Dr Korbinian Brodmann, German Neurologist, Frontpiece of ‘Localisation in the Cerebral Cortex’, 1909, Public Domain*
In the nineteenth century the eminent German Neurologist Dr Korbinian Brodmann developed a brain map based on the brain’s microscopic properties. This map has been very successful and is used even today. Many of the Brodmann areas have been covered in detail elsewhere on this site (see Appendix). This post continues the series looking at selective Brodmann areas in this instance focusing on Brodmann Area 51. Brodmann does not describe this area in humans. Instead, in his classic 1909 text ‘Localisation in the Cerebral Cortex’ he provides a comparison of neuroanatomy in several distinct species. Brodmann Area 51 is described in the Kinkajou. The Kinkajou which can be seen in this video is an arboreal mammal living in Central and South America. Brodmann Area 51 is referred to by Brodmann as the Prepiriform area within the Olfactory region. Brodmann also describes this area in the Rabbit and Ground Squirrel. Brodmann also describes Brodmann Area 51 in the Hedgehog noting that it is expanded and he further subdivides this into 51a, 51b, 51c and 51d. This perhaps reflects the different significance of the Olfactory apparatus across species.
*Public Domain in those countries where the Copyright term of the life of the author (Korbinian Brodmann 1868-1918) plus the additional country specific term has lapsed from Copyright at the time of writing
An index of the site can be found here. The page contains links to all of the articles in the blog in chronological order. Twitter: You can follow ‘The Amazing World of Psychiatry’ Twitter by clicking on this link. Podcast: You can listen to this post on Odiogo by clicking on this link (there may be a small delay between publishing of the blog article and the availability of the podcast). It is available for a limited period. TAWOP Channel: You can follow the TAWOP Channel on YouTube by clicking on this link. Responses: If you have any comments, you can leave them below or alternatively e-mail justinmarley17@yahoo.co.uk. Disclaimer: The comments made here represent the opinions of the author and do not represent the profession or any body/organisation. The comments made here are not meant as a source of medical advice and those seeking medical advice are advised to consult with their own doctor. The author is not responsible for the contents of any external sites that are linked to in this blog.
In this 6th part of the series on using open data for science I’ve take a slight diversion to look at populations and the issue of sampling. This was prompted by a look at the UK mid-2011 Census data shown in the graph below.
Figure 1: Summation of male and female figures for each age from mid-2011 Census. Red bars represent the age group 45-65 and the blue bars represent the age group 16-44
What were going to do is look at the UK population and build a mathematical population and build a model for the populations we’ve looked at in the previous posts. Just to recap, when we compared two populations there are a number of statistical methods for doing this which are dependent on the characteristics of the population. For a normally distribution population we can define this population by the mean and standard deviation. As discussed in previous posts the populations in this post from the census study in mid 2011 which are not normally distributed. In the first segment aged 16-44 there is a somewhat homogenous group?? whilst in the group 45-65 there is a right skewed distribution that is the numbers for each year get progressively smaller.
In the third part in this series I included some of the data from the mid-2011 Census which I will reproduce here to support the subsequent discussion. Summing the male and female figures we get the following results for ages 16 through to 44
680,979
706,234
711,491
741,667
765,895
757,901
757,295
771,297
756,449
768,415
774,921
759,889
768,860
770,810
778,986
782,510
751,251
700,825
690,775
702,024
716,419
729,013
761,347
794,300
820,805
800,550
821,037
819,650
832,297
For ages 45-65 we get the following results
832,727
838,064
831,041
813,798
797,077
770,066
739,859
723,861
708,371
682,824
659,795
637,073
641,145
634,399
618,132
623,508
638,118
655,668
694,644
754,834
583,734
The total estimated population in England and Wales in Mid-2011 for the age group 16-44 is
21993892
and for the age group 45-65 is
15711035
So if we move firstly to the population aged 45-65. This population has a value that begins with 832,727 people aged 45 and decreases to 583,734 at age 65 . First recall that the x-axis represents age and the y-axis is the number of people in each age group. The population can be approximately described by a line of decreasing slope. Now if we’re going to model this we’re going to need to understand what the relationship is between x and y. Quite obviously as x increases y decreases and the relationship is described by y = -x. Looking at the graph above this doesn’t seem intuitive. None of the y values are negative. However if the graph began at (0,0) then it would become negative as x increased. The reason that this doesn’t happen in the above graph is that the line y = -x is translated in a positive direction along the y-axis. So in other words (I will take out the negative sign at this stage as it will be dealt with by the coefficient a)
y = x + c
In addition to this, rather than a straight line with a unit gradient (i.e for every unit increase along the x-axis there is a unit increase along the y-axis) the line has a gradient which we have yet to determine. For the sake of convenience I will refer to this as
y = a x + c
There is a simple introduction to lines and slopes below.
Our job now is to find out what those two variables a and c are. This is going to be an approximation. Turning first to people aged 45
y = a x + c
832,727 = 44 a + c
and for the age 65
583,734 = 65 a + c
We have two equations that we have to solve and two sets of values to do this. Since
832727 = 44 a + c
44 a = 832727 – c
a = (832727-c)/44
Now from the original equations we know that
583,734 = 65 a + c
and therefore substituting
a = (832,727-c)/44
we get
583734 = 65/44 (832727-c) + c
Multiplying out we get
583734 = (1 – 1.477)c + 1230164.89
- 646430.88636 = -0.477c
c = 1354426.6
Substituting back into the original equation
583,734 = 65 a + 1354426.6
Rearranging we get
(583,734 – 1354426.6)/65 = a
a = -11856.81
Substituting the values for a and c into the original equations above, the reader will be see that these values solve the equations. The numbers have been rounded up. Indeed rounding to the nearest number we arrive at the following equation
y = -11857 x + 1354427
This equation approximately describes the UK mid-2011 Census data for the age group 45-65 where y is the total population for each age and x is the age in years within the given range.
Index: There are indices for the TAWOP site here and hereTwitter: You can follow ‘The Amazing World of Psychiatry’ Twitter by clicking on this link. Podcast: You can listen to this post on Odiogo by clicking on this link (there may be a small delay between publishing of the blog article and the availability of the podcast). It is available for a limited period. TAWOP Channel: You can follow the TAWOP Channel on YouTube by clicking on this link. Responses: If you have any comments, you can leave them below or alternatively e-mail justinmarley17@yahoo.co.uk. Disclaimer: The comments made here represent the opinions of the author and do not represent the profession or any body/organisation. The comments made here are not meant as a source of medical advice and those seeking medical advice are advised to consult with their own doctor. The author is not responsible for the contents of any external sites that are linked to in this blog.
This is the first in a series on using PubMed. PubMed is the gateway for several important biomedical databases including Medline. Being able to work with PubMed is a very useful skill in the life sciences. In the first part the reader will need to set up an account with the National Center for Biotechnology Information. I will assume that the reader has done this. The first lesson is very simple and focuses on preferences. As someone that uses PubMed frequently I find shortcuts really useful. The shortcut i’m going to discuss here is one used in searches. The first step is to go to the preferences page once you’re logged into your NCBI account. Then under PubMed Preferences click on ‘Result Display Settings’. Finally select abstract, 200 and Pub Date under preferences. Every time you log into your NCBI account and use this to access PubMed, these preferences will be used automatically.
So what does all this mean? Well firstly the ‘abstract’ preference simply means that all returned results will be displayed with the abstract. This enables you to get a quick overview of the paper without needing to click on a hypertext link to get to the abstract. The second preference ’200′ means that each page will feature 200 results per page. The default is 20 which means you have to click 10 times to see all of the results. The only drawback is that you need appropriate resources on your computer to avoid a sluggish response. Finally the ‘Pub Date’ preferences means that the articles will be displayed in chronological order. This is especially useful if your interested in the most recent papers in the field.
So that’s the lesson – brief and simple and you’ll see the benefits after using the saved preferences on just a few occasions. Of course if your needs are different then you can just adjust the preferences accordingly.
Index: There are indices for the TAWOP site here and hereTwitter: You can follow ‘The Amazing World of Psychiatry’ Twitter by clicking on this link. Podcast: You can listen to this post on Odiogo by clicking on this link (there may be a small delay between publishing of the blog article and the availability of the podcast). It is available for a limited period. TAWOP Channel: You can follow the TAWOP Channel on YouTube by clicking on this link. Responses: If you have any comments, you can leave them below or alternatively e-mail justinmarley17@yahoo.co.uk. Disclaimer: The comments made here represent the opinions of the author and do not represent the profession or any body/organisation. The comments made here are not meant as a source of medical advice and those seeking medical advice are advised to consult with their own doctor. The author is not responsible for the contents of any external sites that are linked to in this blog.
