According to Kalisch et al. resilience should be considered a dimensional and quantifiable outcome; that is, sustained or improved mental health following stress and adversity, where stress is conceptualized in the broadest sense, as an aversive emotional response. Importantly, the authors emphasize the distinction between resilience factors and mechanisms, the latter being of prime interest given that these describe the general processes through which resilience can be achieved. Resilience mechanisms exert their influence by actively limiting aversion in order to adaptively achieve long-term functioning. According to their theory, the main resilience mechanism is positive (re)appraisal, which is supported by inhibition of negative appraisals under severe stress. Overall, we welcome the authors' well-informed effort to bring together research on emotion regulation, stress, conditioning, and extinction to understand resilience. In the following, we will first address a potential general problem of the theory. Second, we will suggest a way to investigate resilience mechanisms by focusing on the temporal dynamics of physiological recovery from stress and adversity.
Let us start with the potential problem. The theory of Kalisch et al. is rather ambitious – or, as the authors themselves state, radical. They suggest that there is a single, general resilience mechanism that serves as a common final path of all resilience factors, namely positive (re)appraisal. The appeal of such an approach is that it seems to explain much, from psychological phenomena down to intricate animal research on extinction. Imagine, however, if we found out that resilience can be explained only by reduced sensitivity – a short perturbation within a negative appraisal system, with fast recovery to normal.. In our understanding, this would not by itself necessitate a positive appraisal style. Kalisch et al. probably would argue that this form of resilience is supported by the first claim of their theory (i.e., positive appraisal), as the threat is appraised (in the long run) “non-negatively.” Defining positive appraisal as everything that is not appraised negatively, however, blurs the important distinction between positive and negative valuation that is realized by distinct brain circuits (Schardt et al. Reference Schardt, Erk, Nüsser, Nöthen, Cichon, Rietschel, Treutlein, Goschke and Walter2010; Staudinger et al. Reference Staudinger, Erk, Abler and Walter2009; Reference Staudinger, Erk and Walter2011) and also neglects the relevance of the time domain. We therefore think that the theory Kalisch et al. propose might rely too heavily on a specific interpretation of the psychological term appraisal and, as a consequence, the theory is difficult to define and to operationalize unambiguously from a neurobiological perspective.
Although we agree that it is necessary to unite psychological theories of resilience mechanisms with neurobiology, we think that it might be helpful to approach resilience in a more reductionist and physiological fashion: Once stress response is defined in physiological terms, we can monitor its signatures (e.g., heart rate and blood pressure increase, cortisol levels, amygdala activation, etc.) and investigate the neural processes by which an organism manages to recover from those changes. Such neural recovery processes can be considered (proxies of) resilience mechanisms in themselves. As such, they do not necessarily have to rely on a general ability, but could instead be domain specific as well; that is, sometimes relying on decreased sensitivity for aversion, sometimes on positive (counter)appraisal, and sometimes on inhibition of negative aversion. A focus on physiological changes and their recovery has several advantages: First, it is neutral on whether resilience is achieved by conscious/effortful or unconscious/automatic processes. Second, it can easily be quantified by measuring changes in physiological parameters.
The second point we want to make is closely related to the aforementioned argument and pertains to the relevance of temporal dynamics of resilience mechanisms on different time scales. A crucial element in resilience is the ability of an organism to achieve stability through change, a process known as allostasis (McEwen & Wingfield Reference McEwen and Wingfield2003) – in our case, to regain homeostasis after a stressful event. Importantly, allostasis can relate to both rapid (e.g., autonomic) and slower (e.g., cognitive) adaptations to a stressor, associated with specific neural markers; these processes, at the same time, all have a specific time course in their own respect. In other words, recovery (or lack thereof) is inherently a temporal phenomenon: (Neuro)physiological parameters of the stress response (reflecting a system state) may recover, may show sensitization, may be perturbed in the long range, or may even show aftereffects long after the acute stressor is gone. For example, it has been shown that the success of effortful emotion regulation in humans can be measured by a reduction of the amygdala signal (Erk et al. Reference Erk, Mikschl, Stier, Ciaramidaro, Gapp, Weber and Walter2010b; Lamke et al. Reference Lamke, Daniels, Dörfel, Gaebler, Abdel-Rahman, Hummel, Erk and Walter2014; Walter et al. Reference Walter, Kalckreuth, Schardt, Stephan, Goschke and Erk2009), and that the dynamics of recovery of the amygdala signal are predictive of later amygdala responses to aversive stimulation (Walter et al. Reference Walter, Kalckreuth, Schardt, Stephan, Goschke and Erk2009). Circuits known to be involved in automatic as well as volitional emotion regulation (e.g., functional connectivity between the prefrontal cortex and amygdala) are affected by stressful situations, and changes within these circuits could be observed even long after the stress has waned (Veer et al. Reference Veer, Oei, Spinhoven, van Buchem, Elzinga and Rombouts2011). Moreover, aftereffects of aversive emotional responses could even be demonstrated a year after effortful emotion regulation (Erk et al. Reference Erk, Kalckreuth and Walter2010a).
We therefore suggest that one way to foster resilience research might be to focus on the temporal dynamics of changes in those brain circuits on different time scales, and on the mechanisms that are involved in the recovery of brain responses to stressful situations. We hypothesize that the ability to recover from perturbations and the temporal pattern of recovery could serve as an index or biomarker that will be predictive of resilience in the long run. The mechanisms that contribute to such recovery might be diverse, or they might indeed be of a more general nature, the latter being in keeping with the theory of Kalisch et al. In this sense, our proposed research strategy might be a natural extension of the generalized theory of resilience as proposed by Kalisch et al., but might also be of interest to other theoretical accounts of resilience.
According to Kalisch et al. resilience should be considered a dimensional and quantifiable outcome; that is, sustained or improved mental health following stress and adversity, where stress is conceptualized in the broadest sense, as an aversive emotional response. Importantly, the authors emphasize the distinction between resilience factors and mechanisms, the latter being of prime interest given that these describe the general processes through which resilience can be achieved. Resilience mechanisms exert their influence by actively limiting aversion in order to adaptively achieve long-term functioning. According to their theory, the main resilience mechanism is positive (re)appraisal, which is supported by inhibition of negative appraisals under severe stress. Overall, we welcome the authors' well-informed effort to bring together research on emotion regulation, stress, conditioning, and extinction to understand resilience. In the following, we will first address a potential general problem of the theory. Second, we will suggest a way to investigate resilience mechanisms by focusing on the temporal dynamics of physiological recovery from stress and adversity.
Let us start with the potential problem. The theory of Kalisch et al. is rather ambitious – or, as the authors themselves state, radical. They suggest that there is a single, general resilience mechanism that serves as a common final path of all resilience factors, namely positive (re)appraisal. The appeal of such an approach is that it seems to explain much, from psychological phenomena down to intricate animal research on extinction. Imagine, however, if we found out that resilience can be explained only by reduced sensitivity – a short perturbation within a negative appraisal system, with fast recovery to normal.. In our understanding, this would not by itself necessitate a positive appraisal style. Kalisch et al. probably would argue that this form of resilience is supported by the first claim of their theory (i.e., positive appraisal), as the threat is appraised (in the long run) “non-negatively.” Defining positive appraisal as everything that is not appraised negatively, however, blurs the important distinction between positive and negative valuation that is realized by distinct brain circuits (Schardt et al. Reference Schardt, Erk, Nüsser, Nöthen, Cichon, Rietschel, Treutlein, Goschke and Walter2010; Staudinger et al. Reference Staudinger, Erk, Abler and Walter2009; Reference Staudinger, Erk and Walter2011) and also neglects the relevance of the time domain. We therefore think that the theory Kalisch et al. propose might rely too heavily on a specific interpretation of the psychological term appraisal and, as a consequence, the theory is difficult to define and to operationalize unambiguously from a neurobiological perspective.
Although we agree that it is necessary to unite psychological theories of resilience mechanisms with neurobiology, we think that it might be helpful to approach resilience in a more reductionist and physiological fashion: Once stress response is defined in physiological terms, we can monitor its signatures (e.g., heart rate and blood pressure increase, cortisol levels, amygdala activation, etc.) and investigate the neural processes by which an organism manages to recover from those changes. Such neural recovery processes can be considered (proxies of) resilience mechanisms in themselves. As such, they do not necessarily have to rely on a general ability, but could instead be domain specific as well; that is, sometimes relying on decreased sensitivity for aversion, sometimes on positive (counter)appraisal, and sometimes on inhibition of negative aversion. A focus on physiological changes and their recovery has several advantages: First, it is neutral on whether resilience is achieved by conscious/effortful or unconscious/automatic processes. Second, it can easily be quantified by measuring changes in physiological parameters.
The second point we want to make is closely related to the aforementioned argument and pertains to the relevance of temporal dynamics of resilience mechanisms on different time scales. A crucial element in resilience is the ability of an organism to achieve stability through change, a process known as allostasis (McEwen & Wingfield Reference McEwen and Wingfield2003) – in our case, to regain homeostasis after a stressful event. Importantly, allostasis can relate to both rapid (e.g., autonomic) and slower (e.g., cognitive) adaptations to a stressor, associated with specific neural markers; these processes, at the same time, all have a specific time course in their own respect. In other words, recovery (or lack thereof) is inherently a temporal phenomenon: (Neuro)physiological parameters of the stress response (reflecting a system state) may recover, may show sensitization, may be perturbed in the long range, or may even show aftereffects long after the acute stressor is gone. For example, it has been shown that the success of effortful emotion regulation in humans can be measured by a reduction of the amygdala signal (Erk et al. Reference Erk, Mikschl, Stier, Ciaramidaro, Gapp, Weber and Walter2010b; Lamke et al. Reference Lamke, Daniels, Dörfel, Gaebler, Abdel-Rahman, Hummel, Erk and Walter2014; Walter et al. Reference Walter, Kalckreuth, Schardt, Stephan, Goschke and Erk2009), and that the dynamics of recovery of the amygdala signal are predictive of later amygdala responses to aversive stimulation (Walter et al. Reference Walter, Kalckreuth, Schardt, Stephan, Goschke and Erk2009). Circuits known to be involved in automatic as well as volitional emotion regulation (e.g., functional connectivity between the prefrontal cortex and amygdala) are affected by stressful situations, and changes within these circuits could be observed even long after the stress has waned (Veer et al. Reference Veer, Oei, Spinhoven, van Buchem, Elzinga and Rombouts2011). Moreover, aftereffects of aversive emotional responses could even be demonstrated a year after effortful emotion regulation (Erk et al. Reference Erk, Kalckreuth and Walter2010a).
We therefore suggest that one way to foster resilience research might be to focus on the temporal dynamics of changes in those brain circuits on different time scales, and on the mechanisms that are involved in the recovery of brain responses to stressful situations. We hypothesize that the ability to recover from perturbations and the temporal pattern of recovery could serve as an index or biomarker that will be predictive of resilience in the long run. The mechanisms that contribute to such recovery might be diverse, or they might indeed be of a more general nature, the latter being in keeping with the theory of Kalisch et al. In this sense, our proposed research strategy might be a natural extension of the generalized theory of resilience as proposed by Kalisch et al., but might also be of interest to other theoretical accounts of resilience.