Affective 1-back task: working memory and affective processing

When we investigated brain-behavior relationships during both executive function and affective face processing, we found that interference was associated with reduced activation in the posterior cingulate gyrus, left hippocampus, right hippocampus, and right amygdala; avoidance with reduced left hippocampus activity; numbing with decreased inferior frontal gyrus activity; and decreased medial PFC and fusiform gyrus activity to verbal working memory performance. These findings suggest there is greater recruitment in affective circuitry and reductions in task-relevant activations during the completion of an executive task in the context of emotional stimuli, as it relates to increased symptom severity. These findings could represent the interference of emotional stimuli on executive function on the neural level, where more neural resources are devoted to emotional face processing than those attributed to the working memory component. It is important to note however, that participants did not do any worse during this task condition.

Specifically, reduced activation in the hippocampus could be the result of sensitivity to stress, in other words blunted hippocampal response may indicate sensitivity to stress. Studies have shown that in early stages of stress, enlarged hippocampal volume or increased activation is seen, while long-term chronic stress results in hippocampal atrophy and loss of function. Alternatively, underlying hippocampal dysfunction may lead to stress and PTSD, as the hippocampus is the prime inhibitor of the HPA axis. Therefore, these findings could provide information about suffering from long-term chronic stress and effects on the brain. Lastly, decreased activation in the dmPFC is consistent with previous findings in PTSD. Previous findings in PTSD demonstrated decreased medial prefrontal cortex activation in response to aversive stimuli, including fearful faces, as was shown in our study.

These findings could be interpreted as emotions taking the cognitive processing system off-line [285]. We may conclude that these effects are small, which is why there was no effect on accuracy or performance. These findings may also suggest compensatory activation that is somehow preserving goal- directed behavior while also processing emotional information. Because significant coping and symptom associations are specific to PTSD-mTBI, the magnitude of the relationships and context in which they appear could be the type of information important for understanding individual neural profiles and their associations with different symptoms; this understanding would therefore improve individualized

treatment options. Our findings support the idea that coping with emotional distraction entails interactions among brain regions responsible for detection/inhibition of emotional distraction (IFG, AMY) and the processing of emotional stimuli and emotional memories (PCC, HC) [232]. Moreover, these findings suggest executive attentional dysfunction secondary to emotional distraction, which may lead to impulsive decision-making during states of high emotion. As our data show enhanced activations under emotional distraction, it aligns with the hypothesis that task-specific activation is boosted to overcome potential distraction.

5.5 Main Conclusion

These findings suggest that the state of chronic hyperarousal and re-experiencing of traumatic events in PTSD effectively keeps veterans with PTSD-mTBI at ceiling, where global hyperactivity may effectively limit the number of different states of activation, therefore resulting in reduced local activity and variability in response to behavioral tasks. The re-experiencing phenomena and affective sequelae in combat-related PTSD-mTBI may result from brain networks becoming “stuck” in configurations that reflect memories, emotions, and thoughts that originate from the traumatizing experience(s). This theory provides neurophysiological evidence that PTSD-mTBI is a disorder of fear learning and fear

conditioning, whereby the re-experiencing of traumatic events arises from frequent reactivation of fear circuits.

Furthermore, our findings suggest that the chosen experimental tasks induce functional correlates of a variety of clinical symptoms, cognitive deficits, and measures of affective dysregulation. These relationships are diverse enough such that it may be imperative to examine individual differences in this population and create individualized treatment plans from this information. Most notably however, is that verbal working memory, impulsivity, and DKEFS-interference were most consistently associated with

network activity. Only during the combined condition executive function and affective processing did we see associations with PTSD symptoms related to coping mechanisms (avoidance and numbing). This could be because this task is closest to real-world situations where the processes often compete, and may indicate that this is when this population is most vulnerable and where the neural circuits get over-exerted and attend to and process non-threatening stimuli as if it were threatening.

In conclusion, our findings suggest that clinical symptoms and neurocognitive deficits are associated with relatively broad changes in functional activation throughout the brain and that these changes are associated with cortico-limbic, and possibly default mode, salience and central executive networks. Furthermore, individual symptom domains are associated with changes in functional activity within these networks and that the patterns of these associations differ between individual symptom domains. These findings contribute to growing evidence that PTSD and mTBI are network-level disorders that affect multiple aspects of neural information processing, dynamics, and communication. By

continuing to explore specific features including functional connectivity, it should become possible to further articulate the mechanisms underlying these disorders. Moreover, insight about neural information processing and communication dynamics gained from clinical populations may ultimately help further appreciate their importance in the context of healthy brain function.

5.6 Future Directions and Implications

Our research indicates that different PTSD-mTBI symptom profiles may have different neural signatures and that characterizing intrinsic connectivity networks is a logical best next step. An eventual

be most appropriate for individual patients. Another important direction would be to determine the origin of functional abnormalities; that is, do they represent familial risk factors for developing PTSD-mTBI or are they acquired signs that occur after PTSD’s and mTBI’s appearance? If amygdala hyper-responsivity, for example, is found to be a familial trait that increases risk for developing PTSD, then hyper-

responsivity in the amygdala could be used to screen those likely to experience trauma, such as military and police officer recruits. However, if amygdala hyper-responsivity is found to be an acquired

characteristic of PTSD, it could become the target of treatments and a potential biologic marker of symptomatic improvement. The field is, in general, searching for biological markers in anxiety and mood disorders, and the amygdala and mPFC have simply been logical places to start. In addition, even if such biological markers for PTSD-mTBI are found, they may be less effective than other clinical data that are obtained more easily and cost-effectively. Continued research is needed to better understand the roles of the brain regions and connectivity patterns involved in the neurocircuitry of PTSD-mTBI and to clarify the origin and potential clinical implications of the regions’ and networks’ functional abnormalities.

Methods such as DTI and resting-state and task-based functional connectivity analyses are critical for further understanding the neural profiles of co-morbid PTSD and mTBI. It is possible that these differential patterns of task-based activity are related to significant group connectivity differences that are modulated by symptom severity and cognitive and affective conditions. For example, Daniels and colleagues (2010) and Lanius et al (2015) showed that during a working memory task, a PTSD group had stronger connectivity with areas implicated in the DMN (specifically, enhanced connectivity between the medial prefrontal cortex and the left parahippocampal gyrus) while controls showed significantly stronger connectivity within areas implicated in the CEN, including the right inferior frontal gyrus and the right inferior parietal lobule [286] [287]. Decreased resting-state connectivity within the CEN has also been found between PTSD participants and trauma-exposed controls during an emotional face-viewing paradigm, with decreased connectivity between frontoparietal regions within a CEN component associated with trauma history and with PTSD symptoms [288]. Additionally, positive correlations

between frequency of dissociative experiences and DMN connectivity with the dorsolateral prefrontal cortex [289] have also been reported. These positive correlations suggest that dissociative experiences may involve alterations in the relationship between the DMN and CEN, which may relate to difficulties switching between DMN and CEN. Therefore, we could propose to take a network level approach using different methods but similar neuroimaging task paradigms to gain a different perspective on the brain- behavior associations in this population.

In addition to CEN abnormalities in PTSD, studies have demonstrated connectivity alterations among brain areas related to the SN, such as between the anterior insula and other SN regions, including the amygdala [288][88][108][175]. These studies suggest that altered connectivity within the SN may result in a change in threat-sensitivity circuits, contributing to the hypervigilance and hyperarousal symptoms in PTSD. Therefore, we could propose to examine how these symptoms relate specifically to SN connectivity. Finally, evidence is emerging that altered resting-state connectivity between key regions of the DMN and regions associated with the SN, including the amygdala and anterior insula, may be a prognostic indicator of PTSD symptomatology [290][229]. All in all, these findings highlight promising directions using the approach of answering further research questions by examining major intrinsic networks’ connectivity based on the findings of our region-based activation analyses.

The significance of examining neural correlates of comorbid PTSD-mTBI lies in the potential that the scientific and medical community would be able to better identify measureable characteristics that reflect the presence of a disease state, ie biomarkers. Isolating biomarkers can potentially provide insight into the following: (i) risk, (ii), diagnosis/trait (iii) state or acuity, (iv) stage, (v) treatment response and (vi) prognosis of clinical diagnoses, all of which can aid in the improvement upon and development of treatments [292]. Additionally, understanding these mechanisms may help clinicians to prevent the long- term biological consequences of exposure to both mental and physical stress, which may be primary precursors to the development and diagnosis of not only PTSD and mTBI, but also many other neuropsychiatric disorders. Another important direction for research would be to use biomarkers to

predict treatment response in PTSD-mTBI. Therefore, identifying the underlying mechanisms of symptoms and cognitive deficits may improve medical treatment for PTSD-mTBI and PTSD and mTBI separately, and help to elucidate the etiology of the disorders.

Our findings highlighted individual differences, and were a novel finding in these studies. Future investigation into these regions as networks may help elucidate the underlying neurobiology. To do this, we could employ tasks that specifically target symptoms and perhaps more interestingly, we could attempt to measure whether neurocognitive deficits predict clinical symptom severity through the use of computational modeling and machine learning. Such a study could be carried out using only behavioral and clinical data, however an analysis that attempts to use resting state connectivity and/or functional activity during for example symptom provocation along with behavioral data and clinical data would ultimately allow us to explore the relationship between clinical symptoms, sensory neurocognitive deficits, and connectivity and activity in intrinsic networks.

Ultimately, many of the symptoms and neurocognitive deficits associated with PTSD-mTBI are shared by other psychiatric disorders. Therefore, determining whether the neural correlates of these symptoms are shared between disorders would ultimately be an important step in understanding the biological features of psychiatric illness.

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