Neural stem cells and cell replacement therapy: making the right cells

The past few years have seen major advances in the field of NSC (neural stem cell) research with increasing emphasis towards its application in cell-replacement therapy for neurological disorders. However, the clinical application of NSCs will remain largely unfeasible until a comprehensive understanding of the cellular and molecular mechanisms of NSC fate specification is achieved. With this understanding will come an increased possibility to exploit the potential of stem cells in order to manufacture transplantable NSCs able to provide a safe and effective therapy for previously untreatable neurological disorders. Since the pathology of each of these disorders is determined by the loss or damage of a specific neural cell population, it may be necessary to generate a range of NSCs able to replace specific neurons or glia rather than generating a generic NSC population. Currently, a diverse range of strategies is being investigated with this goal in mind. In this review, we focus on the relationship between NSC specification and differentiation and discuss how this information may be used to direct NSCs towards a particular fate.

The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions

Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

Making an effort to feel positive: insecure attachment in infancy predicts the neural underpinnings of emotion regulation in adulthood

Background: Animal research indicates that the neural substrates of emotion regulation may be persistently altered by early environmental exposures. If similar processes operate in human development then this is significant, as the capacity to regulate emotional states is fundamental to human adaptation. Methods: We utilised a 22-year longitudinal study to examine the influence of early infant attachment to the mother, a key marker of early experience, on neural regulation of emotional states in young adults. Infant attachment status was measured via objective assessment at 18-months, and the neural underpinnings of the active regulation of affect were studied using fMRI at age 22 years. Results: Infant attachment status at 18-months predicted neural responding during the regulation of positive affect 20-years later. Specifically, while attempting to up-regulate positive emotions, adults who had been insecurely versus securely attached as infants showed greater activation in prefrontal regions involved in cognitive control and reduced co-activation of prefrontal cortex and nucleus accumbens, consistent with relative inefficiency in the neural regulation of positive affect. Conclusions: Disturbances in the mother-infant relationship may persistently alter the neural circuitry of emotion regulation, with potential implications for adjustment in adulthood.

Minor structural abnormalities in the infant face disrupt neural processing: a unique window into early caregiving responses

Infant faces elicit early, specific activity in the orbitofrontal cortex (OFC), a key cortical region for reward and affective processing. A test of the causal relationship between infant facial configuration and OFC activity is provided by naturally occurring disruptions to the face structure. One such disruption is cleft lip, a small change to one facial feature, shown to disrupt parenting. Using magnetoencephalography, we investigated neural responses to infant faces with cleft lip compared with typical infant and adult faces. We found activity in the right OFC at 140 ms in response to typical infant faces but diminished activity to infant faces with cleft lip or adult faces. Activity in the right fusiform face area was of similar magnitude for typical adult and infant faces but was significantly lower for infant faces with cleft lip. This is the first evidence that a minor change to the infant face can disrupt neural activity potentially implicated in caregiving.

Computing Fresnel integrals via modified trapezium rules

In this paper we propose methods for computing Fresnel integrals based on truncated trapezium rule approximations to integrals on the real line, these trapezium rules modified to take into account poles of the integrand near the real axis. Our starting point is a method for computation of the error function of complex argument due to Matta and Reichel (J Math Phys 34:298–307, 1956) and Hunter and Regan (Math Comp 26:539–541, 1972). We construct approximations which we prove are exponentially convergent as a function of N , the number of quadrature points, obtaining explicit error bounds which show that accuracies of 10−15 uniformly on the real line are achieved with N=12 , this confirmed by computations. The approximations we obtain are attractive, additionally, in that they maintain small relative errors for small and large argument, are analytic on the real axis (echoing the analyticity of the Fresnel integrals), and are straightforward to implement.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Opposing neural effects of naltrexone on food reward and aversion: implications for the treatment of obesity

Rationale: Opioid antagonism reduces the consumption of palatable foods in humans but the neural substrates implicated in these effects are less well understood. Objectives: The aim of the present study was to examine the effects of the opioid antagonist, naltrexone, on neural response to rewarding and aversive sight and taste stimuli. Methods: We used functional magnetic resonance imaging (fMRI) to examine the neural responses to the sight and taste of pleasant (chocolate) and aversive (mouldy strawberry) stimuli in 20 healthy volunteers who received a single oral dose of naltrexone (50 mg) and placebo in a double-blind, repeated-measures cross-over, design. Results: Relative to placebo, naltrexone decreased reward activation to chocolate in the dorsal anterior cingulate cortex and caudate, and increased aversive-related activation to unpleasant strawberry in the amygdala and anterior insula. Conclusions: These findings suggest that modulation of key brain areas involved in reward processing, cognitive control and habit formation such as the dorsal anterior cingulate cortex (dACC) and caudate might underlie reduction in food intake with opioid antagonism. Furthermore we show for the first time that naltrexone can increase activations related to aversive food stimuli. These results support further investigation of opioid treatments in obesity.

Neural responses to emotional faces in women recovered from anorexia nervosa

Impairments in emotional processing have been associated with anorexia nervosa. However, it is unknown whether neural and behavioural differences in the processing of emotional stimuli persist following recovery. The aim of this study was to investigate the neural processing of emotional faces in individuals recovered from anorexia nervosa compared with healthy controls. Thirty-two participants (16 recovered anorexia nervosa, 16 healthy controls) underwent a functional magnetic resonance imaging (fMRI) scan. Participants viewed fearful and happy emotional faces and indicated the gender of the face presented. Whole brain analysis revealed no significant differences between the groups to the contrasts of fear versus happy and vice versa. Region of interest analysis demonstrated no significant differences in the neural response to happy or fearful stimuli between the groups in the amygdala or fusiform gyrus. These results suggest that processing of emotional faces may not be aberrant after recovery from anorexia nervosa.

The D2 antagonist sulpiride modulates the neural processing of both rewarding and aversive stimuli in healthy volunteers.

Rationale: Animal studies indicate that dopamine pathways in the ventral striatum code for the motivational salience of both rewarding and aversive stimuli, but evidence for this mechanism in humans is less established. We have developed a functional magnetic resonance imaging (fMRI) model which permits examination of the neural processing of both rewarding and aversive stimuli. Objectives: The aim of the study was to determine the effect of the dopamine receptor antagonist, sulpiride, on the neural processing of rewarding and aversive stimuli in healthy volunteers. Methods: We studied 30 healthy participants who were randomly allocated to receive a single dose of sulpiride (400 mg) or placebo, in a double-blind, parallel-group design. We used fMRI to measure the neural response to rewarding (taste or sight of chocolate) and aversive stimuli (sight of mouldy strawberries or unpleasant strawberry taste) 4 h after drug treatment. Results: Relative to placebo, sulpiride reduced blood oxygenation level-dependent responses to chocolate stimuli in the striatum (ventral striatum) and anterior cingulate cortex. Sulpiride also reduced lateral orbitofrontal cortex and insula activations to the taste and sight of the aversive condition. Conclusions: These results suggest that acute dopamine receptor blockade modulates mesolimbic and mesocortical neural activations in response to both rewarding and aversive stimuli in healthy volunteers. This effect may be relevant to the effects of dopamine receptor antagonists in the treatment of psychosis and may also have implications for the possible antidepressant properties of sulpiride.

Reduced neural response to reward following 7 days treatment with the cannabinoid CB1 antagonist rimonabant in healthy volunteers

Reduced subjective experience of reward (anhedonia) is a key symptom of major depression. The anti-obesity drug and cannabinoid type 1 receptor (CB(1)) antagonist, rimonabant, is associated with significant rates of depression and anxiety in clinical use and was recently withdrawn from the market because of these adverse effects. Using a functional magnetic resonance imaging (fMRI) model of reward we hypothesized that rimonabant would impair reward processing. Twenty-two healthy participants were randomly allocated to receive rimonabant (20 mg), or placebo, for 7 d in a double-blind, parallel group design. We used fMRI to measure the neural response to rewarding (sight and/or flavour of chocolate) and aversive (sight of mouldy strawberries and/or an unpleasant strawberry taste) stimuli on the final day of drug treatment. Rimonabant reduced the neural response to chocolate stimuli in key reward areas such as the ventral striatum and the orbitofrontal cortex. Rimonabant also decreased neural responses to the aversive stimulus condition in the caudate nucleus and ventral striatum, but increased lateral orbitofrontal activations to the aversive sight and taste of strawberry condition. Our findings are the first to show that the anti-obesity drug rimonabant inhibits the neural processing of rewarding food stimuli in humans. This plausibly underlies its ability to promote weight loss, but may also indicate a mechanism for inducing anhedonia which could lead to the increased risk of depressive symptomatology seen in clinical use. fMRI may be a useful method of screening novel agents for unwanted effects on reward and associated clinical adverse reactions.

NK1 receptor antagonism and the neural processing of emotional information in healthy volunteers

The neuropeptide substance P and its receptor NK1 have been implicated in emotion, anxiety and stress in preclinical studies. However, the role of NK1 receptors in human brain function is less clear and there have been inconsistent reports of the value of NK1 receptor antagonists in the treatment of clinical depression. The present study therefore aimed to investigate effects of NK1 antagonism on the neural processing of emotional information in healthy volunteers. Twenty-four participants were randomized to receive a single dose of aprepitant (125 mg) or placebo. Approximately 4 h later, neural responses during facial expression processing and an emotional counting Stroop word task were assessed using fMRI. Mood and subjective experience were also measured using self-report scales. As expected a single dose of aprepitant did not affect mood and subjective state in the healthy volunteers. However, NK1 antagonism increased responses specifically during the presentation of happy facial expressions in both the rostral anterior cingulate and the right amygdala. In the emotional counting Stroop task the aprepitant group had increased activation in both the medial orbitofrontal cortex and the precuneus cortex to positive vs. neutral words. These results suggest consistent effects of NK1 antagonism on neural responses to positive affective information in two different paradigms. Such findings confirm animal studies which support a role for NK1 receptors in emotion. Such an approach may be useful in understanding the effects of novel drug treatments prior to full-scale clinical trials.

Neural representation of reward in recovered depressed patients

These findings support the view that abnormal neural responses to reward may be an endophenotype for depression and a potential target for intervention and prevention strategies.

Computing journey start times with recurrent traffic conditions

n this study, the authors discuss the effective usage of technology to solve the problem of deciding on journey start times for recurrent traffic conditions. The developed algorithm guides the vehicles to travel on more reliable routes that are not easily prone to congestion or travel delays, ensures that the start time is as late as possible to avoid the traveller waiting too long at their destination and attempts to minimise the travel time. Experiments show that in order to be more certain of reaching their destination on time, a traveller has to leave early and correspondingly arrive early, resulting in a large waiting time. The application developed here asks the user to set this certainty factor as per the task in hand, and computes the best start time and route.

Towards optimizing the selection of neurons in affordable neural networks

This paper considers variations of a neuron pool selection method known as Affordable Neural Network (AfNN). A saliency measure, based on the second derivative of the objective function is proposed to assess the ability of a trained AfNN to provide neuronal redundancy. The discrepancies between the various affordability variants are explained by correlating unique sub group selections with relevant saliency variations. Overall this study shows that the method in which neurons are selected from a pool is more relevant to how salient individual neurons are, than how often a particular neuron is used during training. The findings herein are relevant to not only providing an analogy to brain function but, also, in optimizing the way a neural network using the affordability method is trained.