Synapses learn to utilize stochastic pre-synaptic release for the prediction of postsynaptic dynamics DOI Creative Commons
David Kappel, Christian Tetzlaff

PLoS Computational Biology, Год журнала: 2024, Номер 20(11), С. e1012531 - e1012531

Опубликована: Ноя. 4, 2024

Synapses in the brain are highly noisy, which leads to a large trial-by-trial variability. Given how costly synapses terms of energy consumption these high levels noise surprising. Here we propose that use represent uncertainties about somatic activity postsynaptic neuron. To show this, developed mathematical framework, synapse as whole interacts with soma neuron similar way an agent is situated and behaves uncertain, dynamic environment. This framework suggests implicit internal model membrane dynamics being updated by synaptic learning rule, resembles experimentally well-established LTP/LTD mechanisms. In addition, this approach entails utilizes its inherently noisy release also encode uncertainty state potential. Although each strives for predicting neuron, emergent many neuronal network resolve different problems such pattern classification or closed-loop control Hereby, coordinate themselves utilize on level behaviorally ambiguous situations.

Язык: Английский

Curiosity-driven exploration: foundations in neuroscience and computational modeling DOI Creative Commons
Alireza Modirshanechi, Kacper Kondrakiewicz, Wulfram Gerstner

и другие.

Trends in Neurosciences, Год журнала: 2023, Номер 46(12), С. 1054 - 1066

Опубликована: Ноя. 2, 2023

Curiosity refers to the intrinsic desire of humans and animals explore unknown, even when there is no apparent reason do so. Thus far, single, widely accepted definition or framework for curiosity has emerged, but growing consensus that curious behavior not goal-directed related seeking reacting information. In this review, we take a phenomenological approach group behavioral neurophysiological studies which meet these criteria into three categories according type information observed. We then review recent computational models from field machine learning discuss how they enable integrating different types one theoretical framework. Combinations along with modeling will be instrumental in demystifying notion curiosity.

Язык: Английский

Процитировано

21

Why the standard definition of creativity fails to capture the creative act DOI
Anna Abraham

Theory & Psychology, Год журнала: 2024, Номер unknown

Опубликована: Окт. 29, 2024

The “standard definition” of creativity holds that a creative idea is one novel and useful. This judgement customarily based on an external frame reference as it passed by people who are receiving the (the recipient). internal person has generated creator) usually ignored. I make two cases in this paper. First, employing frames assessing products been erroneously applied to understand mind. Second, any definition needs be can reasonably whether following experience or product. With these aims mind, propose amendment creativity: both satisfying.

Язык: Английский

Процитировано

4

Editorial overview: Computational neuroscience as a bridge between artificial intelligence, modeling and data DOI
Pietro Verzelli, Tatjana Tchumatchenko, Jeanette Hellgren Kotaleski

и другие.

Current Opinion in Neurobiology, Год журнала: 2024, Номер 84, С. 102835 - 102835

Опубликована: Янв. 6, 2024

Язык: Английский

Процитировано

3

Brain-inspired reward broadcasting: Brain learning mechanism guides learning of spiking neural network DOI Creative Commons
Miao Wang, Gangyi Ding, Yunlin Lei

и другие.

Neurocomputing, Год журнала: 2025, Номер unknown, С. 129664 - 129664

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0

Pupil dilation offers a time-window on prediction error DOI Open Access
Olympia Colizoli, Tessa M. van Leeuwen, Danaja Rutar

и другие.

Опубликована: Фев. 19, 2025

Task-evoked pupil dilation has been linked to many cognitive variables, perhaps most notably unexpected events. Zénon (2019) proposed a unifying framework stating that related cognition should be considered from an information-theory perspective. In the current study, we investigated whether pupil’s response decision outcome in context of associative learning reflects prediction error defined formally as information gain, while also exploring time course this signal. To do so, adapted simple model trial-by-trial stimulus probabilities based on theory previous literature. We analyzed two data sets which participants performed perceptual decision-making tasks required was recorded. Our findings consistently showed significant proportion variability post-feedback during can explained by formal quantification gain shortly after feedback presentation both task contexts. later window, relationship between information-theoretic variables and differed per task. For first time, present evidence dilates or constricts along with seems dependent, specifically increasing decreasing average uncertainty (entropy) across trials. This study offers empirical showcasing how offer valuable insights into process updating learning, highlighting promising utility readily accessible physiological indicator for investigating internal belief states.

Язык: Английский

Процитировано

0

Pupil dilation offers a time-window on prediction error DOI Open Access
Olympia Colizoli, Tessa M. van Leeuwen, Danaja Rutar

и другие.

Опубликована: Фев. 19, 2025

Task-evoked pupil dilation has been linked to many cognitive variables, perhaps most notably unexpected events. Zénon (2019) proposed a unifying framework stating that related cognition should be considered from an information-theory perspective. In the current study, we investigated whether pupil’s response decision outcome in context of associative learning reflects prediction error defined formally as information gain, while also exploring time course this signal. To do so, adapted simple model trial-by-trial stimulus probabilities based on theory previous literature. We analyzed two data sets which participants performed perceptual decision-making tasks required was recorded. Our findings consistently showed significant proportion variability post-feedback during can explained by formal quantification gain shortly after feedback presentation both task contexts. later window, relationship between information-theoretic variables and differed per task. For first time, present evidence dilates or constricts along with seems dependent, specifically increasing decreasing average uncertainty (entropy) across trials. This study offers empirical showcasing how offer valuable insights into process updating learning, highlighting promising utility readily accessible physiological indicator for investigating internal belief states.

Язык: Английский

Процитировано

0

Predictive coding in the human olfactory system DOI

Sam Lyons,

Jay A. Gottfried

Trends in Cognitive Sciences, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

A shared novelty-seeking basis for creativity and curiosity: Response to the commentators DOI
Tal Ivancovsky, Shira Baror, Moshe Bar

и другие.

Behavioral and Brain Sciences, Год журнала: 2024, Номер 47

Опубликована: Янв. 1, 2024

In our target article, we proposed that curiosity and creativity are both manifestations of the same novelty-seeking process. We received 29 commentaries from diverse disciplines add insights to initial proposal. These ultimately expanded supplemented model. Here draw attention five central practical theoretical issues were raised by commentators: (1) The complex construct novelty associated concepts; (2) underlying subsystems possible mechanisms; (3) different pathways subtypes creativity; (4) "in wild"; (5) link(s) between curiosity.

Язык: Английский

Процитировано

1

Merits of curiosity: a simulation study DOI Open Access

Lucas Gruaz,

Alireza Modirshanechi, Johanni Brea

и другие.

Опубликована: Сен. 2, 2024

'Why are we curious?' has been among the central puzzles of neuroscience and psychology in past decades. Recent 'top-down' theories have hypothesized that curiosity, as a desire for some intrinsically generated rewards (e.g., novelty), is optimal solution survival complex environments where evolved. To formalize test this hypothesis, however, it necessary to understand relationship between (i) intrinsic (as drives curiosity), (ii) optimality conditions objectives (iii) environment structures. Here, demystify through systematic simulation study. We first propose an algorithm generating capture key abstract features different real-world situations. Then, within these environments, simulate artificial agents seeking six representative (novelty, surprise, information gain, empowerment, MOP SPIE) evaluate their performance regarding three potential curiosity (environment exploration, model accuracy uniform state visitation). Our results show comparative each reward highly dependent on structural objective under consideration; indicates 'optimality' top-down needs precise formulation structure. Nevertheless, found combination novelty gain always achieve close-to-optimal performance; proposes two principal axes curiosity-driven behavior. These results, collectively, pave way further development computational models design theory-informed experimental paradigms.

Язык: Английский

Процитировано

1

Exploration in 4‐year‐old children is guided by learning progress and novelty DOI Creative Commons
Francesco Poli, Marlene Meyer, Rogier B. Mars

и другие.

Child Development, Год журнала: 2024, Номер unknown

Опубликована: Сен. 2, 2024

Abstract Humans are driven by an intrinsic motivation to learn, but the developmental origins of curiosity‐driven exploration remain unclear. We investigated computational principles guiding 4‐year‐old children's during a touchscreen game ( N = 102, F 49, M 53, primarily white and middle‐class, data collected in Netherlands from 2021–2023). Children guessed location characters that were hiding following predictable (yet noisy) patterns. could freely switch characters, which allowed us quantify when they decided explore something different what chose explore. Bayesian modeling their responses revealed children selected activities more novel offered greater learning progress (LP). Moreover, interest making LP correlated with better performance. These findings highlight importance novelty exploration.

Язык: Английский

Процитировано

1