effects of stress on cognitive processes

The Role of the Medial Prefrontal Cortex-Amygdala Circuit in Stress Effects on the Extinction of Fear

Irit Akirav¹ and Mouna Maroun²

1	Department of Psychology, The Brain and Behavior Research Center, University of Haifa, Haifa 31905, Israel
2	Department of Neurobiology and Ethology, The Brain and Behavior Research Center, Faculty of Science and Science Education, University of Haifa, Haifa 31905, Israel

Received 15 May 2006; Revised 16 November 2006; Accepted 16 November 2006

Recommended by Georges Chapouthier

 

Stress exposure, depending on its intensity and duration, affects cognition and learning in an adaptive or maladaptive manner. Studies addressing the effects of stress on cognitive processes have mainly focused on conditioned fear, since it is suggested that fear-motivated learning lies at the root of affective and anxiety disorders. Inhibition of fear-motivated response can be accomplished by experimental extinction of the fearful response to the fear-inducing stimulus. Converging evidence indicates that extinction of fear memory requires plasticity in both the medial prefrontal cortex and the amygdala. These brain areas are also deeply involved in mediating the effects of exposure to stress on memory. Moreover, extensive evidence indicates that gamma-aminobutyric acid (GABA) transmission plays a primary role in the modulation of behavioral sequelae resulting from a stressful experience, and may also partially mediate inhibitory learning during extinction. In this review, we present evidence that exposure to a stressful experience may impair fear extinction and the possible involvement of the GABA system. Impairment of fear extinction learning is particularly important as it may predispose some individuals to the development of posttraumatic stress disorder. We further discuss a possible dysfunction in the medial prefrontal cortex-amygdala circuit following a stressful experience that may explain the impaired extinction caused by exposure to a stressor.

Metacognition in the Rat

Allison L. Foote¹ and Jonathon D. Crystal¹,

¹ Department of Psychology, University of Georgia, Athens, Georgia 30602

Corresponding author
Jonathon D. Crystal
jcrystal@uga.edu

The ability to reflect on one’s own mental processes, termed metacognition, is a defining feature of human existence [1, 2]. Consequently, a fundamental question in comparative cognition is whether nonhuman animals have knowledge of their own cognitive states [3]. Recent evidence suggests that people and nonhuman primates [4, 5, 6, 7, 8] but not less “cognitively sophisticated” species [3, 9, 10] are capable of metacognition. Here, we demonstrate for the first time that rats are capable of metacognition—i.e., they know when they do not know the answer in a duration-discrimination test. Before taking the duration test, rats were given the opportunity to decline the test. On other trials, they were not given the option to decline the test. Accurate performance on the duration test yielded a large reward, whereas inaccurate performance resulted in no reward. Declining a test yielded a small but guaranteed reward. If rats possess knowledge regarding whether they know the answer to the test, they would be expected to decline most frequently on difficult tests and show lowest accuracy on difficult tests that cannot be declined [4]. Our data provide evidence for both predictions and suggest that a nonprimate has knowledge of its own cognitive state

How does your brain tell time?

“Time” is the most popular noun in the English language, yet how would we tell time if we didn’t have access to the plethora of watches, clocks and cell phones at our disposal?

For decades, scientists have believed that the brain possesses an internal clock that allows it to keep track of time. Now a UCLA study in the Feb. 1 edition of Neuron proposes a new model in which a series of physical changes to the brain’s cells helps the organ to monitor the passage of time.

“The value of this research lies in understanding how the brain works,” said Dean Buonomano, associate professor of neurobiology and psychiatry at the David Geffen School of Medicine at UCLA and a member of the university’s Brain Research Institute. “Many complex human behaviors — from understanding speech to playing catch to performing music — rely on the brain’s ability to accurately tell time. Yet no one knows how the brain does it.”

The most popular theory assumes that a clock-like mechanism – which generates and counts regular fixed movements — underlies timing in the brain. In contrast, Buonomano suggests a physical model that operates without using a clock. He offers an analogy to explain how it works.

“If you toss a pebble into a lake,” he explained, “the ripples of water produced by the pebble’s impact act like a signature of the pebble’s entry time. The farther the ripples travel the more time has passed.

“We propose that a similar process takes place in the brain that allows it to track time,” he added. “Every time the brain processes a sensory event, such as a sound or flash of light, it triggers a cascade of reactions between brain cells and their connections. Each reaction leaves a signature that enables the brain-cell network to encode time.”

The UCLA team used a computer model to test this theory. By simulating a network of interconnected brain cells in which each connection changed over time in response to stimuli, they were able to show that the network could tell time.

Their simulations indicated that a specific event is encoded within the context of events that precede it. In other words, if one could measure the response of many neurons in the brain to a tone or a flash of light, the response would not only reveal the nature of the event, but the other events that preceded it and when they occurred.

The UCLA team tested the model by asking research volunteers in the study to judge the interval between two auditory tones under a variety of different conditions. The researchers found that volunteers’ sense of timing was impaired when the interval was randomly preceded by a “distracter” tone.

“Our results suggest that the timing mechanisms that underlie our ability to recognize speech and enjoy music are distributed throughout the brain, and do not resemble the conventional clocks we wear on our wrists,” said Buonomano.

Because time-related information is critical to understanding speech, determining how the brain tells time represents an important step toward understanding the causes of diseases, such as dyslexia, that result in impaired linguistic abilities, he noted.

The next step for the research will be recording the response from a large number of brain cells to determine whether they encode information about the timing of stimuli.

Source: University of California – Los Angeles

Meditation produce thicker brain

Meditation has been found to produce structural changes in the brain that could help to offset the effects of aging. It appears – from an imaging study led by Massachusetts General Hospital – that meditation changes the areas of the brain associated with attention and sensory processing.

Meditation practitioners say that meditating can have profound effects on the mind and benefit general mental health, but meditation has been difficult for researchers to study in the past due to the lack of tangible effects.

Now, however, researchers have used magnetic resonance imaging (MRI) to identify specific physical effects associated with meditation. Most interestingly, the effects were observed in ordinary people who meditated, rather than Buddhist monks, who have been the subjects of other studies in the past.

The new study looked at 20 people who practiced Buddhist Insight meditation – which focuses on “mindfulness,” a specific, nonjudgmental awareness of sensations, feelings and state of mind. On average, they meditated for about six hours per week. For comparison, 15 people with no experience of meditation were enrolled as a control group.

After producing detailed images of the participants’ brains using MRI, the researchers found that regions of the brain involved in the mental activities that characterize Insight meditation were thicker in the meditators than in the controls. This provides the first evidence that alterations in brain structure may be associated with meditation. “The area where we see these differences is involved in both the modulation of functions like heart rate and breathing and also the integration of emotion with thought and reward-based decision making – a central switchboard of the brain,” said Sara Lazar, lead author of the study.

The study, in the journal NeuroReport, also found that, in an area associated with the integration of emotional and cognitive processes, differences in cortical thickness were more pronounced in older participants, suggesting that meditation could reduce the thinning of the cortex that typically occurs with aging.

While this is only a small study, it does suggest that meditation could help in staving off age related brain degeneration. “Our results suggest that meditation can produce experience-based structural alterations in the brain. We also found evidence that mediation may slow down the aging-related atrophy of certain areas of the brain,” concluded Lazar.

Source: Massachusetts General Hospital

Neural correlates of error awareness.

Neural correlates of error awareness.

Klein TA, Endrass T, Kathmann N, Neumann J, von Cramon DY, Ullsperger M

Neuroimage. 2007 Feb 15; 34(4): 1774-1781

Error processing results in a number of consequences on multiple levels. The posterior frontomedian cortex (pFMC) is involved in performance monitoring and signalling the need for adjustments, which can be observed as post-error speed-accuracy shifts at the behavioural level. Furthermore autonomic reactions to an error have been reported. The role of conscious error awareness for this processing cascade has received little attention of researchers so far. We examined the neural correlates of conscious error perception in a functional magnetic resonance imaging (fMRI) study. An antisaccade task known to yield sufficient numbers of aware and unaware errors was used. Results from a metaanalysis were used to guide a region of interest (ROI) analysis of the fMRI data. Consistent with previous reports, error-related activity in the rostral cingulate zone (RCZ), the pre-supplementary motor area (pre-SMA) and the insular cortex bilaterally was found. Whereas the RCZ activity did not differentiate between aware and unaware errors, activity in the left anterior inferior insular cortex was stronger for aware as compared to unaware errors. This could be due to increased awareness of the autonomic reaction to an error, or the increased autonomic reaction itself. Furthermore, post-error adjustments were only observed after aware errors and a correlation between post-error slowing and the hemodynamic activity in the RCZ was revealed. The data suggest that the RCZ activity alone is insufficient to drive error awareness. Its signal appears to be useful for post-error speed-accuracy adjustments only when the error is consciously perceived.

Repetition and the brain: neural models of stimulus-specific effects

 Kalanit Grill-Spector^{a, b,} , Richard Henson^c and Alex Martin^d 
 aDepartment of Psychology, Stanford University, Stanford, CA 94305, USA
^bNeurosciences Program, Stanford University, Stanford, CA 94305, USA
^cMRC Cognition and Brain Sciences Unit, Cambridge, UK
^dLaboratory of Brain and Cognition; National Institute of Mental Health, Bethesda, Maryland 20892-1366, USA

Available online 29 November 2005.

One of the most robust experience-related cortical dynamics is reduced neural activity when stimuli are repeated. This reduction has been linked to performance improvements due to repetition and also used to probe functional characteristics of neural populations. However, the underlying neural mechanisms are as yet unknown. Here, we consider three models that have been proposed to account for repetition-related reductions in neural activity, and evaluate them in terms of their ability to account for the main properties of this phenomenon as measured with single-cell recordings and neuroimaging techniques. We also discuss future directions for distinguishing between these models, which will be important for understanding the neural consequences of repetition and for interpreting repetition-related effects in neuroimaging data.