In humans, multisensory interaction is an important strategy for improving the detection of stimuli of different nature and reducing the variability of response. It is known that the presence of visual information affects the auditory perception in the horizontal plane (azimuth), but there are few researches that study the influence of vision in the auditory distance perception. In general, the data obtained from these studies are contradictory and do not completely define the way in which visual cues affect the apparent distance of a sound source. Here psychophysical experiments on auditory distance perception in humans are performed, including and excluding visual cues. The results show that the apparent distance from the source is affected by the presence of visual information and that subjects can store in their memory a representation of the environment that later improves the perception of distance.

We generate an observable which relates the interspike time statistics in a noise driven excitable system with its phase space global properties. Experimental results from a semiconductor laser with optical feedback are analyzed within this framework. PACS numbers: 42.65.Sf, 05.40.Ca, 42.55.Px Escape problems from metastable states are ubiquitous in nature [1]. From biology to physics, several situations are adequately modeled through noise driven equations for which the dynamical output consists of a sequence of spike responses with a more or less complex interspike time distribution [2,3]. In these cases, efforts usually are devoted to the calculation of rate coefficients. Kramers made the seminal contribution to this program. He computed escape rates from both the local properties of the deterministic part of the model in the neighborhood of the metastable state and the noise level [4]. In Ref.[5], pseudoregular oscillations were found in noise driven excitable systems for a specific case: the infinitely dissipative regime. In this work, we analyze the consequences of the global properties of a general excitable system (presenting finite dissipation) in the interspike time distribution of its response to added noise. We find that the interspike distributions present a nontrivial structure. The global properties we refer to are the stable and unstable manifolds of the fixed points of the deterministic part of the model. In particular, we analyze the results of an experiment (a semiconductor laser with optical feedback close to the onset of a regime called low frequency fluctuations) [6][7][8], in terms of a simple model [9].The experimental setup is shown in Fig. 1(a). The diode laser used in our experiment is the single transverse-mode Sharp LT030MD0 (nominal wavelength l 750 nm; solitary laser threshold I th 36.66 mA). The temperature of the laser is stabilized to better than 0.01 ± C. The beam is collimated and directed toward a high reflection mirror (R 99%) located at 50 cm from the laser, which redirects the beam back to it. An antireflection coated lens ( f 25 cm) is placed within the cavity in order to focus the beam into the mirror, which seems to improve the coupling efficiency. The optical feedback strength is controlled by an acusto-optic modulator (AOM) placed inside the cavity, in such a way that a variable amount of light can be removed from the zero order thus reducing the feedback level. The intensity output is detected by a 1 GHz bandwidth photodiode and the signal is analyzed with a HP 54616B 500 MHz digital oscilloscope. In this work, we are interested in the slow dynamics, i.e., time scales much larger than the external cavity round-trip time (t ഠ 3 ns). Actually, the short-time dynamics are washed out by the use of a 30 MHz low-pass filter. Different dynamical scenarios are observed as the parameters (current, feedback) are varied, which are extensively described in the literature (see [6], and references therein).For pump values considerably smaller than the solitary laser threshold t...

Temporal perception is fundamental to environmental adaptation in humans and other animals. To deal with timing and time perception, organisms have developed multiple systems that are active over a broad range of order of magnitude, the most important being circadian timing, interval timing and millisecond timing. The circadian pacemaker is located in the suprachiasmatic nuclei (SCN) of the hypothalamus, and is driven by a selfsustaining oscillator with a period close to 24 h. Time estimation in the second-to-minutes range -known as interval timing -involves the interaction of the basal ganglia and the prefrontal cortex. In this work we tested the hypothesis that interval timing in mice is sensitive to circadian modulations. Animals were trained following the peak-interval (PI) procedure. Results show significant differences in the estimation of 24-second intervals at different times of day, with a higher accuracy in the group trained at night, which were maintained under constant dark (DD) conditions. Interval timing was also studied in animals under constant light (LL) conditions, which abolish circadian rhythmicity. Mice under LL conditions were unable to acquire temporal control in the peak interval procedure.Moreover, short time estimation in animals subjected to circadian desynchronizations (modeling jet lag-like situations) was also affected. Taken together, our results indicate that short-time estimation is modulated by the circadian clock.© 2010 Elsevier B.V. All rights reserved. Keywords:Circadian rhythms Interval timingBasal ganglia Suprachiasmatic nuclei IntroductionTiming and time perception are fundamental to survival and goal reaching in humans and other animals. Organisms have developed diverse mechanisms for timing across different scales, the most important being circadian timing, interval timing and millisecond timing . The circadian pacemaker -which is driven by a self-sustaining oscillator with a period close to 24 h -is located in the suprachiasmatic nuclei (SCN) of the hypothalamus (Dunlap et al., 2004), and the principal signal that adjusts its activity is the light-dark cycle (Morin and Allen, 2006;Golombek and Rosenstein, 2010). The molecular mechanism of the endogenous circadian clock is comprised by interlocked transcription-translation feedback loops (Reppert and Weaver, 2002). On the other hand, the perception of shorter durations in the seconds-to-minutes range, known as interval timing, is crucial to learning, memory, decision making and other cognitive

Biological neural communications channels transport environmental information from sensors through chains of active dynamical neurons to neural centers for decisions and actions to achieve required functions. These kinds of communications channels are able to create information and to transfer information from one time scale to the other because of the intrinsic nonlinear dynamics of the component neurons. We discuss a very simple neural information channel composed of sensory input in the form of a spike train that arrives at a model neuron, then moves through a realistic synapse to a second neuron where the information in the initial sensory signal is read. Our model neurons are four-dimensional generalizations of the Hindmarsh-Rose neuron, and we use a model of chemical synapse derived from first-order kinetics. The four-dimensional model neuron has a rich variety of dynamical behaviors, including periodic bursting, chaotic bursting, continuous spiking, and multistability. We show that, for many of these regimes, the parameters of the chemical synapse can be tuned so that information about the stimulus that is unreadable at the first neuron in the channel can be recovered by the dynamical activity of the synapse and the second neuron. Information creation by nonlinear dynamical systems that allow chaotic oscillations is familiar in their autonomous oscillations. It is associated with the instabilities that lead to positive Lyapunov exponents in their dynamical behavior. Our results indicate how nonlinear neurons acting as input/output systems along a communications channel can recover information apparently ''lost'' in earlier junctions on the channel. Our measure of information transmission is the average mutual information between elements, and because the channel is active and nonlinear, the average mutual information between the sensory source and the final neuron may be greater than the average mutual information at an earlier neuron in the channel. This behavior is strikingly different than the passive role communications channels usually play, and the ''data processing theorem'' of conventional communications theory is violated by these neural channels. Our calculations indicate that neurons can reinforce reliable transmission along a chain even when the synapses and the neurons are not completely reliable components. This phenomenon is generic in parameter space, robust in the presence of noise, and independent of the discretization process. Our results suggest a framework in which one might understand the apparent design complexity of neural information transduction networks. If networks with many dynamical neurons can recover information not apparent at various waystations in the communications channel, such networks may be more robust to noisy signals, may be more capable of communicating many types of encoded sensory neural information, and may be the appropriate design for components, neurons and synapses, which can be individually imprecise, inaccurate ''devices.''