Adaptive whitening with fast gain modulation and slow synaptic plasticity

Neurons in early sensory areas rapidly adapt to changing sensory statistics, both by normalizing the variance of their individual responses and by reducing correlations between their responses. Together, these transformations may be viewed as an adaptive form of statistical whitening. Existing mechanistic models of adaptive whitening exclusively use either synaptic plasticity or gain modulation as the biological substrate for adaptation; however, on their own, each of these models has significant limitations. In this work, we unify these approaches in a normative multi-timescale mechanistic model that adaptively whitens its responses with complementary computational roles for synaptic plasticity and gain modulation. Gains are modified on a fast timescale to adapt to the current statistical context, whereas synapses are modified on a slow timescale to match structural properties of the input statistics that are invariant across contexts. Our model is derived from a novel multi-timescale whitening objective that factorizes the inverse whitening matrix into basis vectors, which correspond to synaptic weights, and a diagonal matrix, which corresponds to neuronal gains. We test our model on synthetic and natural datasets and find that the synapses learn optimal configurations over long timescales that enable adaptive whitening on short timescales using gain modulation.Comment: NeurIPS 2023 Spotlight; 18 pages, 8 figure

Psychiatric Comorbidity and Complex Regional Pain Syndrome Through the Lens of the Biopsychosocial Model: A Comparative Study.

To compare the prevalence of psychiatric comorbidity between patients with complex regional pain syndrome (CRPS) of the hand and non-CRPS patients and to assess the association between biopsychosocial (BPS) complexity profiles and psychiatric comorbidity in a comparative study. We included a total of 103 patients with CRPS of the hand and 290 patients with chronic hand impairments but without CRPS. Psychiatric comorbidities were diagnosed by a psychiatrist, and BPS complexity was measured by means of the INTERMED. The odds ratios (OR) of having psychiatric comorbidities according to BPS complexity were calculated with multiple logistic regression (adjusted for age, sex, and pain). Prevalence of psychiatric comorbidity was 29% in CRPS patients, which was not significantly higher than in non-CRPS patients (21%, relative risk=1.38, 95% CI: 0.95 to 2.01 p=0.10). The median total scores of the INTERMED were the same in both groups (23 points). INTERMED total scores (0-60 points) were related to an increased risk of having psychiatric comorbidity in CRPS patients (OR=1.46; 95% CI: 1.23-1.73) and in non-CRPS patients (OR=1.21; 95% CI: 1.13-1.30). The four INTERMED subscales (biological, psychological, social, and health care) were correlated with a higher risk of having psychiatric comorbidity in both groups. The differences in the OR of having psychiatric comorbidity in relation to INTERMED total and subscale scores were not statistically different between the two groups. The total scores, as well as all four dimensions of BPS complexity measured by the INTERMED, were associated with psychiatric comorbidity, with comparable magnitudes of association between the CRPS and non-CRPS groups. The INTERMED was useful in screening for psychological vulnerability in the two groups

Adaptive whitening in neural populations with gain-modulating interneurons

Statistical whitening transformations play a fundamental role in many computational systems, and may also play an important role in biological sensory systems. Existing neural circuit models of adaptive whitening operate by modifying synaptic interactions; however, such modifications would seem both too slow and insufficiently reversible. Motivated by the extensive neuroscience literature on gain modulation, we propose an alternative model that adaptively whitens its responses by modulating the gains of individual neurons. Starting from a novel whitening objective, we derive an online algorithm that whitens its outputs by adjusting the marginal variances of an overcomplete set of projections. We map the algorithm onto a recurrent neural network with fixed synaptic weights and gain-modulating interneurons. We demonstrate numerically that sign-constraining the gains improves robustness of the network to ill-conditioned inputs, and a generalization of the circuit achieves a form of local whitening in convolutional populations, such as those found throughout the visual or auditory systems.Comment: 20 pages, 10 figures (incl. appendix). To appear in the Proceedings of the 40th International Conference on Machine Learnin

On some multiplicity and mixed multiplicity formulas (Forum Math. 26(2014), 413-442)

This paper gives the additivity and reduction formulas for mixed multiplicities of multi-graded modules $M$ and mixed multiplicities of arbitrary ideals, and establishes the recursion formulas for the sum of all the mixed multiplicities of $M.$ As an application of these formulas we get the recursion formulas for the multiplicity of multi-graded Rees modules

Reconstruction of a function from its spherical (circular) means with the centers lying on the surface of certain polygons and polyhedra

We present explicit filtration/backprojection-type formulae for the inversion of the spherical (circular) mean transform with the centers lying on the boundary of some polyhedra (or polygons, in 2D). The formulae are derived using the double layer potentials for the wave equation, for the domains with certain symmetries. The formulae are valid for a rectangle and certain triangles in 2D, and for a cuboid, certain right prisms and a certain pyramid in 3D. All the present inversion formulae yield exact reconstruction within the domain surrounded by the acquisition surface even in the presence of exterior sources.Comment: 9 figure

Absorbing boundary conditions for the Westervelt equation

The focus of this work is on the construction of a family of nonlinear absorbing boundary conditions for the Westervelt equation in one and two space dimensions. The principal ingredient used in the design of such conditions is pseudo-differential calculus. This approach enables to develop high order boundary conditions in a consistent way which are typically more accurate than their low order analogs. Under the hypothesis of small initial data, we establish local well-posedness for the Westervelt equation with the absorbing boundary conditions. The performed numerical experiments illustrate the efficiency of the proposed boundary conditions for different regimes of wave propagation

Evaluating energy consumption of air gap membrane distillation for seawater desalination at pilot scale level

This study aimed to optimise an air gap membrane distillation (AGMD) system for seawater desalination with respect to distillate production as well as thermal and electrical energy consumption. Pilot evaluation data shows a notable influence of evaporator inlet temperature and water circulation rate on process performance. An increase in both distillate production rate and energy efficiency could be obtained by increasing the evaporator inlet temperature. On the other hand, there was a trade-off between the distillate production rate and energy efficiency when the water circulation rate varied. Increasing the water circulation rate resulted in an improvement in the distillate production rate, but also an increase in both specific thermal and electrical energy consumption. Given the small driving force used in the pilot AGMD, discernible impact of feed salinity on process performance could be observed, while the effects of temperature and concentration polarisation were small. At the optimum operating conditions identified in this study, a stable AGMD operation for seawater desalination could be achieved with specific thermal and electrical energy consumption of 90 and 0.13 kW h/m3, respectively. These values demonstrate the commercial viability of AGMD for small-scale and off-grid seawater desalination where solar thermal or low-grade heat sources are readily available

Quenched Hadrons using Wilson and O(a)-Improved Fermion Actions at beta=6.2

We present the first study of the light hadron spectrum and decay constants for quenched QCD using an O(a)-improved nearest-neighbour Wilson fermion action at \beta=6.2. We compare the results with those obtained using the standard Wilson fermion action, on the same set of 18 gauge field configurations of a 24^3 times 48 lattice. For pseudoscalar meson masses in the range 330-800 MeV, we find no significant difference between the results for the two actions. The scales obtained from the string tension and mesonic sector are consistent, but differ from that derived from baryon masses. The ratio of the pseudoscalar decay constant to the vector meson mass is roughly independent of quark mass as observed experimentally, and in approximate agreement with the measured value.Comment: 11 page

SUSY GUTs contributions and model independent extractions of CP phases

We consider the origin of new phases in supersymmetric grand unification model, and show how significant new contributions arise from the gluino mediated diagram. We then present a more general model independent analysis of various modes of B-decays suggested previously for measurement of the CKM phases and point out what they really measure. It is in principle possible to separate out all the phases.Comment: 13 pages (Latex), 2 PS figures, a few remarks are added and a typo is corrected. To appear in Phys. Rev. Let