while brm scales with body mass ( bm ) , several other factors seem to influence brm , such as sociability , environmental and dietary specializations , as well as energetic costs of brain tissue ( mace et al . , 1981 ) . large brains contain more neurons and neural connections , and thus have greater potential for information processing . large brains also tend to be more modular , which allows a great amount of connections between neurons ( krubitzer and kaas , 2005 ) . hence , increased brain mass and potential for neural connections may have facilitated large brained mammals to colonize complex habitats , develop sensory systems and evolved complex societies ( e.g. , budeau and verts , 1986 ) . for example , the mass - specific metabolic rate of the human brain is nine times higher than that of the body as a whole ( martin , 1981 ) . the metabolic costs by having a large brain must be paid for by a direct mother metabolic constraint or by a trade - off mechanism between brain mass and energy consumption by other functions ( e.g. , gibbons , 1998 ; pitnick et al . , 2006 ) . other energy allocations such as relative costs of flight and reproductive strategy in birds may also be reduced to shunt energy to an enlarged brain ( isler and van schaik , 2006 ) . recent examples also show that brm may become decoupled from bm over short time spans . 2009 ) found that tanganyikan cichlid bm exhibited recent bursts of rapid evolution , a process that is consistent with divergence linked to ecological specialization , while brm showed no bursts of divergence but evolved in gradual manner , consistent with energetic constraints to rapid bm change . originally , aiello and wheeler ( 1995 ) proposed that a primate is able to meet the high metabolic cost of a large brain without incurring a compensatory increase in relative basal metabolic rate ( bmr ) by decreasing the amount of other metabolically expensive tissues ( i.e. , heart , lung , kidney , liver , and gastrointestinal tract ) . a similar hypothesis was recently proposed for fish ( kaufman et al . , 2003 ) . recently , isler and van schaik ( 2009 ) using a large compilation of brain size , bm , and life history data , found evidence that an energetically costly increase in brain size has to be met by either increasing the total energy budget of a species or by compensating changes of energy allocation to other maintenance functions , such as digestion or growth and offspring production , or a combination of these . martin , 1981 , 1996 ) , for example , found that the energetic investment of the mammalian mother during the development of the fetus and during the postnatal life up to the time of weaning resulted in a weak link between bmr and brain mass . similarly , jones and maclarnon ( 2004 ) showed that for certain clades of bats , maternal investment plays an important role in the adult brain mass . while a number of studies have thus focused on these mechanisms of development , little is known about the evolutionary relationship between bmr and brm . very few studies have tested the generality of the  costly brain  hypotheses across multiple species with different evolutionary histories , and using phylogenetic approaches . basal metabolic rate is a fundamental parameter in comparative studies and lineages - specific exponents characterize its allometric scaling ( white et al . , 2009 ) . recently , isler and van schaik ( 2006 ) controlling both for bm and phylogentic relationships found evidence that bmr correlated with brm in large groups of mammals . however , brm explained a small % of the variation in metabolic rate at the species and family level ( 2.6 and 10.4% , respectively ) . at higher taxonomic levels , independent contrast ( ic ) revealed a significant correlation only for primates . it is possible that the use of composite phylogenies lacking resolution and accurate estimates of branch lengths ( bl ) may have obscured the underlying patterns ( e.g. , malia et al . , 2003 ) . other potential confounding we generated a novel phylogeny of wild rodents using bayesian analysis of cytochrome b sequence data . we included species where high - quality bmr , brm , and bm data are available . we then used this analysis to test the hypothesis that bmr and brm are correlated within rodents , after taking into consideration both bm and phylogeny . cytochrome b for 132 rodent species and six rabbits as outgroups ( wilson and reeder , 2005 ) were downloaded from genbank , and one sequence donated ( table a1 in appendix ) . cytochrome b was chosen as that marker has proven to be of high utility for species level phylogenetics ( may - collado and agnarsson , 2006 ; agnarsson et al . , 2010 , 2011 ) sequences were aligned using clustalx 1.83 ( thompson et al . , the preferred model for the bayesian analyses was selected with modeltest ( posada and crandall , 2001 ) using the aic criterion ( posada and buckley , 2004 ) . the best - fitting model was gtr  +    +  i ( yang , 1994 ) . bayesian analyses were carried out using mrbayes v3.12 ( huelsenbeck and ronchist , 2001 ) with the settings as specified in agnarsson and may - collado ( 2008 ) . the markov chain monte carlo search was ran with 10,000,000 generations sampling the markov chain every 1,000 generations , and the sample points of the first 7,000,000 generations were removed (  burnin  ) , after which the chain had reached stationarity . data on the log of brm and bm ( g ) , and bmr ( cmo2/h ) were used in this study ( table a1 in appendix ) . for studies comparing traits among species , such as regression analyses , it is necessary to account for phylogenetic relationships among the compared species ( felsenstein , 1985 ) . ignoring phylogenetic relationships can lead to pseudoreplication as species are not independent data points , rather independent evolutionary changes in the traits being compared are the data points , or the ic ( see felsenstein , 1985 ; may - collado et al . , 2007 ) among species and lineages . to describe the evolutionary relationship between bmr and brm we performed various phylogenetic analyses . ( i ) the pdap module in mesquite ( midford et al . , 2008 ) was used to estimate ic ( felsenstein , 1985 ) . we used bl as estimated by mrbayes testing them for statistic appropriateness using pdap . to correct for bm we regressed bmr and brm against bm and subsequently regressed the residuals from these regressions ( garland et al . , 1993 ) . if the residuals are correlated then that is consistent with a relationship among these variables ( bmr and brm ) , that is independent of the bm of , and phylogenetic relationship among , species ( e.g. , may - collado et al . , 2007 ) . ( ii ) to evaluate the correlated evolution among bmr , brm , and bm , we assess the phylogenetic effect on the trends in character relationships between taxa ( i.e. , the observed pattern ) using the best model of evolution that was found for each character . to do this we evaluated the significance of the relationships between the pair of characters using a measure of correlated evolution ( corr ) in a bayesian framework implemented in bayestrait 1.0 ( pagel and meade , 2007 ) , assessing the probability of positively correlated ( corr  >  0 ) and negatively correlated evolution ( corr  <  0 ) . as the null hypothesis we used a model in which the covariance between characters was set to zero ( i.e. , complete character independence , corr  =  0 ) , and the alternative hypothesis was , then , the observed covariance between characters ( pagel , 1999a , 1999b ) . if the null hypothesis was rejected ( i.e. , a significant historical relationship between characters exists ) , then we concluded that the phylogenetic relationship and the models of evolution of the characters influence the observed patterns , and we corroborate the hypothesis of correlated evolution between bmr , brm , and bm . we used a bayesian approach based on maximum likelihood with 10 test per tree and estimating pagel ( 1999a , b ) escalated phylogenetic parameters ( table a2 in appendix ) . the sign test was used for statistical comparisons ( zar , 1996 ) with statistica 6.0 ( statsoft , 2001 ) . the novel phylogeny finds support for the monophyly of each currently recognized taxonomical bat family with the exception that heteromyidae contains geomyidae , and one species of muridae , sigmodon hispidus , groups with cricetidae ( figure a1 in appendix ) . the phylogeny overall agrees well with recent rodent phylogenies at higher levels ( e.g. , jansa and weksler , 2004 ; montgelard et al . , 2008 ) and thus represents an reasonable hypothesis for to study the evolution of characters ( e.g. , pagel and harvey , 1988 ) independent contrast revealed associations between bm and bmr ( p  <  0.0001 ; r  =  0.77 ) , and with brm ( p  <  0.0001 ; r  =  0.85 ) , and between bmr and brm ( p  <  0.0001 ; r  =  0.71 ) . when using a single value to represent species mass we also found significant correlation between bmr and brm , after accounting for bm . when using a single individual weight to represent the species , bmr explained 9.7% of the variation in brm ( p  =  0.0003 ; r  =  0.097 ; figure 1a ) . two extreme outliers affected the regression and removing these outliers resulted in much stronger regression ( p  <  0.0001 ; r  =  0.20 ; figure 1b ) . the outliers represent 3 species of small rodents ( cricetidae , arvicolinae ) , that inhabit circumpolar northern hemisphere biome ( nowak , 1999 ) . these lemmings seem to have higher metabolic rate than typical rodents with similar brm , which may be related to living in extreme climates requiring higher metabolism . this demonstrates that the climate and habitat as well as other potentially confounding factors ( bm , food habits , substrate , a restriction to islands or highlands , use of torpor , and type of reproduction ) make it difficult to demonstrate a significant correlation between bmr and brm , even when it exists ( e.g. , mcnab , 2008 ) . ( a ) independent contrast regression analysis between bmr and brm residuals , corrected by bm . ( b ) ic regression analysis between bmr and brm residuals , corrected by bm and removing outliners ( myopus schisticolor , lemmus sibiricus , and l. lemmus ) . where bm  =  body mass , bmr  =  basal metabolic rate , and brm  =  rodent brain mass . when using species mean bm , bmr explained approximately 3% of variation in brm ( p  <  0.05 , r  =  0.029 ) . this correlation , however , disappears when using two bm values for each species , one , the estimated species mean , to calculate residuals of brm , and the second , of the individuals used for the bmr experiments , to calculate residuals of bmr ( p  >  0.05 ) . corr indicated significant correlations between all variables ( p  <  0.0001 ; corr 1 ) , with the highest correlation recorded between bm and brm ( p  <  0.0001 ; corr  =  2.86 ; r  =  0.95 ; figure 2 ) , followed by bm and bmr ( p  <  0.0001 ; corr  =  2.24 ; r  =  0.92 ; figure 2 ) , and finally bmr and brm ( p  <  0.0001 ; corr  =  1.86 ; r  =  0.91 ; figure 2 ) . the series of arrows in the middle of the figure indicates the model of correlated evolution between the studied characters in a bayesian framework ( for more details see materials and methods ) , where bm  =  body mass , bmr  =  basal metabolic rate , and brm  =  rodent brain mass . each inset labeled with a lower - case letter contains : on the left - hand side a line graph of a sample of 1,000 markov chain estimations ( x - axis ) of corr ( y - axis ) between pairs of characters , where the continuous black line represents corr  =  0 , and the continuous gray line indicates corr  =  1 ; and on the right - hand side a histogram of the probability distribution of covariance between pairs of characters , where the black bar indicates the average value and the gray bars indicate the lower 5% percentile ( lp ) and upper 95% percentile ( up ) . in particular , the analyzed characters were ( a ) bmr and brm ( lp  =  1.33 , up  =  2.46 ) ; ( b ) bm and bmr ( lp  =  1.50 , up  =  3.12 ) ; and ( c ) bm and brm ( lp  =  2.08 , up  =  3.77 ) . brains are the centers of the nervous system of vertebrates , controlling the organ systems of the body and coordinating responses to changes in the ecological and social environment ( shultz , 2010 ) . although brain mass per se does not capture the complexity of brain function , there is general evidence that relative brain size roughly correlates with cognitive ability ( e.g. , barton and harvey , 2000 ) . hence the evolution of brain size is of broad interest , including what factors may favor and constrain the evolution of relatively large , modular and complex brains ( sol , 2009 ) . basal metabolic rate is influenced by a variety of factors ( bm white and seymour , 2003 ; climate lovegrove , 2000 ; demography kurta and ferkin , 1991 ) . furthermore , an increase in brm results in increased costs for maintenance and information processing ( niven and laughlin , 2008 ) . for example , karbowski ( 2007 ) found that in volume - specific cerebral glucose metabolic rate of different brain structures closely scales with brain volume . these results confirm that information processing in the brain requires large amounts of metabolic energy . here , isler and van schaik ( 2006 ) found support for this relationship across all mammals combined , and within primates ( ic p  =  0.025 , r  =  0.20 ) , but not within other orders , such as rodents . adjustments appear to be clade - specific , the slopes of best - fit lines for brm against bm tend to be higher in analyses of more inclusive taxa ( e.g. , orders and suborders ) and lower in analyses of less inclusive taxa ( families , subfamilies , and genera ; e.g. , finarelli and flynn , 2009 ) . we hypothesize that the discrepancy between our findings and previous studies is potentially caused by two factors . first , the use of a composite versus primary - data based phylogenies , and second , differences in accounting for bm . composite phylogenies often reflect taxonomy , not necessarily phylogeny , and typically lack accurate bl estimates , two aspects that reduce the efficiency of comparative tests . accounting for bm is a complicated problem , but we argue that using more than a single value for a species , as have prior studies , may introduce confounding variables . thus using an estimate of species bm , such as average species bm to generate brm residuals , and the bm of the individual that happened to be used to evaluate bmr to generate bmr residuals , can likely adds noise that may obscure real patterns . if , for example , the evaluation of bmr happened to have been done on an atypically small or large animal , this would strongly affect the bm - bmr residual , and could readily obscure subtle patterns across two or more variables that are both highly correlated with bm . instead using a single value , whether mean bm of a species , or the weight of a single individual seems at least to be a reasonable alternative . furthermore , species mean bm is a measure independent of the available measures for bmr and brm ( typically single individuals ) , and as such provides a relatively neutral control unlikely to result in systematic error . here , we used a novel primary - data - based phylogeny with bl estimates and single estimates of species bm ( species average or single individuals ) . considering the compendium of factors that may contribute to bmr , the up to 20% of variation explained by brm in rodents is high . clearly , though , further research is necessary to understand the interplay between these variables , and ideally accurate estimates of species means based on multiple individuals would be available for each of these variables ( e.g. , smith and jungers , 1997 ) . our study is also consistent with two evolutionary paths  favoring  an increase in brm across rodent species . path in which an increase in bmr correlates with an increase in brm ( figure 2a ) . alternatively , indirect  and additive path in which the effect of bm on bmr allows brm to increase ( figures 2a , b ) . comparatively , the direct scaling effect of bmr on brm is the least important relationship ( figure 2a ) , but the importance of direct scaling increases when considering the indirect path . dunbar and shultz ( 2007 ) supported the indirect path scenario in primates , where bmr had a limiting effect on brm , while bm had an effect on brm through bmr . here , we corroborate the hypothesis of isler and van schaik ( 2006 ) that an increase in brain mass is accompanied by an increase in basal metabolic rate , and suggests that this pattern may be general across mammals . our findings corroborate the hypothesis that large brains evolve when the payoff for increased brain mass is greater than the energetic cost they incur ( niven and laughlin , 2008 ) . 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 . aic , akaike information criterion ; bl , branch lengths in phylogenies ; bm , body mass ; bmr , basal metabolic rate ; brm , brain mass ; corr , measure of correlated evolution between characters in a bayesian framework ; gtr , general time reversible models of nucleotide substitution ; ic , phylogenetic independent contrasts ; pdap , phenotypic diversity analysis programs .