For years, scholars have claimed that suicide terrorists are not suicidal, but rather psychologically normal individuals inspired to sacrifice their lives for an ideological cause, due to a range of social and situational factors. I agree that suicide terrorists are shaped by their contexts, as we all are. However, I argue that these scholars went too far. In The Myth of Martyrdom: What Really Drives Suicide Bombers, Rampage Shooters, and Other Self-Destructive Killers, I take the opposing view, based on my in-depth analyses of suicide attackers from Asia, Africa, Europe, the Middle East, and North America; attackers who were male, female, young, old, Islamic, and Christian; attackers who carried out the most deadly and the least deadly strikes. I present evidence that in terms of their behavior and psychology, suicide terrorists are much like others who commit conventional suicides, murder-suicides, or unconventional suicides where mental health problems, personal crises, coercion, fear of an approaching enemy, or hidden self-destructive urges play a major role. I also identify critical differences between suicide terrorists and those who have genuinely sacrificed their lives for a greater good. By better understanding suicide terrorists, experts in the behavioral and brain sciences may be able to pioneer exciting new breakthroughs in security countermeasures and suicide prevention. And even more ambitiously, by examining these profound extremes of the human condition, perhaps we can more accurately grasp the power of the human survival instinct among those who are actually psychologically healthy.

Conviction Narrative Theory (CNT) is a theory of choice under radical uncertainty – situations where outcomes cannot be enumerated and probabilities cannot be assigned. Whereas most theories of choice assume that people rely on (potentially biased) probabilistic judgments, such theories cannot account for adaptive decision-making when probabilities cannot be assigned. CNT proposes that people use narratives – structured representations of causal, temporal, analogical, and valence relationships – rather than probabilities, as the currency of thought that unifies our sense-making and decision-making faculties. According to CNT, narratives arise from the interplay between individual cognition and the social environment, with reasoners adopting a narrative that feels “right” to explain the available data; using that narrative to imagine plausible futures; and affectively evaluating those imagined futures to make a choice. Evidence from many areas of the cognitive, behavioral, and social sciences supports this basic model, including lab experiments, interview studies, and econometric analyses. We identify 12 propositions to explain how the mental representations (narratives) interact with four inter-related processes (explanation, simulation, affective evaluation, and communication), examining the theoretical and empirical basis for each. We conclude by discussing how CNT can provide a common vocabulary for researchers studying everyday choices across areas of the decision sciences.

Neural correlates exist for a basic component of logical formulae, PREDICATE(x). Vision and audition research in primates and humans shows two independent neural pathways; one locates objects in body-centered space, the other attributes properties, such as colour, to objects. In vision these are the dorsal and ventral pathways. In audition, similarly separable “where” and “what” pathways exist. PREDICATE(x) is a schematic representation of the brain's integration of the two processes of delivery by the senses of the location of an arbitrary referent object, mapped in parietal cortex, and analysis of the properties of the referent by perceptual subsystems.

The brain computes actions using a few “deictic” variables pointing to objects. Parallels exist between such nonlinguistic variables and linguistic deictic devices. Indexicality and reference have linguistic and nonlinguistic (e.g., visual) versions, sharing the concept of attention. The individual variables of logical formulae are interpreted as corresponding to these mental variables. In computing action, the deictic variables are linked with “semantic” information about the objects, corresponding to logical predicates.

Mental scene descriptions are necessary for practical tasks of primates, and preexist language phylogenetically. The type of scene descriptions used by nonhuman primates would be reused for more complex cognitive, ultimately linguistic, purposes. The provision by the brain's sensory/perceptual systems of about four variables for temporary assignment to objects, and the separate processes of perceptual categorization of the objects so identified, constitute a pre-adaptive platform on which an early system for the linguistic description of scenes developed.

The conceptual and investigative tools for the analysis of social behavior can be expanded by integrating biological theory, control systems theory, and Pavlovian conditioning. Biological theory has focused on the costs and benefits of social behavior from ecological and evolutionary perspectives. In contrast, control systems theory is concerned with how machines achieve a particular goal or purpose. The accurate operation of a system often requires feed-forward mechanisms that adjust system performance in anticipation of future inputs. Pavlovian conditioning is ideally suited to subserve this function in behavioral systems. Pavlovian mechanisms have been demonstrated in various aspects of sexual behavior, maternal lactation, and infant suckling. Pavlovian conditioning of agonistic behavior has been also reported, and Pavlovian processes may likewise be involved in social play and social grooming. Several further lines of evidence indicate that Pavlovian conditioning can increase the efficiency and effectiveness of social interactions, thereby improving their cost/benefit ratio. We extend Pavlovian concepts beyond the traditional domain of discrete secretory and other physiological reflexes to complex real-world behavioral interactions and apply abstract laboratory analyses of the mechanisms of associative learning to the daily challenges animals face as they interact with one another in their natural environments.