23 papers · ranked by Valyu relevance
Herbert W. Harris
This paper explores the intersection of phenomenology and neuroscience to address foundational questions about consciousness, particularly the nature of qualia-subjective, ineffable contents of experience. Drawing on Thomas Nagel’s seminal inquiry into subjective experience and Husserlian phenomenology, we propose that…
Alain de Cheveigné
Predictive coding is an influential concept in sensory and cognitive neuroscience. It is often understood as involving top-down prediction of bottom-up sensory patterns, but the term also applies to feed-forward predictive mechanisms, for example in the retina. Here, I discuss a recent model of low-level predictive…
Alain de Cheveigné
Predictive coding is an influential concept in sensory and cognitive neuroscience. It is often understood as involving top-down prediction of bottom-up sensory patterns, but the term also applies to feed-forward predictive mechanisms, for example in the retina. Here, I discuss a recent model of low-level predictive…
Abdullahi Ali, Nasir Ahmad, Elgar de Groot, Marcel Antonius Johannes van Gerven + 1 more
'Marcel Antonius Johannes van Gerven' 'Tim Christian Kietzmann'] Title: Summary Predictive coding is a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring preferential processing of surprising elements. A central aspect of this…
Peter F. Liddle, Elizabeth B. Liddle
Current diagnostic criteria for schizophrenia place emphasis on delusions and hallucinations, whereas the classical descriptions of schizophrenia by Kraepelin and Bleuler emphasized disorganization and impoverishment of mental activity. Despite the availability of antipsychotic medication for treating delusions and…
Qingqing Zhang, Sverre Grødem, Alexa Gracias, Kristian K. Lensjø + 3 more
Predictive coding is a theoretical framework that can explain how animals build internal models of their sensory environments by predicting sensory inputs. Predictive coding may capture either spatial or temporal relationships between sensory objects. While the original theory by Rao and Ballard, 1999 described spatial…
Beren Millidge, Mufeng Tang, Mahyar Osanlouy, Nicol S. Harper + 2 more
'Rafal Bogacz' 'Peter E. Latham'] One of the key problems the brain faces is inferring the state of the world from a sequence of dynamically changing stimuli, and it is not yet clear how the sensory system achieves this task. A well-established computational framework for describing perceptual processes in the brain is…
Beren Millidge, Mufeng Tang, Mahyar Osanlouy, Nicol S. Harper + 1 more
One of the key problems the brain faces is inferring the state of the world from a sequence of dynamically changing stimuli, and it is not yet clear how the sensory system achieves this task. A well-established computational framework for describing perceptual processes in the brain is provided by the theory of…
Lucie Fontaine
—Complementary Learning Systems theory holds that intelligent agents need two learning systems. Semantic memory is encoded in the neocortex with dense, overlapping representations and acquires structured knowledge. Episodic memory is encoded in the hippocampus with sparse, pattern-separated representations and quickly…
Anthony Lin
We introduce a novel predictive coding framework for studying attachment theory. Building off an established model of attachment, the dynamic-maturational model (DMM), as well as the neuroanatomical Embodied Predictive Interoception Coding (EPIC) model of interoception and emotion, we not only elucidate how neural…
Linxing Preston Jiang, Rajesh P. N. Rao
Predictive coding is a unifying framework for understanding perception, action and neocortical organization. In predictive coding, dierent areas of the neocortex implement a hierarchical generative model of the world that is learned from sensory inputs. Cortical circuits are hypothesized to perform Bayesian inference…
Rajesh P. N. Rao, Vishwas Sathish, Linxing Preston Jiang, Matthew Bryan + 1 more
The phenomenal advances in large language models (LLMs) and other foundation models over the past few years have been based on optimizing large-scale transformer models on the surprisingly simple objective of minimizing next-token prediction loss, a form of predictive coding that is also the backbone of an increasingly…
Anne-Lise Marais, Nadege Roche-Labarbe
Sensory prediction and repetition suppression are closely related cognitive mechanisms that allow the brain to form predictions about the environment, and guide perception in synergy with attention. Predictive coding is a theory of the fundamental role of predictive mechanisms in brain functions. Authors have proposed…
Antonio Mastrogiorgio
Predictive brain theory challenges the general assumption of a brain extracting knowledge from sensations and considers the brain as an organ of inference, actively constructing explanations about reality beyond its sensory evidence. Predictive brain has been formalized through Bayesian updating, where top-down…
Bin Wang, Nicholas J Audette, David M Schneider, Johnatan Aljadeff
Neural circuits construct internal ‘world-models’ to guide behavior. The predictive processing framework posits that neural activity signaling sensory predictions and concurrently computing prediction-errors is a signature of those internal models. Here, to understand how the brain generates predictions for complex…
Antony W. N’Dri, William Gebhardt, Céline Teulière, Fleur Zeldenrust + 3 more
'Rajesh P. N. Rao' 'Jochen Triesch' 'Alexander G. Ororbia'] In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding. Specifically, we review the general framework of predictive processing in the context of neurons that emit discrete action…
Nikolas McNeal, Jennifer T. Huang, Aniekan Umoren, Shuqi Dai + 3 more
'Roger B. Dannenberg' 'Richard Randall' 'Tai Sing Lee'] We explore the use of a neural network inspired by predictive coding for modeling human music perception. This network was developed based on the computational neuroscience theory of recurrent interactions in the hierarchical visual cortex. When trained with video…
Romain Brette
Anticipation is a hallmark of all living phenomena, from bacteria to humans. If I notice a cloudy sky, I may take an umbrella to avoid getting wet. In cyanobacteria, which are photosynthetic bacteria, the chromosome decompacts shortly before dawn thanks to circadian rhythms, so that gene expression is favored when it…
Antonino Greco, Clara Rastelli, Leonardo Bonetti, Christoph Braun + 1 more
A longstanding question in cognitive science is whether the human brain learns sensory regularities that are irrelevant to ongoing behavior, a phenomenon known as incidental associative learning. Here, we provide evidence at the single subject level that humans indeed acquired such incidental associations and reveal…
Nihal Dadheech
In our research journey, we undertook a comprehensive exploration of protein-protein interaction (PPI) prediction, with a primary focus on unraveling the intricate web of interactions involving the SARS-CoV-2 virus. Our research endeavor encompassed a multi-faceted approach that seamlessly integrated data…
Authors not listed
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome coronavirus (MERS-CoV) are two important targets in current drug discovery, mainly due to the COVID-19 pandemic and the MERS-CoV outbreaks in recent years. An important target of both SARS-CoV-2 and MERS-CoV is the main…
Fuzhan Rahmanian, Robert M. Lee, Dominik Linzner, Kathrin Michel + 4 more
Predicting and monitoring battery life early and across chemistries is a significant challenge due to the plethora of degradation paths, form factors, and electrochemical testing protocols. Existing models typically translate poorly across different electrode, electrolyte, and additive materials, mostly require a fixed…
Long Qian, Xin Lu, Parvez Haris, Jianyong Zhu + 2 more
Clinical trials are crucial for drug development, but they require significant time and financial resources. Additionally, uncertainties may arise during these trials concerning their results due to concerns surrounding effectiveness, safety, or the enrollment of participants. If robust AI (artificial intelligence)…