Evaluation of ambiguous associations in the amygdala by learning the structure of the environment

Prospective contingency explains behavior and dopamine signals during associative learning

Associative learning depends on contingency, the degree to which a stimulus predicts an outcome. Despite its importance, the neural mechanisms linking contingency to behavior remain elusive. In the present study, we examined the dopamine activity in the ventral striatum-a signal implicated in associative learning-in a Pavlovian contingency degradation task in mice. We show that both anticipatory licking and dopamine responses to a conditioned stimulus decreased when additional rewards were delivered uncued, but remained unchanged if additional rewards were cued. These results conflict with contingency-based accounts using a traditional definition of contingency or a new causal learning model (ANCCR), but can be explained by temporal difference (TD) learning models equipped with an appropriate intertrial interval state representation. Recurrent neural networks trained within a TD framework develop state representations akin to our best 'handcrafted' model. Our findings suggest that the TD error can be a measure that describes both contingency and dopaminergic activity.

Prefrontal encoding of an internal model for emotional inference

A key function of brain systems mediating emotion is to learn to anticipate unpleasant experiences. Although organisms readily associate sensory stimuli with aversive outcomes, higher-order forms of emotional learning and memory require inference to extrapolate the circumstances surrounding directly experienced aversive events to other indirectly related sensory patterns that were not part of the original experience. This type of learning requires internal models of emotion, which flexibly track directly experienced and inferred aversive associations. Although the brain mechanisms of simple forms of aversive learning have been well studied in areas such as the amygdala1-4, whether and how the brain forms and represents internal models of emotionally relevant associations are not known5. Here we report that neurons in the rodent dorsomedial prefrontal cortex (dmPFC) encode a flexible internal model of emotion by linking sensory stimuli in the environment with aversive events, whether they were directly or indirectly associated with that experience. These representations form through a multi-step encoding mechanism involving recruitment and stabilization of dmPFC cells that support inference. Although dmPFC population activity encodes all salient associations, dmPFC neurons projecting to the amygdala specifically represent and are required to express inferred associations. Together, these findings reveal how internal models of emotion are encoded in the dmPFC to regulate subcortical systems for recall of inferred emotional memories.

The role of prospective contingency in the control of behavior and dopamine signals during associative learning

Associative learning depends on contingency, the degree to which a stimulus predicts an outcome. Despite its importance, the neural mechanisms linking contingency to behavior remain elusive. Here we examined the dopamine activity in the ventral striatum - a signal implicated in associative learning - in a Pavlovian contingency degradation task in mice. We show that both anticipatory licking and dopamine responses to a conditioned stimulus decreased when additional rewards were delivered uncued, but remained unchanged if additional rewards were cued. These results conflict with contingency-based accounts using a traditional definition of contingency or a novel causal learning model (ANCCR), but can be explained by temporal difference (TD) learning models equipped with an appropriate inter-trial-interval (ITI) state representation. Recurrent neural networks trained within a TD framework develop state representations like our best 'handcrafted' model. Our findings suggest that the TD error can be a measure that describes both contingency and dopaminergic activity.

Identifying and modulating neural signatures of stress susceptibility and resilience enables control of anhedonia

Anhedonia is a core aspect of major depressive disorder. Traditionally viewed as a blunted emotional state in which individuals are unable to experience joy, anhedonia also diminishes the drive to seek rewards and the ability to value and learn about them 1-4.The neural underpinnings of anhedonia and how this emotional state drives related behavioral changes remain unclear. Here, we investigated these questions by taking advantage of the fact that when mice are exposed to traumatic social stress, susceptible animals become socially withdrawn and anhedonic, where they cease to seek high-value rewards, while others remain resilient. By performing high density electrophysiological recordings and comparing neural activity patterns of these groups in the basolateral amygdala (BLA) and ventral CA1 (vCA1) of awake behaving animals, we identified neural signatures of susceptibility and resilience to anhedonia. When animals actively sought rewards, BLA activity in resilient mice showed stronger discrimination between upcoming reward choices. In contrast, susceptible mice displayed a rumination-like signature, where BLA neurons encoded the intention to switch or stay on a previously chosen reward. When animals were at rest, the spontaneous BLA activity of susceptible mice was higher dimensional than in controls, reflecting a greater number of distinct neural population states. Notably, this spontaneous activity allowed us to decode group identity and to infer if a mouse had a history of stress better than behavioral outcomes alone. Finally, targeted manipulation of vCA1 inputs to the BLA in susceptible mice rescued dysfunctional neural dynamics, amplified dynamics associated with resilience, and reversed their anhedonic behavior. This work reveals population-level neural signatures that explain individual differences in responses to traumatic stress, and suggests that modulating vCA1-BLA inputs can enhance resilience by regulating these dynamics.

Neural signatures of stress susceptibility and resilience in the amygdala-hippocampal network

The neural dynamics that underlie divergent anhedonic responses to stress remain unclear. Here, we identified neuronal dynamics in an amygdala-hippocampal circuit that distinguish stress resilience and susceptibility. In a reward-choice task, basolateral amygdala (BLA) activity in resilient mice showed enhanced discrimination of upcoming reward choices. In contrast, a rumination-like signature emerged in the BLA of susceptible mice; a linear decoder could classify the intention to switch or stay on a previously chosen reward. Spontaneous activity in the BLA of susceptible mice was higher dimensional than controls, reflecting the exploration of a larger number of distinct neural states. Manipulation of vCA1-BLA inputs rescued dysfunctional neural dynamics and anhedonia in susceptible mice, suggesting that targeting this pathway can enhance BLA circuit function and ameliorate of depression-related behaviors.

Prevalence and influencing factors of hyperuricemia in middle-aged and older adults in the Yao minority area of China: a cross-sectional study

Hyperuricemia (HUA) endangers human health, and its prevalence has increased rapidly in recent decades. The current study investigated HUA's prevalence and influencing factors in Gongcheng, southern China. A cross-sectional investigation was conducted; 2128 participants aged 30-93 years were included from 2018 to 2019. Univariate and multivariate logistic regression models were used to screen HUA variables. A Bayesian network model was constructed using the PC algorithm to evaluate the association between influencing factors and HUA. The prevalence of HUA was 15.6% (23.2% in men, 10.7% in women). After screening the variables using a logistic regression analysis model, fatty liver disease (FLD), dyslipidemia, abdominal obesity, creatinine (CREA), somatotype, bone mass, drinking, and physical activity level at work were included in the Bayesian network model. The model results showed that dyslipidemia, somatotype, CREA, and drinking were directly related to HUA. Bone mass and FLD were indirectly associated with HUA by affecting the somatotype. The prevalence of HUA in Gongcheng was high in China. The prevalence of HUA was related to somatotype, drinking, bone mass, physical activity level at work, and other metabolic diseases. A good diet and moderate exercise are recommended to maintain a healthy somatotype and reduce the prevalence rate of HUA.

Mesolimbic dopamine release conveys causal associations

Learning to predict rewards based on environmental cues is essential for survival. It is believed that animals learn to predict rewards by updating predictions whenever the outcome deviates from expectations, and that such reward prediction errors (RPEs) are signaled by the mesolimbic dopamine system-a key controller of learning. However, instead of learning prospective predictions from RPEs, animals can infer predictions by learning the retrospective cause of rewards. Hence, whether mesolimbic dopamine instead conveys a causal associative signal that sometimes resembles RPE remains unknown. We developed an algorithm for retrospective causal learning and found that mesolimbic dopamine release conveys causal associations but not RPE, thereby challenging the dominant theory of reward learning. Our results reshape the conceptual and biological framework for associative learning.

The learning of prospective and retrospective cognitive maps within neural circuits

Brain circuits are thought to form a "cognitive map" to process and store statistical relationships in the environment. A cognitive map is commonly defined as a mental representation that describes environmental states (i.e., variables or events) and the relationship between these states. This process is commonly conceptualized as a prospective process, as it is based on the relationships between states in chronological order (e.g., does reward follow a given state?). In this perspective, we expand this concept on the basis of recent findings to postulate that in addition to a prospective map, the brain forms and uses a retrospective cognitive map (e.g., does a given state precede reward?). In doing so, we demonstrate that many neural signals and behaviors (e.g., habits) that seem inflexible and non-cognitive can result from retrospective cognitive maps. Together, we present a significant conceptual reframing of the neurobiological study of associative learning, memory, and decision making.

Between placebo and nocebo: Response to control treatment is mediated by amygdala activity and connectivity

BACKGROUND

In experimental placebo and nocebo studies, neutral control treatments are often administered for comparison with active treatments, but are of little interest, as, on average, they result in little change. Yet, when considered at an individual level, they fluctuate between baseline and subsequent measurements and may reveal important information about participants' placebo/nocebo responding tendencies.

METHODS

In a paradigm involving application of creams paired with positive, negative and neutral expectations, some subjects rated identical stimuli in the neutral condition as more painful while others as less painful after treatment with inert cream. We divided subjects into two groups based on the median split in these pre-post responses in the neutral control condition, and investigated (a) fMRI signal differences (post minus pre) between the two groups in neutral condition, and (b) seed-based resting state connectivity of the bilateral amygdala, known to be involved in emotional self-regulation, as well as ambiguous stimulus processing and aversive learning.

RESULTS

The results suggested that subjects who rated the same pain stimuli after treatment with explicitly neutral cream as more painful showed stronger fMRI activation of the amygdala during the experiment and had higher connectivity between the left amygdala and the striatum at rest. Neutral pre-post changes predicted behavioural placebo/nocebo response in this and two independent datasets.

CONCLUSION

These findings suggest that measuring pre-post change in the neutral control condition might provide important information about subjects' individual differences in placebo/nocebo response.

SIGNIFICANCE

Pre-post changes in pain ratings in neutral conditions are modulated by amygdala activity and connectivity and can be used to predict placebo/nocebo responses.

Fear not: recent advances in understanding the neural basis of fear memories and implications for treatment development

Fear is a highly adaptive emotion that has evolved to promote survival and reproductive fitness. However, maladaptive expression of fear can lead to debilitating stressor-related and anxiety disorders such as post-traumatic stress disorder. Although the neural basis of fear has been extensively researched for several decades, recent technological advances in pharmacogenetics and optogenetics have allowed greater resolution in understanding the neural circuits that underlie fear. Alongside conceptual advances in the understanding of fear memory, this increased knowledge has clarified mechanisms for some currently available therapies for post-traumatic stress disorder and has identified new potential treatment targets.

Pain: A Precision Signal for Reinforcement Learning and Control

Since noxious stimulation usually leads to the perception of pain, pain has traditionally been considered sensory nociception. But its variability and sensitivity to a broad array of cognitive and motivational factors have meant it is commonly viewed as inherently imprecise and intangibly subjective. However, the core function of pain is motivational-to direct both short- and long-term behavior away from harm. Here, we illustrate that a reinforcement learning model of pain offers a mechanistic understanding of how the brain supports this, illustrating the underlying computational architecture of the pain system. Importantly, it explains why pain is tuned by multiple factors and necessarily supported by a distributed network of brain regions, recasting pain as a precise and objectifiable control signal.

Long time-scales in primate amygdala neurons support aversive learning

Associative learning forms when there is temporal relationship between a stimulus and a reinforcer, yet the inter-trial-interval (ITI), which is usually much longer than the stimulus-reinforcer-interval, contributes to learning-rate and memory strength. The neural mechanisms that enable maintenance of time between trials remain unknown, and it is unclear if the amygdala can support time scales at the order of dozens of seconds. We show that the ITI indeed modulates rate and strength of aversive-learning, and that single-units in the primate amygdala and dorsal-anterior-cingulate-cortex signal confined periods within the ITI, strengthen this coding during acquisition of aversive-associations, and diminish during extinction. Additionally, pairs of amygdala-cingulate neurons synchronize during specific periods suggesting a shared circuit that maintains the long temporal gap. The results extend the known roles of this circuit and suggest a mechanism that maintains trial-structure and temporal-contingencies for learning.

Neural Computations Underlying Causal Structure Learning

Behavioral evidence suggests that beliefs about causal structure constrain associative learning, determining which stimuli can enter into association, as well as the functional form of that association. Bayesian learning theory provides one mechanism by which structural beliefs can be acquired from experience, but the neural basis of this mechanism is poorly understood. We studied this question with a combination of behavioral, computational, and neuroimaging techniques. Male and female human subjects learned to predict an outcome based on cue and context stimuli while being scanned using fMRI. Using a model-based analysis of the fMRI data, we show that structure learning signals are encoded in posterior parietal cortex, lateral prefrontal cortex, and the frontal pole. These structure learning signals are distinct from associative learning signals. Moreover, representational similarity analysis and information mapping revealed that the multivariate patterns of activity in posterior parietal cortex and anterior insula encode the full posterior distribution over causal structures. Variability in the encoding of the posterior across subjects predicted variability in their subsequent behavioral performance. These results provide evidence for a neural architecture in which structure learning guides the formation of associations.SIGNIFICANCE STATEMENT Animals are able to infer the hidden structure behind causal relations between stimuli in the environment, allowing them to generalize this knowledge to stimuli they have never experienced before. A recently published computational model based on this idea provided a parsimonious account of a wide range of phenomena reported in the animal learning literature, suggesting a dedicated neural mechanism for learning this hidden structure. Here, we validate this model by measuring brain activity during a task that involves both structure learning and associative learning. We show that a distinct network of regions supports structure learning and that the neural signal corresponding to beliefs about structure predicts future behavioral performance.

Human Pavlovian fear conditioning conforms to probabilistic learning

Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.

Redundancy in synaptic connections enables neurons to learn optimally

Recent experimental studies suggest that, in cortical microcircuits of the mammalian brain, the majority of neuron-to-neuron connections are realized by multiple synapses. However, it is not known whether such redundant synaptic connections provide any functional benefit. Here, we show that redundant synaptic connections enable near-optimal learning in cooperation with synaptic rewiring. By constructing a simple dendritic neuron model, we demonstrate that with multisynaptic connections synaptic plasticity approximates a sample-based Bayesian filtering algorithm known as particle filtering, and wiring plasticity implements its resampling process. Extending the proposed framework to a detailed single-neuron model of perceptual learning in the primary visual cortex, we show that the model accounts for many experimental observations. In particular, the proposed model reproduces the dendritic position dependence of spike-timing-dependent plasticity and the functional synaptic organization on the dendritic tree based on the stimulus selectivity of presynaptic neurons. Our study provides a conceptual framework for synaptic plasticity and rewiring.

RDoC-based categorization of amygdala functions and its implications in autism

Confusion endures as to the exact role of the amygdala in relation to autism. To help resolve this we turned to the NIMH's Research Domain Criteria (RDoC) which provides a classification schema that identifies different categories of behaviors that can turn pathologic in mental health disorders, e.g. autism. While RDoC incorporates all the known neurobiological substrates for each domain, this review will focus primarily on the amygdala. We first consider the amygdala from an anatomical, historical, and developmental perspective. Next, we examine the different domains and constructs of RDoC that the amygdala is involved in: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Social Processes, and Arousal and Regulatory Systems. Then the evidence for a dysfunctional amygdala in autism is presented with a focus on alterations in development, prenatal valproic acid exposure as a model for ASD, and changes in the oxytocin system therein. Finally, a synthesis of RDoC, the amygdala, and autism is offered, emphasizing the task of disambiguation and suggestions for future research.

Resting state functional connectivity of the amygdala and problem drinking in non-dependent alcohol drinkers

Alcohol misuse is associated with dysfunction of the amygdala-prefrontal cortical circuit. The amygdala and its cortical targets show decreased activity during a variety of task challenges in individuals engaged in problem drinking. On the other hand, it is less clear how amygdala resting state functional connectivity (rsFC) may be altered in association with alcohol misuse and whether such changes are restricted to prefrontal cortical structures. Further, the influences of comorbid substance use and depression and potential sex differences have not been assessed in earlier work. Here, with fMRI data from a Nathan Kline Institute/Rockland sample of 83 non-dependent alcohol drinkers (26 men), we addressed changes in whole brain rsFC of the amygdala in association with problem drinking as indexed by an alcohol involvement score. Imaging data were processed with Statistical Parametric Mapping following standard routines and all results were examined at voxel p < 0.001 uncorrected in combination with cluster p < 0.05 corrected for false discovery rate. Alcohol misuse was correlated with decreased amygdala connectivity with the dorsal anterior cingulate cortex (dACC) irrespective of depression and other substance use. Changes in amygdala-dACC connectivity manifested in the latero-basal subdivision of the amygdala. Further, men as compared to women showed a significantly stronger relationship in decreased amygdala-dACC connectivity and problem drinking, although it should be noted that men also showed a trend toward higher alcohol involvement score than women. The findings add to a growing literature documenting disrupted amygdala-prefrontal cortical functions in relation to alcohol misuse.

Alpha1-adrenergic receptor blockade in the VTA modulates fear memories and stress responses

Activity of the ventral tegmental area (VTA) and its terminals has been implicated in the Pavlovian associative learning of both stressful and rewarding stimuli. However, the role of the VTA noradrenergic signaling in fear responses remains unclear. We aimed to examine how alpha₁-adrenergic receptor (α₁-AR) signaling in the VTA affects conditioned fear. The role of α₁-AR was assessed using the micro-infusions into the VTA of the selective antagonists (0.1-1µg/0.5µl prazosin and 1µg/0.5µl terazosin) in acquisition and expression of fear memory. In addition, we performed control experiments with α₁-AR blockade in the mammillary bodies (MB) - a brain region with α₁-AR expression adjacent to the VTA. Intra-VTA but not intra-MB α₁-AR blockade prevented formation and retrieval of fear memories. Importantly, local administration of α₁-AR antagonists did not influence footshock sensitivity, locomotion or anxiety-like behaviors. Similarly, α₁-AR blockade in the VTA had no effects on negative affect measured as number of 22kHz ultrasonic vocalizations during fear conditioning training. We propose that noradrenergic signaling in the VTA via α₁-AR regulates formation and retrieval of fear memories but not other behavioral responses to stressful environmental stimuli. It enhances the encoding of environmental stimuli by the VTA to form and retrieve conditioned fear memories and to predict future behavioral outcomes. Our results provide novel insight into the role of the VTA α₁-AR signaling in the regulation of stress responsiveness and fear memory.

Interaction of Instrumental and Goal-Directed Learning Modulates Prediction Error Representations in the Ventral Striatum

Goal-directed and instrumental learning are both important controllers of human behavior. Learning about which stimulus event occurs in the environment and the reward associated with them allows humans to seek out the most valuable stimulus and move through the environment in a goal-directed manner. Stimulus-response associations are characteristic of instrumental learning, whereas response-outcome associations are the hallmark of goal-directed learning. Here we provide behavioral, computational, and neuroimaging results from a novel task in which stimulus-response and response-outcome associations are learned simultaneously but dominate behavior at different stages of the experiment. We found that prediction error representations in the ventral striatum depend on which type of learning dominates. Furthermore, the amygdala tracks the time-dependent weighting of stimulus-response versus response-outcome learning. Our findings suggest that the goal-directed and instrumental controllers dynamically engage the ventral striatum in representing prediction errors whenever one of them is dominating choice behavior.

SIGNIFICANCE STATEMENT

Converging evidence in human neuroimaging studies has shown that the reward prediction errors are correlated with activity in the ventral striatum. Our results demonstrate that this region is simultaneously correlated with a stimulus prediction error. Furthermore, the learning system that is currently dominating behavioral choice dynamically engages the ventral striatum for computing its prediction errors. This demonstrates that the prediction error representations are highly dynamic and influenced by various experimental context. This finding points to a general role of the ventral striatum in detecting expectancy violations and encoding error signals regardless of the specific nature of the reinforcer itself.

The developing amygdala: a student of the world and a teacher of the cortex

Amygdala and prefrontal cortex (PFC) function subserving emotional behavior has largely been examined from the perspective of their adult roles, with a tremendous focus on the regulatory influence of the PFC over amygdala activity. Here we consider the circuit's function in its developmental context, when maximal learning about emotion and incentives from the environment is necessary. We argue that during development the amygdala exhibits an overwhelming influence over the developmental destiny of circuitry function, and the amygdala's learning and experiential history are conveyed to the cortex to modulate subsequent PFC development. We present recent findings on the different developmental trajectories of the amygdala and PFC, their functional connectivity, and the timing of environmental influences as evidence supporting our position.

Thalamic Regulation of Sucrose Seeking during Unexpected Reward Omission

The paraventricular nucleus of the thalamus (PVT) is thought to regulate behavioral responses under emotionally arousing conditions. Reward-associated cues activate PVT neurons; however, the specific PVT efferents regulating reward seeking remain elusive. Using a cued sucrose-seeking task, we manipulated PVT activity under two emotionally distinct conditions: (1) when reward was available during the cue as expected or (2) when reward was unexpectedly omitted during the cue. Pharmacological inactivation of the anterior PVT (aPVT), but not the posterior PVT, increased sucrose seeking only when reward was omitted. Consistent with this, photoactivation of aPVT neurons abolished sucrose seeking, and the firing of aPVT neurons differentiated reward availability. Photoinhibition of aPVT projections to the nucleus accumbens or to the amygdala increased or decreased, respectively, sucrose seeking only when reward was omitted. Our findings suggest that PVT bidirectionally modulates sucrose seeking under the negative (frustrative) conditions of reward omission.

The Basolateral Amygdalae and Frontotemporal Network Functions for Threat Perception

Although the amygdalae play a central role in threat perception and reactions, the direct contributions of the amygdalae to specific aspects of threat perception, from ambiguity resolution to reflexive or deliberate action, remain ill understood in humans. Animal studies show that a detailed understanding requires a focus on the different subnuclei, which is not yet achieved in human research. Given the limits of human imaging methods, the crucial contribution needs to come from individuals with exclusive and selective amygdalae lesions. The current study investigated the role of the basolateral amygdalae and their connection with associated frontal and temporal networks in the automatic perception of threat. Functional activation and connectivity of five individuals with Urbach–Wiethe disease with focal basolateral amygdalae damage and 12 matched controls were measured with functional MRI while they attended to the facial expression of a threatening face–body compound stimuli. Basolateral amygdalae damage was associated with decreased activation in the temporal pole but increased activity in the ventral and dorsal medial prefrontal and medial orbitofrontal cortex. This dissociation between the prefrontal and temporal networks was also present in the connectivity maps. Our results contribute to a dynamic, multirole, subnuclei-based perspective on the involvement of the amygdalae in fear perception. Damage to the basolateral amygdalae decreases activity in the temporal network while increasing activity in the frontal network, thereby potentially triggering a switch from resolving ambiguity to dysfunctional threat signaling and regulation, resulting in hypersensitivity to threat.

Wireless inertial measurement of head kinematics in freely-moving rats

While miniature inertial sensors offer a promising means for precisely detecting, quantifying and classifying animal behaviors, versatile inertial sensing devices adapted for small, freely-moving laboratory animals are still lacking. We developed a standalone and cost-effective platform for performing high-rate wireless inertial measurements of head movements in rats. Our system is designed to enable real-time bidirectional communication between the headborne inertial sensing device and third party systems, which can be used for precise data timestamping and low-latency motion-triggered applications. We illustrate the usefulness of our system in diverse experimental situations. We show that our system can be used for precisely quantifying motor responses evoked by external stimuli, for characterizing head kinematics during normal behavior and for monitoring head posture under normal and pathological conditions obtained using unilateral vestibular lesions. We also introduce and validate a novel method for automatically quantifying behavioral freezing during Pavlovian fear conditioning experiments, which offers superior performance in terms of precision, temporal resolution and efficiency. Thus, this system precisely acquires movement information in freely-moving animals, and can enable objective and quantitative behavioral scoring methods in a wide variety of experimental situations.