A stereological study of synapse number in the epileptic human hippocampus

Hippocampal sclerosis is the most frequent pathology encountered in resected mesial temporal structures from patients with intractable temporal lobe epilepsy (TLE). Here, we have used stereological methods to compare the overall density of synapses and neurons between non-sclerotic and sclerotic hippocampal tissue obtained by surgical resection from patients with TLE. Specifically, we examined the possible changes in the subiculum and CA1, regions that seem to be critical for the development and/or maintenance of seizures in these patients. We found a remarkable decrease in synaptic and neuronal density in the sclerotic CA1, and while the subiculum from the sclerotic hippocampus did not display changes in synaptic density, the neuronal density was higher. Since the subiculum from the sclerotic hippocampus displays a significant increase in neuronal density, as well as a various other neurochemical changes, we propose that the apparently normal subiculum from the sclerotic hippocampus suffers profound alterations in neuronal circuits at both the molecular and synaptic level that are likely to be critical for the development or maintenance of seizure activity

Pyramidal cells in prefrontal cortex: comparative observations reveal unparalleled specializations in neuronal structure among primate species

The most ubiquitous neuron in the cerebral cortex, the pyramidal cell, is characterized by markedly different dendritic structure among different cortical areas. The complex pyramidal cell phenotype in granular prefrontal cortex (gPFC) of higher primates endows specific biophysical properties and patterns of connectivity, which differ from those in other cortical regions. However, within the gPFC, data have been sampled from only a select few cortical areas. The gPFC of species such as human and macaque monkey includes more than 10 cortical areas. It remains unknown as to what degree pyramidal cell structure may vary among these cortical areas. Here we undertook a survey of pyramidal cells in the dorsolateral, medial, and orbital gPFC of cercopithecid primates. We found marked heterogeneity in pyramidal cell structure within and between these regions. Moreover, trends for gradients in neuronal complexity varied among species. As the structure of neurons determines their computational abilities, memory storage capacity and connectivity, we propose that these specializations in the pyramidal cell phenotype are an important determinant of species-specific executive cortical functions in primates.

The evolution of the brain, the human nature of cortical circuits and intellectual creativity

The tremendous expansion and the differentiation of the neocortex constitute two major events in the evolution of the mammalian brain. The increase in size and complexity of our brains opened the way to a spectacular development of cognitive and mental skills. This expansion during evolution facilitated the addition of microcircuits with a similar basic structure, which increased the complexity of the human brain and contributed to its uniqueness. However, fundamental differences even exist between distinct mammalian species. Here, we shall discuss the issue of our humanity from a neurobiological and historical perspective.

ESPINA: a tool for the automated segmentation and counting of synapses in large stacks of electron microscopy images

The synapses in the cerebral cortex can be classified into two main types, Gray’s type I and type II, which correspond to asymmetric (mostly glutamatergic excitatory) and symmetric (inhibitory GABAergic) synapses, respectively. Hence, the quantification and identification of their different types and the proportions in which they are found, is extraordinarily important in terms of brain function. The ideal approach to calculate the number of synapses per unit volume is to analyze 3D samples reconstructed from serial sections. However, obtaining serial sections by transmission electron microscopy is an extremely time consuming and technically demanding task. Using focused ion beam/scanning electron microscope microscopy, we recently showed that virtually all synapses can be accurately identified as asymmetric or symmetric synapses when they are visualized, reconstructed, and quantified from large 3D tissue samples obtained in an automated manner. Nevertheless, the analysis, segmentation, and quantification of synapses is still a labor intensive procedure. Thus, novel solutions are currently necessary to deal with the large volume of data that is being generated by automated 3D electron microscopy. Accordingly, we have developed ESPINA, a software tool that performs the automated segmentation and counting of synapses in a reconstructed 3D volume of the cerebral cortex, and that greatly facilitates and accelerates these processes.

The neocortical column

In the middle of the twentieth century, Rafael Lorente de Nó (1902?1990) introduced the fundamental concept of the ?elementary cortical unit of operation,? proposing that the cerebral cortex is formed of small cylinders containing vertical chains of neurons (Lorente de Nó, 1933, 1938). On the basis of this idea, the hypothesis was later developed of the columnar organization of the cerebral cortex, primarily following the physiological and anatomical studies of Vernon Mountcastle, David Hubel, Torsten Wiesel, János Szentágothai, Ted Jones, and Pasko Rakic (for a review of these early studies, see Mountcastle, 1998). The columnar organization hypothesis is currently the most widely adopted to explain the cortical processing of information, making its study of potential interest to any researcher interested in this tissue, both in a healthy and pathological state. However, it is frequently remarked that the nomenclature surrounding this hypothesis often generates problems, as the term ?Column? is used freely and promiscuously to refer to multiple, distinguishable entities, such as cellular or dendritic minicolumns or afferent macrocolumns, with respective diameters of menor que50 and 200?500 ?m. Another problem is the degree to which classical criteria may need to be modified (shared response properties, shared input, and common output) and if so, how. Moreover, similar problems arise when we consider the need to define area-specific and species-specific variations. Finally, and what is more an ultimate goal than a problem, it is still necessary to achieve a better fundamental understanding of what columns are and how they are used in cortical processes. Accordingly, it is now very important to translate recent technical advances and new findings in the neurosciences into practical applications for neuroscientists, clinicians, and for those interested in comparative anatomy and brain evolution.

3D segmentations of neuronal nuclei from confocal microscope image stacks

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario?the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

Three-dimensional distribution of cortical synapses: a replicated point pattern-based analysis

The biggest problem when analyzing the brain is that its synaptic connections are extremely complex. Generally, the billions of neurons making up the brain exchange information through two types of highly specialized structures: chemical synapses (the vast majority) and so-called gap junctions (a substrate of one class of electrical synapse). Here we are interested in exploring the three-dimensional spatial distribution of chemical synapses in the cerebral cortex. Recent research has showed that the three-dimensional spatial distribution of synapses in layer III of the neocortex can be modeled by a random sequential adsorption (RSA) point process, i.e., synapses are distributed in space almost randomly, with the only constraint that they cannot overlap. In this study we hypothesize that RSA processes can also explain the distribution of synapses in all cortical layers. We also investigate whether there are differences in both the synaptic density and spatial distribution of synapses between layers. Using combined focused ion beam milling and scanning electron microscopy (FIB/SEM), we obtained three-dimensional samples from the six layers of the rat somatosensory cortex and identified and reconstructed the synaptic junctions. A total volume of tissue of approximately 4500μm3 and around 4000 synapses from three different animals were analyzed. Different samples, layers and/or animals were aggregated and compared using RSA replicated spatial point processes. The results showed no significant differences in the synaptic distribution across the different rats used in the study. We found that RSA processes described the spatial distribution of synapses in all samples of each layer. We also found that the synaptic distribution in layers II to VI conforms to a common underlying RSA process with different densities per layer. Interestingly, the results showed that synapses in layer I had a slightly different spatial distribution from the other layers.

Neuronanatomy, neurology and Bayesian networks

Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related quality of life in Parkinson's disease. Most of these challenging problems posed by neuroscience involve new Bayesian network designs that can cope with multiple class variables, small sample sizes, or labels annotated by several experts.

On the role of selective attention in visual perception

What is the role of selective attention in visual perception? Before answering this question, it is necessary to differentiate between attentional mechanisms that influence the identification of a stimulus from those that operate after perception is complete. Cognitive neuroscience techniques are particularly well suited to making this distinction because they allow different attentional mechanisms to be isolated in terms of timing and/or neuroanatomy. The present article describes the use of these techniques in differentiating between perceptual and postperceptual attentional mechanisms and then proposes a specific role of attention in visual perception. Specifically, attention is proposed to resolve ambiguities in neural coding that arise when multiple objects are processed simultaneously. Evidence for this hypothesis is provided by two experiments showing that attention—as measured electrophysiologically—is allocated to visual search targets only under conditions that would be expected to lead to ambiguous neural coding.

Functional testicular tissue does not masculinize development of the zebra finch song system.

Current theories of sexual differentiation maintain that ovarian estrogen prevents masculine development of the copulatory system in birds, whereas estrogen derived from testicular androgens promotes masculine sexual differentiation of neuroanatomy and sexual behavior in mammals. Paradoxically, some data suggest that the neural song system in zebra finches follows the mammalian pattern with estrogenic metabolites of testicular secretions causing masculine development. To test whether the removal of estrogen from males during early development would prevent the development of masculine song systems, zebra finches were treated embryonically with an inhibitor of estrogen synthesis. In addition, this treatment in genetic female zebra finches induced both functional ovarian and testicular tissue to develop, thus allowing the assessment of the direct effects of testicular secretions on song system development. In males, the inhibition of estrogen synthesis before hatching had a small but significant effect in demasculinizing one aspect of the neural song system. In treated females, the song systems remained morphologically feminine. These results suggest that masculinization of the song system is not determined solely by testicular androgens or their estrogenic metabolites.

In vitro autoradiography of receptor-activated G proteins in rat brain by agonist-stimulated guanylyl 5'-[gamma-[35S]thio]-triphosphate binding.

Agonists stimulate guanylyl 5'-[gamma-[35S]thio]-triphosphate (GTP[gamma-35S]) binding to receptor-coupled guanine nucleotide binding protein (G proteins) in cell membranes as revealed in the presence of excess GDP. We now report that this reaction can be used to neuroanatomically localize receptor-activated G proteins in brain sections by in vitro autoradiography of GTP[gamma-35S] binding. Using the mu opioid-selective peptide [D-Ala2,N-MePhe4,Gly5-ol]enkephalin (DAMGO) as an agonist in rat brain sections and isolated thalamic membranes, agonist stimulation of GTP[gamma-35S] binding required the presence of excess GDP (1-2 mM GDP in sections vs. 10-30 microM GDP in membranes) to decrease basal G-protein activity and reveal agonist-stimulated GTP[gamma-35S] binding. Similar concentrations of DAMGO were required to stimulate GTP[gamma-35S] binding in sections and membranes. To demonstrate the general applicability of the technique, agonist-stimulated GTP[gamma-35S] binding in tissue sections was assessed with agonists for the mu opioid (DAMGO), cannabinoid (WIN 55212-2), and gamma-aminobutyric acid type B (baclofen) receptors. For opioid and cannabinoid receptors, agonist stimulation of GTP[gamma-35S] binding was blocked by incubation with agonists in the presence of the appropriate antagonists (naloxone for mu opioid and SR-141716A for cannabinoid), thus demonstrating that the effect was specifically receptor mediated. The anatomical distribution of agonist-stimulated GTP[gamma-35S] binding qualitatively paralleled receptor distribution as determined by receptor binding autoradiography. However, quantitative differences suggest that variations in coupling efficiency may exist between different receptors in various brain regions. This technique provides a method of functional neuroanatomy that identifies changes in the activation of G proteins by specific receptors.

Psicoses em patologias não psiquiátricas

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

Qui utilise 10% de son cerveau?

Ce texte examine la croyance largement répandue selon laquelle les humains n'utiliseraient que 10 % de leur cerveau. Le texte comprend quatre parties. Les deux premières parties évaluent l'ampleur du «mythe du 10 %» et en retracent les origines. La troisième partie montre que cette croyance n'est nullement justifiée en passant successivement en revue les connaissances concernant l'anatomie et la physiologie du cerveau, la plasticité cérébrale ainsi que des données sur l'évolution. La dernière partie évoque quelques raisons de la persistance du mythe du 10 %.

Journal für Hirnforschung.

Founded and -1960 edited by C. Vogt and O. Vogt.

Observationum anatomicarum de nervis viscerum abdominalium particula prima quae de ganglio plexuque semilunari agit.

Mode of access: Internet.