Amygdala-dependent learning increases the number of spinophilin-immunoreactive dendritic spines in the lateral amygdala

During Pavlovian auditory fear conditioning a previously neutral auditory stimulus (CS) gains emotional significance through pairing with a noxious unconditioned stimulus (US). These associations are believed to be formed by way of plasticity at auditory input synapses on principal neurons in the lateral nucleus of the amygdala (LA). One proposed form of cellular plasticity involves structural changes in the number and morphology of dendritic spines...

Differences in intrinsic properties of dorsally and ventrally located lateral amygdala neurons of the rat

During Pavlovian auditory fear conditioning a previously neutral auditory stimulus (CS) gains emotional significance through pairing with a noxious unconditioned stimulus (US). These associations are believed to be formed by way of plasticity at auditory input synapses on principal neurons of the lateral nucleus of the amygdala (LA). While the LA has been implicated as a key brain structure for fear learning, how its network of cellular components performs these operations is not yet known...

GABAa receptors contribute to synaptic integration in lateral amygdala neurons

In classical fear conditioning a neutral conditioned stimulus (CS) such as a tone, is paired with an aversive unconditioned stimulus (US) such as a shock. The CS thereby acquires the capacity to elicit a fear response. This type of associative learning is thought to require co-activation of principle neurons in the lateral nucleus of the amygdala (LA) by two sets of synaptic inputs, a weak CS and a strong US...

Acute restraint stress alters subsequent auditory fear conditioning in the rat

The neural basis of Pavlovian fear conditioning is well understood and depends upon neural processes within the amygdala. Stress is known to play a role in the modulation of fear-related behavior, including Pavlovian fear conditioning. Chronic restraint stress has been shown to enhance fear conditioning to discrete and contextual stimuli; however, the time course and extent of restraint that is essential for this modulation of fear learning remains unclear. Thus, we tested the extent to which a single exposure to 1 hr of restraint would alter subsequent auditory fear conditioning in rats.

Jacobi-Schlossberg family papers, undated, 1870-2000.

The collection documents the lives Sarah Simon Jacobi (1857-1943), Freda Moritz Jacobi (1886-1939), Alice Jacobi Schlossberg (1912-1987) and Deda Schlossberg Miller (1940- ), through diaries, baby books, photographs, and correspondence. Also included in the collection are a silver card case, a silver coffee pot and creamer, and an etching of the Jacobi family home. For further information on these objects see the museum curator.

A method of fraud & intrusion detection for e-payment systems in mobile

The need for paying with mobile devices has urged the development of payment systems for mobile electronic commerce. In this paper we have considered two important abuses in electronic payments systems for detection. The fraud, which is an intentional deception accomplished to secure an unfair gain, and an intrusion which are any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. Most of the available fraud and intrusion detection systems for e-payments are specific to the systems where they have been incorporated. This paper proposes a generic model called as Activity-Event-Symptoms(AES) model for detecting fraud and intrusion attacks which appears during payment process in the mobile commerce environment. The AES model is designed to identify the symptoms of fraud and intrusions by observing various events/transactions occurs during mobile commerce activity. The symptoms identification is followed by computing the suspicion factors for event attributes, and the certainty factor for a fraud and intrusion is generated using these suspicion factors. We have tested the proposed system by conducting various case studies, on the in-house established mobile commerce environment over wired and wire-less networks test bed.

Link route pricing for enhanced QoS

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under multiple service classes. Our work draws upon [1] and [2] in various ways. We use the Tirupati pricing scheme in conjunction with the stochastic approximation based adaptive pricing methodology for queue control (proposed in [1]) for minimizing network congestion. However, unlike the methodology of [1] where pricing for entire routes is directly considered, we consider prices for individual link-service grade tuples. Further, we adapt the methodology proposed in [21 for a single-node scenario to the case of a network of nodes, for evaluating performance in terms of price, revenue rate and disutility. We obtain considerable performance improvements using our approach over that in [1]. In particular, our approach exhibits a throughput improvement in the range of 54 to 80 percent in all cases studied (over all routes) while exhibiting a lower packet delay in the range of 26 to 38 percent over the scheme in [1].

Discrete parameter simulation optimization algorithms with applications to admission control with dependent service times

We propose certain discrete parameter variants of well known simulation optimization algorithms. Two of these algorithms are based on the smoothed functional (SF) technique while two others are based on the simultaneous perturbation stochastic approximation (SPSA) method. They differ from each other in the way perturbations are obtained and also the manner in which projections and parameter updates are performed. All our algorithms use two simulations and two-timescale stochastic approximation. As an application setting, we consider the important problem of admission control of packets in communication networks under dependent service times. We consider a discrete time slotted queueing model of the system and consider two different scenarios - one where the service times have a dependence on the system state and the other where they depend on the number of arrivals in a time slot. Under our settings, the simulated objective function appears ill-behaved with multiple local minima and a unique global minimum characterized by a sharp dip in the objective function in a small region of the parameter space. We compare the performance of our algorithms on these settings and observe that the two SF algorithms show the best results overall. In fact, in many cases studied, SF algorithms converge to the global minimum.

Network flow-control using asynchronous stochastic approximation

We propose several stochastic approximation implementations for related algorithms in flow-control of communication networks. First, a discrete-time implementation of Kelly's primal flow-control algorithm is proposed. Convergence with probability 1 is shown, even in the presence of communication delays and stochastic effects seen in link congestion indications. This ensues from an analysis of the flow-control algorithm using the asynchronous stochastic approximation (ASA) framework. Two relevant enhancements are then pursued: a) an implementation of the primal algorithm using second-order information, and b) an implementation where edge-routers rectify misbehaving flows. Next, discretetime implementations of Kelly's dual algorithm and primaldual algorithm are proposed. Simulation results a) verifying the proposed algorithms and, b) comparing the stability properties are presented.

SC-FDMA versus OFDMA: Sensitivity to Large Carrier Frequency and Timing Offsets on the Uplink

In this paper, we present a comparison between the sensitivity of SC-FDMA and OFDMA schemes to large carrier frequency offsets (CFO) and timing offsets (TO) of different users on the uplink. Our study shows the following observations: 1) In the ideal case of zero CFOs and TOs (i.e., perfect synchronization), the uncoded BER performance of SC-FDMA with frequency domain MMSE equalizer is better than that of OFDMA due to the inherent frequency diversity that is possible in SCFDMA. Also, because of inter-symbol interference in SC-FDMA, the performance of SC-FDMA with MMSE equalizer can be further improved by using low-complexity interference cancellation (IC) techniques. 2) In the presence of large CFOs and TOs, significant multiuser interference (MUI) gets introduced, and hence the performance of SC-FDMA with MMSE equalizer can get worse than that of OFDMA. However, the performance advantage of SC-FDMA with MMSE equalizer over OFDMA (due to the potential for frequency diversity benefit in SC-FDMA) can be restored by adopting multistage IC techniques, using the knowledge of CFOs and TOs of different users at the receiver

A Low-Complexity, Full-Rate, Full-Diversity 2 x 2 STBC with Golden Code's Coding Gain

This paper presents a low-ML-decoding-complexity, full-rate, full-diversity space-time block code (STBC) for a 2 transmit antenna, 2 receive antenna multiple-input multiple-output (MIMO) system, with coding gain equal to that of the best and well known Golden code for any QAM constellation. Recently, two codes have been proposed (by Paredes, Gershman and Alkhansari and by Sezginer and Sari), which enjoy a lower decoding complexity relative to the Golden code, but have lesser coding gain. The 2 x 2 STBC presented in this paper has lesser decoding complexity for non-square QAM constellations, compared with that of the Golden code, while having the same decoding complexity for square QAM constellations. Compared with the Paredes-Gershman-Alkhansari and Sezginer-Sari codes, the proposed code has the same decoding complexity for non-rectangular QAM constellations. Simulation results, which compare the codeword error rate (CER) performance, are presented.

Robust Semi-Blind Estimation for Beamforming Based MIMO Wireless Communication

In this paper, we present robust semi-blind (SB) algorithms for the estimation of beamforming vectors for multiple-input multiple-output wireless communication. The transmitted symbol block is assumed to comprise of a known sequence of training (pilot) symbols followed by information bearing blind (unknown) data symbols. Analytical expressions are derived for the robust SB estimators of the MIMO receive and transmit beamforming vectors. These robust SB estimators employ a preliminary estimate obtained from the pilot symbol sequence and leverage the second-order statistical information from the blind data symbols. We employ the theory of Lagrangian duality to derive the robust estimate of the receive beamforming vector by maximizing an inner product, while constraining the channel estimate to lie in a confidence sphere centered at the initial pilot estimate. Two different schemes are then proposed for computing the robust estimate of the MIMO transmit beamforming vector. Simulation results presented in the end illustrate the superior performance of the robust SB estimators.

Robust Transceiver Design for Multiuser MIMO Downlink

In this paper, we consider robust joint linear precoder/receive filter design for multiuser multi-input multi-output (MIMO) downlink that minimizes the sum mean square error (SMSE) in the presence of imperfect channel state information (CSI). The base station is equipped with multiple transmit antennas, and each user terminal is equipped with multiple receive antennas. The CSI is assumed to be perturbed by estimation error. The proposed transceiver design is based on jointly minimizing a modified function of the MSE, taking into account the statistics of the estimation error under a total transmit power constraint. An alternating optimization algorithm, wherein the optimization is performed with respect to the transmit precoder and the receive filter in an alternating fashion, is proposed. The robustness of the proposed algorithm to imperfections in CSI is illustrated through simulations.

Convergence of Power Control in a Random Channel Environment

In this paper, we study the Foschini Miljanic algorithm, which was originally proposed in a static channel environment. We investigate the algorithm in a random channel environment, study its convergence properties and apply the Gerschgorin theorem to derive sufficient conditions for the convergence of the algorithm. We apply the Foschini and Miljanic algorithm to cellular networks and derive sufficient conditions for the convergence of the algorithm in distribution and validate the results with simulations. In cellular networks, the conditions which ensure convergence in distribution can be easily verified.