scholarly journals Neurocognitive processing efficiency for discriminating human non-alarm rather than alarm scream calls

PLoS Biology ◽  
2021 ◽  
Vol 19 (4) ◽  
pp. e3000751
Author(s):  
Sascha Frühholz ◽  
Joris Dietziker ◽  
Matthias Staib ◽  
Wiebke Trost
Keyword(s):  
Decision Making ◽  
Neural System ◽  
Neural Processing ◽  
Perceptual Sensitivity ◽  
Perceptual Decision Making ◽  
Implicit Processing ◽  
Processing Efficiency ◽  
Threat Processing ◽  
Neural Processes ◽  
Processing Bias

Across many species, scream calls signal the affective significance of events to other agents. Scream calls were often thought to be of generic alarming and fearful nature, to signal potential threats, with instantaneous, involuntary, and accurate recognition by perceivers. However, scream calls are more diverse in their affective signaling nature than being limited to fearfully alarming a threat, and thus the broader sociobiological relevance of various scream types is unclear. Here we used 4 different psychoacoustic, perceptual decision-making, and neuroimaging experiments in humans to demonstrate the existence of at least 6 psychoacoustically distinctive types of scream calls of both alarming and non-alarming nature, rather than there being only screams caused by fear or aggression. Second, based on perceptual and processing sensitivity measures for decision-making during scream recognition, we found that alarm screams (with some exceptions) were overall discriminated the worst, were responded to the slowest, and were associated with a lower perceptual sensitivity for their recognition compared with non-alarm screams. Third, the neural processing of alarm compared with non-alarm screams during an implicit processing task elicited only minimal neural signal and connectivity in perceivers, contrary to the frequent assumption of a threat processing bias of the primate neural system. These findings show that scream calls are more diverse in their signaling and communicative nature in humans than previously assumed, and, in contrast to a commonly observed threat processing bias in perceptual discriminations and neural processes, we found that especially non-alarm screams, and positive screams in particular, seem to have higher efficiency in speeded discriminations and the implicit neural processing of various scream types in humans.

scholarly journals Neurocognitive processing efficiency for non-alarm rather than alarm signaling in human scream calls

2020 ◽  
Author(s):  
Sascha Frühholz ◽  
Joris Dietziker ◽  
Matthias Staib ◽  
Wiebke Trost
Keyword(s):  
Decision Making ◽  
Neural System ◽  
Neural Processing ◽  
Perceptual Sensitivity ◽  
Perceptual Decision Making ◽  
Implicit Processing ◽  
Processing Efficiency ◽  
Neural Signal ◽  
Alarm Signaling ◽  
Processing Bias

ABSTRACTAcross many species, scream calls signal the affective significance of events to other agents. Scream calls were often supposed to be of generic alarming and fearful nature to signal potential threats including their instantaneous, involuntary, and accurate recognition by perceivers. However, scream calls are more diverse in their affective signaling nature than being limited to fearfully alarm a threat, and thus the broader sociobiological relevance of various scream types is unclear. Here we used four different psychoacoustic, perceptual decision-making, and neuroimaging experiments in humans to demonstrate, first, the existence of at least six generic and psycho-acoustically distinctive types of scream calls of both an alarming and a non-alarming nature, rather than being limited to only screams caused by fear or aggression. Second, based on perceptual and processing sensitivity measures for decision-making during scream recognition, we found that alarming screams (with some exceptions) were overall discriminated the worst, were responded to the slowest and were associated with the lower perceptual sensitivity for their recognition compared with non-alarm screams. Third, the neural processing of alarm compared with non-alarm screams during an implicit processing task elicited only minimal neural signal and connectivity in perceivers, contrary to the frequent assumption of a threat processing bias of the primate neural system. These findings show that scream calls are more diverse in their signaling and communicative nature in humans and that especially non-alarming screams, and positive screams in particular, seem to have higher efficiency in the cognitive, neural, and communicative processing in humans.

scholarly journals A divisive model of evidence accumulation explains uneven weighting of evidence over time

2019 ◽  
Author(s):  
Waitsang Keung ◽  
Todd A. Hagen ◽  
Robert C. Wilson
Keyword(s):  
Decision Making ◽  
Total Activity ◽  
Neural System ◽  
Perceptual Decision Making ◽  
Evidence Accumulation ◽  
Integration Kernel ◽  
Neural Processes ◽  
Divisive Normalization ◽  
Human Participants ◽  
Over Time

SummaryDivisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the total activity of the system. More recently, dynamical versions of divisive normalization have been shown to account for how neural activity evolves over time in value-based decision making. Despite its ubiquity, divisive normalization has not been studied in decisions that require evidence to be integrated over time. Such decisions are important when we do not have all the information available at once. A key feature of such decisions is how evidence is weighted over time, known as the integration ‘kernel’. Here we provide a formal expression for the integration kernel in divisive normalization, and show that divisive normalization can quantitatively account for the perceptual decision making behaviour of 133 human participants, performing as well as the state-of-the-art Drift Diffusion Model, the predominant model for perceptual evidence accumulation.

Causal evidence for a domain-specific role of left superior frontal sulcus in human perceptual decision-making

2021 ◽  
Author(s):  
Miguel Barretto Garcia ◽  
Marcus Grueschow ◽  
Marius Moisa ◽  
Rafael Polania ◽  
Christian Carl Ruff
Keyword(s):  
Decision Making ◽  
Sequential Sampling ◽  
Computational Modelling ◽  
Perceptual Decision Making ◽  
Domain Specific ◽  
Neural Processes ◽  
Sequential Sampling Model ◽  
Evidence Integration ◽  
Superior Frontal Sulcus

Humans and animals can flexibly choose their actions based on different information, ranging from objective states of the environment (e.g., apples are bigger than cherries) to subjective preferences (e.g., cherries are tastier than apples). Whether the brain instantiates these different choices by recruiting either specialized or shared neural circuitry remains debated. Specifically, domain-general theories of prefrontal cortex (PFC) function propose that prefrontal areas flexibly process either perceptual or value-based evidence depending on what is required for the present choice, whereas domain-specific theories posit that PFC sub- areas, such as the left superior frontal sulcus (SFS), selectively integrate evidence relevant for perceptual decisions. Here we comprehensively test the functional role of the left SFS for choices based on perceptual and value-based evidence, by combining fMRI with a behavioural paradigm, computational modelling, and transcranial magnetic stimulation. Confirming predictions by a sequential sampling model, we show that TMS-induced excitability reduction of the left SFS selectively changes the processing of decision-relevant perceptual information and associated neural processes. In contrast, value-based decision making and associated neural processes remain unaffected. This specificity of SFS function is evident at all levels of analysis (behavioural, computational, and neural, including functional connectivity), demonstrating that the left SFS causally contributes to evidence integration for  perceptual but not value-based decisions.

scholarly journals Ongoing, rational calibration of reward-driven perceptual biases

2018 ◽  
Author(s):  
Yunshu Fan ◽  
Joshua I. Gold ◽  
Long Ding
Keyword(s):  
Decision Making ◽  
Response Times ◽  
Rate Function ◽  
Perceptual Sensitivity ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Reward Function ◽  
Physical Limitations ◽  
Rational Process

AbstractDecision-making is often interpreted in terms of normative computations that maximize a particular reward function for stable, average behaviors. Aberrations from the reward-maximizing solutions, either across subjects or across different sessions for the same subject, are often interpreted as reflecting poor learning or physical limitations. Here we show that such aberrations may instead reflect the involvement of additional satisficing and heuristic principles. For an asymmetric-reward perceptual decision-making task, three monkeys produced adaptive biases in response to changes in reward asymmetries and perceptual sensitivity. Their choices and response times were consistent with a normative accumulate-to-bound process. However, their context-dependent adjustments to this process deviated slightly but systematically from the reward-maximizing solutions. These adjustments were instead consistent with a rational process to find satisficing solutions based on the gradient of each monkey’s reward-rate function. These results suggest new dimensions for assessing the rational and idiosyncratic aspects of flexible decision-making.

scholarly journals Blocking serotonin but not dopamine reuptake alters neural processing during perceptual decision making.

2016 ◽  
Vol 130 (5) ◽  
pp. 461-468 ◽  
Author(s):  
Vincent D. Costa ◽  
Laura C. Kakalios ◽  
Bruno B. Averbeck
Keyword(s):  
Decision Making ◽  
Neural Processing ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Dopamine Reuptake

scholarly journals Choice History Bias in Intertemporal Choice

2019 ◽  
Author(s):  
Martin Schoemann ◽  
Stefan Scherbaum
Keyword(s):  
Decision Making ◽  
Path Dependence ◽  
Intertemporal Choice ◽  
Residual Activity ◽  
Neural System ◽  
Perceptual Decision Making ◽  
Human Decision ◽  
Inter Trial Interval ◽  
Decision Environment ◽  
Actual Decision

Human decision making is prone to many biases that either result from properties of the actual decision or from properties of the decision environment. We investigated the influence of the choice history on the actual decision in the domain of intertemporal choice, known as choice history bias from perceptual decision making. Over a series of three experiments, we demonstrate that the choice history bias also operates in intertemporal choice, but only under specific circumstances. We identified the inter-trial interval to be a determinant of the bias. Our results corroborate recent findings investigating path-dependence of perceptual and preferential decisions, and consolidate the overall mechanistic interpretation that the choice history bias arises due to residual activity in the neural system. Hence, our study bears two implications:First, models of intertemporal choice need to consider the dependency of choices across trials; second, the study of intertemporal choices empirically asks for considering this path-dependence to avoid biased conclusions about individual choices.

scholarly journals Ongoing, rational calibration of reward-driven perceptual biases

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Yunshu Fan ◽  
Joshua I Gold ◽  
Long Ding
Keyword(s):  
Decision Making ◽  
Response Times ◽  
Rate Function ◽  
Perceptual Sensitivity ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Reward Function ◽  
Physical Limitations ◽  
Rational Process

Decision-making is often interpreted in terms of normative computations that maximize a particular reward function for stable, average behaviors. Aberrations from the reward-maximizing solutions, either across subjects or across different sessions for the same subject, are often interpreted as reflecting poor learning or physical limitations. Here we show that such aberrations may instead reflect the involvement of additional satisficing and heuristic principles. For an asymmetric-reward perceptual decision-making task, three monkeys produced adaptive biases in response to changes in reward asymmetries and perceptual sensitivity. Their choices and response times were consistent with a normative accumulate-to-bound process. However, their context-dependent adjustments to this process deviated slightly but systematically from the reward-maximizing solutions. These adjustments were instead consistent with a rational process to find satisficing solutions based on the gradient of each monkey’s reward-rate function. These results suggest new dimensions for assessing the rational and idiosyncratic aspects of flexible decision-making.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

LPCD framework: Analytical tool or psychological model?

2018 ◽  
Vol 41 ◽  
Author(s):  
David Danks
Keyword(s):  
Decision Making ◽  
Analytical Tool ◽  
Mathematical Framework ◽  
Bayesian Decision ◽  
Perceptual Decision Making ◽  
Psychological Model ◽  
Psychological Reality ◽  
Psychological Theories ◽  
Target Article ◽  
Bayesian Decision Making

AbstractThe target article uses a mathematical framework derived from Bayesian decision making to demonstrate suboptimal decision making but then attributes psychological reality to the framework components. Rahnev & Denison's (R&D) positive proposal thus risks ignoring plausible psychological theories that could implement complex perceptual decision making. We must be careful not to slide from success with an analytical tool to the reality of the tool components.

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