2017
DOI: 10.1101/107185
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Evidence for time division multiplexing: Single neurons may encode simultaneous stimuli by switching between activity patterns

Abstract: ABSTRACT:74 How the brain preserves information about multiple simultaneous items is poorly 75 understood. Here, we provide evidence that the brain may accomplish this using time division 76 multiplexing, or interleaving of different signals across time, to represent multiple items in a 77 single neural channel. We evaluated single unit activity in an auditory coding "bottleneck", the 78 inferior colliculus, while monkeys reported the location(s) of one or two simultaneous sounds.

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Cited by 2 publications
(2 citation statements)
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“…In this study, we find that the rat place cell representation of possible futures has an unexpected conjunction of four properties: constancy over time, sub-second speed, temporal segmentation (akin to time-division multiplexing; Akam and Kullmann, 2014;Caruso et al, 2018), and rhythmicity (pacing by the 8 Hz theta rhythm). Further, these temporal properties generalize across (at least) two qualitatively different representational correlates (location and direction).…”
Section: Discussionmentioning
confidence: 73%
“…In this study, we find that the rat place cell representation of possible futures has an unexpected conjunction of four properties: constancy over time, sub-second speed, temporal segmentation (akin to time-division multiplexing; Akam and Kullmann, 2014;Caruso et al, 2018), and rhythmicity (pacing by the 8 Hz theta rhythm). Further, these temporal properties generalize across (at least) two qualitatively different representational correlates (location and direction).…”
Section: Discussionmentioning
confidence: 73%
“…Understandably, it is not possible to summarize nearly a century of developments in statistical physics − not to mention 30 years of applications of these physical concepts to neuroscience−in a single review paper. An excellent introductory paper for newcomers to criticality is Beggs and Timme, 2012. References are available for those interested in diving into the technical details of critical phenomena (Nishimori and Ortiz, 2011;Tomko et al, 2018), including two books on criticality in neural dynamics (Plenz and Niebur, 2014;Tomen et al, 2019). In this section, criticality is introduced from the perspective of phase transitions and is illustrated using the two-dimensional Ising model (see Figure 1).…”
Section: Introductionmentioning
confidence: 99%