**Bilogical, Archeological and Culturological Evidences of Paleoasiatic Origin of Northern Mongoloids, Caucasoids and American Indians**

Ariadna Nazarova

*Institute of Ecology and Evolution Problems, Russian Academy of Sciences, Moscow, Russia* 

#### **1. Introducton**

We were distinguished the Caucasoids frequencies of genes of blood proteins and enzymes in populations of Altaians. The matrix of genetic distances of 28 alleles of 12 loci of proteins, enzymes and blood groups of 11 populations of Europe, Asia and America, and than the matrix of genetic distances of 55 human populations of Europa , Asia, America Africa and Oceania were calculated. On data of this matrixes we constructed the evolutional dendrogrammes. From this dendrogrammes we suggested that Caucasoids were differentiated with North Mongoloids and Amerinds from Ancient Asiatic population while Middle Palaeolithic in region of Altay and in neighbour regions.The investigations of mitochondrial DNA polymorphism are supported our hypothesis about paleoasiatic origin of North Mongoloids, Caucasoids and Amerinds. The haplogroups of mitochondrial DNA of different human populations of Eurasia and America were marked the way of ancient tribes in their Palaeolithic migrations on map constructed by us. The data of Russian anthropologists also supported Palaeoasiatic origin of Caucasoids, for example the distribution of frequencies of supraorbital canals in different human populations.

Russian scientists decoded the petroglifs near Baikal lake as ancient inscription. This inscription marked the holy plases of the goddess Ama-terasu who belonged to the pantheon of ancient inhabitants of Nothern Asia (Siberia) who were ancestors both of the Shumers and the Khetts (ancient Caucasoids) as well as the Japanese (Mongoloids).

We found a Caucasoid frequency of genes of blood proteins and enzymes in seven populations of Altians (1), Table 1. Calculation of the genetic distances of 11 human populations of Europe, Asia and America, more exactly, of the Sami (Lapps), Nentsi, Nganasans, Evenks, Yakuts, Mongols, Altians, Russians, Finns, Germans and American Indians by taking 28 allele frequencies of proteins, enzymes and blood groups showed a certain closeness in the inherited traits of Caucasoids and Northern Mongoloids (2). We made a dendrogram of the relatedness of the population (2) from the data of the matrix of genetic distances of the human populations of Europe, Asia and America enumerated above. Based on it, we have made the assumption that the differentiation from the common ancient Asiatic population of ancestors of American Indians (Amerinds) occurred earlier. It

Bilogical, Archeological and Culturological Evidences of

Paleoasiatic Origin of Northern Mongoloids, Caucasoids and American Indians 221

We drew the possible route of migration of the human population having the haplogroup of mitochondrial DNA, beginning from the Middle Paleolithic from the place of their differentiation in the center of Asia to the place of there current habitation ( Figure 2).

Fig. 1. The dendrogram of 55 populations of Europe, Asia , America, Africa and Oceania constructed by matrix of genetic distances of those populations on 28 allele of 12 loci

proteins, enzymes and blood groups.

probably occurred around 50,000 years ago—the time of the differentiation of the Caucasoids and Mongoloids according to the data of Nei (3) who calculated the genetic distances of the main human races based on the big number of genetic markers.


Table 1. The gene frequencies of seven populations of Altaians.

The next to differentiate were the ancestors of the Sami according to the dendrogram (2) of the ancestors of the populations inhabiting the region of Southern Siberia and (or) the neighboring regions of Central Asia. The remaining populations of the tree divided further into two clusters, there being two subclusters in one of them—the Nentsi, Nganasani and Evenks in one and the Yakuts, Mongols and Altaians in the other. In the other cluster are the populations of the contemporary Caucasoids—Russians, Germans and Finns. That the Caucasoids and Northern Mongoloids are related is confirmed by the data on the polymorphism of the mitochondrial (mt) DNA which showed the presence of similar haplogroups in Altaians and the European Caucasoids (4)—the haplogroups H,J,K,T,U,V,W,F, in the Sami, Evenks and American Indians (5)—the haplogroup V, and in the Altaians and American Indians (6)—haplogroups A,B,C,D. Finally, an identical haplogroup X found in Caucasoids and American Indians (7) confirmed a common origin of these two groups of humans, and the methods of molecular biology showed that this haplogroup X in the Indians was not introduced by contacts with Europeans after the discovery of America by Columbus, but is ancient.

probably occurred around 50,000 years ago—the time of the differentiation of the Caucasoids and Mongoloids according to the data of Nei (3) who calculated the genetic

distances of the main human races based on the big number of genetic markers.

Table 1. The gene frequencies of seven populations of Altaians.

discovery of America by Columbus, but is ancient.

The next to differentiate were the ancestors of the Sami according to the dendrogram (2) of the ancestors of the populations inhabiting the region of Southern Siberia and (or) the neighboring regions of Central Asia. The remaining populations of the tree divided further into two clusters, there being two subclusters in one of them—the Nentsi, Nganasani and Evenks in one and the Yakuts, Mongols and Altaians in the other. In the other cluster are the populations of the contemporary Caucasoids—Russians, Germans and Finns. That the Caucasoids and Northern Mongoloids are related is confirmed by the data on the polymorphism of the mitochondrial (mt) DNA which showed the presence of similar haplogroups in Altaians and the European Caucasoids (4)—the haplogroups H,J,K,T,U,V,W,F, in the Sami, Evenks and American Indians (5)—the haplogroup V, and in the Altaians and American Indians (6)—haplogroups A,B,C,D. Finally, an identical haplogroup X found in Caucasoids and American Indians (7) confirmed a common origin of these two groups of humans, and the methods of molecular biology showed that this haplogroup X in the Indians was not introduced by contacts with Europeans after the We drew the possible route of migration of the human population having the haplogroup of mitochondrial DNA, beginning from the Middle Paleolithic from the place of their differentiation in the center of Asia to the place of there current habitation ( Figure 2).

Fig. 1. The dendrogram of 55 populations of Europe, Asia , America, Africa and Oceania constructed by matrix of genetic distances of those populations on 28 allele of 12 loci proteins, enzymes and blood groups.

Bilogical, Archeological and Culturological Evidences of

back in 1984 (12).

are in three neighboring subclusters.

Paleoasiatic Origin of Northern Mongoloids, Caucasoids and American Indians 223

Europe in him time "Ploughing Skifes". The tribes of the Finnish speaking tribes, the Merjia and the Muroma who are related to the Chuvashes and Udmurts and who inhabed the Moscow, Vladimir and Yaroslvavl regions back in the 1st century BC, became part of the Russian population and totally lost their individual national identity. So the closeness of Russians to Finnish and Iranian populations is understandable. The next big cluster (Fig. 1) begins with the cluster including Arabs and Italians, then there is the subcluster of Bulgarians, Chechens and Armenians—these are the descendents of the tribes settling the regions of the North Caucasus and South Caucasus . The closeness of the Armenians and Chechens is confirmed by the closeness of the Armenian and the Vainah languages (Starostin) (14). The next subcluster is the branches of Georgians and Evenks. Their closeness is due to the fact that the ancestors of the Georgians also roamed around north Asia in ancient times. The Caucasian frequency of the genes of the Evenks we discovered

The Basques and white Northern Americans being in the same subcluster is explained by their common Celtic substrata. In the neighboring recently split off subclusters we find the Swedes, Finns, Estonians, Talyshes and Belorussians. The Talysh are Iranian speaking ethnos in Zakavkasia which we have studied for the first time genetically (13). Its closeness

The subcluster of the English, French and Scots is united by a common Celtic substrata. The Germans and Serbs are in a subcluster together and all the rest of the populations of central and southeastern Europe—the Moldavians, Hungarians, Croatians, Czechs and Ukrainians -

The subcluster of Tartars and Middle East Jews is explained by their common Turks origin: the Tartars are the descendents of the Volga Bulgars who earlier lived in the Bulgar Kaganat in North Caucasus and Azov Sea Region, while the Jews are descendents of the Hazars who lived in the Hazar Kaganate on the Lower Volga and North Caucasus(14). The last subcluster of this big cluster begins with the branch of the Greeks and Mary. The Greeks, the descendents of the ancients Caucasoid Akheitses probably also migrated from Asia to Europe in ancient times as did the Mari, one of the Finnish populations whose early homeland had been Asia (10). Then come the Asian subclusters. The first of them are the

Altaians and the Mongols, and also the Mansi, a people belonging to the Ugor group.

The second branch of the huge cluster including all the Caucasoid populations and the subcluster of the transitional populations—the Altaians, Mongols and Mansi—are the Papua of New Guniea. Then comes the subcluster of the Yakuts and Nganasans, and also the American Eskimos. After that there is the subcluster of the Chukchi and the Eskimos of Chukotka. And finally the subcluster of Japanese and Vietnamese and also the Chinese. The second branch of the cluster of Mongoloids in Eastern Asia is the black Africans. So at the bottom of the dendrogram there is the branch of the Laps (Sami) and the branch of the Indians, who have a complicated origin since they are the result of the intermingling of the Veddoid tribes and the tribes of ancient Caucasoids. The very lowest branch of the dendrogram is the American Indians, whose ancestors were the first to differentiate from the common ancient Asiatic population in the mid Paleolithic. There is anthropological data indicating the Caucasoids were in Asia in the Paleolithic. Academician V.P. Alexeev (16)

to the northern Caucasoids may indicate the route of migration from Asia to Europe.

The migration of the ancient human populations could have been caused by the migration of animals which the Paleolithic people hunted as a result of changes in the climate. The ancestors of the carribou and bisons in the Paleolithic inhabited the region of Southern Siberia (8), but when the climate changed they migrated to the far northeast of Siberia, and then crossed the Bering Strait to America. The ancient tribes of Amerinds followed them. The data on the migration of the invertebrates (annelids) and the migration of birds described in the book (9) shows a general tendency of representatives of the animal kingdom to migrate in ancients time from south Siberia to its north.

We calculated the matrix of genetic distances of 55 human populations belonging to four big human races and living in Europe, Asia, America, Africa and Oceania (10). Using the data of this matrix, we constructed an evolutionary dendrogram of these 55 populations (Fig. 1).

Fig. 2. The ways of migrations of ancient human populations marked with haplogroups of mitochondrial DNA.

From this dendrogram it is evident that the first to differentiate, as in the dendrogram in (2), were the American Indians, and then the Sami. The Poles turned out to be the closest of the Slavic peoples to Russians just as when we calculated the genetic distances of the less number of genetic loci (11). The Iranians, Komi, Chuvashes, Udmurts, Nentsi and the subcluster with the Ossetians and Azerbaijanis turned out to be in one big cluster with Russians.

There is the opinion that Russian are descendents of ancient Iranian Skife tribes who migrated earlier around Asia. Herodot named the tribes inhabiting the territory of eastern

The migration of the ancient human populations could have been caused by the migration of animals which the Paleolithic people hunted as a result of changes in the climate. The ancestors of the carribou and bisons in the Paleolithic inhabited the region of Southern Siberia (8), but when the climate changed they migrated to the far northeast of Siberia, and then crossed the Bering Strait to America. The ancient tribes of Amerinds followed them. The data on the migration of the invertebrates (annelids) and the migration of birds described in the book (9) shows a general tendency of representatives of the animal

We calculated the matrix of genetic distances of 55 human populations belonging to four big human races and living in Europe, Asia, America, Africa and Oceania (10). Using the data of this matrix, we constructed an evolutionary dendrogram of these 55 populations

Fig. 2. The ways of migrations of ancient human populations marked with haplogroups of

From this dendrogram it is evident that the first to differentiate, as in the dendrogram in (2), were the American Indians, and then the Sami. The Poles turned out to be the closest of the Slavic peoples to Russians just as when we calculated the genetic distances of the less number of genetic loci (11). The Iranians, Komi, Chuvashes, Udmurts, Nentsi and the subcluster with the Ossetians and Azerbaijanis turned out to be in one big cluster with

There is the opinion that Russian are descendents of ancient Iranian Skife tribes who migrated earlier around Asia. Herodot named the tribes inhabiting the territory of eastern

kingdom to migrate in ancients time from south Siberia to its north.

(Fig. 1).

mitochondrial DNA.

Russians.

Europe in him time "Ploughing Skifes". The tribes of the Finnish speaking tribes, the Merjia and the Muroma who are related to the Chuvashes and Udmurts and who inhabed the Moscow, Vladimir and Yaroslvavl regions back in the 1st century BC, became part of the Russian population and totally lost their individual national identity. So the closeness of Russians to Finnish and Iranian populations is understandable. The next big cluster (Fig. 1) begins with the cluster including Arabs and Italians, then there is the subcluster of Bulgarians, Chechens and Armenians—these are the descendents of the tribes settling the regions of the North Caucasus and South Caucasus . The closeness of the Armenians and Chechens is confirmed by the closeness of the Armenian and the Vainah languages (Starostin) (14). The next subcluster is the branches of Georgians and Evenks. Their closeness is due to the fact that the ancestors of the Georgians also roamed around north Asia in ancient times. The Caucasian frequency of the genes of the Evenks we discovered back in 1984 (12).

The Basques and white Northern Americans being in the same subcluster is explained by their common Celtic substrata. In the neighboring recently split off subclusters we find the Swedes, Finns, Estonians, Talyshes and Belorussians. The Talysh are Iranian speaking ethnos in Zakavkasia which we have studied for the first time genetically (13). Its closeness to the northern Caucasoids may indicate the route of migration from Asia to Europe.

The subcluster of the English, French and Scots is united by a common Celtic substrata. The Germans and Serbs are in a subcluster together and all the rest of the populations of central and southeastern Europe—the Moldavians, Hungarians, Croatians, Czechs and Ukrainians are in three neighboring subclusters.

The subcluster of Tartars and Middle East Jews is explained by their common Turks origin: the Tartars are the descendents of the Volga Bulgars who earlier lived in the Bulgar Kaganat in North Caucasus and Azov Sea Region, while the Jews are descendents of the Hazars who lived in the Hazar Kaganate on the Lower Volga and North Caucasus(14). The last subcluster of this big cluster begins with the branch of the Greeks and Mary. The Greeks, the descendents of the ancients Caucasoid Akheitses probably also migrated from Asia to Europe in ancient times as did the Mari, one of the Finnish populations whose early homeland had been Asia (10). Then come the Asian subclusters. The first of them are the Altaians and the Mongols, and also the Mansi, a people belonging to the Ugor group.

The second branch of the huge cluster including all the Caucasoid populations and the subcluster of the transitional populations—the Altaians, Mongols and Mansi—are the Papua of New Guniea. Then comes the subcluster of the Yakuts and Nganasans, and also the American Eskimos. After that there is the subcluster of the Chukchi and the Eskimos of Chukotka. And finally the subcluster of Japanese and Vietnamese and also the Chinese. The second branch of the cluster of Mongoloids in Eastern Asia is the black Africans. So at the bottom of the dendrogram there is the branch of the Laps (Sami) and the branch of the Indians, who have a complicated origin since they are the result of the intermingling of the Veddoid tribes and the tribes of ancient Caucasoids. The very lowest branch of the dendrogram is the American Indians, whose ancestors were the first to differentiate from the common ancient Asiatic population in the mid Paleolithic. There is anthropological data indicating the Caucasoids were in Asia in the Paleolithic. Academician V.P. Alexeev (16)

Bilogical, Archeological and Culturological Evidences of

translated it as "Ama-Terasu is judged by Inanna".

populations.

Paleoasiatic Origin of Northern Mongoloids, Caucasoids and American Indians 225

That may be confirmation of their common Asiatic origin. The frequency of the canals among northern Caucasoids—Poles, Dutch, and the English—is lower. It is between 17-21%. The frequency of the supra orbital canals in the Mongoloids of eastern Asia—the Japanese, Koreans, and Chinese and also the Mongols (the Mongoloids in the center of Asia) is between 43-48%. It is interesting that the frequency of the canals among the ancient Egyptians, Etruscans, ancient Slaves (Kiev Polyans) and the Indians of Uttar Pradesh is practically the same—25-28%, which is a bit higher than for the Novgorod Slovenes. This is also evidentely connected with these people being the descendents of ancient Paleo Asiatic

The linguist A. G. Kifishin, decoded the petroglyph discovered by the archeologists V.E. Larichev and A.P. Okladnikov in the Prebaikaliye. As is known, the academician A.P. Okladnikov published the petroglyphs discovered on the shores of the Lena, the Baikal, the Amur and on the Altai. Larichev studied the archeological culture of the Malts in the Irkutsk region dating back to 20,000 years ago. In the opinion of Kifishin, the cliff inscription found by archeologists near the village of Suon-Tit on the river Aldan is the first in the world. It was done in the 18,000 years ago and stands for the following: ama+VARAdara+su-kud-Sin which means Ama Terasu is judged by Sin if translated from Shumer. Kifishin decoded the petroglyphs at ten points in Eastern Siberia (Pribaikaliya). Figure 3 is a petroglyph from a cliff at Khana Shuulun which Kifishin decoded as"ama-inanna-BARA2 dara-si" and

Here for the first time Inanna (A man on a horse-holy star) is in the image of the sun. All ten petroglyphs in Eastern Siberia decoded by Kifishin are in an article by Kifishin and the historian Kikeshev (18). Kifishin and Kikeshev think these places are ancient holy places of the goddess Ama-terasu who belonged to the pantheon of ancients inhabitants of northern Asia (Siberia) who were ancestors both of the Shumers and the Khetts (ancient Caucasoids) as well as the Japanese (Mongoloids).It turned out that there are parallels in the pantheons of the gods of the ancient Shumers and Khetts and in the Japanese religion of Shinto. It is thought that the Japanese came about from an intermingling of the Malaysian and Polenesian tribes and the tribes of the Ural-Altay groups who crossed the Korean Peninsula and ended up on the Japanese islands. In the Shinto religion of the Japanese gods exist in the form of animals, plants stones etc. Some linguists think the Japanese language is related to the Altay group of languages, other to the Australian language family. But according to our research, the ancient Japanese, just as the ancient Shumers, lived in the Altai and Zabaikalya (Selenga region where there was the cult of Ama-baragesi). Kifishin thinks that the Avesta Sea Vorukasha is called Baragesi in Shumer. Ama-baragesi is mentioned in the inscriptions on the 2nd Borodinsky cliff near Chelyabinsk in the Ural mountains (18000 years ago), in the proto Shumer archive in the Stone Grave near Azov Sea (12-3,000 BC), in the archive in Mesopotamian Ur (3000 BC), and in the inscriptions of the Urnanshi from Lagasha (2450 BC). So we can see several points of many thousand year migrations of the ancient proto Shumers from the region of Easrtern Siberia across Priazovya to Near Asia. In the book of the Indian scientist Tilak "The Artic Homeland in the Veds" there is data from the epic works of Caucasoids of Asia about the migrations of the ancestors of the Indians from zones around the North Pole that went to the West Ural from north to south, and the migrations of

the ancestors of the Iranians in the same direction, but more east of the Ural.

wrote about the discovery of Paleolithic skulls with Caucasian traits in a cave in Dundyan in China. He also wrote about the Caucasoid traits of Paleolithic people at a site in Sungir in Eastern Europe who appeared there at a later time (25,000 years ago).

Russian anthropolgist T.V. Tomashevich, discovered a gradient of distribution of the frequencies of the supra orbital canals of the human skulls (17),(Table 2). Supraorbital arteries and veins of the orbital arteries pass through the supraorbital canals. As is evident from the data in Table 2, the highest frequency of encountering supra orbital canals is among the Sams, American Indians, and also the northern Mongoloids—the Yakuts, Yukargirs, Evenks, Chuchuks, and Eskimos. That is possible due to their paleo- Asiatic origin. The frequency of the supra orbital canals is very close and varies without the bounds of 30-38% in the Kets, Yukagirs, Russians, Mansi, Ocetians, and Armenians.

Diferentiation of Mongoloids and Caucasoid


Table 2.

wrote about the discovery of Paleolithic skulls with Caucasian traits in a cave in Dundyan in China. He also wrote about the Caucasoid traits of Paleolithic people at a site in Sungir in

Russian anthropolgist T.V. Tomashevich, discovered a gradient of distribution of the frequencies of the supra orbital canals of the human skulls (17),(Table 2). Supraorbital arteries and veins of the orbital arteries pass through the supraorbital canals. As is evident from the data in Table 2, the highest frequency of encountering supra orbital canals is among the Sams, American Indians, and also the northern Mongoloids—the Yakuts, Yukargirs, Evenks, Chuchuks, and Eskimos. That is possible due to their paleo- Asiatic origin. The frequency of the supra orbital canals is very close and varies without the bounds

Eastern Europe who appeared there at a later time (25,000 years ago).

of 30-38% in the Kets, Yukagirs, Russians, Mansi, Ocetians, and Armenians.

Populations Frequency of supraorbital canals, %

Slovens of Novgorod region, XII-XIV century. 32,5 (152)

Kiev Poljans, IX-XIII century 25,0 (92) Etrusks, VIII-III century B.C. 26,9 (70)

Hollands 21,2 (170) Ancient Egyptians 28,3 Negroes of Ruanda 33,6 (61) Indians of Uttar-Pradesh 25,2 (238)

Table 2.

Negroes of USA 22,3 (202) Japanese 43,2 (1008) Koreans 46,1 (660) Australians 19,0 (122) Chinese 46,5 (202)

Diferentiation of Mongoloids and Caucasoid

Poles 21,3 (47) Russians 35,9 (204) Armenians 30,6 (242) Mansi 32,1 (112) Kets 33,3 (38) Yukagirs 38,1 (42) Ossetians 39,4 (314) Bashkirs 40,0 (122) Sami (Lapps) 47,4 (221) Amerinds 50,2 (124) Chuckchi 57,1 (70) Evenks 57,5 (40) Eskimos 57,4 (302) Yakuts 63,0 (144) English 17,0 (186) Mongols 48,3 (60)

That may be confirmation of their common Asiatic origin. The frequency of the canals among northern Caucasoids—Poles, Dutch, and the English—is lower. It is between 17-21%. The frequency of the supra orbital canals in the Mongoloids of eastern Asia—the Japanese, Koreans, and Chinese and also the Mongols (the Mongoloids in the center of Asia) is between 43-48%. It is interesting that the frequency of the canals among the ancient Egyptians, Etruscans, ancient Slaves (Kiev Polyans) and the Indians of Uttar Pradesh is practically the same—25-28%, which is a bit higher than for the Novgorod Slovenes. This is also evidentely connected with these people being the descendents of ancient Paleo Asiatic populations.

The linguist A. G. Kifishin, decoded the petroglyph discovered by the archeologists V.E. Larichev and A.P. Okladnikov in the Prebaikaliye. As is known, the academician A.P. Okladnikov published the petroglyphs discovered on the shores of the Lena, the Baikal, the Amur and on the Altai. Larichev studied the archeological culture of the Malts in the Irkutsk region dating back to 20,000 years ago. In the opinion of Kifishin, the cliff inscription found by archeologists near the village of Suon-Tit on the river Aldan is the first in the world. It was done in the 18,000 years ago and stands for the following: ama+VARAdara+su-kud-Sin which means Ama Terasu is judged by Sin if translated from Shumer. Kifishin decoded the petroglyphs at ten points in Eastern Siberia (Pribaikaliya). Figure 3 is a petroglyph from a cliff at Khana Shuulun which Kifishin decoded as"ama-inanna-BARA2 dara-si" and translated it as "Ama-Terasu is judged by Inanna".

Here for the first time Inanna (A man on a horse-holy star) is in the image of the sun. All ten petroglyphs in Eastern Siberia decoded by Kifishin are in an article by Kifishin and the historian Kikeshev (18). Kifishin and Kikeshev think these places are ancient holy places of the goddess Ama-terasu who belonged to the pantheon of ancients inhabitants of northern Asia (Siberia) who were ancestors both of the Shumers and the Khetts (ancient Caucasoids) as well as the Japanese (Mongoloids).It turned out that there are parallels in the pantheons of the gods of the ancient Shumers and Khetts and in the Japanese religion of Shinto. It is thought that the Japanese came about from an intermingling of the Malaysian and Polenesian tribes and the tribes of the Ural-Altay groups who crossed the Korean Peninsula and ended up on the Japanese islands. In the Shinto religion of the Japanese gods exist in the form of animals, plants stones etc. Some linguists think the Japanese language is related to the Altay group of languages, other to the Australian language family. But according to our research, the ancient Japanese, just as the ancient Shumers, lived in the Altai and Zabaikalya (Selenga region where there was the cult of Ama-baragesi). Kifishin thinks that the Avesta Sea Vorukasha is called Baragesi in Shumer. Ama-baragesi is mentioned in the inscriptions on the 2nd Borodinsky cliff near Chelyabinsk in the Ural mountains (18000 years ago), in the proto Shumer archive in the Stone Grave near Azov Sea (12-3,000 BC), in the archive in Mesopotamian Ur (3000 BC), and in the inscriptions of the Urnanshi from Lagasha (2450 BC). So we can see several points of many thousand year migrations of the ancient proto Shumers from the region of Easrtern Siberia across Priazovya to Near Asia. In the book of the Indian scientist Tilak "The Artic Homeland in the Veds" there is data from the epic works of Caucasoids of Asia about the migrations of the ancestors of the Indians from zones around the North Pole that went to the West Ural from north to south, and the migrations of the ancestors of the Iranians in the same direction, but more east of the Ural.

Bilogical, Archeological and Culturological Evidences of

Genet., 1978, V.23, P. 341-369.

**2. References** 

1410.

1322.

63, P.1309-1322.

P1701-1707.

1987, Munchen.

M., Nauka, 1978, P.284 .

1988, M., Nauka, 5-32.

the Northern Hemisphere. SPB, 1903.

Lipetsk Publishers, 2000, P.14-20.

USSR, 1991, 317, No.6, P1484-1486.

the Caucasus. M., Nauka, 1990.

Paleoasiatic Origin of Northern Mongoloids, Caucasoids and American Indians 227

[1] Nazarova A.F., Kuznetsova M.G. The genetic structure of Altaians populations. Reports

[2] Nazarova A.F. Genetic data concerning the problems the differentiations of Nothern

[3] Nei M. The theory of genetic distance and evolutions of human races. Jap. J. Hum.

[4] Derenko M.V., Denisova G.A., Malyarchuk B.A., Dambueva I.K., Luzina F.A., Lotosh

[5] Lahermo P., Sajantila A., Sistonen P., Lukka M., Aula P., Peltonen L., Savontaus M.-L.

[6] Sukernik R.I., Shurr T.G., Starikovskaya E.B., Wallace D.C. Mitochondrial DNA variation

[7] Brown M.D., Hosseini S.H., Torroni A., et al. mt DNA haplogroup X: an ancient link

[8] Vereschagin N.K. Questions of Theriology: General and Regional Theriogeography.

[9] Kobelt V. The Geographical Distribution of Animals in the Cold and Moderate Zones of

[10] Nazarova A.F., Alkhutov S.M.. In the book: Evolution of human populations, M.,

[11] Nazarova A.F. Population Genetics of Russians: Genealogical Analysis, Gene frequencies and Genetic Distances. Reports RAN, 1994, 339, No.4, P.563-568. [12] Rychkov Yu.G., Spitsyn V.A., Shneider Yu.V., Nazarova A.F., Boeva S.B.,

[13] Nazarova A.F. Genetics of the population of the Talyshes of Azerbaijan. Reports AN

[14] Novoseltsev A.P. The Khazar State and Its Role in the History of Eastern Europe and

[15] Starostin S.A., Dyakonov I.M. Hurrito-Urartian as an Eastern Caucasian Language.

[16] Alexeev V.P.Paleoanthropology of the Earth and the Formation of the Human Races.

[17] Tomashevich T.V. Laws of Distribution of the Frequencies of Supra Orbital Canals of the Human Skull. Question of Anthropology, 1988, Issue 80, P.119-128.

Novoradovskiy A.G., Tikhomirova E.V. Genetica (Russians), 1984, T.20, No.10,

Mongoloids, American Indians and Caucasoids in the Northern Territory of

E.A., Dorzhu Ch.M., Karamchakova O.N., Solovenchuk L.L., Zakharov I.A. The Structure of Gene Pools of Ethnic Populations of Altai-Sayan Region based on of mitochondrial DNA Polymorphism Data. Genetica(Russians), 2001, No. 10, P. 1402-

The genetic relationship between the Finns and the Finnish Saami (Lapps): analysis of Nuclear DNA and mt DNA. Amer. J. Hum. Genet, 1996, V. 58, P.1309-

in native Siberian, with special reference to the evolutionary history of American

between Europe/Western Asia and North America? Amer.J.Hum.Genet., 1998,V.

of Russian Academy of Sci., 1993, 333, 3, P. 405-409.

Eurasia. Anthropologisher Anzeiger, 2005, 63, 4, 353-364.

Indians. Genetica (Russian), 1996,V. 32,No.3, P. 432-439.

Fig. 3. Petroglif at Hana Shuluun (East Siberia) deshifrated as palaeolithic writing. (Hana-Shuluum)

So both the biological data, the genetic, anthropoligical, paleozoological, and the data of the archeology, and history indicates that the center of Asia (Southern Siberia and the neighboring regions) is the center of differentiation of the European and Asian Caucasoids as well as the Northern Mongoloids and American Indians. It also indicated that they got to the place where they live now as a result of thousands of years of migration.

#### **2. References**

226 Polyphonic Anthropology – Theoretical and Empirical Cross-Cultural Fieldwork

Fig. 3. Petroglif at Hana Shuluun (East Siberia) deshifrated as palaeolithic writing.

the place where they live now as a result of thousands of years of migration.

So both the biological data, the genetic, anthropoligical, paleozoological, and the data of the archeology, and history indicates that the center of Asia (Southern Siberia and the neighboring regions) is the center of differentiation of the European and Asian Caucasoids as well as the Northern Mongoloids and American Indians. It also indicated that they got to

(Hana-Shuluum)


**0**

**14**

**Applying Craniofacial Metrics to Adapt 3D**

Traditionally, the fields of anthropology and biomedical engineering are two diverse areas of science. Over the last few years various subfields of biomedical engineering have been trending towards personalized medicine. Presently there are a limited number of models that neuroscientists use to evaluate theory and solve application problems, thus depersonalizing medicine. This chapter introduces a novel integration of how anthropology can lend to and improve personalized neuromedicine through the study of physical charactersistics, the relationship of races, and gender. By integrating anthropometric and craniofacial data, future head models should accomdate race, gender, age, and size to better approximate personalized

The absence of anthropometrically accurate generic head models limits the field of computational neuroscienece to either simplistic, geometric models or complex, personalized models. Implementation of a universal descriptor for describing three-dimensional (3D) geometry and variations in geometry of similar anatomic structures, such as the human head, extends the efficacy and applications of most systems developed to aid tasks in the fields of computational modeling, automated medical image analysis, image guided surgery and 3D

This chapter opens with reviewing and evaluating various head models ranging from spherical to personalized complex models in sections 3 and 4, respectively. Then section 5 spans the gap between the simple and complex models to describe a range of adaptable generic models. Next, section 6 explains the geometric descriptor of the radial vector technique, and then section 7 demonstrates the application of craniofacial data using the radial angular matrix (RAM). The RAM describes, preserves, and spatially reconstructs magnetic resonance image (MRI) data. Therefore, the example modifies various ethnic groups and sub-groups according to Farkas et al. (2005). The resultant generic models depict the benefits of employing this technique. The chapter concludes with a discussion based upon the

anthropometry. This technique is known as the radial vector representation.

**1. Introduction**

**2. Motivation**

medicine on a wide-scale approach.

craniofacial morphing of the generic models.

Katrina E. Wendel-Mitoraj1 and Michael E. Osadebey2

**Generic Head Models**

<sup>1</sup>*Tampere University of Technology*

<sup>2</sup>*NeuroRX Research Inc.*

<sup>1</sup>*Finland* <sup>2</sup>*Canada*

[18] Kifishin A.G., Kikeshev N.I. Ten Sintoistic Holy Places of Pribaicalie. The Messenger of International Slavic Institute (Russians), 2005, N 9, P. 86-94.

## **Applying Craniofacial Metrics to Adapt 3D Generic Head Models**

Katrina E. Wendel-Mitoraj1 and Michael E. Osadebey2

<sup>1</sup>*Tampere University of Technology* <sup>2</sup>*NeuroRX Research Inc.* <sup>1</sup>*Finland* <sup>2</sup>*Canada*

#### **1. Introduction**

228 Polyphonic Anthropology – Theoretical and Empirical Cross-Cultural Fieldwork

[18] Kifishin A.G., Kikeshev N.I. Ten Sintoistic Holy Places of Pribaicalie. The Messenger of

International Slavic Institute (Russians), 2005, N 9, P. 86-94.

Traditionally, the fields of anthropology and biomedical engineering are two diverse areas of science. Over the last few years various subfields of biomedical engineering have been trending towards personalized medicine. Presently there are a limited number of models that neuroscientists use to evaluate theory and solve application problems, thus depersonalizing medicine. This chapter introduces a novel integration of how anthropology can lend to and improve personalized neuromedicine through the study of physical charactersistics, the relationship of races, and gender. By integrating anthropometric and craniofacial data, future head models should accomdate race, gender, age, and size to better approximate personalized medicine on a wide-scale approach.

#### **2. Motivation**

The absence of anthropometrically accurate generic head models limits the field of computational neuroscienece to either simplistic, geometric models or complex, personalized models. Implementation of a universal descriptor for describing three-dimensional (3D) geometry and variations in geometry of similar anatomic structures, such as the human head, extends the efficacy and applications of most systems developed to aid tasks in the fields of computational modeling, automated medical image analysis, image guided surgery and 3D anthropometry. This technique is known as the radial vector representation.

This chapter opens with reviewing and evaluating various head models ranging from spherical to personalized complex models in sections 3 and 4, respectively. Then section 5 spans the gap between the simple and complex models to describe a range of adaptable generic models. Next, section 6 explains the geometric descriptor of the radial vector technique, and then section 7 demonstrates the application of craniofacial data using the radial angular matrix (RAM). The RAM describes, preserves, and spatially reconstructs magnetic resonance image (MRI) data. Therefore, the example modifies various ethnic groups and sub-groups according to Farkas et al. (2005). The resultant generic models depict the benefits of employing this technique. The chapter concludes with a discussion based upon the craniofacial morphing of the generic models.

dimensions separated by gender (BestWigOutlet, 2005; 2009; HatsUK, 2005; 2012; TheHatSite, 2005; WigSalon, 2005; 2012). WigSalon (2005; 2012) assesses that 92% of women have heads circumferentially measuring between 54.6 cm and 57.2 cm. The average-female cephalometric circumference equates to 55.4 cm per common head accoutrements; thus, the average-female head radius measures 8.82 cm. Likewise calculating the average-male head circumferencial measurement of 58 cm, the average head radius of a male calculates to 9.23 cm; therefore; the average male head is 0.4 cm larger in the radial direction than the average female head

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 231

Furthermore, several sources either reference one set of spherical radii or very few sets of realistic data for an entire population. The majority of these references use radial and thickness measurements that fall inline with an average male head size or larger of Northern European, Central European or caucasian North American descent (Cuffin, 1995; 1996; Ferree et al., 2000; Malmivuo & Plonsey, 1995; Ogoshi et al., 2003; Rush & Driscoll, 1969; Zhou & van Oosterom, 1992). These larger values instantly disregard youths and females in these racial ethnicities and both males and females of other ethnicities in terms of the size and shape variation between genders and across cultures (Adeloye et al., 1975; Farkas et al., 2005; Lynnerup et al.,

The poor sphericity of the viscerocranium and the frontal and temporal lobes of the brain led researchers into improving the geometry beyond the spherical model (Hämäläinen & Sarvas, 1989). Realistically-shaped models specifically correspond to a unique individual and could represent other individuals that are of the same gender, same ethnic group, very similar craniofacial structures and a similar age. Consequently, these models increase the model complexity in order to reduce errors in source localization, source imaging, and scalp potentials Babiloni et al. (1997); Cuffin (1995); Gevins et al. (1991); Huiskamp et al. (1999); Michel et al. (2004). These complex models require numerical solutions such as the boundary element method (BEM), finite element method (FEM), or finite difference method (FDM) (Hallez et al., 2007; Wendel, Väisänen, Malmivuo, Gencer, Vanrumste, Durka, Magjarevi´c,

Realistic models are constructed from a set of segmented image slices, usually originating from one of the primary medical imaging modalities — computed tomography (CT), MRI, or a matched MRI-CT set (Cuffin, 1995; Haueisen et al., 1997; Huiskamp et al., 1999; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008). Considering their pros and cons, CT more accurately images the skull due to its sensitivity to hard tissue via radiation, whereas MRI better images soft tissues such as the skin, cortex, and the gray matter-white matter boundary and is safe. The differences between the three-layer CT- and MRI-based models in (Huiskamp

Unfortunately, diagnostic equipment that is available to adults is not optimal for children in terms of safe radiation limits. Such imaging modalities include CT, PET, and SPECT, which use ionizing radiation or radioactive tracers. Due to the nature of these technologies, children will only obtain such screening in extreme cases Yusof (2007). Magnetoencephalograpy (MEG) is safe, but it is often limited by the availability of smaller helmets, which locate the gradiometers closer to the scalp surface. EEG is also safe and readily adaptable to various head sizes due to the elastic nature of most EEG caps. Therefore, analyses that require

Supek, Pascu, Fontenelle & Grave de Peralta Menendez, 2009).

et al., 1999) illustrate significant differences at the base of the skull.

concerning racial and ethnic neutrality.

**4. Realistic individual models**

2005).

#### **3. Spherical and elliptical models**

The forward problem has a unique solution (Malmivuo & Plonsey, 1995; Wendel, Väisänen, Malmivuo, Gencer, Vanrumste, Durka, Magjarevi´c, Supek, Pascu, Fontenelle & Grave de Peralta Menendez, 2009), but the model it is based upon is still only an estimate of the anatomy and physiology of the human head. The human head can be modeled and analyzed as a sphere or an ellipsoid. These simplistic geometries can only explain the theory of how something works regarding neuroscience but are incapable of identifying accurate results. The spherical model was introduced by the seminal works of Rush & Driscoll (1968; 1969). They proposed three concentric spheres to represent the brain, skull, and scalp. In the last four decades, several studies have used this configuration (Gordon et al., 2006; Malmivuo et al., 1997; Ryynänen et al., 2004a;b; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008; Wendel, Väisänen, Kybartaite, Hyttinen & Malmivuo, 2010). The CSF has been added as the fourth shell to the spherical model (Ferree et al., 2000; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008; Wendel, Väisänen, Kybartaite, Hyttinen & Malmivuo, 2010; Zhou & van Oosterom, 1992). Consequently, these models are referred to as 3-shell and 4-shell models.

These 3- and 4-shell spherical models contribute to neuroscience by theoretically explaining the lead field and volume conductor currents of how a lead measures from the tissue beneathe it. Although the resolution of the spherical and elliptical models is of a few centimeters (Crouzeix et al., 1999; Roth et al., 1993), they explain the general theory. Investigations that continued this pursuit of a general understanding of the neuroelectric phenomena involved often tailor spherical models to address specific issues such as local variations (Cuffin, 1993), noise (Ryynänen et al., 2006), conductivity values (Ryynänen et al., 2006), electrode properties in 2-D and 3-D (Ollikainen et al., 2000; Suesserman et al., 1991), source localization (Vanrumste et al., 2001), and spatial resolution (Malmivuo & Suihko, 2004; Malmivuo et al., 1997).

#### **3.1 Simple generic models**

Simple generic models in the most simplistic form can be represented by geometrical shapes such as spheres and ellipsoids. The elegance of these simple models is inherent in that they can be solved analytically. The analytical method has a direct solution, hence it does not require an iterative numerical solver. This simplicity is extended through to the ellipsoid and perturbed spheroid solutions (Nolte & Curio, 1999). However, when realistically-shaped electrodes replace the point electrode model, a numerical method is necessary to solve either the forward or inverse problem using the spherical volume conductor model (Gordon et al., 2006; Ollikainen et al., 2000; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008).

Several electroencephalography (EEG) or related head modeling publications consistently reference the same or similar measurements all relating to a larger male head of Northern European caucasian descent. These correlations match hat and wig sizes, which correlate with anthropometric, craniometric, and cephalometric data (Department of Defense, 1997; Donelson & Gordon, 1991; Farkas et al., 2005; Howells, 1973). This implies that there is a paucity of analysis for head sizes that are not represented (Yusof, 2007).

In Wendel, Narra, Hannula, Kauppinen & Malmivuo (2008) we previously derived the external radius for our spherical head models from transverse circumferential cephalometric dimensions separated by gender (BestWigOutlet, 2005; 2009; HatsUK, 2005; 2012; TheHatSite, 2005; WigSalon, 2005; 2012). WigSalon (2005; 2012) assesses that 92% of women have heads circumferentially measuring between 54.6 cm and 57.2 cm. The average-female cephalometric circumference equates to 55.4 cm per common head accoutrements; thus, the average-female head radius measures 8.82 cm. Likewise calculating the average-male head circumferencial measurement of 58 cm, the average head radius of a male calculates to 9.23 cm; therefore; the average male head is 0.4 cm larger in the radial direction than the average female head concerning racial and ethnic neutrality.

Furthermore, several sources either reference one set of spherical radii or very few sets of realistic data for an entire population. The majority of these references use radial and thickness measurements that fall inline with an average male head size or larger of Northern European, Central European or caucasian North American descent (Cuffin, 1995; 1996; Ferree et al., 2000; Malmivuo & Plonsey, 1995; Ogoshi et al., 2003; Rush & Driscoll, 1969; Zhou & van Oosterom, 1992). These larger values instantly disregard youths and females in these racial ethnicities and both males and females of other ethnicities in terms of the size and shape variation between genders and across cultures (Adeloye et al., 1975; Farkas et al., 2005; Lynnerup et al., 2005).

#### **4. Realistic individual models**

2 Will-be-set-by-IN-TECH

The forward problem has a unique solution (Malmivuo & Plonsey, 1995; Wendel, Väisänen, Malmivuo, Gencer, Vanrumste, Durka, Magjarevi´c, Supek, Pascu, Fontenelle & Grave de Peralta Menendez, 2009), but the model it is based upon is still only an estimate of the anatomy and physiology of the human head. The human head can be modeled and analyzed as a sphere or an ellipsoid. These simplistic geometries can only explain the theory of how something works regarding neuroscience but are incapable of identifying accurate results. The spherical model was introduced by the seminal works of Rush & Driscoll (1968; 1969). They proposed three concentric spheres to represent the brain, skull, and scalp. In the last four decades, several studies have used this configuration (Gordon et al., 2006; Malmivuo et al., 1997; Ryynänen et al., 2004a;b; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008; Wendel, Väisänen, Kybartaite, Hyttinen & Malmivuo, 2010). The CSF has been added as the fourth shell to the spherical model (Ferree et al., 2000; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008; Wendel, Väisänen, Kybartaite, Hyttinen & Malmivuo, 2010; Zhou & van Oosterom, 1992). Consequently, these models are referred to as 3-shell and 4-shell

These 3- and 4-shell spherical models contribute to neuroscience by theoretically explaining the lead field and volume conductor currents of how a lead measures from the tissue beneathe it. Although the resolution of the spherical and elliptical models is of a few centimeters (Crouzeix et al., 1999; Roth et al., 1993), they explain the general theory. Investigations that continued this pursuit of a general understanding of the neuroelectric phenomena involved often tailor spherical models to address specific issues such as local variations (Cuffin, 1993), noise (Ryynänen et al., 2006), conductivity values (Ryynänen et al., 2006), electrode properties in 2-D and 3-D (Ollikainen et al., 2000; Suesserman et al., 1991), source localization (Vanrumste

et al., 2001), and spatial resolution (Malmivuo & Suihko, 2004; Malmivuo et al., 1997).

Simple generic models in the most simplistic form can be represented by geometrical shapes such as spheres and ellipsoids. The elegance of these simple models is inherent in that they can be solved analytically. The analytical method has a direct solution, hence it does not require an iterative numerical solver. This simplicity is extended through to the ellipsoid and perturbed spheroid solutions (Nolte & Curio, 1999). However, when realistically-shaped electrodes replace the point electrode model, a numerical method is necessary to solve either the forward or inverse problem using the spherical volume conductor model (Gordon et al., 2006; Ollikainen et al., 2000; Wendel & Malmivuo, 2008; Wendel et al., 2007; Wendel, Narra,

Several electroencephalography (EEG) or related head modeling publications consistently reference the same or similar measurements all relating to a larger male head of Northern European caucasian descent. These correlations match hat and wig sizes, which correlate with anthropometric, craniometric, and cephalometric data (Department of Defense, 1997; Donelson & Gordon, 1991; Farkas et al., 2005; Howells, 1973). This implies that there is a

In Wendel, Narra, Hannula, Kauppinen & Malmivuo (2008) we previously derived the external radius for our spherical head models from transverse circumferential cephalometric

paucity of analysis for head sizes that are not represented (Yusof, 2007).

**3. Spherical and elliptical models**

models.

**3.1 Simple generic models**

Hannula, Kauppinen & Malmivuo, 2008).

The poor sphericity of the viscerocranium and the frontal and temporal lobes of the brain led researchers into improving the geometry beyond the spherical model (Hämäläinen & Sarvas, 1989). Realistically-shaped models specifically correspond to a unique individual and could represent other individuals that are of the same gender, same ethnic group, very similar craniofacial structures and a similar age. Consequently, these models increase the model complexity in order to reduce errors in source localization, source imaging, and scalp potentials Babiloni et al. (1997); Cuffin (1995); Gevins et al. (1991); Huiskamp et al. (1999); Michel et al. (2004). These complex models require numerical solutions such as the boundary element method (BEM), finite element method (FEM), or finite difference method (FDM) (Hallez et al., 2007; Wendel, Väisänen, Malmivuo, Gencer, Vanrumste, Durka, Magjarevi´c, Supek, Pascu, Fontenelle & Grave de Peralta Menendez, 2009).

Realistic models are constructed from a set of segmented image slices, usually originating from one of the primary medical imaging modalities — computed tomography (CT), MRI, or a matched MRI-CT set (Cuffin, 1995; Haueisen et al., 1997; Huiskamp et al., 1999; Wendel, Narra, Hannula, Kauppinen & Malmivuo, 2008). Considering their pros and cons, CT more accurately images the skull due to its sensitivity to hard tissue via radiation, whereas MRI better images soft tissues such as the skin, cortex, and the gray matter-white matter boundary and is safe. The differences between the three-layer CT- and MRI-based models in (Huiskamp et al., 1999) illustrate significant differences at the base of the skull.

Unfortunately, diagnostic equipment that is available to adults is not optimal for children in terms of safe radiation limits. Such imaging modalities include CT, PET, and SPECT, which use ionizing radiation or radioactive tracers. Due to the nature of these technologies, children will only obtain such screening in extreme cases Yusof (2007). Magnetoencephalograpy (MEG) is safe, but it is often limited by the availability of smaller helmets, which locate the gradiometers closer to the scalp surface. EEG is also safe and readily adaptable to various head sizes due to the elastic nature of most EEG caps. Therefore, analyses that require

**5.3 The future of adaptable head models**

**6. Radial vector representation**

this method (Darvas et al., 2006; van 't Ent et al., 2001).

matrix (RAM) can be found in Wendel et al. (2012).

**7. Application of the radial vector representation**

modulation of the power function

Future studies that will advance the field of source imaging will save time and money. They will optimize the deformation, i.e., adaptability, of head models by minimizing the need for expensive MRIs and CTs, and eliminating the segmentation time. As scalp and skull tissue atlases are compiled and analyzed across age, gender, and ethnicity, the understanding of how to apply changes to a template will improve a model to match the non-imaged patient (Wendel, Osadebey & Malmivuo, 2008; 2009). Ultimately, incorporating the exact electrode locations to guide the deformation according to the patient's scalp surface would improve

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 233

Borrowing from the field of cranial anthropology, we mathematically transform a universal head model to reflect the size of an average female of other ethnic groups. The basis for the universal head model is the Visible Human Woman (VHW) from the Visible Human Project (National Institutes of Health (NIH), 1995). Our goal is to make deformable generic head models readily available for individuals who have not been medically imaged. The radial vector technique was briefly described in Wendel, Osadebey & Malmivuo (2008; 2009). The full mathematical description of the radial vector technique manipulating the radial angular

We started with a segmented head of the VHW measuring 640 by 530 by 670 pixels per dimension, having a 0.33 mm resolution per each axis unit. Ultimately, we constructed a four tissue model extending from the vertex down to the nasion. We constrained our slice-selection criteria for each tissue beginning with the apical slice after the noise removal from the first few slices of the radial- angular distances, i.e. the length measured from the tissue centroid to the tissue boundary for each slice. According to image analysis, we optimized our geometry based on the variation of the major and minor radial-angular axes of the transverse slice sections. The radial vector technique uses the cylindrical coordinate system, which is origin-centered through each tissue centroid. The RAM is a matrix of radial angular geometric descriptors forming atlases of any tissue segmented within the human body. This technique

A few cultural groups were presented in our previous study (Wendel, Osadebey & Malmivuo, 2009). In this chapter we present the full range of racial groups studied by Farkas et al. (2005). In this section we provide example mathematical functions to manipulate the RAM to generate several ethnic subgroups. We calculate the deformed geometry of a realistically shaped female head model based on the Visible Human Project woman dataset (Fig. 1). We used the cylindrical coordinate system to parametrically deform the template according to the

where *b* is the exponent of 0.01 used to deform the parietal lobe and *a* and *c* are derived from the coordinates of the template. We used the elliptical curve to reshape the frontal and

*f*(*x*) = *ax<sup>b</sup>* + *c*, (1)

requires imaged and segmented image sets usually based upon a patient's MRI.

computational modeling require generic models to better represent subpopulations that the patient shares geometrical congruency.

#### **5. Generic models**

Computationally-tractable head models that represent various populations and subpopulations demand that we examine the anatomy of the neurocranium, basicranium, and splanchnocranium i.e. the cranial vault, cranial base, and the face (Venes, 2005) as well as how head models are typically constructed. Generic models comprise a wide range of models attempting to encompass a range of ages, genders, and ethnic groups. From the models that exist in literature, two classes of generic models exist – simple and complex. For the purpose of this discussion, the complex models are additionally referred to as adaptable. A few three-dimensional (3-D) atlases of large data sets provide the data to form the models (Yusof, 2007).

#### **5.1 Smoothed generic models**

Simple generic models simulate down-sampled and smoothed tissue boundaries (Kybic et al., 2006; Wendel, Osadebey & Malmivuo, 2008; 2009). These models represent larger groups of people through their approximated shapes and sizes. Their sources are originally derived from the specific realistic images, and subsequently they are geometrically adapted to correspond with wider groups of gender, race, ethnicity, and age. These models are best suited for evaluating and analyzing how different parameters affect the sensitivity distributions applicable to EEG, bioimpedance, and transcutaneous electric neural stimulation (TENS).

Whether researchers build spherically or realistically shaped models, it is important to obtain measurement data representative of a population when making observations about that particular population. Clearly, the best model for a particular patient matches his image data exactly; however, it is not always possible or feasible to have an exact model that fits every patient, so an appropriate generic model is warranted (Darvas et al., 2006; Wendel, Osadebey & Malmivuo, 2009). Therefore, it is of utmost importance to obtain data representive of the population that a patient can be represented by in order to make quick utility of the likely closest-fitting, realistic model.

#### **5.2 Complex generic models**

The current and near future of time-efficient and cost-effective EEG source localization models lies in the progression of deformable head geometries (Wendel, Osadebey & Malmivuo, 2009). Anthropometric data currently exists detailing deformations in craniometric landmarks (Department of Defense, 1997; Donelson & Gordon, 1991; Farkas et al., 2005; Howells, 1973); however, a database of landmark sizes coupled with age (Wendel & Malmivuo, 2006; Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), gender (Wendel, Osadebey & Malmivuo, 2009; Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), ethnic origin (Wendel, Osadebey & Malmivuo, 2009), and head shape (Wendel, Osadebey & Malmivuo, 2009) would improve the accuracy beyond the overly used fixed-geometry of highly complex models such as from the Visible Human Project (Ackerman, 1991; National Institutes of Health (NIH), 1995).

#### **5.3 The future of adaptable head models**

4 Will-be-set-by-IN-TECH

computational modeling require generic models to better represent subpopulations that the

Computationally-tractable head models that represent various populations and subpopulations demand that we examine the anatomy of the neurocranium, basicranium, and splanchnocranium i.e. the cranial vault, cranial base, and the face (Venes, 2005) as well as how head models are typically constructed. Generic models comprise a wide range of models attempting to encompass a range of ages, genders, and ethnic groups. From the models that exist in literature, two classes of generic models exist – simple and complex. For the purpose of this discussion, the complex models are additionally referred to as adaptable. A few three-dimensional (3-D) atlases of large data sets provide the data to form the models

Simple generic models simulate down-sampled and smoothed tissue boundaries (Kybic et al., 2006; Wendel, Osadebey & Malmivuo, 2008; 2009). These models represent larger groups of people through their approximated shapes and sizes. Their sources are originally derived from the specific realistic images, and subsequently they are geometrically adapted to correspond with wider groups of gender, race, ethnicity, and age. These models are best suited for evaluating and analyzing how different parameters affect the sensitivity distributions applicable to EEG, bioimpedance, and transcutaneous electric neural stimulation (TENS).

Whether researchers build spherically or realistically shaped models, it is important to obtain measurement data representative of a population when making observations about that particular population. Clearly, the best model for a particular patient matches his image data exactly; however, it is not always possible or feasible to have an exact model that fits every patient, so an appropriate generic model is warranted (Darvas et al., 2006; Wendel, Osadebey & Malmivuo, 2009). Therefore, it is of utmost importance to obtain data representive of the population that a patient can be represented by in order to make quick utility of the likely

The current and near future of time-efficient and cost-effective EEG source localization models lies in the progression of deformable head geometries (Wendel, Osadebey & Malmivuo, 2009). Anthropometric data currently exists detailing deformations in craniometric landmarks (Department of Defense, 1997; Donelson & Gordon, 1991; Farkas et al., 2005; Howells, 1973); however, a database of landmark sizes coupled with age (Wendel & Malmivuo, 2006; Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), gender (Wendel, Osadebey & Malmivuo, 2009; Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), ethnic origin (Wendel, Osadebey & Malmivuo, 2009), and head shape (Wendel, Osadebey & Malmivuo, 2009) would improve the accuracy beyond the overly used fixed-geometry of highly complex models such as from the Visible Human Project (Ackerman, 1991; National Institutes of Health (NIH),

patient shares geometrical congruency.

**5. Generic models**

(Yusof, 2007).

**5.1 Smoothed generic models**

closest-fitting, realistic model.

**5.2 Complex generic models**

1995).

Future studies that will advance the field of source imaging will save time and money. They will optimize the deformation, i.e., adaptability, of head models by minimizing the need for expensive MRIs and CTs, and eliminating the segmentation time. As scalp and skull tissue atlases are compiled and analyzed across age, gender, and ethnicity, the understanding of how to apply changes to a template will improve a model to match the non-imaged patient (Wendel, Osadebey & Malmivuo, 2008; 2009). Ultimately, incorporating the exact electrode locations to guide the deformation according to the patient's scalp surface would improve this method (Darvas et al., 2006; van 't Ent et al., 2001).

#### **6. Radial vector representation**

Borrowing from the field of cranial anthropology, we mathematically transform a universal head model to reflect the size of an average female of other ethnic groups. The basis for the universal head model is the Visible Human Woman (VHW) from the Visible Human Project (National Institutes of Health (NIH), 1995). Our goal is to make deformable generic head models readily available for individuals who have not been medically imaged. The radial vector technique was briefly described in Wendel, Osadebey & Malmivuo (2008; 2009). The full mathematical description of the radial vector technique manipulating the radial angular matrix (RAM) can be found in Wendel et al. (2012).

We started with a segmented head of the VHW measuring 640 by 530 by 670 pixels per dimension, having a 0.33 mm resolution per each axis unit. Ultimately, we constructed a four tissue model extending from the vertex down to the nasion. We constrained our slice-selection criteria for each tissue beginning with the apical slice after the noise removal from the first few slices of the radial- angular distances, i.e. the length measured from the tissue centroid to the tissue boundary for each slice. According to image analysis, we optimized our geometry based on the variation of the major and minor radial-angular axes of the transverse slice sections. The radial vector technique uses the cylindrical coordinate system, which is origin-centered through each tissue centroid. The RAM is a matrix of radial angular geometric descriptors forming atlases of any tissue segmented within the human body. This technique requires imaged and segmented image sets usually based upon a patient's MRI.

#### **7. Application of the radial vector representation**

A few cultural groups were presented in our previous study (Wendel, Osadebey & Malmivuo, 2009). In this chapter we present the full range of racial groups studied by Farkas et al. (2005). In this section we provide example mathematical functions to manipulate the RAM to generate several ethnic subgroups. We calculate the deformed geometry of a realistically shaped female head model based on the Visible Human Project woman dataset (Fig. 1). We used the cylindrical coordinate system to parametrically deform the template according to the modulation of the power function

$$f(\mathbf{x}) = a\mathbf{x}^b + c,\tag{1}$$

where *b* is the exponent of 0.01 used to deform the parietal lobe and *a* and *c* are derived from the coordinates of the template. We used the elliptical curve to reshape the frontal and

Fig. 1. Generic template of the adult female of Caucasian American origin.

occipital lobes evaluating

$$\mathbf{x} = h + a\cos(t) - b\sin(t)\sin(\phi)\tag{2}$$

(a) African American (b) Caucasian American (c) Azerbaijan

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 235

(d) Bulgarian (e) Chinese (f) Croatian

(g) Czech (h) German (i) Greek

(j) Hungarian (k) Indian (l) Italian

(m) Japanese (n) Vietnamese (o) Zulu

Fig. 2. Generating Generic Ethnic Head Models: (a-o) adult female heads of average size per ethnic group. All heads are scaled accordingly and modified with an exponential function of

0.01.

$$y = k + b\sin(t) + a\cos(t)\sin(\phi). \tag{3}$$

We set the major-to-minor axis ratio to 0.3 and the orientation to 25◦.

#### **7.1 Results**

We alter pre-existing individual realistically-shaped head models by applying modulation of the power and elliptical functions (Fig. 2 & 3). We simply scale the template according to anthropometric statistics reported by Farkas et al. (2005) that belongs to each ethnic subpopulation to generate a new model. While deriving multiple generic head models, we use stochastic factors to generate a set of anatomical possibilities and constraints to prevent subsequent models with nonhuman and atypical human shapes and sizes. When applying too large exponents or major-to-minor axis ratios we yielded cone-head shaped models, which do not represent normal humans.

#### **7.2 Discussion**

In order to improve upon the state of current models, we must refine the basic geometric models in accordance with particular subpopulations. However, simply analyzing the diameters of the cranium is an older technique used to study cranial evolution. Contrastingly, the current analysis of spatial relationships between different anatomical structures can be applied to inter- and intra-ethnic comparisons (Bruner, 2007). We can alter pre-existing individual realistically-shaped head models by applying translation, rotation, scaling, warping, or applying more advanced metrics such as elliptical and power functions (Figs. 2 and 3). For instance we could simply scale one individual that belongs to the same subpopulation to generate a congruent model to represent another size of perhaps a different age. While deriving multiple generic head models, we can use stochastic factors to generate a set of anatomical possibilities and constraints to prevent subsequent models with nonhuman and atypical human shapes and sizes. A more encompassing approach would make use of a multivariate analysis of 2D and 3D anatomical features across numerous models (Bruner, 2007). Furthermore, these analyses and constraints can be applied not only to wide-ranging generic head models but additionally to various ethnic groups to create subpopulation-specific generic models.

6 Will-be-set-by-IN-TECH

We alter pre-existing individual realistically-shaped head models by applying modulation of the power and elliptical functions (Fig. 2 & 3). We simply scale the template according to anthropometric statistics reported by Farkas et al. (2005) that belongs to each ethnic subpopulation to generate a new model. While deriving multiple generic head models, we use stochastic factors to generate a set of anatomical possibilities and constraints to prevent subsequent models with nonhuman and atypical human shapes and sizes. When applying too large exponents or major-to-minor axis ratios we yielded cone-head shaped models, which do

In order to improve upon the state of current models, we must refine the basic geometric models in accordance with particular subpopulations. However, simply analyzing the diameters of the cranium is an older technique used to study cranial evolution. Contrastingly, the current analysis of spatial relationships between different anatomical structures can be applied to inter- and intra-ethnic comparisons (Bruner, 2007). We can alter pre-existing individual realistically-shaped head models by applying translation, rotation, scaling, warping, or applying more advanced metrics such as elliptical and power functions (Figs. 2 and 3). For instance we could simply scale one individual that belongs to the same subpopulation to generate a congruent model to represent another size of perhaps a different age. While deriving multiple generic head models, we can use stochastic factors to generate a set of anatomical possibilities and constraints to prevent subsequent models with nonhuman and atypical human shapes and sizes. A more encompassing approach would make use of a multivariate analysis of 2D and 3D anatomical features across numerous models (Bruner, 2007). Furthermore, these analyses and constraints can be applied not only to wide-ranging generic head models but additionally to various ethnic groups to create

*x* = *h* + *a*cos(*t*) − *b*sin(*t*)sin(*φ*) (2) *y* = *k* + *b*sin(*t*) + *a*cos(*t*)sin(*φ*). (3)

Fig. 1. Generic template of the adult female of Caucasian American origin.

We set the major-to-minor axis ratio to 0.3 and the orientation to 25◦.

occipital lobes evaluating

not represent normal humans.

subpopulation-specific generic models.

**7.1 Results**

**7.2 Discussion**

Fig. 2. Generating Generic Ethnic Head Models: (a-o) adult female heads of average size per ethnic group. All heads are scaled accordingly and modified with an exponential function of 0.01.

We can further look to cranial morphology to enhance our models. Bruner (2007) investigated the evolution of the cranium through the scope of allometry, indicating that the size and shape of the skull changes due to adaptations as well as stochastic factors. They attributed the increase in volumetric cranial capacity as one of the primary factors affecting the cranial shape. Additionally, the neocranium, face, and base of the skull change in shape and size as a result of the growth of the internal organs, primarily the brain, thus leading us to the connection between modern man, the *Homo sapiens*, and his three prehistoric counterparts

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 237

Many anthropologists no longer accept that modern man has evolved from one sole ancestor but has independently evolved in parallel through at least 3 differently evolved human species: *H. sapiens* in Africa, *H. neanderthalensis* in Europe, and *H. erectus* in Asia Bruner (2007); Manzi (2004); Rightmire (1998; 2001); Stringer (2002). It is clearly evident that different ethnic groups today have different shapes both in the cranial features as well as the cranial case. We can plausibly relate the cranial capacity of various ethnic groups to their prehistoric differences Bruner (2007). In 1870 Huxley (1870) mildly focused on cranial shape. By 1962 Coon (1962) described five racial types (i.e. skull shapes) based upon craniofacial features: *Caucasoids* from Europe, West Asia, and parts of India; *Capoids* from South Africa; *Congoids* from sub-sahara Africa; *Australoids* from Australia, New Guinea, and Melanesia; *Mongoloids* from East Asia and artic North America. Capoids and Congoids are the two main branches of

Today forensic anthropometry and reconstructive surgery utilize and apply racial types to obtain appropriate craniofacial metrics. Depending on the specific requirements, only three racial types are considered instead of five - Caucasoids, Mongloids, and Negroids. We concur that using a normalized representative of each of these three groups as the basis for mathematical manipulation will allow us to more plausibly derive the different head shapes across different ethnic groups belonging to each class with localized deformations such as in the frontal, temporal, or occipital lobes. Mathematically it is easier to make these manipulations while staying within one racial type due to the complex relation of multiple craniofacial metrics. If we consider the midsagittal profile, most Caucasoids have a rounded

We should consider the effects of shape versus size changes. Whether we reference our current universal base model or these three representative racial base models, mathematical congruency associated with growth will have the same effect Bruner (2007). Figs. 2 and 3 correctly scale each ethnic model in terms of head breadth, length, and depth per international anthropometric surveys Farkas et al. (2005); Howells (1973). Contrastingly, our exponential and elliptical transformation of our universal caucasian model across racial types does not fully exhibit the cranial or facial metrics of the new (target) ethnic groups of the target racial type. In the instance of the cross racial transformation the new model fails to assume the correct shape of the midsagittal profile of its racial type. In order to accomplish this, we need to further employ a combination of multiple deformations considered together and to increase our statistical survey according to Farkas et al. (2005) or we need to define a few

profile, Mongoloids have an arched profile, and Negroids have a flat profile.

generic templates to truly capture the behavior of the skull.

originating from *Homo ergaster*.

the single African race known as negroids.

Fig. 3. Generating Generic Ethnic Head Models: (a-h) adult female heads of average size per ethnic group. All heads are scaled accordingly and modified with an elliptical curve having a ratio of the major axis length to the minor axis length of 0.3 and orientation of 25 degrees.

When we want to evaluate a method or an analysis, it is critical that we evaluate the appropriateness of the geometry of the model that we are claiming as a basis of a set of results. We believe that when authors state certain claims regarding a certain subpopulation, they should validate that their model corresponds within statistical significance of the experimental subpopulation possibly within the context of race, ethnicity, gender, and age.

Archeological studies analyzing the cranial structures of prehistoric man use covariation of multiple traits to investigate the evolutionary changes of man via computational geometric analyses supported by multivariate statistics. Stochastic factors generate a set of anatomical possibilities and constraints in the determination of prehistoric evolution, which can be applied to the shape and size distinctions of various subpopulations according to ethnicity and gender. Currently, the key areas of development that we can adopt are morphological modularity, anatomical integration, and heterochrony.

8 Will-be-set-by-IN-TECH

(a) African American (b) Caucasian American (c) German

(d) Indian (e) Italian (f) Japanese

(g) Vietnamese (h) Zulu

Fig. 3. Generating Generic Ethnic Head Models: (a-h) adult female heads of average size per ethnic group. All heads are scaled accordingly and modified with an elliptical curve having a ratio of the major axis length to the minor axis length of 0.3 and orientation of 25 degrees.

When we want to evaluate a method or an analysis, it is critical that we evaluate the appropriateness of the geometry of the model that we are claiming as a basis of a set of results. We believe that when authors state certain claims regarding a certain subpopulation, they should validate that their model corresponds within statistical significance of the experimental

Archeological studies analyzing the cranial structures of prehistoric man use covariation of multiple traits to investigate the evolutionary changes of man via computational geometric analyses supported by multivariate statistics. Stochastic factors generate a set of anatomical possibilities and constraints in the determination of prehistoric evolution, which can be applied to the shape and size distinctions of various subpopulations according to ethnicity and gender. Currently, the key areas of development that we can adopt are morphological

subpopulation possibly within the context of race, ethnicity, gender, and age.

modularity, anatomical integration, and heterochrony.

We can further look to cranial morphology to enhance our models. Bruner (2007) investigated the evolution of the cranium through the scope of allometry, indicating that the size and shape of the skull changes due to adaptations as well as stochastic factors. They attributed the increase in volumetric cranial capacity as one of the primary factors affecting the cranial shape. Additionally, the neocranium, face, and base of the skull change in shape and size as a result of the growth of the internal organs, primarily the brain, thus leading us to the connection between modern man, the *Homo sapiens*, and his three prehistoric counterparts originating from *Homo ergaster*.

Many anthropologists no longer accept that modern man has evolved from one sole ancestor but has independently evolved in parallel through at least 3 differently evolved human species: *H. sapiens* in Africa, *H. neanderthalensis* in Europe, and *H. erectus* in Asia Bruner (2007); Manzi (2004); Rightmire (1998; 2001); Stringer (2002). It is clearly evident that different ethnic groups today have different shapes both in the cranial features as well as the cranial case. We can plausibly relate the cranial capacity of various ethnic groups to their prehistoric differences Bruner (2007). In 1870 Huxley (1870) mildly focused on cranial shape. By 1962 Coon (1962) described five racial types (i.e. skull shapes) based upon craniofacial features: *Caucasoids* from Europe, West Asia, and parts of India; *Capoids* from South Africa; *Congoids* from sub-sahara Africa; *Australoids* from Australia, New Guinea, and Melanesia; *Mongoloids* from East Asia and artic North America. Capoids and Congoids are the two main branches of the single African race known as negroids.

Today forensic anthropometry and reconstructive surgery utilize and apply racial types to obtain appropriate craniofacial metrics. Depending on the specific requirements, only three racial types are considered instead of five - Caucasoids, Mongloids, and Negroids. We concur that using a normalized representative of each of these three groups as the basis for mathematical manipulation will allow us to more plausibly derive the different head shapes across different ethnic groups belonging to each class with localized deformations such as in the frontal, temporal, or occipital lobes. Mathematically it is easier to make these manipulations while staying within one racial type due to the complex relation of multiple craniofacial metrics. If we consider the midsagittal profile, most Caucasoids have a rounded profile, Mongoloids have an arched profile, and Negroids have a flat profile.

We should consider the effects of shape versus size changes. Whether we reference our current universal base model or these three representative racial base models, mathematical congruency associated with growth will have the same effect Bruner (2007). Figs. 2 and 3 correctly scale each ethnic model in terms of head breadth, length, and depth per international anthropometric surveys Farkas et al. (2005); Howells (1973). Contrastingly, our exponential and elliptical transformation of our universal caucasian model across racial types does not fully exhibit the cranial or facial metrics of the new (target) ethnic groups of the target racial type. In the instance of the cross racial transformation the new model fails to assume the correct shape of the midsagittal profile of its racial type. In order to accomplish this, we need to further employ a combination of multiple deformations considered together and to increase our statistical survey according to Farkas et al. (2005) or we need to define a few generic templates to truly capture the behavior of the skull.

Coon, C. S. (1962). *The Origin of Races*, Alfred A. Knopf, New York.

models, *IEEE Trans Biomed Eng* 43(3): 299–303.

source analysis, *Human Brain Mapping* 27: 129–143.

*Eng* 110(12): 2176–2188.

*Biomed Eng* 42(1): 68–71.

16(4): 615–646.

*Topogr* 4(2): 125–131.

*Rehabilitation* 4(46).

hatsukhtml/bible/hatsize.htm.

hatsukhtml/bible/hatsize.htm.

Ethnology, Cambridge, Massachusetts.

pp. 262–283.

*IEEE Trans Biomed Eng* 40(1): 42–48.

Design Guidelines, MIL-HDBK-759C.

Crouzeix, A., Yvert, B., Bertrand, O. & Pernier, J. (1999). An evaluation of dipole

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 239

Cuffin, B. (1993). Effects of local variations in skull and scalp thickness on EEG's and MEG's,

Cuffin, B. (1995). A method for localizing EEG sources in realistic head models, *IEEE Trans*

Cuffin, B. (1996). EEG localization accuracy improvements using realistically shaped head

Darvas, F., Ermer, J., Mosher, J. & Leahy, R. (2006). Generic head models for atlas-based EEG

Department of Defense (1997). Department of Defense Handbook: Human Engineering

Donelson, S. & Gordon, C. (1991). 1988 Anthropometric Survey of U.S. Army Personnel:

Ferree, T., Eriksen, K. & Tucker, D. (2000). Regional head tissue conductivity estimation for

Gevins, A., Le, J., Brickett, P., Reutter, B. & Desmond, J. (1991). Seeing through the skull:

Gordon, R., Arola, T., Wendel, K., Ryynanen, O. & Hyttinen, J. (2006). Accuracy of numerical

Hallez, H., Vanrumste, B., Grech, R., Muscat, J., De Clercq, W., Vergult, A., D'Asseler,

Hämäläinen, M. & Sarvas, J. (1989). Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data, *IEEE Trans Biomed Eng* 36(2): 165–171. HatsUK (2005). The hat bible: Head and hat sizing, http://www.hatsuk.com/hatsuk/

HatsUK (2012). The hat bible: Head and hat sizing, http://www.hatsuk.com/hatsuk/

Haueisen, J., Ramon, C., Eiselt, M., Brauer, H. & Nowak, H. (1997). Influence of tissue

Howells, W. (1973). *Cranial Variation in Man: A Study by Multivariate Analysis of Patterns of*

element model of the head, *IEEE Trans Biomed Eng* 44(8): 727–735.

resistivities on neuromagnetic fields and electric potentials studied with a finite

*Difference Among Recent Human Populations*, Peabody Museum of Archaeology and

Research, Development, and Engineering Center, Natick, MA, U.S.A. Farkas, L., Katic, M. & Forrest, C. (2005). International anthropometric study of

improved EEG analysis, *IEEE Trans Biomed Eng* 47(12): 1584–1592.

Pilot Summary Statistics, *Technical Report TR-91/040, pp. 184-185*, U.S. Army Natick

facial morphology in various ethnic groups/races, *Journal of Craniofacial Surgery*

advanced EEGs use MRIs to accurately measure cortical activity from the scalp, *Brain*

methods by calculating static and quasistatic electric fields, *in* M. Min (ed.), *Proc Estonian Acad Sci Eng*, Vol. 12, Estonian Academy Publishers, Tallinn, Estonia,

Y., Camilleri, K., Fabri, S., Van Huffel, S. & Lemahieu, I. (2007). Review on solving the forward problem in EEG source analysis, *Journal of NeuroEngineering and*

reconstruction accuracy with spherical and realistic head models, *IEEE Trans Biomed*

#### **8. Conclusion**

The current and near future of an exposition on EEG measurement sensitivity distributions will benefit many clinical neurophysiologists such as anesthesiologists, neurologists, and cognitive neuroscientists. These benefits will come from the adaptation of highly detailed generic volume conductor models assessing different electrode types and locations (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010). Anthropometric data currently exists detailing deformations in craniometric landmarks; however, a database of landmark sizes coupled with age (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), gender (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), ethnic origin (Wendel, Osadebey & Malmivuo, 2009), and head shape (Wendel, Osadebey & Malmivuo, 2009) would improve the accuracy of the overly used fixed-geometry in highly complex models.

We found that mathematically deformed generic models can represent various ethnic groups. We applied the power function and elliptical function to more accurately reflect the profiles associate with each ethnic group. We can partially mathematically reflect the new shape of the midsagittal profiles of the target racial type. In our goal of EEG modeling, we aim to primarily fit the cranial case to the patient although the facial features may represent another individual. According to the field of anthropometry, we found grounds for requiring three base models destined for mathematical manipulation – one of each racial type: *Caucasoid, Mongloid*, and *Negroid* or the need to acquire more statistically databased medically-imaged data according to ethnicity.

#### **9. Acknowledgements**

The authors would like to thank the Academy of Finland (project number 123159: 2008 – 2011), the Ragnar Granit Foundation, the International Graduate School on Biomedical Engineering and Medical Physics (iBioMep), the Alfred Kordelin Foundation, and the Department of Biomedical Engineering, Tampere University of Technology for funding this work. Furthermore, we would like to express our gratitude to Prof. Jaakko Malmivuo, who guided us in the field of EEG.

#### **10. References**

Ackerman, M. (1991). The visible human project, *J. Biocommun.* 18(14).


10 Will-be-set-by-IN-TECH

The current and near future of an exposition on EEG measurement sensitivity distributions will benefit many clinical neurophysiologists such as anesthesiologists, neurologists, and cognitive neuroscientists. These benefits will come from the adaptation of highly detailed generic volume conductor models assessing different electrode types and locations (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010). Anthropometric data currently exists detailing deformations in craniometric landmarks; however, a database of landmark sizes coupled with age (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), gender (Wendel, Väisänen, Seemann, Hyttinen & Malmivuo, 2010), ethnic origin (Wendel, Osadebey & Malmivuo, 2009), and head shape (Wendel, Osadebey & Malmivuo, 2009) would improve

We found that mathematically deformed generic models can represent various ethnic groups. We applied the power function and elliptical function to more accurately reflect the profiles associate with each ethnic group. We can partially mathematically reflect the new shape of the midsagittal profiles of the target racial type. In our goal of EEG modeling, we aim to primarily fit the cranial case to the patient although the facial features may represent another individual. According to the field of anthropometry, we found grounds for requiring three base models destined for mathematical manipulation – one of each racial type: *Caucasoid, Mongloid*, and *Negroid* or the need to acquire more statistically databased medically-imaged data according

The authors would like to thank the Academy of Finland (project number 123159: 2008 – 2011), the Ragnar Granit Foundation, the International Graduate School on Biomedical Engineering and Medical Physics (iBioMep), the Alfred Kordelin Foundation, and the Department of Biomedical Engineering, Tampere University of Technology for funding this work. Furthermore, we would like to express our gratitude to Prof. Jaakko Malmivuo, who

Adeloye, A., Kattan, K. & Silverman, F. (1975). Thickness of the normal skull in the American blacks and whites, *American Journal of Physical Anthropology* 43: 23–30. Babiloni, F., Babiloni, C., Carducci, F., Fattorini, L., Anello, C., Onorati, P. & Urbano, A.

BestWigOutlet (2005). How to find your head size, http://www.bestwigoutlet.com/

BestWigOutlet (2009). How to find your head size, http://www.bestwigoutlet.com/

Bruner, E. (2007). Cranial shape and size variation in human evolution: structural and

(1997). High resolution EEG: a new model-dependent spatial deblurring method using a realistically-shaped MR-constructed subject's head model, *Electroencph. Clin.*

the accuracy of the overly used fixed-geometry in highly complex models.

Ackerman, M. (1991). The visible human project, *J. Biocommun.* 18(14).

\_e/page/1031/How\_to\_find\_your\_Head\_Size.htm.

\_e/page/1031/How\_to\_find\_your\_Head\_Size.htm.

functional perspectives, *Childs Nerv Syst* 23: 1357–1365.

**8. Conclusion**

to ethnicity.

**9. Acknowledgements**

guided us in the field of EEG.

*Neurophysiol.* 102: 69–80.

**10. References**

Coon, C. S. (1962). *The Origin of Races*, Alfred A. Knopf, New York.


Ryynänen, O., Hyttinen, J. & Malmivuo, J. (2006). Effect of measurement noise and

Applying Craniofacial Metrics to Adapt 3D Generic Head Models 241

Stringer, C. (2002). Modern human origins: progress and prospects, *Philosophical Transactions*

Suesserman, M., Spelman, F. & Rubinstein, J. (1991). In vitro measurement and

TheHatSite (2005). Hat sizing and how to measure your head, http://www.thehatsite.

van 't Ent, D., de Munck, J. & Kaas, A. (2001). A fast method to derive realistic BEM models for E/MEG source reconstruction, *IEEE Trans Biomed Eng* 48(12): 1434–1443. Vanrumste, B., Van Hoey, G., Van de Walle, R., D'Havé, M., Lemahieu, I. & Boon, P. (2001).

Venes, D. (2005). *Taber's Cyclopedic Medical Dictionary*, 20th edn, F. A. Davis Company,

Wendel, K. & Malmivuo, J. (2006). Correlation between live and post mortem skull

Wendel, K. & Malmivuo, J. (2008). The effect of electrode size on cortical eeg sensitivity distributions, *14th Nordic-Baltic Conference on Biomedical Engineering*, IFMBE, Riga. Wendel, K., Narra, N., Hannula, M., Hyttinen, J. & Malmivuo, J. (2007). The Influence of Electrode Size on EEG Lead Field Sensitivity Distributions, *IJBEM* 9(2): 116–117. Wendel, K., Narra, N., Hannula, M., Kauppinen, P. & Malmivuo, J. (2008). The Influence

Wendel, K., Osadebey, M., Jayasundara, A. & Dastidar, P. (2012). Radial Vector Representation

Wendel, K., Osadebey, M. & Malmivuo, J. (2008). Coupling axis-length profiles with bezier

Wendel, K., Osadebey, M. & Malmivuo, J. (2009). Incorporating craniofacial anthropometry

*Proceedings*, Vol. 25, World Congress 2009, Munich, Germany, pp. 1706–1709. Wendel, K., Väisänen, J., Kybartaite, A., Hyttinen, J. & Malmivuo, J. (2010). The significance

Wendel, K., Väisänen, J., Seemann, G., Hyttinen, J. & Malmivuo, J. (2010). The influence of age

Wendel, K., Väisänen, O., Malmivuo, J., Gencer, N., Vanrumste, B., Durka, P., Magjarevi´c,

3D Anthropometry, *IEEE Trans Med Img* Submitted.

*Intelligence and Neuroscience* 2010(397272): 7 pages.

problem in EEG dipole source analysis, *Brain Topogr* 14(2): 83–92.

*of the Royal Society B: Biological Sciences* 357: 563–579.

53(9): 1851–1858.

38(5): 401–408.

Philadelphia.

com/measuring.html.

IEEE EMBS, pp. 4285–4288.

*Biomed Eng* 55(4): 1454–1456.

*engineering*, IFMBE, Riga.

55(3): 123–131.

electrode density on the spatial resolution of cortical potential distribution with different resistivity values for the skull, *IEEE Transactions on Biomedical Engineering*

characterization of current density profiles produced by nonrecesed, simple recessed, and radially varying recessed stimulating electrodes, *IEEE Trans Biomed Eng*

The validation of the finite difference method and reciprocity for solving the inverse

conductivity measurements, *28th Ann. Int. Conf. of the IEEE Eng Med and Biol Society*,

of CSF on EEG Sensitivity Distributions of Multilayered Head Models, *IEEE Trans*

of MRI Data: A Universal Geometric Descriptor for Human Anatomic Structures and

splines in finite element head models, *14th Nordic-Baltic Conference on Biomedical*

into realistically-shaped head models, *in* O. Dössel & W. Schlegel (eds), *IFMBE*

of relative conductivity on thin layers in EEG sensitivity distributions, *Biomed Eng*

and skull conductivity on surface and subdermal bipolar EEG leads, *Computational*

R., Supek, S., Pascu, M., Fontenelle, H. & Grave de Peralta Menendez, R. (2009).


URL: *http://www.nlm.nih.gov/research/visible/visible\_human.html*


12 Will-be-set-by-IN-TECH

Huiskamp, G., Vroeijenstijn, M., van Dijk, R., Wieneke, G. & van Huffelen, A. (1999). The

Huxley, T. (1870). On the geographical distribution of the chief modifications of mankind,

Kybic, J., Clerc, M., Faugeras, O., Keriven, R. & Papadopoulo, T. (2006). Generalized head

Lynnerup, N., Astrup, J. & Sejrsen, B. (2005). Thickness of the human cranial diploe in relation

Malmivuo, J. & Plonsey, R. (1995). *Bioelectromagnetism — Principles and Applications of Bioelectric*

Malmivuo, J. & Suihko, V. (2004). Effect of skull resistivity on the spatial resolution of EEG

Malmivuo, J., Suihko, V. & Eskola, H. (1997). Sensitivity distributions of EEG and MEG

Manzi, G. (2004). Human evolution at the matuyama-brunhes boundary, *Evolutionary*

Michel, C., Murray, M., Lantz, G., Gonzalez, S. & Grave de Peralta, R. (2004). EEG source

National Institutes of Health (NIH) (1995). Visible human project, U.S. National Library of

Nolte, G. & Curio, G. (1999). Perturbative analytical solutions of the electric forward problem

Ogoshi, Y., Hayashi, T., Fukui, Y. & Okada, E. (2003). Analysis of light propagation in adult

Ollikainen, J., Vauhkonen, M., Karjalainen, P. & Kaipio, J. (2000). Effects of electrode properties

Rightmire, G. (1998). Human evolution in the middle pleistocene: the role of *Homo*

Rightmire, G. (2001). Patterns of hominid evolution and dispersal in the middle pleistocene,

Roth, B., Balish, M., Gorbach, A. & Sato, S. (1993). How well does a three-sphere model predict

Rush, S. & Driscoll, D. (1968). Current distribution in the brain from surface electrodes,

Rush, S. & Driscoll, D. (1969). EEG electrode sensitivity — An application of reciprocity, *IEEE*

Ryynänen, O., Hyttinen, J., Laarne, P. & Malmivuo, J. (2004a). Effect of electrode density and

Ryynänen, O., Hyttinen, J., Laarne, P. & Malmivuo, J. (2004b). Effect of measurement noise on

head model by direct hybrid monte carlo-diffusion method, *IEEE EMBS Asian-Pacific*

on EEG measurements and a related inverse problem, *Med Eng & Phys* 22(8): 535–545.

positions of dipoles in a realistically shaped head?, *Electroencph. Clin. Neurophysiol.*

measurement noise on the spatial resolution of cortical potential distribution, *IEEE*

to age, sex and general body build, *Head & Face Med* 1(13).

*and Biomagnetic Fields*, Oxford University Press, New York.

URL: *http://www.nlm.nih.gov/research/visible/visible\_human.html*

for realistic volume conductors, *J App Phy* 86(5): 2800–2811.

*Conference on Biomedical Engineering*, IEEE EMBS, pp. 316–317.

*heidelbergensis*, *Evolutionary Anthropology* 6: 218–227.

the spatial resolution of EEG, *Biomed Tech* 48(2): 94–97.

*Quaternary International* 75: 77–84.

*Anesthesia Analgesia* 47: 717–723.

*Trans Biomed Eng* 16(1): 15–22.

*Trans Biomed Eng* 51(9): 1547–1554.

and MEG, *IEEE Trans Biomed Eng* 51(7): 1276–1280.

imaging, *Clin. Neurophysiol.* 115: 2195–2222.

measurements, *IEEE Trans Biomed Eng* 44(3): 196–208.

*Eng* 46(11): 1281–1287.

*Anthropology* 13: 11–24.

Medicine.

87: 175–184.

*Journal of the Ethnological Society of London* .

*Medicine and Biology* 51: 1333–1346.

need for correct realistic geometry in the inverse EEG problem, *IEEE Trans Biomed*

models for meg/eeg: boundary element method beyond nested volumes, *Physics in*


EEG/MEG source imaging: Methods, challenges, and open issues, *Computational Intelligence and Neuroscience* 2009(656092): 12 pages.

WigSalon (2005). Head sizes for wigs, http://www.wigsalon.com/prowig.html.

WigSalon (2012). Head sizes for wigs, http://www.wigsalon.com/prowig.html.


14 Will-be-set-by-IN-TECH

242 Polyphonic Anthropology – Theoretical and Empirical Cross-Cultural Fieldwork

Zhou, H. & van Oosterom, A. (1992). Computation of the potential distribution in a four-layer

WigSalon (2005). Head sizes for wigs, http://www.wigsalon.com/prowig.html. WigSalon (2012). Head sizes for wigs, http://www.wigsalon.com/prowig.html. Yusof, A. (2007). *Craniofacial Growth Changes in Malaysian Malay Children and Young Adults: A*

*Intelligence and Neuroscience* 2009(656092): 12 pages.

Australia.

*Engineering* 39(2): 154–158.

EEG/MEG source imaging: Methods, challenges, and open issues, *Computational*

*Cross-Sectional 3-Dimensional CT Study*, PhD thesis, University of Adelaide, Adelaide,

anisotropic concentric spherical volume conductor, *IEEE Transactions on Biomedical*

### *Edited by Massimo Canevacci*

This book connects anthropology and polyphony: a composition that multiplies the researcher's glance, the style of representation, the narrative presence of subjectivities. Polyphonic anthropology is presenting a complex of bio-physical and psycho-cultural case studies. Digital culture and communication has been transforming traditional way of life, styles of writing, forms of knowledge, the way of working and connecting. Ubiquities, identities, syncretisms are key-words if a researcher wish to interpret and transform a cultural contexts. It is urgent favoring trans-disciplinarity for students, scholars, researchers, professors; any reader of this polyphonic book has to cross philosophy, anatomy, psychology, psychoanalysis, sociology, architecture, archeology, biology. I believe in an anthropological mutation inside any discipline. And I hope this book may face such a challenge.

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Polyphonic Anthropology - Theoretical and Empirical Cross-Cultural Fieldwork

Polyphonic Anthropology

Theoretical and Empirical

Cross-Cultural Fieldwork