Tris+/Na+ permeability ratios of nicotinic acetylcholine receptors are reduced by mutations near the intracellular end of the M2 region

Tris+/Na+ permeability ratios were measured from shifts in the biionic reversal potentials of the macroscopic ACh-induced currents for 3 wild- type (WT), 1 hybrid, 2 subunit-deficient, and 25 mutant nicotinic receptors expressed in Xenopus oocytes. At two positions near the putative intracellular end of M2, 2' (alpha Thr244, beta Gly255, gamma Thr253, delta Ser258) and -1', point mutations reduced the relative Tris+ permeability of the mouse receptor as much as threefold. Comparable mutations at several other positions had no effects on relative Tris+ permeability. Mutations in delta had a greater effect on relative Tris+ permeability than did comparable mutations in gamma; omission of the mouse delta subunit (delta 0 receptor) or replacement of mouse delta with Xenopus delta dramatically reduced relative Tris+ permeability. The WT mouse muscle receptor (alpha beta gamma delta) had a higher relative permeability to Tris+ than the wild-type Torpedo receptor. Analysis of the data show that (a) changes in the Tris+/Na+ permeability ratio produced by mutations correlate better with the hydrophobicity of the amino acid residues in M2 than with their volume; and (b) the mole-fraction dependence of the reversal potential in mixed Na+/Tris+ solutions is approximately consistent with the Goldman- Hodgkin-Katz voltage equation. The results suggest that the main ion selectivity filter for large monovalent cations in the ACh receptor channel is the region delimited by positions -1' and 2' near the intracellular end of the M2 helix

Modeling Boundedly Rational Agents with Latent Inference Budgets

We study the problem of modeling a population of agents pursuing unknown goals subject to unknown computational constraints. In standard models of bounded rationality, sub-optimal decision-making is simulated by adding homoscedastic noise to optimal decisions rather than explicitly simulating constrained inference. In this work, we introduce a latent inference budget model (L-IBM) that models agents' computational constraints explicitly, via a latent variable (inferred jointly with a model of agents' goals) that controls the runtime of an iterative inference algorithm. L-IBMs make it possible to learn agent models using data from diverse populations of suboptimal actors. In three modeling tasks -- inferring navigation goals from routes, inferring communicative intents from human utterances, and predicting next moves in human chess games -- we show that L-IBMs match or outperform Boltzmann models of decision-making under uncertainty. Inferred inference budgets are themselves meaningful, efficient to compute, and correlated with measures of player skill, partner skill and task difficulty

Generating Pragmatic Examples to Train Neural Program Synthesizers

Programming-by-example is the task of synthesizing a program that is consistent with a set of user-provided input-output examples. As examples are often an under-specification of one's intent, a good synthesizer must choose the intended program from the many that are consistent with the given set of examples. Prior work frames program synthesis as a cooperative game between a listener (that synthesizes programs) and a speaker (a user choosing examples), and shows that models of computational pragmatic inference are effective in choosing the user intended programs. However, these models require counterfactual reasoning over a large set of programs and examples, which is infeasible in realistic program spaces. In this paper, we propose a novel way to amortize this search with neural networks. We sample pairs of programs and examples via self-play between listener and speaker models, and use pragmatic inference to choose informative training examples from this sample.We then use the informative dataset to train models to improve the synthesizer's ability to disambiguate user-provided examples without human supervision. We validate our method on the challenging task of synthesizing regular expressions from example strings, and find that our method (1) outperforms models trained without choosing pragmatic examples by 23% (a 51% relative increase) (2) matches the performance of supervised learning on a dataset of pragmatic examples provided by humans, despite using no human data in training

Diversity of vertebrate nicotinic acetylcholine receptors

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Acute stress impairs reward learning in men

Acute stress is ubiquitous in everyday life, but the extent to which acute stress affects how people learn from the outcomes of their choices is still poorly understood. Here, we investigate how acute stress impacts reward and punishment learning in men using a reinforcement-learning task. Sixty-two male participants performed the task whilst under stress and control conditions. We observed that acute stress impaired participants' choice performance towards monetary gains, but not losses. To unravel the mechanism(s) underlying such impairment, we fitted a reinforcement-learning model to participants' trial-by-trial choices. Computational modeling indicated that under acute stress participants learned more slowly from positive prediction errors - when the outcomes were better than expected - consistent with stress-induced dopamine disruptions. Such mechanistic understanding of how acute stress impairs reward learning is particularly important given the pervasiveness of stress in our daily life and the impact that stress can have on our wellbeing and mental health.ortuguese Foundation for Science and Technology (FCT) to A. Seara-Cardoso [PTDC/MHC-PCN/2296/2014, co-financed by FEDER through COMPETE2020 under the PT2020 Partnership Agreement (POCI-01-0145-FEDER-016747)] and to A. Mesquita (IF/00750/2015). J. Carvalheiro was supported by a FCT PhD fellowship (PD/BD/128467/2017). This study was conducted at the Psychology Research Centre (PSI/01662), School of Psychology, University of Minho, supported by FCT and the Portuguese Ministry of Science, Technology and Higher Education (UID/PSI/01662/2019), through national funds (PIDDAC

An acetylcholine receptor lacking both γ and ε subunits mediates transmission in zebrafish slow muscle synapses

Fast and slow skeletal muscle types in larval zebrafish can be distinguished by a fivefold difference in the time course of their synaptic decay. Single-channel recordings indicate that this difference is conferred through kinetically distinct nicotinic acetylcholine receptor (AChR) isoforms. The underlying basis for this distinction was explored by cloning zebrafish muscle AChR subunit cDNAs and expressing them in Xenopus laevis oocytes. Measurements of single-channel conductance and mean open burst duration assigned α2βδε to fast muscle synaptic current. Contrary to expectations, receptors composed of only αβδ subunits (presumed to be α2βδ2 receptors) recapitulated the kinetics and conductance of slow muscle single-channel currents. Additional evidence in support of γ/ε-less receptors as mediators of slow muscle synapses was reflected in the inward current rectification of heterologously expressed α2βδ2 receptors, a property normally associated with neuronal-type nicotinic receptors. Similar rectification was reflected in both single-channel and synaptic currents in slow muscle, distinguishing them from fast muscle. The final evidence for α2βδ2 receptors in slow muscle was provided by our ability to convert fast muscle synaptic currents to those of slow muscle by knocking down ε subunit expression in vivo. Thus, for the first time, muscle synaptic function can be ascribed to a receptor isoform that is composed of only three different subunits. The unique functional features offered by the α2βδ2 receptor likely play a central role in mediating the persistent contractions characteristic to this muscle type

Molecular and ontogenic analysis of the mammalian GABA_A receptor

γ-aminobutyric acid is the major inhibitory neurotransmitter in the adult mammalian central nervous system (CNS) and may also play a neurotrophic role during CNS development. Diversification of GABAA receptor mediated responses are in part a result ofvariation in subunit composition in the receptor complex. This variation arises both from the number of different subtypes of GABAA receptor subunits (α1-6, β1-4, γ1-3, δ1, ρ1-3, ε, ρ), as well as from post-transcriptional processes such as RNA splicing. In this thesis, I have investigated the developmental onset of GABAA receptor gene expression and the distribution and temporal expression of GABAA receptor subunit mRNAs and 12 splice variants within the developing and adult murine CNS.Preliminary studies using S 1 nuclease protection analysis demonstrated that α1, β3 and γ2 were the predominant subtypes of GABAA receptor subunits expressed at embryonic day 14 and in the adult murine CNS. In situ hybridisation analysis demonstrated overlapping but distinct spatial and temporal patterns of GABAA subunit mRNA expression during postnatal development and in the adult murine CNS. Analysis of γ2 mRNA splice variants demonstrated that the γ2S transcript is the predominant γ2 mRNA expressed during latter stages of embryo genesis, while the γ2L transcript is the predominant γ2 isoform present inthe adult CNS.Since there is a 29 to 47 percent amino acid identity among the various GABAA receptor subunits, I have also demonstrated through site-directed mutagenesis studies, that changes in a conserved amino acid in the cysteine loop of the bovine a 1 GABAA receptor subunit resulted in a loss of agonist and antagonist binding (DI49N), while a change in a conserved amino acid in the M1 transmembrane domain of the bovine α1 GABAA receptor subunit resulted in loss of agonist binding and reduction in the Bmax and Kd for antagonist binding (P243A). 'These results are in contrast to the effect of identical mutations in the bovine β1 subunit and suggest that if the pentameric GABAA receptor assembly is composed of (α1)2(β1)1(γ2)2, then changes in highly conserved amino acids in the α1 receptor subunit would have a greater distortion on the structure of the receptor complex