Functional connectivity (FC) in the cerebral cortex of humans in the resting state and of anesthetized macaque monkeys measured by functional magnetic resonance imaging (fMRI) is commonly assumed to reflect the underlying anatomical connectivity (AC). But it is known that cortical regions with no direct anatomical connectioncan also have strong FC, suggesting an important role ofindirect anatomical pathways mediated by multiple cortical regionson the shaping of FC.The direction of axonal projections along the pathways essentially determines the causal directions in the neuronal interactions; nevertheless, there has been no empirical study on how the directionality of AC contributes to FC at the inter-areal level, because of the lack of noninvasive techniques to distinguish the directionality of AC in humans.

In macaque monkeys, anatomical projections across a wide range of brain regions have been investigated for decades, and their directionality is known. In this study, by using fMRI in macaque monkeys, we examined empirically how FC between an area pair is dependent on indirect AC patterns between the pair,and weinvestigated computationally how this relationship depends on the global network structure of the cerebral cortex.

We acquired BOLD fMRI in anesthetized macaque monkeys with a 4.7-T MRI scannerand extracted the time series of BOLD signals from 39 regions in each hemisphere of the animals.Then,by correlating the BOLD time seriesafter preprocessings, FC was computed in all the area pairs within each hemisphere in each BOLD run.Figure 1a shows the FC matrix averaged across all BOLD runsand across both hemispheres fromall animals.Information about the presence and the direction of anatomical connections among the macaque cortical areas examined in present study direction of anatomical connections among the macaque cortical areas examined in present study direction of anatomical connections among the macaque cortical areas examined in present study direction of anatomical connections among the macaque cortical areas examined in present study direction of anatomical connections among the macaque cortical areas examined in present study direction of anatomical connections among the macaque cortical areas 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In the empirical FC and AC matrices (Figs 1a and 1b), area pairs with direct AC (unidirectional or bidirectional) indeed have larger FC on average than those with no direct AC, but considerable proportions of unconnected area pairs have FC values comparable to connected area pairs (Fig. 1c). We examined how the number of indirect anatomical connections between an area pair affects the FC of the area pair. In the macaque FC (Fig. 1a) and AC (Fig. 1b) matrices, FC of area pairs with no direct AC significantly increases with the total number of the indirect AC mediated by just one area in-between ('length-2 AC') (linear regression, n=479, slope=6.6 ×10(-3), P < 0.001). However,the number of indirect AC with two areas in-between ('length-3 AC') does not contribute to the increase of FC in area pairs with neither direct nor length-2 AC (linear regression, n=74, slope=-7.3×10(-4), P= 0.03). In the macaque AC matrix (Fig. 1b) there is only one area pair with neither direct, length-2, nor -3 AC, and there is no area pair with neither direct, length-2, -3, nor -4 AC. These results imply that FC increases with the number of indirect AC only at length-2 AC.

The information about the directionality of tract projections in the macaque monkey allowedus to distinguish the six different length-2 AC patterns (A to F in Fig. 2a), which are not distinguishable in diffusion MRI tractography. Then we examined whether these six length-2 AC patterns make differential contributions to FC in the macaque monkey. The contribution of each length-2 AC pattern to FC (Fig. 2a)was estimated for each hemisphere of each monkey by using multiple linear regressions (P< 0.001 in the fittings for all the hemispheres). A three-way ANOVA for the estimated contributions (AC pattern ×Monkey ×Hemisphere) revealed a significant main effect of AC pattern (F5,5= 8.18, P < 0.05), no significant main effects of Monkey and Hemisphere (F1,5= 0.57 and F1,5= 0.89 respectively, P> 0.1 for both), and no significant two-way interactions (P>0.05 for all). In particular we focused on the comparison of the directed AC patterns (motifs) of 'common efferents' (pattern A), 'disynaptic relay' (pattern B), and 'common afferents' (pattern C). Based on the apparent causal relationships represented inthe AC patterns A, B, and C, one might expect that the contribution of common efferents (pattern A) to FC is smaller than that of the other two patterns; however, our comparison revealed that, contrary to the expectation, not only common afferents (pattern C) but also common efferents (pattern A) make greater contributions to FC than the disynaptic relay (pattern B) (P < 0.01, Tukey test).

This counterintuitive observation demands an interpretation from a viewpoint beyond the localaspects of the AC patterns. Therefore we computationally investigated how the global network structure relates to this empirical observation.A previous computational study(Honey et al. 2007) simulated BOLD time series of macaque cortical areas including the areas examined in the present empirical data, based on a model incorporating empirically known axonal projections ('macaque-type anatomical network'). The FC matrix based on the simulated BOLD time series ('macaque-type simulation')significantly correlates with the empirical FC (Fig. 1a) (R= 0.55, P< 0.001). We confirmed that the above-mentioned relations between FC and AC in the empirical data are preserved in the macaque-type simulation: the significant difference of FC between area pairs with direct AC (bidirectional and unidirectional) and those with no direct AC and the significant positive contribution of the combined length-2 AC to FC (linear regression, slope=1.0 ×10(-2), P< 0.001). Most importantly, the respective contributions of the length-2 AC patterns are also preserved (correlation coefficient R= 0.91, P< 0.05; Fig. 2b). We defined the z-score-transformed correlation coefficient as the 'match-with-empirical index' (MEI; MEI=2.64 for the macaque-type simulation). MEI represents how well the simulation preserves the contributions of the length-2 AC patterns. These agreements strongly suggest that the empirically detected contributions of length-2 AC patterns to FC (Fig. 2a) are induced by the anatomical network that is shared by the macaque-type simulation and the real macaque neocortex.

Thus, we can computationally investigate whether the contributions of the length-2 AC patterns to FC (Figs. 2aand 2b) are specific to the macaque cortical network, by comparing the MEI in the macaque-type simulation with the MEIs in simulations on randomly rewired anatomical networks. We first generated random anatomical networks in which the number of afferent and efferent connections of each area (degree) is matched with that in the macaque-type network. Then we simulated the BOLD-FC matrix and computed the MEI for each random network. Compared with all the random networks (n= 1,000), the MEI of the macaque-type network is exceptionally large (P< 0.001; Fig 2c). Therefore the empirically detected contributions of length-2AC patterns to FC (Fig. 2a) are unique to the anatomical network of the macaque cortex.

Next we examined whether some network metrics can capture the uniqueness of the macaque cortical network that appears in the local AC-FC relation. As the candidates for the metrics, we focused on the clustering coefficient, the modularity, and the motif frequencies of size M=2 and 3 (mf2 and mf3). The clustering coefficient and the modularity are found at higher levels in the macaque network. For each metric we constructed rewired anatomical networks (n=1,000) in which the values of the metric as well as the degrees are matched with those of the macaque-type network. Then, for each network, the BOLD-FC matrix was simulated, and the MEI was computed. Figure 2cshows that the mf2-matched (MF2) and the mf3-matched (MF3) networks have significantly larger MEIs than other networks (P < 0.001). These results suggest that the configuration of anatomical motifs in the cortical network have a role in generating the contributions of length-2AC patterns that are empirically observed. Nonetheless, in all of the four sets of metric-matched networks, the MEI of the macaque-type network is highly exceptional (P < 0.001, P=0.002, P=0.04, and P=0.037 for MD, CL, MF2, and MF3networks, respectively; Fig. 2c). Thus these network metrics might not fully capture the unique properties of the macaque cortical network.

Our results demonstrate how macaque cortical FC is dependent on local AC patterns and on the direction of inter-regional pathways (Fig. 2a). The AC-FC relation is not determined solely by local inter-regional causality but instead is dominated by the network-levelanatomical architecture of the cortex (Fig. 2c), which would include the distribution and arrangement of directed anatomical motifs and the hierarchical organization of the cerebral cortex. The observation that the contributions of common efferents and afferents to FC are larger than that of the disynaptic serial relay supports the notion that functionally related areas have common profiles ofanatomical inputs and outputs. The high consistency of empirical and simulated FC also suggests that the local AC-FC relations revealed in this study are largely supported by cortico-cortical pathways, and less dependenton anatomical links with subcortical structures.

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Figure 2

本研究では、マカクサルにおいて4.7テスラMRI装置を用いた磁気共鳴機能画像法(fMRI)実験を行い、大脳皮質領域間の機能的結合性(functional connectivity)を大脳の広範囲にわたって網羅的に計測し、神経軸索投射によって構成される解剖学的な領野間ネットワーク構造との関係を調べた。とくに、直接に軸索投射をもたない領野間に生じるfunctional connectivityについて、最短経路を介した信号伝達だけではfunctional connectivityの大きさは決定しないことを明らかにした。さらに、大型計算機を利用したシミュレーションにより、領野間のfunctional connectivityの大きさは、解剖学的結合(anatomical connectivity, AC)のネットワーク構造に大きく影響を受け、中でもネットワークモチーフの大脳皮質全体における構成による影響が大きいことを示した。

近年、安静状態のヒトや、麻酔下マカクサルにおいて、大脳皮質領野間のfunctional connectivityを、BOLD(blood-oxygenation-level-dependent)効果を利用したfMRIを用いて測定する研究が広く行われている。通常BOLD functional connectivityは、神経軸索投射による解剖学的結合を反映しているものとされる。しかし、直接には解剖学的結合をもたない大脳皮質領野間においても、大きなfunctional connectivityが存在しうることが報告されている。このことは、他領野を介した間接的な経路が、functional connectivityを形成する上で重要な役割をもつことを示唆している。神経活動の細胞間因果関係は軸索の投射方向により決定されるが、大脳領野間のfunctional connectivityが、間接経路の軸索投射方向とどのような関係にあるのかについては、これまで実験に基づいた報告は存在しない。理由の一つは、ヒトにおいては、軸索投射の方向性を同定する非侵襲的な技術が存在しないことである。

マカクサルにおいては、神経トレーサーを用いた膨大な研究の蓄積により多くの大脳領野間で軸索投射の有無とその方向性が知られている。本研究では、マカクザルを用いてfMRI実験を行い、直接に結合のない大脳領野間のfunctional connectivityが、間接経路における軸索投射の方向性にどのように依存しているかを調べた。

2頭の麻酔下マカクサルにおいて取得したfMRIデータから、大脳半球内の39領野のBOLD信号時系列を抽出し、各半球内のすべての領野の組み合わせにおいてfunctional connectivityを計算した。直接に(一方向または双方向に)軸索投射が存在する領野間では、直接結合のない領野間に比べてfunctional connectivityの平均値は有意に大きいが、しかし同時に、直接結合のない領野間においても、直接結合のある領野間と同程度の大きさのfunctional connectivityが多数存在することが確認された。また、直接に軸索投射のない領野間のfunctional connectivityの大きさは、1つだけ領野を介する間接結合の数とともに増加することが確認され、それに対し2つの領野を介する間接結合の数はfunctional connectivityの増加には寄与しないことがわかった。

1つの領野を介する間接的な経路は、軸索投射の方向性を考慮すると、さらに6つの異なるパターン(ACパターン)に区別することができる。それぞれのパターンのfunctional connectivityへの寄与を重回帰分析によって推定した結果、2つのシナプスを介したリレーパターン(disynaptic relay)よりも、共通入力(common afferents)さらには共通出力(common efferents)の寄与が大きいことが分かった。もしfunctional connectivityが最短経路に大きく依存しているならば、各ACパターンで表現される因果関係に基づけば、'common efferents'は、'disynaptic relay'や'common afferents'と比較して寄与が小さくなると予想され、上述の結果はこの予想に反するものである。

これらの予想に反する結果が、領野間軸索結合のネットワーク的性質によるものであるかどうかを、BOLD functional connectivityの計算機シミュレーションモデルを利用して調べた。このモデルは領野間軸索結合の情報を取り込んだもので、結合を任意に配線しなおすことにより、ネットワークの構造とfunctional connectivityの関係を調べることができる。ランダムなネットワークと、以下の4種類のネットワーク指標についてマカクサル大脳皮質と同じ値に設定したネットワークを、各1000個ずつ生成した:(i)クラスター係数、(ii)モジュラリティー、(iii)2つあるいは(iv)3つの領野からなるネットワークモチーフの出現回数。それぞれのネットワークで領野間のfunctional connectivityをシミュレートした結果、3つの領野からなるネットワークモチーフ出現回数を保存するネットワークにおいて、上記のサルにおける実験結果を再現する確率が大幅に上昇することが示された。

本研究は、マカクサル大脳領野間functional connectivityを網羅的に実験計測して調べた初めての研究である。以上の結果は、大脳領野間の機能的な相互関係は局所的な信号伝達だけでは決定されず、領野間の解剖学的ネットワークに特有な構造を強く反映していることを示すものである。この知見は、いまだよく分かっていないfunctional connectivity生成のメカニズムや、解剖学的結合ネットワークとその上で生じる機能的な相互作用との関係の解明に、重要な貢献をなすと考えられる。

この論文は、長田貴宏氏、渡部喬光氏、Olaf Sporns教授、松井鉄平氏、宮本健太郎氏、宮下保司教授との共同研究であるが、論文提出者が主体となって研究を行ったもので、提出者の寄与が十分であると認められる。従って審査員一同は同提出者に博士(理学)の学位を授与出来ると判断する。