Second is the need to discriminate between processes operating at different timescales, and to understand the mechanisms that link transient short-term variations to more permanent long-term change3. Establishing these links will help identify mechanisms that are short-term precursors of long-term development.
Third, to arrive at mechanistic explanations of behavioural change, behaviour must be connected with neuronal organization and genetic composition. These connections are rarely one-to-one, as many behaviours have multiple underlying implementations within the brain. Therefore, as an individual develops, changes in behavioural repertoires are likely to be associated with ongoing changes in multiple brain–behaviour mappings. Some of these re-mapping gradients might be relatively universal and age-graded, whereas others might be more variable, reflecting genetic differences, person-specific learning histories, the path-dependent nature of developmental dynamics or a combination of the three.
Considering these concepts and challenges, studies on behavioural development should meet one or more of three criteria: focus on how individuals develop in the context of their physical and social environments, explore and track the ability of individuals to change their behaviour (behavioural plasticity) in response to new demands from the environment4,5 (Fig. 2), and integrate neuronal and psychological evidence across timescales, while taking into account functions of behaviour. A growing number of recent studies fulfil one or more of these criteria.
For example, the interactive effects of learning and senescence on the ability to process multiple sensory inputs was investigated by Lövdén6. His team asked adults aged 20–30 or 60–70 years to find their way to a bistro in a museum, represented as a virtual reality projection on a screen in front of a treadmill. Walking demands affected navigation performance only in the older adults, implying that sensori-motor behaviour is more attention-demanding in this population.
In a separate study, a team led by Brehmer tracked how learning and maturation affect episodic memory — remembering specific events — and how this changes and develops with age7. Four groups, aged 9–10, 11–12, 20–25 and 65–78 years, were taught a memory technique. Children and older adults were at a similar level at baseline and immediately after instruction, but the children improved more with practice and reached higher levels than the older adults. Retested after 11-months, all children had improved, but the older adults’ performance had declined. Re-instruction had little effect on the children’s performance but improved that of the older adults. This suggests that learning and maturation forge a strong alliance in middle childhood, which enhances episodic memory plasticity.