Cognitive science

Cognitive Science is the scientific study of the mind and brain and how they give rise to behavior. The field is highly interdisciplinary and is closely related to several other areas, including psychology (especially cognitive psychology), artificial intelligence, linguistics and psycholinguistics, philosophy (especially philosophy of mind), neuroscience, logic, robotics, anthropology and biology (including biomechanics).

Experimental methods

Many different methodologies are used to study cognitive science. The types of methodologies are closely related to the levels of analysis.

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Behavioral methods

These methods are often used to investigate cognitive phenomena at the behavioral level of analysis.

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• Reaction time: The time between the presentation of a stimulus and an appropriate response can indicate differences between two cognitive processes, and can indicate some things about their nature. For example, if in a search task the reaction times vary proportionally with the number of elements, then it is evident that this cognitive process of searching involves serial and not parallel processing.
• Psychophysical responses: Psychophysical experiments are an old psychological technique which have been adopted by cognitive psychology. They typically involve making judgements of some physical property, e.g. the loudness of a sound. Correlation of subjective scales between individuals can show cognitive or sensory biases as compared to actual physical measurements. Some examples include:
• sameness judgements for colors, tones, textures, etc.
• threshold differences for colors, tones, textures, etc.
• Eye tracking: This methodology is used to study a variety of cognitive processes, most notably visual perception and language processing. The fixation point of the eyes is linked to an individual's focus of attention. Thus, by monitoring eye movements, we can study what information is being processed at a given time. Eye tracking allows us to study cognitive processes on extremely short time scales. Eye movements reflect online decision making during a task, and they provide us with some insight into the ways in which those decisions may be processed.

Brain imaging

Brain imaging involves analyzing activity within the brain while performing various cognitive tasks. Different types of imaging techniques vary in their temporal (time-based) and spatial (location-based) resolution.

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• EEG: Electroencephalography (EEG) measures the electrical fields generated by large populations of neurons in the cortex by placing a series of electrodes on the scalp of the subject. This technique has an extremely high temporal resolution, but a relatively poor spatial resolution.
• fMRI: fMRI measures the relative amount of oxygenated blood flowing to different parts of the brain. More oxygenated blood in a particular region is correlated with an increase in neural activity in that part of the brain. This allows us to localize particular functions within different brain regions. fMRI has moderate spatial and temporal resolution.
• Positron emission tomography PET uses a radioactive isotope, usually in the form of glucose, which is injected into the subject's bloodstream and taken up by the brain. By observing which areas of the brain take up the radioactive isotope, we can see which areas of the brain are more active than others. PET has similar spatial resolution to fMRI, but it has extremely poor temporal resolution.
• Optical imaging: This technique uses infrared transmitters and receivers to measure the amount of light reflectance by blood near different areas of the brain. Since oxygenated and deoxygenated blood reflect light by different amounts, we can study which areas are more active (those that have more oxygenated blood). Optical imaging has moderate temporal resolution, but poor spatial resolution. It also has the advantage that it is extremely safe and can be used to study infants' brains.

Computational methods

• Connectionist models: Connectionism relies on the idea that the mind/brain is composed of simple nodes and that the power of the system comes primarily from the existance, and manner of connections between the simple nodes. Neural nets are textbook implementations of this approach. Some critics of this approach feel that while it may be true as a represtantion of how the system works it does not have explanative powers, as complicated systems of connections with even simple rules are extremely complex, and often less interpretable then the system they model.
• Symbolic models
• Dynamical systems

Neurobiological methods

• Single-cell recording
• Direct brain stimulation
• Animal models
• Lesion patients