Bernhard Spitzer
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View article: Aligning machine and human visual representations across abstraction levels
Aligning machine and human visual representations across abstraction levels Open
Deep neural networks have achieved success across a wide range of applications, including as models of human behaviour and neural representations in vision tasks 1,2 . However, neural network training and human learning differ in fundament…
View article: Increased generalisation in trait anxiety is driven by aversive value transfer not reduced perceptual discrimination
Increased generalisation in trait anxiety is driven by aversive value transfer not reduced perceptual discrimination Open
Anxiety has been linked to increased generalisation of threat expectations to perceptually similar stimuli. Such generalisation can arise either from a failure to distinguish threatening from non-threatening stimuli (perceptual mechanism) …
View article: Increased generalisation in trait anxiety is driven by value transfer, not reduced perceptual discrimination
Increased generalisation in trait anxiety is driven by value transfer, not reduced perceptual discrimination Open
Anxiety has been linked to increased generalisation of threat expectations to stimuli that are perceptually similar. Such generalisation can arise either from a failure to distinguish between threatening and non-threatening stimuli (percep…
View article: Increased generalisation in trait anxiety is driven by value transfer, not reduced perceptual discrimination
Increased generalisation in trait anxiety is driven by value transfer, not reduced perceptual discrimination Open
Anxiety has been linked to increased generalisation of threat expectations to stimuli that areperceptually similar. Such generalisation can arise either from a failure to distinguishbetween threatening and non-threatening stimuli (perceptu…
View article: Long-Term Effects of Working Memory Retrieval From Prioritized and Deprioritized States
Long-Term Effects of Working Memory Retrieval From Prioritized and Deprioritized States Open
Which factors determine whether information temporarily held in working memory (WM) can later be remembered from long-term memory (LTM)? Previous work has shown that retrieving (“testing”) memories from LTM can benefit their future LTM rec…
View article: Aligning Machine and Human Visual Representations across Abstraction Levels
Aligning Machine and Human Visual Representations across Abstraction Levels Open
Deep neural networks have achieved success across a wide range of applications, including as models of human behavior and neural representations in vision tasks. However, neural network training and human learning differ in fundamental way…
View article: Asymmetric learning and adaptability to changes in relational structure during transitive inference
Asymmetric learning and adaptability to changes in relational structure during transitive inference Open
Humans and other animals can generalise from local to global relationships in a transitive manner. Recent research has shown that asymmetrically biased learning, where beliefs about only the winners (or losers) of local comparisons are upd…
View article: Geometry of visuospatial working memory information in miniature gaze patterns
Geometry of visuospatial working memory information in miniature gaze patterns Open
Stimulus-dependent eye movements have been recognized as a potential confound in decoding visual working memory information from neural signals. Here we combined eye-tracking with representational geometry analyses to uncover the informati…
View article: EEG-representational geometries and psychometric distortions in approximate numerical judgment
EEG-representational geometries and psychometric distortions in approximate numerical judgment Open
When judging the average value of sample stimuli (e.g., numbers) people tend to either over- or underweight extreme sample values, depending on task context. In a context of overweighting, recent work has shown that extreme sample values w…
View article: Geometry of visual working memory information in human gaze patterns
Geometry of visual working memory information in human gaze patterns Open
Stimulus-dependent eye movements have been recognized as a potential confound in decoding visual working memory information from neural signals. Here, we combined eye-tracking with representational geometry analyses to uncover the very inf…
View article: Prioritization of semantic over visuo- perceptual aspects in multi-item working memory
Prioritization of semantic over visuo- perceptual aspects in multi-item working memory Open
All data and code supporting Prioritization of semantic over visuo- perceptual aspects in multi-item working memory
View article: Prioritization of semantic over visuo-perceptual aspects in multi-item working memory
Prioritization of semantic over visuo-perceptual aspects in multi-item working memory Open
Working Memory (WM) keeps information temporarily available for upcoming tasks. How the contents of WM are distinguished from perceptual representations on the one hand, and from long-term memories on the other, is still debated. Here, we …
View article: Prioritization of semantic over visuo- perceptual aspects in multi-item working memory
Prioritization of semantic over visuo- perceptual aspects in multi-item working memory Open
All data and code supporting Prioritization of semantic over visuo- perceptual aspects in multi-item working memory
View article: EEG-representational geometries and psychometric distortions in approximate numerical judgment
EEG-representational geometries and psychometric distortions in approximate numerical judgment Open
When judging the average value of sample stimuli (e.g., numbers) people tend to either over- or underweight extreme sample values, depending on task context. In a context of overweighting, recent work has shown that extreme sample values w…
View article: Over- and Underweighting of Extreme Values in Decisions from Sequential Samples
Over- and Underweighting of Extreme Values in Decisions from Sequential Samples Open
People routinely make decisions based on samples of numerical values. A common conclusion from the literature in psychophysics and behavioral economics is that observers subjectively compress magnitudes, such that extreme values have less …
View article: Over- and Underweighting of Extreme Values in Decisions from Sequential Samples
Over- and Underweighting of Extreme Values in Decisions from Sequential Samples Open
People routinely make decisions based on samples of numerical values. A common conclusion from the literature in psychophysics and behavioral economics is that observers subjectively compress magnitudes, such that extreme values have less …
View article: Control over sampling boosts numerical evidence processing in human decisions from experience
Control over sampling boosts numerical evidence processing in human decisions from experience Open
When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over information acquisition affect the quali…
View article: Control over sampling boosts numerical evidence processing in human decisions from experience
Control over sampling boosts numerical evidence processing in human decisions from experience Open
When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over sampling affect the quality of experienc…
View article: Asymmetric learning facilitates human inference of transitive relations
Asymmetric learning facilitates human inference of transitive relations Open
Humans and other animals are capable of inferring never-experienced relations (e.g., A>C) from other relational observations (e.g., A>B and B>C). The processes behind such transitive inference are subject to intense research. Here, we demo…
View article: Optimal utility and probability functions for agents with finite computational precision
Optimal utility and probability functions for agents with finite computational precision Open
Significance When making economic decisions, humans can evaluate probabilities and magnitudes of outcomes in an idiosyncratic way that can lead to poor decisions. This suggests that the internal functions that map objective quantities onto…
View article: Selective Integration during Sequential Sampling in Posterior Neural Signals
Selective Integration during Sequential Sampling in Posterior Neural Signals Open
Decisions are typically made after integrating information about multiple attributes of alternatives in a choice set. Where observers are obliged to consider attributes in turn, a computational framework known as “selective integration” ca…
View article: Optimal utility and probability functions for agents with finite computational precision
Optimal utility and probability functions for agents with finite computational precision Open
When making economic choices, such as those between goods or gambles, humans act as if their internal representation of the value and probability of a prospect is distorted away from its true value. These distortions give rise to decisions…
View article: Optimal utility and probability functions for agents with finite computational precision
Optimal utility and probability functions for agents with finite computational precision Open
When making economic choices, such as those between goods or gambles, humans act as if their internal representation of the value and probability of a prospect is distorted away from its true value. These distortions give rise to decisions…
View article: Impaired Desynchronization of Beta Activity Underlies Memory Deficits in People with Parkinson’s Disease
Impaired Desynchronization of Beta Activity Underlies Memory Deficits in People with Parkinson’s Disease Open
There is a pressing need to better understand the mechanisms underpinning the increasingly recognised non-motor deficits in Parkinson’s disease. Brain activity during Parkinson’s disease is excessively synchronized within the beta range (1…
View article: Selective integration during sequential sampling in posterior neural signals
Selective integration during sequential sampling in posterior neural signals Open
Decisions are typically made after integrating information about multiple attributes of alternatives in a choice set. The computational mechanisms by which this integration occurs have been a focus of extensive research in humans and other…
View article: Neural structure mapping in human probabilistic reward learning
Neural structure mapping in human probabilistic reward learning Open
Humans can learn abstract concepts that describe invariances over relational patterns in data. One such concept, known as magnitude, allows stimuli to be compactly represented on a single dimension (i.e. on a mental line). Here, we measure…