Biased ART: A Neural Architecture that Shifts Attention Toward Previously Disregarded Features Following an Incorrect Prediction

Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Twodimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/.

The role of larval nutrition in pre-imaginal biasing of caste in the primitively eusocial wasp Ropalidia marginata (Hymenoptera: Vespidae)

1. When freshly eclosed females of the primitively eusocial wasp Ropalidia marginata (Lep.) are isolated, only about 50% of them build nests and lay eggs thereby suggesting a pre-imaginal biasing of caste. 2. Wasps that lay eggs take a very variable amount of time after eclosion to start doing so. 3. Females eclosing from nests where larvae are fed at a relatively higher rate are more likely to become egg-layers and are likely to take less time after eclosion to begin to lay eggs. 4. Thus, both forms of pre-imaginal biasing of caste, namely, differences in egg laying capacity and differences in the time taken to attain reproductive maturity, appear to be influenced by larval nutrition.

Effect of ``dipolar-biasing'' on the tunability of tunneling magnetoresistance in transition metal oxide systems

We observe an unusual tunneling magnetoresistance (TMR) phenomenon in a composite of La2/3Sr1/3MnO3 with CoFe2O4 where the TMR versus applied magnetic field loop suggests a ``negative coercive field.'' Tracing its origin back to a ``dipolar-biasing'' of La2/3Sr1/3MnO3 by CoFe2O4, we show that the TMR of even a single composite can be tuned continuously so that the resistance peak or the highest sensitivity of the TMR can be positioned anywhere on the magnetic field axis with a suitable magnetic history of the sample. This phenomenon of an unprecedented tunability of the TMR should be present in general in all such composites. (C) 2012 American Institute of Physics.http://dx.doi.org/10.1063/1.4731206]

Suppression Of Barkhausen Noise Due To Exchange Biasing In Fe-FeMn Bilalayers

Exchange biased Fe(FM)-FeMn(AFM) bilayers were grown by pulsed laser ablation in UHV and probed by SQUID magnetometer and planar Hall effect measurements. A suppression of barkhausen avalanches was observed during the switching of the bilayer when compared to that of pure Fe, which is indicative of a change in the reversal mechanism.

Long-distance correlations in TCABR biasing experiments

Long-distance correlations (LDCs) of plasma potential fluctuations in the plasma edge have been investigated in the TCABR tokamak in the regime of edge biasing H-mode using an array of multi-pin Langmuir probes. This activity was carried out as part of the scientific programme of the 4th IAEA Joint Experiment (2009). The experimental data confirm the effect of amplification of LDCs in potential fluctuations during biasing recently observed in stellarators and tokamaks. For long toroidal distances between probes, the cross-spectrum is concentrated at low frequencies f < 60 kHz with peaks at f < 5 kHz, f = 13-15 kHz and f similar to 40 kHz and low wave numbers with a maximum at k = 0. The effects of MHD activity on the LDCs in potential fluctuation are investigated.

Emotion recognition: The role of featural and configural face information

Several studies investigated the role of featural and configural information when processing facial identity. A lot less is known about their contribution to emotion recognition. In this study, we addressed this issue by inducing either a featural or a configural processing strategy (Experiment 1) and by investigating the attentional strategies in response to emotional expressions (Experiment 2). In Experiment 1, participants identified emotional expressions in faces that were presented in three different versions (intact, blurred, and scrambled) and in two orientations (upright and inverted). Blurred faces contain mainly configural information, and scrambled faces contain mainly featural information. Inversion is known to selectively hinder configural processing. Analyses of the discriminability measure (A′) and response times (RTs) revealed that configural processing plays a more prominent role in expression recognition than featural processing, but their relative contribution varies depending on the emotion. In Experiment 2, we qualified these differences between emotions by investigating the relative importance of specific features by means of eye movements. Participants had to match intact expressions with the emotional cues that preceded the stimulus. The analysis of eye movements confirmed that the recognition of different emotions rely on different types of information. While the mouth is important for the detection of happiness and fear, the eyes are more relevant for anger, fear, and sadness.

A model for mesoscale patterns in motile populations

Experimental observations of cell migration often describe the presence of mesoscale patterns within motile cell populations. These patterns can take the form of cells moving as aggregates or in chain-like formation. Here we present a discrete model capable of producing mesoscale patterns. These patterns are formed by biasing movements to favor a particular configuration of agent–agent attachments using a binding function f(K), where K is the scaled local coordination number. This discrete model is related to a nonlinear diffusion equation, where we relate the nonlinear diffusivity D(C) to the binding function f. The nonlinear diffusion equation supports a range of solutions which can be either smooth or discontinuous. Aggregation patterns can be produced with the discrete model, and we show that there is a transition between the presence and absence of aggregation depending on the sign of D(C). A combination of simulation and analysis shows that both the existence of mesoscale patterns and the validity of the continuum model depend on the form of f. Our results suggest that there may be no formal continuum description of a motile system with strong mesoscale patterns.