Neurocomputational Models of Interval Timing: Seeing the Forest for the Trees.

Area of Science:

• Neuroscience
• Computational Biology
• Animal Behavior

Background:

• Temporal regularity extraction is vital for organism adaptiveness in ecological niches.
• Interval timing, the perception of seconds-to-minutes, is mediated by an evolutionarily conserved internal clock.
• Vertebrate timing behaviors share statistical signatures, providing benchmarks for computational models.

Purpose of the Study:

• To introduce prominent (neuro)computational approaches to modeling interval timing.
• To explain the processing dynamics of the internal clock for a general audience.
• To categorize and compare diverse interval timing models.

Main Methods:

• Review and synthesis of established (neuro)computational models of interval timing.
• Discussion of models including pacemaker accumulator, scalar expectancy theory, and neural trajectory models.
• Categorization of models based on conceptual frameworks (e.g., threshold vs. clock-adaptive, dedicated clock vs. emergent time).

Main Results:

• Multiple computational models exist to explain interval timing mechanisms.
• Models vary in their assumptions about clock architecture and time representation.
• A conceptual framework is proposed to classify and compare these diverse models.

Conclusions:

• Understanding the internal clock's 'tick' requires diverse computational approaches.
• Comparative analysis of models aids in unraveling the neural basis of interval timing.
• These models provide a foundation for future research into temporal cognition.