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Retrosplenial Cortex Codes for Permanent Landmarks  [PDF]
Stephen D. Auger, Sinéad L. Mullally, Eleanor A. Maguire
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0043620
Abstract: Landmarks are critical components of our internal representation of the environment, yet their specific properties are rarely studied, and little is known about how they are processed in the brain. Here we characterised a large set of landmarks along a range of features that included size, visual salience, navigational utility, and permanence. When human participants viewed images of these single landmarks during functional magnetic resonance imaging (fMRI), parahippocampal cortex (PHC) and retrosplenial cortex (RSC) were both engaged by landmark features, but in different ways. PHC responded to a range of landmark attributes, while RSC was engaged by only the most permanent landmarks. Furthermore, when participants were divided into good and poor navigators, the latter were significantly less reliable at identifying the most permanent landmarks, and had reduced responses in RSC and anterodorsal thalamus when viewing such landmarks. The RSC has been widely implicated in navigation but its precise role remains uncertain. Our findings suggest that a primary function of the RSC may be to process the most stable features in an environment, and this could be a prerequisite for successful navigation.
Small-Scale Module of the Rat Granular Retrosplenial Cortex: An Example of the Minicolumn-Like Structure of the Cerebral Cortex  [PDF]
Noritaka Ichinohe
Frontiers in Neuroanatomy , 2012, DOI: 10.3389/fnana.2011.00069
Abstract: Structures associated with the small-scale module called “minicolumn” can be observed frequently in the cerebral cortex. However, the description of functional characteristics remains obscure. A significant confounding factor is the marked variability both in the definition of a minicolumn and in the diagnostic markers for identifying a minicolumn (see for review, Jones, 2000; DeFelipe et al., 2002; Rockland and Ichinohe, 2004). Within a minicolumn, cell columns are easily visualized by conventional Nissl staining. Dendritic bundles were first discovered with Golgi methods, but are more easily seen with microtubule-associated protein 2 immunohistochemistry. Myelinated axon bundles can be seen by Tau immunohistochemistry or myelin staining. Axon bundles of double bouquet cell can be seen by calbindin immunohistochemistry. The spatial interrelationship among these morphological elements is more complex than expected and is neither clear nor unanimously agreed upon. In this review, I would like to focus first on the minicolumnar structure found in layers 1 and 2 of the rat granular retrosplenial cortex. This modular structure was first discovered as a combination of prominent apical dendritic bundles from layer 2 pyramidal neurons and spatially matched thalamocortical patchy inputs (Wyss et al., 1990). Further examination showed more intricate components of this modular structure, which will be reviewed in this paper. Second, the postnatal development of this structure and potential molecular players for its formation will be reviewed. Thirdly, I will discuss how this modular organization is transformed in mutant rodents with a disorganized layer structure in the cerebral cortex (i.e., reeler mouse and shaking rat Kawasaki). Lastly, the potential significance of this type of module will be discussed.
Single Axon Branching Analysis in Rat Thalamocortical Projection from the Anteroventral Thalamus to the Granular Retrosplenial Cortex  [PDF]
Saori Odagiri,Yoshiya Asano,Noritaka Ichinohe
Frontiers in Neuroanatomy , 2011, DOI: 10.3389/fnana.2011.00063
Abstract: The granular retrosplenial cortex (GRS) in the rat has a distinct microcolumn-type structure. The apical tufts of dendritic bundles at layer I, which are formed by layer II neurons, co-localize with patches of thalamic terminations from anteroventral (AV) thalamic nucleus. To further understand this microcolumn-type structure in the GRS, one of remaining questions is whether this structure extends into other layers, such as layers III/IV. Other than layer I, previous tracer injection study showed that AV thalamic nucleus also projects to layer III/IV in the GRS. In this study, we examined the morphology of branches in the GRS from the AV thalamus in single axon branch resolution in order to determine whether AV axon branches in layer III/IV are branches of axons with extensive branch in layer I, and, if so, whether the extent of these arborizations in layer III/IV vertically matches with that in layer I. For this purpose, we used a small volume injection of biotinylated dextran-amine into the AV thalamus and reconstructing labeled single axon branches in the GRS. We found that the AV axons consisted of heterogeneous branching types. Type 1 had extensive arborization occurring only in layer Ia. Type 2 had additional branches in III/IV. Types 1 and 2 had extensive ramifications in layer Ia, with lateral extensions within the previously reported extensions of tufts from single dendritic bundles (i.e., 30–200 μm; mean 78 μm). In type 2 branches, axon arborizations in layer III/IV were just below to layer Ia ramifications, but much wider (148–533 μm: mean, 341 μm) than that in layer Ia axon branches and dendritic bundles, suggesting that layer-specific information transmission spacing existed even from the same single axons from the AV to the GRS. Thus, microcolumn-type structure in the upper layer of the GRS was not strictly continuous from layer I to layer IV. How each layer and its components interact each other in different spatial scale should be solved future.
Does the Budapest Reference Connectome Server Shed Light on the Development of the Connections of the Human Brain?  [PDF]
Csaba Kerepesi,Balázs Szalkai,Bálint Varga,Vince Grolmusz
Quantitative Biology , 2015,
Abstract: The human braingraph or the connectome is the object of an intensive research today. The advantage of the graph-approach to brain science is that the rich structures, algorithms and definitions of graph theory can be applied to the 1000-node anatomical networks of the connections of the human brain. In these graphs, the vertices correspond to the small (1-1.5 cm$^2$) areas of the gray matter, and two vertices are connected by an edge, if a diffusion-MRI based workflow finds fibers of axons, running between those small gray matter areas in the white matter of the brain. In a previous work we have reported the construction of the Budapest Reference Connectome Server http://connectome.pitgroup.org, which generates the consensus braingraph of 96 subjects, according to selectable parameters. After the Budapest Reference Connectome Server had been published, we recognized a surprising and unforeseen property of the server. The server can generate the braingraph of connections that are present in at least $k$ graphs out of the 96, for any value of $k=1,2,...,96$. When the value of $k$ is changed from $k=96$ through $1$ by moving a slider at the webserver, certainly more and more edges appear in the consensus graph. The astonishing observation is that the appearance of the new edges is not random: it is similar to a growing tree. We hypothesize that this movement of the slider in the webserver may copy the development of the connections in the human brain in the following sense: the connections that are present in almost all subjects are the oldest ones, and those that are present only in a fraction of the subjects are the newest connections in the individual brain development. An animation on the phenomenon is available at https://youtu.be/EnWwIf_HNjw
The Connectome Viewer Toolkit: An Open Source Framework to Manage, Analyze, and Visualize Connectomes  [PDF]
Stephan Gerhard,Alessandro Daducci,Alia Lemkaddem,Reto Meuli,Jean-Philippe Thiran
Frontiers in Neuroinformatics , 2011, DOI: 10.3389/fninf.2011.00003
Abstract: Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit – a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer’s plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/
Statistical structure of lateral connections in the primary visual cortex
Hunt Jonathan J,Bosking William H,Goodhill Geoffrey J
Neural Systems & Circuits , 2011, DOI: 10.1186/2042-1001-1-3
Abstract: Background The statistical structure of the visual world offers many useful clues for understanding how biological visual systems may understand natural scenes. One particularly important early process in visual object recognition is that of grouping together edges which belong to the same contour. The layout of edges in natural scenes have strong statistical structure. One such statistical property is that edges tend to lie on a common circle, and this 'co-circularity' can predict human performance at contour grouping. We therefore tested the hypothesis that long-range excitatory lateral connections in the primary visual cortex, which are believed to be involved in contour grouping, display a similar co-circular structure. Results By analyzing data from tree shrews, where information on both lateral connectivity and the overall structure of the orientation map was available, we found a surprising diversity in the relevant statistical structure of the connections. In particular, the extent to which co-circularity was displayed varied significantly. Conclusions Overall, these data suggest the intriguing possibility that V1 may contain both co-circular and anti-cocircular connections.
Comparison of Entorhinal Cortex and Hippocampal Volume Measurements of Patients With Mesial Temporal Sclerosis  [PDF]
?brahim BORA,Nazan CANBULAT,Aylin B?CAN,Bahattin HAKYEMEZ
Journal of Neurological Sciences , 2011,
Abstract: The aim of this study is to evaluate the frequency of EC ( Entorhinal cortex) atrophy in patients with TLE (Temporal Lobe Epilepsy) demostrate the diagnostic value in patients with or without hippocampal sclerosis.Metod: 23 patients, with TLE who were observed and recording in the Video-EEG monitorization and a control group of 17 patients were involved in the study. In both goups differences between video recordings of seizures with syncronized EEG recording were evaluated and lateralization of the seizure focus or the relation with the dominant hemisphere were recorded. 3D-T1 secands hippocampus and EC layers were calculated and mean volüme were calculated.Results: The lateralization signs; versiv head deviation, concurrency of ipsilateral automatism with contralateral dystonic posture and the 4 sign were found to lateralize the contralateral of the seizure focus, while speech arrest lateralize the dominant hemisphere. There were no differences in the frequency of lateralization sign between the group of patients with hippocampal sclerosis and the other group without hippocampal screlosis. In both of the patient groups, frequency of EC atrophy was statistically significant. Although reduction of EC volümes were frequently bilateral in both groups, EC volümes were found to be smaller at the ipsilateral seizure focus.Conclusion: The present study demostrated that most of the patients with TLE had EC atrophy. EC volüme measurements with Video-EEG monitoring and neuropsychometric tests can be useful in some circumstanses where it's difficult to distinguish between TLE and Extra Temporal Lobe Epilepsy and especially to distinguish frontal and temporal seizures.
The Potential of the Human Connectome as a Biomarker of Brain Disease  [PDF]
Marcus Kaiser
Physics , 2013, DOI: 10.3389/fnhum.2013.00484
Abstract: The human connectome at the level of fiber tracts between brain regions has been shown to differ in patients with brain disorders compared to healthy control groups. Nonetheless, there is a potentially large number of different network organizations for individual patients that could lead to cognitive deficits prohibiting correct diagnosis. Therefore changes that can distinguish groups might not be sufficient to diagnose the disease that an individual patient suffers from and to indicate the best treatment option for that patient. We describe the challenges introduced by the large variability of connectomes within healthy subjects and patients and outline three common strategies to use connectomes as biomarkers of brain diseases. Finally, we propose a fourth option in using models of simulated brain activity (the dynamic connectome) based on structural connectivity rather than the structure (connectome) itself as a biomarker of disease. Dynamic connectomes, in addition to currently used structural, functional, or effective connectivity, could be an important future biomarker for clinical applications.
Communication and wiring in the cortical connectome  [PDF]
Julian M. L. Budd,Zoltán F. Kisvárday
Frontiers in Neuroanatomy , 2012, DOI: 10.3389/fnana.2012.00042
Abstract: In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns.
Magnetic Resonance Connectome Automated Pipeline  [PDF]
William R. Gray,John A. Bogovic,Joshua T. Vogelstein,Bennett A. Landman,Jerry L. Prince,R. Jacob Vogelstein
Physics , 2011,
Abstract: This manuscript presents a novel, tightly integrated pipeline for estimating a connectome, which is a comprehensive description of the neural circuits in the brain. The pipeline utilizes magnetic resonance imaging (MRI) data to produce a high-level estimate of the structural connectivity in the human brain. The Magnetic Resonance Connectome Automated Pipeline (MRCAP) is efficient and its modular construction allows researchers to modify algorithms to meet their specific requirements. The pipeline has been validated and over 200 connectomes have been processed and analyzed to date. This tool enables the prediction and assessment of various cognitive covariates, and this research is applicable to a variety of domains and applications. MRCAP will enable MR connectomes to be rapidly generated to ultimately help spur discoveries about the structure and function of the human brain.
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