Noise and Periodic Modulations in Neural Excitable Media

We have analyzed the interplay between noise and periodic modulations in a mean field model of a neural excitable medium. To this purpose, we have considered two types of modulations; namely, variations of the resistance and oscillations of the threshold. In both cases, stochastic resonance is present, irrespective of if the system is monostable or bistable.Comment: 13 pages, RevTex, 5 PostScript figure

Higher Education and behavior analysis in Europe::Creating a unified approach for the training of autism professionals

Training of behaviour analysts for autism services, has improved notably within a European higher education context. However, regional discrepancies associated with economic, health care, social services, and institutional policies magnify the importance of creating appropriate unified training and consumer protection. Although the European Association for Behaviour Analysis (EABA) has endorsed the Behavior Analyst Certification Board’s (BACB) designations, the absence of European and national regulations, recognition, and accreditation remain significant barriers to quality training and implementation. These challenges are  particularly pertinent in light of BACB decision to limit certification to residents in the USA and Canada after 2022. Advances, challenges, and future directions are discussed within the context of higher education in the United Kingdom, the Czech Republic, Greece, Iceland, Italy, Norway, and Sweden. The post-Bologna European agenda for higher education, globalization and opportunities for the training of behaviour analysts within European higher education are outlined

Differential impact of drugs on the outcome of ETV6-RUNX1 positive childhood B-cell precursor acute lymphoblastic leukaemia : results of the EORTC CLG 58881 and 58951 trials

info:eu-repo/semantics/publishe

Outcome of infants younger than 1 year with acute lymphoblastic leukemia treated with the interfant-06 protocol: Results from an international phase III randomized study

PURPOSE Infant acute lymphoblastic leukemia (ALL) is characterized by KMT2A (MLL) gene rearrangements and coexpression of myeloid markers. The Interfant-06 study, comprising 18 national and international study groups, tested whether myeloid-style consolidation chemotherapy is superior to lymphoid style, the role of stemcell transplantation (SCT), and which factors had independent prognostic value. MATERIALS AND METHODS Three risk groups were defined: low risk (LR): KMT2A germline; high risk (HR): KMT2A-rearranged and older than 6 months with WBC count 300 3 109/L or more or a poor prednisone response; and medium risk (MR): all other KMT2A-rearranged cases. Patients in the MR and HR groups were randomly assigned to receive the lymphoid course low-dose cytosine arabinoside [araC], 6-mercaptopurine, cyclophosphamide (IB) or experimental myeloid courses, namely araC, daunorubicin, etoposide (ADE) and mitoxantrone, araC, etoposide (MAE). RESULTS A total of 651 infants were included, with 6-year event-free survival (EFS) and overall survival of 46.1% (SE, 2.1) and 58.2% (SE, 2.0). In West European/North American groups, 6-year EFS and overall survival were 49.4% (SE, 2.5) and 62.1% (SE, 2.4), which were 10% to 12% higher than in other countries. The 6-year probability of disease-free survival was comparable for the randomized arms (ADE1MAE 39.3% [SE 4.0; n = 169] v IB 36.8% [SE, 3.9; n = 161]; log-rank P = .47). The 6-year EFS rate of patients in the HR group was 20.9% (SE, 3.4) with the intention to undergo SCT; only 46% of them received SCT, because many had early events. KMT2A rearrangement was the strongest prognostic factor for EFS, followed by age, WBC count, and prednisone response. CONCLUSION Early intensification with postinduction myeloid-type chemotherapy courses did not significantly improve outcome for infant ALL compared with the lymphoid-type course IB. Outcome for infant ALL in Interfant- 06 did not improve compared with that in Interfant-99

Electronic gaming machine characteristics: it's the little things that count

A range of gamblers, from low-frequency social gamblers through to problem gamblers in treatment, participated in focus groups discussing the characteristics of Electronic Gaming Machines (EGMs) that they found attractive. Analyses of the resulting transcripts resulted in two groups of EGM characteristics being identified as important, one group associated with winning and one with betting. Overall, free spin features were identified in all groups as the most attractive characteristic of EGMS. Beyond that it was smaller win-related characteristics, and low-denomination machines with multiple playable lines that were associated with increased duration and intensity of gambling behaviour. The important characteristics were consistent across different levels of gamblers, with the key behavioural difference being a self-reported ‘expertise’, and ‘strategic’ approach to gambling amongst higher-frequency gamblers and problem gamblers in treatment. The key characteristics all occur frequently and result in more wins and extended gambling sessions. The patterns identified resonated with established behavioural principles, and with models describing the development of problem gambling and addictions more generally

A Stable Biologically Motivated Learning Mechanism for Visual Feature Extraction to Handle Facial Categorization

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task

Predicted contextual modulation varies with distance from pinwheel centers in the orientation preference map

In the primary visual cortex (V1) of some mammals, columns of neurons with the full range of orientation preferences converge at the center of a pinwheel-like arrangement, the ‘pinwheel center' (PWC). Because a neuron receives abundant inputs from nearby neurons, the neuron's position on the cortical map likely has a significant impact on its responses to the layout of orientations inside and outside its classical receptive field (CRF). To understand the positional specificity of responses, we constructed a computational model based on orientation preference maps in monkey V1 and hypothetical neuronal connections. The model simulations showed that neurons near PWCs displayed weaker but detectable orientation selectivity within their CRFs, and strongly reduced contextual modulation from extra-CRF stimuli, than neurons distant from PWCs. We suggest that neurons near PWCs robustly extract local orientation within their CRF embedded in visual scenes, and that contextual information is processed in regions distant from PWCs

The benefit of symbols: monkeys show linear, human-like, accuracy when using symbols to represent scalar value

When humans and animals estimate numbers of items, their error rate is proportional to the number. To date, however, only humans show the capacity to represent large numbers symbolically, which endows them with increased precision, especially for large numbers, and with tools for manipulating numbers. This ability depends critically on our capacity to acquire and represent explicit symbols. Here we show that when rhesus monkeys are trained to use an explicit symbol system, they too show more precise, and linear, scaling than they do using a one-to-one corresponding numerosity representation. We also found that when taught two different types of representations for reward amount, the monkeys systematically undervalued the less precise representation. The results indicate that monkeys, like humans, can learn alternative mechanisms for representing a single value scale and that performance variability and relative value depend on the distinguishability of each representation

Adaptive Gain Modulation in V1 Explains Contextual Modifications during Bisection Learning

The neuronal processing of visual stimuli in primary visual cortex (V1) can be modified by perceptual training. Training in bisection discrimination, for instance, changes the contextual interactions in V1 elicited by parallel lines. Before training, two parallel lines inhibit their individual V1-responses. After bisection training, inhibition turns into non-symmetric excitation while performing the bisection task. Yet, the receptive field of the V1 neurons evaluated by a single line does not change during task performance. We present a model of recurrent processing in V1 where the neuronal gain can be modulated by a global attentional signal. Perceptual learning mainly consists in strengthening this attentional signal, leading to a more effective gain modulation. The model reproduces both the psychophysical results on bisection learning and the modified contextual interactions observed in V1 during task performance. It makes several predictions, for instance that imagery training should improve the performance, or that a slight stimulus wiggling can strongly affect the representation in V1 while performing the task. We conclude that strengthening a top-down induced gain increase can explain perceptual learning, and that this top-down signal can modify lateral interactions within V1, without significantly changing the classical receptive field of V1 neurons

Axonal Dynamics of Excitatory and Inhibitory Neurons in Somatosensory Cortex

Electrophysiology-delivery of fluorescent viral vectors-and two-photon microscopy were used to demonstrate the rapidity of axonal restructuring of both excitatory and inhibitory neurons in rodent cortical layer II/III following alterations in sensory experience