998 resultados para Alpha rhythm


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This article explores the role of radio sound in establishing what I term ‘affective rhythms’ in everyday life. Through exploring the affective qualities of radio sound and its capacity for mood generation in the home, this article explores personal affective states and personal organisation. The term affective rhythm relates both to mood, and to routine. It is the combination of both that allows the possibility of thinking about sound and affect, and how they relate to, and integrate with, routine everyday life. The notion of ‘affective rhythm’ forces us to consider the idea of mood in the light of the routine nature of everyday domestic life.

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Generative music algorithms frequently operate by making musical decisions in a sequence, with each step of the sequence incorporating the local musical context in the decision process. The context is generally a short window of past musical actions. What is not generally included in the context is future actions. For real-time systems this is because the future is unknown. Offline systems also frequently utilise causal algorithms either for reasons of efficiency [1] or to simulate perceptual constraints [2]. However, even real-time agents can incorporate knowledge of their own future actions by utilising some form of planning. We argue that for rhythmic generation the incorporation of a limited form of planning - anticipatory timing - offers a worthwhile trade-off between musical salience and efficiency. We give an example of a real-time generative agent - the Jambot - that utilises anticipatory timing for rhythmic generation. We describe its operation, and compare its output with and without anticipatory timing.

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The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

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Recently discovered intrinsically photosensitive melanopsin retinal ganglion cells contribute to the maintenance of pupil diameter, recovery and post-illumination components of the pupillary light reflex and provide the primary environmental light input to the suprachiasmatic nucleus for photoentrainment of the circadian rhythm. This review summarises recent progress in understanding intrinsically photosensitive ganglion cell histology and physiological properties in the context of their contribution to the pupillary and circadian functions and introduces a clinical framework for using the pupillary light reflex to evaluate inner retinal (intrinsically photosensitive melanopsin ganglion cell) and outer retinal (rod and cone photoreceptor) function in the detection of retinal eye disease.

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Intrinsically photosensitive retinal ganglion cells (ipRGCs) in the eye transmit the environmental light level, projecting to the suprachiasmatic nucleus (SCN) (Berson, Dunn & Takao, 2002; Hattar, Liao, Takao, Berson & Yau, 2002), the location of the circadian biological clock, and the olivary pretectal nucleus (OPN) of the pretectum, the start of the pupil reflex pathway (Hattar, Liao, Takao, Berson & Yau, 2002; Dacey, Liao, Peterson, Robinson, Smith, Pokorny, Yau & Gamlin, 2005). The SCN synchronizes the circadian rhythm, a cycle of biological processes coordinated to the solar day, and drives the sleep/wake cycle by controlling the release of melatonin from the pineal gland (Claustrat, Brun & Chazot, 2005). Encoded photic input from ipRGCs to the OPN also contributes to the pupil light reflex (PLR), the constriction and recovery of the pupil in response to light. IpRGCs control the post-illumination component of the PLR, the partial pupil constriction maintained for > 30 sec after a stimulus offset (Gamlin, McDougal, Pokorny, Smith, Yau & Dacey, 2007; Kankipati, Girkin & Gamlin, 2010; Markwell, Feigl & Zele, 2010). It is unknown if intrinsic ipRGC and cone-mediated inputs to ipRGCs show circadian variation in their photon-counting activity under constant illumination. If ipRGCs demonstrate circadian variation of the pupil response under constant illumination in vivo, when in vitro ipRGC activity does not (Weng, Wong & Berson, 2009), this would support central control of the ipRGC circadian activity. A preliminary experiment was conducted to determine the spectral sensitivity of the ipRGC post-illumination pupil response under the experimental conditions, confirming the successful isolation of the ipRGC response (Gamlin, et al., 2007) for the circadian experiment. In this main experiment, we demonstrate that ipRGC photon-counting activity has a circadian rhythm under constant experimental conditions, while direct rod and cone contributions to the PLR do not. Intrinsic ipRGC contributions to the post-illumination pupil response decreased 2:46 h prior to melatonin onset for our group model, with the peak ipRGC attenuation occurring 1:25 h after melatonin onset. Our results suggest a centrally controlled evening decrease in ipRGC activity, independent of environmental light, which is temporally synchronized (demonstrates a temporal phase-advanced relationship) to the SCN mediated release of melatonin. In the future the ipRGC post-illumination pupil response could be developed as a fast, non-invasive measure of circadian rhythm. This study establishes a basis for future investigation of cortical feedback mechanisms that modulate ipRGC activity.

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Alcohol use disorders (AUDs) impact millions of individuals and there remain few effective treatment strategies. Despite evidence that neuronal nicotinic acetylcholine receptors (nAChRs) have a role in AUDs, it has not been established which subtypes of the nAChR are involved. Recent human genetic association studies have implicated the gene cluster CHRNA3-CHRNA5-CHRNB4 encoding the α3, α5, and β4 subunits of the nAChR in susceptibility to develop nicotine and alcohol dependence; however, their role in ethanol-mediated behaviors is unknown due to the lack of suitable and selective research tools. To determine the role of the α3, and β4 subunits of the nAChR in ethanol self-administration, we developed and characterized high-affinity partial agonists at α3β4 nAChRs, CP-601932, and PF-4575180. Both CP-601932 and PF-4575180 selectively decrease ethanol but not sucrose consumption and operant self-administration following long-term exposure. We show that the functional potencies of CP-601932 and PF-4575180 at α3β4 nAChRs correlate with their unbound rat brain concentrations, suggesting that the effects on ethanol self-administration are mediated via interaction with α3β4 nAChRs. Also varenicline, an approved smoking cessation aid previously shown to decrease ethanol consumption and seeking in rats and mice, reduces ethanol intake at unbound brain concentrations that allow functional interactions with α3β4 nAChRs. Furthermore, the selective α4β2(*) nAChR antagonist, DHβE, did not reduce ethanol intake. Together, these data provide further support for the human genetic association studies, implicating CHRNA3 and CHRNB4 genes in ethanol-mediated behaviors. CP-601932 has been shown to be safe in humans and may represent a potential novel treatment for AUDs.