Automatic segmentation of the short association fibers of the fronto-parietal and insula brain regions

2014 ◽  
Author(s):  
D. Seguel ◽  
D. Le Bihan ◽  
M. Guevara ◽  
A. Lebois ◽  
P. Guevara ◽  
...  
Keyword(s):  
Automatic Segmentation ◽  
Brain Regions ◽  
Association Fibers

scholarly journals Automatic Segmentation of the Dorsal Claustrum in Humans Using in vivo High-Resolution MRI

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Shai Berman ◽  
Roey Schurr ◽  
Gal Atlan ◽  
Ami Citri ◽  
Aviv A Mezer
Keyword(s):  
High Resolution ◽  
Automatic Segmentation ◽  
Thin Sheet ◽  
Brain Regions ◽  
Reproducible Research ◽  
Human Connectome Project ◽  
High Resolution Mri ◽  
Magnetic Resonance Imaging Mri ◽  
And Function

Abstract The claustrum is a thin sheet of neurons enclosed by white matter and situated between the insula and the putamen. It is highly interconnected with sensory, frontal, and subcortical regions. The deep location of the claustrum, with its fine structure, has limited the degree to which it could be studied in vivo. Particularly in humans, identifying the claustrum using magnetic resonance imaging (MRI) is extremely challenging, even manually. Therefore, automatic segmentation of the claustrum is an invaluable step toward enabling extensive and reproducible research of the anatomy and function of the human claustrum. In this study, we developed an automatic algorithm for segmenting the human dorsal claustrum in vivo using high-resolution MRI. Using this algorithm, we segmented the dorsal claustrum bilaterally in 1068 subjects of the Human Connectome Project Young Adult dataset, a publicly available high-resolution MRI dataset. We found good agreement between the automatic and manual segmentations performed by 2 observers in 10 subjects. We demonstrate the use of the segmentation in analyzing the covariation of the dorsal claustrum with other brain regions, in terms of macro- and microstructure. We identified several covariance networks associated with the dorsal claustrum. We provide an online repository of 1068 bilateral dorsal claustrum segmentations.

scholarly journals A deep convolutional neural network approach for astrocyte detection

2017 ◽  
Author(s):  
Ilida Suleymanova ◽  
Tamas Balassa ◽  
Sushil Tripathi ◽  
Csaba Molnar ◽  
Mart Saarma ◽  
...  
Keyword(s):  
Image Analysis ◽  
Automatic Segmentation ◽  
Brain Regions ◽  
Cell Counting ◽  
Detection Accuracy ◽  
Cell Detection ◽  
Strong Positive Correlation ◽  
Deep Convolutional Neural Networks ◽  
Neural Network Approach ◽  
Microscopy Images

AbstractAstrocytes are involved in brain pathologies such as trauma or stroke, neurodegenerative disorders like Alzheimer’s and Parkinson’s disease, chronic pain, and many others. Determining cell density and timing of morphological and biochemical changes is important for a proper understanding of the role of astrocytes in physiological and pathological conditions. One of the most important of such analyses is astrocytes count within a complex tissue environment in microscopy images. The most widely used approaches for the quantification of microscopy images data are either manual stereological cell counting or semi-automatic segmentation techniques. Detecting astrocytes automatically is a highly challenging computational task, for which we currently lack efficient image analysis tools. In this study, we developed a fast and fully automated software that assesses the number of astrocytes using Deep Convolutional Neural Networks (DCNN). The method highly outperforms state-of-the-art image analysis and machine learning methods and provides detection accuracy and precision comparable to that of human experts. Additionally, the runtime of cell detection is significantly less than other three analyzed computational methods, and it is faster than human observers by orders of magnitude. We applied DCNN-based method to examine the number of astrocytes in different brain regions of rats with opioid-induced hyperalgesia/tolerance (OIH/OIT) as morphine tolerance is believed to activate glial cells in the brain. We observed strong positive correlation between manual cell detection and DCNN-based analysis method for counting astrocytes in the brains of experimental animals.

scholarly journals Automatic segmentation of Drosophila neural compartments using GAL4 expression data reveals novel visual pathways

2015 ◽  
Author(s):  
Karin Panser ◽  
Laszlo Tirian ◽  
Florian Schulze ◽  
Santiago Villalba ◽  
Gregory SXE Jefferis ◽  
...  
Keyword(s):  
Large Scale ◽  
Automatic Segmentation ◽  
Brain Regions ◽  
Confocal Imaging ◽  
Central Complex ◽  
Projection Neurons ◽  
Fiber Tracts ◽  
Large Brain ◽  
Gal4 Expression ◽  
Visual Projection

We made use of two recent, large-scale Drosophila GAL4 libraries and associated confocal imaging datasets to automatically segment large brain regions into smaller putative functional units such as neuropils and fiber tracts. The method we developed is based on the hypothesis that molecular identity can be used to assign individual voxels to biologically meaningful regions. Our results (available at https://strawlab.org/braincode) are consistent with this hypothesis because regions with well-known anatomy, namely the antennal lobes and central complex, were automatically segmented into familiar compartments. We then applied the algorithm to the central brain regions receiving input from the optic lobes. Based on the automated segmentation and manual validation, we can identify and provide promising driver lines for 10 previously identified and 14 novel types of visual projection neurons and their associated optic glomeruli. The same strategy can be used in other brain regions and likely other species, including vertebrates.

scholarly journals Automatic MS Lesion Segmentation by Outlier Detection and Information Theoretic Region Partitioning

2008 ◽  
Author(s):  
Marcel Prastawa ◽  
Guido Gerig
Keyword(s):  
Outlier Detection ◽  
Automatic Segmentation ◽  
Brain Mri ◽  
Brain Regions ◽  
Lesion Detection ◽  
Training Data ◽  
Information Theoretic ◽  
Leibler Divergence ◽  
Fully Automatic ◽  
Brain Tissue Damage

Multiple Sclerosis (MS) is a neurodegenerative disease that is associated with brain tissue damage primarily observed as white matter abnormalities such as lesions. We present a novel, fully automatic segmentation method for MS lesions in brain MRI that combines outlier detection and region partitioning. The method is based on an atlas of healthy subjects and detects lesions as outliers, without requiring the use of training data with segmented lesions. In order to segment lesions as spatially coherent objects and avoid spurious lesion detection, we perform classification on regions (connected groups of voxels) instead of individual voxels. Each voxel location is assigned to a region that would maximize overall relative entropy or Kullback-Leibler divergence between neighboring regions. Our proposed method is fully automatic and does not require manual selection or outlining of specific brain regions. The method can also be adapted to MR images obtained from different scanners and scanning parameters as it requires no training.

Synaptic organization of the gustatory NST

1994 ◽  
Vol 52 ◽  
pp. 150-151
Author(s):  
M. C. Whitehead
Keyword(s):  
Central Nervous System ◽  
Dendritic Spines ◽  
Fundamental Problem ◽  
Cell Types ◽  
Brain Regions ◽  
Excitatory Synapses ◽  
Solitary Tract ◽  
Synaptic Organization ◽  
Synaptic Junctions ◽  
Afferent Terminals

A fundamental problem in taste research is to determine how gustatory signals are processed and disseminated in the mammalian central nervous system. An important first step toward understanding information processing is the identification of cell types in the nucleus of the solitary tract (NST) and their synaptic relationships with oral primary afferent terminals. Facial and glossopharyngeal (LIX) terminals in the hamster were labelled with HRP, examined with EM, and characterized as containing moderate concentrations of medium-sized round vesicles, and engaging in asymmetrical synaptic junctions. Ultrastructurally the endings resemble excitatory synapses in other brain regions.Labelled facial afferent endings in the RC subdivision synapse almost exclusively with distal dendrites and dendritic spines of NST cells. Most synaptic relationships between the facial synapses and the dendrites are simple. However, 40% of facial endings engage in complex synaptic relationships within glomeruli containing unlabelled axon endings particularly ones termed "SP" endings. SP endings are densely packed with small, pleomorphic vesicles and synapse with both the facial endings and their postsynaptic dendrites by means of nearly symmetrical junctions.

Musical Anhedonia

2020 ◽  
Vol 31 (2) ◽  
pp. 62-68
Author(s):  
Sara E. Holm ◽  
Alexander Schmidt ◽  
Christoph J. Ploner
Keyword(s):  
Quality Of Life ◽  
Nucleus Accumbens ◽  
Brain Damage ◽  
Parietal Cortex ◽  
Neurological Disorders ◽  
Brain Regions ◽  
Precise Information ◽  
Exact Localization ◽  
High Prevalence

Abstract. Some people, although they are perfectly healthy and happy, cannot enjoy music. These individuals have musical anhedonia, a condition which can be congenital or may occur after focal brain damage. To date, only a few cases of acquired musical anhedonia have been reported in the literature with lesions of the temporo-parietal cortex being particularly important. Even less literature exists on congenital musical anhedonia, in which impaired connectivity of temporal brain regions with the Nucleus accumbens is implicated. Nonetheless, there is no precise information on the prevalence, causes or exact localization of both congenital and acquired musical anhedonia. However, the frequent involvement of temporo-parietal brain regions in neurological disorders such as stroke suggest the possibility of a high prevalence of this disorder, which leads to a considerable reduction in the quality of life.

Serotonergic Genes and Suicidality

Crisis ◽  
2001 ◽  
Vol 22 (2) ◽  
pp. 54-60 ◽  
Author(s):  
Lisheng Du ◽  
Gabor Faludi ◽  
Miklos Palkovits ◽  
David Bakish ◽  
Pavel D. Hrdina
Keyword(s):  
Suicidal Ideation ◽  
Suicidal Behavior ◽  
Tryptophan Hydroxylase ◽  
Association Studies ◽  
Receptor Gene ◽  
Brain Regions ◽  
Depressive Illness ◽  
Control Group ◽  
Serotonergic Activity ◽  
Completed Suicide

Summary: Several lines of evidence indicate that abnormalities in the functioning of the central serotonergic system are involved in the pathogenesis of depressive illness and suicidal behavior. Studies have shown that the number of brain and platelet serotonin transporter binding sites are reduced in patients with depression and in suicide victims, and that the density of 5-HT2A receptors is increased in brain regions of depressed in suicide victims and in platelets of depressed suicidal patients. Genes that code for proteins, such as tryptophan hydroxylase, 5-HT transporter, and 5-HT2A receptor, involved in regulating serotonergic neurotransmission, have thus been major candidate genes for association studies of suicide and suicidal behavior. Recent studies by our group and by others have shown that genetic variations in the serotonin-system-related genes might be associated with suicidal ideation and completed suicide. We have shown that the 102 C allele in 5-HT2A receptor gene was significantly associated with suicidal ideation (χ2 = 8.5, p < .005) in depressed patients. Patients with a 102 C/C genotype had a significantly higher mean HAMD item #3 score (indication of suicidal ideation) than T/C or T/T genotype patients. Our results suggest that the 102T/C polymorphism in 5-HT2A receptor gene is primarily associated with suicidal ideation in patients with major depression and not with depression itself. We also found that the 5-HT transporter gene S/L polymorphism was significantly associated with completed suicide. The frequency of the L/L genotype in depressed suicide victims was almost double of that found in control group (48.6% vs. 26.2%). The odds ratio for the L allele was 2.1 (95% CI 1.2-3.7). The association between polymorphism in serotonergic genes and suicidality supports the hypothesis that genetic factors can modulate suicide risk by influencing serotonergic activity.

Inefficient Encoding as an Explanation for Age-Related Deficits in Recollection-Based Processing

2014 ◽  
Vol 28 (3) ◽  
pp. 148-161 ◽  
Author(s):  
David Friedman ◽  
Ray Johnson
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Cognitive Processes ◽  
Brain Activity ◽  
Memory Performance ◽  
Brain Regions ◽  
Semantic Retrieval ◽  
Age Related ◽  
The Face ◽  
Episodic Memories

A cardinal feature of aging is a decline in episodic memory (EM). Nevertheless, there is evidence that some older adults may be able to “compensate” for failures in recollection-based processing by recruiting brain regions and cognitive processes not normally recruited by the young. We review the evidence suggesting that age-related declines in EM performance and recollection-related brain activity (left-parietal EM effect; LPEM) are due to altered processing at encoding. We describe results from our laboratory on differences in encoding- and retrieval-related activity between young and older adults. We then show that, relative to the young, in older adults brain activity at encoding is reduced over a brain region believed to be crucial for successful semantic elaboration in a 400–1,400-ms interval (left inferior prefrontal cortex, LIPFC; Johnson, Nessler, & Friedman, 2013 ; Nessler, Friedman, Johnson, & Bersick, 2007 ; Nessler, Johnson, Bersick, & Friedman, 2006 ). This reduced brain activity is associated with diminished subsequent recognition-memory performance and the LPEM at retrieval. We provide evidence for this premise by demonstrating that disrupting encoding-related processes during this 400–1,400-ms interval in young adults affords causal support for the hypothesis that the reduction over LIPFC during encoding produces the hallmarks of an age-related EM deficit: normal semantic retrieval at encoding, reduced subsequent episodic recognition accuracy, free recall, and the LPEM. Finally, we show that the reduced LPEM in young adults is associated with “additional” brain activity over similar brain areas as those activated when older adults show deficient retrieval. Hence, rather than supporting the compensation hypothesis, these data are more consistent with the scaffolding hypothesis, in which the recruitment of additional cognitive processes is an adaptive response across the life span in the face of momentary increases in task demand due to poorly-encoded episodic memories.

Inflammational Animal Models for Schizophrenia

2015 ◽  
Vol 223 (3) ◽  
pp. 157-164 ◽  
Author(s):  
Georg Juckel
Keyword(s):  
Animal Model ◽  
Animal Models ◽  
Immune Activation ◽  
Microglial Activation ◽  
Treatment Options ◽  
Early Adulthood ◽  
Brain Regions ◽  
Synaptic Connections ◽  
Preventive Interventions ◽  
Immunological System

Abstract. Inflammational-immunological processes within the pathophysiology of schizophrenia seem to play an important role. Early signals of neurobiological changes in the embryonal phase of brain in later patients with schizophrenia might lead to activation of the immunological system, for example, of cytokines and microglial cells. Microglia then induces – via the neurotoxic activities of these cells as an overreaction – a rarification of synaptic connections in frontal and temporal brain regions, that is, reduction of the neuropil. Promising inflammational animal models for schizophrenia with high validity can be used today to mimic behavioral as well as neurobiological findings in patients, for example, the well-known neurochemical alterations of dopaminergic, glutamatergic, serotonergic, and other neurotransmitter systems. Also the microglial activation can be modeled well within one of this models, that is, the inflammational PolyI:C animal model of schizophrenia, showing a time peak in late adolescence/early adulthood. The exact mechanism, by which activated microglia cells then triggers further neurodegeneration, must now be investigated in broader detail. Thus, these animal models can be used to understand the pathophysiology of schizophrenia better especially concerning the interaction of immune activation, inflammation, and neurodegeneration. This could also lead to the development of anti-inflammational treatment options and of preventive interventions.

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