Swift-Hohenberg equation for lasers

Pattern formation in large aspect ratio, single longitudinal mode, two-level lasers with flat end reflectors, operating near peak gain, is shown to be described by a complex Swift-Hohenberg equation for class A and C lasers and by a complex Swift-Hohenberg equation coupled to a mean flow for the case of a class B laser

Neuronal Activity in the Human Subthalamic Nucleus Encodes Decision Conflict during Action Selection

The subthalamic nucleus (STN), which receives excitatory inputs from the cortex and has direct connections with the inhibitory pathways\ud of the basal ganglia, is well positioned to efficiently mediate action selection. Here, we use microelectrode recordings captured during\ud deep brain stimulation surgery as participants engage in a decision task to examine the role of the human STN in action selection. We\ud demonstrate that spiking activity in the STN increases when participants engage in a decision and that the level of spiking activity\ud increases with the degree of decision conflict. These data implicate the STN as an important mediator of action selection during decision\ud processes.\u

Control of Integrable Hamiltonian Systems and Degenerate Bifurcations

We discuss control of low-dimensional systems which, when uncontrolled, are integrable in the Hamiltonian sense. The controller targets an exact solution of the system in a region where the uncontrolled dynamics has invariant tori. Both dissipative and conservative controllers are considered. We show that the shear flow structure of the undriven system causes a Takens-Bogdanov birfurcation to occur when control is applied. This implies extreme noise sensitivity. We then consider an example of these results using the driven nonlinear Schrodinger equation.Comment: 25 pages, 11 figures, resubmitted to Physical Review E March 2004 (originally submitted June 2003), added content and reference

Early detection of cyanobacterial blooms and associated cyanotoxins using fast detection strategy

Fast detection of cyanobacteria and cyanotoxins is achieved using a Fast Detection Strategy (FDS). Only 24 h are needed to unravel the presence of cyanobacteria and related cyanotoxins in water samples and in an organic matrix, such as bivalve extracts. FDS combines remote/proximal sensing techniques with analytical/ bioinformatics analyses. Sampling spots are chosen through multi-disciplinary, multi-scale, and multi-parametric monitoring in a three-dimensional physical space, including remote sensing. Microscopic observation and taxonomic analysis of the samples are performed in the laboratory setting, which allows for the identification of cyanobacterial species. Samples are then extracted with organic solvents and processed with LC-MS/MS. Data obtained by MS/MS are analyzed using a bioinformatic approach using the online platform Global Natural Products Social (GNPS) to create a network of molecules. These networks are analyzed to detect and identify toxins, comparing data of the fragmentation spectra obtained by mass spectrometry with the GNPS library. This allows for the detection of known toxins and unknown analogues that appear related in the same molecular network

External Fluctuations in a Pattern-Forming Instability

The effect of external fluctuations on the formation of spatial patterns is analysed by means of a stochastic Swift-Hohenberg model with multiplicative space-correlated noise. Numerical simulations in two dimensions show a shift of the bifurcation point controlled by the intensity of the multiplicative noise. This shift takes place in the ordering direction (i.e. produces patterns), but its magnitude decreases with that of the noise correlation length. Analytical arguments are presented to explain these facts.Comment: 11 pages, Revtex, 10 Postscript figures added with psfig style (included). To appear in Physical Review

Can music be figurative? Exploring the possibility of crossmodal similarities between music and visual arts

According to both experimental research and common sense, classical music is a better fit for figurative art than jazz. We hypothesize that similar fits may reflect underlying crossmodal structural similarities between music and painting genres. We present two preliminary studies aimed at addressing our hypothesis. Experiment 1 tested the goodness of the fit between two music genres (classical and jazz) and two painting genres (figurative and abstract). Participants were presented with twenty sets of six paintings (three figurative, three abstract) viewed in combination with three sound conditions: 1) silence, 2) classical music, or 3) jazz. While figurative paintings scored higher aesthetic appreciation than abstract ones, a gender effect was also found: the aesthetic appreciation of paintings in male participants was modulated by music genre, whilst music genre did not affect the aesthetic appreciation in female participants. Our results support only in part the notion that classical music enhances the aesthetic appreciation of figurative art. Experiment 2 aimed at testing whether the conceptual categories ‘figurative’ and ‘abstract’ can be extended also to music. In session 1, participants were first asked to classify 30 paintings (10 abstract, 10 figurative, 10 ambiguous that could fit either category) as abstract or figurative and the to rate them for pleasantness; in session 2 participants were asked to classify 40 excerpts of music (20 classical, 20 jazz) as abstract or figurative and to rate them for pleasantness. Paintings which were clearly abstract or figurative were all classified accordingly, while the majority of ambiguous paintings were classified as abstract. Results also show a gender effect for painting’s pleasantness: female participants rated higher ambiguous and abstract paintings. More interestingly, results show an effect of music genre on classification, showing that it is possible to classify music as figurative or abstract, thus supporting the hypothesis of cross-modal similarities between the two sensory-different artistic expressions

Effects of conventional and high-definition transcranial direct current stimulation (tDCS) on driving abilities: A tDCS-driving simulator study

Due to the multitasking nature of driving, drivers are physiologically distracted by both relevant and irrelevant environmental stimuli. The ability to select relevant stimuli and suppress irrelevant distractors during driving are two relevant factors for safety. There is a lot of evidence suggesting that the frontal eye field (FEF) plays an important role in target selection and distractors suppression, as well as in attentional mechanisms crucial for safety driving performance. Taking these two points into account, this study was designed to examine the effects of different transcranial direct current stimulation (tDCS) montages over right FEF to determine whether stimulation of FEF could improve attentional mechanisms in a simulated driving environment. Twenty-seven adult participants took part in the study. A specific driving simulator task was developed in which participants had to respond to brake light events of a preceding car in front of them while driving. The second distracting task consisted of road signs of countries and cities that appeared together with braking lights or alone. Participants were required to respond to one of the two categories with their right hand. These two tasks could be performed alone or in a combined condition. Each participant completed three sessions comparing the effects of different tDCS montages, i.e. conventional, focal 4*1 ring high-definition (HD-tDCS) and sham stimulations over the right FEF. Results indicated an overall better performance under the focal HD-tDCS condition. In particular, participants improved their performance both in braking light RTs and in the second distracting task. Taken together these results are interesting from a theoretical and methodological point of view, by demonstrating a direct effect of anodal focal HD-tDCS on FEF in attentional response during an ecological driving task

On the connection between the Nekhoroshev theorem and Arnold Diffusion

The analytical techniques of the Nekhoroshev theorem are used to provide estimates on the coefficient of Arnold diffusion along a particular resonance in the Hamiltonian model of Froeschl\'{e} et al. (2000). A resonant normal form is constructed by a computer program and the size of its remainder $||R_{opt}||$ at the optimal order of normalization is calculated as a function of the small parameter $\epsilon$. We find that the diffusion coefficient scales as $D\propto||R_{opt}||^3$, while the size of the optimal remainder scales as $||R_{opt}|| \propto\exp(1/\epsilon^{0.21})$ in the range $10^{-4}\leq\epsilon \leq 10^{-2}$. A comparison is made with the numerical results of Lega et al. (2003) in the same model.Comment: Accepted in Celestial Mechanics and Dynamical Astronom

Hippocampal theta oscillations support successful associative memory formation

Models of memory formation posit that episodic memory formation depends critically on the hippocampus, which binds features of an event to its context. For this reason, the contrast between study items that are later recollected with their associative pair versus those for which no association is made should reveal electrophysiological patterns in the hippocampus selectively involved in associative memory encoding. Extensive data from studies in rodents support a model in which theta oscillations fulfill this role, but results in humans have not been as clear. Here, we used an associative recognition memory procedure to identify hippocampal correlates of successful associative memory encoding and retrieval in patients (10 females and 9 males) undergoing intracranial EEG monitoring. We identified a dissociation between 2–5 Hz and 5–9 Hz theta oscillations, by which power increases in 2–5 Hz oscillations were uniquely linked with successful associative memory in both the anterior and posterior hippocampus. These oscillations exhibited a significant phase reset that also predicted successful associative encoding and distinguished recollected from nonrecollected items at retrieval, as well as contributing to relatively greater reinstatement of encoding-related patterns for recollected versus nonrecollected items. Our results provide direct electrophysiological evidence that 2–5 Hz hippocampal theta oscillations preferentially support the formation of associative memories, although we also observed memory-related effects in the 5–9 Hz frequency range using measures such as phase reset and reinstatement of oscillatory activity