Limits...
Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques.

Osada T, Adachi Y, Miyamoto K, Jimura K, Setsuie R, Miyashita Y - PLoS Biol. (2015)

Bottom Line: We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns.Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs.These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, The University of Tokyo School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan; Department of Physiology, Juntendo University School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.

ABSTRACT
Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC) are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i) activated PFC areas dynamically form an ordered network centered at a task-specific "functional hub" and (ii) the lesion-effective site corresponds to the "functional hub," but not to a task-invariant "structural hub." To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad). The predicted severity of impairment was proportional to the network "hubness" of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs. These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.

No MeSH data available.


Related in: MedlinePlus

Hub-centric cortical network for temporal-order judgment.(A) PPI (MIDDLE > BOTH-END). Color t-map of PPI is superimposed on the inflated brain. Upper and lower panels show the PPI maps for the seeds in areas 10 and 9/46d, respectively. (B, C) Two bar plots in each column show z-values for PPIs from area 10 (B) or area 9/46d (C) to other ipsilateral homotopic areas (gray) and PPIs from other homotopic areas to area 10 (B) or area 9/46d (C) (white). Dashed lines indicate significant z-value (p = 0.05 [FDR correction]). * p < 0.05 (FDR correction). (D) PPI matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. Significant connectivities are enclosed by thick black lines (p < 0.05 [FDR correction]). (E) Betweenness centralities of each area calculated based on (D). The dashed line indicates the significance at p = 0.05 (randomization test [comparison with the distribution of the randomized network]). * p < 0.05. (F) PPI matrix among the ten homotopic areas without assumptions of directionality. The weight of the connection between A and B is evaluated as the mean value of PPIA->B and PPIB->A. (G) Betweenness centralities of each area calculated based on (F). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05. (H) Anatomical connectivity matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. A white (black) square indicates the presence (absence) of anatomical connection from row to column. Anatomical information is based on the CoCoMac database [41,47,48]. The projections to/from areas 8Ad, SEF, and LIP listed in the matrix are categorized as those to/from areas 8A, 6DR, and POa in CoCoMac, respectively. (I) Betweenness centralities of each area calculated based on (H). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4488377&req=5

pbio.1002177.g003: Hub-centric cortical network for temporal-order judgment.(A) PPI (MIDDLE > BOTH-END). Color t-map of PPI is superimposed on the inflated brain. Upper and lower panels show the PPI maps for the seeds in areas 10 and 9/46d, respectively. (B, C) Two bar plots in each column show z-values for PPIs from area 10 (B) or area 9/46d (C) to other ipsilateral homotopic areas (gray) and PPIs from other homotopic areas to area 10 (B) or area 9/46d (C) (white). Dashed lines indicate significant z-value (p = 0.05 [FDR correction]). * p < 0.05 (FDR correction). (D) PPI matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. Significant connectivities are enclosed by thick black lines (p < 0.05 [FDR correction]). (E) Betweenness centralities of each area calculated based on (D). The dashed line indicates the significance at p = 0.05 (randomization test [comparison with the distribution of the randomized network]). * p < 0.05. (F) PPI matrix among the ten homotopic areas without assumptions of directionality. The weight of the connection between A and B is evaluated as the mean value of PPIA->B and PPIB->A. (G) Betweenness centralities of each area calculated based on (F). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05. (H) Anatomical connectivity matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. A white (black) square indicates the presence (absence) of anatomical connection from row to column. Anatomical information is based on the CoCoMac database [41,47,48]. The projections to/from areas 8Ad, SEF, and LIP listed in the matrix are categorized as those to/from areas 8A, 6DR, and POa in CoCoMac, respectively. (I) Betweenness centralities of each area calculated based on (H). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05.

Mentions: We next conducted a PPI analysis to examine whether temporal-order retrieval load affects connectivity among the identified areas. When we located the PPI seed in area 10, a significant increase in task-evoked connectivity (MIDDLE > BOTH-END) from this area was found in diverse PFC areas, including areas 9/46d and 8Ad (Fig 3A, upper panels). On the other hand, when we located the PPI seed in area 9/46d, a significant increase in task-evoked connectivity was found in areas 8Ad and TEa, but not in area 10 (Fig 3A, lower panels; for the profiles of PPI values for areas 10 and 9/46d, Fig 3B and 3C, S3 Fig; for the characterization of functions of area 10, see S4 Fig). When we estimated all the combinations of PPIs among the ten homotopic areas within the same hemisphere, a three-way ANOVA on PPI values (laterality [left or right] × seed area × target area) revealed a significant interaction between seed area and target area (F(81, 81) = 1.49, p = 0.03) with no significant main effect of laterality (F(1, 1) = 0.001, p = 0.98) or its interactions with seed area (F(9, 9) = 0.45, p = 0.87) or with target area (F(9, 9) = 0.73, p = 0.67). These results indicate that the PPI patterns were characterized solely by combinations of connectivity among the homotopic areas (Fig 3D). Similar PPI patterns among the ten homotopic areas were found in the PPI connectivities with contralateral regions (r = 0.78, p = 1.1 × 10−19) (S5 Fig; for individual monkey data, S6 Fig), and these patterns were significantly correlated between monkeys (r = 0.25, p = 0.004).


Dynamically Allocated Hub in Task-Evoked Network Predicts the Vulnerable Prefrontal Locus for Contextual Memory Retrieval in Macaques.

Osada T, Adachi Y, Miyamoto K, Jimura K, Setsuie R, Miyashita Y - PLoS Biol. (2015)

Hub-centric cortical network for temporal-order judgment.(A) PPI (MIDDLE > BOTH-END). Color t-map of PPI is superimposed on the inflated brain. Upper and lower panels show the PPI maps for the seeds in areas 10 and 9/46d, respectively. (B, C) Two bar plots in each column show z-values for PPIs from area 10 (B) or area 9/46d (C) to other ipsilateral homotopic areas (gray) and PPIs from other homotopic areas to area 10 (B) or area 9/46d (C) (white). Dashed lines indicate significant z-value (p = 0.05 [FDR correction]). * p < 0.05 (FDR correction). (D) PPI matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. Significant connectivities are enclosed by thick black lines (p < 0.05 [FDR correction]). (E) Betweenness centralities of each area calculated based on (D). The dashed line indicates the significance at p = 0.05 (randomization test [comparison with the distribution of the randomized network]). * p < 0.05. (F) PPI matrix among the ten homotopic areas without assumptions of directionality. The weight of the connection between A and B is evaluated as the mean value of PPIA->B and PPIB->A. (G) Betweenness centralities of each area calculated based on (F). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05. (H) Anatomical connectivity matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. A white (black) square indicates the presence (absence) of anatomical connection from row to column. Anatomical information is based on the CoCoMac database [41,47,48]. The projections to/from areas 8Ad, SEF, and LIP listed in the matrix are categorized as those to/from areas 8A, 6DR, and POa in CoCoMac, respectively. (I) Betweenness centralities of each area calculated based on (H). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4488377&req=5

pbio.1002177.g003: Hub-centric cortical network for temporal-order judgment.(A) PPI (MIDDLE > BOTH-END). Color t-map of PPI is superimposed on the inflated brain. Upper and lower panels show the PPI maps for the seeds in areas 10 and 9/46d, respectively. (B, C) Two bar plots in each column show z-values for PPIs from area 10 (B) or area 9/46d (C) to other ipsilateral homotopic areas (gray) and PPIs from other homotopic areas to area 10 (B) or area 9/46d (C) (white). Dashed lines indicate significant z-value (p = 0.05 [FDR correction]). * p < 0.05 (FDR correction). (D) PPI matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. Significant connectivities are enclosed by thick black lines (p < 0.05 [FDR correction]). (E) Betweenness centralities of each area calculated based on (D). The dashed line indicates the significance at p = 0.05 (randomization test [comparison with the distribution of the randomized network]). * p < 0.05. (F) PPI matrix among the ten homotopic areas without assumptions of directionality. The weight of the connection between A and B is evaluated as the mean value of PPIA->B and PPIB->A. (G) Betweenness centralities of each area calculated based on (F). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05. (H) Anatomical connectivity matrix among the ten homotopic areas. Rows and columns indicate seed and target areas, respectively. A white (black) square indicates the presence (absence) of anatomical connection from row to column. Anatomical information is based on the CoCoMac database [41,47,48]. The projections to/from areas 8Ad, SEF, and LIP listed in the matrix are categorized as those to/from areas 8A, 6DR, and POa in CoCoMac, respectively. (I) Betweenness centralities of each area calculated based on (H). The dashed line indicates significance at p = 0.05 (randomization test). * p < 0.05.
Mentions: We next conducted a PPI analysis to examine whether temporal-order retrieval load affects connectivity among the identified areas. When we located the PPI seed in area 10, a significant increase in task-evoked connectivity (MIDDLE > BOTH-END) from this area was found in diverse PFC areas, including areas 9/46d and 8Ad (Fig 3A, upper panels). On the other hand, when we located the PPI seed in area 9/46d, a significant increase in task-evoked connectivity was found in areas 8Ad and TEa, but not in area 10 (Fig 3A, lower panels; for the profiles of PPI values for areas 10 and 9/46d, Fig 3B and 3C, S3 Fig; for the characterization of functions of area 10, see S4 Fig). When we estimated all the combinations of PPIs among the ten homotopic areas within the same hemisphere, a three-way ANOVA on PPI values (laterality [left or right] × seed area × target area) revealed a significant interaction between seed area and target area (F(81, 81) = 1.49, p = 0.03) with no significant main effect of laterality (F(1, 1) = 0.001, p = 0.98) or its interactions with seed area (F(9, 9) = 0.45, p = 0.87) or with target area (F(9, 9) = 0.73, p = 0.67). These results indicate that the PPI patterns were characterized solely by combinations of connectivity among the homotopic areas (Fig 3D). Similar PPI patterns among the ten homotopic areas were found in the PPI connectivities with contralateral regions (r = 0.78, p = 1.1 × 10−19) (S5 Fig; for individual monkey data, S6 Fig), and these patterns were significantly correlated between monkeys (r = 0.25, p = 0.004).

Bottom Line: We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns.Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs.These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.

View Article: PubMed Central - PubMed

Affiliation: Department of Physiology, The University of Tokyo School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan; Department of Physiology, Juntendo University School of Medicine, Hongo, Bunkyo-ku, Tokyo, Japan.

ABSTRACT
Neuroimaging and neurophysiology have revealed that multiple areas in the prefrontal cortex (PFC) are activated in a specific memory task, but severity of impairment after PFC lesions is largely different depending on which activated area is damaged. The critical relationship between lesion sites and impairments has not yet been given a clear mechanistic explanation. Although recent works proposed that a whole-brain network contains hubs that play integrative roles in cortical information processing, this framework relying on an anatomy-based structural network cannot account for the vulnerable locus for a specific task, lesioning of which would bring impairment. Here, we hypothesized that (i) activated PFC areas dynamically form an ordered network centered at a task-specific "functional hub" and (ii) the lesion-effective site corresponds to the "functional hub," but not to a task-invariant "structural hub." To test these hypotheses, we conducted functional magnetic resonance imaging experiments in macaques performing a temporal contextual memory task. We found that the activated areas formed a hierarchical hub-centric network based on task-evoked directed connectivity, differently from the anatomical network reflecting axonal projection patterns. Using a novel simulated-lesion method based on support vector machine, we estimated severity of impairment after lesioning of each area, which accorded well with a known dissociation in contextual memory impairment in macaques (impairment after lesioning in area 9/46d, but not in area 8Ad). The predicted severity of impairment was proportional to the network "hubness" of the virtually lesioned area in the task-evoked directed connectivity network, rather than in the anatomical network known from tracer studies. Our results suggest that PFC areas dynamically and cooperatively shape a functional hub-centric network to reallocate the lesion-effective site depending on the cognitive processes, apart from static anatomical hubs. These findings will be a foundation for precise prediction of behavioral impacts of damage or surgical intervention in human brains.

No MeSH data available.


Related in: MedlinePlus