Graduate Thesis Or Dissertation


Does thinking about the past reduce temporal discounting? An investigation into the effects of episodic thought on intertemporal choice Public Deposited

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  • Humans show a preference for present rewards over delayed rewards, a phenomenon known as temporal discounting (TD). TD, of perennial interest because of its violation of rational economic theory, is associated with poor outcomes such as drug addiction and perhaps even global warming. Recent research has shown that episodic future thinking can reduce temporal discounting, possibly by modulating subjective valuation processes through imagery-based operations supported by the medial temporal lobe and connecting structures. Interestingly, a growing body of additional research suggests that episodic memory and episodic future thought share similar cognitive processes and neural mechanisms. Given these findings, an immediate question is whether episodic memory can also reduce temporal discounting. To investigate this question, we created a behavioral paradigm whereby participants performed intertemporal choice trials, but each trial was primed by either a brief period of episodic past thought, episodic future thought, or a non-episodic imagery control condition. In line with previous findings, participants discounted future rewards compared to present rewards and showed wide inter-individual variability in their discounting rates. However, when comparing discounting rates between the three conditions, results revealed that episodic memory reduced TD more than episodic future thought and the imagery control condition. In contrast, no differences in TD were observed between the episodic future thought condition and the control condition. Given that the episodic past thought condition was associated with higher self-reported imagery than the episodic future thought condition, these findings suggest that basic episodic imagery processes might play an important role in modulating intertemporal decision-making.
Date Issued
  • 2011
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Last Modified
  • 2019-11-18
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