Neural Networks With Motivation.

Animals rely on internal motivational states to make decisions. The role of motivational salience in decision making is in early stages of mathematical understanding. Here, we propose a reinforcement learning framework that relies on neural networks to learn optimal ongoing behavior for dynamically changing motivation values. First, we show that neural networks implementing Q-learning with motivational salience can navigate in environment with dynamic rewards without adjustments in synaptic strengths when the needs of an agent shift. In this setting, our networks may display elements of addictive behaviors. Second, we use a similar framework in hierarchical manager-agent system to implement a reinforcement learning algorithm with motivation that both infers motivational states and behaves. Finally, we show that, when trained in the Pavlovian conditioning setting, the responses of the neurons in our model resemble previously published neuronal recordings in the ventral pallidum, a basal ganglia structure involved in motivated behaviors. We conclude that motivation allows Q-learning networks to quickly adapt their behavior to conditions when expected reward is modulated by agent's dynamic needs. Our approach addresses the algorithmic rationale of motivation and makes a step toward better interpretability of behavioral data via inference of motivational dynamics in the brain

Spatiotemporal 3D image registration for mesoscale studies of brain development

Comparison of brain samples representing different developmental stages often necessitates registering the samples to common coordinates. Although the available software tools are successful in registering 3D images of adult brains, registration of perinatal brains remains challenging due to rapid growth-dependent morphological changes and variations in developmental pace between animals. To address these challenges, we introduce CORGI (Customizable Object Registration for Groups of Images), an algorithm for the registration of perinatal brains. First, we optimized image preprocessing to increase the algorithm's sensitivity to mismatches in registered images. Second, we developed an attention-gated simulated annealing procedure capable of focusing on the differences between perinatal brains. Third, we applied classical multidimensional scaling (CMDS) to align ("synchronize") brain samples in time, accounting for individual development paces. We tested CORGI on 28 samples of whole-mounted perinatal mouse brains (P0-P9) and compared its accuracy with other registration algorithms. Our algorithm offers a runtime of several minutes per brain on a laptop and automates such brain registration tasks as mapping brain data to atlases, comparing experimental groups, and monitoring brain development dynamics

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Monitoring the ADP/ATP ratio via induced circularly‐polarised europium luminescence

A series of three europium complexes is reported bearing picolyl amine moieties with different substituents, that possess differing binding affinities towards Zn2+ and three nucleotides ‐ AMP, ADP and ATP. A large increase of the total emission intensity was observed upon binding Zn2+, followed by further signal amplification upon addition of nucleotides. The resulting adducts possess strong induced circularly polarised emission, with ADP and ATP signals being of opposite sign. Model DFT geometries of the adducts suggest the Δ diastereoisomer is preferred for ATP and the Λ isomer for ADP/AMP. Such a change in sign allows the ADP:/ATP (or AMP/ATP) ratio to be assessed by monitoring changes in the emission dissymmetry factor, gem

Chiral probes for α1-AGP reporting by species-specific induced circularly polarised luminescence

Luminescence spectroscopy has been used to monitor the selective and reversible binding of pH sensitive, macrocyclic lanthanide complexes, [LnL1], to the serum protein α1-AGP, whose concentration can vary significantly in response to inflammatory processes. On binding α1-AGP, a very strong induced circularly-polarised europium luminescence signal was observed that was of opposite sign for human and bovine variants of α1-AGP – reflecting the differences in the chiral environment of their drug-binding pockets. A mixture of [EuL1] and [TbL1] complexes allowed the ratiometric monitoring of α1-AGP levels in serum. Moreover, competitive displacement of [EuL1] from the protein by certain prescription drugs could be monitored, allowing the determination of drug binding constants. Reversible binding of the sulphonamide arm as a function of pH, led to a change of the coordination environment around the lanthanide ion, from twisted square antiprism (TSAP) to a square antiprismatic geometry (SAP), signalled by emission spectral changes and verified by detailed computations and the fitting of NMR pseudocontact shift data in the sulphonamide bound TSAP structure for the Dy and Eu examples. Such analyses allowed a full definition of the magnetic susceptibility tensor for [DyL1]

Selective signalling of glyphosate in water using europium luminescence

A series of four emissive europium complexes has been evaluated for the binding of glyphosate in various aqueous media, including river water and grain extracts. Binding selectivity toward inorganic phosphate and bicarbonate was enhanced by measuring samples at pH 5.9, above the pKa of glyphosate itself. The highest affinity was shown with [Eu·L1], which creates an exocyclic tripicolylamine moiety when one pyridine group dissociates from Eu. Glyphosate was bound selectively over dihydrogenphosphate, glycinate, aminomethylphosphonate and the related herbicide glufosinate. The complex was used to measure glyphosate over the range 5 to 50 μM, in river water and grain extracts