Intraparietal Sulcus

A study involving 218 participants aged 18-88 has looked at the effects of age on the brain activity of participants viewing an edited version of a 1961 Hitchcock TV episode (given that participants viewed the movie while in a MRI machine, the 25 minute episode was condensed to 8 minutes).

While many studies have looked at how age changes brain function, the stimuli used have typically been quite simple. This thriller-type story provides more complex and naturalistic stimuli.

Younger adults' brains responded to the TV program in a very uniform way, while older adults showed much more idiosyncratic responses. The TV program (“Bang! You're dead”) has previously been shown to induce widespread synchronization of brain responses (such movies are, after all, designed to focus attention on specific people and objects; following along with the director is, in a manner of speaking, how we follow the plot). The synchronization seen here among younger adults may reflect the optimal response, attention focused on the most relevant stimulus. (There is much less synchronization when the stimuli are more everyday.)

The increasing asynchronization with age seen here has previously been linked to poorer comprehension and memory. In this study, there was a correlation between synchronization and measures of attentional control, such as fluid intelligence and reaction time variability. There was no correlation between synchronization and crystallized intelligence.

The greatest differences were seen in the brain regions controlling attention (the superior frontal lobe and the intraparietal sulcus) and language processing (the bilateral middle temporal gyrus and left inferior frontal gyrus).

The researchers accordingly suggested that the reason for the variability in brain patterns seen in older adults lies in their poorer attentional control — specifically, their top-down control (ability to focus) rather than bottom-up attentional capture. Attentional capture has previously been shown to be well preserved in old age.

Of course, it's not necessarily bad that a watcher doesn't rigidly follow the director's manipulation! The older adults may be showing more informed and cunning observation than the younger adults. However, previous studies have found that older adults watching a movie tend to vary more in where they draw an event boundary; those showing most variability in this regard were the least able to remember the sequence of events.

The current findings therefore support the idea that older adults may have increasing difficulty in understanding events — somthing which helps explain why some old people have increasing trouble following complex plots.

The findings also add to growing evidence that age affects functional connectivity (how well the brain works together).

It should be noted, however, that it is possible that there could also be cohort effects going on — that is, effects of education and life experience.

Research has shown that younger adults are better decision makers than older adults — a curious result. A new study tried to capture more ‘real-world’ decision-making, by requiring participants to evaluate each result in order to strategize the next choice.

This time (whew!), the older adults did better.

In the first experiment, groups of older (60-early 80s) and younger (college-age) adults received points each time they chose from one of four options and tried to maximize the points they earned.  For this task, the younger adults were more efficient at selecting the options that yielded more points.

In the second experiment, the rewards received depended on the choices made previously.  The “decreasing option” gave a larger number of points on each trial, but caused rewards on future trials to be lower. The “increasing option” gave a smaller reward on each trial but caused rewards on future trials to increase.  In one version of the test, the increasing option led to more points earned over the course of the experiment; in another, chasing the increasing option couldn’t make up for the points that could be accrued grabbing the bigger bite on each trial.

The older adults did better on every permutation.

Understanding more complex scenarios is where experience tells. The difference in performance also may reflect the different ways younger and older adults use their brains. Decision-making can involve two different reward learning systems, according to recent thinking. In the model-based system, a cognitive model is constructed that shows how various actions and their rewards are connected to each other. Decisions are made by simulating how one decision will affect future decisions. In the model-free system, on the other hand, only values associated with each choice are considered.

These systems are rooted in different parts of the brain. The model-based system uses the intraparietal sulcus and lateral prefrontal cortex, while the model-free system uses the ventral striatum. There is some evidence that younger adults use the ventral striatum (involved in habitual, reflexive learning and immediate reward) for decision-making more than older adults, and older adults use the dorsolateral prefrontal cortex (involved in more rational, deliberative thinking) more than younger adults.

If our brains are full of clusters of neurons resolutely only responding to specific features (as suggested in my earlier report), how do we bring it all together, and how do we switch from one point of interest to another? A new study using resting state data from 58 healthy adolescents and young adults has found that the intraparietal sulcus, situated at the intersection of visual, somatosensory, and auditory association cortices and known to be a key area for processing attention, contains a miniature map of all the things we can pay attention to (visual, auditory, motor stimuli etc).

Moreover, this map is copied in at least 13 other places in the brain, all of which are connected to the intraparietal sulcus. Each copy appears to do something different with the information. For instance, one map processes eye movements while another processes analytical information. This map of the world may be a fundamental building block for how information is represented in the brain.

There were also distinct clusters within the intraparietal sulcus that showed different levels of connectivity to auditory, visual, somatosensory, and default mode networks, suggesting they are specialized for different sensory modalities.

The findings add to our understanding of how we can shift our attention so precisely, and may eventually help us devise ways of treating disorders where attention processing is off, such as autism, attention deficit disorder, and schizophrenia.

[1976] Anderson JS, Ferguson MA, Lopez-Larson M, Yurgelun-Todd D. Topographic maps of multisensory attention. Proceedings of the National Academy of Sciences [Internet]. 2010 ;107(46):20110 - 20114. Available from:

Older news items (pre-2010) brought over from the old website

September 2009

Learning to juggle grows white matter

A study in which 24 young adults practiced juggling for half an hour a day for six weeks found that they grew more white matter in the area underlying the intraparietal sulcus. This occurred in all the jugglers, regardless of skill, suggesting it's the learning process itself that is important. Previous research has found that juggling increases grey matter. After four weeks without juggling, the new white matter remained and the amount of grey matter had even increased.

[241] Scholz J, Klein MC, Behrens TEJ, Johansen-Berg H. Training induces changes in white-matter architecture. Nat Neurosci [Internet]. 2009 ;12(11):1370 - 1371. Available from:

December 2006

Watching with intent to repeat ignites key learning area of brain

Observing an activity engaged the same brain regions involved in actually performing the motor sequence, but observing with the intention of later replicating the activity increased the degree of activity in those regions and the greater the activity in one of these regions (the intraparietal sulcus), the better the actions were subsequently reproduced.

Frey, S.H. & Gerry, V.E. 2006. Modulation of Neural Activity during Observational Learning of Actions and Their Sequential Orders. Journal of Neuroscience, 26, 13194-13201.

May 2005

Brain networks change according to cognitive task

Using a newly released method to analyze functional magnetic resonance imaging, researchers have demonstrated that the interconnections between different parts of the brain are dynamic and not static. Moreover, the brain region that performs the integration of information shifts depending on the task being performed. The study involved two language tasks, in which subjects were asked to read individual words and then make a spelling or rhyming judgment. Imaging showed that the lateral temporal cortex (LTC) was active for the rhyming task, while the intraparietal sulcus (IPS) was active for the spelling task. The inferior frontal gyrus (IFG) and the fusiform gyrus (FG) were engaged by both tasks. However, Dynamic Causal Modeling (the new method for analyzing imaging data) revealed that the network took different configurations depending on the goal of the task, with each task preferentially strengthening the influences converging on the task-specific regions (LTC for rhyming, IPS for spelling). This suggests that task specific regions serve as convergence zones that integrate information from other parts of the brain. Additionally, switching between tasks led to changes in the influence of the IFG on the task-specific regions, suggesting the IFG plays a pivotal role in making task-specific regions more or less sensitive. This is consistent with previous studies showing that the IFG is active in many different language tasks and plays a role in integrating brain regions.

Bitan, T., Booth, J.R., Choy, J., Burman, D.D., Gitelman, D.R. & Mesulam, M-M. 2005. Shifts of Effective Connectivity within a Language Network during Rhyming and Spelling. Journal of Neuroscience, 25, 5397-5403.

May 2001

Significant brain differences between professional musicians trained at an early age and non-musicians

Research has revealed significant differences in the gray matter distribution between professional musicians trained at an early age and non-musicians, specifically in the primary sensorimotor regions, the left more than the right intraparietal sulcus region, left basal ganglia region, left posterior perisylvian region, and the cerebellum. It is most likely that this is due to intensive musical training at an early age, although it is also possible that the musicians were born with these differences, which led them to pursue musical training.

Schlaug, G. & Christian, G. Paper presented May 7 at the American Academy of Neurology's 53rd Annual Meeting in Philadelphia, PA.