teenage adolescent brain

The Adolescent Brain

The adolescent brain undergoes profound changes in both structure and function that are visible in the MRI, DTI and EEG.  Here’s a look at some of them.

Adolescence is broadly defined as the second decade of life, although its precise start and end points are often ambiguous and differ between cultures and individuals. It is characterized by immense hormonal and physical changes as well as changes in brain functioning and behavior (e.g. cognitive flexibility, risk taking, social behavior) which ready the individual for adulthood.  What is actually happening in the brain?  Over the last decade, there has been a considerable effort to understand both the structural and functional changes taking place during adolescence.  Here’s a look at some of the things we know so far.

Mapping the structural changes.

Much of our structural understanding comes from imaging techniques such as structural MRI and diffusion tensor imaging (DTI) [2] to reveal changes in grey matter volume across different regions of the brain, as well as changes in the white matter tracts between brain regions. For example, one longitudinal MRI study (n= from 388; covering the age range from 8 to 30 years) across 3 countries (United States, the Netherlands and Norway) found decreases in grey matter volume across the cortex throughout adolescence, with the largest decreases occurring in the prefrontal, parietal and temporal cortices [3]. In addition, longitudinal DTI studies during adolescence have suggested that white matter pathways that support executive control mature through adolescence [4], and that there is an overall increase in the efficiency of the brain’s structural network [5]. These structural modifications have been proposed to reflect the underlying neurobiological changes which appear to take place during adolescence (e.g. synaptic pruning, myelination), however the details are still not fully elucidated [1].

Functional Changes in the EEG

Changes in the maturing adolescent brain can also be observed with EEG. For example, studies have used evoked potentials (e.g. error-related negativity), coherence measures, and EEG during sleep to measure the neurophysiological changes in different age groups from childhood to adulthood, some of which have employed a longitudinal approach [6]. (See The EEG from infancy to adulthood). For example, one recent longitudinal EEG study analyzed intra-hemispheric resting coherence in school age children (n = 40; across the age range 6–18 years) and revealed significant increases in short-distance local and long-distance global synchronization with increasing age [7]. The authors suggest that disorders which often emerge during childhood and adolescence (e.g.  schizophrenia, autism) may be associated with an imbalance in this local and global information processing.

Sleep EEG as a window into the developing adolescent brain.

Another longitudinal EEG study measured sleep EEG to track changes in spectral power in individuals aged 6 to 18 years across 3 overlapping cohorts of individuals (total n=98: from 6-10 years: n = 28; from 9-14 years: n = 32; from 12-17 years: n = 38) [8]. To do this, they recorded all-night sleep EEG twice yearly for 4 consecutive school nights in the children’s homes.

Overall, their analysis showed that there is approximately a 60% decline in NREM delta power between ages 11 and 16.5 years. Or to put it another way “The magnitude of the EEG changes can be appreciated by a simple fact: the decline of NREM delta EEG over 6 years of adolescence exceeds the decline over the subsequent 50 years of life” [9]. Subsequent analysis shows a similar magnitude of decline in REM delta power.


Comparison of the maturational trajectories for average delta (1–4 Hz) EEG power in non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. [11]

In addition, the authors also tracked changes in NREM and REM theta band activity and found a similar pattern and magnitude of decline during adolescence, although starting earlier in childhood, whilst analysis of sleep sigma activity (11-15 Hz) revealed a shift in its peak frequency [10].

Comparison of the maturational trajectories for theta (4–8 Hz) FFT power in NREM sleep and REM sleep. [11]

The authors suggest that this decline in delta and theta mirrors the changes in synaptic density and cerebral metabolic rate which occur concurrently during adolescence. They also note the changing sleep habits of an adolescent (e.g. staying up late, sleeping in more at the weekend) which could also play an interactive role with the changing patterns of oscillatory activity. Furthermore they suggest that a disturbance in the decline in NREM delta activity may be a risk factor in the onset of schizophrenia, where there appears to be an even greater delta decline – i.e. an exaggeration of the process of normal adolescent development – compared to healthy development (See Schizophrenia: A Meta-analysis of Resting-State EEG Studies) [9]. However, these are all still speculative and it is possible that changes simply reflect things like increasing education. Further longitudinal studies are still needed to more adequately explore the potential opportunities for linking adolescent brain development and psychiatric vulnerability.


In summary, adolescence is a time of significant change in both the structural and functional aspects of the brain, one that perhaps confers vulnerability to certain psychiatric disorders. However, only with additional longitudinal studies using large-scale cross-cultural populations with comprehensive demographic and other experiential data, will it be possible to start to understand the many contributing factors such as education, technology and social experience that influence the trajectory of brain changes during adolescence, and that may enhance psychiatric vulnerability during this critical period of development.  Indeed, a large scale study is underway now that is anticipated to yield a host of new insights.

Dataset: Longitudinal EEG Sleep Data from the UC Davis study available at the National Database for Autism Research Archive:



  1. Tamnes, C., Roalf, D., Goddings, A., & Lebel, C. (2018). Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress. Developmental Cognitive Neuroscience, 33, 161-175. doi: 10.1016/j.dcn.2017.12.002
  2. Tamnes, C., Herting, M., Goddings, A., Meuwese, R., Blakemore, S., & Dahl, R. et al. (2017). Development of the Cerebral Cortex across Adolescence: A Multisample Study of Inter-Related Longitudinal Changes in Cortical Volume, Surface Area, and Thickness. The Journal Of Neuroscience, 37(12), 3402-3412. doi: 10.1523/jneurosci.3302-16.2017
  3. Simmonds, D., Hallquist, M., Asato, M., & Luna, B. (2014). Developmental stages and sex differences of white matter and behavioral development through adolescence: A longitudinal diffusion tensor imaging (DTI) study. Neuroimage, 92, 356-368. doi: 10.1016/j.neuroimage.2013.12.044
  4. Koenis, M., Brouwer, R., van den Heuvel, M., Mandl, R., van Soelen, I., & Kahn, R. et al. (2015). Development of the brain’s structural network efficiency in early adolescence: A longitudinal DTI twin study. Human Brain Mapping, 36(12), 4938-4953. doi: 10.1002/hbm.22988
  5. Paus, T., Keshavan, M., & Giedd, J. (2008). Why do many psychiatric disorders emerge during adolescence?. Nature Reviews Neuroscience, 9(12), 947-957. doi: 10.1038/nrn2513
  6. Segalowitz, S., Santesso, D., & Jetha, M. (2010). Electrophysiological changes during adolescence: A review. Brain And Cognition, 72(1), 86-100. doi: 10.1016/j.bandc.2009.10.003
  7. Gmehlin, D., Thomas, C., Weisbrod, M., Walther, S., Resch, F., & Oelkers-Ax, R. (2011). Development of brain synchronisation within school-age – Individual analysis of resting (alpha) coherence in a longitudinal data set. Clinical Neurophysiology, 122(10), 1973-1983. doi: 10.1016/j.clinph.2011.03.016
  8. Campbell, I., & Feinberg, I. (2009). Longitudinal trajectories of non-rapid eye movement delta and theta EEG as indicators of adolescent brain maturation. Proceedings Of The National Academy Of Sciences, 106(13), 5177-5180. doi: 10.1073/pnas.0812947106
  9. Feinberg, I., & Campbell, I. (2010). Sleep EEG changes during adolescence: An index of a fundamental brain reorganization. Brain And Cognition, 72(1), 56-65. doi: 10.1016/j.bandc.2009.09.008
  10. Campbell, I., & Feinberg, I. (2016). Maturational Patterns of Sigma Frequency Power Across Childhood and Adolescence: A Longitudinal Study. Sleep, 39(1), 193-201. doi: 10.5665/sleep.5346
  11. Feinberg, I., & Campbell, I. (2013). Longitudinal sleep EEG trajectories indicate complex patterns of adolescent brain maturation. American Journal Of Physiology-Regulatory, Integrative And Comparative Physiology, 304(4), R296-R303. doi: 10.1152/ajpregu.00422.2012



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