Emergence of oriented circuits driven by synaptic pruning associated with spike-timing-dependent plasticity (STDP)

ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.

The role of tributary relative timing and sequencing in controlling large floods

Hydrograph convolution is a product of tributary inputs from across the watershed. The time-space distribution of precipitation, the biophysical processes that control the conversion of precipitation to runoff and channel flow conveyance processes, are heterogeneous and different areas respond to rainfall in different ways. We take a subwatershed approach to this and account for tributary flow magnitude, relative timing, and sequencing. We hypothesize that as the scale of the watershed increases so we may start to see systematic differences in subwatershed hydrological response. We test this hypothesis for a large flood (T >100 years) in a large watershed in northern England. We undertake a sensitivity analysis of the effects of changing subwatershed hydrological response using a hydraulic model. Delaying upstream tributary peak flow timing to make them asynchronous from downstream subwatersheds reduced flood magnitude. However, significant hydrograph adjustment in any one subwatershed was needed for meaningful reductions in stage downstream, although smaller adjustments in multiple tributaries resulted in comparable impacts. For larger hydrograph adjustments, the effect of changing the timing of two tributaries together was lower than the effect of changing each one separately. For smaller adjustments synergy between two subwatersheds meant the effect of changing them together could be greater than the sum of the parts. Thus, this work shows that while the effects of modifying biophysical catchment properties diminishes with scale due to dilution effects, their impact on relative timing of tributaries may, if applied in the right locations, be an important element of flood management.

What interventions facilitate client progress through the assimilation model? A task analysis of interventions in the psychodynamic treatment of depression.

A variation of task analysis was used to build an empirical model of how therapists may facilitate client assimilation process, described in the Assimilation of Problematic Experiences Scale. A rational model was specified and considered in light of an analysis of therapist in-session performances (N = 117) drawn from six inpatient therapies for depression. The therapist interventions were measured by the Comprehensive Psychotherapeutic Interventions Rating Scale. Consistent with the rational model, confronting interventions were particularly useful in helping clients elaborate insight. However, rather than there being a small number of progress-related interventions at lower levels of assimilation, therapists' use of interventions was broader than hypothesized and drew from a wide range of therapeutic approaches. Concerning the higher levels of assimilation, there was insufficient data to allow an analysis of the therapist's progress-related interventions.

Task-induced deactivation from rest extends beyond the default mode brain network

Activity decreases, or deactivations, of midline and parietal cortical brain regions are routinely observed in human functional neuroimaging studies that compare periods of task-based cognitive performance with passive states, such as rest. It is now widely held that such task-induced deactivations index a highly organized"default-mode network" (DMN): a large-scale brain system whose discovery has had broad implications in the study of human brain function and behavior. In this work, we show that common task-induced deactivations from rest also occur outside of the DMN as a function of increased task demand. Fifty healthy adult subjects performed two distinct functional magnetic resonance imaging tasks that were designed to reliably map deactivations from a resting baseline. As primary findings, increases in task demand consistently modulated the regional anatomy of DMN deactivation. At high levels of task demand, robust deactivation was observed in non-DMN regions, most notably, the posterior insular cortex. Deactivation of this region was directly implicated in a performance-based analysis of experienced task difficulty. Together, these findings suggest that task-induced deactivations from rest are not limited to the DMN and extend to brain regions typically associated with integrative sensory and interoceptive processes.

Task complexity, the Cognition Hypothesis and second language learning and performance

In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.

Transferring control demands across incidental learning tasks - Stronger sequence usage in serial reaction task after shortcut option in letter string checking

After incidentally learning about a hidden regularity, participants can either continue to solve the task as instructed or, alternatively, apply a shortcut. Past research suggests that the amount of conflict implied by adopting a shortcut seems to bias the decision for vs. against continuing instruction-coherent task processing. We explored whether this decision might transfer from one incidental learning task to the next. Theories that conceptualize strategy change in incidental learning as a learning-plus-decision phenomenon suggest that high demands to adhere to instruction-coherent task processing in Task 1 will impede shortcut usage in Task 2, whereas low control demands will foster it. We sequentially applied two established incidental learning tasks differing in stimuli, responses and hidden regularity (the alphabet verification task followed by the serial reaction task, SRT). While some participants experienced a complete redundancy in the task material of the alphabet verification task (low demands to adhere to instructions), for others the redundancy was only partial. Thus, shortcut application would have led to errors (high demands to follow instructions). The low control demand condition showed the strongest usage of the fixed and repeating sequence of responses in the SRT. The transfer results are in line with the learning-plus-decision view of strategy change in incidental learning, rather than with resource theories of self-control.

Aortic blood pressure measured via EIT: investigation of different measurement settings.

Electrical impedance tomography (EIT) allows the measurement of intra-thoracic impedance changes related to cardiovascular activity. As a safe and low-cost imaging modality, EIT is an appealing candidate for non-invasive and continuous haemodynamic monitoring. EIT has recently been shown to allow the assessment of aortic blood pressure via the estimation of the aortic pulse arrival time (PAT). However, finding the aortic signal within EIT image sequences is a challenging task: the signal has a small amplitude and is difficult to locate due to the small size of the aorta and the inherent low spatial resolution of EIT. In order to most reliably detect the aortic signal, our objective was to understand the effect of EIT measurement settings (electrode belt placement, reconstruction algorithm). This paper investigates the influence of three transversal belt placements and two commonly-used difference reconstruction algorithms (Gauss-Newton and GREIT) on the measurement of aortic signals in view of aortic blood pressure estimation via EIT. A magnetic resonance imaging based three-dimensional finite element model of the haemodynamic bio-impedance properties of the human thorax was created. Two simulation experiments were performed with the aim to (1) evaluate the timing error in aortic PAT estimation and (2) quantify the strength of the aortic signal in each pixel of the EIT image sequences. Both experiments reveal better performance for images reconstructed with Gauss-Newton (with a noise figure of 0.5 or above) and a belt placement at the height of the heart or higher. According to the noise-free scenarios simulated, the uncertainty in the analysis of the aortic EIT signal is expected to induce blood pressure errors of at least ± 1.4 mmHg.

Hippocampal Theta-Phase Modulation of Replay Correlates with Configural-Relational Short-Term Memory Performance

Thereis now growing evidencethatthe hippocampus generatestheta rhythmsthat can phase biasfast neural oscillationsinthe neocortex, allowing coordination of widespread fast oscillatory populations outside limbic areas. A recent magnetoencephalographic study showed that maintenance of configural-relational scene information in a delayed match-to-sample (DMS) task was associated with replay of that information during the delay period. The periodicity of the replay was coordinated by the phase of the ongoing theta rhythm, and the degree of theta coordination during the delay period was positively correlated with DMS performance. Here, we reanalyzed these data to investigate which brain regions were involved in generating the theta oscillations that coordinated the periodic replay of configural- relational information. We used a beamformer algorithm to produce estimates of regional theta rhythms and constructed volumetric images of the phase-locking between the local theta cycle and the instances of replay (in the 13- 80 Hz band). We found that individual differences in DMS performancefor configural-relational associations were relatedtothe degree of phase coupling of instances of cortical reactivations to theta oscillations generated in the right posterior hippocampus and the right inferior frontal gyrus. This demonstrates that the timing of memory reactivations in humans is biased toward hippocampal theta phase

Quantifying the time for accurate EEG decoding of single value-based decisions.

BACKGROUND: Recent neuroimaging studies suggest that value-based decision-making may rely on mechanisms of evidence accumulation. However no studies have explicitly investigated the time when single decisions are taken based on such an accumulation process. NEW METHOD: Here, we outline a novel electroencephalography (EEG) decoding technique which is based on accumulating the probability of appearance of prototypical voltage topographies and can be used for predicting subjects' decisions. We use this approach for studying the time-course of single decisions, during a task where subjects were asked to compare reward vs. loss points for accepting or rejecting offers. RESULTS: We show that based on this new method, we can accurately decode decisions for the majority of the subjects. The typical time-period for accurate decoding was modulated by task difficulty on a trial-by-trial basis. Typical latencies of when decisions are made were detected at ∼500ms for 'easy' vs. ∼700ms for 'hard' decisions, well before subjects' response (∼340ms). Importantly, this decision time correlated with the drift rates of a diffusion model, evaluated independently at the behavioral level. COMPARISON WITH EXISTING METHOD(S): We compare the performance of our algorithm with logistic regression and support vector machine and show that we obtain significant results for a higher number of subjects than with these two approaches. We also carry out analyses at the average event-related potential level, for comparison with previous studies on decision-making. CONCLUSIONS: We present a novel approach for studying the timing of value-based decision-making, by accumulating patterns of topographic EEG activity at single-trial level.

EAACI IG Biologicals task force paper on the use of biologic agents in allergic disorders.

Biologic agents (also termed biologicals or biologics) are therapeutics that are synthesized by living organisms and directed against a specific determinant, for example, a cytokine or receptor. In inflammatory and autoimmune diseases, biologicals have revolutionized the treatment of several immune-mediated disorders. Biologicals have also been tested in allergic disorders. These include agents targeting IgE; T helper 2 (Th2)-type and Th2-promoting cytokines, including interleukin-4 (IL-4), IL-5, IL-9, IL-13, IL-31, and thymic stromal lymphopoietin (TSLP); pro-inflammatory cytokines, such as IL-1β, IL-12, IL-17A, IL-17F, IL-23, and tumor necrosis factor (TNF); chemokine receptor CCR4; and lymphocyte surface and adhesion molecules, including CD2, CD11a, CD20, CD25, CD52, and OX40 ligand. In this task force paper of the Interest Group on Biologicals of the European Academy of Allergy and Clinical Immunology, we review biologicals that are currently available or tested for the use in various allergic and urticarial pathologies, by providing an overview on their state of development, area of use, adverse events, and future research directions.

Effects of manipulating Task Complexity on self-repairs during L2 oral production

This paper analyses the effects of manipulating the cognitive complexity of L2 oral tasks on language production. It specifically focuses on self-repairs, which are taken as a measure of accuracy since they denote both attention to form and an attempt at being accurate. By means of a repeated measures de- sign, 42 lower-intermediate students were asked to perform three different tasks types (a narrative, and instruction-giving task, and a decision-making task) for which two degrees of cognitive complexity were established. The narrative task was manipulated along +/− Here-and-Now, an instruction-giving task ma- nipulated along +/− elements, and the decision-making task which is manipu- lated along +/− reasoning demands. Repeated measures ANOVAs are used for the calculation of differences between degrees of complexity and among task types. One-way ANOVA are used to detect potential differences between low- proficiency and high-proficiency participants. Results show an overall effect of Task Complexity on self-repairs behavior across task types, with different be- haviors existing among the three task types. No differences are found between the self-repair behavior between low and high proficiency groups. Results are discussed in the light of theories of cognition and L2 performance (Robin- son 2001a, 2001b, 2003, 2005, 2007), L1 and L2 language production models (Levelt 1989, 1993; Kormos 2000, 2006), and attention during L2 performance (Skehan 1998; Robinson, 2002).

Emotional intelligence compensates for low IQ and boosts low emotionality individuals in a self-presentation task

The research on emotional intelligence (EI) has focused mainly on testing the incremental validity of EI with respect to general intelligence and personality; less attention has been devoted to investigating the potential interaction effects. In a self-presentation task that required participants to obtain positive evaluations from others, individuals low in IQ but high in EI performed as well as the high IQ individuals. In addition, the low emotionality individuals performed significantly higher when also high in EI. The results extend the previous findings on the compensatory effect of EI on low IQ to the domain of interpersonal effectiveness and shed light on the effective functioning of personality traits when interpreted with the interaction of EI. Overall this study suggests that the role of EI in predicting performance might have been overlooked by checking solely for main effects and illustrates new venues for understanding the contribution of EI in explaining emotion-laden performance.

Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety.

PURPOSE: To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data. METHODS: As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting. RESULTS: The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators. CONCLUSIONS: As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of 'arising after admission' (yes/no), with permitted designations of 'unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing flag.