Insights into the neural mechanisms supporting cognitive stability and flexibility from human intracranial electroencephalography.

Humans and animals track temporal information on multiple timescales, to estimate, for example, the location of a sound source based on millisecond time differences of sound arrival at the two ears, the interval duration between the perception of lightning and thunder, or the days, months and years that have elapsed since an autobiographical event took place [–]. For autobiographical memories, recall of the “when” information is often an explicit and conscious reconstruction-based process [], for example, “we went to Turkey the year my sister got married, she is five years older than me, got married at the age of 30, and I am now 37 years old, so this must have been 12 years ago.” However, even without explicit reconstruction, healthy human adults usually have a good sense of whether a recalled event happened yesterday, a year ago or decades ago, and there is evidence for automatic processes, in particular in young infants without a fully developed episodic memory system [–]. Also corvids, rodents, and other species with an episodic-like “what-where-when” memory can remember the time of past events on timescales of days to months [,]. Whereas on timescales from milliseconds to minutes, multiple mechanisms based on changing neuronal activity patterns are known to support accurate interval timing [–], little is known about the neuronal mechanisms that support the recall of the time of past events on much longer timescales. Memories on these timescales are likely to rely on long-term synaptic plasticity [] and possibly on systems consolidation []. Multiple research communities have developed models of episodic memory to explain recall of past events []. These models focus on different aspects, such as replicating data from laboratory-based memory tasks, such as free or serial recall of lists (reviewed in []), embedding episodic memory in cognitive architectures (reviewed in []), developing attractor neural networks consistent with anatomical and physiological knowledge of the hippocampal formation (reviewed in []), or explaining systems consolidation (reviewed in []). However, little work has been devoted to understanding specifically how humans and animals remember the time of past events, although attempts at categorizing different theories of the time of past events have been made [].