Decision Making: Remembering to choose the future

A brain region known as the hippocampus is required when people assess different options before making a value-based choice.
  1. Lesley K Fellows  Is a corresponding author
  1. McGill University, Canada

From the philosophers of ancient Greece to the self-help books of today, humans have long been interested in choice. Philosophers and ethicists have debated what goals we ought to choose for millennia, and for a century or more economists and psychologists have studied what goals we will choose. However, neuroscience has only recently begun to systematically address how we choose.

Whether we are pondering life-defining decisions about love, career or commitment to a cause, or simply picking which snacks to buy in the grocery store, it is still unclear what regions of the brain are involved in making choices, and what information those regions encode. In everyday language, we often talk about ‘value’ (or in economic terms, ‘utility’) as the driver of such decisions: we consider our options, and select the one with the highest value. Hundreds of functional MRI (or fMRI) studies in healthy humans have identified a consistent set of brain regions which seem to process signals associated with subjective values; this suggests that value is indeed a concept that has biological roots (Bartra et al., 2013). However, the nature of the information that contributes to the neural signals related to value remains a matter of debate (O'Doherty, 2014). In other words, it is not clear what we think about when we think about value.

In fact, scientists know far less about choices based on value than they do about perceptual decisions (such as assessing if a noisy array of moving dots is trending more to the left or to the right; Shadlen and Kiani, 2013). During perceptual choices, external information is repeatedly sampled and the neural representation of this evidence accumulates until a threshold is crossed and a decision is triggered. These tasks are associated with well-known behavioral phenomena – for instance, choices with less perceptual evidence take longer to resolve – which are captured by drift diffusion models (Ratcliff and McKoon, 2008).

It has been proposed that value-based decisions might occur in a similar way (Rangel et al., 2008). However, while it is obvious what knowledge is accumulating as a person gazes at a screen filled with moving dots, it is less clear what information might be sampled to support a decision based on value. Now, in eLife, Akram Bakkour of Columbia University and colleagues report that, at least in part, we may be thinking about past experiences (Bakkour et al., 2019).

Their work makes a strong case that value-based deliberation engages the hippocampus, a small structure within the brain that is involved in long-term memory. Although past experiences are a likely source of relevant information in value-based decisions, to date researchers have focused mostly on other regions of the brain such as the ventral prefrontal cortex and the striatum.

Bakkour et al. – who are based at Columbia and the Memory Disorders Research Center – first used fMRI to establish that activity in the hippocampus is greater for longer deliberations during value-based choice. They then harnessed the power of a lesion experiment to infer that the structure is necessary for such choices (Vaidya et al., 2019). Patients with hippocampal damage were slower to make decisions, and somewhat more variable in what they chose. These hippocampal effects were specific to value-based decisions. Deliberation time in a classic perceptual decision task did not relate to hippocampal signal, nor was it influenced by hippocampal damage. While perceptual decisions involve sampling external evidence, Bakkour et al. propose that deliberation during value-based choice requires sampling internal evidence. This includes – although is presumably not limited to – using the hippocampus to conjure up past experiences with similar options. Ultimately, these results will help to broaden the anatomical scope of decision neuroscience.

Studies have already shown that ‘attention’, while intuitive and attractive as a holistic concept, is in fact composed of dozens of distinct processes with definable characteristics that rely on different neural circuits. It is likely that ‘value’ will also require further decomposition. Armed with this knowledge, it may become possible to better understand how the brain carries out the important value-based decisions that define us as individuals and shape the directions of our societies.

References

Article and author information

Author details

  1. Lesley K Fellows

    Lesley K Fellows is in the Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada

    For correspondence
    lesley.fellows@mcgill.ca
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9144-092X

Publication history

  1. Version of Record published: August 14, 2019 (version 1)

Copyright

© 2019, Fellows

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,730
    Page views
  • 148
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Lesley K Fellows
(2019)
Decision Making: Remembering to choose the future
eLife 8:e49828.
https://doi.org/10.7554/eLife.49828
  1. Further reading

Further reading

    1. Neuroscience
    Sven Dorkenwald, Nicholas L Turner ... H Sebastian Seung
    Research Article Updated

    Learning from experience depends at least in part on changes in neuronal connections. We present the largest map of connectivity to date between cortical neurons of a defined type (layer 2/3 [L2/3] pyramidal cells in mouse primary visual cortex), which was enabled by automated analysis of serial section electron microscopy images with improved handling of image defects (250 × 140 × 90 μm3 volume). We used the map to identify constraints on the learning algorithms employed by the cortex. Previous cortical studies modeled a continuum of synapse sizes by a log-normal distribution. A continuum is consistent with most neural network models of learning, in which synaptic strength is a continuously graded analog variable. Here, we show that synapse size, when restricted to synapses between L2/3 pyramidal cells, is well modeled by the sum of a binary variable and an analog variable drawn from a log-normal distribution. Two synapses sharing the same presynaptic and postsynaptic cells are known to be correlated in size. We show that the binary variables of the two synapses are highly correlated, while the analog variables are not. Binary variation could be the outcome of a Hebbian or other synaptic plasticity rule depending on activity signals that are relatively uniform across neuronal arbors, while analog variation may be dominated by other influences such as spontaneous dynamical fluctuations. We discuss the implications for the longstanding hypothesis that activity-dependent plasticity switches synapses between bistable states.

    1. Biochemistry and Chemical Biology
    2. Neuroscience
    Jinli Geng, Yingjun Tang ... Xiaodong Liu
    Research Article Updated

    Dynamic Ca2+ signals reflect acute changes in membrane excitability, and also mediate signaling cascades in chronic processes. In both cases, chronic Ca2+ imaging is often desired, but challenged by the cytotoxicity intrinsic to calmodulin (CaM)-based GCaMP, a series of genetically-encoded Ca2+ indicators that have been widely applied. Here, we demonstrate the performance of GCaMP-X in chronic Ca2+ imaging of cortical neurons, where GCaMP-X by design is to eliminate the unwanted interactions between the conventional GCaMP and endogenous (apo)CaM-binding proteins. By expressing in adult mice at high levels over an extended time frame, GCaMP-X showed less damage and improved performance in two-photon imaging of sensory (whisker-deflection) responses or spontaneous Ca2+ fluctuations, in comparison with GCaMP. Chronic Ca2+ imaging of one month or longer was conducted for cultured cortical neurons expressing GCaMP-X, unveiling that spontaneous/local Ca2+ transients progressively developed into autonomous/global Ca2+ oscillations. Along with the morphological indices of neurite length and soma size, the major metrics of oscillatory Ca2+, including rate, amplitude and synchrony were also examined. Dysregulations of both neuritogenesis and Ca2+ oscillations became discernible around 2–3 weeks after virus injection or drug induction to express GCaMP in newborn or mature neurons, which were exacerbated by stronger or prolonged expression of GCaMP. In contrast, neurons expressing GCaMP-X were significantly less damaged or perturbed, altogether highlighting the unique importance of oscillatory Ca2+ to neural development and neuronal health. In summary, GCaMP-X provides a viable solution for Ca2+ imaging applications involving long-time and/or high-level expression of Ca2+ probes.