Puberty edit Flashcards
Schulz & Sisk (2016), Romeo (2003)
animal studies in relation to OAH
Peper et al. (2018)
200 p 14, 16, 18 y/o
Hormones and behaviour
BART task - track the amount of money made and number of explosions over age as a measure for risky decision making in adolescents.
Can predict the number of explosions simply by looking at the amount of bioavailable testosterone in the brain.
Linear relationship, the more testosterone in the brain the more explosions and risky behaviour/decision making there is.
Self report measure, more impulsivity reported greater bioavailable testosterone. can predict impulsivity simply by looking at the amount of testosterone in the brain.
Testosterone is having a direct influence on behaviour.
Peper et al. (2009)
214 9 y/o TS 1 and 2
Looked at grey matte morphology of th entire brain for individuals who had entered puberty and those who were still pre-puberty.
just one age but variation in pubertal stage, some will have started puberty TS 2 while others will be yet to start TS 1
Found decline in grey matter ONLY in individuals in Tanner stage 2, who had started puberty.
Only those who ahd entered puberty saw the initiation of grey matter changes.
seems to be intiated with the onset of puberty.
Blanton et al. (2012)
54 9-16 y/o
Compare to Ostby
very high density of androgen receptors in the amygdala and hippocampus, so should be more influenced by any changes in androgen release/secretion.
Hierarchical regression model
GM in the hippocampus and amygdala decreases with increasing Tanner stage. Greater stage of puberty reduces grey matter independent of age.
localised puberty- brain relationship.
Marshall & Tanner (1969;1970)
The Tanner Stages of Pubertal Development
Longitudinal study, created classification of physical changes.
5 stages they categorise according to secondary sexual characteristics,
1 = prepubertal, 2-4 = intermediate stages, 5 = reproductive maturity
Boys- testicular volume, Girls - breast size and areola characteristics, Both - bodily hair.
Simple ways of quantifying pubertal development, very observable, easy to visualise indices
Need a train clinician to do it, humiliating for p
Petersen et al. (1988)
Pubertal Development Scale
self-report, simple questions some specific for girls, boys or both
ask p to rate their development in relation to peers
less humiliating but indirect and subjective
Vijayakumar et al. (2018)
meta-analysis - any critique saying about how different studies use different measures of puberty, TS , PDS, hormones, blood, urine, saliva,
PDS does not map directly on to TS as it struggles to capture adrenarche and early gonadal development- low PDS scores can actually be quite physically developed according to TS. PDS does not track genital development.
Should try scoring methods to transform PDS into TS, Shirtcliff et al (2009)
Physical examination is deemed gold standard
Hormones are a direct indices of biological change but fluctuate so much. Estradiol vary across the day and menstrual cycle. Take samples immediately following awakening as hormone are at their highest concentrations.
Herting et al. (2012)
77 p, 10 - 16 y/o
white matter density increases during adolescence
Increased FA and reduced MD values though to be an index of greater myelination or axonal callibre, don’t know which. Greater FA & lower MD = better white matter.
Increments in pubertal scale, geta strengthening of FA.
Looked at bioavailable testosterone or estradiol in the brain. Found with greater FA in boys, with more testosterone available in the male brain, getting higher white matter integrity in some of these tracts. E.g. the corpus callosum. greater testosterone is strengthening the connections between the two hemispheres in boys.
Sexual dimorphism
Estradiol sometimes seems to be having the opposite effect, in some white matter tracts it showed a -ve relationship, the more bioavailable estrodiol less white matter integrity.
Not all hormones have the same effect on WM, and hormones do not necessarily have the same effect on WM in boys and girls.
The hormone - brain structure relationhip is complex. Discrete areas of the brain may have implications for specific behaviours.
Amaro et al. (2012)
54 9-16 TS
PET scan, measured how oestrogen was taken up by receptors in the brain.
higher affinity for oestrogen in the female brain in those WM tracts. WM has receptors ready to take up these hormones and these hormones can have massive effects on the WM calibre/integrity of these axons.
Perrin et al. (2008)
400, 12-18 y/o
bioavailable testosterone in the brain and specific receptors for testosterone.
AR in the brain come in one of 2 forms, short-form or long-form. Short form are more effective and efficient.
As the amount of bioavailable testosterone increases, there is an increase in white matter. Get a steeper increase in individuals with a genetic profile which shows a short version of the androgen receptor. The more efficient receptor for testosterone, the more the brain is wired to effectively receive testosterone, this influences the amount of effect testosterone in the brain can have.
In males, white matter volume increases more rapidly with age than in females brain, seems to be mediated by the effectiveness/efficacy of androgen receptors in the brain (short vs long). Doesn’t matter how much testosterone we pump into the brain, there has to be a receptor waiting to take it, and that receptor must be quite efficient.
Grey matter thinning in individuals with a short AR, with more testosterone see greater grey matter thinning. Testosterone isn’t just affecting white matter, might be one of the mechanisms behind this grey matter thinning. But this is more prevalent in individuals with short AR gene, than in those with a long AR. Starting to tease apart the mechanisms that might be driving those developmental trajectories. The influence of hormones and the receptors sat there waiting for them. The generation of receptors would be a structure organisation, the production and influx of hormones would be an activation – the organisation-activation is interactive and there needs to be a structure in place to receive the activating hormones, and the hormones need to be in place for the structure to take effect.
Paus (2010)
sexual dimorphisms - overall brain volume 11% greater in males. larger relative volume of WM by 7%, butlower relative volume of GM by 2%
Moore et al. (2012)
is the responsiveness face processing area influenced by pubertal stage?
110 F; 13.5-15.5 yrs; Took 2 sets of individuals, 10 y/o, and 13 y/o. At different developmental stages.
Brain response to faces in that face processing network and see if it is correlated at all with the self-reported pubertal stage.
Yes, brain responses are greater in the face processing network with greater Tanner stage. Might suggest greater concentration of sex steroids. Links brain structure with function.
Op de Macks et al. (2011)
50 p, 33 f, 17 m 10-16.
fMRI.
Participants make gambling decisions - whether to stick or spin the wheel.
More impulsivity and risk taking, more likely they are to take a gamble. Unsurprisingly this engages the reward circuitry.
Furthermore, measured testosterone in males and females. Does the amount of bioavailable testosterone influence the responsiveness/activation of the reward system in the brain in adolescence?
Yes it does in both boys and girls, with greater bioavailable testosterone there is greater response/sensitivity of the reward processing network during adolescence in response to this simple task
Mareckova et al. (2012)
20 women 18-29, 10 OC, 10 FC
Participants passively view ambiguous and angry facial expressions and brain response mapped out .
2 groups of females, one group on the contraceptive pill, one group were not (free cycling).
During the menstrual cycle, progesterone takes a massive steep peak during the point of menstruation and then declines quite quickly. The pill elevates progesterone and keeps it stable during that period.
Progesterone (derivative of estradoil), if greater hormones influence greater brain function, maybe it should influence greater brain function towards certain stimuli.
Found engagement of the face processing network, and in females who were on the pill, there was a greater brain response relative to females freely cycling (controlled for the stage of the cycle).
Greater brain response in females undergoing the contraceptive pill – its main mechanism it to elevate progesterone. This almost gives us a cause and effect relationship, almost an intervention but the researcher hasn’t intervened, p did it themselves.
In mid-cycle vs menstruation, when there has been the peak relative to the decrease, females who have experienced this massive peak in progesterone just before the point of menstruation have a greater brain response to faces.
Need the structure there in the first place (organisation part) to happen prepuberty, but once that structure is in place, the activation effects can continue for quite a long time, in to adulthood.
Response to both ambiguous and angry face in females on the pill seems to respond in a dose dependent manner. The longer they have been on the pill, the greater the brain response in the face processing network to faces. Cause-effect relationship here.
