Using adaptive psychophysics to identify the neural network reset time in subsecond interval timing
| Autor: | Devin Blair Terhune, Renata Sadibolova, Stella Sun |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
genetic structures
Computer science Boundary (topology) behavioral disciplines and activities Discrimination Psychological Psychophysics Humans Temporal discrimination Stimulus interval Adaptive psychophysics Artificial neural network musculoskeletal neural and ocular physiology General Neuroscience Interstimulus interval Time perception Network dynamics State-dependent network Duration (music) Breakpoint Time Perception Auditory Perception Interval (graph theory) Neural Networks Computer Reset (computing) Algorithm psychological phenomena and processes Research Article |
| Zdroj: | Experimental Brain Research King's College London |
| ISSN: | 1432-1106 0014-4819 |
| Popis: | State dependent network models of sub-second interval timing propose that duration is encoded in states of neuronal populations that need to reset prior to a novel timing operation in order to maintain optimal timing performance. Previous research has shown that the approximate boundary of this reset interval can be inferred by varying the interstimulus interval between two to-be-timed intervals. However, the estimated boundary of this reset interval is broad (250-500ms) and remains underspecified with implications for the characteristics of state dependent network dynamics subserving interval timing. Here we probed the interval specificity of this reset boundary by manipulating the interstimulus interval between standard and comparison intervals in two sub-second auditory duration discrimination tasks (100 and 200ms) and a control (pitch) discrimination task using adaptive psychophysics. We found that discrimination thresholds improved with the introduction of a 333ms interstimulus interval relative to a 250ms interstimulus interval in both duration discrimination tasks, but not in the control task. This effect corroborates previous findings of a breakpoint in the discrimination performance for sub-second stimulus interval pairs as a function of an incremental interstimulus delay but more precisely localizes the minimal interstimulus delay range. These results suggest that state dependent networks subserving sub-second timing require approximately 250-333ms for the network to reset in order to maintain optimal interval timing.New & NoteworthyThe state-dependent-network model considers interval timing as an intrinsic ability of neuronal populations to track the temporal evolution of their collective state. However, the time-dependent nature of neuronal properties imposes constraints on a maximum encodable interval and on the processing of intervals that are presented before the network resets to its baseline state. Investigating temporal discrimination thresholds as a function of variable inter-stimulus-intervals, we showed that the network reset time is between 250 and 333ms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink