Spontaneous travelling cortical waves gate perception in behaving primates

Davis, Zachary W.; Muller, Lyle; Martinez‐Trujillo, Julio; Sejnowski, Terrence J.; Reynolds, John H.

doi:10.1038/s41586-020-2802-y

Cited by 171 publications

(259 citation statements)

References 61 publications

(56 reference statements)

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“…Traveling waves of neural activity in awake cortex have been observed under stimulusevoked 41,58,59 , behavior-evoked [60][61][62] , and spontaneous conditions 5 . The fundamental neural circuit mechanism for these waves, however, had remained unclear.…”

Section: Discussionmentioning

confidence: 99%

“…Fluctuating synaptic inputs can have a significant impact on neural excitability 25 , gain modulation 26 , and readout of sensory information 13 . To understand the impact of the spontaneous network state on evoked responses in the awake visual cortex, we recorded spontaneous and stimulus-evoked activity from chronically implanted multi-electrode Utah arrays (Blackrock Microsystems) in area MT of two common marmosets (Callithrix jacchus; data previously reported in Davis et al, 2020). Spontaneous multiunit activity recorded from a single electrode while a marmoset fixated a fixation point was characterized by a low, irregular firing rate.…”

Section: Spontaneous Synaptic Fluctuations Are Comparable To Those Dumentioning

confidence: 99%

“…3a). To classify these activity patterns as traveling waves and quantify their properties relative to cortical recordings from marmoset cortex, we applied the same analysis technique developed for the experimental recordings (Generalized Phase, GP 5 ) to the simulated LFP in each 10 x 10 neuronal pool. We then adapted a technique previously developed for detecting traveling waves in noisy multielectrode recordings 41,42 .…”

Section: Spontaneous Traveling Waves Can Emerge In Network Models Witmentioning

confidence: 99%

“…Briefly, for each real-valued time series , where and are the number of columns and rows, respectively, we compute the generalized phase (GP) at each point using the corrected analytic signal representation introduced in recent work 5 . We next calculated the gradient of GP at each moment in time:…”

Section: Analysis Of Spatiotemporal Dynamicsmentioning

confidence: 99%

“…Recent work has shown that spontaneous traveling waves are present in the awake state, that they influence the magnitude of sensory-evoked activity, and that-depending on their retinotopic alignment with sensory input-they can improve perceptual sensitivity 5 . However, the mechanisms that generate them, and whether they are consistent with the asynchronousirregular spiking dynamics characteristic of awake cortex 20 , is unknown.…”

Section: Introductionmentioning

confidence: 99%

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Spontaneous traveling waves naturally emerge from horizontal fiber time delays and travel through locally asynchronous-irregular states

Davis

Benigno

Fletterman

et al. 2020

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Sensory neuroscience has focused a great deal of its attention on characterizing the mean firing rate that is evoked by a stimulus, and while it has long been recognized that the firing rates of individual neurons fluctuate around the mean, these fluctuations are often treated as a form of internally generated noise1. There is, however, evidence that these “ongoing” fluctuations of activity in sensory cortex during normal, waking function shape neuronal excitability and responses to external input2,3. We have recently found that spontaneous fluctuations are organized into waves traveling at speeds consistent with the speed of action potentials traversing unmyelinated horizontal cortical fibers (0.1-0.6 m/s)4 across the cortical surface5. These waves systematically modulate excitability across the retinotopic map, strongly affecting perceptual sensitivity as measured in a visual detection task. The underlying mechanism for these waves, however, is unknown. Further, it is unclear whether waves are consistent with the low rate, highly irregular, and weakly correlated “asynchronous-irregular” dynamics observed in computational models6 and cortical recordings in vivo7. Here, we study a large-scale computational model of a cortical sheet, with connections ranging up to biological scales. Using an efficient custom simulation framework, we study networks with topographically-organized connectivity and distance-dependent axonal conduction delays from several thousand up to one million neurons. We find that spontaneous traveling waves are a general property of these networks and are consistent with the asynchronous-irregular regime. These waves are well matched to spontaneous waves recorded in the neocortex of awake monkeys. Further, individual neurons sparsely participate in waves, yielding a sparse-wave regime that offers a unique operating mode, where traveling waves coexist with locally asynchronous-irregular dynamics, without inducing deleterious neuronal correlations8.

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