Background: T-pattern analysis is a procedure developed for detecting non-randomly recurring hierarchical and multiordinal real-time sequential patterns (T-patterns).
New method: We have inquired whether such patterns of action potentials (spikes) can be extracted from extracellular activity sampled simultaneously from many neurons across the mitral cell layer of the olfactory bulb (OB). Spikes were sampled from urethane-anaesthetized rats over a 6h recording session, or a period lasting as long as permitted by the physiological condition of the animal. Breathing was recorded to mark peak inhalation and exhalation.
Results: Complex T-patterns of up to ∼20 elements were identified with functional connections often spanning the full extent of the array. A considerable proportion of these sequences incorporated breathing.
Comparison with existing methods: In contrast to sequence detection by synfire, the incidence of sequences detected in our real data is very much greater than in the same data when randomized either by shuffling, or an alternative procedure preserving the interval structure of each spike train, and so more conservative. Further, when recordings were terminated before completion of the full recording session, the relative pattern detection in real and randomized data was a strong indicator of physiological condition-in recordings leading up to the preparation becoming physiologically unstable, the number of patterns detected in real data approached that in the randomized data.
Conclusions: We conclude that such sequences are an important physiological property of the neural system studied, and suggest that they may form a basis for encoding sensory information.
Keywords: Electrophysiology; Neural networks; Olfactory bulb; Randomization; Spike sequences; T-pattern analysis.
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