Women S Brains Essay Summary Format

In the mid- to late-nineteenth century, author George Eliot sought to discount the widespread belief that women were innately inferior to men in regards to intelligence. This prevailing outlook was largely supported by the scientific work of one of her contemporaries, Paul Broca, professor of clinical surgery at the Faculty of Medicine in Paris. Relying on comparisons of skull measurement, Broca averred that because women's brains were smaller than men's, they clearly were incapable of reaching the intellectual heights of their male counterparts. Although a few of his fellow scientists rejected his claims about the inferiority of women, Broca's conclusions were widely accepted. Backing up these claims of brain size as the main indicator of intellectual potential with an interpretation of accepted gender social roles and resulting evolutionary pressures, Topinard, "Broca's chief disciple," went so far as to assert:

The man who fights for two or more in the struggle for existence, who has all the responsibility and the cares of tomorrow...needs more brain than the woman whom he must protect and nourish, the sedentary woman...whose role is to raise children, love, and be passive.

During those same years, Gustave Le Bon, a close adherent of Broca's school of thought, published a virulent attack upon women, saying:

All psychologists who have studied the intelligence of women, as well as poets and novelists, recognize...that [women] represent the most inferior forms of human evolution...they excel in fickleness, inconstancy, absence of thought and logic, and incapacity to reason.

Le Bon was "horrified" at suggested social reforms which would grant women access to higher education on the same basis as men. He warned that if women,

misunderstanding the inferior occupations which nature has given her...leave the home and take...

(The entire section is 680 words.)

1. Hagmann P, Grant PE, Fair DA (2012) MR connectomics: a conceptual framework for studying the developing brain. Front Syst Neurosci6: 43 doi: 10.3389/fnsys.2012.00043[PMC free article][PubMed]

2. Craddock RC, Milham MP, LaConte SM (2013) Predicting intrinsic brain activity. Neuroimage82: 127–136. doi: 10.1016/j.neuroimage.2013.05.072[PubMed]

3. Ghasemi J, Ghaderi R, Mollaei MK, Hojjatoleslami S (2013) A novel fuzzy dempster-shafer inference system for brain {MRI} segmentation. Information Sciences223: 205–220. doi: 10.1016/j.ins.2012.08.026

4. Ortiz A, Gorriz J, Ramirez J, Salas-Gonzalez D (2014) Improving MR brain image segmentation using self-organising maps and entropy-gradient clustering. Information Sciences262: 117–136. doi: 10.1016/j.ins.2013.10.002

5. Ball G, Aljabar P, Zebari S, Tusor N, Arichi T, Merchant N, et al. (2014) Rich-club organization of the newborn human brain. Proc Natl Acad Sci U S A111: 7456–7461. doi: 10.1073/pnas.1324118111[PMC free article][PubMed]

6. Bargmann CI (2012) Beyond the connectome: how neuromodulators shape neural circuits. Bioessays34: 458–465. doi: 10.1002/bies.201100185[PubMed]

7. Batalle D, Muñoz-Moreno E, Figueras F, Bargallo N, Eixarch E, Gratacos E (2013) Normalization of similarity-based individual brain networks from gray matter MRI and its association with neurodevelopment in infants with intrauterine growth restriction. Neuroimage83: 901–911. doi: 10.1016/j.neuroimage.2013.07.045[PubMed]

8. Graham DJ (2014) Routing in the brain. Front Comput Neurosci8: 44 doi: 10.3389/fncom.2014.00044[PMC free article][PubMed]

9. Agosta F, Galantucci S, Valsasina P, Canu E, Meani A, Marcone A et al. (2014) Disrupted brain connectome in semantic variant of primary progressive aphasia. Neurobiol Aging. doi: 10.1016/j.neurobiolaging.2014.05.017[PubMed]

10. Alexander-Bloch AF, Reiss PT, Rapoport J, McAdams H, Giedd JN, Bullmore Ed T. et al. (2014) Abnormal cortical growth in schizophrenia targets normative modules of synchronized development. Biol Psychiatry. doi: 10.1016/j.biopsych.2014.02.010[PMC free article][PubMed]

11. Baker JT, Holmes AJ, Masters GA, Yeo BTT, Krienen F, Buckner, Randy L. et al. (2014) Disruption of cortical association networks in schizophrenia and psychotic bipolar disorder. JAMA Psychiatry71: 109–118. doi: 10.1001/jamapsychiatry.2013.3469[PMC free article][PubMed]

12. Besson P, Dinkelacker V, Valabregue R, Thivard L, Leclerc X, Derambure P. et al. (2014) Structural connectivity differences in left and right temporal lobe epilepsy. Neuroimage100C: 135–144. doi: 10.1016/j.neuroimage.2014.04.071[PubMed]

13. Bonilha L, Nesland T, Rorden C, Fillmore P, Ratnayake RP, Fridriksson J. (2014) Mapping remote subcortical ramifications of injury after ischemic strokes. Behav Neurol2014: 215380 doi: 10.1155/2014/215380[PMC free article][PubMed]

14. Ingalhalikar M, Smith A, Parker D, Satterthwaite TD, Elliott MA, Ruparel K, et al. (2014) Sex differences in the structural connectome of the human brain. Proc Natl Acad Sci U S A111: 823–828. doi: 10.1073/pnas.1316909110[PMC free article][PubMed]

15. Joel D, Tarrasch R (2014) On the mis-presentation and misinterpretation of gender-related data: the case of Ingalhalikar’s human connectome study. Proc Natl Acad Sci U S A111: E637 doi: 10.1073/pnas.1323319111[PMC free article][PubMed]

16. Ingalhalikar M, Smith A, Parker D, Satterthwaite TD, Elliott MA, Ruparel K, et al. (2014) Reply to Joel and Tarrasch: On misreading and shooting the messenger. Proc Natl Acad Sci U S A111: E638 doi: 10.1073/pnas.1323601111[PMC free article][PubMed]

17. Fine C (2014) Neuroscience. his brain, her brain?Science346: 915–916. [PubMed]

18. Witelson SF, Beresh H, Kigar DL (2006) Intelligence and brain size in 100 postmortem brains: sex, lateralization and age factors. Brain129: 386–398. doi: 10.1093/brain/awh696[PubMed]

19. Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Kawashima R, et al. (2011) Correlations among brain gray matter volumes, age, gender, and hemisphere in healthy individuals. PLoS One6: e22734 doi: 10.1371/journal.pone.0022734[PMC free article][PubMed]

20. Lawler EL (1976) Combinatorial optimization: networks and matroids. Courier Dover Publications.

21. Ford LR, Fulkerson DR (1956) Maximal flow through a network. Canadian Journal of Mathematics8: 399–404. doi: 10.4153/CJM-1956-045-5

22. Ade P, Aghanim N, Armitage-Caplan C, Arnaud M, Ashdown M, Atrio-Barandela, F, et al. (2013) Planck 2013 results. XVI. Cosmological parameters. arXiv preprint arXiv:13035076.

23. Garey MR, Johnson DS, Stockmeyer L (1976) Some simplified NP-complete graph problems. Theoretical computer science1: 237–267. doi: 10.1016/0304-3975(76)90059-1

24. Tarjan RE (1983) Data structures and network algorithms, volume 44 of CBMS-NSF Regional Conference Series in Applied Mathematics. Society for Industrial Applied Mathematics.

25. Hoory S, Linial N, Wigderson A (2006) Expander graphs and their applications. Bulletin of the American Mathematical Society43: 439–561. doi: 10.1090/S0273-0979-06-01126-8

26. Lovász L (2007) Combinatorial problems and exercises. American Mathematical Society, 2nd edition.

27. Prüfer H (1918) Neuer Beweis eines Satzes über Permutationen. Arch Math Phys27: 742–744.

28. Kirchhoff G (1847) über die Auflösung der Gleichungen, auf welche man bei der untersuchung der linearen verteilung galvanischer Ströme geführt wird. Ann Phys Chem72.

29. Chung FR (1997) Spectral graph theory, volume 92 American Mathematical Soc.

30. Li R (2013) Lower bounds for the Kirchhoff index. MATCH Commun Math Comput Chem70: 163–174.

31. Feng L, Gutman I, Yu G (2013) Degree Kirchhoff index of unicyclic graphs. Communications in Mathematical and in Computer Chemistry/MATCH69: 629–648.

32. McNab JA, Edlow BL, Witzel T, Huang SY, Bhat H, Heberlein, Keith, et al. (2013) The Human Connectome Project and beyond: initial applications of 300 mT/m gradients. Neuroimage80: 234–245. doi: 10.1016/j.neuroimage.2013.05.074[PMC free article][PubMed]

33. Daducci A, Gerhard S, Griffa A, Lemkaddem A, Cammoun L, Gigandet X, et al. (2012) The connectome mapper: an open-source processing pipeline to map connectomes with MRI. PLoS One7: e48121 doi: 10.1371/journal.pone.0048121[PMC free article][PubMed]

34. Tournier J, Calamante F, Connelly A, (2012) Mrtrix: diffusion tractography in crossing fiber regions. International Journal of Imaging Systems and Technology22: 53–66. doi: 10.1002/ima.22005

35. Basser PJ, Pierpaoli C (2011) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor mri. 1996. J Magn Reson213: 560–570. [PubMed]

36. Hochbaum DS (1982) Approximation algorithms for the set covering and vertex cover problems. SIAM Journal on Computing11: 555–556. doi: 10.1137/0211045

37. Achterberg T, Berthold T, Koch T, Wolter K (2008) Constraint integer programming: A new approach to integrate CP and MIP In: Integration of AI and OR techniques in constraint programming for combinatorial optimization problems, Springer; pp. 6–20.

38. Achterberg T (2009) Scip: solving constraint integer programs. Mathematical Programming Computation1: 1–41. doi: 10.1007/s12532-008-0001-1

39. Jbabdi S, Johansen-Berg H (2011) Tractography: where do we go from here?Brain Connect1: 169–183. doi: 10.1089/brain.2011.0033[PMC free article][PubMed]

40. Girard G, Whittingstall K, Deriche R, Descoteaux M (2014) Towards quantitative connectivity analysis: reducing tractography biases. Neuroimage98: 266–278. doi: 10.1016/j.neuroimage.2014.04.074[PubMed]

41. Hoel PG (1984) Introduction to mathematical statistics. John Wiley & Sons, Inc, New York, 5fth edition.

42. Wonnacott TH, Wonnacott RJ (1972) Introductory statistics, volume 19690 Wiley; New York.

43. Holm S (1979) A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics: 65–70.


Leave a Reply

Your email address will not be published. Required fields are marked *