Representation of Accumulating Evidence for a Decision in Two Parietal Areas

Lafuente, Víctor de; Jazayeri, Mehrdad; Shadlen, Michael N.

doi:10.1523/jneurosci.2451-14.2015

Cited by 167 publications

(180 citation statements)

References 72 publications

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“…The ensuing pattern of firing reflects a saltatory or stepwise evidence accumulation in which expectations about occupying the chosen and unchosen states diverge as the trial progresses. This belief updating is formally identical to evidence accumulation described by drift diffusion or race-to-bound models (Solway & Botvinick, 2012;Zhang & Maloney, 2012;de Lafuente et al, 2015;Kira et al, 2015) and nicely recapitulates the emergence of a choice as evaluation of options proceeds (Hunt et al, 2012). Furthermore, the separation of timescales implicit in variational updating reproduces the stepping dynamics seen in parietal responses during decision making (Latimer et al, 2015).…”

Section: Electrophysiological Correlates Of Variational Belief Updatingsupporting

confidence: 52%

“…These include repetition suppression (de Gardelle, Waszczuk, Egner, & Summerfield, 2013), violation and omission responses (Bendixen, SanMiguel, & Schroger, 2012), and neuronal responses that are characteristic of the hippocampus, namely, place cell activity (Moser, Rowland, & Moser, 2015), theta-gamma coupling, theta sequences and phase precession (Burgess, Barry, & O'Keefe, 2007;Lisman & Redish, 2009). We also touch on dynamics seen in parietal and prefrontal cortex, such as evidence accumulation and race-to-bound or threshold (Huk & Shadlen, 2005, Gold & Shadlen, 2007Hunt et al, 2012;Solway & Botvinick, 2012;de Lafuente, Jazayeri, & Shadlen, 2015;FitzGerald, Moran, Friston, & Dolan, 2015;Latimer, Yates, Meister, Huk, & Pillow, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Active Inference: A Process Theory

et al. 2017

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This is the published version of the paper.This version of the publication may differ from the final published version. behavior prescribed by these dynamics has a degree of face validity, providing a formal explanation for reward seeking, context learning, and epistemic foraging. Technically, the fact that a gradient descent appears to be a valid description of neuronal activity means that variational free energy is a Lyapunov function for neuronal dynamics, which therefore conform to Hamilton's principle of least action. Permanent repository link

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Section: Electrophysiological Correlates Of Variational Belief Updatingsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Active Inference: A Process Theory

et al. 2017

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“…These expectations have been confirmed in a simple but well-controlled perceptual task that by now has become the classical model of decision-making: the saccadic decisions made by appropriately trained monkeys (e.g. Palmer et al, 2005;Shadlen and Kiani, 2013;Kiani et al, 2014;de Lafuente et al, 2015). In these forced-choice tasks (Fig.…”

Section: Introductionmentioning

confidence: 67%

Archerfish fast-start decisions can take an additional variable into account

Reinel

Schuster

2016

Journal of Experimental Biology

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The analysis of saccadic decision-making tasks with two or four alternatives has shown what appears to be a general hallmark of decision-making: adding more alternatives decreases speed and accuracy. In their everyday lives, however, animals often select among many more than two options and under heavy constraints on speed and accuracy. Here we analyse a rapid decision made by hunting archerfish. As in the classical saccadic tasks, the fish must first estimate sensory information: based on an estimate of horizontal speed, azimuthal direction and initial height of falling prey, the fish must quickly select a suitable fast-start to arrive at the right place at the right time. Our results suggest that the fast-start decisions of archerfish are surprisingly robust with respect to adding a further decision-relevant variable. We show that the fish can appropriately account for vertical speed as an independent further variable -but the need to do so does not affect speed or accuracy of the decisions. Our findings suggest novel ways by which rapid and yet complex decisions could be balanced against increasing complexity.

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“…We first established the presence of firing-rate encoding of choice and the temporal structure of the neuronal activity in the PPC (11,32,35) before testing whether and how decision coding varies with the temporal structure of neuronal activity.…”

Section: Resultsmentioning

confidence: 99%

“…Firing rates of neurons in the PPC encode movement intention and the temporal evolution of movement choices (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13) as well as decision variables such as expected rewards, the subjective desirability during reward-guided decisions (14)(15)(16)(17)(18), and the certainty in perceptual decisions (19). Decisions are made within a network that extends across many regions of the brain (20)(21)(22)(23)(24)(25), so efficient and flexible mechanisms are required to enable distributed computations.…”

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confidence: 99%

Temporal coding of reward-guided choice in the posterior parietal cortex

Hawellek

Wong

Pesaran

2016

Proc. Natl. Acad. Sci. U.S.A.

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Making a decision involves computations across distributed cortical and subcortical networks. How such distributed processing is performed remains unclear. We test how the encoding of choice in a key decision-making node, the posterior parietal cortex (PPC), depends on the temporal structure of the surrounding population activity. We recorded spiking and local field potential (LFP) activity in the PPC while two rhesus macaques performed a decision-making task. We quantified the mutual information that neurons carried about an upcoming choice and its dependence on LFP activity. The spiking of PPC neurons was correlated with LFP phases at three distinct time scales in the theta, beta, and gamma frequency bands. Importantly, activity at these time scales encoded upcoming decisions differently. Choice information contained in neural firing varied with the phase of beta and gamma activity. For gamma activity, maximum choice information occurred at the same phase as the maximum spike count. However, for beta activity, choice information and spike count were greatest at different phases. In contrast, theta activity did not modulate the encoding properties of PPC units directly but was correlated with beta and gamma activity through cross-frequency coupling. We propose that the relative timing of local spiking and choice information reveals temporal reference frames for computations in either local or large-scale decision networks. Differences between the timing of task information and activity patterns may be a general signature of distributed processing across large-scale networks.decision making | phase-of-firing | neural code | saccade | reach T he posterior parietal cortex (PPC) integrates sensory signals for impending actions. Firing rates of neurons in the PPC encode movement intention and the temporal evolution of movement choices (1-13) as well as decision variables such as expected rewards, the subjective desirability during reward-guided decisions (14-18), and the certainty in perceptual decisions (19). Decisions are made within a network that extends across many regions of the brain (20-25), so efficient and flexible mechanisms are required to enable distributed computations. Dynamic and frequency-specific correlations in activity between brain areas are ubiquitous and offer potential physiological mechanisms supporting distributed computations in decision networks (13,21,(26)(27)(28)(29)(30)(31)(32)(33)(34). We hypothesize that the encoding of decisions in the PPC should depend on the temporal structure present in neuronal activity. Previous studies have shown that coherently active ensembles of cells in the PPC predict reaction times (9) and movement choices (13, 21) better than neurons without coherent dynamics. However, whether and how the coding of decisions depends on the temporally structured firing of PPC neurons remains unknown. We examined temporal structure in the encoding of look-reach decisions by PPC neurons. ResultsWe analyzed the activity of 149 units [97 units (31 single units and 66 multiun...

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Representation of Accumulating Evidence for a Decision in Two Parietal Areas

Cited by 167 publications

References 72 publications

Active Inference: A Process Theory

Active Inference: A Process Theory

Archerfish fast-start decisions can take an additional variable into account

Temporal coding of reward-guided choice in the posterior parietal cortex

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