Foraging behavior in visual search: A review of theoretical and mathematical models in humans and animals

Bella-Fernández, Marcos; Suñé, Manuel Suero; Liaño, Beatriz Gil-Gómez de

doi:10.1007/s00426-021-01499-1

Cited by 12 publications

(13 citation statements)

References 203 publications

(290 reference statements)

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“…This inference was necessary because the colors representing the gain and loss stimuli overlapped, making it impossible for observers to determine with certainty whether a particular stimulus was a gain or loss stimulus. The inference process involved various forms of learning, including associative learning (Blaser et al, 2004; Cheng & Spetch, 2001), reinforcement learning (Constantino & Daw, 2015; Kolling & Akam, 2017), and Bayesian updating (Bella-Fernández et al, 2022; Oaten, 1977). Specifically, in this particular case, Bayesian updating could contribute to suboptimal adaptation to each environment.…”

Section: Discussionmentioning

confidence: 99%

Disrupting optimal decision making in visual foraging: The impact of search experience.

Kobayashi,

Matsui,

Ogawa

2024

Journal of Experimental Psychology: Human Perception and Perfor

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Section: Discussionmentioning

confidence: 99%

Disrupting optimal decision making in visual foraging: The impact of search experience.

Kobayashi,

Matsui,

Ogawa

2024

Journal of Experimental Psychology: Human Perception and Perfor

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“…The resulting chain resembled Lévy flights in semantic space, characterized by mostly short transitions to nearby words and occasional large jumps. Similar dynamic processes have been used to describe eye movements during visual search (Bella-Fernández et al, 2021) and the movement of animals during reward foraging (Brown et al, 2007; Hills et al, 2015). It is intriguing to consider that a similar process may describe how decision-makers search their memory for evidence that bears on a decision.…”

Section: Discussionmentioning

confidence: 99%

Value construction through sequential sampling explains serial dependencies in decision making

Zylberberg,

Bakkour,

Shohamy

et al. 2024

Preprint

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Many decisions are expressed as a preference for one item over another. When these items are familiar, it is often assumed that the decision maker assigns a value to each of the items and chooses the item with the highest value. These values may be imperfectly recalled, but are assumed to be stable over the course of an interview or psychological experiment. Choices that are inconsistent with a stated valuation are thought to occur because of unspecified noise that corrupts the neural representation of value. Assuming that the noise is uncorrelated over time, the pattern of choices and response times in value-based decisions are modeled within the framework of Bounded Evidence Accumulation (BEA), similar to that used in perceptual decision-making. In BEA, noisy evidence samples accumulate over time until the accumulated evidence for one of the options reaches a threshold. Here, we argue that the assumption of temporally uncorrelated noise, while reasonable for perceptual decisions, is not reasonable for value-based decisions. Subjective values depend on the internal state of the decision maker, including their desires, needs, priorities, attentional state, and goals, which may change over time. These internal states may change over time, or undergo revaluation, as will the subjective values. We reasoned that these hypothetical value changes should be detectable in the pattern of choices made over a sequence of decisions. We reanalyzed data from a well-studied task in which participants were presented with pairs of snacks and asked to choose the one they preferred. Using a novel algorithm (Reval), we show that the subjective value of the items changes significantly during a short experimental session (about 1 hour). Values derived with Reval explain choice and response time better than explicitly stated values. They also better explain the BOLD signal in the ventromedial prefrontal cortex, known to represent the value of decision alternatives. Revaluation is also observed in a BEA model in which successive evidence samples are not assumed to be independent. We argue that revaluation is a consequence of the process by which values are constructed during deliberation to resolve preference choices.

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“…Stated differently, as anticipated in Table 1 , one could think of the eye (or the brain networks controlling eye behaviour) as a forager searching for valuable information (preys) in a given (and possibly time varying) scene (foraging landscape). The LFFH has been applied as modelling choice in different studies concerning eye movements, for simulation or descriptive purposes (see [ 84 ], for an in-depth discussion).…”

Section: Modelling Eye Movements Dynamicsmentioning

confidence: 99%

Using Gaze for Behavioural Biometrics

D’Amelio

Patania

Buršić

et al. 2023

Sensors

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A principled approach to the analysis of eye movements for behavioural biometrics is laid down. The approach grounds in foraging theory, which provides a sound basis to capture the uniqueness of individual eye movement behaviour. We propose a composite Ornstein-Uhlenbeck process for quantifying the exploration/exploitation signature characterising the foraging eye behaviour. The relevant parameters of the composite model, inferred from eye-tracking data via Bayesian analysis, are shown to yield a suitable feature set for biometric identification; the latter is eventually accomplished via a classical classification technique. A proof of concept of the method is provided by measuring its identification performance on a publicly available dataset. Data and code for reproducing the analyses are made available. Overall, we argue that the approach offers a fresh view on either the analyses of eye-tracking data and prospective applications in this field.

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Foraging behavior in visual search: A review of theoretical and mathematical models in humans and animals

Abstract: https://repositorio.uam.es Esta es la versión de autor del artículo publicado en: This is an author produced version of a paper published in:

Cited by 12 publications

References 203 publications

Disrupting optimal decision making in visual foraging: The impact of search experience.

Disrupting optimal decision making in visual foraging: The impact of search experience.

Value construction through sequential sampling explains serial dependencies in decision making

Using Gaze for Behavioural Biometrics

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