Memory Processing -- Creation to Consolidation

Scientific Understanding of Consciousness
Consciousness as an Emergent Property of Thalamocortical Activity

Memory Processing -- Creation to Consolidation

PLoS Biology

From Creation to Consolidation: A Novel Framework for Memory Processing

Edwin M. Robertson

Berenson-Allen Center for Non-Invasive Brain Stimulation, Harvard Medical School, Beth Israel Deaconess Medical Center, Boston, Massachusetts

Citation: Robertson EM (2009) From Creation to Consolidation: A Novel Framework for Memory Processing. PLoS Biol 7(1): e1000019. doi:10.1371/journal.pbio.1000019

Published: January 27, 2009

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Memory Classification

Human memories have been classified into two broad types: declarative memories, dealing with memories for facts and events, and procedural memories, dealing with memories for skills. Overlying this classification is another classification distinguishing between memories that individuals are aware of acquiring (explicit memory) and unaware of acquiring (implicit memory). These different classifications should be seen as being largely independent. We can be aware of acquiring a new skill; for example, learning to ride a bike (explicit-procedural), but it is also possible to be unaware of acquiring a new skill, as occurs for the grammatical rules we learn (implicit-procedural). Similarly, we are aware of learning a new set of terms (explicit-declarative) but unaware that subliminal advertising, or priming in a psychology experiment, may affect our selection of a brand, or cause us to declare that we have already seen a list of words (implicit-declarative). The declarative-procedural classification has been mapped onto specific neural circuits: the mediotemporal lobe (MTL) supports declarative memories while motor cortical areas and subcortical areas, including the striatum and cerebellum, support procedural memories. This concept has been challenged by recent work showing that the MTL, at times, makes important contributions to procedural learning. Rather than constituting part of a declarative memory system, the MTL may support a set of computations that are important to both declarative and procedural memory processing

Memory Consolidation

A memory passes through at least three key milestones in its development: initially it is encoded, then it is consolidated, and finally it is retrieved. During consolidation a memory can undergo both quantitative and qualitative changes. A memory may be enhanced, demonstrated by a quantitative increase in performance, or it may be stabilized, demonstrated by becoming quantitatively less susceptible to interference. A memory can also undergo qualitative changes: there can be a shift in the strategy used to solve a problem or the emergence of awareness for what had earlier been learned. Although there is a rich diversity in the behavioral expression of consolidation, each of these examples may rely upon the same underlying computation. Consolidation is measured as a change in performance between testing and retesting. Contrasting final performance at retesting against an initial baseline provides a direct measure of “offline” performance changes that occur during consolidation.

Disengagement of memory systems during sleep

During wakefulness, reciprocal interactions occur between memory systems; whereas during sleep these systems operate independently. For example, declarative learning can block the consolidation of motor skills during wakefulness but not during sleep. Likewise, motor skill learning can block the consolidation of declarative memories during wakefulness but not during sleep. Such observations may specifically arise from a reciprocal interaction between the movement component of a motor skill memory, which is processed during wakefulness, and a declarative memory. Overall, these observations show that reciprocal interactions occur between memory systems during wakefulness, but that these systems operate independently during sleep.

Disengagement may increase the computational power of memory processing during sleep by removing the interfering effects of memory system interactions. It is during sleep that the brain's capacity to reorganize information and reveal “hidden patterns” becomes particularly marked. This greater ability to discover hidden patterns may underlie our intuitive sense that “sleeping on a problem” can produce a solution. For example, a mathematical problem can be solved either by systematically working through a series of intermediary steps to calculate the final solution, or by discovering a hidden pattern and seeing that one of the early steps predicts the final solution. An individual's capacity to bypass the intermediary steps increases following sleep and requires the formation of an association between one of the early steps and the final solution. Forming associations between temporally distant events occurs readily during sleep and may depend upon placing small fragments of juxtaposed events in the correct temporal order, and then fusing those events together. For example, a sequence of items may be recalled as a series of short fragments, such as 2-1-2, 2-3, and 3-4. After a night's sleep, these fragments may be fused together to form 2-1-2-3-4. Forming these high-order associations may allow memories that have been disrupted during the day to be reconstructed during sleep. Such high-order processing can occur within the declarative memory system—expressed as enhanced declarative recall —and within the procedural system—expressed as improved motor performance.

High-Order Associations during Sleep

Generation of high-order associations has been linked to the hippocampus, a brain area frequently implicated in sleep-dependent processing. The brain's greater affinity to generate high-order associations during sleep may stem, at least in part, from disengaging the memory systems. Disengagement may be restricted to a specific stage of sleep (e.g., NREM); while other brain states, including other stages of sleep (e.g., rapid eye movement [REM] sleep) and wakefulness, support a more interactive mode of processing. Competition for access to these brain states, and their associated interactive and disengaged modes of processing, could produce a diverse range of processing individually tailored to each memory.

The disengagement between memory systems during sleep may be due to changes in functional connectivity. During wakefulness, there is a reciprocal dialogue between the hippocampus and cortical areas; in contrast, during NREM sleep, communication appears unidirectional, from the cortex to the hippocampus. These changes in connectivity may impair the communication between memory processing areas within the hippocampus and cortex, which may lead to memory system disengagement. Thus, some brain areas appear to become functionally isolated during NREM, due to diminished connectivity, while other areas may remain as functionally connected as they were during wakefulness.

These heterogeneous changes in functional connectivity during NREM sleep may support reduced connectivity between memory systems, allowing disengagement, while simultaneously supporting enhanced or maintained connectivity within memory systems, allowing the offline processing necessary for memory consolidation.

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