Meditation can be conceptualized as a family of complex emotional and attentional regulatory training regimes developed for various ends, including the cultivation of well-being and emotional balance. Among these various practices, there are two styles that are commonly studied. One style, focused attention meditation, entails the voluntary focusing of attention on a chosen object. The other style, open monitoring meditation, involves nonreactive monitoring of the content of experience from moment to moment. The potential regulatory functions of these practices on attention and emotion processes could have a long-term impact on the brain and behavior.

PrefaceIt has been argued that emotion, pain, and cognitive control are functionally segregated in distinct subdivisions of the cingulate cortex. But recent observations encourage a fundamentally different view. Imaging studies indicate that negative affect, pain, and cognitive control activate an overlapping region of dorsal cingulate, the anterior midcingulate cortex (aMCC). Anatomical studies reveal that aMCC constitutes a hub where information about reinforcers can be linked to motor centers responsible for expressing affect and executing goal-directed behavior. Computational modeling and other kinds of evidence suggest that this intimacy reflects control processes that are common to all three domains. These observations compel a reconsideration of dorsal cingulate's contribution to negative affect and pain. † Manuscript Correspondence: Alexander J. Shackman (shackman@wisc.edu) or Tim V. Salomons (tvsalomons@gmail.com) Competing Interests StatementThe authors declare no competing financial interests. NIH Public Access Author ManuscriptNat Rev Neurosci. Author manuscript; available in PMC 2011 September 1. IntroductionIn humans and other primates, the cingulate, a thick belt of cortex encircling the corpus callosum, is one of the most prominent features on the mesial surface of the brain ( Figure 1a). Early research suggested that the rostral cingulate gyrus (Brodmann's 'precingulate' 1 ; architectonic areas 24, 25, 32, and 33) plays a key role in affect and motivation (Figure 1b) 2 .More recent research has enlarged the breadth of functions ascribed to this region; in addition to emotion 3 , the rostral cingulate plays a central role in contemporary models of pain 4, 5 and cognitive control 6,7 . Work in these three basic domains has, in turn, strongly influenced prominent models of social behavior 8 , psychopathology [9][10][11] , and neurological disorders 12 .Despite this progress, key questions about the functional organization and significance of activity in the rostral cingulate remain unresolved. Perhaps the most basic question is whether emotion, pain, and cognitive control are segregated into distinct subdivisions of the rostral cingulate or are instead integrated in a common region. In a pair of landmark reviews, Devinsky et al. 13 and Bush et al. 14 marshaled a broad range of functional imaging, electrophysiological, and anatomical data in support of functional segregation, arguing that the anterior cingulate cortex (ACC or 'rostral' ACC) is specialized for affective processes, whereas the midcingulate cortex (MCC or 'dorsal' ACC) is specialized for cognitive processes (Figure 1c, 1d). Subsequent meta-analyses of imaging studies have provided some support for this claim 15 .Although the segregationist model remains highly influential, new data suggests that it is no longer tenable. For instance, recent imaging data implicate MCC in the regulation of autonomic activity 16,17 and the perception and production of emotion 3,18 . Likewise, neuronal recordings demonstrate that MCC is responsive to ...

The information processing capacity of the human mind is limited, as is evidenced by the so-called “attentional-blink” deficit: When two targets (T1 and T2) embedded in a rapid stream of events are presented in close temporal proximity, the second target is often not seen. This deficit is believed to result from competition between the two targets for limited attentional resources. Here we show, using performance in an attentional-blink task and scalp-recorded brain potentials, that meditation, or mental training, affects the distribution of limited brain resources. Three months of intensive mental training resulted in a smaller attentional blink and reduced brain-resource allocation to the first target, as reflected by a smaller T1-elicited P3b, a brain-potential index of resource allocation. Furthermore, those individuals that showed the largest decrease in brain-resource allocation to T1 generally showed the greatest reduction in attentional-blink size. These observations provide novel support for the view that the ability to accurately identify T2 depends upon the efficient deployment of resources to T1. The results also demonstrate that mental training can result in increased control over the distribution of limited brain resources. Our study supports the idea that plasticity in brain and mental function exists throughout life and illustrates the usefulness of systematic mental training in the study of the human mind.

The capacity to stabilize the content of attention over time varies among individuals, and its impairment is a hallmark of several mental illnesses. Impairments in sustained attention in patients with attention disorders have been associated with increased trial-to-trial variability in reaction time and event-related potential deficits during attention tasks. At present, it is unclear whether the ability to sustain attention and its underlying brain circuitry are transformable through training. Here, we show, with dichotic listening task performance and electroencephalography, that training attention, as cultivated by meditation, can improve the ability to sustain attention. Three months of intensive meditation training reduced variability in attentional processing of target tones, as indicated by both enhanced theta-band phase consistency of oscillatory neural responses over anterior brain areas and reduced reaction time variability. Furthermore, those individuals who showed the greatest increase in neural response consistency showed the largest decrease in behavioral response variability. Notably, we also observed reduced variability in neural processing, in particular in low-frequency bands, regardless of whether the deviant tone was attended or unattended. Focused attention meditation may thus affect both distracter and target processing, perhaps by enhancing entrainment of neuronal oscillations to sensory input rhythms, a mechanism important for controlling the content of attention. These novel findings highlight the mechanisms underlying focused attention meditation and support the notion that mental training can significantly affect attention and brain function.

Although the adult brain was once seen as a rather static organ, it is now clear that the organization of brain circuitry is constantly changing as a function of experience or learning. Yet, research also shows that learning is often specific to the trained stimuli and task, and does not improve performance on novel tasks, even very similar ones. This perspective examines the idea that systematic mental training, as cultivated by meditation, can induce learning that is not stimulus or task specific, but process specific. Many meditation practices are explicitly designed to enhance specific, well-defined core cognitive processes. We will argue that this focus on enhancing core cognitive processes, as well as several general characteristics of meditation regimens, may specifically foster process-specific learning. To this end, we first define meditation and discuss key findings from recent neuroimaging studies of meditation. We then identify several characteristics of specific meditation training regimes that may determine process-specific learning. These characteristics include ongoing variability in stimulus input, the meta-cognitive nature of the processes trained, task difficulty, the focus on maintaining an optimal level of arousal, and the duration of training. Lastly, we discuss the methodological challenges that researchers face when attempting to control or characterize the multiple factors that may underlie meditation training effects.

Previous research has identified a component of the event-related brain potential (ERP), the feedback-related negativity, that is elicited by feedback stimuli associated with unfavourable outcomes. In the present research we used event-related functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) recordings to test the common hypothesis that this component is generated in the caudal anterior cingulate cortex. The EEG results indicated that our paradigm, a time estimation task with trial-to-trial performance feedback, elicited a large feedback-related negativity (FRN). Nevertheless, the fMRI results did not reveal any area in the caudal anterior cingulate cortex that was differentially activated by positive and negative performance feedback, casting doubt on the notion that the FRN is generated in this brain region. In contrast, we found a number of brain areas outside the posterior medial frontal cortex that were activated more strongly by positive feedback than by negative feedback. These included areas in the rostral anterior cingulate cortex, posterior cingulate cortex, right superior frontal gyrus, and striatum. An anatomically constrained source model assuming equivalent dipole generators in the rostral anterior cingulate, posterior cingulate, and right superior frontal gyrus produced a simulated scalp distribution that corresponded closely to the observed scalp distribution of the FRN. These results support a new hypothesis regarding the neural generators of the FRN, and have important implications for the use of this component as an electrophysiological index of performance monitoring and reward processing.

The information processing capacity of the human mind is limited, as is evidenced by the attentional blink-a deficit in identifying the second of two targets (T1 and T2) presented in close succession. This deficit is thought to result from an overinvestment of limited resources in T1 processing. We previously reported that intensive mental training in a style of meditation aimed at reducing elaborate object processing, reduced brain resource allocation to T1, and improved T2 accuracy [Slagter, H. A., Lutz, A., Greisschar, L. L., Frances, A. D., Nieuwenhuis, S., Davis, J., et al. Mental training affects distribution of limited brain resources. PloS Biology, 5, e138, 2007]. Here we report EEG spectral analyses to examine the possibility that this reduction in elaborate T1 processing rendered the system more available to process new target information, as indexed by T2-locked phase variability. Intensive mental training was associated with decreased cross-trial variability in the phase of oscillatory theta activity after successfully detected T2s, in particular, for those individuals who Bullock, McClune, & Enright, 2003 Sinkkonen, Tiitinen, & Näätänen, 1995 1 This simulation used the EEG data from 17 participants that had at least 80 no-blink trials at Time 1 (7 practitioners) and focused on the theta frequency band (4.1-8.5 Hz) and a time period of 300-350 msec post-T1. This was done as preliminary analyses using all participants showed phase locking of this band to T1 for this time window at Time 1 (see also below). For each participant, normalized PLF values were calculated based on different subsets of trials varying in size (n = 20, 30, 40, 50, 60, 70, or 80). These trials were randomly selected from the total number of trials available. Analyses revealed that although the pattern of results was unstable (i.e., which electrodes showed significant phase locking) when 20 or 30 trials were included, when 40 or more trials were included, the same pattern of results emerged in each analysis. Although the inclusion of more than 40 trials increased normalized PLF values, the overall scalp topography of significant theta phase-locking effects did not differ appreciably between the analyses using 40 or more trials. Thus, a minimum of 40 trials appears necessary to obtain reliable phase-locking estimates. 2 This conclusion is further strengthened by an additional analysis, which directly compared target phase locking in no-blink and blink trials at Time 1. Due to our requirement of at least 40 trials per trial type for reliable phase-locking estimates (see Methods), only 14 participants could be included in this analysis. We therefore collapsed across groups. A significant main effect of condition (blink, noblink) was observed over the same midline frontal (maximal at Fz at 266 msec post-T2; p = .023) and right ventrolateral frontal (maximal at FC6 at 406 msec post-T2: p = .005) scalp regions that showed a mental training-related increase in theta phase locking in no-blink trials over time. This effect reflect...

Behavioral studies have shown that consistent practice of a cognitive task can increase the speed of performance and reduce variability of responses and error rate, reflecting a shift from controlled to automatic processing. This study examines how the shift from controlled to automatic processing changes brain activity. A verbal Sternberg task was used with continuously changing targets (novel task, NT) and with constant, practiced targets (practiced task, PT). NT and PT were presented in a blocked design and contrasted to a choice reaction time (RT) control task (CT) to isolate working memory (WM)-related activity. The three-dimensional (3-D) PRESTO functional magnetic resonance imaging (fMRI) sequence was used to measure hemodynamic responses. Behavioral data revealed that task processing became automated after practice, as responses were faster, less variable, and more accurate. This was accompanied specifically by a decrease in activation in regions related to WM (bilateral but predominantly left dorsolateral prefrontal cortex (DLPFC), right superior frontal cortex (SFC), and right frontopolar area) and the supplementary motor area. Results showed no evidence for a shift of foci of activity within or across regions of the brain. The findings have theoretical implications for understanding the functional anatomical substrates of automatic and controlled processing, indicating that these types of information processing have the same functional anatomical substrate, but differ in efficiency. In addition, there are practical implications for interpreting activity as a measure for task performance, such as in patient studies. Whereas reduced activity can reflect poor performance if a task is not sensitive to practice effects, it can reflect good performance if a task is sensitive to practice effects.