scholarly journals HIV Infection Is Associated with Attenuated Frontostriatal Intrinsic Connectivity: A Preliminary Study

2015 ◽  
Vol 21 (3) ◽  
pp. 203-213 ◽  
Author(s):  
Jonathan C. Ipser ◽  
Gregory G. Brown ◽  
Amanda Bischoff-Grethe ◽  
Colm G. Connolly ◽  
Ronald J. Ellis ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Brain Regions ◽  
Group Differences ◽  
Hiv Rna ◽  
Functional Connections ◽  
Intrinsic Connectivity ◽  
Dorsolateral Prefrontal ◽  
Independent Replication ◽  
Subcortical Regions ◽  
The Brain

AbstractHIV-associated cognitive impairments are prevalent, and are consistent with injury to both frontal cortical and subcortical regions of the brain. The current study aimed to assess the association of HIV infection with functional connections within the frontostriatal network, circuitry hypothesized to be highly vulnerable to HIV infection. Fifteen HIV-positive and 15 demographically matched control participants underwent 6 min of resting-state functional magnetic resonance imaging (RS-fMRI). Multivariate group comparisons of age-adjusted estimates of connectivity within the frontostriatal network were derived from BOLD data for dorsolateral prefrontal cortex (DLPFC), dorsal caudate and mediodorsal thalamic regions of interest. Whole-brain comparisons of group differences in frontostriatal connectivity were conducted, as were pairwise tests of connectivity associations with measures of global cognitive functioning and clinical and immunological characteristics (nadir and current CD4 count, duration of HIV infection, plasma HIV RNA). HIV – associated reductions in connectivity were observed between the DLPFC and the dorsal caudate, particularly in younger participants (<50 years, N=9). Seropositive participants also demonstrated reductions in dorsal caudate connectivity to frontal and parietal brain regions previously demonstrated to be functionally connected to the DLPFC. Cognitive impairment, but none of the assessed clinical/immunological variables, was also associated with reduced frontostriatal connectivity. In conclusion, our data indicate that HIV is associated with attenuated intrinsic frontostriatal connectivity. Intrinsic connectivity of this network may therefore serve as a marker of the deleterious effects of HIV infection on the brain, possibly via HIV-associated dopaminergic abnormalities. These findings warrant independent replication in larger studies. (JINS, 2015, 21, 1–11)

scholarly journals Structured sequence processing and combinatorial binding: neurobiologically and computationally informed hypotheses

2019 ◽  
Vol 375 (1791) ◽  
pp. 20190304 ◽  
Author(s):  
Ryan Calmus ◽  
Benjamin Wilson ◽  
Yukiko Kikuchi ◽  
Christopher I. Petkov
Keyword(s):  
Temporal Cortex ◽  
Brain Regions ◽  
Position Information ◽  
Sequence Processing ◽  
Oscillatory Dynamics ◽  
Structured Representations ◽  
Dorsolateral Prefrontal ◽  
Frontal Operculum ◽  
Structured Information ◽  
The Brain

Understanding how the brain forms representations of structured information distributed in time is a challenging endeavour for the neuroscientific community, requiring computationally and neurobiologically informed approaches. The neural mechanisms for segmenting continuous streams of sensory input and establishing representations of dependencies remain largely unknown, as do the transformations and computations occurring between the brain regions involved in these aspects of sequence processing. We propose a blueprint for a neurobiologically informed and informing computational model of sequence processing (entitled: Vector-symbolic Sequencing of Binding INstantiating Dependencies, or VS-BIND). This model is designed to support the transformation of serially ordered elements in sensory sequences into structured representations of bound dependencies, readily operates on multiple timescales, and encodes or decodes sequences with respect to chunked items wherever dependencies occur in time. The model integrates established vector symbolic additive and conjunctive binding operators with neurobiologically plausible oscillatory dynamics, and is compatible with modern spiking neural network simulation methods. We show that the model is capable of simulating previous findings from structured sequence processing tasks that engage fronto-temporal regions, specifying mechanistic roles for regions such as prefrontal areas 44/45 and the frontal operculum during interactions with sensory representations in temporal cortex. Finally, we are able to make predictions based on the configuration of the model alone that underscore the importance of serial position information, which requires input from time-sensitive cells, known to reside in the hippocampus and dorsolateral prefrontal cortex. This article is part of the theme issue ‘Towards mechanistic models of meaning composition’.

scholarly journals Neural Correlates of Group Bias During Natural Viewing

2018 ◽  
Vol 29 (8) ◽  
pp. 3380-3389
Author(s):  
Timothy J Andrews ◽  
Ryan K Smith ◽  
Richard L Hoggart ◽  
Philip I N Ulrich ◽  
Andre D Gouws
Keyword(s):  
Time Course ◽  
Social Groups ◽  
Sensory Information ◽  
Brain Regions ◽  
Group Differences ◽  
Neural Basis ◽  
Brain Responses ◽  
The World ◽  
High Level ◽  
The Brain

Abstract Individuals from different social groups interpret the world in different ways. This study explores the neural basis of these group differences using a paradigm that simulates natural viewing conditions. Our aim was to determine if group differences could be found in sensory regions involved in the perception of the world or were evident in higher-level regions that are important for the interpretation of sensory information. We measured brain responses from 2 groups of football supporters, while they watched a video of matches between their teams. The time-course of response was then compared between individuals supporting the same (within-group) or the different (between-group) team. We found high intersubject correlations in low-level and high-level regions of the visual brain. However, these regions of the brain did not show any group differences. Regions that showed higher correlations for individuals from the same group were found in a network of frontal and subcortical brain regions. The interplay between these regions suggests a range of cognitive processes from motor control to social cognition and reward are important in the establishment of social groups. These results suggest that group differences are primarily reflected in regions involved in the evaluation and interpretation of the sensory input.

scholarly journals Identifying Brain Abnormalities with Schizophrenia Based on a Hybrid Feature Selection Technology

2019 ◽  
Vol 9 (10) ◽  
pp. 2148 ◽  
Author(s):  
Chen Qiao ◽  
Lujia Lu ◽  
Lan Yang ◽  
Paul J. Kennedy
Keyword(s):  
Feature Selection ◽  
Feature Selection Method ◽  
Brain Regions ◽  
Selection Method ◽  
Small Sample ◽  
Brain Abnormalities ◽  
Network Analyses ◽  
Functional Connections ◽  
The Brain ◽  
Abnormal Brain

Many medical imaging data, especially the magnetic resonance imaging (MRI) data, usually have a small sample size, but a large number of features. How to reduce effectively the data dimension and locate accurately the biomarkers from such kinds of data are quite crucial for diagnosis and further precision medicine. In this paper, we propose a hybrid feature selection method based on machine learning and traditional statistical approaches and explore the brain abnormalities of schizophrenia by using the functional and structural MRI data. The results show that the abnormal brain regions are mainly distributed in the supramarginal gyrus, cingulate gyrus, frontal gyrus, precuneus and caudate, and the abnormal functional connections are related to the caudate nucleus, insula and rolandic operculum. In addition, some complex network analyses based on graph theory are utilized on the functional connection data, and the results demonstrate that the located abnormal functional connections in brain can distinguish schizophrenia patients from healthy controls. The identified abnormalities in brain with schizophrenia by the proposed hybrid feature selection method show that there do exist some abnormal brain regions and abnormal disruption of the network segregation and network integration for schizophrenia, and these changes may lead to inaccurate and inefficient information processing and synthesis in the brain, which provide further evidence for the cognitive dysmetria of schizophrenia.

scholarly journals Episodic memory-related activation in schizophrenia: meta-analysis

2005 ◽  
Vol 187 (6) ◽  
pp. 500-509 ◽  
Author(s):  
Amélie M. Achim ◽  
Martin Lepage
Keyword(s):  
Episodic Memory ◽  
Temporal Lobe ◽  
Medial Temporal Lobe ◽  
Meta Analysis ◽  
Temporal Cortex ◽  
Neural Correlates ◽  
Brain Regions ◽  
Group Differences ◽  
Memory Encoding ◽  
The Brain

BackgroundNumerous studies have examined the neural correlates of episodic memory deficits in schizophrenia, yielding both consistencies and discrepancies in the reported patterns of results.AimsTo identify in schizophrenia the brain regions in which activity is consistently abnormal across imaging studies of memory.MethodData from 18 studies meeting the inclusion criteria were combined using a recently developed quantitative meta-analytic approach.ResultsRegions of consistent differential activation between groups were observed in the left inferior prefrontal cortex, medial temporal cortex bilaterally, left cerebellum, and in other prefrontal and temporal lobe regions. Subsequent analyses explored memory encoding and retrieval separately and identified between-group differences in specific prefrontal and medial temporal lobe regions.ConclusionsBeneath the apparent heterogeneity of published findings on schizophrenia and memory, a consistent and robust pattern of group differences is observed as a function of memory processes.

scholarly journals HIV-Associated Structural and Functional Brain Alterations in Homosexual Males

2022 ◽  
Vol 12 ◽  
Author(s):  
Qiong Ma ◽  
Xiudong Shi ◽  
Guochao Chen ◽  
Fengxiang Song ◽  
Fengjun Liu ◽  
...  
Keyword(s):  
Sexual Orientation ◽  
Hiv Infection ◽  
Brain Regions ◽  
Regional Homogeneity ◽  
Anterior Cingulate ◽  
Parahippocampal Gyrus ◽  
Functional Brain ◽  
The Right ◽  
The Impact ◽  
The Brain

Purpose:Neuroimaging elucidations have shown structural and functional brain alterations in HIV-infected (HIV+) individuals when compared to HIV-negative (HIV–) controls. However, HIV− groups used in previous studies were not specifically considered for sexual orientation, which also affects the brain structures and functions. The current study aimed to characterize the brain alterations associated with HIV infection while controlling for sexual orientation.Methods:Forty-three HIV+ and 40 HIV– homosexual men (HoM) were recruited and underwent resting-state MRI scanning. Group differences in gray matter volume (GMV) were assessed using a voxel-based morphometry analysis. Brain regions with the altered GMV in the HIV+ HoM group were then taken as regions of interest in a seed-based analysis to identify altered functional connectivity. Furthermore, the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity values were compared between the two groups to evaluate the HIV-associated functional abnormalities in local brain regions.Results:HIV+ HoM showed significantly increased GMV in the bilateral parahippocampal gyrus and amygdala, and decreased GMV in the right inferior cerebellum, compared with the HIV– HoM. The brain regions with increased GMV were hyper-connected with the left superior cerebellum, right lingual gyrus, and left precuneus in the HIV+ HoM. Moreover, the ALFF values of the right fusiform gyrus, and left parahippocampal gyrus were increased in the HIV+ HoM. The regional homogeneity values of the right anterior cingulate and paracingulate gyri, and left superior cerebellum were decreased in the HIV+ HoM.Conclusion:When the study population was restricted to HoM, HIV+ individuals exhibited structural alterations in the limbic system and cerebellum, and functional abnormalities in the limbic, cerebellum, and visual network. These findings complement the existing knowledge on the HIV-associated neurocognitive impairment from the previous neuroimaging studies by controlling for the potential confounding factor, sexual orientation. Future studies on brain alternations with the exclusion of related factors like sexual orientation are needed to understand the impact of HIV infection on neurocognitive function more accurately.

scholarly journals Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes

2021 ◽  
Author(s):  
Ajay Peddada ◽  
Kevin Holly ◽  
Tejaswi D Sudhakar ◽  
Christina Ledbetter ◽  
Christopher E. Talbot ◽  
...  
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Temporal Lobe ◽  
Resting State ◽  
Classification Accuracy ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Group Differences ◽  
Functional Connections ◽  
White Matter Tractography

Background: Following mild traumatic brain injury (mTBI) compromised white matter structural integrity can result in alterations in functional connectivity of large-scale brain networks and may manifest in functional deficit including cognitive dysfunction . Advanced magnetic resonance neuroimaging techniques, specifically diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging (rs-fMRI), have demonstrated an increased sensitivity for detecting microstructural changes associated with mTBI. Identification of novel imaging biomarkers can facilitate early detection of these changes for effective treatment. In this study, we hypothesize that feature selection combining both structural and functional connectivity increases classification accuracy. Methods: 16 subjects with mTBI and 20 healthy controls underwent both DTI and resting state functional imaging. Structural connectivity matrices were generated from white matter tractography from DTI sequences. Functional connectivity was measured through pairwise correlations of rs-fMRI between brain regions. Features from both DTI and rs-fMRI were selected by identifying five brain regions with the largest group differences and were used to classify the generated functional and structural connectivity matrices, respectively. Classification was performed using linear support vector machines and validated with leave-one-out cross validation. Results: Group comparisons revealed increased functional connectivity in the temporal lobe and cerebellum as well as decreased structural connectivity in the temporal lobe. After training on structural connections only, a maximum classification accuracy of 78% was achieved when structural connections were selected based on their corresponding functional connectivity group differences. After training on functional connections only, a maximum classification accuracy of 69% was achieved when functional connections were selected based on their structural connectivity group differences. After training on both structural and functional connections, a maximum classification accuracy of 69% was achieved when connections were selected based on their structural connectivity. Conclusions: Our multimodal approach to ROI selection achieves at highest, a classification accuracy of 78%. Our results also implicate the temporal lobe in the pathophysiology of mTBI. Our findings suggest that white matter tractography can serve as a robust biomarker for mTBI when used in tandem with resting state functional connectivity.

scholarly journals Osteopontin/Secreted Phosphoprotein-1 Behaves as a Molecular Brake Regulating the Brain Translocator Protein-Dependent Neuroinflammatory Response to Chronic Viral Infection

2020 ◽  
Author(s):  
Farina J Mahmud ◽  
Yong Du ◽  
Elizabeth Greif ◽  
Thomas Boucher ◽  
Robert F Dannals ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Brain Tissue ◽  
Calcium Binding ◽  
Molecular Mechanisms ◽  
Inflammatory Responses ◽  
Brain Regions ◽  
Translocator Protein ◽  
Positron Emission ◽  
Molecular Brake ◽  
The Brain

Abstract Background Osteopontin (OPN) as a secreted signaling protein, is dramatically induced in response to cellular injury and neurodegeneration. Microglial inflammatory responses in the brain are tightly associated with the neuropathologic hallmarks of neurodegenerative disease, but understanding of the molecular mechanisms remains in several contexts, poorly understood. Methods Positron emission tomography (PET) neuroimaging using radioligands to detect increased expression of the translocator protein (TSPO) receptor in the brain, is a non-invasive tool used to track neuroinflammation in living mammals. Results In humanized, chronically HIV-infected mice in which OPN expression was knocked down with functional aptamers, uptake of TSPO radioligand, DPA-713 was markedly upregulated in the hippocampus, cortex, olfactory bulb, cerebellum and significantly increased in other key brain regions analyzed compared to controls. TSPO+ microglia were detected by immunolabeling of post-mortem brain tissue, thus validating the neuroimaging findings. Unexpectedly, two types of neurons also selectively stained positively for TSPO. The reactive cells were the specialized neurons of the cerebellum, Purkinje cells, and a subset of tyrosine hydroxylase positive neurons of the substantia nigra. Two-way ANOVA of immunoreactivity revealed that a well-validated marker of microglial activation in brain tissue, ionized calcium-binding adaptor molecule-1 (Iba-1) was significantly increased, in an interaction that depended on HIV replication. Interestingly, similar analyses of TSPO immunoreactivity showed a significant interaction with OPN expression. Conclusions Collectively, these findings using a model of chronic HIV-infection revealed for the first time two key findings: 1) two different pathways of neuroinflammation are activated, and 2) osteopontin acts as a molecular brake regulating in the brain, the inflammatory response to HIV infection.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals The Impact of Undiagnosed Synaesthesia on the Interpretation of Structural and Functional MRI Images Connectivity Maps and Resulting Diagnoses

2016 ◽  
Vol 15 (11) ◽  
pp. 7227-7234
Author(s):  
Nourhan Zayed
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Diffusion Tensor ◽  
Sensory Modality ◽  
Structural Connectivity ◽  
Brain Regions ◽  
Resonance Imaging ◽  
Functional Connections ◽  
The Impact ◽  
The Brain

Synathesia is a condition in which stimulation of a sensory modality triggers another sensation in the alike or an unalike sensory modality. Currently, synaesthesia is deemed a neurological condition that engages unwanted transfer of signals between brain regions from one sense to another “crosstalk activation”. The probability that undiagnosed synaesthesia may impact the results of structural magnetic resonance imaging (MRI), Diffusion Tensor imaging (DTI), functional magnetic resonance imaging (fMRI) and resting state connectivity studies is high, given the multiple anatomical and functional connections within the brain. In this paper, the currently available literature to mark which sensations adjured by synaesthesia and how could this impact MRI different modalities. Our study found that synaesthesia can have an opaque impact on fMRI studies of sensory, memory and cognitive functions, and there is testimony to suggest structural connections in the brain are also mutated DTI measurements especially, it shows enhanced structural connectivity for synesthetes between brain regions, higher Fractional anisotropy (FA), as well as increased in the white matter integrity between some regions.. Given the low dispersal of synaesthesia, the likelihood of synaesthesia being a perplexing factor in DTI, fMRI studies of patient groups is small; however, determining the existence of synaesthesia is paramount for investigating individual patients especially Shizoherenia, and autistic patients.

scholarly journals Brain-wide electrical dynamics encode an appetitive socioemotional state

2020 ◽  
Author(s):  
Stephen D. Mague ◽  
Austin Talbot ◽  
Cameron Blount ◽  
Lara J. Duffney ◽  
Kathryn K. Walder-Christensen ◽  
...  
Keyword(s):  
Social Preference ◽  
Brain Regions ◽  
Brain Network ◽  
Network Activity ◽  
Brain State ◽  
Genetic Mouse Model ◽  
Spatially Distributed ◽  
Subcortical Regions ◽  
Complex Social Behavior ◽  
The Brain

AbstractMany cortical and subcortical regions contribute to complex social behavior; nevertheless, the network level architecture whereby the brain integrates this information to encode appetitive socioemotional behavior remains unknown. Here we measure electrical activity from eight brain regions as mice engage in a social preference assay. We then use machine learning to discover an explainable brain network that encodes the extent to which mice chose to engage another mouse. This socioemotional network is organized by theta oscillations leading from prelimbic cortex and amygdala that converge on ventral tegmental area, and network activity is synchronized with brain-wide cellular firing. The network generalizes, on a mouse-by-mouse basis, to encode socioemotional behaviors in healthy animals, but fails to encode an appetitive socioemotional state in a ‘high confidence’ genetic mouse model of autism. Thus, our findings reveal the architecture whereby the brain integrates spatially distributed activity across timescales to encode an appetitive socioemotional brain state in health and disease.

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