Topic: internal model

Cognitive offloading occurs when environmental affordances expand cognitive capacity as well as facilitate spatial and social behaviors. Yet capacity-related constraints are also important, particularly as an embodied agent comes online during development. Vast differences in brain size and offloading capacity exist across the tree of life. Taking a developmental perspective, we utilize several concepts from cybernetics and the evolution of development to understand how we might determine the proportion of internal model (brain) to externalized processing (offloading) in a developing embodied

A major problem in systems neuroscience, specifically in sensory-motor control, is understanding how the brain plans and executes proper movements in the face of delayed and noisy stimuli. A prominent framework for addressing such control problems is Optimal Feedback Control (OFC). OFC generates control actions that optimize behaviorally relevant criteria by integrating noisy sensory stimuli and the predictions of an internal model using the Kalman filter or its extensions. However, a satisfactory neural model of Kalman filtering and control is lacking because existing proposals have the follo

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 world around us is complex, but at the same time full of meaningful regularities. We can detect, learn and exploit these regularities automatically in an unsupervised manner i.e. without any direct instruction or explicit reward. For example, we effortlessly estimate the average tallness of people in a room, or the boundaries between words in a language. These regularities and prior knowledge, once learned, can affect the way we acquire and interpret new information to build and update our internal model of the world for future decision-making processes. Despite the ubiquity of passively l

The ability to decide and act autonomously is a distinctive feature of human cognition. From a motor neurophysiology viewpoint, these 'voluntary' actions can be distinguished by the lack of an obvious triggering sensory stimulus: the action is considered to be a product of thought, rather than a reflex result of a specific input. A reverse engineering approach shows that such actions are caused by neurons of the primary cortex, which in turn depend on medial frontal areas, and finally a combination of prefrontal cortical connections and subcortical drive from basal ganglia loops. One tradit

Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we can also infer associations between loosely related events to infer and imagine the outcome of entirely novel choices. In the first part of the talk I will show that during successful inference, the mammalian brain uses a hippocampal prospective code to forecast temporally structured learned associations. Moreover, during periods of rest, co-activation of hippocampal cells in sharp-wave/ripples represent inferred relationships that include reward, thereby “joining-the-dots” betwe