Quantum optics meets quantum many-body theory:Coupled cluster studies of the Rabi Hamiltonian

The Rabi Hamiltonian, which describes the interaction of a single mode of electromagnetic radiation with a two-level system, is one of the fundamental models of quantum optics. It is also of wider interest as it provides a. generic model for the interaction of bosons and fermions. To allow for a systematic analysis of the strong-coupling behaviour, we have applied the coupled cluster method (CCM) to the Rabi Hamiltonian to calculate its spectrum. We find strong evidence for the existence of a somewhat subtle quantum phase transition

Four theorems on the psychometric function

In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by [Formula: see text], where [Formula: see text] is the β of the Weibull function that fits best to the cumulative noise distribution, and [Formula: see text] depends on the transducer. We derive general expressions for [Formula: see text] and [Formula: see text], from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when [Formula: see text], [Formula: see text]. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian

Toxoplasmosis-associated IRIS involving the CNS: a case report with longitudinal analysis of T cell subsets

Background: HIV-infected patients may present an unforeseen clinical worsening after initiating antiretroviral therapy known as immune reconstitution inflammatory syndrome (IRIS). This syndrome is characterized by a heightened inflammatory response toward infectious or non-infectious triggers, and it may affect different organs. Diagnosis of IRIS involving the central nervous system (CNS-IRIS) is challenging due to heterogeneous manifestations, absence of biomarkers to identify this condition, risk of long-term sequelae and high mortality. Hence, a deeper knowledge of CNS-IRIS pathogenesis is needed. Case presentation: A 37-year-old man was diagnosed with AIDS and cerebral toxoplasmosis. Anti-toxoplasma treatment was initiated immediately, followed by active antiretroviral therapy (HAART) 1 month later. At 2 months of HAART, he presented with progressive hyposensitivity of the right lower limb associated with brain and dorsal spinal cord lesions, compatible with paradoxical toxoplasmosis-associated CNS-IRIS, a condition with very few reported cases. A stereotactic biopsy was planned but was postponed based on its inherent risks. Patient showed clinical improvement with no requirement of corticosteroid therapy. Routine laboratorial analysis was complemented with longitudinal evaluation of blood T cell subsets at 0, 1, 2, 3 and 6 months upon HAART initiation. A control group composed by 9 HIV-infected patients from the same hospital but with no IRIS was analysed for comparison. The CNS-IRIS patient showed lower percentage of memory CD4(+) T cells and higher percentage of activated CD4(+) T cells at HAART initiation. The percentage of memory CD4(+) T cells drastically increased at 1 month after HAART initiation and became higher in comparison to the control group until clinical recovery onset; the percentage of memory CD8(+) T cells was consistently lower throughout follow-up. Interestingly, the percentage of regulatory T cells (Treg) on the CNS-IRIS patient reached a minimum around 1 month before symptoms onset. Conclusion: Although both stereotactic biopsies and steroid therapy might be of use in CNS-IRIS cases and should be considered for these patients, they might be unnecessary to achieve clinical improvement as shown in this case. Immunological characterization of more CNS-IRIS cases is essential to shed some light on the pathogenesis of this condition.Portuguese Foundation for Science and Technology (FCT; PIC/IC/83313/2007) and co-financed by the Portuguese North Regional Operational Program (ON.2 - O Novo Norte) under the National Strategic Reference Framework (QREN) through the European Regional Development Fund (FEDER). A FCT fellowship was attributed to RRS (PD/BD/106047/2015; Inter-University Doctoral Program in Ageing and Chronic Disease) and to CN [SFRH/BPD/65380/2009; Programa Operacional Potencial Humano (POPH) through the Fundo Social Europeu (FSE)]info:eu-repo/semantics/publishedVersio

Action planning and the timescale of evidence accumulation

Perceptual decisions are based on the temporal integration of sensory evidence for different states of the outside world. The timescale of this integration process varies widely across behavioral contexts and individuals, and it is diagnostic for the underlying neural mechanisms. In many situations, the decision-maker knows the required mapping between perceptual evidence and motor response (henceforth termed “sensory-motor contingency”) before decision formation. Here, the integrated evidence can be directly translated into a motor plan and, indeed, neural signatures of the integration process are evident as build-up activity in premotor brain regions. In other situations, however, the sensory-motor contingencies are unknown at the time of decision formation. We used behavioral psychophysics and computational modeling to test if knowledge about sensory-motor contingencies affects the timescale of perceptual evidence integration. We asked human observers to perform the same motion discrimination task, with or without trial-to-trial variations of the mapping between perceptual choice and motor response. When the mapping varied, it was either instructed before or after the stimulus presentation. We quantified the timescale of evidence integration under these different sensory-motor mapping conditions by means of two approaches. First, we analyzed subjects’ discrimination threshold as a function of stimulus duration. Second, we fitted a dynamical decision-making model to subjects’ choice behavior. The results from both approaches indicated that observers (i) integrated motion information for several hundred ms, (ii) used a shorter than optimal integration timescale, and (iii) used the same integration timescale under all sensory-motor mappings. We conclude that the mechanisms limiting the timescale of perceptual decisions are largely independent from long-term learning (under fixed mapping) or rapid acquisition (under variable mapping) of sensory-motor contingencies. This conclusion has implications for neurophysiological and neuroimaging studies of perceptual decision-making

A neural circuit model of decision uncertainty and change-of-mind

Decision-making is often accompanied by a degree of confidence on whether a choice is correct. Decision uncertainty, or lack in confidence, may lead to change-of-mind. Studies have identified the behavioural characteristics associated with decision confidence or change-of-mind, and their neural correlates. Although several theoretical accounts have been proposed, there is no neural model that can compute decision uncertainty and explain its effects on change-of-mind. We propose a neuronal circuit model that computes decision uncertainty while accounting for a variety of behavioural and neural data of decision confidence and change-of-mind, including testable model predictions. Our theoretical analysis suggests that change-of-mind occurs due to the presence of a transient uncertainty-induced choice-neutral stable steady state and noisy fluctuation within the neuronal network. Our distributed network model indicates that the neural basis of change-of-mind is more distinctively identified in motor-based neurons. Overall, our model provides a framework that unifies decision confidence and change-of-mind