Puberty Flashcards
Peper et al. (2018)
BART & bioavailable testosterone
N>200; 14, 16 and 18 yrs.
Track the amount of money made and number of explosions on the BART task over age - metric of risky decision making in adolescence. General increase in both during adolescence.
Can predict the number of balloon 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.
The more impulsive (as measured on a self report instrument) individuals report themselves to be, the more testosterone there is.
Can predict the impulsivity simply my looking at bioavailable testosterone in the brain. Hormones having a direct influence on behaviour.
Peper et al. (2009)
GM and pubertal stage
N=214; TS; 9 yrs - large sample of MZ and DZ twins.
Only looked at 9 y/o children, pre-pubertal, but loads of variability in the onset of puberty. Some were at Tanner stage 2 and other were stage 1.
Looked at grey matter morphology of the entire brain for individuals who had entered puberty and those who were still at pre-pubertal stage.
Only started to see decrease in grey matterin the 9 y/o who had entered into puberty (Tanner stage 2). Only those who have entered puberty saw the initiation of these grey matter changes (developmental trajectories, decline in grey matter). Seems to be initiated with the onset of puberty.
Blanton et al. (2012)
GM in amygdalae and hippocampus
N=54; 9-16; TS; – very high density of androgen receptors in the amygdala and hippocampus, see whether the grey matter in the hippocampi and the amygdalae shows a relationship with pubertal stage.
Already shown that grey matter is related to age, but is it more to do with the developmental phase that the individual has hit at that age.
Hierarchical regression model.
Grey matter in the hippocampus and amygdalae decreases with increasing Tanner stage. Greater stage of puberty reduces grey matter independent of their age. Same age but which Tanner stage they are at determines their grey matter volume.
This is a localised puberty – brain structure relationship.
Marshall & Tanner (1969;1970)
TS
the Tanner stages of pubertal development.
Large longitudinal study, came up with a classification of physical changes. 5 stages of pubertal development categorised according to secondary sexual characteristics.
Defined in males by testicular volume, in females by breast size and areola characteristics, and for a measurement common to both, bodily hair .
+ve very observable, easy to visualise indices of pubertal development, easier than taking blood or saliva samples, very simple ways of quantifying pubertal development.
-ve needs a trained clinician to determine the age of participants. Humiliating for the participant, but may be the most effective way of doing it bc it is a single individual making a classification.
Petersen et al. (1988)
PDS
a questionnaire with simple questions some specific to girls or boys or some common to both.
Self-report, asking how they feel they have developed relative to their peers (relative-measure),
asking what kind of developmental phase they are in indirectly.
Much less humiliating but much more subjective.
Herting et al. (2011)
WM, FA and MD
77 adolescents - 38 M, 39 F; 10–16 yrs; Higher FA/lower MD = increased axon caliber, myelination
White matter density increases during adolescence, myelination of the axon or diameter/calibre of the axon?
Difficult to tell with MRI. Greater FA values and lower MD values = an index of greater myelination or axonal calibre. Greater FA, lower MD = better white matter. See with increments in pubertal scale, get a strengthening of FA, i.e. more myelination/ greater axonal calibre/ more white matter integrity in a very localised area (e.g. insula cortex) with pubertal scale independent of age.
Bioavailable testosterone or estradiol in the brain. If puberty has this relationship with discrete white matter tracts, maybe it is the hormonal events occurring during those pubertal stages.
See with greater FA in boys, with more testosterone available in the male brain, getting higher white matter integrity in some of these tracts. Corpus callosum – . Seeing that greater testosterone is strengthening the connection between the two hemispheres in boys.
Sexual dimorphism, estradiol sometimes seems to be having an opposite effect, some of these tracts have a –ve relationship, with more estradiol have less white matter integrity. Not all hormones have the same effect on white matter, nor do hormones have the same effect on white matter in males and females – very complex relationship between the nature of the hormone and the effect it is having on brain structure.
In discrete areas of the brain that might have direct relationships with behaviour e.g. amygdala and emotional responsivity, striatum and nucleus accumbens and basal ganglia in terms of reward seeking and sensation seeking.
robust sex differences exist in FA and MD in adolescents, with boys having higher FA and lower MD compared with girls, while controlling for age and puberty.
blood samples taken from one particular time in the menstrual cycle, when estradiol levels are uniformly low, other times would have shown more variability.
Cross-sectional design
Amaro et al. (2018)
PET scans and oestrogen
N=54; 9-16; TS; No effect of age when puberty partialed out.
PET scan – look to see how oestrogen was take up by receptors in the brain.
Have higher affinity for receptors for oestrogen in the female brain in those white matter tracts. Hormones have massive effects on the calibre/white matter integrity of these axons.
The female brain is wired ready to take on these androgens/female sex steroids.
Perrin et al. (2008)
Androgen receptors and WM
N>400, 12-18 yrs, bioavailable testosterone in the brain and specific receptors for testosterone.
Androgen receptors in the brain can come in one of two forms – short-form or long-form. Short- is more effective, more efficient than the long-form.
As 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.
Link towards the O-A-H. Influx of hormones which influence brain structure, brain has receptors ready to accept these hormones (as preprogrammed earlier), sometimes these receptors are more efficient than others. Could argue a genetic pre-programming or could argue that early life events may influence the effectiveness of androgen receptors. Can look at this as a gene-environment-brain-hormone relationship. The efficiency of the androgen receptors influences the amount that testosterone or androgens in the brain (as released during puberty) will have an effect on brain structure, particularly white matter/white matter connections.
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.
Paus et al. (2010)
f vs m brain size, GM and WM
(n=419; 12–18 years). The brains of male and female adolescents appear to differ both in global size, volumes of white and grey matter, and in regional grey-matter densities.
Overall brain size (male>female by 11%), male adolescents still have larger relative volume of WM (by 7%) but lower relative volume of GM (by 2%) than female adolescents. higher GM density in female vs. male adolescents across a number of cortical regions.
Functional polymorphism in AR gene modulates both the age-related changes in relative WM and GM volumes.
The age-related decreases in GM density observed more robust in those with the short than the long AR.
Moore et al. (2012)
Face processing and TS
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)
Gambling and testosterone
50 healthy adolescents (aged 10–16 years; 33 girls, 17 boys)
fMRI, gambling game, make gambling decisions, win or lose (10 Eurocents). provided saliva samples for hormone assessment.
The sample of girls was doubled relative to the boys, because less variation in testosterone levels was expected.
More impulsivity and risk taking, more likely they are to take a gamble.
Engages the reward circuitry.
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.
Girls and boys exhibit similar risk taking behavior and recruit similar brain areas in response to monetary reward
Results for estradiol, a more reliable measure of pubertal development in girls, also showed a positive relation with reward-related activation in the dorsal striatum, DLPFC, and medial PFC, although again at a less stringent threshold.
Hierarchical regression analyses showed that testosterone, not age, was the best predictor for neural activity in boys and girls.
Marečková et al. (2012)
face processing and OC
Both behavioural and neuroimaging evidence support a female advantage in the perception of human faces.
This relationship may be partially mediated by female sex hormones.
20 young women [aged 18-29, 10 freely cycling and 10 taking oral contraception
Participants passively view ambiguous and angry facial expressions and brain response mapped out .
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).
Found engagement of the face processing network, and in females who were on the pill, there was a greater brain response (controlled for the stage of the cycle).
Found stronger neural responses to faces in the right fusiform face area (FFA) in women taking oral contraceptives (vs freely cycling women) and during mid-cycle (vs menstruation) in both groups. Mean BOLD response in both left and right FFA increased as function of the duration of OC use.
Greater brain response in females undergoing the contraceptive- pill’s 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.
