Measurement of empathy toward rape victims and rapists

The purpose of the present study was the construction of the Rape Empathy Scale (RES), designed to measure subjects' empathy toward the rape victim and the rapist in a heterosexual rape situation. The results of psychometric analyses of reliability for both a student and juror sample are presented, in addition to evidence of cross-validation on separate student and juror samples. Significant differences between male and female subjects' RES scores were found, as well as differences between scores of women who had experienced a rape situation (rape victims and rape resisters) and women with no previous exposure to rape. RES scores were predictive of both students' and jurors' ratings of defendant guilt, as well as their recommended sentences for the defendant and their attributions of responsibility for the crime. Furthermore, subjects' RES scores were predictive of their social perceptions of the rape victim and defendant, and male jurors' RES scores were negatively correlated with their reported desire to rape a woman. The results are discussed in relation to the low conviction rate for sexual assault cases and the importance of juror selection as a vehicle for increasing the number of just convictions in rape cases.

The role of type 4 phosphodiesterases in generating microdomains of cAMP: large scale stochastic simulations

Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons.

Transient calcium and dopamine increase PKA activity and DARPP-32 phosphorylation

Reinforcement learning theorizes that strengthening of synaptic connections in medium spiny neurons of the striatum occurs when glutamatergic input (from cortex) and dopaminergic input (from substantia nigra) are received simultaneously. Subsequent to learning, medium spiny neurons with strengthened synapses are more likely to fire in response to cortical input alone. This synaptic plasticity is produced by phosphorylation of AMPA receptors, caused by phosphorylation of various signalling molecules. A key signalling molecule is the phosphoprotein DARPP-32, highly expressed in striatal medium spiny neurons. DARPP-32 is regulated by several neurotransmitters through a complex network of intracellular signalling pathways involving cAMP (increased through dopamine stimulation) and calcium (increased through glutamate stimulation). Since DARPP-32 controls several kinases and phosphatases involved in striatal synaptic plasticity, understanding the interactions between cAMP and calcium, in particular the effect of transient stimuli on DARPP-32 phosphorylation, has major implications for understanding reinforcement learning. We developed a computer model of the biochemical reaction pathways involved in the phosphorylation of DARPP-32 on Thr34 and Thr75. Ordinary differential equations describing the biochemical reactions were implemented in a single compartment model using the software XPPAUT. Reaction rate constants were obtained from the biochemical literature. The first set of simulations using sustained elevations of dopamine and calcium produced phosphorylation levels of DARPP-32 similar to that measured experimentally, thereby validating the model. The second set of simulations, using the validated model, showed that transient dopamine elevations increased the phosphorylation of Thr34 as expected, but transient calcium elevations also increased the phosphorylation of Thr34, contrary to what is believed. When transient calcium and dopamine stimuli were paired, PKA activation and Thr34 phosphorylation increased compared with dopamine alone. This result, which is robust to variation in model parameters, supports reinforcement learning theories in which activity-dependent long-term synaptic plasticity requires paired glutamate and dopamine inputs.

Reinforcement learning, based on the association of a stimulus-triggered movement with a reward, involves changes in connection strength between neurons. Memory storage occurs in the striatum, the input stage of the basal ganglia, when a stimulus or movement signal originating from the cortex and a reward signal originating from the midbrain reach the target striatal cells together. Repetitive pairing of these two signals strengthens the connection between cortical and striatal cells. The strengthening of the connections is caused by activation of biochemical signalling pathways inside the striatal cells. These intracellular signalling pathways are explored in a quantitative computational model describing the biochemical pathways important for reinforcement learning. Lindskog et al.'s study shows that when brief reward and stimuli signals are paired, a stronger response in the intracellular signalling occurs compared with the situation when each signal is given alone. This result illustrates mechanisms whereby paired stimuli, but not unpaired stimuli, can cause learning. Furthermore, the model predicts that the biochemical responses are different after brief stimulation as compared with prolonged stimulation. This result highlights the difficulties in predicting the nonlinear interactions within signalling cascades based on prolonged stimulations, which often are used in biochemical experiments.

A comparative voltage and current-clamp analysis of feedback and feedforward synaptic transmission in the striatal microcircuit in vitro

Striatal spiny projection (SP) neurons control movement initiation by integrating cortical inputs and inhibiting basal ganglia outputs. Central to this control lies a "microcircuit" that consists of a feedback pathway formed by axon collaterals between GABAergic SP neurons and a feedforward pathway from fast spiking (FS) GABAergic interneurons to SP neurons. Here, somatically evoked postsynaptic potentials (PSPs) and currents (PSCs) were compared for both pathways with dual whole cell patch recording in voltage- and current-clamp mode using cortex-striatum-substantia nigra organotypic cultures. On average, feedforward inputs were 1 ms earlier, more reliable, and about twice as large in amplitude compared with most feedback inputs. On the other hand, both pathways exhibited widely varying, partially overlapping amplitude distributions. This variability was already established for single FS neurons targeting many SP neurons. In response to precisely timed action potential bursts, feedforward and feedback inputs consistently showed short-term depression < or =50-70% in voltage-clamp, although feedback inputs also displayed strong augmentation in current-clamp in line with previous reports. The augmentation of feedback inputs was absent in gramicidin D perforated-patch recording, which also showed the natural reversal potential for both inputs to be near firing threshold. Preceding depolarizing feedback inputs during the down state did not consistently change subsequent postsynaptic action potentials. We conclude that feedback and feedforward inputs have their dominant effect during the up-state. The reversal potential close to the up-state potential, which supports shunting operation with millisecond precision and the strong synaptic depression, should enable both pathways to carry time-critical information.

Stop! border ahead: Automatic detection of subthalamic exit during deep brain stimulation surgery

BACKGROUND

Microelectrode recordings along preplanned trajectories are often used for accurate definition of the subthalamic nucleus (STN) borders during deep brain stimulation (DBS) surgery for Parkinson's disease. Usually, the demarcation of the STN borders is performed manually by a neurophysiologist. The exact detection of the borders is difficult, especially detecting the transition between the STN and the substantia nigra pars reticulata. Consequently, demarcation may be inaccurate, leading to suboptimal location of the DBS lead and inadequate clinical outcomes.

METHODS

We present machine-learning classification procedures that use microelectrode recording power spectra and allow for real-time, high-accuracy discrimination between the STN and substantia nigra pars reticulata.

RESULTS

A support vector machine procedure was tested on microelectrode recordings from 58 trajectories that included both STN and substantia nigra pars reticulata that achieved a 97.6% consistency with human expert classification (evaluated by 10-fold cross-validation). We used the same data set as a training set to find the optimal parameters for a hidden Markov model using both microelectrode recording features and trajectory history to enable real-time classification of the ventral STN border (STN exit). Seventy-three additional trajectories were used to test the reliability of the learned statistical model in identifying the exit from the STN. The hidden Markov model procedure identified the STN exit with an error of 0.04 ± 0.18 mm and detection reliability (error < 1 mm) of 94%.

CONCLUSIONS

The results indicate that robust, accurate, and automatic real-time electrophysiological detection of the ventral STN border is feasible. © 2016 International Parkinson and Movement Disorder Society.

Calcium: amplitude, duration, or location?

Calcium plays a role in long-term plasticity by triggering postsynaptic signaling pathways for both the strengthening (LTP) and weakening (LTD) of synapses. Since these are opposing processes, several hypotheses have been developed to explain how calcium can trigger LTP in some situations and LTD in others. These hypotheses fall broadly into three categories, based on the amplitude of calcium concentration, the duration of the calcium elevation, and the location of the calcium influx. Here we review the experimental evidence for and against each of these hypotheses and the recent computational models utilizing each. We argue that with new experimental techniques for the precise visualization of calcium and new computational techniques for the modeling of calcium diffusion, it is time to take a new look at the location hypothesis.

Postsynaptic signal transduction models for long-term potentiation and depression

More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.

Utility of a Wisconsin Card Sorting Test short form in persons with Alzheimer's and Parkinson's disease

The utility of administering only the first deck of 64 cards from the Wisconsin Card Sorting Test (WCST-64) in persons with Alzheimer's (AD) and Parkinson's disease (PD) was evaluated. There were 35 elderly subjects matched for gender, age, and education in each of four groups: controls, PD without dementia (PDN), PD with dementia (PDD), and AD. Additionally, the control and PDN subjects were matched for level of cognitive functioning as were the PDD and AD groups. Results revealed that demented persons performed significantly worse than nondemented subjects. The WCST-64 was also sensitive to the subtle executive deficits demonstrated by persons with PD without dementia. The findings support the use of the WCST-64 in elderly persons with AD and PD.

Subcellular location of PKA controls striatal plasticity: stochastic simulations in spiny dendrites

Dopamine release in the striatum has been implicated in various forms of reward dependent learning. Dopamine leads to production of cAMP and activation of protein kinase A (PKA), which are involved in striatal synaptic plasticity and learning. PKA and its protein targets are not diffusely located throughout the neuron, but are confined to various subcellular compartments by anchoring molecules such as A-Kinase Anchoring Proteins (AKAPs). Experiments have shown that blocking the interaction of PKA with AKAPs disrupts its subcellular location and prevents LTP in the hippocampus and striatum; however, these experiments have not revealed whether the critical function of anchoring is to locate PKA near the cAMP that activates it or near its targets, such as AMPA receptors located in the post-synaptic density. We have developed a large scale stochastic reaction-diffusion model of signaling pathways in a medium spiny projection neuron dendrite with spines, based on published biochemical measurements, to investigate this question and to evaluate whether dopamine signaling exhibits spatial specificity post-synaptically. The model was stimulated with dopamine pulses mimicking those recorded in response to reward. Simulations show that PKA colocalization with adenylate cyclase, either in the spine head or in the dendrite, leads to greater phosphorylation of DARPP-32 Thr34 and AMPA receptor GluA1 Ser845 than when PKA is anchored away from adenylate cyclase. Simulations further demonstrate that though cAMP exhibits a strong spatial gradient, diffusible DARPP-32 facilitates the spread of PKA activity, suggesting that additional inactivation mechanisms are required to produce spatial specificity of PKA activity.

The striatum is a part of the basal ganglia which plays a role in addiction and reward learning. Its importance is underscored by pathologies such as Parkinson's disease and Huntington's disease in which degeneration of the dopamine inputs to the striatum or degeneration of neurons in the striatum, respectively, produces motor dysfunction. Dopamine in the striatum activates cascades of signaling molecules, ultimately producing an activity dependent change in the strength of connections between neurons. However, the dispersive movement of signaling molecules seems incompatible with the strengthening of specific subsets of connections, which is required for formation of distinct memories. Anchoring proteins, which restrict molecules to particular compartments within the neuron, are proposed to achieve specificity. We develop a reaction-diffusion model of dopamine activated signaling pathways to explore mechanisms whereby anchoring proteins can produce specificity. We use an efficient Monte-Carlo simulator to implement the cascades of signaling molecules in a neuronal dendrite with multiple dendritic spines. Simulations demonstrate that spatial specificity requires both anchoring proteins and inactivation mechanisms that limit the diffusion of signaling molecules.

Synchronized firing of fast-spiking interneurons is critical to maintain balanced firing between direct and indirect pathway neurons of the striatum

The inhibitory circuits of the striatum are known to be critical for motor function, yet their contributions to Parkinsonian motor deficits are not clear. Altered firing in the globus pallidus suggests that striatal medium spiny neurons (MSN) of the direct (D1 MSN) and indirect pathway (D2 MSN) are imbalanced during dopamine depletion. Both MSN classes receive inhibitory input from each other and from inhibitory interneurons within the striatum, specifically the fast-spiking interneurons (FSI). To investigate the role of inhibition in maintaining striatal balance, we developed a biologically-realistic striatal network model consisting of multicompartmental neuron models: 500 D1 MSNs, 500 D2 MSNs and 49 FSIs. The D1 and D2 MSN models are differentiated based on published experiments of individual channel modulations by dopamine, with D2 MSNs being more excitable than D1 MSNs. Despite this difference in response to current injection, in the network D1 and D2 MSNs fire at similar frequencies in response to excitatory synaptic input. Simulations further reveal that inhibition from FSIs connected by gap junctions is critical to produce balanced firing. Although gap junctions produce only a small increase in synchronization between FSIs, removing these connections resulted in significant firing differences between D1 and D2 MSNs, and balanced firing was restored by providing synchronized cortical input to the FSIs. Together these findings suggest that desynchronization of FSI firing is sufficient to alter balanced firing between D1 and D2 MSNs.

Sensitivity to theta-burst timing permits LTP in dorsal striatal adult brain slice

Long-term potentiation (LTP) of excitatory afferents to the dorsal striatum likely occurs with learning to encode new skills and habits, yet corticostriatal LTP is challenging to evoke reliably in brain slice under physiological conditions. Here we test the hypothesis that stimulating striatal afferents with theta-burst timing, similar to recently reported in vivo temporal patterns corresponding to learning, evokes LTP. Recording from adult mouse brain slice extracellularly in 1 mM Mg(2+), we find LTP in dorsomedial and dorsolateral striatum is preferentially evoked by certain theta-burst patterns. In particular, we demonstrate that greater LTP is produced using moderate intraburst and high theta-range frequencies, and that pauses separating bursts of stimuli are critical for LTP induction. By altering temporal pattern alone, we illustrate the importance of burst-patterning for LTP induction and demonstrate that corticostriatal long-term depression is evoked in the same preparation. In accord with prior studies, LTP is greatest in dorsomedial striatum and relies on N-methyl-d-aspartate receptors. We also demonstrate a requirement for both Gq- and Gs/olf-coupled pathways, as well as several kinases associated with memory storage: PKC, PKA, and ERK. Our data build on previous reports of activity-directed plasticity by identifying effective values for distinct temporal parameters in variants of theta-burst LTP induction paradigms. We conclude that those variants which best match reports of striatal activity during learning behavior are most successful in evoking dorsal striatal LTP in adult brain slice without altering artificial cerebrospinal fluid. Future application of this approach will enable diverse investigations of plasticity serving striatal-based learning.

Signaling pathways involved in striatal synaptic plasticity are sensitive to temporal pattern and exhibit spatial specificity

The basal ganglia is a brain region critically involved in reinforcement learning and motor control. Synaptic plasticity in the striatum of the basal ganglia is a cellular mechanism implicated in learning and neuronal information processing. Therefore, understanding how different spatio-temporal patterns of synaptic input select for different types of plasticity is key to understanding learning mechanisms. In striatal medium spiny projection neurons (MSPN), both long term potentiation (LTP) and long term depression (LTD) require an elevation in intracellular calcium concentration; however, it is unknown how the post-synaptic neuron discriminates between different patterns of calcium influx. Using computer modeling, we investigate the hypothesis that temporal pattern of stimulation can select for either endocannabinoid production (for LTD) or protein kinase C (PKC) activation (for LTP) in striatal MSPNs. We implement a stochastic model of the post-synaptic signaling pathways in a dendrite with one or more diffusionally coupled spines. The model is validated by comparison to experiments measuring endocannabinoid-dependent depolarization induced suppression of inhibition. Using the validated model, simulations demonstrate that theta burst stimulation, which produces LTP, increases the activation of PKC as compared to 20 Hz stimulation, which produces LTD. The model prediction that PKC activation is required for theta burst LTP is confirmed experimentally. Using the ratio of PKC to endocannabinoid production as an index of plasticity direction, model simulations demonstrate that LTP exhibits spine level spatial specificity, whereas LTD is more diffuse. These results suggest that spatio-temporal control of striatal information processing employs these Gq coupled pathways.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Ryanodine receptor modulation of in vitro associative learning in Hermissenda crassicornis

Classical conditioning of the mollusc, Hermissenda crassicornis, is a model system used to study cellular correlates of associative learning. Paired presentation of light and turbulence, but not unpaired presentations, causes Hermissenda to contract its foot in response to light alone. Intracellular recordings from the type B photoreceptors of the Hermissenda eye reveal a learning specific increase of input resistance, and a reduction of voltage-dependent potassium currents, both of which depend on an elevation of intracellular calcium. Two previously demonstrated sources of calcium are influx through voltage-dependent channels, and release of calcium from intracellular stores through the IP3 receptor channel. Both modeling studies and identification of memory-related genes using RNA fingerprinting suggest that a third source of calcium, release from intracellular stores through the ryanodine receptor, may be involved in classical conditioning. We describe here an experiment suggesting that this third source of calcium is necessary for the cellular changes underlying associative memory storage. Paired presentations of a light stimulus with a turbulence stimulus resulted in a significant increase in input resistance. Unpaired presentations of light and turbulence did not produce a significant increase in input resistance. A third group of nervous systems first was incubated in dantrolene to block release of calcium through the ryanodine receptor, and then received paired training. There was no change in input resistance for this group. The effect of dantrolene on light adaptation of the photoreceptor was assessed by measuring the generator potential of a second light pulse presented some number of seconds after a first light pulse. The results show that at interpulse intervals of 5 s, 10 s and 20 s, the generator potential of the dantrolene group is significantly greater than that of the control group. These results suggest a role for the ryanodine receptor in both a cellular correlate of classical conditioning and light adaptation.

The road to ERK activation: Do neurons take alternate routes?

The ERK cascade is a central signaling pathway that regulates a wide variety of cellular processes including proliferation, differentiation, learning and memory, development, and synaptic plasticity. A wide range of inputs travel from the membrane through different signaling pathway routes to reach activation of one set of output kinases, ERK1&2. The classical ERK activation pathway beings with growth factor activation of receptor tyrosine kinases. Numerous G-protein coupled receptors and ionotropic receptors also lead to ERK through increases in the second messengers calcium and cAMP. Though both types of pathways are present in diverse cell types, a key difference is that most stimuli to neurons, e.g. synaptic inputs, are transient, on the order of milliseconds to seconds, whereas many stimuli acting on non-neural tissue, e.g. growth factors, are longer duration. The ability to consolidate these inputs to regulate the activation of ERK in response to diverse signals raises the question of which factors influence the difference in ERK activation pathways. This review presents both experimental studies and computational models aimed at understanding the control of ERK activation and whether there are fundamental differences between neurons and other cells. Our main conclusion is that differences between cell types are quite subtle, often related to differences in expression pattern and quantity of some molecules such as Raf isoforms. In addition, the spatial location of ERK is critical, with regulation by scaffolding proteins producing differences due to colocalization of upstream molecules that may differ between neurons and other cells.

An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping

Stochastic simulation of reaction-diffusion systems enables the investigation of stochastic events arising from the small numbers and heterogeneous distribution of molecular species in biological cells. Stochastic variations in intracellular microdomains and in diffusional gradients play a significant part in the spatiotemporal activity and behavior of cells. Although an exact stochastic simulation that simulates every individual reaction and diffusion event gives a most accurate trajectory of the system's state over time, it can be too slow for many practical applications. We present an accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems designed to improve the speed of simulation by reducing the number of time-steps required to complete a simulation run. This method is unique in that it employs two strategies that have not been incorporated in existing spatial stochastic simulation algorithms. First, diffusive transfers between neighboring subvolumes are based on concentration gradients. This treatment necessitates sampling of only the net or observed diffusion events from higher to lower concentration gradients rather than sampling all diffusion events regardless of local concentration gradients. Second, we extend the non-negative Poisson tau-leaping method that was originally developed for speeding up nonspatial or homogeneous stochastic simulation algorithms. This method calculates each leap time in a unified step for both reaction and diffusion processes while satisfying the leap condition that the propensities do not change appreciably during the leap and ensuring that leaping does not cause molecular populations to become negative. Numerical results are presented that illustrate the improvement in simulation speed achieved by incorporating these two new strategies.

Calcium dynamics predict direction of synaptic plasticity in striatal spiny projection neurons

The striatum is a major site of learning and memory formation for sensorimotor and cognitive association. One of the mechanisms used by the brain for memory storage is synaptic plasticity - the long-lasting, activity-dependent change in synaptic strength. All forms of synaptic plasticity require an elevation in intracellular calcium, and a common hypothesis is that the amplitude and duration of calcium transients can determine the direction of synaptic plasticity. The utility of this hypothesis in the striatum is unclear in part because dopamine is required for striatal plasticity and in part because of the diversity in stimulation protocols. To test whether calcium can predict plasticity direction, we developed a calcium-based plasticity rule using a spiny projection neuron model with sophisticated calcium dynamics including calcium diffusion, buffering and pump extrusion. We utilized three spike timing-dependent plasticity (STDP) induction protocols, in which postsynaptic potentials are paired with precisely timed action potentials and the timing of such pairing determines whether potentiation or depression will occur. Results show that despite the variation in calcium dynamics, a single, calcium-based plasticity rule, which explicitly considers duration of calcium elevations, can explain the direction of synaptic weight change for all three STDP protocols. Additional simulations show that the plasticity rule correctly predicts the NMDA receptor dependence of long-term potentiation and the L-type channel dependence of long-term depression. By utilizing realistic calcium dynamics, the model reveals mechanisms controlling synaptic plasticity direction, and shows that the dynamics of calcium, not just calcium amplitude, are crucial for synaptic plasticity.

Subcellular interactions between parallel fibre and climbing fibre signals in Purkinje cells predict sensitivity of classical conditioning to interstimulus interval

Classical conditioning of the nictitating membrane response requires a specific temporal interval between conditioned stimulus and unconditioned stimulus, and produces an increase in Protein Kinase C (PKC) activation in Purkinje cells. To evaluate whether biochemical interactions within the Purkinje cell may explain the temporal sensitivity, a model of PKC activation by Ca2+, diacylglycerol (DAG), and arachidonic acid (AA) is developed. Ca2+ elevation is due to CF stimulation and IP3 induced Ca2+ release (IICR). DAG and IP3 result from PF stimulation, while AA results from phospholipase A2 (PLA2). Simulations predict increased PKC activation when PF stimulation precedes CF stimulation by 0.1 to 3 s. The sensitivity of IICR to the temporal relation between PF and CF stimulation, together with the buffering system of Purkinje cells, significantly contribute to the temporal sensitivity.

Measurement of empathy toward rape victims and rapists

The purpose of the present study was the construction of the Rape Empathy Scale (RES), designed to measure subjects' empathy toward the rape victim and the rapist in a heterosexual rape situation. The results of psychometric analyses of reliability for both a student and juror sample are presented, in addition to evidence of cross-validation on separate student and juror samples. Significant differences between male and female subjects' RES scores were found, as well as differences between scores of women who had experienced a rape situation (rape victims and rape resisters) and women with no previous exposure to rape. RES scores were predictive of both students' and jurors' ratings of defendant guilt, as well as their recommended sentences for the defendant and their attributions of responsibility for the crime. Furthermore, subjects' RES scores were predictive of their social perceptions of the rape victim and defendant, and male jurors' RES scores were negatively correlated with their reported desire to rape a woman. The results are discussed in relation to the low conviction rate for sexual assault cases and the importance of juror selection as a vehicle for increasing the number of just convictions in rape cases.

The effect of white and filtered noise on contrast detection thresholds

Models of the dipper effect seen in contrast discrimination experiments predict that small amounts of noise should facilitate detection of a subthreshold sinusoidal grating. Although facilitation of chromatic sine waves has been measured with chromatic or luminance noise, a facilitory effect of luminance sinusoidal gratings has not been measured, most likely because the stimulus characteristics were not tuned for revealing facilitation. The present study measures contrast detection thresholds (CDTs) of sinusoidal gratings in two-dimensional, static, band-limited white noise and low-pass and high-pass filtered noise using a two-interval forced-choice paradigm. The results show facilitation in near threshold white noise of middle frequency sinusoidal gratings, and facilitation in filtered noise of sinusoidal gratings whose frequency is far outside the pass band of the noise. Based on these results, a model of contrast detection thresholds is modified such that the facilitation is attributed to reduced observer uncertainty caused by small amounts of noise.

β-adrenergic signaling broadly contributes to LTP induction

Long-lasting forms of long-term potentiation (LTP) represent one of the major cellular mechanisms underlying learning and memory. One of the fundamental questions in the field of LTP is why different molecules are critical for long-lasting forms of LTP induced by diverse experimental protocols. Further complexity stems from spatial aspects of signaling networks, such that some molecules function in the dendrite and some are critical in the spine. We investigated whether the diverse experimental evidence can be unified by creating a spatial, mechanistic model of multiple signaling pathways in hippocampal CA1 neurons. Our results show that the combination of activity of several key kinases can predict the occurrence of long-lasting forms of LTP for multiple experimental protocols. Specifically Ca²⁺/calmodulin activated kinase II, protein kinase A and exchange protein activated by cAMP (Epac) together predict the occurrence of LTP in response to strong stimulation (multiple trains of 100 Hz) or weak stimulation augmented by isoproterenol. Furthermore, our analysis suggests that activation of the β-adrenergic receptor either via canonical (G_s-coupled) or non-canonical (G_i-coupled) pathways underpins most forms of long-lasting LTP. Simulations make the experimentally testable prediction that a complete antagonist of the β-adrenergic receptor will likely block long-lasting LTP in response to strong stimulation. Collectively these results suggest that converging molecular mechanisms allow CA1 neurons to flexibly utilize signaling mechanisms best tuned to temporal pattern of synaptic input to achieve long-lasting LTP and memory storage.

Long-term potentiation of the strength of synaptic connections is a mechanism of learning and memory storage. One of the most confusing aspects of hippocampal synaptic potentiation is that numerous experiments have revealed the requirement for a plethora of signaling molecules. Furthermore the degree to which molecules activated by the stress response modify hippocampal synaptic potentiation and memory is still unclear. We used a computational model to demonstrate that this molecular diversity can be explained by considering a combination of several key molecules. We also show that activation of β-adrenergic receptors by the stress response appears to be involved in most forms of synaptic potentiation, though in some cases unconventional mechanisms are utilized. This suggests that novel treatments for stress-related disorders may have more success if they target unconventional mechanisms activated by β-adrenergic receptors.

A unified computational model for cortical post-synaptic plasticity

Signalling pathways leading to post-synaptic plasticity have been examined in many types of experimental studies, but a unified picture on how multiple biochemical pathways collectively shape neocortical plasticity is missing. We built a biochemically detailed model of post-synaptic plasticity describing CaMKII, PKA, and PKC pathways and their contribution to synaptic potentiation or depression. We developed a statistical AMPA-receptor-tetramer model, which permits the estimation of the AMPA-receptor-mediated maximal synaptic conductance based on numbers of GluR1s and GluR2s predicted by the biochemical signalling model. We show that our model reproduces neuromodulator-gated spike-timing-dependent plasticity as observed in the visual cortex and can be fit to data from many cortical areas, uncovering the biochemical contributions of the pathways pinpointed by the underlying experimental studies. Our model explains the dependence of different forms of plasticity on the availability of different proteins and can be used for the study of mental disorder-associated impairments of cortical plasticity.

Control of βAR- and N-methyl-D-aspartate (NMDA) Receptor-Dependent cAMP Dynamics in Hippocampal Neurons

Norepinephrine, a neuromodulator that activates β-adrenergic receptors (βARs), facilitates learning and memory as well as the induction of synaptic plasticity in the hippocampus. Several forms of long-term potentiation (LTP) at the Schaffer collateral CA1 synapse require stimulation of both βARs and N-methyl-D-aspartate receptors (NMDARs). To understand the mechanisms mediating the interactions between βAR and NMDAR signaling pathways, we combined FRET imaging of cAMP in hippocampal neuron cultures with spatial mechanistic modeling of signaling pathways in the CA1 pyramidal neuron. Previous work implied that cAMP is synergistically produced in the presence of the βAR agonist isoproterenol and intracellular calcium. In contrast, we show that when application of isoproterenol precedes application of NMDA by several minutes, as is typical of βAR-facilitated LTP experiments, the average amplitude of the cAMP response to NMDA is attenuated compared with the response to NMDA alone. Models simulations suggest that, although the negative feedback loop formed by cAMP, cAMP-dependent protein kinase (PKA), and type 4 phosphodiesterase may be involved in attenuating the cAMP response to NMDA, it is insufficient to explain the range of experimental observations. Instead, attenuation of the cAMP response requires mechanisms upstream of adenylyl cyclase. Our model demonstrates that Gs-to-Gi switching due to PKA phosphorylation of βARs as well as Gi inhibition of type 1 adenylyl cyclase may underlie the experimental observations. This suggests that signaling by β-adrenergic receptors depends on temporal pattern of stimulation, and that switching may represent a novel mechanism for recruiting kinases involved in synaptic plasticity and memory.

Noradrenaline is a stress related molecule that facilitates learning and memory when released in the hippocampus. The facilitation of memory is related to modulation of synaptic plasticity, but the mechanisms underlying this modulation are not well understood. We utilize a combination of live cell imaging and computational modeling to discover how noradrenergic receptor stimulation interacts with other molecules, such as calcium, required for synaptic plasticity and memory storage. Though prior work has shown that noradrenergic receptors and calcium interact synergistically to elevate intracellular second messengers when combined simultaneously, our results demonstrate that prior stimulation of noradrenergic receptors inhibits the elevation of intracellular second messengers. Our results further demonstrate that the inhibition may be caused by the noradrenergic receptor switching signaling pathways, thereby recruiting a different set of memory kinases. This switching represents a novel mechanism for recruiting molecules involved in synaptic plasticity and memory.

Dopamine Oppositely Modulates State Transitions in Striosome and Matrix Direct Pathway Striatal Spiny Neurons

Corticostriatal synaptic integration is partitioned among striosome (patch) and matrix compartments of the dorsal striatum, allowing compartmentalized control of discrete aspects of behavior. Despite the significance of such organization, it's unclear how compartment-specific striatal output is dynamically achieved, particularly considering new evidence that overlap of afferents is substantial. We show that dopamine oppositely shapes responses to convergent excitatory inputs in mouse striosome and matrix striatal spiny projection neurons (SPNs). Activation of postsynaptic D1 dopamine receptors promoted the generation of long-lasting synaptically evoked "up-states" in matrix SPNs but opposed it in striosomes, which were more excitable under basal conditions. Differences in dopaminergic modulation were mediated, in part, by dendritic voltage-gated calcium channels (VGCCs): pharmacological manipulation of L-type VGCCs reversed compartment-specific responses to D1 receptor activation. These results support a novel mechanism for the selection of striatal circuit components, where fluctuating levels of dopamine shift the balance of compartment-specific striatal output.

Computational models of neuronal biophysics and the characterization of potential neuropharmacological targets

The identification and characterization of potential pharmacological targets in neurology and psychiatry is a fundamental problem at the intersection between medicinal chemistry and the neurosciences. Exciting new techniques in proteomics and genomics have fostered rapid progress, opening numerous questions as to the functional consequences of ligand binding at the systems level. Psycho- and neuro-active drugs typically work in nerve cells by affecting one or more aspects of electrophysiological activity. Thus, an integrated understanding of neuropharmacological agents requires bridging the gap between their molecular mechanisms and the biophysical determinants of neuronal function. Computational neuroscience and bioinformatics can play a major role in this functional connection. Robust quantitative models exist describing all major active membrane properties under endogenous and exogenous chemical control. These include voltage-dependent ionic channels (sodium, potassium, calcium, etc.), synaptic receptor channels (e.g. glutamatergic, GABAergic, cholinergic), and G protein coupled signaling pathways (protein kinases, phosphatases, and other enzymatic cascades). This brief review of neuromolecular medicine from the computational perspective provides compelling examples of how simulations can elucidate, explain, and predict the effect of chemical agonists, antagonists, and modulators in the nervous system.