Predictive processing

…The conversation also examines predictive processing, representation and the role of AI in understanding brains and minds.

Predictive processing offers a unifying view of neural computation, proposing that brains continuously anticipate sensory input and update internal models based on prediction errors. In this talk, I will present converging evidence for the computational mechanisms underlying this framework across human neuroscience and deep neural networks. I will begin with recent work showing that large-scale distributed prediction-error encoding in the human brain directly predicts how sensory representations reorganize through predictive learning. I will then turn to PredNet, a popular predictive coding in

…Predictive processing accounts of hallucinations suggest that these alterations bias patients’ perception toward their sensory expectations. However, 1) whether this framework holds when considering real-world hallucinations with complex content and 2) which upstream neural mechanisms cause these alterations in learning are hotly debated. To address these questions, we used fMRI to record neur

As we learn we are constantly processing sensory input to guide our purposeful behavior, creating a continuous perception-action loop. This interaction emphasizes the transformation of sensory information into motor output, influencing how we engage with our environment. Sensory cortices have been recently shown to send divergent projections to the cerebellum, a key motor control region. Our recent studies on corticocerebellar projections revealed unique pathways for auditory stimuli, highlighting structural and functional distinctions in auditory fields linked to locomotion. Our exploration o

Aims: In the context of the maternal immune activation and neuroinflammation hypotheses of schizophrenia (SZ), we studied NLRP1 mRNA and protein expression in the postmortem brain tissue from a total of 10 SZ and 10 controls. Methods: RNA underwent reverse transcription and was hybridized onto the Affymetrix HG-U133 Plus 2.0 array, using the same protocol as the GeneChip Human Exon 1.0ST Arrays (Affymetrix, Santa Clara, CA, USA), which examines over a million exons, spanning 17,868 NCBI RefSeq transcripts. Brain tissue samples were embedded in paraffin, cut into 12 μm-thin sections, and subjec

Body movement conveys important information about agents’ internal states, such as their emotions or intentions. But how do humans use movement cues to understand others? A growing body of behavioural and neuroimaging work suggests that we map observed actions onto our own motor system to successfully interpret others’ movements, and that movement similarity between an agent and observer facilitates accurate inferences about the agent’s internal state. A network of frontal, parietal and occipitotemporal regions, termed the action-observation network (AON), is presumed to subserve this coupling

The predictive processing framework conceptualizes perception as co-constructed by sensory information and priors. These priors arise from different sources including long-term and short-term perceptual history. According to predictive processing, psychosis can be explained as a reduced weighting of priors relative to sensory information. This study investigated how short-term priors from different sources are used in perceptual decision-making and how psychosis proneness (PP) modulates the use of these priors.Across two online experiments, 101 healthy participants completed an auditory percep

Predictive processing is a computational framework that aims to explain how the brain processes sensory information by making predictions about the environment and minimizing prediction errors. It can also be used to explain some of the key symptoms of psychotic disorders such as schizophrenia. In my talk, I will provide an overview of our progress in this endeavor.

…maintaining these mappings, is that of predictive processing. The functional implementation of this algorithm in cortex implies two computational

…We propose a plasticity rule based on predictive processing, where neurons learn a low-rank model of the synaptic input dynamics in their membrane potential. Neurons thereby amplify those synapses that maximally predict o

…based on the theoretical framework of predictive processing, which proposes that inferences regarding the state of the world are made by combining prior beliefs with sensory signals. Delusions and hallucinations are the core symptoms of psychosis and often co-occur. Yet, different predictive-processing alterations have been proposed for these two symptom dimensions, according to which the relative weighting of prior beliefs in perceptual inference is

…Predictions lead to efficient neural processing of incoming stimuli and hence facilitate perception. Although the existence of prediction signals is known, much less is known about the neural mechanisms underlying the propagation of prediction signals, especially in higher-vision. Predictive processing theories propose that in cortical hierarchies, high-leve

…the neural substrates underlying this predictive information processing [1]. An integral part of predictive processing is a subset of excitatory neurons that encode prediction errors: while negative prediction-error (nPE) neurons are only activated when sensory signals are weaker than predicted, positive prediction-error (pPE) neurons respond only when sensory signals exceed the

Despite the increasing recognition of predictive processing in circuit neuroscience, little is known about how it may be implemented in cortical circuits. We set out to develop and characterise a biological model system with layer 5 pyramidal cells in the centre. We aim to gain access to prediction and internal model generating processes by controlling, understanding or monitoring everything else: the sensory environment, feed-forward and feed-back inputs, integrative properties, their spiking activity and output. I’ll show recent work from the lab establishing such a model system both in term

The theory of predictive processing posits that the brain computes expectations to process information predictively. Empirical evidence in support of this theory, however, is scarce and largely limited to sensory areas. Here, we report a precise and adaptive mechanism in the frontal cortex of non-human primates consistent with predictive processing of temporal events. We found that the speed of neural dynamics is precisely adjusted according to the average time of an expected stimulus. This speed adjustment, in turn, enables neurons to encode stimuli in terms of deviations from expectation. Th

…by the accounts of hierarchical predictive processing, using dynamic causal modelling (DCM). D

…a role for prediction in local sensory processing. However, it is unclear whether this phenomenon derives from a precise movement-based prediction or how it affects the neural representation of incoming stimuli. We address the

…of human existence is underpinned by predictive regulation of the interior of the body, using the framework of predictive processing, or active inference. I start by showing how conscious experiences of the world around us can be understood in terms of perceptual predictions, drawing on examples from psychophysics and virtual reality. Then, turning the lens inwards, we will see how the experience of being

According to the theory of predictive processing, expectations modulate neural activity so as to optimize the processing of sensory inputs expected in the current environment. While there is accumulating evidence that the brain indeed operates under this principle, most of the attention has been placed on mechanisms that rely on static coding properties of neurons. The potential contribution of dynamical features, such as those reflected in the evolution of neural population dynamics, has thus far been overlooked. In this talk, I will present evidence for a novel mechanism for predictive proce