Basic Psychology: Psychophysiology


  1. Introduction
  2. Background
  3. Measures
  4. Uses
  5. Emotions as example of psychophysiological studies
  6. Psychophysiological inference and physiological computer games


Psychophysiology is the branch of psychology that studies the physiological underpinnings of psychological processes. While in the 1960s and 1970s, psychophysiology was a broad field of study, it has now become quite specialised, based on methods, research topics, and scientific traditions. Electrophysiological methods (such as EEG), neuroimaging (MRI, PET), and neurochemistry are used in various combinations. Subspecializations in social, sport, cognitive, cardiovascular, clinical, and other branches of psychophysiology have emerged.


Some people have trouble telling the difference between a psychophysiologist and a physiological psychologist, two very different perspectives. Psychologists are interested in why we fear spiders, while physiologists are interested in the amygdala's input/output system. A psychophysiologist will try to connect the two. Psychophysiologists generally study the psychological/physiological link in human subjects that are still alive. While early psychophysiologists almost always investigated the impact of psychological states on physiological system responses, since the 1970s, psychophysiologists have increasingly investigated the impact of physiological states and systems on psychological states and processes. This approach to studying the interface of mind and body distinguishes psychophysiologists.

Most psychophysiologists have traditionally focused on the physiological responses and organ systems innervated by the autonomic nervous system. Psychophysiologists have recently become equally, if not more, interested in the central nervous system, investigating cortical brain potentials such as the various types of event-related potentials (ERPs), brain waves, and utilising advanced technology such as functional magnetic resonance imaging (fMRI), MRI, PET, MEG, and other neuroimagery techniques. A psychophysiologist may investigate how stress affects the cardiovascular system, such as changes in heart rate (HR), vasodilation/vasoconstriction, myocardial contractility, or stroke volume. Overlaps in areas of interest between psychophysiologists and physiological psychologists may include observing how one cardiovascular or endocrine event influences another, or how activation of one neural brain structure exerts excitatory activity in another, which then induces an inhibitory effect in another system. Physiological psychologists frequently use surgical or invasive techniques and processes to investigate the effects they study in infrahuman subjects.

Psychophysiology is closely related to neuroscience, which is concerned with the interactions between psychological events and brain processes. Endocrinology, psychosomatics, and psychopharmacology are all medical disciplines that are related to psychophysiology.

Prior to the 1940s, psychophysiology was a discipline outside the mainstream of psychological and medical science. More recently, psychophysiology has found itself at the intersection of psychological and medical science, and its popularity and importance have grown in tandem with the realisation of the interconnectedness of mind and body.


Psychophysiology measures can be found in a variety of contexts, including reports, electrophysiological studies, neurochemistry, neuroimaging, and behavioural methods. Participant introspection and self-ratings of internal psychological states or physiological sensations, such as self-report of arousal levels on the self-assessment manikin, or measures of interoceptive visceral awareness, such as heartbeat detection, are used in evaluative reports. The benefits of self-report include a focus on accurately understanding the participants' subjective experience and perception; however, its drawbacks include the possibility of participants misinterpreting a scale or incorrectly recalling events. Instruments that read bodily events such as heart rate change, electrodermal activity (EDA), muscle tension, and cardiac output can also be used to measure physiological responses. Modern psychophysiology includes many indices, such as brain waves (electroencephalography, EEG), fMRI (functional magnetic resonance imaging), electrodermal activity (a standardised term encompassing skin conductance response, SCR, and galvanic skin response, GSR), cardiovascular measures (heart rate, HR; beats per minute, BPM; heart rate variability, HRV; vasomotor activity), muscle activity (electromyography, EMG), electrogastrogram (EGG These measures are advantageous because they provide objective data that is accurate and perceiver-independent when recorded by machinery. However, any physical activity or motion can alter responses, and basal levels of arousal and responsiveness can differ between individuals and even between situations.  Neurochemical methods are used to investigate the functionality and processes of neurotransmitters and neuropeptides.

Finally, overt action or behaviour can be measured by observing and recording actual actions such as running, freezing, eye movement, and facial expression. These are good animal response measures that are simple to record, but they are not as commonly used in human studies.


Psychophysiological measures are frequently used to investigate emotion and attention responses to stimuli, during physical exertion, and, increasingly, to better understand cognitive processes. Emotions have been detected using physiological sensors in schools and intelligent tutoring systems.

Emotions as example of psychophysiological studies

Emotions are the most commonly studied aspect of behaviour in psychophysiology. It has long been recognised that physiological responses play a role in emotional episodes. The first studies linking emotions to psychophysiology focused on mapping consistent autonomic nervous system (ANS) responses to discrete emotional states. Anger, for example, could be defined by a specific set of physiological responses, such as increased cardiac output and high diastolic blood pressure, allowing us to better understand and predict emotional responses. Some studies, such as one conducted in 1983 by Paul Ekman and colleagues, were able to detect consistent patterns of ANS responses that corresponded to specific emotions in specific contexts "Emotion-specific activity in the autonomic nervous system was induced by constructing emotion-specific facial prototypes muscle by muscle and reliving past emotional experiences. The produced autonomic activity distinguished not only between positive and negative emotions, but also between negative emotions ".. However, as more studies were conducted, more variability in ANS responses to discrete emotion inductions was discovered, not only among individuals, but also over time in the same individuals, and significantly across social groups. Some of these differences can be attributed to variables such as induction technique, study context, or stimuli classification, which can change a perceived scenario or emotional response. However, it was discovered that participant characteristics could also influence ANS responses. Factors such as basal level of arousal during experimentation or between test recovery, learned or conditioned responses to specific stimuli, range and maximal level of effect of ANS action, and individual attentiveness can all alter physiological responses in a lab setting. Even ostensibly distinct emotional states lack specificity. Some emotional typologists, for example, believe that fear has subtypes that include fleeing or freezing, both of which can have distinct physiological patterns and potentially distinct neural circuitry. As a result, no definitive correlation can be drawn between specific autonomic patterns and discrete emotions, prompting emotion theorists to reconsider traditional definitions of emotions.

Psychophysiological inference and physiological computer games

Physiological computing is a subcategory of affective computing that includes real-time software adaptation to the user's psychophysiological activity. The overarching goal is to create a computer that responds to user emotion, cognition, and motivation. The approach involves granting the software access to a representation of the user's psychological status in order to enable implicit and symmetrical human-computer communication.

There are several methods for representing the user's psychological state (discussed in the affective computing page). The benefits of using psychophysiological indices are that their changes are continuous, the measurements are covert and implicit, and they are the only available data source when the user interacts with the computer without using any explicit communication or input device. These systems are predicated on the assumption that the psychophysiological measure accurately represents a relevant psychological dimension such as mental effort, task engagement, and frustration.

All physiological computing systems contain an element known as an adaptive controller, which can be used to represent the player. This adaptive controller represents the decision-making process that is at the heart of software adaptation. Adaptive controllers are expressed in their most basic form as Boolean statements. Adaptive controllers include not only the decision-making rules, but also the psychophysiological inference implied in the quantification of the trigger points that activate the rules. When using an adaptive controller, the representation of the player can become very complex, but it is often only one-dimensional. The biocybernetic loop is the term used to describe this process. The biocybernetic loop describes a closed loop system that receives psychophysiological data from the player, converts that data into a computerised response, and then shapes the player's future psychophysiological response. As the player-software loop strives for a higher level of desirable performance, a positive control loop becomes unstable. The adaptive controller in the physiological computer game may include both positive and negative loops.


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