Human Brain Expansion during Evolution Is Independent of Fire Control and Cooking

Abstract

What makes humans unique? This question has fascinated scientists and philosophers for centuries and it is still a matter of intense debate. Nowadays, human brain expansion during evolution has been acknowledged to explain our empowered cognitive capabilities. The drivers for such accelerated expansion remain, however, largely unknown. In this sense, studies have suggested that the cooking of food could be a pre-requisite for the expansion of brain size in early hominins. However, this appealing hypothesis is only supported by a mathematical model suggesting that the increasing number of neurons in the brain would constrain body size among primates due to a limited amount of calories obtained from diets. Here, we show, by using a similar mathematical model, that a tradeoff between body mass and the number of brain neurons imposed by dietary constraints during hominin evolution is unlikely. Instead, the predictable number of neurons in the hominin brain varies much more in function of foraging efficiency than body mass. We also review archeological data to show that the expansion of the brain volume in the hominin lineage is described by a linear function independent of evidences of fire control, and therefore, thermal processing of food does not account for this phenomenon. Finally, we report experiments in mice showing that thermal processing of meat does not increase its caloric availability in mice. Altogether, our data indicate that cooking is neither sufficient nor necessary to explain hominin brain expansion.

Full text

ORIGINAL RESEARCH
published: 25 April 2016
doi: 10.3389/fnins.2016.00167
Frontiers in Neuroscience | www.frontiersin.org 1 A
pril 2016 | Volume 10 | Article 167
Edited by:
J. Michael Williams,
Drexel University, USA
Reviewed by:
Matt Joseph Rossano,
Southeastern Louisiana University,
USA
Rosemary Hopcroft,
University of North Carolina at
Charlotte, USA
*Correspondence:
Alianda M. Cornélio
alianda@neuro.ufrn.br;
Marcos R. Costa
mrcosta@neuro.ufrn.br
Specialty section:
This article was submitted to
Evolutionary Psychology and
Neuroscience,
a section of the journal
Frontiers in Neuroscience
Received: 20 January 2016
Accepted: 04 April 2016
Published: 25 April 2016
Citation:
Cornélio AM, de
Bittencourt-Navarrete RE, de
Bittencourt Brum R, Queiroz CM and
Costa MR (2016) Human Brain
Expansion during Evolution Is
Independent of Fire Control and
Cooking. Front. Neurosci. 10:167.
doi: 10.3389/fnins.2016.00167
Human Brain Expansion during
Evolution Is Independent of Fire
Control and Cooking
Alianda M. Cornélio
1, 2
*
, Ruben E. de Bittencourt-Navarrete
3
,
Ricardo de Bittencourt Brum
1
, Claudio M. Queiroz
1
and Marcos R. Costa
1
*
1
Brain Institute, Federal University of Rio Grande do Norte, Natal, Brazil,
2
Department of Morphology, Center of Biosciences,
Federal University of Rio Grande do Norte, Natal, Brazil,
3
Department of Physiology, Institute of Biological Sciences, Federal
University of Juiz de Fora, Juiz de Fora, Brazil
What makes humans unique? This question has fascinated scientists and philosophers
for centuries and it is still a matter of intense debate. Nowadays, human brain
expansion during evolution has been acknowledged to explain our empowered cognitive
capabilities. The drivers for such accelerated expansion remain, however, largely
unknown. In this sense, studies have suggested that the cooking of food could be a
pre-requisite for the expansion of brain size in early hominins. However, this appealing
hypothesis is only supported by a mathematical model suggesting that the increasing
number of neurons in the brain would constrain body size among primates due to
a limited amount of calories obtained from diets. Here, we show, by using a similar
mathematical model, that a tradeoff between body mass and the number of brain
neurons imposed by dietary constraints during hominin evolution is unlikely. Instead,
the predictable number of neurons in the hominin brain varies much more in function
of foraging efficiency than body mass. We also review archeological data to show that
the expansion of the brain volume in the hominin lineage is described by a linear function
independent of evidence of fire control, and therefore, thermal processing of food does
not account for this phenomenon. Finally, we report experiments in mice showing that
thermal processing of meat does not increase its caloric availability in mice. Altogether,
our data indicate that cooking is neither sufficient nor necessary to explain hominin brain
expansion.
Keywords: human evolution, brain size, fire control, thermal processing of food, cooking
INTRODUCTION
Human evolution is marked by a significant increase in the total brain size relative to body size,
referred to as encephalization. Although increased encephalization is a clear hallmark of human
cognitive and cultural evolution, there is little consensus on the causes of such phenomenon. In
part, this lack of agreement reflects the difficulty to test directly numerous hypotheses proposed to
explain the brain growth in the hominin lineage.
Studies on human brain evolution have been largely based upon two main lines of evidence:
(i) fossil records, termed paleoneurology; and (ii) indirect evidence coming from anatomical,
physiological, and behavioral comparison between humans and closely related extant primates,
such as chimpanzee. While the former allows inferences about the total brain volume of extinct

Cornélio et al. Cooking and Human Brain Evolution
hominins, comparisons between existing primates permit a more
detailed analysis on how gross and microscopic organization
of the brain correlates with different behaviors, thus allowing
some inferences about anatomic and functional aspects of the
brain. However, it is important to bear in mind that extant
living species, such as chimpanzee, gorilla, and macaque, are the
endpoints of their own evolutionary lines and not our ancestors
(Holloway, 1968). Therefore, the combination of direct and
indirect evidence is mandatory to develop a better understanding
of when and how the human brain evolved.
Based on such “direct” and “indirect” evidence, many different
theories have been proposed to explain the disproportionate
growth of the brain in the human lineage, considering the high
energetic cost of larger brains (Mink et al., 1981). The expensive-
tissue hypothesis, for example, explains brain evolution by
proposing a tradeoff between the size of the brain and that of the
digestive tract, which is smaller than expected for a primate of
our body size (Ai ello and Wheeler, 1995). However, an important
study, in which body mass was controlled for fat-free body mass,
failed to find negative correlations between the relative size of
the brain and the digestive tract (or any other expensive organ
such as heart, lungs, kidneys, spleen, or liver) for t h e 100 species
of mammals analyzed, including 23 primates (Navarrete et al.,
2011).
Recently, it has been proposed that energetic constraints
could impose a tradeoff between body and brain growth during
primates’ evolution (Fonseca-Azevedo and Herculano-Houzel,
2012). According to this hypothesis, limitations for calories
obtained during foraging hours would impose a selective pressure
on body vs. brain growth. In that case, primates with larger
body size would present proportionally smaller brain mass due
to dietetic restraints. Human ancestors, but not other primates,
are supposed to have bypassed such constraints by cooking. This
would increase the available calorie content in the food (
Carmody
et al., 2011; Fonseca-Azevedo and Herculano-Houzel, 2012).
In th is work, we revisit the c orrelations between brain size and
cooking by means of archeological and neuroanatomical data, as
well as new metabolic data on the energetic content of raw and
cooked meat. We show that large primate encephalization was
reached millions of years before the widespread control of fire,
a pre-requisite for cooking, and provide evidence indicating that
early hominins were likely to obtain enough calories from raw
meat to afford for the size of their brains.
MATERIALS AND METHODS
Mathematical Model
Kleiber’s law (
Kleiber, 1947) was used to determine body’s daily
energetic need (E
BD
) according to the equation:
E
BD
= Z × M
BD
0.75
(1)
where Z is a correction factor that varies among species and
according to physical activity and M
BD
is t h e body mass. To
maintain proper physiological functions and stable body mass
during no exercise or sedentary conditions, we have used
Harris
and Benedict (1918)
equation, in which:
E
BD
= BMR × 1.2 (2)
where BMR is the basal metabolic rate of the body. According to
this approach (
Harris and Benedict, 1918), BMR can be calculated
by using the following equation (for men):
BMR = 66 +
(
13.7 × w
)
+

5 × h

−
(
6.8 × a
)
(3)
where w is weight (in kilogram), h is height (in centimeter), and
a is age (in years). Combining Equations (1) and (2), one obtains:
BMR × 1.2 = Z × M
BD
0.75
(4)
Using Equations (3, 4), it is possible to calculate the Z factor for an
early male hominin (70 kg, 1.6 m and 30 years-old) under resting
conditions (Harris and Benedict, 1918; Kleiber, 1947):
BMR × 1.2 = Z × M
BD
0.75
[
66 +
(
13.7 × 70
)
+
(
5 × 160
)
−
(
6.8 × 30
)
]
× 1.2 = Z × 70
0.75
1621 × 1.2 = Z × 24.2
Z = 80.3
Previous work (
Fonseca-Azevedo and Herculano-Houzel, 2012)
has adopted Z = 70, likely underestimating daily energetic need
(see Dis c ussion). Here, we expect that early hominins would have
at least moderate physical activity (e.g., at least 60 min/day, 5
times per week) and, therefore, would have an energetic need 1.5 5
times the BMR (
Harris a nd Benedict, 1918). Updating Equation
(4) to:
BMR × 1.55 = Z × M
BD
0.75
(5)
leads to
[
66 +
(
13.7 × 70
)
+
(
5 × 160
)
−
(
6.8 × 30
)
]
× 1.55 = Z × 70
0.75
1621 × 1.55 = Z × 24.2
Z = 103
Unless otherwise stated, this Z factor value was used in all the
following calculations.
Brain volumes for different species were obtained from
previous publications (see Table 1) . To enable comparisons
between the present and pre v ious studies, the estimated number
of neurons per brain was the same used by Fonseca-Azevedo
and Herculano-Houzel (2012). Graphics and stati stical tests were
performed using Matlab program (version 7, R14, Mathworks) or
GraphPad Prism version 5.00 (San Diego California USA, www.
graphpad.com). The confidence interval was set to 95%.
Archeological Data
We classified the evidence of fire control (by hominins) in strong
(SE), weak (WE), very weak (VWE), and non-existent (NE)
according to
James (1989). Briefly, we classified archeological
findings into two main categories: (1) Suggestive of human
action: fire-hardened wood (FHW), burned bones (BB), burned
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Cornélio et al. Cooking and Human Brain Evolution
TABLE 1 | Brain volumes and body mass of hominid species throughout evolution.
Taxon Fossile evidence Time (MYA) Brain volume (cc) Body mass (Kg) References
G. gorilla (Afar, Ethiopia, 2007) 10,0–12,0 420–680 150 Suwa et al., 2007
Pan troglodytes (East of Great Rift Valley, Kenya, 2005) 4,0–5,0 320–480 50 McBrearty and Jablonski, 2005
Ardipithecus ramidus (Asduma, Ethiopia, 1994) 4,6–4,3 350 27 Semaw et al., 2005
Australopithecus anamensis (Kanapoi, Kenya, 1994) 4,2–3,9 50 Leakey et al., 1995
Aus. afarensis (Lucy) (Afar, Ethiopia, 1974) 3,7–3 375–550 37 Johanson and White, 1980
Aus. africanus (Taung, South Africa, 1924) 3–2,4 460 35 McHenry, 1992
Aus. Garhi (Awash, Ethiopia, 1996) 2–3,0 450 unknown Asfaw et al., 1999
Aus. sediba (Malapa, South Africa, 2008) 1,9–1,8 420–450 unknown Berger et al., 2010
Paranthropus aethiopicus (Omo River, Ethiopia, 1968) 2,6–2,2 400–490 37 Falk et al., 2005
Par. Boisei (Olduvai, Tanzania, 1959) 2,3–1,2 480–515 50 Leakey et al., 1961, 1964
Par. robustus (Kromdraai, South Africa, 1938) 2–1,3 400–450 36 Curnoe et al., 2001
Homo rudolfensis (Koobi Fora, Kenya, 1972) 2,4–1,8 520–750 45 Leakey and Wood, 1973
H. habilis (Olduvai, Tanzania, 1962) 2,4–1,4 510–650 35 Leakey, 1966; McHenry, 1992
H. ergaster (Koobi Fora, Kenya,1975) 1,9–1 800–880 60 Swisher et al., 1994
H. georgicus (Dmanisi, Georgia, 2002) 1,8 680–770 55 Vekua et al., 2002
H. erectus (Yuanmoun, China, 1965) 1,8–0,3 940–1200 60 Pu et al., 1977; Leigh, 1992
H. erectus erectus (Trinil, Java, Indonesia, 1892) 1,8–0,3 85 0–1200 unknown Dubois, 1894
H. lantianensis (Lantian, Shaanxi, China, 1964) 1–0,53 780–1120 unknown Woo, 1964, 1965
H. pekinensis (Zhoukoudian, Peking, China, 1927) 0,5–0,25 1075 unknown Shen et al., 2009
H. antecessor (Atapuerca, Burgos, Spain, 1994) 0,95–0,75 1100–1150 75 Bermudez de Castro et al., 1997
H. cepranensis (Ceprano, Lazio, Italy, 1994) 0,7–0,43 1200 unknown Manzi et al., 2001
H. rhodesiensis (Broken Hill, now Kabwe, Zambia, 1921) 0,63–0,16 1250–1320 unknown Murrill, 1975; Rightmire, 1983;
Conroy et al., 2000
H. heidelbergensis (Heidelberg, Germany, 1908) 0,65–0,2 1100–1370 80–100 Schoetensack, 1908; Arsuaga
et al., 1993
H. neanderthalensis (Dusseldorf, Germany, 1856) 0,45–0,028 1200–1500 70–90 King, 1864; Holloway, 1997;
Helmuth, 1998
H. sapiens (Omo River, Ethiopia, 1967) 0,195 1250–1400 70 Holloway, 1997; White et al.,
2003; McDougall et al., 2005
shells (BS), burned food (BF), fire-cracked rock (FR), burned
lithics (BL), and hearth (H); and (2) Potentially accidental:
charcoal (C), burned deposit (BD), baked clay (BC), ashes (A),
reddened area (RA). Next, we examined the association of these
findings with human bones (HB) and tools (T). Evidence of
human control of fire was classified as strong when at least one
archeological finding of fire was associated with human bones
or tools; weak evidence was classified when the association was
not clear; and very weak evidence for sites where only potentially
accidental findings of fire were present, with no association with
human bones or tools (Table 2).
Energetic Gain from Raw and Cooked Meat
To directly test whether thermal processing of meat could
increase the energetic gain we used the protocol described by
Carmody et al. (2011). Briefly, adult male Swiss mice weigh ing
31–51 g, were fed with raw or cooked beef eye round (B. Taurus).
Meat was acquired from a local supermarket (Nordestão, Natal,
RN) and kept in a refrigerator at 4
◦
C during all tests days. Meat
was cut in cubes (∼1.5 cm per side) and weighted in portions
(30.0 ± 0.5 g). Cooked meat samples were placed into Petri dishes
and roasted in preheated conve c tion oven at 220
◦
C for 15 min.
Raw meat samples were kept in the refrigerator for the same time
of roasting. Diets were kept at room temperature to equilibrate
before feeding started (Supplementary Figure 1).
Mice housed individually received water and the experiment a l
diet provided in Petri dishes, during all experiment period. Cages,
liners, diets, and water were changed daily. Mice were fed for
four consecutive days with either raw (RW) or cooked (CK)
meat diets. Both diets were offered at the same time each day
to all animals. Body weight was recorded daily. Residual food
from the previous 24 h was collected and weighed for analysis.
All experiments were carried out in accordance with Brazilian
and international laws for animal care and were approved by the
Institutional Animal Care and Use Committee (IACUC).
RESULTS
Foraging Efficiency Is Important to Sustain
Large Number of Neurons
Recent work suggests that the energetic cost of the brain is
proportional to its number of neurons. Hence, increasing the
number of neurons during primate evolution would impose
a metabolic constraint to the body and brain sizes (
Fonseca-
Azevedo and Herculano-Houzel, 2012). Mathematical models
assuming that the caloric intake per hour among hominins scales
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Cornélio et al. Cooking and Human Brain Evolution
TABLE 2 | Archeological evidences of fire control by hominids.
Archeological site Dat e (MYA) Country Kind of evidence Association Classification References
Yuanmou 1,7 China C BB? None VWE James, 1989
Koobi Fora 1,55 Kenya BL? None VWE James, 1989
Koobi Fora 1,4 Kenya RA BL? None VWE James, 1989
Chesowanja 1,4 Kenya BC None VWE James, 1989
Swartkrans 1,2 South Africa BB not clear WE Brain and Sillen, 1988
Wonderwerk Cave 1 South Africa A BB T not clear WE Berna et al., 2012
Gesher Benot Yaakov 0,79 Israel H T Clear SE Alperson-Afil et al., 2009
Zhoukoudian 0,5 China BD BL None VWE Weiner et al., 1998
Atapuerca 0,6 Spain H T HB Clear SE Arsuaga et al., 1993
Zhoukoudian 0,45 China H BB BF not clear WE Wu, 1999
Schöningen 0,4 Germany A C FHW BF clear SE Thieme, 1997
Qesem Cave 0,38 Israel H BB BF HB T clear SE Karkanas et al., 2007
Bajondillo 0,15 Spain H BF BB HB T clear SE Cortés-Sanchez et al., 2011
Bolomar 0,13 Spain H BF T HB clear SE Blasco, 2008
SE, strong evidence; WE, weak evidence; VWE, very weak evidence; NE, non-existent evidence; FHW, fire-hardened wood; BB, burned bones; BS, burned shells; BF, burned food; FR,
fire-cracked rock; BL, burned lithics; H, hearth; C, charcoal; BD, burned deposit; BC, baked clay; A, ashes; RA, reddened area; HB, human bones; T, tools.
as a function of the body mass (M
BD
) with an exponent equals
to 0.526 (M
BD
0.526
) support this conclusion (
Fonseca-Azevedo
and Herculano-Houzel, 2012). However, this function (M
BD
0.526
)
derives from estimates comprising th e daily h ours of foraging
and body masses of 10 non-human primates with a largely
vegetarian- or frugivorous-b ased diet (
Richards, 2002). Worth
noting, this model does not take into consideration any other
probable changes in the diet of early hominins, such as increased
consumption of animal protein and fat. Therefore, we set out
to re-evaluate whether metabolic limitations would impose a
tradeoff between body size and t he number of brain neurons in
human evolution, assuming that foraging efficiency does not vary
according to the body mass.
Firstly, we assumed that the d a ily energy intake (E
IN
) is
directly proportional to the number of foraging hours (H) and the
average amount of calories obtained per hour of foraging, which
represents the foraging efficiency (Q). Next, we calculated the
energetic need of the body (E
BD
) with moderate activity (spent
during foraging) per species using the Kleiber’s law (E
BD
= 103 ×
M
BD
0.75
, see Equation 1, Materials and Methods). In the steady
state, E
IN
= E
BD
or H × Q = 103 × M
BD
0.75
. To separate the
energetic costs of the brain and the body, we subtracted the brain
mass (M
BR
) from M
BD
in Equation (1) and included the energy
of t he brain (E
BR
) as a new variable:
H × Q = 103 × (M
BD
− M
BR
)
0.75
+ E
BR
(6)
Since M
BD
includes M
BR
, we have that
M
BD
− M
BR
= (1 − r) × M
BD
(7)
where r = M
BR
/M
BD
, i.e., the ratio between brain and body size.
Finally, assuming that the energetic cost of the brain is a linear
function of its number of neurons and that the energetic cost
of each neuron is 6 × 10
−9
kcal per day in different species
(
Herculano-Houzel, 2011) we c a n derive the equation:
H × Q = 103 × ((1 − r) × M
BD
)
0.75
+ (N × 6 × 10
−9
) (8)
where N is the total number of neurons.
Using Equation (8), we first simulated how t he number of
neurons varies as a function of body mass for five different
values of E
IN
(500–4500 kcal/day) and four values of the ratio (r)
M
BR
/M
BD
(Figure 1). Interestingly, t he ratio M
BR
/M
BD
did not
influence significantly the number of neurons in the brain (each
r’s function is barely discernible from each othe r). In contrast,
increasing the daily energy inta ke by 1000 kcal significantly
boosted the number of neurons afforded in a body, irrespective of
its mass. Thus, this simulation suggests t hat energy intake could
be a limiting factor for an allometric scaling of body size and
the number of neurons in the brain. Moreover, it also shows that
species obtaining a given amount of calories per day could vary
their number of brain neurons in the order of billions without
significant changes in their body mass. For instance, a gorilla
weighing 110 kg would need 3695 kcal/day t o sustain a brain with
33 billion neurons (Figure 1). By reducing its weight to 100 kg
(∼10% reduction), the same gorilla could likely sustain a brain
with 6 0 billion neurons (similar to the inferred number for Homo
erectus) while maintaining the same amount of energy intake
(red dot in the figure). These data suggest that the appealing
hypothesis of a tradeoff between body mass and the number of
brain neurons imposed by dietary constraints during primate
evolution is unlikely.
Next, we simulated the number of foraging hours (H) as a
function of body mass (M
BD
) to five values of N (10–130 billion
of neurons) and three values of foraging efficiency (Q) (Figure 2).
We observed that increasing foraging efficiency would have a
dramatic effect on the number of foraging hours necessary to
sustain a high number of neurons even in species with a great
body mass. For instance, a homo sapiens weighing 70 kg could
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Cornélio et al. Cooking and Human Brain Evolution
FIGURE 1 | Theoretical effects of foraging efficiency over the number
of brain neurons related to body weight. The graphic predicts the number
of neurons in different foraging efficiencies, 500 (dark blue), 1500 (green), 2500
(orange), 3500 (light blue), and 4500 (purple) kcal per day. Ratios of brain and
body mass vary from 0.5 to 2%. Species of primates are indicated in the
graphic (black circles). Observe that small variations in the body mass are
associated with dramatic increases in the number of neurons. A primate with a
foraging efficiency of 3500 kcal, such as the gorilla, could easily afford the
same number of neurons as a Homo erectus by simply reducing its weight in
about 10 kg (red circle).
easily maintain 10
11
neurons t hrough 5 h foraging with an
efficiency of 500 kcal/h (Figure 2B). Moreover, increased body
weight affects foraging hours more strongly than augmented
number of neurons, especially when foraging efficiency is low
(Figure 2A). For high foraging efficiencies (500 and 750 kcal),
subtle increases in the number of foraging hours could be
sufficient to sustain increases of one order of magnitude in the
number of neurons per brain, maintaining the same body weig h t
(Figures 2B,C). Thus, the present model suggests that brain
size evolution in the human lineage would heavily depend on
strategies to increase foraging efficiency, rather t han on a tradeoff
between brain and body size. In fact, we observed no correlation
between brain volumes and body masses for 16 species of
primates analyzed in this work (Supplementary Figure 2B).
Onset of Human Brain Size Expansion
Does Not Match Control of Fire and
Cooking
Which strategies early hominins may have developed to increase
their foraging efficiency? Recently, it has been suggested that
thermal processing of food could be the turning point in
human brain evolution once it would allow increased foraging
efficiency (i.e., increasing the energy content per amount of
food) without a significant increase in foraging time (
Carmody
et al., 2011; Fonseca-Azevedo a nd Herculano-Houzel, 2012
).
Obviously, thermal processing of food required the control of
fire by early hominins. However, human control of fire and its
association with cooking at the onset of human brain expansion
is highly controversial.
The earliest evidence of fire in archeological records dates
back approximately 1 million years ago (MYA). In 1988, Brain
and Sillen described the presence of burnt bones inside the
Swartkrans caves (South Africa). In spite of evidence of cut-
marked bones indicating butchery, those authors are cautious,
stating that fire was not necessarily used for cooking (
Brain
and Sillen, 1988). More recently Berna and collaborators found
burned bones and ashes from plants at the site of Wonderwerk
cave (Northern C a pe Province, South Africa). Yet, no clear
association with human activity was des cribed (Berna et al.,
2012). Similarly, archeological data in the localities of Yanmou
(China), Chesowanja and Koobi Fora (Kenya, Africa) 1.5
MYA do not support t he human origin of the fire remains
(James, 1989). Weiner et al. (1998) analyzed evidence of the
use of fire in sediments accumulated from about 500,000–
200,000 years ago (YA) at Zhoukoudian, China and concluded
that no inference drawn from the human origin of those
deposits is clear-cut. The complexity of fossil deposits commonly
leads to misinterpretations. The origin of such fires might be
attributed for instance to the fortuitous association between
hominins action and natural causes like lightning or flames from
volcanic eruptions. Furthermore, burning remains could have
been carried down into caves by streams of water or seismic
fractures.
Weiner et al. ( 1998) point out th e absence of ashes and
charcoal and also the lack of evidence of human action in those
sites.
A different scenario arises regarding the site of Gesher Benot
Ya’aqov in Israel (
Alperson-Afil et al., 2009). Hearths remains
kept in the same area through several generations of hominins
are estimated to be from 790,000 to 690,000 YA. In those sites, the
presence of burned nuts is suggestive of the use of fire by humans,
although it has also been associated with t he use of lithic tools.
Notwithstanding the clear presence of human-made fire, its goal
is yet unclear. Alternative applications may include illumination,
heating or even an approach to keep predators and insects away.
In favor of earlier human control over fire, it has been
suggested that no occupation of Europe by hominins would
be feasible without it. Nevertheless, Roebroeks and Villa (2011)
show that “surprisingly, evidence for use of fire in the Early and
early Middle Pleistocene of Europe is extremely weak. Or, more
exactly, it is nonexistent, until ∼300,000–400,000 YA.” According
to these authors, the oldest evidence of fire use in Europe would
be present at Beeches Pit (England) and S chöningen (Germany),
around 400,000 YA. Arsuaga et al. (1993) provide older data
in Sierra de Atapuerca (Spain), where H. heidelbergensis fossil
records dated 600,000 YA, are associated with hearths. More
recently Karkanas et al. (2007) have described consistent use of
fire in the cave of Qesem (Israel), between 382,000 and 200,000
YA, for several purposes, including cooking food. Thereafter, the
fire use by hominins is broadly documented throughout the Old
World (James, 1989). There are also interesting cases where fire
was used with aims unrelated to cooking, such as for making
stones more workable, observed for the first time in the Stillbay
culture (Cape Province, South Africa), 164 –72,0 00 YA (
Brown
et al., 2009
). Regarding the specific fire use for cooking purposes,
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Cornélio et al. Cooking and Human Brain Evolution
FIGURE 2 | Augmented foraging efficiency allows increases in body weight, saving daily hours of feeding, and maintaining a great number of neurons.
(A–C) Graphics show variations in foraging hours related to body mass for primates supporting 10 (dark blue), 40 (green), 70 (orange), 100 (light blue), or 130 (purple)
billion of neurons, in three different foraging efficiencies: 250 kcal/h (A), 500 kcal/h (B), or 750 kcal/h (C). Observe that increasing the foraging efficiency to 750 kcal/h,
primates could easily weigh more than 100 kg and have 100 billion neurons spending >5 h in foraging.
it is reasonable to accept its archeological onset 700,000 YA at the
localities of Gesher Benot Ya’aqov.
However, Foley and Gamble (2009) identified t h e fire control
with cooking purposes as early as 800,000 YA. Wu (1999) argues
that H. erectus pekinensis was able to cook in the cave of Getzetang
(in the complex of Zhoukoudien caves) around 450,000 YA. A
little later, according to
Thieme (1997), H. heidelbergensis hunted
and cooked horses in Schöningen, Northern Germany, which
would represent the first collective hunts, around 400,000 YA.
Meanwhile, hominins from Qesem (Israel) cooked deer and
turtles 400,000 YA, a practice kept t hroughout 200,000 YA at the
same locality (Karkanas et a l., 2007).
In Spain, Cortés-Sanchez et al. (2011) describe how
H. neanderthalensis ate cooked mussels in the cave of Bajondillo,
Malaga, 150,000 YA, while Blasco (2008) reports the practice of
cooking turtles in their shells, which were subsequently broken
with stones, around 130,00 0 YA in the cave of Bolomar, Valencia.
In short, according to the archeological data available, it is
reasonable to assume that fire control by hominins occurred
throughout the last 1 MYA and, during the first half of such
period, t h e evidence is sparse (Table 2). Consistent use of this
element, likely associated with cooking, represents a slow process
with an onset around 790,000 YA. The truly widespread use of
fire control takes place with our Neanderthal “cousins,” around
450,000 YA, and our present species has finally universalized it.
Based on these archeological evidence, we correlated maximal
brain volume of different hominins species according to their
time of appearance a nd the strength of evidence of their fire
control (Figure 3). Firstly, we observed a linear brain volume
increase in the human evolutionary lines during the last 4
millions of years (MY) (Figure 3A and Supplementary Figure
2A). It suggests that no evolutionary leap occurred in the human
ancestry, but rather a steady and regular process took place. More
importantly, adding evidence of fire control does not improve th e
description of brain evolution (Figure 3A). Indeed, species with
large brains appeared at periods when no evidence of fire control
exists (H. ergaster) or evidence of fire is very weak (H. antecessor
and H. latianensis). Interestingly, brain volumes of distinct fossils
of H. erectus dated from periods with weak and strong evidence
for human control of fire display very similar brain volumes
(Figure 3B). These data suggest that thermal processing of food is
unlikely to explain th e increase in foraging efficiency necessary to
evolve large brains, or alternatively, brain increase results from
still unknown evolutionary pathways. Therefore, archeological
evidence of fire control in the human lineage does not support the
view that thermal processing of food contributed to the evolution
of the human brain by increasing foraging efficiency.
Raw and Cooked Meat Bears Similar
Energetic Contents
Unlike the lack of evidence of fire control, there is considerable
evidence of the consumption of seeds (
Richards, 2002; Strait
et al., 2009) and meat (Heinzelin, 1999) dating back over 2 MY.
Nevertheless, if we were to assume that thermal processing of
food could arise at a similar stage and contribute to foraging
efficiency, cooked meat should provide a higher caloric content
than raw meat. To directly assess this possibility, we fed adult
mice for 4 days with similar amounts of raw and cooked meat. As
readout of t h e diet energetic content, we measured the animals
weight every day and calculated whether the absolute or relative
variation of weight correlated with meat consumption (Figure 4).
We observed a similar weight variation among animals fed
with eit he r cooked or raw meat (Figure 4A). Interestingly,
animals fed with cooked meat ingested, on the average, more
meat than animals fed with raw meat (Figure 4B). In both
groups, ingestion of meat was lower on the first day, likely due
to the adaptation to a new diet. As a consequence, animals
from both groups lost around 2 g on this first day of the diet,
but afterward their weight stabilized (Figure 4C). Finally, we
correlated the weight variation and meat consumption for each
animal (Figure 4D) and observed that, for a given value of
weight variation, animals fed with cooked meat required a higher
ingestion of food than animals fed with raw meat, probably
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Cornélio et al. Cooking and Human Brain Evolution
FIGURE 3 | Increase in the brain size during human evolution is
independent of fire control. (A) Maximal brain volume of different hominin
species related to their oldest possible time of origin (Table 1). Data indicate
that brain volume increased linearly in time (R
2
= 0.8032; p < 0.0001). Colors
represent the strength of archeological evidence supporting cooking by
hominins throughout the time (C; see also Table 2). (B) Maximal brain volume
of different Homo erectus fossils related to their oldest possible time of origin
(Table 3). Observe that similar brain volumes o f fossils dated from periods with
weak and strong evidence for human control of fire. (C) Summary of
archeological evidence used to classify the strength of data supporting fire
control in hominin lineage. Observe that strong evidence of fire control is
present only in the last 790,000 years and archeological data becomes more
prominent in the last 400,000 year with Homo neanderthalensis and Homo
sapiens. Also, note that species with a maximal brain volume, as large as
modern humans’, such as Homo erectus, appear at times when no evidence
of fire control is present. Legends: a) Aus. Afarensis; b) Aus. Africanus; c) Aus.
garhi; d) Aus. sediba; e) Homo rudolphensis; f) Homo habilis; g) Homo
ergaster; h) Homo georgicus; i) Homo erectus (Modjokento, Indonesia); j)
Homo erectus (Sangiran I, Indonesia); k) Homo erectus (Olduvai, Tanzania); l)
Homo lantianensis; m) Homo antecessor; n) Homo cepranensis; o) Homo
rhodesiensis; p) Homo heidelbergensis; q) Homo pekinensis; r) Homo
neanderthalensis; s) Homo sapiens.
reflecting the loss of fat caused by thermal processing (Sheard
et al., 1998
). Thus, our data indicate that energetic gain in a diet
based exclusively on raw meat is similar to, or even higher than,
a diet of cooked meat.
TABLE 3 | Maximal brain volume of Homo erectus fossils.
Location Time (MYA) Brain volume (cc)
Modjokerto, Indonesia 1,8 860
Koobi Fora I, Kenya 1,75 848
Nariokotome, Kenya 1,6 880–909
Trinil I, Indonesia 1,6 855
Koobi Fora II, Kenya 1,57 900
KNM-ER 42700, Kenya 1,55 1030
Sangiran I, Indonesia 1,5 1030
Olduvai, Tanzania 1,15 1065
Daka, Etyopia 1 995
Buia, Eritrea 1 820
Sangiran II, Indonesia 1 1010
Lantian, Shaanxi, China 1 780
Sangiran III, Indonesia 1 1100
Zhoukoudian, China 0,5 980–1075
Trinil II, Indonesia 0,4 1100
Dali, Shaanxi, China 0,3–0,26 1120
Solo, Java, Indonesia 0,14–0,12 1015–1250
Ngandong, Indonesia 0,2–0,07 917–1200
DISCUSSION
The disproportional increase in brain size relative to body size
is a distinctive evolutionary feature of humans. Given the high
metabolic cost of the human brain, many authors have suggested
that dietary modifications played important roles during human
evolution (
Heinzelin, 1999; Richards, 2002; Strait et al., 2009;
Organ et al., 2011; Wrangham, 2013). This conceivable metabolic
constraint has been further extrapolated to suggest a tradeoff
between brain and body size (Fonseca-Azevedo and Herculano-
Houzel, 2012). Here, we show that energy int a ke is likely to have
influenced human evolution, but not imposing a direct tradeoff
between those variables. Furthermore, we provide direct evidence
for the unlikelihood of thermal food processing as an important
factor to increase calorie availability to sustain the increased
number of brain neurons in t h e hominin lineage.
Energy int ak e is a direct product of the number of foraging
hours (H) and average caloric content of food (i.e., foraging
efficiency, Q). Here, we show that early hominins are likely to
have obtained enough energy to sustain a large brain on a raw-
food diet with 5–6 h of foraging per day. These observations are in
clear contradiction with pre vious data in the literature suggesting
that early hominins would require more than 9 h of foraging per
day to sustain their body mass and number of neurons (
Fonseca-
Azevedo and Herculano-Houzel, 2012). We believe that such
discrepancy can be explained by the fact that previous work
underestimated the energy intake of hominins and, therefore,
assumed an extremely limited foraging efficiency (∼200–250
kcal/h) for early hominins (Fonseca-Azevedo and Herculano-
Houzel, 2012
). In fact, Fonseca-Azevedo and Herculano-Houzel
(2012)
used a Z factor of 70 to calculate the energetic
needs of non-human primates, which likely underestimates the
foraging efficiency of these species (
Alperson-Afil et al., 2009).
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Cornélio et al. Cooking and Human Brain Evolution
FIGURE 4 | Mice fed with cooked or raw meat present similar weight variations. (A) Relative daily weight variation of mice fed exclusively on a raw meat diet
(white squares) or cooked meat diet (black squares). (B) Average amount of meat consumed per day in groups fed with raw (white bar) or cooked (black bar) meat.
(C) Absolute weight variation in both raw (white bar) and cooked (black bar) meat diet groups. Note that only on the first day there is a small decrease in the weight of
both groups. (D) Correlation between weight variation and meat consumption during 4 days. Observe that the linear regression for the raw meat group (red) is shifted
to the left, as compared to the cooked group (blue), indicating that for a similar variation of weight, animals fed on a raw meat diet require a lower amount of meat.
Furthermore, they t ook into account only the diet of non-human
primates predominantly frugivorous or herbivores, which leads
us t o the conclusion that the equation used in their work to
estimate foraging efficiency (E
IN
= 25.352 × M
0.526
BD
× H) does
not reflect the omnivorous diet of species in the hominin lineage
(Richards, 2002).
Accordingly, pieces of evidence indicate that, compared to
non-human primates, modern humans are clear evolutionary
outliers for the number of hours spent foraging (Organ et al.,
2011
). For instance, hunter-gatherers, such as the Kalahari
Bushmen and Hadza of Tanzania spend on the average 3–
5 h per day foraging, obtaining from 2140 to 3000 kcal/day
(Cohen, 2000). These values indic at e a foraging efficiency of
430 (minimum) to 1000 kcal/h (maximum), which is far greater
than that estimated by Fonsec a-Azevedo and Herculano-Houzel
(250 kcal/h) and closer to our estimates predicting that early
hominins could easily afford their brain and body size spending
about 5 h foraging. Foraging efficiency of early hominins could
also have been deeply influenced by cooperative hunting and
butchering (
Dominguez-Rodrigo et al., 2010) as well as by
new forms of communitarianism. These forms of cooperation,
including egalitarianism, developing of sophisticated empathy
and mind reading, language and cultural transmission are now
considered key aspects of hominin evolution, as proposed by
the “socio-cognitive niche” hypothesis (
Whiten and Erd al, 2012).
Thus, the enhancement of cognitive and behavioral complexity
transformed our ancestors in the most efficient predators on
Earth in spite of their lack of anatomical-hunting adaptations.
Early hominins likely increased their foraging efficiency by
varying their diets, including seeds and meat, which are more
caloric foods than wild plants and fruits. We provide compelling
evidence indicating that thermal food processing is unlikely to
explain increases in the foraging efficiency of early hominins.
Firstly, there is no archeological evidence of fire control at
the onset of brain expansion in the human lineage. Secondly,
archeological data establishing a cle ar relationship between fire
control and cooking by hominins are present only in t he last
790,000 YA. Thirdly, thermal processing of meat does not
increase energy content as indicated by variations in th e body
mass of mice fed in a raw or cooked meat diet. Although possible
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Cornélio et al. Cooking and Human Brain Evolution
energetic benefits of cooked meat may have evolved slowly over
time and not be appreciable in mice, our da ta in th is animal
model is important to refute previous data in the literature
supporting the cooking hypothesis (Carmody et al., 2011). In
this work, Carmody and colleagues suggest that the cooking of
tubers and meat increases energetic gain in mice, as reflected by
weight gain. Here, we repeated the same experiment with meat
and failed to find such energetic benefit in the thermal processing
of meat. Interestingly,
Carmody and Wrangham (2009) have
correctly pointed out in a previous work the paucity of studies
directly comparing raw and cooked meat with respect to energy.
They also highlight that results obtained from the few studies
to d a te were often contradictory. Therefore, we conclude that
more experiments need to be performed in order to address
the possible energetic benefits of thermal processing of meat in
humans.
Notably, even t he guardians of theories stating that a relatively
rapid increase in brain size, observed in the Homo erectus, is
the result of cooking acknowledge the lack of archeological
(
Wrangham, 2013) evidence in t h eir favor. Such theories must
include mandatory e vi dence of control of fire associated with
cooking, at least, 2 MYA, which is currently out of question.
Therefore, in this study, we favor the most classical view
suggesting that early hominins increased their foraging efficiency
by including new sources of food in their diet, especially seeds
and meat (Milton, 1999; Richards, 2002). Also, the use of tools is
well documented (Keeley and Toth, 1981; Domínguez-Rodrigo
et al., 2005) and strongly correlates with the increase in brain
size during human evolution (
Klein, 1977; Holloway, 1997).
Indeed, recent evidence indicates that the use of Lower Paleolithic
technologies to process meat and tubers reduced the number
of chewing cycles and the total masticatory force (Zink and
Lieberman, 2016), explaining the increased foraging efficiency of
early hominins at the onset of brain expansion. Therefore, the rise
in the use of tools, rather than cooking, is more likely to explain
how e arly hominins increased their daily energetic intake.
It is also possible that the emergence of new physiological
mechanisms improved the capacity of early hominins to obtain
energy from food intake. For instance, differential expression of
glucose transporters in the human brain could facilitate energy
allocation (
Fedrigo et al., 2011) and even changes in the gut
microbiota could contribute to raise the absorption of nutrients,
thus increasing the caloric content obtained from food (
Bäckhed
et al., 2005).
In conclusion, the appea ling hypothesis of thermal processing
of food as a pre-requisite to brain expansion during evolution
is not supported by archeological, physiological, and metabolic
evidence. Most likely, the control of fi re and cooking are
rather a consequence of the emergence of a sophisticated
cognition among hominins. We therefore, advocate that
the hypothesis on what builds h umankind uniqueness need
consistent archeological and physiological data before being
heralded.
AUTHOR CONTRIBUTIONS
MC and AC wrote the manuscript. RDN and RDB revised
archeological data. CQ, AC, and MC have worked in
the mathematic a l model. AC collected data from animal
experiments. MC designed the study and compiled results.
All authors read and approved the final version of the
manuscript.
ACKNOWLEDGMENTS
We thank Dr. Sergio Neuenschwander for the critical reading
and helpful discussions on early versions of the manuscript.
This work was supported by grants from the National Counsel
of Technological and Scientific Development (CNPq). AC was
supported by a PNPD/CAPES postdoctoral fellowship.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found
online at: http://journal.frontiersin.org/article/10.3389/fnins.
2016.00167
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Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
Copyright © 2016 Cornélio, de Bittencourt-Navarrete, de Bittencourt Brum,
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