Behavior problems

Behaviors that interfere with harmonious social relationships or normal everyday activity (e.g., aggression, hyperactivity, excess irritability). See Aggressive behavior, Attention deficit hyperactivity disorder, Conduct disorder, Fetal programming, Indirect aggression, Obsessive-compulsive disorder (OCD), Oppositional defiant disorder (ODD), Risk factors

Behavior modification

In psychotherapy, a treatment approach that uses techniques such as biofeedback, conditioning, reinforcement, or aversion therapy to extinguish or inhibit inappropriate or maladaptive behavior, rather than remove the causes of such behaviour.  It can involve social praise, material reinforcers, and tokens, punishment-oriented techniques, including verbal reprimand, and time-outs when the person receiving the therapy has …

Behavior genetics

The study of behavioral variation among individuals, which is separated into genetic versus environmental components.  The most common research methodologies employed are family, twin, and adoption studies.  Environmental influences are divided into two classes, shared and non-shared (or unique) environment.  The former is the environment shared by siblings reared in the same family, and which …

Behavior mechanism

A hypothetical structure in the central nervous system that, when activated, produces an event of behavioral interest such as a particular perception, a specific motor pattern, or an identifiable internal state.  Similar in meaning to cognitive structure. See Cause (or causal factor), Cognitive structures, Mechanism, Process

Bayley Scales of Infant and Toddler Development

Used to assess infant and toddler mental and motor development through a series of standardized tasks.  From performance on the tasks, a normed developmental quotient is derived for each scale.  The Mental Scale is designed to assess a range of responses involving, for example, object permanence, memory, problem solving, and language-related abilities.  The Motor Scale …

Bayesian learning

Process of learning by means ofprobabilistic Bayesian inferences.  In Bayesian learning, current knowledge isrepresented as a set of hypotheses with a probability distribution (priorprobabilities, or shortly priors).  Learning consists in observing evidence andre-estimating probability distribution of the hypotheses given the observedevidence (thus creating posterior probabilities).  The inference that generatesposterior probability of each hypothesis follows Bayes’ …