Abstract:Lévy walks describe patterns of intermittent motion with variable step sizes. In complex biological systems, Lévy walks (non-Brownian, superdiffusive random walks) are associated with behaviors such as search patterns of animals foraging for food. Here we show that Lévy walks also describe patterns of oscillatory activity in primate cerebral cortex. We used a combination of empirical observation and modeling to investigate high-frequency (gamma band) local field potential activity in visual motion-processing c… Show more
“…The attention activity pattern wanders around one spatial location for a while and then switches to another one (movie S4); during this process, clusters of short step sizes are occasionally interspersed with longer movements or jumps. This intermittent switching motion of the localized activity pattern in space can be fundamentally characterized as superdiffusive Lévy motion, a type of random motion that has been widely observed in natural systems including movements of human and other animals ( 25 , 40 ) and in the movement of gamma activity patterns in monkey middle temporal (MT) area ( 41 ).…”
Recent evidence has demonstrated that during visual spatial attention sampling, neural activity and behavioral performance exhibit large fluctuations. To understand the origin of these fluctuations and their functional role, here, we introduce a mechanism based on the dynamical activity pattern (attention spotlight) emerging from neural circuit models in the transition regime between different dynamical states. This attention activity pattern with rich spatiotemporal dynamics flexibly samples from different stimulus locations, explaining many key aspects of temporal fluctuations such as variable theta oscillations of visual spatial attention. Moreover, the mechanism expands our understanding of how visual attention exploits spatially complex fluctuations characterized by superdiffusive motion in space and makes experimentally testable predictions. We further illustrate that attention sampling based on such spatiotemporal fluctuations provides profound functional advantages such as adaptive switching between exploitation and exploration activities and is particularly efficient at sampling natural scenes with multiple salient objects.
“…The attention activity pattern wanders around one spatial location for a while and then switches to another one (movie S4); during this process, clusters of short step sizes are occasionally interspersed with longer movements or jumps. This intermittent switching motion of the localized activity pattern in space can be fundamentally characterized as superdiffusive Lévy motion, a type of random motion that has been widely observed in natural systems including movements of human and other animals ( 25 , 40 ) and in the movement of gamma activity patterns in monkey middle temporal (MT) area ( 41 ).…”
Recent evidence has demonstrated that during visual spatial attention sampling, neural activity and behavioral performance exhibit large fluctuations. To understand the origin of these fluctuations and their functional role, here, we introduce a mechanism based on the dynamical activity pattern (attention spotlight) emerging from neural circuit models in the transition regime between different dynamical states. This attention activity pattern with rich spatiotemporal dynamics flexibly samples from different stimulus locations, explaining many key aspects of temporal fluctuations such as variable theta oscillations of visual spatial attention. Moreover, the mechanism expands our understanding of how visual attention exploits spatially complex fluctuations characterized by superdiffusive motion in space and makes experimentally testable predictions. We further illustrate that attention sampling based on such spatiotemporal fluctuations provides profound functional advantages such as adaptive switching between exploitation and exploration activities and is particularly efficient at sampling natural scenes with multiple salient objects.
“…1 a), a type of non-equilibrium motion that has been shown to be essential for animals to optimally search for spatially distributed food 41 , 42 , for T-cells to efficiently find target pathogens in brain explants 43 , and for optimally transporting energy in turbulent fluids 44 . Notably, it has been shown that Lévy motion underlies the propagation of gamma (30–100 Hz) burst patterns in the MT area of marmoset monkeys 45 , and that hippocampal sharp wave ripples exhibit random movements with occasional long jumps 46 . Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Such fractional motions in space give rise to irregular propagation trajectories and speeds with large variability. Propagating activity patterns have been widely observed at the circuit and the whole brain levels 22 , 23 ; notably, localized gamma activity patterns with Lévy motion have been found in the MT area of marmoset monkeys 45 . We have repeated the analysis on the broadband LFP from ref.…”
A range of perceptual and cognitive processes have been characterized from the perspective of probabilistic representations and inference. To understand the neural circuit mechanism underlying these probabilistic computations, we develop a theory based on complex spatiotemporal dynamics of neural population activity. We first implement and explore this theory in a biophysically realistic, spiking neural circuit. Population activity patterns emerging from the circuit capture realistic variability or fluctuations of neural dynamics both in time and in space. These activity patterns implement a type of probabilistic computations that we name fractional neural sampling (FNS). We further develop a mathematical model to reveal the algorithmic nature of FNS and its computational advantages for representing multimodal distributions, a major challenge faced by existing theories. We demonstrate that FNS provides a unified account of a diversity of experimental observations of neural spatiotemporal dynamics and perceptual processes such as visual perception inference, and that FNS makes experimentally testable predictions.
“…Several cortical and subcortical regions including the frontal eye field, superior colliculus, and cerebellar cortex participate in controlling and executing saccades 28 and various neurons show spike bursts in these regions 8 , 9 , 29 , 30 . Propagation of gamma-frequency ( 40 Hz) bursts of the local field potentials also obeys Lévy flight in the middle temporal cortex of marmosets, which is engaged in visual motion processing 31 . Other examples of Lévy flight are found in memory processing of animals.…”
Isolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. Neuronal bursting also has implications in neurodegenerative diseases and mental disorders. Despite these findings on the roles of bursts, whether and how bursts have an advantage over isolated spikes in the network-level computation remains elusive. Here, we demonstrate in a computational model that not isolated spikes, but intrinsic bursts can greatly facilitate learning of Lévy flight random walk trajectories by synchronizing burst onsets across a neural population. Lévy flight is a hallmark of optimal search strategies and appears in cognitive behaviors such as saccadic eye movements and memory retrieval. Our results suggest that bursting is crucial for sequence learning by recurrent neural networks when sequences comprise long-tailed distributed discrete jumps.
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