Behavior (Neuroscience)

Publisher Summary

Behavior includes movement, social interaction, cognition, and learning. At its core, behavior provides animals with adaptive mechanisms for adjusting to changes in their environment and for manipulating the world around them. This chapter illustrates that using the four central questions of animal behavior—causation, development, survival value, and evolution—a testable hypotheses can be formed and much deeper understanding of behavior can be achieved. The discussion expands these questions and analyzes how they can be applied. Two animals are discussed in particular—the wolf and the cockroach—that have contributed greatly to the understanding of animal behavior. The chapter concludes with an overview of the history of the study of animal behavior. The discussion appreciates that contemporary studies of animal behavior are rooted in ethology, comparative psychology, sociobiology, and behavioral ecology.

6 Conclusions

Behavior is the primary means by which an organism interacts with its environment (Weiss and Cory-Slechta, 1994). To survive, organisms must be sensitive to events occurring in their environments and respond appropriately. To this end, it is important to emphasize drug effects at the level of behavior. In fact, the final criterion in any study of CNS insult or modification (e.g. drug use) includes characteristics associated with the whole animal; characteristics like the development and longevity of the animal are important, but so too is the functional integrity and quality of performance that animal is capable of engaging in, as is the emotional reactivity of the animal (Weiss, 1978). And because the whole animal is our interest, it is necessary that behavior is our subject matter as only it reflects the summed and integrated capacity of an organism to handle the environment within which it exists (Weiss, 1978). The tasks described here, and the data generated from them, build upon many decades of work from Pavlovian conditioning and operant psychology where task development was driven by the desire to understand and predict behavior. Building on these literatures, contemporary scientists are tasked with adapting and developing procedures for the use in new animal models that will produce informative and reliable measures of behavior change so that the field of behavioral pharmacology may continue to make advancements in our understanding of drug effects, and endogenous systems.

1 Introduction

Behavior is a complex phenomenon that empowers living organisms to adapt, survive, and procreate in dynamic biological galaxies on our planet. Diverse behavioral acts and states emerged over thousands of years of competition for resources with other life forms. During this period, mammals developed complex sensory systems enabling them to perceive, learn, and respond to challenges from the outer environment. Inside the body however, the immune system evolved to continuously detect, neutralize, and remove potential threats (e.g., viruses, bacteria, tumors) undetectable to the five senses. These ⿿internal stressors⿿ induce various immune responses which (via the enteric/peripheral nervous system and the endocrine system) affect multiple behavioral domains, from locomotion and emotional reactivity, to learning and memory. When homeostasis is disturbed by either central or systemic diseases, the analysis of behavioral responses requires more a comprehensive design, multiple tests (i.e., behavioral phenotyping), as well as adequate statistical approaches and careful interpretations. Since behavioral phenotyping is often time-consuming, the use of isolated behavioral paradigms has become the norm in today⿿s fast-paced academic and industrial environments. This review is prepared for a fledging behaviorist (or an expert from a field different from behavioral neurosciences), who wants to better understand and examine performance deficits in the commonly used water maze (WM) paradigm, largely reflective of spatial learning/memory capacity. The sequence of chapters guides a reader from theoretical backgrounds and practical aspects, to empirically-based inferences and common misconceptions. We hope that a deeper understanding of factors underlying WM performance will improve scientific rigor and merit of experimental studies of chronic human diseases characterized by cognitive retardation or decline.

Highlights

Introduction

Behavior is dynamic, complex, and seemingly noisy — this presents challenges for both quantifying it and connecting it with the underlying neural activity that generates it [1]. One challenge with quantifying behavior is defining it — while neural activity can be measured in spikes or fluctuations of membrane voltage, scientists have yet to agree on a definition of what constitutes ‘behavior’. For example, a survey of ethologists [2] yielded largely inconsistent definitions. The respondents agreed with incompatible statements such as both ‘only animals behave’ and ‘algae chemotaxis is behavior’, ‘behavior is always executed through muscular activity’ but ‘sponges behave’ (without muscles), and ‘a person deciding to do nothing is behaving’ (without using muscles). One way to make progress on this question may then be to simply quantify as much as possible about what an animal does (what we here refer to as ‘behavior’). Thanks to developments in computer science and the increasing availability of high resolution, high-frame rate cameras, we are now able to capture and quantify orders of magnitude more data about animal movements and actions than was possible even a decade ago. Faced with these new large datasets, there has been a recent explosion of interest in developing algorithms to automate the classification of behavior. Rather than focus on summary statistics, these algorithms provide the ability to precisely measure individual-level variation in behavior, as it evolves over time. In addition, these methods represent a powerful alternative to human classification, which is typically slow, difficult to reproduce, and often introduces unwanted biases [3,4]. These automated tools further provide consistency when analyzing phenotypes that result from genetic and neural perturbations [4].

In parallel, new computational frameworks now allow scientists to estimate the sensory experience of the animal under study. That is, both the input and output space of the nervous system can be extensively sampled. These data can then be used to build models that not only predict behavior (keeping in mind that an animal's own behavior affects its sensory experience), but also identify the internal computations that the nervous system performs. These capabilities become even more powerful when combined with a simple nervous system and genetic toolkit that facilitate testing predictions from models via targeted neural manipulations and recordings (e.g., determining the specific neurons involved in a given behavior and over what timescales). We therefore focus our review on new methods for behavioral quantification in worms and flies, delving into how to use quantitative behavioral analysis in combination with genetic tools to map full sensorimotor pathways, from neurons that process sensory information all the way to neurons that coordinate behavior (Figure 1).

Figure 1. Mapping full sensorimotor pathways. Solving the sensorimotor transformations that nervous systems perform requires quantification of sensory inputs, neural dynamics and behavioral outputs. Sensory inputs influence neural activity which drives behavior, which in turn can change the sensory input that an animal receives.

Image of fly adapted from Muijres et al. (2014).

13.19.1 Introduction

Behavior allows an organism to react and adapt to its environment: it is required for survival and reproduction. Moreover, behavior represents the integration of motor, sensory, and associative neuronal functions, which cannot be assessed using only neurochemical, histological, or physiological techniques (Mello 1975). The study of behavior is the most integrated method for evaluating the integrity of the nervous system in the whole organism; as such, it is generally regarded as a sensitive indicator of nervous system function (Kulig et al. 1996; Tilson 1990; Tilson and Mitchell 1984). Whishaw justified the study of behavior most succinctly, writing “The nervous system is designed to produce behavior, and so behavioral analysis is the ultimate assay of neural function” (Whishaw et al. 1999, p. 1243).

A change in behavior may be the first measurable effect of chemical exposure, being evident at lower doses or having an earlier onset, than overt clinical signs or structural lesions. For example, neuromotor deficits preceded structural changes in the neurotoxicity produced by compounds such as acrylamide and carbon disulfide (LoPachin et al. 2002; Moser et al. 1992, 1998), and cognitive changes occur months after developmental exposure to lead, in the face of normal growth patterns and no other toxic signs (Cory-Slechta 2003). The primary advantage of behavioral end points, however, is more in that they reflect the subject’s overall functioning rather than being specifically more sensitive or an inherently superior test.

An organism’s behavioral patterns are unlearned, that is, innate, reflexive, instinctive, or else learned, that is, modified by previous experiences. The latter are measured in laboratory animals with a variety of tasks, often based on learning or conditioning, and therefore require training. These tests often measure particular aspects of behavior, for example, spatial learning, but the specificity of the task must be established to rule out confounds, for example, olfactory cues. The behavior is modified and controlled by the procedure. The ability to manipulate the experimental variables and parameters often leads to lower variability of the response, which increases the sensitivity of the test. On the other hand, innate behaviors allow direct observation with minimal experimental interference. They provide a broad assessment of neurological function, and, while easier to evaluate, may not be very specific. This makes interpretation more complicated (see Section 13.19.3.4). Because there is no external or procedural control on the behavior, it may be more variable than trained behaviors. This chapter will focus on the study of innate behaviors that have proven useful for screening in toxicology.

Highlights

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Behavior is the interface between the central nervous system and the living environment.

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As interface, behavior is a unique starting point to address the complexity of the brain.

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As interface, behavior is a privileged level of control of brain structure and activity.

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Therapies directly targeting behavior are highly effective in treating mental illness.

I INTRODUCTION

Behavior lies at the overlap of many different research fields. To some extent, behavior is the final functional goal of many systems under study, since genetic, biochemical, and physiological systems are all oriented toward providing controlled patterns of behavior, for the advantage, survival, and reproduction of the organism. Since behavior is the action of the animal in its environment and reflects the outcome of the integration and the fine tuning of all systems of the organism, it could thus possibly be considered an “emergent function,” as opposed to a simple summation of its numerous single components. Nevertheless, it is obvious that a certain behavioral sequence would be limited (or constrained) by the machinery, from circuitry to molecules, subserving the performance of the living organism. Such machinery is undoubtedly (though arguably only initially) determined by genetic makeup.

Genetics and behavior have for a long time enjoyed an ambiguous relationship (Greenspan, 1995). At one end of the behavior/genetics spectrum lies the tendency of the geneticist to wish to assign each behavior to a gene, whereas at the other end of the spectrum, behavior itself is often only partially described in terms of its relative difficulties in definition, description, and quantification. For several molecular geneticists, a behavioral mutant can be considered a type of developmental mutant, and behavior is therefore considered only the secondary consequence of a defect accumulated during the development process. Conversely, for the behaviorist, what makes behavior interesting is how, when, and finally why an animal might perform a certain behavioral sequence. In these terms, we temptingly assume that “how” could refer to the description of the behavioral sequence itself, which thus must first be well described and quantified (which is not always the case, and there is much room for such effort). [For example, the design of a quantitative paradigm has made it possible to identify a highly organized fractal structure within locomotor activity (see later discussion; Martin et al., in press). In addition to designing a novel courtship conditioning paradigm, Siwicki and her colleagues (McBride et al., 1999) have been able to show that courtship conditioning in wild-type male flies establishes a long-term memory, lasting up to 9 days, whereas in Mushroom-Body ablated males, this memory dissipates completely within a day.] The “when” probably relates to the conjunction of the immediate external environment with the body’s internal physiological needs. Finally, the “why” implies a “decision process” that most likely deals with the actual state of the organism (external environment in combination with the body’s internal physiological needs) in addition to the sum of knowledge acquired from previous life experience stored somewhere in the brain, as a memory trace. Indeed, certain fly behaviors, such as courtship, have been shown to be subject to sensitization (a nonassociative form of plasticity; Kyriacou and Hall, 1984), as well as to associative modification (Siegel and Hall, 1979; Siegel et al., 1984). Such results lead to the suggestion that previous experience can participate in modifying the “decision process” according to a further similarly given context, and this therefore could represent adaptative value in favor of evolutionary fitness.

Over the past few decades, the explosion of molecular genetics in general, and particularly in the fruit fly Drosophila melanogaster, has led to the identification of a huge number of genes, some of which, when mutated, affect various behavioral sequences directly or indirectly. However, beyond the genetic and molecular characterization of such genes and their associated molecular pathways, only very few have been revealed to be behavior-specific mutants [several previous reviews have already covered the topic of behavioral genetics (Hall and Greenspan, 1979; Hall, 1982, 1994a; Heisenberg, 1994; Kyriacou and Hall, 1994; Pflugfelder, 1998)]. On the other hand, recent advances in molecular genetics have contributed to the development of new tools dedicated more specifically to the dissection of the neural bases of behaviors. In particular, the conjunction of the development of two techniques, the enhancer-trap detection system (O’Kane and Gehring, 1987) and the targeted gene expression system, based on the yeast transcriptional activator GAL4, has led to the binary enhancer-trap P[GAL4] expression system, which allows the selective activation of any cloned gene in a wide variety of tissue- and cell-specific patterns (Brand and Perrimon, 1993). Initially, this system allows the anatomical characterization of specific neuronal circuitry, by way of the expression of a variety of marker reporter genes. Similarly, this genetic tool also allows the expression of toxic genes, in particular the tetanus toxin light chain (TeTxLC) gene, expression of which is found to specifically block synaptic transmission, leading to neuronal silencing. The ability to thus silence neurons is of particular facility to the study of neuronal circuitry in an otherwise normally functioning fly.

This review focuses on the use of transgenic TeTxLC to dissect the neurobiology of behavior. We will describe how and why this tool has been constructed, its mechanism of action, and the enhancer-trap P[GAL4] system used to specifically target it in precise groups of neurons. We will then describe how certain behavioral sequences have been impaired in direct correlation with relevant electrophysiological data. Finally, we will present results of research in which this toxigenetic tool has been successfully used to study various sensory functions in addition to dissecting some of the complexity of central brain function.

1 Introduction

Behavior is the reaction of a living being to external or internal causal factors [2,3]. In humans and animals, this reaction is coordinated by the central nervous system (CNS) in a contextualized and coherent fashion [4]. Any complex or simple action, like raising a hand, smiling, walking or speaking, involves several and complex processes in the CNS; therefore, an injury or a malfunction at any level of the CNS may result in substantial behavioral or movement disorder. These anomalies, as isolated episodes or, otherwise, related to delicate phases of psychomotor development, sometimes lead to a range of disorders, often socially dysfunctional, such as aggressiveness, impulsiveness, hyperactivity or stereotypies. In neuropsychiatry, the term “behavioral disorder” is extremely broad and it includes a wide range of diseases with heterogeneous etiology. On this subject, the Diagnostic and Statistical Manual of Mental Disorders [5] indicates, just to name a few, the Neurodevelopmental Disorders such as Autism Spectrum Disorders, Attention-Deficit Hyperactivity Disorder (ADHD), motor disorders associated with self-injurious behaviors, Tourette's syndrome and other tic disorders, psychotic disorders, bipolar disorders, depressive disorders, anxiety disorders, Obsessive-Compulsive Spectrum Disorders, feeding and eating disorders, Substance-Related and Addictive Disorders, Neurocognitive Disorders, Personality Disorders. On the basis of the Official Information Sheet from the World Health Organization, the social economic burden of these disorders is dramatic and increasing with substantial impact on health, daily life, employment and social relations in general [6]. Consequently, in these fields, it becomes of fundamental importance and actuality a scientific research, aimed at identifying new approaches, tools and methodologies for a better and a deeper understanding of the physio-pathological basis of these conditions. During the last decades an approach known as T-pattern analysis (TPA) has been employed with increasing frequency to study neurological and neuropsychiatric disorders associated with movement and/or behavioral anomalies. Aim of the present review is to offer an outline of the use of TPA in this field. Various applications of TPA in the study of behavior in human patients and in animal models of neurological disorders will be discussed.

For its intrinsic features, TPA is completely different from conventional quantitative evaluations of behavior such as assessments of frequencies, durations, percent distributions etc. of individual behavioral components. Actually, it is worth noting that a lot of researches and clinical studies in the field of movement and behavioral disorders have made available a huge amount of data on the individual aspects of the behavioral anomalies associated with these conditions and, importantly, on the effects induced by independent variables such as the use of specific drugs or other treatments. Alongside these studies, during the last decades, it has gradually increased the need to evaluate neurological and neuropsychiatric disorders by using approaches able to provide information on the temporal aspects of behavior, in its comprehensive structure, rather than on individual parameters, detached from the real organization of the subject's activity. As a matter of fact, individual elements of any behavior, physiological or pathological, simple or complex, unfold over time. On the basis of the words of Irenäus Eibl-Eibesfeldt, “Behavior consists of patterns in time. Investigations of behavior deal with sequences that, in contrast to bodily characteristics, are not always visible” [7]. One of the methods able to provide detailed information about the temporal features of behavioral disorders associated with neurological and/or neuropsychiatric diseases is the T-pattern detection and analysis (TPA), a multivariate technique widely and fruitfully applied, during the last decades, to study several aspects of animal and human behavior [8–13]. To better understand the difference between a classic quantitative approach and TPA various clarifications and technical details will be provided in the following section. The purpose of this review is to make available a framework on TPA and its usefulness in the study of neuropsychiatric conditions associated with behavioral disorders. Besides human pathologies, the application of TPA to study animal models of neurological disorders it will be discussed. By providing an overview on the literature concerning this subject, this review aims to be a useful tool for researchers who intend to utilize this approach to study neurological and neuropsychiatric conditions characterized by movement and/or behavioral disorders.