Prediction error

The canonical model of the dentate gyrus (DG) of the hippocampus suggests the DG performs pattern separation, orthogonalizing similar input patterns [1, 2] aided by an approximate 5-fold expansion of the cell population relative to its entorhinal cortex inputs [3]. However, more recent experimental results challenge this standard model, suggesting the DG also supports the precise binding of objects and events to space and the integration of information across episodes [4]. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG, the sup

Task design optimization using adaptive task difficulty adjustment has been used to improve behavioral performance [1]; however, its theory-free approach lacks feasibility for personalized cognitive enhancement. We aim to provide a computational framework for Cognitive Bias (CB) training with the goal of reducing cognitive bias (Fig.1A), particularly in memory and inference, that designs individually tailored task based on a metacognitive monitoring and control theory [2]. Our cognitive training strategy is inspired by the successes of neural network training through loss minimization. This fr

How can the hippocampal system transition from episodic one-shot learning to a multi-shot learning regime and what is the utility of the resultant neural representations? This talk will explore the role of the dentate gyrus (DG) anatomy in this context. The canonical DG model suggests it performs pattern separation. More recent experimental results challenge this standard model, suggesting DG function is more complex and also supports the precise binding of objects and events to space and the integration of information across episodes. Very recent studies attribute pattern separation and patte

The ability to robustly recognize strings of letters, a cornerstone of reading, was observed in Baboons and Pigeons despite their lack of phonological and semantic knowledge. Here, we apply a comparative modeling approach to investigate the neuro-cognitive basis of Human, Baboon, and Pigeon orthographic decision behavior, addressing whether phylogenetic relatedness entails similar underlying neuro-cognitive phenotypes. We use the highly transparent Speechless Reader Model (SLR), which assumes letter string recognition based on widely accepted computational principles of predictive coding so th

Repetition suppression (RS), the diminished neural response to repeated stimuli, is a well-documented phenomenon potentially explained by predictive coding. This theory suggests that the brain anticipates incoming information, minimizing further processing for familiar stimuli. For example, fusiform face area (FFA) consistently shows decreased neural response to repeated presentation of the same faces. According to the traditional model of visual processing, information progresses from the lower brain regions' superficial cortical layers to the higher areas' middle layers. Within this framewor

…In the framework of reconsolidation, a prediction error (PE) is proposed as the key mechanism that triggers the process. Generally speaking, a PE is a mismatch between expected (based on prior experience) and current events. Previous associative memory reconsolidation studies show that incomplete reminders (IR) are a subtype of prediction error that strengthen memory trace. These reminders consist in an incomplete trial that ends abru

…reports were a function of the error between participants’ belief, as determined by cues that informed participants about the level of forthcoming noxious stimulation, and the actual stimulation intensity, such that greater error decreased the influence of prior belief. Although this result appeared to present a challenge to established models of perception, our analysis did not formally compare the result against es

Memory reconsolidation is the mechanism by which consolidated memories are updated in strength and/or content. Thus, memory reactivation can enhance the retention of reactivated items at long delays. An underlying hypothesis to these findings suggests that reconsolidation would be “reactivation specific”, implying that only the reactivated elements after consolidation would be susceptible to modifications. However, episodic memories are intrinsically associative, which implies that they are integrated into interconnected- networks between its elements and the acquisition context. Reactivation

Identifying situations in which exploration could be beneficial, and learning from such choices, is critical for survival in complex environments. Nonetheless, it is still unclear how animals adapt their choice strategies depending on the potential benefits of exploration and what the neural underpinning of this ability is. We thus adapted a 2-option forced-choice task in which 3 rhesus macaques made choices while the information and the feedback they received was being manipulated: (i) feedback was given about either just the chosen option or both the chosen and unchosen counterfactual option

…in the nucleus accumbens core encodes prediction error signals to regulate reinforcement learning while dopamine release in the nucleus accumbens shell signals incentive salience and promotes motivated responses. Here we record bulk calcium dynamics in projection-specific ventral tegmental area (V

…decision-making model inspired by the prediction error signals and introspective neuronal replay reported in the brain. In the model, decisions are chosen based on ‘anticipated surprise’, defined by a nonlinear average of the differences between individual outcomes and a reference point. T

…actions are regulated by calculating prediction error, which is the difference between sensory experience and expectation based on self-generated actions. Signals consistent with prediction error have been reported in mouse visual cortex (V1) when visual flow coupled to running was unexpectedly stopped. Here, we show such signals can be elicited by visual stimuli uncoupled to animal’s running. We recorded V1 neurons while presenting drifting gratings that unexpectedly stop

The brain is a prediction machine. Yet the world is never entirely predictable, for any animal. Unexpected events are surprising and this typically evokes prediction error signatures in animal brains. In humans such mismatched expectations are often associated with an emotional response as well. Appropriate emotional responses are understood to be important for memory consolidation, suggesting that valence cues more generally constitute an ancient mechanism designed to potently refine and generalize internal models of the world and thereby minimize prediction errors. On the other hand, abolish