One of the most critical and common features of tool use is that the tool essentially functions as a part of the body. This feature is likely rooted in biological features that are shared by tool users. To establish an ideal primate model to explore the neurobiological mechanisms supporting tool-use behaviours, we trained common marmosets, a small New World monkey species that is not usually associated with tool use, to use a rake-shaped tool to retrieve food. Five naive common marmosets were systematically trained to manipulate the tool using a 4-stage, step-by-step protocol. The relative positions of the tool and the food were manipulated, so that the marmosets were required to (1) pull the tool vertically, (2) move the tool horizontally, (3) make an arc to retrieve a food item located behind the tool and (4) retrieve the food item. We found considerable individual differences in tool-use technique; for example, one animal consistently used a unilateral hand movement for all of the steps, whereas the others (n = 4) used both hands to move the tool depending on the location of the food item. After extensive training, all of the marmosets could manipulate the rake-shaped tool, which is reported in this species for the first time. The common marmoset is thus a model primate for such studies. This study sets the stage for future research to examine the biological mechanisms underlying the cognitive ability of tool use at the molecular and genetic levels.Electronic supplementary materialThe online version of this article (doi:10.1007/s00221-011-2778-9) contains supplementary material, which is available to authorized users.

Working memory is used to solve various cognitive problems by maintaining information for some time and then by refreshing this information after certain purposes are achieved. In the present study, we explored the ability of common marmosets to perform a delayed matching to position (DMTP) task in a controlled environment using operant conditioning. The DMTP task requires the subjects to respond to the sample stimulus and to select one of two comparison stimuli with a position matching that of the sample stimulus after a programmed delay period. Positional arrangement of the sample and comparison stimuli, which were quasi-randomly determined in each trial, was employed to prevent the subjects from using any strategies based on their own body positions or orientations. The delay intervals between presentations of the sample and comparison stimuli were fixed at 0.5 and 1s in the initial phases and were then varied between 5 intervals per delay set (e.g., 0.5, 1, 2, 4, and 8s) intermixed in a session. The longest delay interval within a set was gradually increased after the marmosets achieved the criterion of each task. The subjects were successfully trained in the procedure and showed accurate performance even following delays of more than 100 s. The response times in the trials suggested that they used different strategies depending on the delay interval length. Thus, the present study shows the robust ability of common marmosets in a task requiring positional memory, which is related to their foraging strategy observed in the wild.

Whether animals use relational cues in transposition tests has long been considered a controversial issue. In the present study, we examined whether common marmosets could generalize relational responses to untrained stimulus pairs and further apply these generalizations to unknown shapes. The subjects were trained to perform simple discrimination tasks using a pair of stimuli. The stimuli differed in size, and the subjects were required to select the larger or smaller of the 2 sizes, depending on the given contingencies. After experiencing several reversals, the subjects were examined using 2 different tests: transposition and shape generalization. In the transposition test trials, in which squares of different sizes than those used in the training trials were presented, the subjects selected the stimulus based on the relative size of the stimulus. In the shape generalization tests, sets of 5 novel shapes with the same relative sizes were presented with the training stimuli. The subjects' performance indicated successful transposition to the novel stimulus pairs, and further analysis showed that transposition was more likely to occur when the test stimuli shared physical features, such as the outer length and the number of line segments, with the trained stimuli. Thus, the present study demonstrated the robust ability of transposition in common marmosets based on relative size, both with and without common shape features, and offered a possible method for specifying the critical stimulus features through which transposition can be more readily observed.

Complex motor skills of eventual benefit can be learned after considerable trial and error. What do structural brain changes that accompany such effortful long-term learning tell us about the mechanisms for developing innovative behavior? Using MRI, we monitored brain structure before, during and after four marmosets learnt to use a rake, over a long period of 10–13 months. Throughout learning, improvements in dexterity and visuo-motor co-ordination correlated with increased volume in the lateral extrastriate cortex. During late learning, when the most complex behavior was maintained by sustained motivation to acquire the skill, the volume of the nucleus accumbens increased. These findings reflect the motivational state required to learn, and show accelerated function in higher visual cortex that is consistent with neurocognitive divergence across a spectrum of primate species.

Abstracts / Neuroscience Research 71S (2011) e108-e415 e373 coding neurons. Neurons whose phasic or tonic response to the CS presentation was positively correlated with the reward probability were classified as stimulus value coding neurons. Neurons whose activity increased before the delivery of an expected reward were classified as reward expectation coding neurons. We then examined sensitivity to time discounting for these neurons by increasing the duration of the delay period. With increasing delay, the CS response decreased and the reward response increased in the RPE coding neurons, which may be due to an increase of unpredictability of the reward; the CS response decreased in the stimulus value coding neurons, which may be due to a decrease of the stimulus value, and the activity decreased and its peak latency shifted toward the new time of the reward delivery in the reward expectation coding neurons, which may be due to the animal's adaptation to the new time of the reward delivery. These results suggest that the CS, delay, and reward-related activities of striatal neurons can be affected by time discounting.