Muscarinic acetylcholine receptor expression in memory circuits: Implications for treatment of Alzheimer disease

Cholinergic transmission at muscarinic acetylcholine receptors (mAChR) has been implicated in higher brain functions such as learning and memory, and loss of synapses may contribute to the symptoms of Alzheimer disease. A heterogeneous family of five genetically distinct mAChR subtypes differentially modulate a variety of intracellular signaling systems as well as the processing of key molecules involved in the pathology of the disease. Although many muscarinic effects have been identified in memory circuits, including a diversity of pre- and post-synaptic actions in hippocampus, the identities of the molecular subtypes responsible for any given function remain elusive. All five mAChR genes are expressed in hippocampus, and subtype-specific antibodies have enabled identification, quantification, and localization of the encoded proteins. The m1, m2, and m4 mAChR proteins are most abundant in forebrain regions and they have distinct cellular and subcellular localizations suggestive of various pre- and postsynaptic functions in cholinergic circuits. The subtypes are also differentially altered in postmortem brain samples from Alzheimer disease cases. Further understanding of the molecular pharmacology of failing synapses in Alzheimer disease, together with the development of new subtype-selective drugs, may provide more specific and effective treatments for the disease.

Adrenocortical suppression blocks the memory-enhancing effects of amphetamine and epinephrine.

This study examined glucocorticoid-adrenergic interactions in modulating acquisition and memory storage for inhibitory avoidance training. Systemically (s.c.) administered amphetamine (1 mg/kg), but not epinephrine (0.1 mg/kg) or the peripherally acting amphetamine derivative 4-OH amphetamine (2 mg/kg), given to rats shortly before training facilitated acquisition performance in a continuous multiple-trial inhibitory avoidance (CMIA) task. Adrenocortical suppression with the 11beta-hydroxylase inhibitor metyrapone (50 mg/kg; s.c.), given to rats 90 min before training, did not block the effect of amphetamine and did not affect acquisition performance of otherwise untreated animals. Retention of CMIA and one-trial inhibitory avoidance was enhanced by either pre- or posttraining injections of amphetamine as well as 4-OH amphetamine and epinephrine. The finding that injections of amphetamine and epinephrine have comparable effects on memory is consistent with the view that amphetamine may modulate memory storage, at least in part, by inducing the release of epinephrine from the adrenal medulla. Metyrapone pretreatment blocked the memory-enhancing effects of amphetamine, 4-OH amphetamine, and epinephrine but did not affect retention performance of otherwise untreated animals. Posttraining injections of different doses of epinephrine (ranging from 0.0001 to 1.0 mg/kg) produced a dose-dependent memory enhancement for inhibitory avoidance training and metyrapone blocked the memory-enhancing effects of all these doses. These findings provide further evidence that the sympathoadrenal and adrenocortical systems are intimately coupled during processes of memory storage.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Role of Dopamine D2 Receptors in the Consolidation of Amphetamine-Cue Memory in Conditioned Activity in Rats

The neurotransmitter dopamine (DA) plays an essential role in reward-related incentive learning, whereby neutral stimuli gain the ability to elicit approach and other responses. In an incentive learning paradigm called conditioned activity, animals receive a stimulant drug in a specific environment over the course of several days. When then placed in that environment drug-free, they generally display a conditioned hyperactive response. Modulating DA transmission at different time points during the paradigm has been shown to disrupt or enhance conditioning effects. For instance, blocking DA D2 receptors before sessions generally impedes the acquisition of conditioned activity. To date, no studies have examined the role of D2 receptors in the consolidation phase of conditioned activity; this phase occurs immediately after acquisition and involves the stabilization of memories for long-term storage. To investigate this possible role, I trained Wistar rats (N = 108) in the conditioned activity paradigm produced by amphetamine (2.0 mg/kg, intraperitoneally) to examine the effects of the D2 antagonist haloperidol (doses 0.10, 0.25, 0.50, 0.75, 1.0, & 2.0 mg/kg, intraperitoneally) administered 5 min after conditioning sessions. Two positive control groups received haloperidol 1 h before conditioning sessions (doses 1.0 mg/kg and 2.0 mg/kg). The results revealed that post-session haloperidol at all doses tested did not disrupt the consolidation of conditioned activity, while pre-session haloperidol at 2.0 mg/kg prevented acquisition, with the 1.0 mg/kg group trending toward a block. Additionally, post-session haloperidol did not diminish activity during conditioning days, unlike pre-session haloperidol. One possible reason for these findings is that the consolidation phase may have begun earlier than when haloperidol was administered, since the conditioned activity paradigm uses longer learning sessions than those generally used in consolidation studies. Future studies may test if conditioned activity can be achieved with shorter sessions; if so, haloperidol would then be re-tested at an earlier time point. D2 receptor second messenger systems may also be investigated in consolidation. Since drug-related incentive stimuli can evoke cravings in those with drug addiction, a better understanding of the mechanisms of incentive learning may lead to the development of solutions for these individuals.

Time-sharing on a computer with a small memory,

"Supported in part by Atomic Energy Commission Contract AT(11-1)-1469."

All semiconductor distributed aerospace processor/memory study /

"August 1973."

Impaired memory and olfactory performance in NaSi-1 sulphate transporter deficient mice

In the present study, NaSi-l sulphate transporter knock-out (Nas1-/-) mice, an animal model of hyposulphataernia, were examined for spatial memory and learning in a Morris water maze, and for olfactory function in a cookie test. The Nas1-/- mice displayed significantly (P < 0.05) increased latencies to find an escape platform in the reversal teaming trials at 2 days but not 1 day after the last acquisition trial in a Morris water maze test. suggesting that Nas1-/- mice may have proactive memory interference. While the wild-type (Ncis1+/+) mice showed a significant (P < 0.02) decrease in time to locate a hidden food reward over four trials after overnight fasting, Nas1-/- mice did not change their performance, resulting in significantly (P < 0.05) higher latencies when compared to their Nas1+/+ littermates. There were no significant differences between Nas1-/- and Nas1+/+ mice in the cookie test after moderate food deprivation. In addition, both Nas1-/- and Nas1+/+ mice displayed similar escape latencies in the acquisition phase of the Morris water maze test, suggesting that learning, motivation, vision and motor skills required for the task may not be affected in Nas1-/- mice. This is the first study to demonstrate an impairment in memory and olfactory performance in the hyposulphataemic Nas1-/- mouse. (c) 2004 Elsevier B.V. All rights reserved.

Asymptotic theory of time varying networks with memory and heterogeneous activation pattern

In this thesis work we develop a new generative model of social networks belonging to the family of Time Varying Networks. The importance of correctly modelling the mechanisms shaping the growth of a network and the dynamics of the edges activation and inactivation are of central importance in network science. Indeed, by means of generative models that mimic the real-world dynamics of contacts in social networks it is possible to forecast the outcome of an epidemic process, optimize the immunization campaign or optimally spread an information among individuals. This task can now be tackled taking advantage of the recent availability of large-scale, high-quality and time-resolved datasets. This wealth of digital data has allowed to deepen our understanding of the structure and properties of many real-world networks. Moreover, the empirical evidence of a temporal dimension in networks prompted the switch of paradigm from a static representation of graphs to a time varying one. In this work we exploit the Activity-Driven paradigm (a modeling tool belonging to the family of Time-Varying-Networks) to develop a general dynamical model that encodes fundamental mechanism shaping the social networks' topology and its temporal structure: social capital allocation and burstiness. The former accounts for the fact that individuals does not randomly invest their time and social interactions but they rather allocate it toward already known nodes of the network. The latter accounts for the heavy-tailed distributions of the inter-event time in social networks. We then empirically measure the properties of these two mechanisms from seven real-world datasets and develop a data-driven model, analytically solving it. We then check the results against numerical simulations and test our predictions with real-world datasets, finding a good agreement between the two. Moreover, we find and characterize a non-trivial interplay between burstiness and social capital allocation in the parameters phase space. Finally, we present a novel approach to the development of a complete generative model of Time-Varying-Networks. This model is inspired by the Kaufman's adjacent possible theory and is based on a generalized version of the Polya's urn. Remarkably, most of the complex and heterogeneous feature of real-world social networks are naturally reproduced by this dynamical model, together with many high-order topological properties (clustering coefficient, community structure etc.).

The TAP approach to intensive and extensive connectivity systems

The Thouless-Anderson-Palmer (TAP) approach was originally developed for analysing the Sherrington-Kirkpatrick model in the study of spin glass models and has been employed since then mainly in the context of extensively connected systems whereby each dynamical variable interacts weakly with the others. Recently, we extended this method for handling general intensively connected systems where each variable has only O(1) connections characterised by strong couplings. However, the new formulation looks quite different with respect to existing analyses and it is only natural to question whether it actually reproduces known results for systems of extensive connectivity. In this chapter, we apply our formulation of the TAP approach to an extensively connected system, the Hopfield associative memory model, showing that it produces identical results to those obtained by the conventional formulation.

Memory effects in a non-equilibrium growth model

We study memory effects in a kinetic roughening model. For d=1, a different dynamic scaling is uncovered in the memory dominated phases; the Kardar-Parisi-Zhang scaling is restored in the absence of noise. dc=2 represents the critical dimension where memory is shown to smoothen the roughening front (a=0). Studies on a discrete atomistic model in the same universality class reconfirm the analytical results in the large time limit, while a different scaling behavior shows up for tmemory characteristic of the atomistic model. Results can be generalized for other nonconservative systems.

The influence of memory in a threshold model for distributed task assignment

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive. We propose a threshold based algorithm in order to maximise the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability.

Knowledge transfer in globally distributed teams:the role of transactive memory

This paper explores the role of transactive memory in enabling knowledge transfer between globally distributed teams. While the information systems literature has recently acknowledged the role transactive memory plays in improving knowledge processes and performance in colocated teams, little is known about its contribution to distributed teams. To contribute to filling this gap, knowledge-transfer challenges and processes between onsite and offshore teams were studied at TATA Consultancy Services. In particular, the paper describes the transfer of knowledge between onsite and offshore teams through encoding, storing and retrieving processes. An in-depth case study of globally distributed software development projects was carried out, and a qualitative, interpretive approach was adopted. The analysis of the case suggests that in order to overcome differences derived from the local contexts of the onsite and offshore teams (e.g. different work routines, methodologies and skills), some specific mechanisms supporting the development of codified and personalized ‘directories’ were introduced. These include the standardization of templates and methodologies across the remote sites as well as frequent teleconferencing sessions and occasional short visits. These mechanisms contributed to the development of the notion of ‘who knows what’ across onsite and offshore teams despite the challenges associated with globally distributed teams, and supported the transfer of knowledge between onsite and offshore teams. The paper concludes by offering theoretical and practical implications.

Frontopolar cortical inefficiency may underpin reward and working memory dysfunction in bipolar disorder

Objectives. Emotional dysregulation in bipolar disorder is thought to arise from dysfunction within prefrontal cortical regions involved in cognitive control coupled with increased or aberrant activation within regions engaged in emotional processing. The aim of this study was to determine the common and distinct patterns of functional brain abnormalities during reward and working memory processing in patients with bipolar disorder. Methods. Participants were 36 euthymic bipolar disorder patients and 37 healthy comparison subjects matched for age, sex and IQ. Functional magnetic resonance imaging (fMRI) was conducted during the Iowa Gambling Task (IGT) and the n-back working memory task. Results. During both tasks, patients with bipolar disorder demonstrated a pattern of inefficient engagement within the ventral frontopolar prefrontal cortex with evidence of segregation along the medial-lateral dimension for reward and working memory processing, respectively. Moreover, patients also showed greater activation in the anterior cingulate cortex during the Iowa Gambling Task and in the insula during the n-back task. Conclusions. Our data implicate ventral frontopolar dysfunction as a core abnormality underpinning bipolar disorder and confirm that overactivation in regions involved in emotional arousal is present even in tasks that do not typically engage emotional systems. © 2012 Informa Healthcare.

Cognitive systems associated with the hippocampus of the human brain and their role in behaviour and neurodegenerative disease

Cognitive systems research involves the synthesis of ideas from natural and artificial systems in the analysis, understanding, and design of all intelligent systems. This chapter discusses the cognitive systems associated with the hippocampus (HC) of the human brain and their possible role in behaviour and neurodegenerative disease. The hippocampus (HC) is concerned with the analysis of highly abstract data derived from all sensory systems but its specific role remains controversial. Hence, there have been three major theories concerning its function, viz., the memory theory, the spatial theory, and the behavioral inhibition theory. The memory theory has its origin in the surgical destruction of the HC, which results in severe anterograde and partial retrograde amnesia. The spatial theory has its origin in the observation that neurons in the HC of animals show activity related to their location within the environment. By contrast, the behavioral inhibition theory suggests that the HC acts as a ‘comparator’, i.e., it compares current sensory events with expected or predicted events. If a set of expectations continues to be verified then no alteration of behavior occurs. If, however, a ‘mismatch’ is detected then the HC intervenes by initiating appropriate action by active inhibition of current motor programs and initiation of new data gathering. Understanding the cognitive systems of the hippocampus in humans may aid in the design of intelligent systems involved in spatial mapping, memory, and decision making. In addition, this information may lead to a greater understanding of the course of clinical dementia in the various neurodegenerative diseases in which there is significant damage to the HC.