Detection of Polarization in the Cosmic Microwave Background using DASI

We report the detection of polarized anisotropy in the Cosmic Microwave Background radiation with the Degree Angular Scale Interferometer (DASI), located at the Amundsen-Scott South Pole research station. Observations in all four Stokes parameters were obtained within two 3.4 FWHM fields separated by one hour in Right Ascension. The fields were selected from the subset of fields observed with DASI in 2000 in which no point sources were detected and are located in regions of low Galactic synchrotron and dust emission. The temperature angular power spectrum is consistent with previous measurements and its measured frequency spectral index is -0.01 (-0.16 -- 0.14 at 68% confidence), where 0 corresponds to a 2.73 K Planck spectrum. The power spectrum of the detected polarization is consistent with theoretical predictions based on the interpretation of CMB anisotropy as arising from primordial scalar adiabatic fluctuations. Specifically, E-mode polarization is detected at high confidence (4.9 sigma). Assuming a shape for the power spectrum consistent with previous temperature measurements, the level found for the E-mode polarization is 0.80 (0.56 -- 1.10), where the predicted level given previous temperature data is 0.9 -- 1.1. At 95% confidence, an upper limit of 0.59 is set to the level of B-mode polarization with the same shape and normalization as the E-mode spectrum. The TE correlation of the temperature and E-mode polarization is detected at 95% confidence, and also found to be consistent with predictions. These results provide strong validation of the underlying theoretical framework for the origin of CMB anisotropy and lend confidence to the values of the cosmological parameters that have been derived from CMB measurements.Comment: 20 pages, 6 figure

Dopamine, affordance and active inference.

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level