Setting boundaries: brain dynamics of modal and amodal illusory shape completion in humans.

Normal visual perception requires differentiating foreground from background objects. Differences in physical attributes sometimes determine this relationship. Often such differences must instead be inferred, as when two objects or their parts have the same luminance. Modal completion refers to such perceptual "filling-in" of object borders that are accompanied by concurrent brightness enhancement, in turn termed illusory contours (ICs). Amodal completion is filling-in without concurrent brightness enhancement. Presently there are controversies regarding whether both completion processes use a common neural mechanism and whether perceptual filling-in is a bottom-up, feedforward process initiating at the lowest levels of the cortical visual pathway or commences at higher-tier regions. We previously examined modal completion (Murray et al., 2002) and provided evidence that the earliest modal IC sensitivity occurs within higher-tier object recognition areas of the lateral occipital complex (LOC). We further proposed that previous observations of IC sensitivity in lower-tier regions likely reflect feedback modulation from the LOC. The present study tested these proposals, examining the commonality between modal and amodal completion mechanisms with high-density electrical mapping, spatiotemporal topographic analyses, and the local autoregressive average distributed linear inverse source estimation. A common initial mechanism for both types of completion processes (140 msec) that manifested as a modulation in response strength within higher-tier visual areas, including the LOC and parietal structures, is demonstrated, whereas differential mechanisms were evident only at a subsequent time period (240 msec), with amodal completion relying on continued strong responses in these structures.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Three essays on liquidity risk

Preface In this thesis we study several questions related to transaction data measured at an individual level. The questions are addressed in three essays that will constitute this thesis. In the first essay we use tick-by-tick data to estimate non-parametrically the jump process of 37 big stocks traded on the Paris Stock Exchange, and of the CAC 40 index. We separate the total daily returns in three components (trading continuous, trading jump, and overnight), and we characterize each one of them. We estimate at the individual and index levels the contribution of each return component to the total daily variability. For the index, the contribution of jumps is smaller and it is compensated by the larger contribution of overnight returns. We test formally that individual stocks jump more frequently than the index, and that they do not respond independently to the arrive of news. Finally, we find that daily jumps are larger when their arrival rates are larger. At the contemporaneous level there is a strong negative correlation between the jump frequency and the trading activity measures. The second essay study the general properties of the trade- and volume-duration processes for two stocks traded on the Paris Stock Exchange. These two stocks correspond to a very illiquid stock and to a relatively liquid stock. We estimate a class of autoregressive gamma process with conditional distribution from the family of non-central gamma (up to a scale factor). This process was introduced by Gouriéroux and Jasiak and it is known as Autoregressive gamma process. We also evaluate the ability of the process to fit the data. For this purpose we use the Diebold, Gunther and Tay (1998) test; and the capacity of the model to reproduce the moments of the observed data, and the empirical serial correlation and the partial serial correlation functions. We establish that the model describes correctly the trade duration process of illiquid stocks, but have problems to adjust correctly the trade duration process of liquid stocks which present long-memory characteristics. When the model is adjusted to volume duration, it successfully fit the data. In the third essay we study the economic relevance of optimal liquidation strategies by calibrating a recent and realistic microstructure model with data from the Paris Stock Exchange. We distinguish the case of parameters which are constant through the day from time-varying ones. An optimization problem incorporating this realistic microstructure model is presented and solved. Our model endogenizes the number of trades required before the position is liquidated. A comparative static exercise demonstrates the realism of our model. We find that a sell decision taken in the morning will be liquidated by the early afternoon. If price impacts increase over the day, the liquidation will take place more rapidly.

Synchronous and baroceptor-sensitive oscillations in skin microcirculation: evidence for central autonomic control.

To determine whether skin blood flow is local or takes part in general regulatory mechanisms, we recorded laser-Doppler flowmetry (LDF; left and right index fingers), blood pressure, muscle sympathetic nerve activity (MSNA), R-R interval, and respiration in 10 healthy volunteers and 3 subjects after sympathectomy. We evaluated 1) the synchronism of LDF fluctuations in two index fingers, 2) the relationship with autonomically mediated fluctuations in other signals, and 3) the LDF ability to respond to arterial baroreflex stimulation (by neck suction at frequencies from 0.02 to 0.20 Hz), using spectral analysis (autoregressive uni- and bivariate, time-variant algorithms). Synchronous LDF fluctuations were observed in the index fingers of healthy subjects but not in sympathectomized patients. LDF fluctuations were coherent with those obtained for blood pressure, MSNA, and R-R interval. LDF fluctuations were leading blood pressure in the low-frequency (LF; 0.1 Hz) band and lagging in the respiratory, high-frequency (HF; approximately 0.25 Hz) band, suggesting passive "downstream" transmission only for HF and "upstream" transmission for LF from the microvessels. LDF fluctuations were responsive to sinusoidal neck suction up to 0.1 Hz, indicating response to sympathetic modulation. Skin blood flow thus reflects modifications determined by autonomic activity, detectable by frequency analysis of spontaneous fluctuations.

Regression analysis of spatial data.

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Antagonism of neuromuscular blockade but not muscle relaxation affects depth of anaesthesia

RÉSUMÉ Introduction L'effet des agents myorelaxants ainsi que des anticholinestérases sur la profondeur d'anesthésie a été étudié avec des résultats contradictoires. C'est pourquoi nous avons évalué l'effet de l'atracurium et de la néostigmine sur le BIS (bispectral index) ainsi que sur les potentiels auditives évoqués (middle-latency auditory evoked potentials, A-Line® autoregressive index [AAI]). Méthodes Après avoir obtenu l'accord du comité d'éthique local, nous avons étudié 40 patients ayant donné leur consentement écrit, ASA I-II, âgé de 18-69 ans. L'anesthésie générale a consisté en anesthésie intra-veineuse à objectif de concentration avec du propofol et du remifentanil. La fonction de la jonction neuromusculaire était monitorée en continu au moyen d'un électromyographe. Le BIS et l'AAI ont été enregistrés en continu. Après avoir atteint des valeurs stables au niveau du BIS, les patients ont été attribués à deux groupes par randomisation. Les patients du groupe 1 ont reçu 0.4 mg kg-1 d'atracurium et 5 minutes plus tard le même volume de NaCI 0.9%, dans le groupe 2 la séquence d'injection était inversée, le NaCI 0.9% en premier et l'atracurium en deuxième. Au moment où le premier « twitch » d'un train de quatre atteignait 10% de l'intensité avant la relaxation, les patients ont été randomisés une deuxième fois. Les patients du groupe N ont reçu 0.04 mg kg-1 de néostigmine et 0.01 rn9 kg-1 de glycopyrrolate alors que le groupe contrôle (G) ne recevait que 0.01 mg kg-] de glycopyrrolate. Résultats : L 'injection d'atracurium ou de NaCI 0.9% n'a pas eu d'effet sur le BIS ou l'AAI. Après l'injection de néostigmine avec glycopyrrolate, le BIS et I `AAI a augmenté de manière significative (changement maximal moyen du BIS 7.1 ± 7.5, P< 0.001, de l'AAI 9.7 ± 10.5, P< 0.001). Suite à l'injection de glycopyrrolate seule, le BIS et l'AAI a augmenté également (changement maximal moyen du BIS 2.2 ± 3.4, P< 0.008, de l'AAI 3.5 ± 5.7, P< 0.012), mais cette augmentation était significativement moins importante que dans le groupe N (P< 0.012 pour le BIS, P< 0.027 pour l'AAI). Conclusion Ces résultats laissent supposer que la néostigmine peut altérer la profondeur de l'anesthésie. La diminution de la profondeur d'anesthésie enregistrée par le BIS et l'AAI correspond probablement à une réapparition brusque d'une stimulation centrale liée à la proprioception. Au contraire, lors de la curarisation, le tonus musculaire diminue de manière beaucoup plus progressive, pouvant ainsi expliquer l'absence d'effet sur la profondeur d'anesthésie. ABSTRACT Background. Conflicting effects of neuromuscular blocking drugs and anticholinesterases on depth of anaesthesia have been reported. Therefore we evaluated the effect of atracurium and neostigmine on bispectral index (BIS) and middle-latency auditory evoked potentials (AAI). Methods. We studied 40 patients (ASA I-II) aged 18-69 yr. General anaesthesia consisted of propofol and remifentanil by target-controlled infusion and neuromuscular function was monitored by electromyography. When BIS reached stable values, patients were randomly assigned to one of two groups. Group I received atracurium 0.4 mg kg-1 and, 5 min later, the same volume of NaCl 0.9%; group 2 received saline first and then atracurium. When the first twitch of a train of four reached 10% of control intensity, patients were again randomized: one group (N) received neostigmine 0.04 mg kg-1 and glycopyrrolate 0.01 mg kg-1, and the control group (G) received only glycopyrrolate. Results. Injection of atracurium or NaCl 0.9% had no effect on BIS or AAI. After neostigmine¬glycopyrrolate, BIS and AAI increased significantly (mean maximal change of BIS 7.1 [SD 7.5], P<0.001; mean maximal change of AAI 9.7 [10.5], P<0.001). When glycopyrrolate was injected alone BIS and AAI also increased (mean maximal change of BIS 2.2 [3.4], P=0.008; mean maximal change of AAI 3.5 [5.7], P=0.012), but this increase was significantly less than in group N (P=0.012 for BIS; P=0.027 for AAI). Conclusion. These data suggest that neostigmine alters the state of propofol-remifentanil anaesthesia and may enhance recovery.

Un regard bayesien sur les modèles dynamiques de la macroéconomie

http://alize.finances.gouv.fr/prevision/revue/resumes/ep183184/pdf/rsf183184a6.pdf

Weakened functional connectivity in patients with psychogenic non-epileptic seizures (PNES) converges on basal ganglia.

BACKGROUND: Psychogenic non-epileptic seizures (PNES) are involuntary paroxysmal events that are unaccompanied by epileptiform EEG discharges. We hypothesised that PNES are a disorder of distributed brain networks resulting from their functional disconnection.The disconnection may underlie a dissociation mechanism that weakens the influence of unconsciously presented traumatising information but exerts maladaptive effects leading to episodic failures of behavioural control manifested by psychogenic 'seizures'. METHODS: To test this hypothesis, we compared functional connectivity (FC) derived from resting state high-density EEGs of 18 patients with PNES and 18 age-matched and gender-matched controls. To this end, the EEGs were transformed into source space using the local autoregressive average inverse solution. FC was estimated with a multivariate measure of lagged synchronisation in the θ, α and β frequency bands for 66 brain sites clustered into 18 regions. A multiple comparison permutation test was applied to deduce significant between-group differences in inter-regional and intraregional FC. RESULTS: The significant effect of PNES-a decrease in lagged FC between the basal ganglia and limbic, prefrontal, temporal, parietal and occipital regions-was found in the α band. CONCLUSION: We believe that this finding reveals a possible neurobiological substrate of PNES, which explains both attenuation of the effect of potentially disturbing mental representations and the occurrence of PNES episodes. By improving understanding of the aetiology of this condition, our results suggest a potential refinement of diagnostic criteria and management principles.