Draganski et al (2004)- FINISH- NEUROPLASTICITY

aim

aim

the aim of the study was to see whether learning a new skill- in this case juggling- would affect the brains of participants.

or

To see whether brain structure (gray matter) changed in response to environmental demands (juggling)

paricipants

24 volunteers between the age of 20 and 24. There were 21 females and 3 males. They randomly allocated these volunteers into one of two groups, jugglers or non-jugglers.

Method

All participants were non-jugglers at the start of the study. Each participant had an MRI scan at the beginning of the study to serve as a base rate for grey matter and brain structure.

those who were in the juggling condition were taught a 3-ball cascade juggling routine and were asked to practice this routine for 3 months. A brain scan was performed (at 3 months)

Then the participants were told NOT to practice their juggling routine and a 3rd final brain scan was taken after 3 months.

Then, the control group (non-jugglers) just lived their daily lives and had their brain scanned 3 times on the same schedule as the jugglers.

results

to analyze the MRI scans, the researcher used voxel based morphology (VBM) to determine if there were any significant differences in neural density (gray matter) in the brains of jugglers vs non jugglers. From the baseline scans- taken before the study began- they found no significant regional differences in grey matter between the 2 conditions

However at the end of the first part of the study, the jugglers showed significantly lrger am ount of grey matter in the mid temporal area of both hemispheres- an area assossiated with visual memo ry. 3 months zfter teh pzrrticipants stopped juggling- when many were no longer able to carry out the routine- the amount of grey matter in these parts of the brain had decreased.

conclusion

evaluation

The study used a pre-test/post-test design to show differences in neural density over time.
It was experimental so there was a cause and effect relationship.
there was a group that didn’t juggle that served as a control
the sample size was very small so it is possible that by using averages of neural growth, the data may not be reliable
The study was a field experiment- that is the IV was manipulated under natural conditions; therefore the study has potential problems with internal validity as the participants were in their home environments for a majority of the study.

Link: neuroplasticity (rewrite and check)

Neuroplasticity refers to the dynamic nature of the brain and the way it can change shape depending on it’s interactions of cognition with the enviroment, or the enviromental demands assosssiated with juggling in the study conducted by draginski et al (2004). Since neuroplacticity results in the change of neural density, draginski et al studied the change in grey matter when a new skill was learnt. A new skill causes a change in grey matter because the active neurons (the functional unit of the brain) continuosly fire as a skill is repeated and learn’t and neural pathways are created. There is a form of stregnthening neural synapses known long term potentiation and it is due to the recent patterns of neuron firing. It supports draginski’s findings, as long term potentiation argues that the more is repeated/ practiced the more the dendriting branching or dendritic aborization which leads to an increase in neural density, as seen by the amount of grey matter increasing in the 2nd scan.

Link: Brain imaging

The brains tissues have various compositions of hydrogen and the MRI uses this fact to create high resolution 3D images of the brain. It works on the principle that atoms specifically hydrogen emit energy in a magnentic field, and thus it uses magnetic fields and radio waves to detect and create a scan of the brain which can either be a slice or a full 3D representation. Since it doesn't use X-rays, there is a reduced risk of radiation induced cancer for the [participants. In draginski et al the resolution or speciffically the spatial resoultion was very important for voxel based morphomettry and obtaining accurate results, and MRIs have very high resolution specifically spatial resolution, however they could easily be ruined by movement, and it limits the participants as people who have metal in them can’t go in the machine, they are also extremely expensive

Link: neural pruning- liner

Draginski (2004) presents compelling evidence for neural pruning through a study on juggling. The study involved participants who showed an increase in gray matter in the brain after learning to juggle. This initial increase in gray matter suggested that the process of acquiring a new skill, in this case, juggling, led to the generation of additional synapses or neural connections in the brain. Subsequently, after the participants stopped juggling, there was a notable decrease in gray matter. This decrease indicated a reduction in the number of synapses, thus reflecting the phenomenon of neural pruning.

​The evidence gathered from this study strongly suggests that neural pruning is the process by which the brain eliminates extra synapses in order to maintain more efficient brain function as individuals age. These findings highlight the dynamic nature of the brain and its ability to adapt and optimize its neural architecture based on the demands and experiences placed upon it.

Link: neural networks

Draganski et al. (2004) conducted a study that provides compelling evidence for the role of neuroplasticity in brain structure and function, particularly demonstrating the involvement of neural networks. The study aimed to investigate whether structural changes in the brain occur in response to learning and ceasing juggling ((52))((69)).

The results of the study showed that juggling training induced significant structural changes in the brain. Specifically, the participants who underwent juggling training exhibited a significant increase in gray matter volume in the mid-temporal area of the brain, an area associated with visual processing, spatial perception, and motor coordination ((52))((73)).

This evidence of increased gray matter volume in the mid-temporal area provides insight into the role of neuroplasticity in the formation and changes of neural networks. The findings demonstrate that learning, in this case, juggling, leads to structural changes in the brain, indicating the involvement of neural networks in acquiring and mastering new motor skills and spatial processing ((53))((75)).

The study supports the idea that through neuroplasticity, new neural connections are formed, and existing ones are strengthened or rearranged, contributing to changes in brain structure and the formation of neural networks. This study offers a valuable demonstration of how the brain adapts and changes in response to learning experiences, offering important insights into the mechanisms of neuroplasticity and the formation of neural networks.

The study's use of neuroimaging techniques such as structural magnetic resonance imaging (MRI) and functional MRI to measure changes in brain structure and function provides a comprehensive view of the changes in neural networks that occurred in response to the juggling training, further solidifying its evidence for the involvement of neural networks in neuroplasticity

In summary, Draganski et al. (2004) offers robust evidence for neural networks' involvement in neuroplasticity by demonstrating how learning, in this case, juggling, induces structural changes in the brain, particularly in the mid-temporal area, thereby highlighting the remarkable adaptability of the brain through the formation and modification of neural networks.