Proactive and reactive inhibition during overt and covert actions. An electrical neuroimaging study.

Response inhibition is the ability to suppress inadequate but automatically activated, prepotent or ongoing response tendencies. In the framework of motor inhibition, two distinct operating strategies have been described: “proactive” and “reactive” control modes. In the proactive modality, inhibition is recruited in advance by predictive signals, and actively maintained before its enactment. Conversely, in the reactive control mode, inhibition is phasically enacted after the detection of the inhibitory signal. To date, ample evidence points to a core cerebral network for reactive inhibition comprising the right inferior frontal gyrus (rIFG), the presupplementary motor area (pre-SMA) and the basal ganglia (BG). Moreover, fMRI studies showed that cerebral activations during proactive and reactive inhibition largely overlap. These findings suggest that at least part of the neural network for reactive inhibition is recruited in advance, priming cortical regions in preparation for the upcoming inhibition. So far, proactive and reactive inhibitory mechanisms have been investigated during tasks in which the requested response to be stopped or withheld was an “overt” action execution (AE) (i.e., a movement effectively performed). Nevertheless, inhibitory mechanisms are also relevant for motor control during “covert actions” (i.e., potential motor acts not overtly performed), such as motor imagery (MI). MI is the conscious, voluntary mental rehearsal of action representations without any overt movement. Previous studies revealed a substantial overlap of activated motor-related brain networks in premotor, parietal and subcortical regions during overtly executed and imagined movements. Notwithstanding this evidence for a shared set of cerebral regions involved in encoding actions, whether or not those actions are effectively executed, the neural bases of motor inhibition during MI, preventing covert action from being overtly performed, in spite of the activation of the motor system, remain to be fully clarified. Taking into account this background, we performed a high density EEG study evaluating cerebral mechanisms and their related sources elicited during two types of cued Go/NoGo task, requiring the execution or withholding of an overt (Go) or a covert (MI) action, respectively. The EEG analyses were performed in two steps, with different aims: 1) Analysis of the “response phase” of the cued overt and covert Go/NoGo tasks, for the evaluation of reactive inhibitory control of overt and covert actions. 2) Analysis of the “preparatory phase” of the cued overt and covert Go/NoGo EEG datasets, focusing on cerebral activities time-locked to the preparatory signals, for the evaluation of proactive inhibitory mechanisms and their related neural sources. For these purposes, a spatiotemporal analysis of the scalp electric fields was applied on the EEG data recorded during the overt and covert Go/NoGo tasks. The spatiotemporal approach provide an objective definition of time windows for source analysis, relying on the statistical proof that the electric fields are different and thus generated by different neural sources. The analysis of the “response phase” revealed that key nodes of the inhibitory circuit, underpinning inhibition of the overt movement during the NoGo response, were also activated during the MI enactment. In both cases, inhibition relied on the activation of pre-SMA and rIFG, but with different temporal patterns of activation in accord with the intended “covert” or “overt” modality of motor performance. During the NoGo condition, the pre-SMA and rIFG were sequentially activated, pointing to an early decisional role of pre-SMA and to a later role of rIFG in the enactment of inhibitory control of the overt action. Conversely, a concomitant activation of pre-SMA and rIFG emerged during the imagined motor response. This latter finding suggested that an inhibitory mechanism (likely underpinned by the rIFG), could be prewired into a prepared “covert modality” of motor response, as an intrinsic component of the MI enactment. This mechanism would allow the rehearsal of the imagined motor representations, without any overt movement. The analyses of the “preparatory phase”, confirmed in both overt and covert Go/NoGo tasks the priming of cerebral regions pertaining to putative inhibitory network, reactively triggered in the following response phase. Nonetheless, differences in the preparatory strategies between the two tasks emerged, depending on the intended “overt” or “covert” modality of the possible incoming motor response. During the preparation of the overt Go/NoGo task, the cue primed the possible overt response programs in motor and premotor cortex. At the same time, through preactivation of a pre-SMA-related decisional mechanism, it triggered a parallel preparation for the successful response selection and/or inhibition during the subsequent response phase. Conversely, the preparatory strategy for the covert Go/NoGo task was centred on the goal-oriented priming of an inhibitory mechanism related to the rIFG that, being tuned to the instructed covert modality of the motor performance and instantiated during the subsequent MI enactment, allowed the imagined response to remain a potential motor act. Taken together, the results of the present study demonstrate a substantial overlap of cerebral networks activated during proactive recruitment and subsequent reactive enactment of motor inhibition in both overt and covert actions. At the same time, our data show that preparatory cues predisposed ab initio a different organization of the cerebral areas (in particular of the pre-SMA and rIFG) involved with sensorimotor transformations and motor inhibitory control for executed and imagined actions. During the preparatory phases of our cued overt and covert Go/NoGo tasks, the different adopted strategies were tuned to the “how” of the motor performance, reflecting the intended overt and covert modality of the possible incoming action.

Signal Processing Techniques for Chipless UWB RFID Thermal Threshold Detector Detection.

This letter presents signal processing techniques to detect a passive thermal threshold detector based on a chipless time-domain ultrawideband (UWB) radio frequency identification (RFID) tag. The tag is composed by a UWB antenna connected to a transmission line, in turn loaded with a biomorphic thermal switch. The working principle consists of detecting the impedance change of the thermal switch. This change occurs when the temperature exceeds a threshold. A UWB radar is used as the reader. The difference between the actual time sample and a reference signal obtained from the averaging of previous samples is used to determine the switch transition and to mitigate the interferences derived from clutter reflections. A gain compensation function is applied to equalize the attenuation due to propagation loss. An improved method based on the continuous wavelet transform with Morlet wavelet is used to overcome detection problems associated to a low signal-to-noise ratio at the receiver. The average delay profile is used to detect the tag delay. Experimental measurements up to 5 m are obtained.

Re-Examining the Stop-Signal Task to Test Competing Theories of AD/HD

The current study tested two competing models of Attention-Deficit/Hyperactivity Disorder (AD/HD), the inhibition and state regulation theories, by conducting fine-grained analyses of the Stop-Signal Task and another putative measure of behavioral inhibition, the Gordon Continuous Performance Test (G-CPT), in a large sample of children and adolescents. The inhibition theory posits that performance on these tasks reflects increased difficulties for AD/HD participants to inhibit prepotent responses. The model predicts that putative stop-signal reaction time (SSRT) group differences on the Stop-Signal Task will be primarily related to AD/HD participants requiring more warning than control participants to inhibit to the stop-signal and emphasizes the relative importance of commission errors, particularly "impulsive" type commissions, over other error types on the G-CPT. The state regulation theory, on the other hand, proposes response variability due to difficulties maintaining an optimal state of arousal as the primary deficit in AD/HD. This model predicts that SSRT differences will be more attributable to slower and/or more variable reaction time (RT) in the AD/HD group, as opposed to reflecting inhibitory deficits. State regulation assumptions also emphasize the relative importance of omission errors and "slow processing" type commissions over other error types on the G-CPT. Overall, results of Stop-Signal Task analyses were more supportive of state regulation predictions and showed that greater response variability (i.e., SDRT) in the AD/HD group was not reducible to slow mean reaction time (MRT) and that response variability made a larger contribution to increased SSRT in the AD/HD group than inhibitory processes. Examined further, ex-Gaussian analyses of Stop-Signal Task go-trial RT distributions revealed that increased variability in the AD/HD group was not due solely to a few excessively long RTs in the tail of the AD/HD distribution (i.e., tau), but rather indicated the importance of response variability throughout AD/HD group performance on the Stop-Signal Task, as well as the notable sensitivity of ex-Gaussian analyses to variability in data screening procedures. Results of G-CPT analyses indicated some support for the inhibition model, although error type analyses failed to further differentiate the theories. Finally, inclusion of primary variables of interest in exploratory factor analysis with other neurocognitive predictors of AD/HD indicated response variability as a separable construct and further supported its role in Stop-Signal Task performance. Response variability did not, however, make a unique contribution to the prediction of AD/HD symptoms beyond measures of motor processing speed in multiple deficit regression analyses. Results have implications for the interpretation of the processes reflected in widely-used variables in the AD/HD literature, as well as for the theoretical understanding of AD/HD.

Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Primary and secondary metabolites production in signal grass around the year under nitrogen fertilizer

Plants produce a number of substances and products and primary and secondary metabolites (SM) are amongst them with many benefits but limitation as well. Usually, the fodder are not considered toxic to animals or as a source having higher SM. The Brachiaria decumbens has a considerable nutritional value, but it is considered as a toxic grass for causing photosensitization in animals, if the grass is not harvested for more than 30 days or solely. The absence of detailed information in the literature about SM in Brachiaria, metabolites production and its chemical profile enable us to focus not only on the nutritive value but to get answers in all aspects and especially on toxicity. The study was conducted in the period of december 2013 to december 2014; in greenhouse FZEA-USP. B. decumbens was used with two cutting heights (10 and 20 cm) and nitrogen doses (0, 150, 300 and 450 kg ha-1) in complete randomized block design. The bromatological analysis were carried out on near infrared spectroscopy. Generally, the application of 150 kg ha-1 N was sufficient to promote the nutritional value in B. decumbens but above it the nitrogen use efficiency decline significantly. The highest dry matter yield (99.97 g/pot) was observed in autumn and the lowest was in winter (30.20 g/pot). While, as per nitrogen dose the average highest dry matter yield was at 150 kg ha-1 (79.98 g/pot). The highest crude protein was observed in winter (11.88%) and the lowest in autumn (7.78%). By the cutting heights; the 10 cm proved to have high CP (9.51%). In respect of fibrous contents, the highest acid detergent fiber was noted in summer (36.37%) and lowest in winter (30.88%). While the neutral detergent fiber was being highest in autumn and lowest in spring (79.60%). The highest in vitro dry matter and organic matter digestibilities were noted at 300 kg ha-1 N; being 68.06 and 60.57%; respectively; with the lowest observed in without N treatments (62.63% and 57.97), respectively. For determination of the classes, types and concentration of SM in B. decumbens, phytochemical tests, thin layer and liquid chromatography-mass spectrometry and nuclear magnetic resonance analysis were carried out. Height, nitrogen and seasons significantly (P <0.0001) affected the secondary metabolic profile. A new protodioscin isomer (protoneodioscin (25S-)) was identified for first time in B. decumbens and is supposed to be the probable toxicity reason. Its structure was verified by 1D and 2D NMR techniques (1H, 13C) and 1D (COSY-45, edited HSQC, HMBC, H2BC, HSQC -TOCSY, NOESY and 1 H, 1 H, J). All factors influence the metabolic profile significantly (P <0.0001). The lowest phenols were at 300 kg ha-1 while the lowest flavones were at 0 kg ha-1. Season wise the highest phenols occurred in autumn (19.65 mg/g d.wt.) and highest flavones (28.87 mg/g d.wt.) in spring. Seasons effect the saponin production significantly (P <0.0001) and the results showed significant differences in the protodioscin (17.63±4.3 - 22.57±2.2 mg/g d.wt.) and protoneodioscin (23.3±1.2 - 31.07±2.9 mg/g d.wt.) concentrations. The highest protodioscin isomers concentrations were observed in winter and spring and by N doses the highest were noted in 300 kg ha-1. Simply, all factors significantly played their role in varying concentrations of secondary metabolites.

Alterations in energy metabolism, neuroprotection and visual signal transduction in the retina of parkinsonian, MPTP-treated monkeys

Parkinson disease is mainly characterized by the degeneration of dopaminergic neurons in the central nervous system, including the retina. Different interrelated molecular mechanisms underlying Parkinson disease-associated neuronal death have been put forward in the brain, including oxidative stress and mitochondrial dysfunction. Systemic injection of the proneurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) to monkeys elicits the appearance of a parkinsonian syndrome, including morphological and functional impairments in the retina. However, the intracellular events leading to derangement of dopaminergic and other retinal neurons in MPTP-treated animal models have not been so far investigated. Here we have used a comparative proteomics approach to identify proteins differentially expressed in the retina of MPTP-treated monkeys. Proteins were solubilized from the neural retinas of control and MPTP-treated animals, labelled separately with two different cyanine fluorophores and run pairwise on 2D DIGE gels. Out of >700 protein spots resolved and quantified, 36 were found to exhibit statistically significant differences in their expression levels, of at least ±1.4-fold, in the parkinsonian monkey retina compared with controls. Most of these spots were excised from preparative 2D gels, trypsinized and subjected to MALDI-TOF MS and LC-MS/MS analyses. Data obtained were used for protein sequence database interrogation, and 15 different proteins were successfully identified, of which 13 were underexpressed and 2 overexpressed. These proteins were involved in key cellular functional pathways such as glycolysis and mitochondrial electron transport, neuronal protection against stress and survival, and phototransduction processes. These functional categories underscore that alterations in energy metabolism, neuroprotective mechanisms and signal transduction are involved in MPTPinduced neuronal degeneration in the retina, in similarity to mechanisms thought to underlie neuronal death in the Parkinson’s diseased brain and neurodegenerative diseases of the retina proper.

A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

The current trend in the evolution of sensor systems seeks ways to provide more accuracy and resolution, while at the same time decreasing the size and power consumption. The use of Field Programmable Gate Arrays (FPGAs) provides specific reprogrammable hardware technology that can be properly exploited to obtain a reconfigurable sensor system. This adaptation capability enables the implementation of complex applications using the partial reconfigurability at a very low-power consumption. For highly demanding tasks FPGAs have been favored due to the high efficiency provided by their architectural flexibility (parallelism, on-chip memory, etc.), reconfigurability and superb performance in the development of algorithms. FPGAs have improved the performance of sensor systems and have triggered a clear increase in their use in new fields of application. A new generation of smarter, reconfigurable and lower power consumption sensors is being developed in Spain based on FPGAs. In this paper, a review of these developments is presented, describing as well the FPGA technologies employed by the different research groups and providing an overview of future research within this field.

Evolution of the last koninckinids (Athyridida, Koninckinidae), a precursor signal of the early Toarcian mass extinction event in the Western Tethys

Koninckinids are a suitable group to shed light on the biotic crisis suffered by brachiopod fauna in the Early Jurassic. Koninckinid fauna recorded in the late Pliensbachian–early Toarcian from the easternmost Subbetic basin is analyzed and identified as a precursor signal for one of the most conspicuous mass extinction events of the Phylum Brachiopoda, a multi-phased interval with episodes of changing environmental conditions, whose onset can be detected from the Elisa–Mirabile subzones up to the early Toarcian extinction boundary in the lowermost Serpentinum Zone (T-OAE). The koninckinid fauna had a previously well-established migration pattern from the intra-Tethyan to the NW-European basins but a first phase with a progressive warming episode in the Pliensbachian–Toarcian transition triggered a koninckinid fauna exodus from the eastern/central Tethys toward the westernmost Mediterranean margins. A second stage shows an adaptive response to more adverse conditions in the westernmost Tethyan margins and finally, an escape and extinction phase is detected in the Atlantic areas from the mid-Polymorphum Zone onwards up to their global extinction in the lowermost Serpentinum Zone. This migration pattern is independent of the paleogeographic bioprovinciality and is unrelated to a facies-controlled pattern. The anoxic/suboxic environmental conditions should only be considered as a minor factor of partial control since well-oxygenated habitats are noted in the intra-Tethyan basins and this factor is noticeable only in the second westward migratory stage (with dwarf taxa and oligotypical assemblages). The analysis of cold-seep proxies in the Subbetic deposits suggests a radiation that is independent of methane releases in the Subbetic basin.

Paris Climate Agreement 2015 – EU needs to ensure ‘signal’ and ‘direction’. IES Policy Brief Issue 2014/08/October 2014

Summary. Parties to the UN Framework Convention on Climate Change are expected to agree on a new international climate agreement applicable to all countries from 2020 at the Paris climate summit in December 2015. This Policy Brief investigates the possible role of the European Union (EU) towards the 2015 Paris climate agreement. It argues for renewed efforts by the EU at coalition building with progressive developing countries, leadership by example and a more prominent, complementary role of individual EU member states. It also argues for a Paris agreement that provides a strong “signal” and “direction”, and discusses what this may entail.

What signal from the Fed? Should the ECB ease further? CEPS Commentary, 18 September 2015

The Federal Reserve left rates unchanged at its closely-watched meeting on September 17th, although many had argued that the real economy data, especially on the labour market, would have justified an exit (from the zero interest policy). In this CEPS Commentary, Daniel Gros observes that no similar decision on exit is in sight in the euro area, despite the fact that some have argued that the ECB should consider further easing measures (pushing the deposit rate deeper into negative territory or increasing the size of its asset purchase programme). He asks, in fact, whether further easing measures should be even discussed at this point.

Manipulation of the Quorum Sensing Signal AI-2 Affects the Antibiotic-Treated Gut Microbiota

The mammalian gut microbiota harbors a diverse ecosystem where hundreds of bacterial species interact with each other and their host. Given that bacteria use signals to communicate and regulate group behaviors (quorum sensing), we asked whether such communication between different commensal species can influence the interactions occurring in this environment. We engineered the enteric bacterium, Escherichia coli, to manipulate the levels of the interspecies quorum sensing signal, autoinducer-2 (AI-2), in the mouse intestine and investigated the effect upon antibiotic-induced gut microbiota dysbiosis. E. coli that increased intestinal AI-2 levels altered the composition of the antibiotic-treated gut microbiota, favoring the expansion of the Firmicutes phylum. This significantly increased the Firmicutes/Bacteroidetes ratio, to oppose the strong effect of the antibiotic, which had almost cleared the Firmicutes. This demonstrates that AI-2 levels influence the abundance of the major phyla of the gut microbiota, the balance of which is known to influence human health.

Prospective longitudinal study of subcortical brain volumes in individuals at high familial risk of mood disorders with or without subsequent onset of depression

Subcortical volumetric brain abnormalities have been observed in mood disorders. However, it is unknown whether these reflect adverse effects predisposing to mood disorders or emerge at illness onset. Magnetic resonance imaging was conducted at baseline and after two years in 111 initially unaffected young adults at increased risk of mood disorders because of a close family history of bipolar disorder and 93 healthy controls (HC). During the follow-up, 20 high-risk subjects developed major depressive disorder (HR-MDD), with the others remaining well (HR-well). Volumes of the lateral ventricles, caudate, putamen, pallidum, thalamus, hippocampus and amygdala were extracted for each hemisphere. Using linear mixed-effects models, differences and longitudinal changes in subcortical volumes were investigated between groups (HC, HR-MDD, HR-well). There were no significant differences for any subcortical volume between groups controlling for multiple testing. Additionally, no significant differences emerged between groups over time. Our results indicate that volumetric subcortical brain abnormalities of these regions using the current method appear not to form familial trait markers for vulnerability to mood disorders in close relatives of bipolar disorder patients over the two-year time period studied. Moreover, they do not appear to reduce in response to illness onset at least for the time period studied.

Evaluation of emergency vehicle signal preemption on the Route 7 Virginia corridor.

Federal Highway Administration, Office of Operations Research and Development, McLean, Va.