Brain states

Tang, Rothbart and Posner have a new paper reviewing the neural correlates of three brain states (citation below). The states that were reviewed were rest, being alert (waiting for a target and responding to it), and meditation (Integrative Body-Mind training in three stages of training). They looked at the switching between these and the maintenance of them over time.


One very interesting result: the resting state is not ‘restful’ in the ordinary sense.

Although the resting state does not involve an external task, it shows strong activation of a number of brain areas, some of which show reduced activation during task performance, and it consumes a greater amount of energy in comparison with task-evoked states. The resting state accounts for much of the metabolic activity of the human brain, with specific activations during tasks involving only small changes (about 5%).


The active networks in rest are:

medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and posterior cingulate cortex (PCC), often called the Default Mode Network (DMN), along with a number of other areas that are active and correlated at rest.


The alert state seems to be a suppression of activity when the target is expected, until it appears. Before the target the parasympathetic system is more active and during response, it is the sympathetic that is active. The authors assume that this is the result of ACC levels of activity.

(The suppression of activity is show in the) Contingent Negative Variation (CNV): a negative direct current shift in electrophysiological recordings that occurs when a warning signal leads one to prepare for an upcoming target. … This negative change appears to arise, at least in part, in ACC and adjacent structures. The CNV may arise within 100 ms after the warning .


They discuss the release of norepinepherine (NE) from the locus coeruleus . This results in changes in the recognition of the target.

How does the alert state influence task performance? The warning increases rapid motor responses to signals. However, it appears to accomplish this in a specific way . The alert state speeds the motor response without altering signal quality. This accords with the anatomical distribution of NE (norepinepherine), which does not appear to influence the ventral pathways involved in object recognition. … whereas the response is speeded, the quality of information to which the person responds is reduced, resulting in increased error rates. Posner argued that these effects can be understood if the warning signal allows faster input to parts of the brain that mediate conscious detection of the target. This allows not only for enhanced overt response, but also for the priority of the signal to consciousness.


The work on mediation is very specific to a particular type and its stages of learning. There may be great similarities between the neural correlates of the different methods of mediation – or there may not. The neural correlates involved in changes of state are summarized in the IAS hypothesis.

Key neural correlates of changing brain states include the insula, ACC, and striatum (IAS). The ACC is involved in maintaining a state by reducing conflict with other states; the insula serves a primary role in switching between states; the striatum is linked to the reward experience and formation of habits required to make state maintenance easier.


I hope this group and others continue this type of study. Here is the paper’s abstract:

Although the study of brain states is an old one in neuroscience, there has been growing interest in brain state specification owing to MRI studies tracing brain connectivity at rest. In this review, we summarize recent research on three relatively well-described brain states: the resting, alert, and meditation states. We explore the neural correlates of maintaining a state or switching between states, and argue that the anterior cingulate cortex and striatum play a critical role in state maintenance, whereas the insula has a major role in switching between states. Brain state may serve as a predictor of performance in a variety of perceptual, memory, and problem solving tasks. Thus, understanding brain states is critical for understanding human performance.

Yi-Yuan Tang, Mary K. Rothbart, & Michael I. Posner (2012). Neural correlates of establishing, maintaining, and switching brain states Trends in Cognitive Sciences, 16 (6) DOI: 10.1016/j.tics.2012.05.001

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