Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function.

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We provide two biologically plausible implementations for this reset that propose functional roles in stabilizing consolidation for core elements of the cerebellar circuit.

Oculomotor plant and neural dynamics suggest gaze control requires integration on distributed timescales.

A fundamental principle of biological motor control is that the neural commands driving movement must conform to the response properties of the motor plants they control. In the oculomotor system, characterizations of oculomotor plant dynamics traditionally supported models in which the plant responds to neural drive to extraocular muscles on exclusively short, subsecond timescales. These models predict that the stabilization of gaze during fixations between saccades requires neural drive that approximates eye position on longer timescales and is generated through the temporal integration of brief eye velocity-encoding signals that cause saccades. However, recent measurements of oculomotor plant behaviour have revealed responses on longer timescales. Furthermore, measurements of firing patterns in the oculomotor integrator have revealed a more complex encoding of eye movement dynamics. Yet, the link between these observations has remained unclear. Here we use measurements from the larval zebrafish to link dynamics in the oculomotor plant to dynamics in the neural integrator. The oculomotor plant in both anaesthetized and awake larval zebrafish was characterized by a broad distribution of response timescales, including those much longer than 1 s. Analysis of the firing patterns of oculomotor integrator neurons, which exhibited a broadly distributed range of decay time constants, demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with distributed response timescales. This work suggests that leaky integration on multiple, distributed timescales by the oculomotor integrator reflects an inverse model for generating oculomotor commands, and that multi-timescale dynamics may be a general feature of motor circuitry. KEY POINTS: Recent observations of oculomotor plant response properties and neural activity across the oculomotor system have called into question classical formulations of both the oculomotor plant and the oculomotor integrator. Here we use measurements from new and published experiments in the larval zebrafish together with modelling to reconcile recent oculomotor plant observations with oculomotor integrator function. We developed computational techniques to characterize oculomotor plant responses over several seconds in awake animals, demonstrating that long timescale responses seen in anaesthetized animals extend to the awake state. Analysis of firing patterns of oculomotor integrator neurons demonstrates the sufficiency of this activity for stabilizing gaze given an oculomotor plant with multiple, distributed response timescales. Our results support a formulation of gaze stabilization by the oculomotor system in which commands for stabilizing gaze are generated through integration on multiple, distributed timescales.

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation.

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

Chemistry of Simple Organic Peroxy Radicals under Atmospheric through Combustion Conditions: Role of Temperature, Pressure, and NOx Level.

Organic peroxy radicals (RO2) are key intermediates in the oxidation of organic compounds in both combustion systems and the atmosphere. While many studies have focused on reactions of RO2 in specific applications, spanning a relatively limited range of reaction conditions, the generalized behavior of RO2 radicals across the full range of reaction conditions (temperatures, pressures, and NO levels) has, to our knowledge, never been explored. In this work, two simple model systems, n-propyl peroxy radical and γ-isobutanol peroxy radical, are used to evaluate RO2 fate using pressure-dependent kinetics. The fate of these radicals was modeled based on literature data over 250-1250 K, 0.01-100 bar, and 1 ppt to 100 ppm of NO, which spans the typical range of atmospheric and combustion conditions. Covering this entire range provides a broad overview of the reactivity of these species under both atmospheric and combustion conditions, as well as under conditions intermediate to the two. A particular focus is on the importance of reactions that were traditionally considered to occur in only one of the two sets of conditions: RO2 unimolecular isomerization reactions (long known to occur in combustion systems but only recently appreciated in atmospheric systems) and RO2 bimolecular reactions of RO2 with NO (thought to occur mainly in atmospheric systems and rarely considered in combustion chemistry).

Pressure-dependent kinetics of peroxy radicals formed in isobutanol combustion.

Bio-derived isobutanol has been approved as a gasoline additive in the US, but our understanding of its combustion chemistry still has significant uncertainties. Detailed quantum calculations could improve model accuracy leading to better estimation of isobutanol's combustion properties and its environmental impacts. This work examines 47 molecules and 38 reactions involved in the first oxygen addition to isobutanol's three alkyl radicals located α, ß, and γ to the hydroxide. Quantum calculations are mostly done at CCSD(T)-F12/cc-pVTZ-F12//B3LYP/CBSB7, with 1-D hindered rotor corrections obtained at B3LYP/6-31G(d). The resulting potential energy surfaces are the most comprehensive isobutanol peroxy networks published to date. Canonical transition state theory and a 1-D microcanonical master equation are used to derive high-pressure-limit and pressure-dependent rate coefficients, respectively. At all conditions studied, the recombination of γ-isobutanol radical with O2 forms HO2 + isobutanal. The recombination of ß-isobutanol radical with O2 forms a stabilized hydroperoxy alkyl radical below 400 K, water + an alkoxy radical at higher temperatures, and HO2 + an alkene above 1200 K. The recombination of ß-isobutanol radical with O2 results in a mixture of products between 700-1100 K, forming acetone + formaldehyde + OH at lower temperatures and forming HO2 + alkenes at higher temperatures. The barrier heights, high-pressure-limit rates, and pressure-dependent kinetics generally agree with the results from previous quantum chemistry calculations. Six reaction rates in this work deviate by over three orders of magnitude from kinetics in detailed models of isobutanol combustion, suggesting the rates calculated here can help improve modeling of isobutanol combustion and its environmental fate.

Modeling of aromatics formation in fuel-rich methane oxy-combustion with an automatically generated pressure-dependent mechanism.

With the rise in production of natural gas, there is increased interest in homogeneous partial oxidation (POX) to convert methane to syngas (CO + H2), ethene (C2H4) and acetylene (C2H2). In POX, polycyclic aromatic hydrocarbons (PAH) are important undesired byproducts. To improve the productivity of such POX processes, it is necessary to have an accurate chemical mechanism for methane-rich combustion including PAH. A new mechanism was created to capture the chemistry from C0 to C12, incorporating new information derived from recent quantum chemistry calculations, with help from the Reaction Mechanism Generator (RMG) software. For better estimation of kinetics and thermochemistry of aromatic species, including reactions through carbene intermediates, new reaction families and additional data from quantum chemistry calculations were added to RMG-database. Many of the rate coefficients in the new mechanism are significantly pressure-dependent at POX conditions. The new mechanism was validated against electron-ionization molecular beam mass spectrometry (EI-MBMS) data from a high-temperature flow reactor reported by Kohler et al. In this work quantification of additional species from those experiments is reported including phenylacetylene (C8H6), indene (C9H8), naphthalene (C10H8) and acenaphthylene (C12H8) at many temperatures for several feed compositions. Comparison of the experimental species concentration data and the new kinetic model is satisfactory; the new mechanism is generally more accurate than other published mechanisms. Moreover, because the new mechanism is composed of elementary chemical reaction steps instead of global fitted kinetics, pathway analysis of species could be investigated step-by-step to understand PAH formation. For methane-rich combustion, the most important routes to key aromatics are propargyl recombination for benzene, reactions of the propargyl radical with the phenyl radical for indene, and hydrogen abstraction acetylene addition (HACA) for naphthalene.

Correct Symmetry Treatment for X + X Reactions Prevents Large Errors in Predicted Isotope Enrichment.

Confusion over how to account for symmetry numbers when reactants are identical can cause significant errors in isotopic studies. An extraneous factor of 2 in the reaction symmetry number, as proposed in the literature, violates reaction equilibrium and causes huge enrichment errors in isotopic analysis. In actuality, no extra symmetry factor is needed with identical reactants.

Synchronization of Electrically Coupled Resonate-and-Fire Neurons.

Electrical coupling between neurons is broadly present across brain areas and is typically assumed to synchronize network activity. However, intrinsic properties of the coupled cells can complicate this simple picture. Many cell types with electrical coupling show a diversity of post-spike subthreshold fluctuations, often linked to subthreshold resonance, which are transmitted through electrical synapses in addition to action potentials. Using the theory of weakly coupled oscillators, we explore the effect of both subthreshold and spike-mediated coupling on synchrony in small networks of electrically coupled resonate-and-fire neurons, a hybrid neuron model with damped subthreshold oscillations and a range of post-spike voltage dynamics. We calculate the phase response curve using an extension of the adjoint method that accounts for the discontinuous post-spike reset rule. We find that both spikes and subthreshold fluctuations can jointly promote synchronization. The subthreshold contribution is strongest when the voltage exhibits a significant post-spike elevation in voltage, or plateau potential. Additionally, we show that the geometry of trajectories approaching the spiking threshold causes a "reset-induced shear" effect that can oppose synchrony in the presence of network asymmetry, despite having no effect on the phase-locking of symmetrically coupled pairs.

Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.

A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory.

Encapsulation of enzyme via one-step template-free formation of stable organic-inorganic capsules: A simple and efficient method for immobilizing enzyme with high activity and recyclability.

Enzyme encapsulation is a simple, gentle, and general method for immobilizing enzyme, but it often suffers from one or more problems regarding enzyme loading efficiency, enzyme leakage, mechanical stability, and recyclability. Here we report a novel, simple, and efficient method for enzyme encapsulation to overcome these problems by forming stable organic-inorganic hybrid capsules. A new, facile, one-step, and template-free synthesis of organic-inorganic capsules in aqueous phase were developed based on PEI-induced simultaneous interfacial self-assembly of Fmoc-FF and polycondensation of silicate. Addition of an aqueous solution of Fmoc-FF and sodium silicate into an aqueous solution of PEI gave a new class of organic-inorganic hybrid capsules (FPSi) with multi-layered structure in high yield. The capsules are mechanically stable due to the incorporation of inorganic silica. Direct encapsulation of enzyme such as epoxide hydrolase SpEH and BSA along with the formation of the organic-inorganic capsules gave high yield of enzyme-containing capsules (∼1.2 mm in diameter), >90% enzyme loading efficiency, high specific enzyme loading (158 mg protein g(-1) carrier), and low enzyme leakage (<3% after 48 h incubation). FPSi-SpEH capsules catalyzed the hydrolysis of cyclohexene oxide to give (1R, 2R)-cyclohexane-1,2-diol in high yield and concentration, with high specific activity (6.94 U mg(-1) protein) and the same high enantioselectivity as the free enzyme. The immobilized SpEH demonstrated also excellent operational stability and recyclability: retaining 87% productivity after 20 cycles with a total reaction time of 80 h. The new enzyme encapsulation method is efficient, practical, and also better than other reported encapsulation methods.

NMDA and GABAB (KIR) conductances: the "perfect couple" for bistability.

Networks that produce persistent firing in response to novel input patterns are thought to be important in working memory and other information storage functions. One possible mechanism for maintaining persistent firing is dendritic voltage bistability in which the depolarized state depends on the voltage dependence of the NMDA conductance at recurrent synapses. In previous models, the hyperpolarized state is dependent on voltage-independent conductances, including GABA(A). The interplay of these conductances leads to bistability, but its robustness is limited by the fact that the conductance ratio must be within a narrow range. The GABA(B) component of inhibitory transmission was not considered in previous analyses. Here, we show that the voltage dependence of the inwardly rectifying potassium (KIR) conductance activated by GABA(B) receptors adds substantial robustness to network simulations of bistability and the persistent firing that it underlies. The hyperpolarized state is robust because, at hyperpolarized potentials, the GABA(B)/KIR conductance is high and the NMDA conductance is low; the depolarized state is robust because, at depolarized potentials, the NMDA conductance is high and the GABA(B)/KIR conductance is low. Our results suggest that this complementary voltage dependence of GABA(B)/KIR and NMDA conductances makes them a "perfect couple" for producing voltage bistability.

Nitrosamine formation in amine scrubbing at desorber temperatures.

Amine scrubbing is a thermodynamically efficient and industrially proven method for carbon capture, but amine solvents can nitrosate in the desorber, forming potentially carcinogenic nitrosamines. The kinetics of reactions involving nitrite and monoethanolamine (MEA), diethanolamine (DEA), methylethanolamine (MMEA), and methyldiethanolamine (MDEA) were determined under desorber conditions. The nitrosations of MEA, DEA, and MMEA are first order in nitrite, carbamate species, and hydronium ion. Nitrosation of MDEA, a tertiary amine, is not catalyzed by the addition of CO2 since it cannot form a stable carbamate. Concentrated and CO2 loaded MEA was blended with low concentrations of N-(2-hydroxyethyl) glycine (HeGly), hydroxyethyl-ethylenediamine (HEEDA), and DEA, secondary amines common in MEA degradation. Nitrosamine yield was proportional to the concentration of secondary amine and was a function of CO2 loading and temperature. Blends of tertiary amines with piperazine (PZ) showed n-nitrosopiperazine (MNPZ) yields close to unity, validating the slow nitrosation rates hypothesized for tertiary amines. These results provide a useful tool for estimating nitrosamine accumulation over a range of amine solvents.

Parental depression confers greater prospective depression risk to females than males in emerging adulthood.

Females are at greater risk of depression than males, a pattern arising in adolescence and continuing in adulthood. One hypothesis is that major risk factors operate more robustly for females. We tested whether parental depression history imposes greater prospective depression risk for female emerging adults in a large community sample (ages 18-19, N = 637). Utilizing linear mixed regressions to model symptom changes over 2 years, we found the predictive utility of parental depression varied by gender. Females had higher depression symptoms overall, and those with parental depression remained at high levels throughout the adulthood transition, compared to at-risk males whose elevated symptoms decreased. This effect was specific to offspring depression (versus anxiety) and was found only for parental depression (versus other disorders). Female emerging adults with a parental depression history are at increased risk for future depression symptom elevations, which may partially explain their increased risk for depressive disorders in adulthood.

Interactions between circuit architecture and plasticity in a closed-loop cerebellar system.

Determining the sites and directions of plasticity underlying changes in neural activity and behavior is critical for understanding mechanisms of learning. Identifying such plasticity from neural recording data can be challenging due to feedback pathways that impede reasoning about cause and effect. We studied interactions between feedback, neural activity, and plasticity in the context of a closed-loop motor learning task for which there is disagreement about the loci and directions of plasticity: vestibulo-ocular reflex learning. We constructed a set of circuit models that differed in the strength of their recurrent feedback, from no feedback to very strong feedback. Despite these differences, each model successfully fit a large set of neural and behavioral data. However, the patterns of plasticity predicted by the models fundamentally differed, with the direction of plasticity at a key site changing from depression to potentiation as feedback strength increased. Guided by our analysis, we suggest how such models can be experimentally disambiguated. Our results address a long-standing debate regarding cerebellum-dependent motor learning, suggesting a reconciliation in which learning-related changes in the strength of synaptic inputs to Purkinje cells are compatible with seemingly oppositely directed changes in Purkinje cell spiking activity. More broadly, these results demonstrate how changes in neural activity over learning can appear to contradict the sign of the underlying plasticity when either internal feedback or feedback through the environment is present.

Synaptic weight dynamics underlying memory consolidation: implications for learning rules, circuit organization, and circuit function.

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit. Significance Statement: How are memories transformed over time? We propose a simple organizing principle for how long term memories are moved from an initial to a final site of storage. We show that successful transfer occurs when the late site of memory storage is endowed with synaptic plasticity rules that stably accumulate changes in activity occurring at the early site of memory storage. We instantiate this principle in a simple computational model that is representative of brain circuits underlying a variety of behaviors. The model suggests how a neural circuit can store new memories while preserving core features of older ones, and suggests novel roles for core elements of the cerebellar circuit.

A Lyapunov theory demonstrating a fundamental limit on the speed of systems consolidation.

The nervous system reorganizes memories from an early site to a late site, a commonly observed feature of learning and memory systems known as systems consolidation. Previous work has suggested learning rules by which consolidation may occur. Here, we provide conditions under which such rules are guaranteed to lead to stable convergence of learning and consolidation. We use the theory of Lyapunov functions, which enforces stability by requiring learning rules to decrease an energy-like (Lyapunov) function. We present the theory in the context of a simple circuit architecture motivated by classic models of learning in systems consolidation mediated by the cerebellum. Stability is only guaranteed if the learning rate in the late stage is not faster than the learning rate in the early stage. Further, the slower the learning rate at the late stage, the larger the perturbation the system can tolerate with a guarantee of stability. We provide intuition for this result by mapping the consolidation model to a damped driven oscillator system, and showing that the ratio of early-to late-stage learning rates in the consolidation model can be directly identified with the (square of the) oscillator's damping ratio. This work suggests the power of the Lyapunov approach to provide constraints on nervous system function.

Context-dependence of deterministic and nondeterministic contributions to closed-loop steering control.

In natural circumstances, sensory systems operate in a closed loop with motor output, whereby actions shape subsequent sensory experiences. A prime example of this is the sensorimotor processing required to align one's direction of travel, or heading, with one's goal, a behavior we refer to as steering. In steering, motor outputs work to eliminate errors between the direction of heading and the goal, modifying subsequent errors in the process. The closed-loop nature of the behavior makes it challenging to determine how deterministic and nondeterministic processes contribute to behavior. We overcome this by applying a nonparametric, linear kernel-based analysis to behavioral data of monkeys steering through a virtual environment in two experimental contexts. In a given context, the results were consistent with previous work that described the transformation as a second-order linear system. Classically, the parameters of such second-order models are associated with physical properties of the limb such as viscosity and stiffness that are commonly assumed to be approximately constant. By contrast, we found that the fit kernels differed strongly across tasks in these and other parameters, suggesting context-dependent changes in neural and biomechanical processes. We additionally fit residuals to a simple noise model and found that the form of the noise was highly conserved across both contexts and animals. Strikingly, the fitted noise also closely matched that found previously in a human steering task. Altogether, this work presents a kernel-based analysis that characterizes the context-dependence of deterministic and non-deterministic components of a closed-loop sensorimotor task.

Kinetics of N-nitrosopiperazine formation from nitrite and piperazine in CO2 capture.

Piperazine (PZ) is an efficient amine for carbon capture systems, but it can form N-nitrosopiperazine (MNPZ), a carcinogen, from nitrogen oxides (NO(x)) in flue gas from coal or natural gas combustion. The reaction of nitrite with PZ was studied in 0.1 to 5 mol/dm(3) PZ with 0.001 to 0.8 mol CO2/mol PZ at 50 to 135 °C. The reaction forming MNPZ is first order in nitrite, piperazine carbamate species, and hydronium ion. The activation energy is 84 ± 2 kJ/mol with a rate constant of 8.5 × 10(3) ± 1.4 × 10(3) dm(6) mol(-2) s(-1) at 100 °C. The proposed mechanism involves protonation of the carbamate species, nucleophilic attack of the carbamic acid, and formation of bicarbonate and MNPZ. These kinetics and mechanism will be useful in identifying inhibitors and other strategies to reduce nitrosamine accumulation in CO2 capture by scrubbing with PZ or other amines.

An oscillatory mechanism for multi-level storage in short-term memory.

Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here we demonstrate a simple mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity that encodes information not only in the spatial pattern of activity, but also in the amplitude of activity. This is accomplished through a phase-locking phenomenon that permits many different amplitudes of persistent activity to be stored without requiring exact tuning of model parameters. Altogether, this work proposes a class of models for the storage of information in working memory, a potential role for brain oscillations, and a dynamical mechanism for maintaining multi-stable neural representations.