Daniel Nettle, writes an article in Journal Of Theoretical Biology about the evolution of low mood states. Before I get to his central thesis, let us review what he reviews:
Low mood describes a temporary emotional and physiological state in humans, typically characterised by fatigue, loss of motivation and interest, anhedonia (loss of pleasure in previously pleasurable activities), pessimism about future actions, locomotor retardation, and other symptoms such as crying.
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This paper focuses on a central triad of symptoms which are common across many types of low mood, namely anhedonia, fatigue and pessimism. Theorists have argued that, whereas their opposites facilitate novel and risky behavioural projects. These symptoms function to reduce risk-taking. They do this, proximately, by making the potential payoffs seem insufficiently rewarding (anhedonia), the energy required seem too great (fatigue), or the probability of success seem insufficiently high (pessimism). An evolutionary hypothesis for why low mood has these features, then, is that is adaptive to avoid risky behaviours when one is in a relatively poor current state, since one would not be able to bear the costs of unsuccessful risky endeavors at such times .
I would like to pause here and note how he has beautifully summed up the low mood symptoms and key features; taking liberty to define using my own framework of Value X Expectancy and distinction between cognitive(‘wanting’) and behavioral (‘liking’) side of things :
- Anhedonia: behavioral inability to feel rewarded by previously pleasurable activities. Loss of ‘liking’ following the act. Less behavioral Value assigned.
- Loss of motivation and interest: cognitive inability to look forward to or value previously desired activities. Loss of ‘wanting’ prior to the act. Less cognitive Value assigned.
- Fatigue: behavioral inability to feel that one can achieve the desired outcome due to feelings that one does not have sufficient energy to carry the act to success. Less behavioral Expectancy assigned.
- Pessimism: cognitive inability to look forward to or expect good things about the future or that good outcomes are possible. Less cognitive Expectancy assigned.
The reverse conglomeration is found in high mood- High wanting and liking, high energy and outlook. Thus, I agree with Nettle fully that low mood and high mood are defined by these opposed features and also that these features of low and high mood are powerful proximate mechanisms that determine the risk proneness of the individual: by subjectively manipulating the Value and Expectancy associated with an outcome, the high and low mood mediate the risk proneness that an organism would display while assigning a utility to the action. Thus, it is fairly settled: if ultimate goal is to increase risk-prone behavior than the organism should use the proximate mechanism of high mood; if the ultimate goal is to avoid risky behavior, then the organism should display low mood which would proximately help it avoid risky behavior.
Now let me talk about Nettle’s central thesis. It has been previously proposed in literature that low mood (and thus risk-aversion) is due to being in a poor state wherein one can avoid energy expenditure (and thus worsening of situation) by assuming a low profile. Nettle plays the devil’s advocate and argues that an exactly opposite argument can be made that the organism in a poor state needs to indulge in high risk (and high energy) activities to get out of the poor state. Thus, there is no a prior reason as to why one explanation may be more sound than the other. To find out when exactly high risk behavior pay off and when exactly low risk behaviors are more optimal, he develops a model and uses some elementary mathematics to derive some conclusions. He, of course , bases his model on a Preventive focus, whereby the organism tries to minimize getting in a state R , which is sub-threshold. He allows the S(t) to be maximized under the constraint that one does not lose sight of R. I’ll not go into the mathematics, but the results are simple. When there is a lot of difference between R (dreaded state) and S (current state), then the organism adopts a risky behavioral profile. when the R and S are close, he maintains low risk behavior, however when he is in dire circumstances (R and S are very close) then risk proneness again rises to dramatic levels. To quote:
The model predicts that individuals in a good state will be prepared to take relatively large risks, but as their state deteriorates, the maximum riskiness of behaviour that they will choose declines until they become highly risk-averse. However, when their state becomes dire, there is a predicted abrupt shift towards being totally risk-prone. The switch to risk-proneness at the dire end of the state continuum is akin to that found near the point of starvation in the original optimal foraging model from which the current one is derived (Stephens, 1981). The graded shift towards greater preferred risk with improving state is novel to this model, and stems from the stipulation that if the probability of falling into the danger zone in the next time step is minimal, then the potential gain in S at the next time step should be maximised. However, a somewhat similar pattern of risk proneness in a very poor state, risk aversion in an intermediate state, and some risk proneness in a better state, is seen in an optimal-foraging model where the organism has not just to avoid the threshold of starvation, but also to try to attain the threshold of reproduction (McNamara et al., 1991). Thus, the qualitative pattern of results may emerge quite generally from models using different assumptions.
Nettle, then extrapolates the clinical significance from this by proposing that ‘agitated’ / ‘excited’ depression can be explained as when the organism is in dire straits and has thus become risk-prone. He also uses a similar logic for dysphoric mania although I don’t buy that. However, I agree that euphoric mania may just be the other extreme of high mood and more risk proneness and goal achievements; while depression the normal extreme of low mood and adverse circumstances and risk aversion. To me this model ties up certain things we know about life circumstances and the risk profile and mood tone of people and contributes to deepening our understanding. 
Nettle, D. (2009). An evolutionary model of low mood states Journal of Theoretical Biology, 257 (1), 100-103 DOI: 10.1016/j.jtbi.2008.10.033
The problem is that shrinks want to classify every human conditions giving it clear symptoms to diagnose them (or a percentage of possibility for that symptoms); but indeed there is the full spectrum of possibilities for human conditions and their surroundings.
“Happiness doesn’t resit mental reflection”