Classical Analogue of the Ionic Hubbard Model

In our earlier work [M. Hafez, {\em et al.}, Phys. Lett. A {\bf 373} (2009) 4479] we employed the flow equation method to obtain a classic effective model from a quantum mechanical parent Hamiltonian called, the ionic Hubbard model (IHM). The classical ionic Hubbard model (CIHM) obtained in this way contains solely Fermionic occupation numbers of two species corresponding to particles with \up and \down spin, respectively. In this paper, we employ the transfer matrix method to analytically solve the CIHM at finite temperature in one dimension. In the limit of zero temperature, we find two insulating phases at large and small Coulomb interaction strength, $U$, mediated with a gap-less metallic phase, resulting in two continuous metal-insulator transitions. Our results are further supported with Monte Carlo simulations.Comment: 12 figure

A value chain analysis of Malaysia's seaweed industry

A global shortfall in protein supply from capture fisheries has motivated the Malaysian government to revise its aquaculture strategy, focusing on three commodities: seaweed, fish and marine shrimp. However, the performance of the Malaysian aquaculture sector, particularly seaweed production, is poorly documented. This is the first empirical study to undertake a value chain analysis (VCA) of the Malaysian seaweed sector using stakeholder perceptions and secondary data that encompass members of seaweed farming cooperatives (the Semporna Area Farmers’ Association and the governments’ flagship Seaweed Cluster Project). Fieldwork was conducted between April and June 2015 among seaweed stakeholders involved in the value chain using a mixed methods approach—in-depth interviews with key informants, focus group discussions, household surveys, personal observation and secondary data. Qualitative and quantitative data were collected from both upstream (seaweed farming, marketing structure and the Malaysian Good Aquaculture Practices [MyGAP] certification programme) and downstream (seaweed processing) activities involving farmers, intermediaries/middlemen (buyers), processors and officials. Kappaphycus spp. was sold in two forms: (1) dried seaweed to be used as raw materials in carrageenan processing (approximately 90% of total harvest) and (2) fresh seaweed to be used as a source of seedlings (approximately 10% of total harvest). The value chain ended with the carrageenan form, which is exported to international markets. The price of dried seaweed varied according to a combination of seaweed quality, the strength of farmer’s relationships with intermediaries and processors and in response to demand from the carrageenan industry. The prices obtained by Malaysian farmers for dried seaweed and carrageenan remained low, US$0.60 and US$ 4.43 per kg, respectively, despite efforts by the government to enhance the value chain by imposing seaweed standards (via MyGAP) for farm management, dried seaweed and semi-refined carrageenan. The VCA was a useful tool to identify and map the market, with the results providing a better understanding of the seaweed sector, which could be helpful in supporting further aquaculture development in Malaysia

Sampling time and performance in rat whisker sensory system

We designed a behavioural paradigm for vibro-tactile detection to characterise the sampling time and performance in the rat whisker sensory system. Rats initiated a trial by nose-poking into an aperture where their whiskers came into contact with two meshes. A continuous nose-poke for a random duration triggered stimulus presentation. Stimuli were a sequence of discrete Gaussian deflections of the mesh that increased in amplitude over time - across 5 conditions, time to maximum amplitude varied from 0.5 to 8 seconds. Rats indicated the detected stimulus by choosing between two reward spouts. Two rats completed more than 500 trials per condition. Rats' stimulus sampling duration increased and performance dropped with increasing task difficulty. For all conditions the median reaction time was longer for correct trials than incorrect trials. Higher rates of increment in stimulus amplitude resulted in faster rise in performance as a function of stimulus sampling duration. Rats' behaviour indicated a dynamic stimulus sampling whereby nose-poke was maintained until a stimulus was correctly identified or the rat experienced a false alarm. The perception was then manifested in behaviour after a motor delay. We thus modelled the results with 3 parameters: signal detection, false alarm, and motor delay. The model captured the main features of the data and produced parameter estimates that were biologically plausible and highly similar across the two rats

Population decoding in rat barrel cortex: optimizing the linear readout of correlated population responses

Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting stimuli of 0, 6 and 12 µm in amplitude. Using the framework of signal detection theory, we quantified the performance of a linear decoder which sums the responses of neurons after applying an optimum set of weights. Optimum weights were found by the analytical solution that maximized the average signal-to-noise ratio based on Fisher linear discriminant analysis. This provided a biologically plausible decoder that took into account the neuronal variability, covariability, and signal correlations. The optimal decoder achieved consistent improvement in discrimination performance over simple pooling. Decorrelating neuronal responses by trial shuffling revealed that, unlike pooling, the performance of the optimal decoder was minimally affected by noise correlation. In the non-adapted state, noise correlation enhanced the performance of the optimal decoder for some populations. Under adaptation, however, noise correlation always degraded the performance of the optimal decoder. Nonetheless, sensory adaptation improved the performance of the optimal decoder mainly by increasing signal correlation more than noise correlation. Adaptation induced little systematic change in the relative direction of signal and noise. Thus, a decoder which was optimized under the non-adapted state generalized well across states of adaptation

Adaptation improves neural coding efficiency despite increasing correlations in variability

Exposure of cortical cells to sustained sensory stimuli results in changes in the neuronal response function. This phenomenon, known as adaptation, is a common feature across sensory modalities. Here, we quantified the functional effect of adaptation on the ensemble activity of cortical neurons in the rat whisker-barrel system. A multishank array of electrodes was used to allow simultaneous sampling of neuronal activity. We characterized the response of neurons to sinusoidal whisker vibrations of varying amplitude in three states of adaptation. The adaptors produced a systematic rightward shift in the neuronal response function. Consistently, mutual information revealed that peak discrimination performance was not aligned to the adaptor but to test amplitudes 3–9 um higher. Stimulus presentation reduced single neuron trial-to-trial response variability (captured by Fano factor) and correlations in the population response variability (noise correlation). We found that these two types of variability were inversely proportional to the average firing rate regardless of the adaptation state. Adaptation transferred the neuronal operating regime to lower rates with higher Fano factor and noise correlations. Noise correlations were positive and in the direction of signal, and thus detrimental to coding efficiency. Interestingly, across all population sizes, the net effect of adaptation was to increase the total information despite increasing the noise correlation between neurons.This work was supported by the Australian Research Council Discovery Project DP0987133 and the Australian National Health and Medical Research Council Project Grant 1028670