Page 1 of 13
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
1 Reviewer: 1 Recommendation: Major Revision Comments: Li and colleagues present an interesting study to investigate effective connectivity measures during both task performance and resting-state (restricted to the DMN) in elder subjects, and their relationship with task performance. Main findings include increased effective connectivity modulation during the face-name task compared to during resting-state, and significant linear correlation between performance on the memory tasks and effective connectivity. Technically, in my opinion, this is a solid paper and I do not have any comments at this level, particularly as the authors have proved former experience in publishing studies using similar methodological approaches. My concerns are more on the side of the interpretation of the findings. I think that overall the authors need to perform some more efforts to put the findings within the context of the biological meaning for the aging brain. First, I think the paper lacks a more clear rationale as why this methodology is necessary or meaningful to illuminate relevant questions specifically for the aging literature. What are the specific questions addressed regarding the current knowledge of the functional brain characteristics of the aged brain? There is a long history of studying connectivity loss in aging and Alzheimer’s’ disease (AD) subjects. Generally, it has been found that there is decreased functional and structural connectivity in these subjects (Clerx et al., 2012; Damoiseaux et al., 2012; Damoiseaux et al., 2009; Rose et al., 2000). However, only a few studies have been carried out to investigate effective connectivity (causality) in ageing and AD. Causality analysis methods are very useful to investigate long distance network integration in the human brain. However, due to the nature of the Blood Oxygenation Level Dependent (BOLD) response, effective connectivity results from this method are modulated by different input stimuli. Therefore, it is necessary to conduct experiments to study effective connectivity changes under different condition, i.e., using different stimuli as brain system inputs. The purpose of this study was to achieve this goal. We studied dynamic brain network modulation effects using different stimuli and investigated the neuronal dynamic properties in ageing subjects. The biological implication is that older adults and possible AD, there is decreased neuronal dynamics, which may contribute to reduced functional and structural connectivity. The loss of neuronal population dynamics could happen before function and structural changes are detected using neuroimaging, consequently, 1
Page 2 of 13
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
2 this could be a new biomarker for early AD diagnose, or for the detection of agerelated changes in neural network dynamics. This study goes one step further to understanding the dynamics properties of functional brain characteristics in the aged brain. Please see that this discussion of the rationale for the study has also been inserted into the Introduction of the revised manuscript, page 5.
Also, I do not clearly understand what motivated to select an emotional implicit memory task in this study. Emotional processes are not amongst the most affected processes in normal elders. The use of an emotional task, in my opinion, hampers the generalization of the findings to other fMRI studies using more classic (non-emotional) episodic memory tasks.
Although emotional processes may not be the most vulnerable to age-related decline, there have been many studies reporting changes in emotional processing and the neural processes that support them in both healthy ageing (Kehoe et al., 2013; Mather, 2012) and AD (Grady et al., 2001; Rosenbaum et al., 2010). The dynamic nature of emotional networks have been less well studied in ageing, and additionally, we have experience and an interest in the study of emotional processing (Kehoe et al., 2013). Please see page 6, first paragraph (around middle) of the Introduction of the revised manuscript, where some of these comments have been incorporated into the text.
In general the authors need to interpret their regional findings according to the recent models of neuroimaging in aging, i.e. do their findings relate to large-range connections within the DMN (i.e. those affecting medial frontal and parietal structures) as more relevant than short or local-range connections? Is there some kind of increased anterior or prefrontal effective connectivity (for instance associated with successful task performance), which could align with some other views of functional neuroimaging of aging in the literature?, other areas such as the hippocampus seem also be more relevant than, for instance, visual associative regions?
The findings in the DMN are mainly focused on the posterior cingulate cortex, hippocampus and amygdala. The main associations between effective connectivity and memory performance are with the hippocampus, and amygdala given the emotional content of the faces and the evidence in the current manuscript would support shorter length connections. We cannot directly address the question as we only have an older healthy cohort in our study.
The resting-state fMRI acquisition seems to be performed always after the task-related activation, but yet the authors mention a paper (Sala-Llonch et al. 2012) where memory 2
Page 3 of 13
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
3 performance was predicted from resting state connectivity obtained before the task itself, which in this case really suggests a predictive effect. Can the authors clarify what do they mean by ‘prediction’ in their study?
The resting state fMRI scan in our study was always performed before the fMRI task, apologies if this was not clear from the description of our methods. This was to ensure that the any residual effects of the face-name encoding task did not modulate the resting state activity. It also meant that the encoding task was nearer the end of the scanning session, facilitating a shorter recognition period (approximately 30 minutes). This detail has been added to the methods section page 10. The ‘prediction’ in this study means how strong the relationship is between rfMRI and task fMRI for the effective connectivity measures. The word prediction has been removed from text to minimize mis-understanding.
The mean performance of the task is not reported: where there subjects performing at chance level? Where they excluded? The following has been added to the results section: The average memory performance on the tasks is now included in the updated manuscript, see pages 24-25. To briefly summarise, in recognition task 1 (forced choice recognition task) the participants correctly recognised 67.33 ±15.59 % of the faces from the scanning session (Old Correct), whilst they forgot 31.75 ± 11.60 % of the faces (Old Incorrect). Nine foils (faces not seen in the scanning session) were also presented and of these the participants on average incorrectly classified 39.20 ±11.62 % as ones they had seen before (New Incorrect), but correctly classified 61.31 ±11.60 % as new faces. To control for false memory an adjusted recognition score was used for the correlations with the fMRI results, (% Old Correct) – (% New Incorrect). On recognition task 2 the participants on average selected the correct name for faces they had seen in the scanner on 55.69 ±12.24 % of trials. On average they chose the incorrect name on 42.86 ±12.11 % of trials, and there were 1.32 ±5.72 % missed trials (i.e. no response). Can the authors provide the correspondence between significant thresholds set at T values with those corresponding to p corrected values in each case?
Yes, we have added p values in the manuscript. All the significance level of default p value in this study is P0.37, p
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
1 Reviewer: 1 Recommendation: Major Revision Comments: Li and colleagues present an interesting study to investigate effective connectivity measures during both task performance and resting-state (restricted to the DMN) in elder subjects, and their relationship with task performance. Main findings include increased effective connectivity modulation during the face-name task compared to during resting-state, and significant linear correlation between performance on the memory tasks and effective connectivity. Technically, in my opinion, this is a solid paper and I do not have any comments at this level, particularly as the authors have proved former experience in publishing studies using similar methodological approaches. My concerns are more on the side of the interpretation of the findings. I think that overall the authors need to perform some more efforts to put the findings within the context of the biological meaning for the aging brain. First, I think the paper lacks a more clear rationale as why this methodology is necessary or meaningful to illuminate relevant questions specifically for the aging literature. What are the specific questions addressed regarding the current knowledge of the functional brain characteristics of the aged brain? There is a long history of studying connectivity loss in aging and Alzheimer’s’ disease (AD) subjects. Generally, it has been found that there is decreased functional and structural connectivity in these subjects (Clerx et al., 2012; Damoiseaux et al., 2012; Damoiseaux et al., 2009; Rose et al., 2000). However, only a few studies have been carried out to investigate effective connectivity (causality) in ageing and AD. Causality analysis methods are very useful to investigate long distance network integration in the human brain. However, due to the nature of the Blood Oxygenation Level Dependent (BOLD) response, effective connectivity results from this method are modulated by different input stimuli. Therefore, it is necessary to conduct experiments to study effective connectivity changes under different condition, i.e., using different stimuli as brain system inputs. The purpose of this study was to achieve this goal. We studied dynamic brain network modulation effects using different stimuli and investigated the neuronal dynamic properties in ageing subjects. The biological implication is that older adults and possible AD, there is decreased neuronal dynamics, which may contribute to reduced functional and structural connectivity. The loss of neuronal population dynamics could happen before function and structural changes are detected using neuroimaging, consequently, 1
Page 2 of 13
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
2 this could be a new biomarker for early AD diagnose, or for the detection of agerelated changes in neural network dynamics. This study goes one step further to understanding the dynamics properties of functional brain characteristics in the aged brain. Please see that this discussion of the rationale for the study has also been inserted into the Introduction of the revised manuscript, page 5.
Also, I do not clearly understand what motivated to select an emotional implicit memory task in this study. Emotional processes are not amongst the most affected processes in normal elders. The use of an emotional task, in my opinion, hampers the generalization of the findings to other fMRI studies using more classic (non-emotional) episodic memory tasks.
Although emotional processes may not be the most vulnerable to age-related decline, there have been many studies reporting changes in emotional processing and the neural processes that support them in both healthy ageing (Kehoe et al., 2013; Mather, 2012) and AD (Grady et al., 2001; Rosenbaum et al., 2010). The dynamic nature of emotional networks have been less well studied in ageing, and additionally, we have experience and an interest in the study of emotional processing (Kehoe et al., 2013). Please see page 6, first paragraph (around middle) of the Introduction of the revised manuscript, where some of these comments have been incorporated into the text.
In general the authors need to interpret their regional findings according to the recent models of neuroimaging in aging, i.e. do their findings relate to large-range connections within the DMN (i.e. those affecting medial frontal and parietal structures) as more relevant than short or local-range connections? Is there some kind of increased anterior or prefrontal effective connectivity (for instance associated with successful task performance), which could align with some other views of functional neuroimaging of aging in the literature?, other areas such as the hippocampus seem also be more relevant than, for instance, visual associative regions?
The findings in the DMN are mainly focused on the posterior cingulate cortex, hippocampus and amygdala. The main associations between effective connectivity and memory performance are with the hippocampus, and amygdala given the emotional content of the faces and the evidence in the current manuscript would support shorter length connections. We cannot directly address the question as we only have an older healthy cohort in our study.
The resting-state fMRI acquisition seems to be performed always after the task-related activation, but yet the authors mention a paper (Sala-Llonch et al. 2012) where memory 2
Page 3 of 13
Brain Connectivity Modulation of effective connectivity in the default mode network at rest and during a memory task (doi: 10.1089/brain.2014.0249) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.
3 performance was predicted from resting state connectivity obtained before the task itself, which in this case really suggests a predictive effect. Can the authors clarify what do they mean by ‘prediction’ in their study?
The resting state fMRI scan in our study was always performed before the fMRI task, apologies if this was not clear from the description of our methods. This was to ensure that the any residual effects of the face-name encoding task did not modulate the resting state activity. It also meant that the encoding task was nearer the end of the scanning session, facilitating a shorter recognition period (approximately 30 minutes). This detail has been added to the methods section page 10. The ‘prediction’ in this study means how strong the relationship is between rfMRI and task fMRI for the effective connectivity measures. The word prediction has been removed from text to minimize mis-understanding.
The mean performance of the task is not reported: where there subjects performing at chance level? Where they excluded? The following has been added to the results section: The average memory performance on the tasks is now included in the updated manuscript, see pages 24-25. To briefly summarise, in recognition task 1 (forced choice recognition task) the participants correctly recognised 67.33 ±15.59 % of the faces from the scanning session (Old Correct), whilst they forgot 31.75 ± 11.60 % of the faces (Old Incorrect). Nine foils (faces not seen in the scanning session) were also presented and of these the participants on average incorrectly classified 39.20 ±11.62 % as ones they had seen before (New Incorrect), but correctly classified 61.31 ±11.60 % as new faces. To control for false memory an adjusted recognition score was used for the correlations with the fMRI results, (% Old Correct) – (% New Incorrect). On recognition task 2 the participants on average selected the correct name for faces they had seen in the scanner on 55.69 ±12.24 % of trials. On average they chose the incorrect name on 42.86 ±12.11 % of trials, and there were 1.32 ±5.72 % missed trials (i.e. no response). Can the authors provide the correspondence between significant thresholds set at T values with those corresponding to p corrected values in each case?
Yes, we have added p values in the manuscript. All the significance level of default p value in this study is P0.37, p
