Anatomical connections of the periaqueductal gray: specific neural substrates for different kinds of fear

The periaqueductal gray (PAG) has been traditionally considered to be an exit relay for defensive responses. Functional mapping of its subdivisions has advanced our knowledge of this structure, but synthesis remains difficult mainly because results from lesion and stimulation studies have not correlated perfectly. After using a strategy that combined both techniques and a reevaluation of the available literature on PAG function and connections, we propose here that freezing could be mediated by different PAG subdivisions depending on the presence of immediate danger or exposure to related signaling cues. These subdivisions are separate functional entities with distinct descending and ascending connections that are likely to play a role in different defensive responses. The existence of ascending connections also suggests that the PAG is not simply a final common path for defensive responses. For example, the possibility that indirect ascending connections to the cingulate cortex could play a role in the expression of freezing evoked by activation of the neural substrate of fear in the dorsal PAG has been considered.

Activation of neural cholecystokinin-1 receptors induces relaxation of the isolated rat duodenum which is reduced by nitric oxide synthase inhibitors

Cholecystokinin (CCK) influences gastrointestinal motility, by acting on central and peripheral receptors. The aim of the present study was to determine whether CCK has any effect on isolated duodenum longitudinal muscle activity and to characterize the mechanisms involved. Isolated segments of the rat proximal duodenum were mounted for the recording of isometric contractions of longitudinal muscle in the presence of atropine and guanethidine. CCK-8S (EC50: 39; 95% CI: 4.1-152 nM) and cerulein (EC50: 58; 95% CI: 18-281 nM) induced a concentration-dependent and tetrodotoxin-sensitive relaxation. Nomeganitro-L-arginine (L-NOARG) reduced CCK-8S- and cerulein-induced relaxation (IC50: 5.2; 95% CI: 2.5-18 µM) in a concentration-dependent manner. The magnitude of 300 nM CCK-8S-induced relaxation was reduced by 100 µM L-NOARG from 73 ± 5.1 to 19 ± 3.5% in an L-arginine but not D-arginine preventable manner. The CCK-1 receptor antagonists proglumide, lorglumide and devazepide, but not the CCK-2 receptor antagonist L-365,260, antagonized CCK-8S-induced relaxation in a concentration-dependent manner. These findings suggest that CCK-8S and cerulein activate intrinsic nitrergic nerves acting on CCK-1 receptors in order to cause relaxation of the rat duodenum longitudinal muscle.

An immunohistochemical, clinical and electroneuromyographic correlative study of the neural markers in the neuritic form of leprosy

The nerve biopsies of 11 patients with pure neuritic leprosy were submitted to routine diagnostic procedures and immunoperoxidase staining with antibodies against axonal (neurofilament, nerve growth factor receptor (NGFr), and protein gene product (PGP) 9.5) and Schwann cell (myelin basic protein, S-100 protein, and NGFr) markers. Two pairs of non-adjacent histological cross-sections of the peripheral nerve were removed for quantification. All the fascicles of the nerve were examined with a 10X-ocular and 40X-objective lens. The immunohistochemistry results were compared to the results of semithin section analysis and clinical and electroneuromyographic data. Neurofilament staining was reduced in 100% of the neuritic biopsies. NGFr positivity was also reduced in 81.8%, PGP staining in 100% of the affected nerves, S100 positivity in 90.9%, and myelin basic protein immunoreactivity in 90.9%. Hypoesthesia was associated with decreased NGFr (81.8%) and PGP staining (90.9%). Reduced potential amplitudes (electroneuromyographic data) were found to be associated with reduced PGP 9.5 (63.6%) and nerve fiber neurofilament staining (45.4%) by immunohistochemistry and with loss of myelinated fibers (100%) by semithin section analysis. On the other hand, the small fibers (immunoreactive dots) seen amid inflammatory cells continued to be present even after 40% of the larger myelinated fibers had disappeared. The present study shows an in-depth view of the destructive effects of leprosy upon the expression of neural markers and the integrity of nerve fiber. The association of these structural changes with the clinical and electroneuromyographic manifestations of leprosy peripheral neuropathy was also discussed.

Water deprivation and the double- depletion hypothesis: common neural mechanisms underlie thirst and salt appetite

Water deprivation-induced thirst is explained by the double-depletion hypothesis, which predicts that dehydration of the two major body fluid compartments, the extracellular and intracellular compartments, activates signals that combine centrally to induce water intake. However, sodium appetite is also elicited by water deprivation. In this brief review, we stress the importance of the water-depletion and partial extracellular fluid-repletion protocol which permits the distinction between sodium appetite and thirst. Consistent enhancement or a de novo production of sodium intake induced by deactivation of inhibitory nuclei (e.g., lateral parabrachial nucleus) or hormones (oxytocin, atrial natriuretic peptide), in water-deprived, extracellular-dehydrated or, contrary to tradition, intracellular-dehydrated rats, suggests that sodium appetite and thirst share more mechanisms than previously thought. Water deprivation has physiological and health effects in humans that might be related to the salt craving shown by our species.

Engagement of multifocal neural circuits during recall of autobiographical happy events

Happy emotional states have not been extensively explored in functional magnetic resonance imaging studies using autobiographic recall paradigms. We investigated the brain circuitry engaged during induction of happiness by standardized script-driven autobiographical recall in 11 healthy subjects (6 males), aged 32.4 ± 7.2 years, without physical or psychiatric disorders, selected according to their ability to vividly recall personal experiences. Blood oxygen level-dependent (BOLD) changes were recorded during auditory presentation of personal scripts of happiness, neutral content and negative emotional content (irritability). The same uniform structure was used for the cueing narratives of both emotionally salient and neutral conditions, in order to decrease the variability of findings. In the happiness relative to the neutral condition, there was an increased BOLD signal in the left dorsal prefrontal cortex and anterior insula, thalamus bilaterally, left hypothalamus, left anterior cingulate gyrus, and midportions of the left middle temporal gyrus (P < 0.05, corrected for multiple comparisons). Relative to the irritability condition, the happiness condition showed increased activity in the left insula, thalamus and hypothalamus, and in anterior and midportions of the inferior and middle temporal gyri bilaterally (P < 0.05, corrected), varying in size between 13 and 64 voxels. Findings of happiness-related increased activity in prefrontal and subcortical regions extend the results of previous functional imaging studies of autobiographical recall. The BOLD signal changes identified reflect general aspects of emotional processing, emotional control, and the processing of sensory and bodily signals associated with internally generated feelings of happiness. These results reinforce the notion that happiness induction engages a wide network of brain regions.

Central chemoreceptors and neural mechanisms of cardiorespiratory control

The arterial partial pressure (P CO2) of carbon dioxide is virtually constant because of the close match between the metabolic production of this gas and its excretion via breathing. Blood gas homeostasis does not rely solely on changes in lung ventilation, but also to a considerable extent on circulatory adjustments that regulate the transport of CO2 from its sites of production to the lungs. The neural mechanisms that coordinate circulatory and ventilatory changes to achieve blood gas homeostasis are the subject of this review. Emphasis will be placed on the control of sympathetic outflow by central chemoreceptors. High levels of CO2 exert an excitatory effect on sympathetic outflow that is mediated by specialized chemoreceptors such as the neurons located in the retrotrapezoid region. In addition, high CO2 causes an aversive awareness in conscious animals, activating wake-promoting pathways such as the noradrenergic neurons. These neuronal groups, which may also be directly activated by brain acidification, have projections that contribute to the CO2-induced rise in breathing and sympathetic outflow. However, since the level of activity of the retrotrapezoid nucleus is regulated by converging inputs from wake-promoting systems, behavior-specific inputs from higher centers and by chemical drive, the main focus of the present manuscript is to review the contribution of central chemoreceptors to the control of autonomic and respiratory mechanisms.

Neural regulation of the stress response: glucocorticoid feedback mechanisms

The mammalian stress response is an integrated physiological and psychological reaction to real or perceived adversity. Glucocorticoids are an important component of this response, acting to redistribute energy resources to both optimize survival in the face of challenge and to restore homeostasis after the immediate challenge has subsided. Release of glucocorticoids is mediated by the hypothalamo-pituitary-adrenal (HPA) axis, driven by a neural signal originating in the paraventricular nucleus (PVN). Stress levels of glucocorticoids bind to glucocorticoid receptors in multiple body compartments, including the brain, and consequently have wide-reaching actions. For this reason, glucocorticoids serve a vital function in negative feedback inhibition of their own secretion. Negative feedback inhibition is mediated by a diverse collection of mechanisms, including fast, non-genomic feedback at the level of the PVN, stress-shut-off at the level of the limbic system, and attenuation of ascending excitatory input through destabilization of mRNAs encoding neuropeptide drivers of the HPA axis. In addition, there is evidence that glucocorticoids participate in stress activation via feed-forward mechanisms at the level of the amygdala. Feedback deficits are associated with numerous disease states, underscoring the necessity for adequate control of glucocorticoid homeostasis. Thus, rather than having a single, defined feedback ‘switch’, control of the stress response requires a wide-reaching feedback ‘network’ that coordinates HPA activity to suit the overall needs of multiple body systems.

What ethologically based models have taught us about the neural systems underlying fear and anxiety

Classical Pavlovian fear conditioning to painful stimuli has provided the generally accepted view of a core system centered in the central amygdala to organize fear responses. Ethologically based models using other sources of threat likely to be expected in a natural environment, such as predators or aggressive dominant conspecifics, have challenged this concept of a unitary core circuit for fear processing. We discuss here what the ethologically based models have told us about the neural systems organizing fear responses. We explored the concept that parallel paths process different classes of threats, and that these different paths influence distinct regions in the periaqueductal gray - a critical element for the organization of all kinds of fear responses. Despite this parallel processing of different kinds of threats, we have discussed an interesting emerging view that common cortical-hippocampal-amygdalar paths seem to be engaged in fear conditioning to painful stimuli, to predators and, perhaps, to aggressive dominant conspecifics as well. Overall, the aim of this review is to bring into focus a more global and comprehensive view of the systems organizing fear responses.

Mapping and signaling of neural pathways involved in the regulation of hydromineral homeostasis

Several forebrain and brainstem neurochemical circuitries interact with peripheral neural and humoral signals to collaboratively maintain both the volume and osmolality of extracellular fluids. Although much progress has been made over the past decades in the understanding of complex mechanisms underlying neuroendocrine control of hydromineral homeostasis, several issues still remain to be clarified. The use of techniques such as molecular biology, neuronal tracing, electrophysiology, immunohistochemistry, and microinfusions has significantly improved our ability to identify neuronal phenotypes and their signals, including those related to neuron-glia interactions. Accordingly, neurons have been shown to produce and release a large number of chemical mediators (neurotransmitters, neurohormones and neuromodulators) into the interstitial space, which include not only classic neurotransmitters, such as acetylcholine, amines (noradrenaline, serotonin) and amino acids (glutamate, GABA), but also gaseous (nitric oxide, carbon monoxide and hydrogen sulfide) and lipid-derived (endocannabinoids) mediators. This efferent response, initiated within the neuronal environment, recruits several peripheral effectors, such as hormones (glucocorticoids, angiotensin II, estrogen), which in turn modulate central nervous system responsiveness to systemic challenges. Therefore, in this review, we shall evaluate in an integrated manner the physiological control of body fluid homeostasis from the molecular aspects to the systemic and integrated responses.

Artificial neural network models for predicting 1-year mortality in elderly patients with intertrochanteric fractures in China

The mortality rate of older patients with intertrochanteric fractures has been increasing with the aging of populations in China. The purpose of this study was: 1) to develop an artificial neural network (ANN) using clinical information to predict the 1-year mortality of elderly patients with intertrochanteric fractures, and 2) to compare the ANN's predictive ability with that of logistic regression models. The ANN model was tested against actual outcomes of an intertrochanteric femoral fracture database in China. The ANN model was generated with eight clinical inputs and a single output. ANN's performance was compared with a logistic regression model created with the same inputs in terms of accuracy, sensitivity, specificity, and discriminability. The study population was composed of 2150 patients (679 males and 1471 females): 1432 in the training group and 718 new patients in the testing group. The ANN model that had eight neurons in the hidden layer had the highest accuracies among the four ANN models: 92.46 and 85.79% in both training and testing datasets, respectively. The areas under the receiver operating characteristic curves of the automatically selected ANN model for both datasets were 0.901 (95%CI=0.814-0.988) and 0.869 (95%CI=0.748-0.990), higher than the 0.745 (95%CI=0.612-0.879) and 0.728 (95%CI=0.595-0.862) of the logistic regression model. The ANN model can be used for predicting 1-year mortality in elderly patients with intertrochanteric fractures. It outperformed a logistic regression on multiple performance measures when given the same variables.

HYBRID ARTIFICIAL NEURAL NETWORK APPLIEDTO MODELING SCFE OF BASIL AND ROSEMARY OILS

This work presents the results of a Hybrid Neural Network (HNN) technique as applied to modeling SCFE curves obtained from two Brazilian vegetable matrices. A series Hybrid Neural Network was employed to estimate the parameters of the phenomenological model. A small set of SCFE data of each vegetable was used to generate an extended data set, sufficient to train the network. Afterwards, other sets of experimental data, not used in the network training, were used to validate the present approach. The series HNN correlates well the experimental data and it is shown that the predictions accomplished with this technique may be promising for SCFE purposes.

Power and Performance Management Strategies on NoC-Based Multicore Platforms, Using DVFS, Adaptive Algorithm and Task Parallelism

This work presents synopsis of efficient strategies used in power managements for achieving the most economical power and energy consumption in multicore systems, FPGA and NoC Platforms. In this work, a practical approach was taken, in an effort to validate the significance of the proposed Adaptive Power Management Algorithm (APMA), proposed for system developed, for this thesis project. This system comprise arithmetic and logic unit, up and down counters, adder, state machine and multiplexer. The essence of carrying this project firstly, is to develop a system that will be used for this power management project. Secondly, to perform area and power synopsis of the system on these various scalable technology platforms, UMC 90nm nanotechnology 1.2v, UMC 90nm nanotechnology 1.32v and UMC 0.18 μmNanotechnology 1.80v, in order to examine the difference in area and power consumption of the system on the platforms. Thirdly, to explore various strategies that can be used to reducing system’s power consumption and to propose an adaptive power management algorithm that can be used to reduce the power consumption of the system. The strategies introduced in this work comprise Dynamic Voltage Frequency Scaling (DVFS) and task parallelism. After the system development, it was run on FPGA board, basically NoC Platforms and on these various technology platforms UMC 90nm nanotechnology1.2v, UMC 90nm nanotechnology 1.32v and UMC180 nm nanotechnology 1.80v, the system synthesis was successfully accomplished, the simulated result analysis shows that the system meets all functional requirements, the power consumption and the area utilization were recorded and analyzed in chapter 7 of this work. This work extensively reviewed various strategies for managing power consumption which were quantitative research works by many researchers and companies, it's a mixture of study analysis and experimented lab works, it condensed and presents the whole basic concepts of power management strategy from quality technical papers.

Pretraining Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks (CNN) have become the state-of-the-art methods on many large scale visual recognition tasks. For a lot of practical applications, CNN architectures have a restrictive requirement: A huge amount of labeled data are needed for training. The idea of generative pretraining is to obtain initial weights of the network by training the network in a completely unsupervised way and then fine-tune the weights for the task at hand using supervised learning. In this thesis, a general introduction to Deep Neural Networks and algorithms are given and these methods are applied to classification tasks of handwritten digits and natural images for developing unsupervised feature learning. The goal of this thesis is to find out if the effect of pretraining is damped by recent practical advances in optimization and regularization of CNN. The experimental results show that pretraining is still a substantial regularizer, however, not a necessary step in training Convolutional Neural Networks with rectified activations. On handwritten digits, the proposed pretraining model achieved a classification accuracy comparable to the state-of-the-art methods.

Modelling the colour difference by artificial neural network

This thesis work studies the modelling of the colour difference using artificial neural network. Multilayer percepton (MLP) network is proposed to model CIEDE2000 colour difference formula. MLP is applied to classify colour points in CIE xy chromaticity diagram. In this context, the evaluation was performed using Munsell colour data and MacAdam colour discrimination ellipses. Moreover, in CIE xy chromaticity diagram just noticeable differences (JND) of MacAdam ellipses centres are computed by CIEDE2000, to compare JND of CIEDE2000 and MacAdam ellipses. CIEDE2000 changes the orientation of blue areas in CIE xy chromaticity diagram toward neutral areas, but on the whole it does not totally agree with the MacAdam ellipses. The proposed MLP for both modelling CIEDE2000 and classifying colour points showed good accuracy and achieved acceptable results.