed subsets of data from two well-characterized cohorts of healthy adults: (1) The DREAMS Subjects Database (n = 20), and (2) The Cleveland Family Study (n = 60). Our analyses indicate that slow wave/spindle coupled events can be characterized as frontal vs. central in their relative distribution between electroencephalography (EEG) channels. The frontal predominant slow waves are identifiable by their coupling to late-fast spindles and occur more frequently during stage N3 sleep. Conversely, the central-associated slow waves are identified by coupling to early-fast spindles and favor occurrence during stage N2 sleep. Together, both types of slow wave/spindle coupled events form the composite of SWA, and their relative contribution to the SWA rises and falls across cycles of NREM sleep in accordance with depth of sleep. Exploratory analyses indicated that older adults produce a different composition of SWA, with a shift toward the N3, frontal subtype, which becomes increasingly predominant during cycles of NREM sleep. Overall, these data demonstrate that subtypes of slow wave/spindle events have distinct cortical propagation patterns and differ in their distribution across lighter vs. deeper NREM sleep. Future efforts to understand how slow wave sleep and slow wave/spindle coupling impact memory performance and neurological disease may benefit from examining the composition of SWA to avoid potential confounds that may occur when comparing dissimilar neurophysiological events.

Using Advanced Diffusion-Weighted Imaging to Predict Cell Counts in Gray Matter: Potential and Pitfalls.

Recent advances in diffusion imaging have given it the potential to non-invasively detect explicit neurobiological properties, beyond what was previously possible with conventional structural imaging. However, there is very little known about what cytoarchitectural properties these metrics, especially those derived from newer multi-shell models like Neurite Orientation Dispersion and Density Imaging (NODDI) correspond to. While these diffusion metrics do not promise any inherent cell type specificity, different brain cells have varying morphologies, which could influence the diffusion signal in distinct ways. This relationship is currently not well-characterized. Understanding the possible cytoarchitectural signatures of diffusion measures could allow them to estimate important neurobiological properties like cell counts, potentially resulting in a powerful clinical diagnostic tool. Here, using advanced diffusion imaging (NODDI) in the mouse brain, we demonstrate that different regions have unique relationships between cell counts and diffusion metrics. We take advantage of this exclusivity to introduce a framework to predict cell counts of different types of cells from the diffusion metrics alone, in a region-specific manner. We also outline the challenges of reliably developing such a model and discuss the precautions the field must take when trying to tie together medical imaging modalities and histology.

Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights

A cardinal feature of the neocortex is the progressive increase of the spatial receptive fields along the cortical hierarchy. Recently, theoretical and experimental findings have shown that the temporal response windows also gradually enlarge, so that early sensory neural circuits operate on short timescales whereas higher-association areas are capable of integrating information over a long period of time. While an increased receptive field is accounted for by spatial summation of inputs from neurons in an upstream area, the emergence of timescale hierarchy cannot be readily explained, especially given the dense interareal cortical connectivity known in the modern connectome. To uncover the required neurobiological properties, we carried out a rigorous analysis of an anatomically based large-scale cortex model of macaque monkeys. Using a perturbation method, we show that the segregation of disparate timescales is defined in terms of the localization of eigenvectors of the connectivity matrix, which depends on three circuit properties: 1) a macroscopic gradient of synaptic excitation, 2) distinct electrophysiological properties between excitatory and inhibitory neuronal populations, and 3) a detailed balance between long-range excitatory inputs and local inhibitory inputs for each area-to-area pathway. Our work thus provides a quantitative understanding of the mechanism underlying the emergence of timescale hierarchy in large-scale primate cortical networks.

Behavioral aspects and neurobiological properties underlying medical cannabis treatment in Shank3 mouse model of autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disease with a wide spectrum of manifestation. The core symptoms of ASD are persistent deficits in social communication, and restricted and repetitive patterns of behavior, interests, or activities. These are often accompanied by intellectual disabilities. At present, there is no designated effective treatment for the core symptoms and co-morbidities of ASD. Recently, interest is rising in medical cannabis as a treatment for ASD, with promising clinical data. However, there is a notable absence of basic pre-clinical research in this field. In this study, we investigate the behavioral and biochemical effects of long-term oral treatment with CBD-enriched medical cannabis oil in a human mutation-based Shank3 mouse model of ASD. Our findings show that this treatment alleviates anxiety and decreases repetitive grooming behavior by over 70% in treated mutant mice compared to non-treated mutant mice. Furthermore, we were able to uncover the involvement of CB1 receptor (CB1R) signaling in the Avidekel oil mechanism, alongside a mitigation of cerebrospinal fluid (CSF) glutamate concentrations. Subsequently, RNA sequencing (RNA seq) of cerebellar brain samples revealed changes in mRNA expression of several neurotransmission-related genes post-treatment. Finally, our results question the relevancy of CBD enrichment of medical cannabis for treating the core symptoms of ASD, and emphasize the importance of the THC component for alleviating deficits in repetitive and social behaviors in ASD.

Is There Justification to Treat Neurodegenerative Disorders by Repurposing Drugs? The Case of Alzheimer's Disease, Lithium, and Autophagy.

Lithium is the prototype mood-stabilizer used for acute and long-term treatment of bipolar disorder. Cumulated translational research of lithium indicated the drug’s neuroprotective characteristics and, thereby, has raised the option of repurposing it as a drug for neurodegenerative diseases. Lithium’s neuroprotective properties rely on its modulation of homeostatic mechanisms such as inflammation, mitochondrial function, oxidative stress, autophagy, and apoptosis. This myriad of intracellular responses are, possibly, consequences of the drug’s inhibition of the enzymes inositol-monophosphatase (IMPase) and glycogen-synthase-kinase (GSK)-3. Here we review lithium’s neurobiological properties as evidenced by its neurotrophic and neuroprotective properties, as well as translational studies in cells in culture, in animal models of Alzheimer’s disease (AD) and in patients, discussing the rationale for the drug’s use in the treatment of AD.

MORC1 methylation and BDI are associated with microstructural features of the hippocampus and medial prefrontal cortex

BackgroundAlterations in the hippocampus and prefrontal cortex (PFC) have frequently been reported in depressed patients. These parameters might prove to be a consistent finding in depression. In addition, peripheral DNA methylation of the MORC1 gene promoter showed stable associations with depression across independent samples. However, the question arises whether MORC1, supposedly acting as transcription factor, might also be involved in neurobiological alterations accompanying depression. This study further analyses the role of MORC1 in depression by investigating a potential correlation between peripheral MORC1 DNA methylation and neuronal structural properties previously associated with depression in humans. MethodsBeck Depression Inventory (BDI) was assessed in 52 healthy participants. DNA was extracted from buccal cells and MORC1 methylation correlated with micro- and macrostructural properties derived from magnetic resonance imaging (MRI) and neurite orientation dispersion and density imaging (NODDI) in the hippocampus and medial prefrontal cortex (mPFC). ResultsMORC1 methylation was associated with volume reduction and neurite orientation dispersion and density markers in the hippocampus and mPFC. BDI was positively associated with neurite orientation dispersion and density markers in the hippocampus. LimitationsThe study was conducted in a small sample of healthy participants with subclinical depressive symptoms. Peripheral tissue was analyzed. ConclusionWe found significant negative associations between peripheral MORC1 methylation and macro- and microstructural markers in the hippocampus and mPFC. Thus, MORC1 might be involved in neurobiological properties. Studies investigating neuronal methylation patterns of MORC1 are needed to support this hypothesis.

Breast Milk Components and Neurodevelopment of Children

Breast milk is considered the gold standard in pediatric nutrition. It contains a wide range of nutrients and other bioactive factors that support enteric and immunologic development of neonates. Some of these constituents have neurobiological properties that play vital role in early brain development and facilitate cognitive development. Understanding the role of these functional nutrients in modulating developmental processes in the brain is emerging area of research. These developmental events depend not only on availability of nutrients, but it also depends on a variety of growth factors and proteins. These components are transported from the mother to the fetus via the placenta prenatally and postnatally through milk. Many studies have highlighted a positive association between breastfeeding on structural brain development, such as increased white matter development and increased cortical thickness. Reports also suggest beneficial effects of breastfeeding on brain and cognitive development from infancy to in adolescence. This review discusses various components in breast milk components which can influence neurodevelopment in children.

Statistical decision theory and multiscale analyses of human brain data

BackgroundIn the era of Big Data, large scale electrophysiological data from animal and human studies are abundant. These data contain information at multiple spatiotemporal scales. However, current approaches for the analysis of electrophysiological data often focus on a single spatiotemporal scale only. New methodWe discuss a multiscale approach for the analysis of electrophysiological data. This is based on combining neural models that describe brain data at different scales. It allows us to make laminar-specific inferences about neurobiological properties of cortical sources using non invasive human electrophysiology data. ResultsWe provide a mathematical proof of this approach using statistical decision theory. We also consider its extensions to brain imaging studies including data from the same subjects performing different tasks. As an illustration, we show that changes in gamma oscillations between different people might originate from differences in recurrent connection strengths of inhibitory interneurons in layers 5/6. Comparison with existing methodsThis is a new approach that follows up on our recent work. It is different from other approaches where the scale of spatiotemporal dynamics is fixed. ConclusionsWe discuss a multiscale approach for the analysis of human MEG data. This uses a neural mass model that includes constraints informed by a compartmental model. This has two advantages. First, it allows us to find differences in cortical laminar dynamics and understand neurobiological properties like neuromodulation, excitation to inhibition balance etc. using non invasive data. Second, it allows us to validate macroscale models by exploiting animal data.

Breast Milk Components and Neurodevelopment of Children

Breast milk is considered the gold standard in pediatric nutrition. It contains a wide range of nutrients and other bioactive factors that support enteric and immunologic development of neonates. Some of these constituents have neurobiological properties that play vital role in early brain development and facilitate cognitive development. Understanding the role of these functional nutrients in modulating developmental processes in the brain is emerging area of research. These developmental events depend not only on availability of nutrients, but it also depends on a variety of growth factors and proteins. These components are transported from the mother to the fetus via the placenta prenatally and postnatally through milk. Many studies have highlighted a positive association between breastfeeding on structural brain development, such as increased white matter development and increased cortical thickness. Reports also suggest beneficial effects of breastfeeding on brain and cognitive development from infancy to in adolescence. This review discusses various components in breast milk components which can influence neurodevelopment in children.

Characterizing the gradients of structural covariance in the human hippocampus

The hippocampus is a plastic brain structure that has been associated with a range of behavioral aspects but also shows vulnerability to the most frequent neurocognitive diseases. Different aspects of its organization have been revealed by studies probing its different neurobiological properties. In particular, histological work has shown a pattern of differentiation along the proximal-distal dimension, while studies examining functional properties and large-scale functional integration have primarily highlighted a pattern of differentiation along the anterior-posterior dimension.To better understand how these organizational dimensions underlie the pattern of structural covariance (SC) in the human hippocampus, we here applied a non-linear decomposition approach, disentangling the major modes of variation, to the pattern of gray matter volume correlation of hippocampus voxels with the rest of the brain in a sample of 377 healthy young adults. We additionally investigated the consistency of the derived gradients in an independent sample of life-span adults and also examined the relationships between these major modes of variations and the patterns derived from microstructure and functional connectivity mapping.Our results showed that similar major modes of SC-variability are identified across the two independent datasets. The major dimension of variation found in SC runs along the hippocampal anterior-posterior axis and followed closely the principal dimension of functional differentiation, suggesting an influence of network level interaction in this major mode of morphological variability. The second main mode of variability in the SC showed a gradient along the dorsal-ventral axis, and was moderately related to variability in hippocampal microstructural properties.Thus our results depicting relatively reliable patterns of SC-variability within the hippocampus show an interplay between the already known organizational principles on the pattern of variability in hippocampus’ macrostructural properties. This study hence provides a first insight on the underlying organizational forces generating different co-plastic modes within the human hippocampus that may, in turn, help to better understand different vulnerability patterns of this crucial structure in different neurological and psychiatric diseases.

Microstructural Alterations in Hippocampal Subfields Mediate Age-Related Memory Decline in Humans.

Aging, even in the absence of clear pathology of dementia, is associated with cognitive decline. Neuroimaging, especially diffusion-weighted imaging, has been highly valuable in understanding some of these changes in live humans, non-invasively. Traditional tensor techniques have revealed that the integrity of the fornix and other white matter tracts significantly deteriorates with age, and that this deterioration is highly correlated with worsening cognitive performance. However, traditional tensor techniques are still not specific enough to indict explicit microstructural features that may be responsible for age-related cognitive decline and cannot be used to effectively study gray matter properties. Here, we sought to determine whether recent advances in diffusion-weighted imaging, including Neurite Orientation Dispersion and Density Imaging (NODDI) and Constrained Spherical Deconvolution, would provide more sensitive measures of age-related changes in the microstructure of the medial temporal lobe. We evaluated these measures in a group of young (ages 20–38 years old) and older (ages 59–84 years old) adults and assessed their relationships with performance on tests of cognition. We found that the fiber density (FD) of the fornix and the neurite density index (NDI) of the fornix, hippocampal subfields (DG/CA3, CA1, and subiculum), and parahippocampal cortex, varied as a function of age in a cross-sectional cohort. Moreover, in the fornix, DG/CA3, and CA1, these changes correlated with memory performance on the Rey Auditory Verbal Learning Test (RAVLT), even after regressing out the effect of age, suggesting that they were capturing neurobiological properties directly related to performance in this task. These measures provide more details regarding age-related neurobiological properties. For example, a change in fiber density could mean a reduction in axonal packing density or myelination, and the increase in NDI observed might be explained by changes in dendritic complexity or even sprouting. These results provide a far more comprehensive view than previously determined on the possible system-wide processes that may be occurring because of healthy aging and demonstrate that advanced diffusion-weighted imaging is evolving into a powerful tool to study more than just white matter properties.