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February 5, 2010

Brain change

Cutting-edge imaging technology shows that monkeys’ brains grow as they learn to use tools

Figure 1: Macaque monkeys rarely use tools in the wild, but they can be taught, and it appears that their brains change in response to these new tasks.

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Many scientists once believed that the human brain doesn’t change significantly after a person reaches maturity. This opinion has been overturned in the last few decades as studies have revealed that the brain has a very flexible structure, even in adulthood, and changes considerably according to use.

Now, Atsushi Iriki at the RIKEN Brain Science Institute (BSI) in Wako and colleagues have directly observed changes in the brain structure of macaque monkeys, while the monkeys were being taught to use tools1. The study, performed using a non-invasive imaging technique, is the first to reveal significant changes in the brain of an individual animal, and could provide insight into the evolution of human intelligence.

Growth through learning

Figure 2: MRI images of the brain showing the areas around the intraparietal sulcus (IPS), superior temporal sulcus (STS) and the secondary somatosensory area (SII) in which gray matter increased as monkeys learned to use a rake tool to retrieve food (CS, central sulcus; IPS, intraparietal sulcus; LS, lateral sulcus).

Reproduced from Ref. 1 © 2009 by National Academy of Sciences USA

Several research groups have measured changes in human brain structure by analyzing the brains of experts in a particular field and comparing them to non-experts. This work has revealed, for example, that London taxi drivers, who have to remember a huge network of streets, display enhanced growth in the hippocampus region associated with spatial memory, and expert musicians have larger auditory and motor cortices thanks to their years of practice.

Iriki was particularly inspired by a study conducted by German scientists in 2004, in which human volunteers were trained to juggle over a three-month period. After the training, the volunteers showed increased gray matter in regions of the brain associated with motor skills2. Iriki was keen to discover whether these effects could be observed in macaque monkeys (Fig. 1).

“In our previous work, we found that neurons in the intraparietal cortex of monkeys trained to use tools change their receptive field properties to represent tools as an extension of the body parts holding them,” he explains. Iriki and his colleagues observed gene expression in the same areas, and the growth of new axons and synapses. This suggests that tool-use training might induce rapid structural changes in the brain, at least on a microscopic scale.

“So, when I read the paper describing expansion of cortical gray matter in jugglers, I decided to do a similar study in monkeys,” says Iriki.

Scanning in stages

Macaque monkeys rarely use tools in the wild, but can master basic tools after a few weeks training. To gain insight into this learning process the researchers used magnetic resonance imaging (MRI) to examine the brains of three monkeys before, during, and after training them to use a rake to retrieve food that was just out of reach.

The researchers used a technique called voxel-based morphometry (VBM) to classify areas of brain tissue in their MRI images as grey matter, white matter, or cerebro-spinal fluid, and to compare the volume of each tissue at different stages of learning. The work was possible thanks to a fruitful collaboration between RIKEN BSI and the Institute of Neurology at University College London (UCL).

“Marsha Maria Quallo, a PhD student from UCL, came to BSI to train the monkeys and analyze behavioral data, during which time she acquired structural MRI images using our high resolution scanner,” explains Iriki. “She took the MRI data back to London and analyzed them under supervision of VBM experts there.”

The analysis showed that the MRI signal from some areas of gray matter increased, suggesting their volume in the monkey’s brains increased as the monkeys got better at using the tool. The growth was mainly in areas around the superior temporal sulcus (STS), intraparietal sulcus (IPS), and the secondary somatosensory area (SII) which all belong to a network previously associated with tool use (Fig. 2). The researchers also noticed an increase in signals, suggesting volume expansion, from white matter in the cerebellum, which is well known as having a role in motor control.

The benefit of monkey models

The study is important because it is the first to detect statistically significant brain structure changes in individual animals, compared to human studies that pooled data from several people.

“Although there have been some human VBM studies suggesting gray matter expansions in experts, they could only be detected in group analyses by comparing between groups of experts and non-experts,” Iriki explains. “In contrast, we detected large changes in specific brain regions by using animals that were naïve to the task, and showed for the first time that these can be detected in individual animals.”

For example, the juggling study reported only a 3% increase in signals averaged across twelve volunteers, whereas the individual macaques in Iriki’s study showed up to 17% signal increase in some areas. The changes may be larger in the monkeys because they had never used tools, unlike humans who would have already performed many skilled motor tasks. This illustrates that monkeys are an ideal model for studying such brain changes.

Looking deeper

Iriki and colleagues now hope to discover exactly how different brain areas increase in volume when learning a task, on a cellular, genetic and molecular basis.

“Our study opens up the means to study concrete neurobiological mechanisms underlying gray matter expansion, which we have actually already started,” says Iriki. “We are particularly keen, in collaboration with other groups in Japan, on using marmosets—smaller primates in which transgenic techniques are available.”

Most interestingly, Iriki points out that the brain areas highlighted in his study correspond closely to the cortical areas that expanded most while primates were evolving into humans.

“I would hope this could give us some clues to understanding human intellectual evolution,” he says.

References

  1. Quallo, M.M., Price, C.J., Ueno, K., Asamizuya, T., Cheng, K., Lemon, R.N. & Iriki, A. Gray and white matter changes associated with tool-use learning in macaque monkeys. Proceedings of the National Academy of Sciences USA 106, 18379–18384 (2009).  (Link)
  2. Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U. & May, A. Neuroplasticity: Changes in grey matter induced by training. Nature 427, 311–312 (2004). (Link)

About the Researcher

Atsushi Iriki

Atsushi Iriki received his Ph.D. in Neurophysiology from Tokyo Medical and Dental University in 1986. He held research associate positions at the Tokyo Medical and Dental University and then at the Rockefeller University. He joined the faculty of Toho University Medical School as an assistant professor and as an associate professor in Physiology  (1991-1999). In 1999, he returned to Tokyo Medical and Dental University as a full professor in Cognitive Neurobiology. Atsushi Iriki is now a Head of Laboratory for Symbolic Cognitive Development at RIKEN Brain Science Institute since 2004. He is an adjunct professor of Tokyo Medical and Dental University, The University of Tokyo, Keio University, and a visiting senior fellow of University College London. Based on behavioral and neurophysiological analyses on chronic macaque monkeys, which were trained to use tools and other high-tech apparatus, he tries to uncover evolutionary precursors of human higher cognitive functions grounded onto physical morphologies and patterns of structured bodily actions. He extrapolates these mechanisms to constitute bases of communicatory functions by sharing above machineries among individuals, and eventually understand neural mechanism of social behaviors. Further, he is aiming at extending these mechanisms onto evolutionary as well as developmental clues of symbolic cognitive functions to subserve inference, metaphysical thoughts etc. that characterise human intelligence.