The Brain: A Systems Neuroscience Perspective

Neural Systems in Learning and Memory

Author(s): Vikas Rai *

Pp: 30-50 (21)

DOI: 10.2174/9789815256987124010004

* (Excluding Mailing and Handling)

Abstract

In this chapter, theories of learning are not discussed at all. Numerous texts exist where they can be found. It would be enough to note that behavior has two aspects: 1) explorative and 2) exploitative in active inference. The former is sensitive to ambiguity, and the latter is sensitive to risk. In the absence of ambiguity, active inference reduces to a Bellman scheme [1]. Bayesian inference is integrated with active inference in free-energy formulation. Actions are guided by predictions and are refined by sensory feedback. The variational free energy is a function of observations and a probability density over their hidden causative agents. The time average of energy is action. Minimum variational free energy corresponds to a principle of least action. Perception can be regarded as a minimum of free energy with respect to inbound sensory information and action as a minimization of free energy with respect to outbound action.

Synaptic modification is a prerequisite for learning to occur. What one learns must be preserved for future use. Therefore, it needs to be stored. That storage is memory. Neural plasticity is the basis for memory formation. Information about biologically important events (Pavlovian conditional fear, Pavlovian conditioned eye-blink) reach centers in the amygdala and cerebellum through circuitry, which depends on the modality of stimulus and its complexity. In the present chapter, memory systems are introduced to the reader, starting from the Baddeley-Hitch model of working memory. Working memory is also known as short-term memory (STM). Certain information stored in short-term memory is transferred to a memory system known as Long-term memory (LTM). The brain makes decisions as to which information is to be transferred to LTM. The role of brain oscillations in memory formation is also discussed. 7±2 rule states that STM in humans can store only 5 pieces of information when it is complex; on the other hand, it can store 9 pieces when information is simple. A method to characterize the complexity of information is given. Information transport in the brain is thoroughly discussed. The chapter ends with a discussion on the discovery of engram cells, which participate in systems consolidation of memory.


Keywords: Active Inference, Bursting, Brain Dynamics, Cellular Signaling, Cognition, Declarative Memory, Excitability, Energy Efficiency, Emotion, Episodic Memory, Free Energy Principle, Functional Connectivity, Global Sate Interactions, Information Transport, Information Complexity, Long-term memory, Neurocognitive networks, Protocol, Perception, Solution of a Task, Sensory Memory, Short-term memory, 7±2 rule.

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