Size frequency distribution of senile plaques in post-mortem brains of five patients with senile dementia of the Alzheimer type (SDAT)

Numerous senile plaques are one of the most characteristic histological findings in SDAT brains. Large classical plaques may develop from smaller uncored forms. There is no strong evidence that, once formed, plaques disappear from the tissue. We have examined cresyl-violet stained sections of the parahippocampal gyrus (PHG), hippocampus, frontal lobe and temporal lobe of five SDAT patients. The frequency of various sizes of plaques were determined in each of these brain regions. Statistical analysis showed that the ratio of large plaques to small plaques was greater in the hippocampal formation (especially the PHG) than in the neocortex. One explanation of these results is that plaques grow more rapidly in the hippocampal formation than elsewhere. Alternatively, if the rate of plaque growth is much the same in different brain regions, the data suggest that plaques develop first in the hippocampal formation (especially the PHG) and only later spread to the neocortex. This interpretation is also consistent with the theory that the neuropathology of SDAT spreads from the olfactory cortex via the hippocampal formation to the neocortex. Further development of this technique may help identify the site of the primary lesion in SDAT.

Effect of dopamine on synchronous neuronal oscillations in the globus pallidus-subthalamic nucleus network

Changes in the pattern of activity of neurones within the basal ganglia are relevant in the pathophysiology and symptoms of Parkinson’s disease. The globus pallidus (GP) – subthalamic nucleus (STN) network has been proposed to form a pacemaker driving regenerative synchronous bursting activity. In order to test whether this activity can be sustained in vitro a 20o parasagittal slice of mouse midbrain was developed which preserved functional connectivity between the STN and GP. Mouse STN and GP cells were characterised electrophysiologically by the presence or absence of a voltage sag in response to hyperpolarising current steps indicative of Ih and the presence of rebound depolarisations. The presence of evoked and spontaneous post-synaptic GABA and glutamatergic currents indicated functional connectivity between the STN and GP. In control slices, STN cells fired action potentials at a regular rate, activity which was unaffected by bath application of the GABAA receptor antagonist picrotoxin (50 μM) or the glutamate receptor antagonist CNQX (10 μM). Paired extracellular recordings of STN cells showed uncorrelated firing. Oscillatory burst activity was induced pharmacologically using the glutamate receptor agonist, NMDA (20 μM), in combination with the potassium channel blocker apamin (50 -100 nM). The burst activity was unaffected by bath application of picrotoxin or CNQX while paired STN recordings showed uncorrelated activity indicating that the activity is not produced by the neuronal network. Thus, no regenerative activity is evident in this mouse brain preparation, either in control slices or when bursting is pharmacologically induced, suggesting the requirement of other afferent inputs that are not present in the slice. Using single-unit extracellular recording, dopamine (30 μM) produced an excitation of STN cells. This excitation was independent of synaptic transmission and was mimicked by both the Dl-like receptor agonist SKF38393 (10 μM) and the D2-like receptor agonist quinpirole (10 μM). However, the excitation was partially reduced by the D1-like antagonist SCH23390 (2 μM) but not by the D2-like antagonists sulpiride (10 μM) and eticlopride (10 μM). Using whole-recordings, dopamine was shown to induce membrane depolarisation. This depolarisation was caused either by a D1-like receptor mediated increase in a conductance which reversed at -34 mV, consistent with a non-specific cation conductance, or a D2-like receptor mediated decrease in conductance which reversed around -100 mV, consistent with a potassium conductance. Bath application of dopamine altered the pattern of the burst-firing produced by NMDA an apamin towards a more regular pattern. This effect was associated with a decrease in amplitude and ll1crease in frequency of TTX-resistant plateau potentials which underlie the burst activity.

Changes in neural complexity during the perception of 3D images using random dot stereograms

One developing theme in consciousness research is that consciousness is not the product of any specific component of the brain, rather it is an emergent property of the changing patterns of connectivity between different specialised functional components. For example, the dynamic core hypothesis proposes that conscious experience requires high levels of neural complexity, where complexity is defined in terms of functional connectivity. To test this hypothesis, electroencephalography was recorded while participants were shown random dot-stereograms. Consistent with the dynamic core hypothesis, neural complexity increased as the participants changed from simply viewing the stereogram to consciously perceiving the hidden 3D image.

Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans

Because of attentional limitations, the human visual system can process for awareness and response only a fraction of the input received. Lesion and functional imaging studies have identified frontal, temporal, and parietal areas as playing a major role in the attentional control of visual processing, but very little is known about how these areas interact to form a dynamic attentional network. We hypothesized that the network communicates by means of neural phase synchronization, and we used magnetoencephalography to study transient long-range interarea phase coupling in a well studied attentionally taxing dual-target task (attentional blink). Our results reveal that communication within the fronto-parieto-temporal attentional network proceeds via transient long-range phase synchronization in the beta band. Changes in synchronization reflect changes in the attentional demands of the task and are directly related to behavioral performance. Thus, we show how attentional limitations arise from the way in which the subsystems of the attentional network interact. The human brain faces an inestimable task of reducing a potentially overloading amount of input into a manageable flow of information that reflects both the current needs of the organism and the external demands placed on it. This task is accomplished via a ubiquitous construct known as “attention,” whose mechanism, although well characterized behaviorally, is far from understood at the neurophysiological level. Whereas attempts to identify particular neural structures involved in the operation of attention have met with considerable success (1-5) and have resulted in the identification of frontal, parietal, and temporal regions, far less is known about the interaction among these structures in a way that can account for the task-dependent successes and failures of attention. The goal of the present research was, thus, to unravel the means by which the subsystems making up the human attentional network communicate and to relate the temporal dynamics of their communication to observed attentional limitations in humans. A prime candidate for communication among distributed systems in the human brain is neural synchronization (for review, see ref. 6). Indeed, a number of studies provide converging evidence that long-range interarea communication is related to synchronized oscillatory activity (refs. 7-14; for review, see ref. 15). To determine whether neural synchronization plays a role in attentional control, we placed humans in an attentionally demanding task and used magnetoencephalography (MEG) to track interarea communication by means of neural synchronization. In particular, we presented 10 healthy subjects with two visual target letters embedded in streams of 13 distractor letters, appearing at a rate of seven per second. The targets were separated in time by a single distractor. This condition leads to the “attentional blink” (AB), a well studied dual-task phenomenon showing the reduced ability to report the second of two targets when an interval <500 ms separates them (16-18). Importantly, the AB does not prevent perceptual processing of missed target stimuli but only their conscious report (19), demonstrating the attentional nature of this effect and making it a good candidate for the purpose of our investigation. Although numerous studies have investigated factors, e.g., stimulus and timing parameters, that manipulate the magnitude of a particular AB outcome, few have sought to characterize the neural state under which “standard” AB parameters produce an inability to report the second target on some trials but not others. We hypothesized that the different attentional states leading to different behavioral outcomes (second target reported correctly or not) are characterized by specific patterns of transient long-range synchronization between brain areas involved in target processing. Showing the hypothesized correspondence between states of neural synchronization and human behavior in an attentional task entails two demonstrations. First, it needs to be demonstrated that cortical areas that are suspected to be involved in visual-attention tasks, and the AB in particular, interact by means of neural synchronization. This demonstration is particularly important because previous brain-imaging studies (e.g., ref. 5) only showed that the respective areas are active within a rather large time window in the same task and not that they are concurrently active and actually create an interactive network. Second, it needs to be demonstrated that the pattern of neural synchronization is sensitive to the behavioral outcome; specifically, the ability to correctly identify the second of two rapidly succeeding visual targets

A Statistical Convergence Aplication for the Hopfield Networks

When Recurrent Neural Networks (RNN) are going to be used as Pattern Recognition systems, the problem to be considered is how to impose prescribed prototype vectors ξ^1,ξ^2,...,ξ^p as fixed points. The synaptic matrix W should be interpreted as a sort of sign correlation matrix of the prototypes, In the classical approach. The weak point in this approach, comes from the fact that it does not have the appropriate tools to deal efficiently with the correlation between the state vectors and the prototype vectors The capacity of the net is very poor because one can only know if one given vector is adequately correlated with the prototypes or not and we are not able to know what its exact correlation degree. The interest of our approach lies precisely in the fact that it provides these tools. In this paper, a geometrical vision of the dynamic of states is explained. A fixed point is viewed as a point in the Euclidean plane R2. The retrieving procedure is analyzed trough statistical frequency distribution of the prototypes. The capacity of the net is improved and the spurious states are reduced. In order to clarify and corroborate the theoretical results, together with the formal theory, an application is presented

On the Vertex Separation of Cactus Graphs

This paper is part of a work in progress whose goal is to construct a fast, practical algorithm for the vertex separation (VS) of cactus graphs. We prove a \main theorem for cacti", a necessary and sufficient condition for the VS of a cactus graph being k. Further, we investigate the ensuing ramifications that prevent the construction of an algorithm based on that theorem only.

On the Vertex Separation of Maximal Outerplanar Graphs

We investigate the NP-complete problem Vertex Separation (VS) on Maximal Outerplanar Graphs (mops). We formulate and prove a “main theorem for mops”, a necessary and sufficient condition for the vertex separation of a mop being k. The main theorem reduces the vertex separation of mops to a special kind of stretchability, one that we call affixability, of submops.

A New Approach for Eliminating the Spurious States in Recurrent Neural Networks

As is well known, the Convergence Theorem for the Recurrent Neural Networks, is based in Lyapunov ́s second method, which states that associated to any one given net state, there always exist a real number, in other words an element of the one dimensional Euclidean Space R, in such a way that when the state of the net changes then its associated real number decreases. In this paper we will introduce the two dimensional Euclidean space R2, as the space associated to the net, and we will define a pair of real numbers ( x, y ) , associated to any one given state of the net. We will prove that when the net change its state, then the product x ⋅ y will decrease. All the states whose projection over the energy field are placed on the same hyperbolic surface, will be considered as points with the same energy level. On the other hand we will prove that if the states are classified attended to their distances to the zero vector, only one pattern in each one of the different classes may be at the same energy level. The retrieving procedure is analyzed trough the projection of the states on that plane. The geometrical properties of the synaptic matrix W may be used for classifying the n-dimensional state- vector space in n classes. A pattern to be recognized is seen as a point belonging to one of these classes, and depending on the class the pattern to be retrieved belongs, different weight parameters are used. The capacity of the net is improved and the spurious states are reduced. In order to clarify and corroborate the theoretical results, together with the formal theory, an application is presented.

A Linear Time Algorithm for Computing Longest Paths in Cactus Graphs

ACM Computing Classification System (1998): G.2.2.

Brain activity modifications following spinal cord stimulation for chronic neuropathic pain:a systematic review

Background and objective: Spinal cord stimulation (SCS) is believed to exert supraspinal effects; however, these mechanisms are still far from fully elucidated. This systematic review aims to assess existing neurophysiological and functional neuroimaging literature to reveal current knowledge regarding the effects of SCS for chronic neuropathic pain on brain activity, to identify gaps in knowledge, and to suggest directions for future research. Databases and data treatment: Electronic databases and hand-search of reference lists were employed to identify publications investigating brain activity associated with SCS in patients with chronic neuropathic pain, using neurophysiological and functional neuroimaging techniques (fMRI, PET, MEG, EEG). Studies investigating patients with SCS for chronic neuropathic pain and studying brain activity related to SCS were included. Demographic data (age, gender), study factors (imaging modality, patient diagnoses, pain area, duration of SCS at recording, stimulus used) and brain areas activated were extracted from the included studies. Results: Twenty-four studies were included. Thirteen studies used neuroelectrical imaging techniques, eight studies used haemodynamic imaging techniques, two studies employed both neuroelectrical and haemodynamic techniques separately, and one study investigated cerebral neurobiology. Conclusions: The limited available evidence regarding supraspinal mechanisms of SCS does not allow us to develop any conclusive theories. However, the studies included appear to show an inhibitory effect of SCS on somatosensory evoked potentials, as well as identifying the thalamus and anterior cingulate cortex as potential mediators of the pain experience. The lack of substantial evidence in this area highlights the need for large-scale controlled studies of this kind.

Pediatric CNS pathophysiology

Research in pediatric central nervous system pathophysiology is focused around three primary goals: identification of neurodevelopmental disorders, understanding the differences in brain development which underlie these disorders, and improving treatment for these young children. Autism spectrum disorders (ASDs) are a complex set of disorders which are characterized by difficulties in language and social interactions. These behavioral measures are highly variable and a number of underlying causes can generate similar behavioral effects. Therefore, it is important to identify neurophysiological markers to better identify and characterize these disorders. Recent ASD findings using MEG show atypical latency and amplitude responses and poor cortical connectivity in children with ASDs across the cognitive spectrum from basic auditory processing, multisensory integration, to face and semantic processing. These results further support the view that ASDs are a complex neurologically-based disorder. On the other hand, the cause of Down syndrome is well understood as originating from a partial or full replication of chromosome 21. However, the cognitive and neurological consequences of this chromosomal abnormality are not yet well understood. Using a simple observation and motor execution task, poor functional connectivity in sensory-motor areas, particularly in the gamma band range, has been identified in children with Down syndrome and is consistent with behavioral deficits in the sensory-motor realm. Additional studies are needed to better understand whether targeted identification of these abnormalities can facilitate treatment in this disorder. Finally, while epilepsy can be reliably diagnosed, seizure control is still limited in many cases where the seizure onset zone is not readily apparent. Advances in pre-surgical evaluation and intra-operative co-registration will be described. These studies describing pediatric CNS pathophysiology will be discussed. © Springer-Verlag 2010.

Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.

A Study of Some Centrality Measures in Graphs

Centrality is in fact one of the fundamental notions in graph theory which has established its close connection with various other areas like Social networks, Flow networks, Facility location problems etc. Even though a plethora of centrality measures have been introduced from time to time, according to the changing demands, the term is not well defined and we can only give some common qualities that a centrality measure is expected to have. Nodes with high centrality scores are often more likely to be very powerful, indispensable, influential, easy propagators of information, significant in maintaining the cohesion of the group and are easily susceptible to anything that disseminate in the network.

Propriedades Psicométricas da Bateria de Avaliação Frontal numa Amostra de Adultos da População Portuguesa

The Frontal Assessment Batery / A Bateria de Avaliação Frontal (FAB) é um teste neuropsicológico, constituído por seis subtestes, cujo objetivo é avaliar a disfunção executiva global, nomeadamente as funções relacionadas com o lobo frontal, tais como a concetualização, flexibilidade mental, programação motora, sensibilidade à interferência, controlo inibitório e autonomia ambiental frontal. De forma a contribuir para o avanço dos estudos normativos em Portugal, esta dissertação tem como objetivo avaliar as propriedades psicométricas da FAB, numa amostra de adultos da população portuguesa. O protocolo abrangeu a seguinte bateria de testes neuropsicológicos: Bateria de Avaliação Frontal, Figura Complexa de Rey, Matrizes Progressivas de Raven e Teste do Desenho do Relógio. A amostra deste estudo incluiu 376 indivíduos, 155 do sexo masculino e 221 do sexo feminino. Os resultados desta investigação sugerem que a pontuação da FAB é influenciada por algumas variáveis sociodemográficas, designadamente a idade, escolaridade, profissões e região. A análise correlacional mostrou que há apenas uma correlação positiva moderada entre a FAB e as Matrizes Progressivas de Raven. Apesar da consistência interna da FAB ser baixa, existe uma estabilidade temporal moderada. Ao finalizar, consideramos que a FAB reúne os requisitos para se apresentar como uma bateria útil e eficaz, demonstrando um grau razoável de estabilidade temporal, mas fraca consistência interna, sugerindo que a FAB não é indicada para amostra não clínica. / The Frontal Assessment Baterry (FAB) is a neuropsychological test, composed of six subtests, whose aim is to assess the overall executive dysfunction, namely functions related to the frontal lobe, such as conceptualization, mental flexibility, motor programming, sensitivity to interference, inhibitory control and environmental autonomy. In order to contribute to the advancement of normative studies in Portugal, this dissertation aim to evaluate the psychometric properties of the FAB, in an adult sample of the portuguese population. The protocol included the following battery of neuropsychological tests: Frontal Assessment Battery, Complex Figure of Rey, Raven's Progressive Matrices and Clock Drawing Test. The sample this study included 376 individuals, 155 male and 221 female. The results of this investigation suggest that FAB is influenced by some sociodemographic variables, namely age, education, profession and region. The correlational analysis showed that there is only a moderate positive correlation between the FAB and the Raven Progressive Matrices. However, also they found low positive correlations between the FAB and the Complex Figure of Rey, and Clock Drawing Test. Although the FAB has a low internal consistency, there is a moderate temporal stability. Finally, we consider that the FAB gathers the requirements to present itself as a useful and effective battery, demonstrating a reasonable degree of temporal stability, but weaker internal consistency, suggesting that the FAB is not indicate for non-clinical sample.

Cerebrotendinous xanthomatosis with bradyphrenia and psychiatric disorders: a case with 18F-FDG PET imaging and a literature review

Background and Objectives: Cerebrotendinous xanthomatosis (CTX) is a rare autosomal recessive lipid-storage disease caused by mutations in the CYP27A1. The purpose of this study is to determine the clinical characteristics, neuroimaging and mutation detect in a family with CTX systematically. Methods: Collecting history materials and detecting the routine clinical biochemical tests and imaging examination, and for the first time taking the whole body positron emission tomography (PET)-CT examination for probed in the world to research abnormal metabolism activities in CTX. To observe the effect of treatment with chenodeoxycholic acid (CDCA) and stains before and after the intervention, using serum lipid level detection and neuropsychological evaluation. Genetic testing was carried out to screen the nine exons and exon-intron boundaries about 200-300bq of CYP27A1. Results: A 37-year-old woman with typical clinical characteristics of CTX. Magnetic resonance imaging (MRI) of brain showed bilateral lesions in the dentate nucleus of the cerebellum, then, PET images revealed multiple abnormal hypermetabolism areas at distal tendon, and multifocal areas of hypometabolism in bilateral sides of cerebellar hemispheres, the frontal lobe and temporal lobe. Histopathology reveals accumulation of xanthoma cells and dispersed lipid crystal clefts in xanthomas. In genetic analysis, it shown an insertion of cytosine (77-78insC) located in the first exon of CYP27A1 in the proband. Conclusions: We found that a Chinese patient presented a typical clinical feature of CTX along with clear correlation on both structural and functional imaging had a novel mutation in the CYP27A1 gene.