Pulin Gong

Pulin Gong
The University of Sydney · School of Physics

About

75
Publications
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Introduction
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Publications

Publications (75)
Article
Full-text available
Perceptual and cognitive processing relies on flexible communication among cortical areas; however, the underlying neural mechanism remains unclear. Here we report a mechanism based on the realistic spatiotemporal dynamics of propagating wave patterns in neural population activity. Using a biophysically plausible, multiarea spiking neural circuit m...
Article
Full-text available
Neural activity in the brain exhibits correlated fluctuations that may strongly influence the properties of neural population coding. However, how such correlated neural fluctuations may arise from the intrinsic neural circuit dynamics and subsequently affect the computational properties of neural population activity remains poorly understood. The...
Article
Full-text available
The large-scale activity of the human brain exhibits rich and complex patterns, but the spatiotemporal dynamics of these patterns and their functional roles in cognition remain unclear. Here by characterizing moment-by-moment fluctuations of human cortical functional magnetic resonance imaging signals, we show that spiral-like, rotational wave patt...
Article
Full-text available
Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolu...
Article
Full-text available
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...
Article
We investigate the emergence of complex dynamics in networks with heavy-tailed connectivity by developing a non-Hermitian random matrix theory. We uncover the existence of an extended critical regime of spatially multifractal fluctuations between the quiescent and active phases. This multifractal critical phase combines features of localization and...
Article
Full-text available
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 mod...
Preprint
Full-text available
Deep neural networks (DNNs) have been successfully applied to many real-world problems, but a complete understanding of their dynamical and computational principles is still lacking. Conventional theoretical frameworks for analysing DNNs often assume random networks with coupling weights obeying Gaussian statistics. However, non-Gaussian, heavy-tai...
Preprint
Full-text available
We investigate the emergence of complex dynamics in networks with heavy-tailed connectivity by developing a non-Hermitian random matrix theory. We uncover the existence of an extended critical regime of spatially multifractal fluctuations between the quiescent and active phases. This multifractal critical phase combines features of localization and...
Article
Learning in deep neural networks (DNNs) is implemented through minimizing a highly non-convex loss function, typically by a stochastic gradient descent (SGD) method. This learning process can effectively find generalizable solutions at flat minima. In this study, we present a novel account of how such effective deep learning emerges through the int...
Conference Paper
Full-text available
Foreword from the editors. We hosted four keynote speakers: Wolf Singer, Bill Bialek, Danielle Bassett, and Sonja Gruen. They enlightened us about computations in the cerebral cortex, the reduction of high-dimensional data, the emerging field of computational psychiatry, and the significance of spike patterns in motor cortex. From the submissions,...
Article
Full-text available
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...
Article
Full-text available
Cortical circuits generate patterned activities that reflect intrinsic brain dynamics that lay the foundation for any, including stimuli-evoked, cognition and behavior. However, the spatiotemporal organization properties and principles of this intrinsic activity have only been partially elucidated because of previous poor resolution of experimental...
Article
Full-text available
Interactions of large numbers of spiking neurons give rise to complex neural dynamics with fluctuations occurring at multiple scales. Understanding the dynamical mechanisms underlying such complex neural dynamics is a long-standing topic of interest in neuroscience, statistical physics and nonlinear dynamics. Conventionally, fluctuating neural dyna...
Preprint
Full-text available
Learning in deep neural networks (DNNs) is implemented through minimizing a highly non-convex loss function, typically by a stochastic gradient descent (SGD) method. This learning process can effectively find good wide minima without being trapped in poor local ones. We present a novel account of how such effective deep learning emerges through the...
Preprint
Interactions of large numbers of spiking neurons give rise to complex neural dynamics with fluctuations occurring at multiple scales. Understanding the dynamical mechanisms underlying such complex neural dynamics is a long-standing topic of interest in neuroscience, statistical physics and nonlinear dynamics. Conventionally, fluctuating neural dyna...
Article
Full-text available
Key points We measured fractal (self‐similar) fluctuations in ongoing spiking activity in subcortical (lateral geniculate nucleus, LGN) and cortical (area MT) visual areas in anaesthetised marmosets. Cells in the evolutionary ancient koniocellular LGN pathway and in area MT show high‐amplitude fractal fluctuations, whereas evolutionarily newer parv...
Article
Full-text available
Cortical populations produce complex spatiotemporal activity spontaneously without sensory inputs. However, the fundamental computational roles of such spontaneous activity remain unclear. Here, we propose a new neural computation mechanism for understanding how spontaneous activity is actively involved in cortical processing: Computing by Modulati...
Article
Full-text available
Propagating waves with complex dynamics have been widely observed in neural population activity. To understand their formation mechanisms, we investigate a type of two-dimensional neural field model by systematically varying its recurrent excitatory and inhibitory inputs. We show that the neural field model exhibits a rich repertoire of dynamical a...
Article
Full-text available
Experimental studies have begun revealing essential properties of the structural connectivity and the spatiotemporal activity dynamics of cortical circuits. To integrate these properties from anatomy and physiology, and to elucidate the links between them, we develop a novel cortical circuit model that captures a range of realistic features of syna...
Data
Rich-club connectivity and lognormal distribution of connection strengths emerge from transfer entropy-based effective connectivity. (PDF)
Data
Sample video for Fig 3C. The localized propagating wave state. (MP4)
Data
Variance decomposition analysis. (PDF)
Data
Bayes factor for the detected spiking wave. (PDF)
Data
Sample video for Fig 3E. The transition state. (MP4)
Data
Sample video for State II in Fig 6E. The video is visualized in the same way as in Fig 3B–3E. The parameters used for the critical case video are ξ/ξc = 1.15 and aΓ = 2, where the excitatory population firing rate is 6.6 Hz. (MP4)
Data
Diffusion-approximation-based analysis. (PDF)
Data
The reverse-pooling technique. (PDF)
Data
Sample video for Fig 3D. The global propagating wave state. (MP4)
Article
Full-text available
There is growing evidence that population-level brain activity is often organized into propagating waves that are structured in both space and time. Such spatiotemporal patterns have been linked to brain function and observed across multiple recording methodologies and scales. The ability to detect and analyze these patterns is thus essential for u...
Article
Full-text available
Diverse plasticity mechanisms are orchestrated to shape the spatiotemporal dynamics underlying brain functions. However, why these plasticity rules emerge and how their dynamics interact with neural activity to give rise to complex neural circuit dynamics remains largely unknown. Here we show that both Hebbian and homeostatic plasticity rules emerg...
Article
A deep understanding of the dynamical properties of natural time-varying images is essential for interpreting how they are efficiently processed in the brain. Here we examine natural time-varying images from the perspective of their spatiotemporal patterns and find evidence of dynamical thermodynamic criticality. We further demonstrate that these s...
Article
Full-text available
Recent experimental studies show cortical circuit responses to external stimuli display varied dynamical properties. These include stimulus strength-dependent population response patterns, a shift from synchronous to asynchronous states and a decline in neural variability. To elucidate the mechanisms underlying these response properties and explore...
Data
Supplementary Materials for Dynamical Patterns Underlying Response Properties of Cortical Circuits
Article
Full-text available
Visual stimuli can evoke waves of neural activity that propagate across the surface of visual cortical areas. The relevance of these waves for visual processing is unknown. Here, we measured the phase and amplitude of local field potentials (LFPs) in electrode array recordings from the motion-processing medial temporal (MT) area of anesthetized mal...
Article
Full-text available
Recent neural ensemble recordings have established a link between goal-directed spatial decision making and internally generated neural sequences in the hippocampus of rats. To elucidate the synaptic mechanisms of these sequences underlying spatial decision making processes, we develop and investigate a spiking neural circuit model endowed with a c...
Article
Key points: How parallel are the primate visual pathways? In the present study, we demonstrate that parallel visual pathways in the dorsal lateral geniculate nucleus (LGN) show distinct patterns of interaction with rhythmic activity in the primary visual cortex (V1). In the V1 of anaesthetized marmosets, the EEG frequency spectrum undergoes transi...
Article
Full-text available
Memory retrieval is of central importance to a wide variety of brain functions. To understand the dynamic nature of memory retrieval and its underlying neurophysiological mechanisms, we develop a biologically plausible spiking neural circuit model, and demonstrate that free memory retrieval of sequences of events naturally arises from the model und...
Article
The formation of dynamic patterns such as localized propagating waves is a fascinating self-organizing phenomenon that happens in a wide range of spatially extended systems including neural systems, in which they might play important functional roles. Here we derive a type of two-dimensional neural-field model with refractoriness to study the forma...
Article
Full-text available
Beta-band (15–30 Hz) oscillations in motor cortex have been implicated in voluntary movement and postural control. Yet the mechanisms linking those oscillations to function remains elusive. Recently, spatial waves of synchronized beta oscillations have been observed in primary and pre-motor cortex during delayed-reaching movements. Here we propose...
Article
Full-text available
Slow brain rhythms are attributed to near-simultaneous (synchronous) changes in activity in neuron populations in the brain. Because they are slow and widespread, synchronous rhythms have not been considered crucial for information processing in the waking state. Here we adapted methods from turbulence physics to analyze δ-band (1-4 Hz) rhythms in...
Article
Full-text available
Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregula...
Article
Full-text available
Bump attractors are localized activity patterns that can self-sustain after stimulus presentation, and they are regarded as the neural substrate for a host of perceptual and cognitive processes. One of the characteristic features of bump attractors is that they are neutrally stable, so that noisy inputs cause them to drift away from their initial l...
Article
Full-text available
Associative learning of temporally disparate events is of fundamental importance for perceptual and cognitive functions. Previous studies of the neural mechanisms of such association have been mainly focused on individual neurons or synapses, often with an assumption that there is persistent neural firing activity that decays slowly. However, exper...
Article
Formation of localized propagating patterns is a fascinating self-organizing phenomenon that happens in a wide range of spatially extended, excitable systems in which individual elements have resting, activated, and refractory states. Here we study a type of stochastic three-state excitable network model that has been recently developed; this model...
Article
Full-text available
Spike-timing-dependent plasticity (STDP) is an important synaptic dynamics that is capable of shaping the complex spatiotemporal activity of neural circuits. In this study, we examine the effects of STDP on the spatiotemporal patterns of a spatially extended, two-dimensional spiking neural circuit. We show that STDP can promote the formation of mul...
Article
Full-text available
A number of novel dynamical patterns are found in an integrate-and-fire network, including periodic breathers with single, double, and triple wavefronts, and chaotic breathers. It is found that the periodic breathers always propagate whereas the chaotic ones always remain stationary. A novel route to chaotic breathers through intermittency is ident...
Article
Refractoriness is one of the most fundamental states of neural firing activity, in which neurons that have just fired are unable to produce another spike, regardless of the strength of afferent stimuli. Another essential and unavoidable feature of neural systems is the existence of noise. To study the role of these essential factors in spatiotempor...
Article
Full-text available
Adaptive changes in behavior require rapid changes in brain states yet the brain must also remain stable. We investigated two neural mechanisms for evoking rapid transitions between spatiotemporal synchronization patterns of beta oscillations (13-30 Hz) in motor cortex. Cortex was modeled as a sheet of neural oscillators that were spatially coupled...
Article
Full-text available
The spatiotemporal behavior of human EEG oscillations is investigated. Traveling waves in the alpha and theta ranges are found to be common in both prestimulus and poststimulus EEG activity. The dynamical properties of these waves, including their speeds, directions, and durations, are systematically characterized for the first time, and the result...
Article
Spatially extended, excitable systems with resting, activated, and refractory states, and emergent localized propagating patterns, are widespread in nature. Here a unique type of three-state excitable network model is shown to generate such dynamic patterns with rich collective dynamics. It is shown that symmetry breaking leads to the formation of...
Article
Full-text available
Psychiatric illnesses characterized by disorganized cognition, such as schizophrenia, have been described in terms of fragmentation and hence understood as reduction in functional brain connectivity, particularly in prefrontal and parietal areas. However, as graph theory shows, relatively small numbers of nonlocal connections are sufficient to ensu...
Article
Full-text available
Background Rapid changes in behavior require rapid changes in brain states, yet the brain must also remain stable in the face of noise and uncertainty. The problem is exemplified by motor readiness in which execution of a planned motor behavior is voluntarily delayed until the onset of a ‘go’ stimulus. Achieving such rapid changes between otherwise...
Data
The ongoing behavior of several propagating, coherent activity patterns. (0.19 MB MOV)
Data
The space-time behavior of two propagating coherent activity patterns. Among several self-sustained propagating patterns, for the purpose of revealing ongoing interactions between them, only two localized coherent structures are shown in the video. (0.11 MB MOV)
Data
The ongoing behavior of several propagating, coherent activity patterns. (0.12 MB MOV)
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The mean value of the speeds of localized propagating patterns as a function of excitatory coupling strength. (1.61 MB EPS)
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The mean value of the sizes of localized propagating patterns as a function of excitatory coupling strength. (1.15 MB EPS)
Article
Full-text available
Activity in neural circuits is spatiotemporally organized. Its spatial organization consists of multiple, localized coherent patterns, or patchy clusters. These patterns propagate across the circuits over time. This type of collective behavior has ubiquitously been observed, both in spontaneous activity and evoked responses; its function, however,...
Article
Full-text available
We investigated the relationship between visual experience and temporal intervals of synchronized brain activity. Using high-density scalp electroencephalography, we examined how synchronized activity depends on visual stimulus information and on individual observer sensitivity. In a perceptual grouping task, we varied the ambiguity of visual stimu...
Article
We investigate patterns of collective phase synchronization in brain activity in awake, resting humans with eyes closed. The alpha range of human electroencephalographic activity is characterized by ever-changing patterns, with strong fluctuations in both time and overall level of phase synchronization. The correlations of these patterns are reflec...
Article
Full-text available
We demonstrate the widespread occurrence of dynamically maintained spike timing sequences in recurrent networks of pulse-coupled spiking neurons with large time delays. The sequences occur in transient, quasistable phase-locking states. The system spontaneously jumps between these states. This collective dynamics enables the system to generate a la...
Article
Full-text available
The European Physical Society (EPS) is a not for profit association whose members include 41 National Physical Societies in Europe, individuals from all fields of physics, and European research institutions. As a learned society, the EPS engages in activities that strengthen ties among the physicists in Europe. As a federation of National Physical...
Article
Full-text available
The attentional blink (AB) phenomenon occurs when perceivers must report two targets embedded in a sequence of distracters; if the first target precedes the second by 200-600 msec, the second one is often missed. We investigated AB by measuring dynamic cross-lag phase synchronization for 565 electrode pairs in 40-Hz-range EEG. Phase synchrony, on a...
Article
Full-text available
Data from a previous event-related potential (ERP) study in visual-perceptual grouping [Nikolaev AR, van Leeuwen C. Flexibility in spatial and non-spatial feature grouping: an event-related potentials study. Brain Res Cogn Brain Res 2004;22:13-25] were re-analyzed to identify event-related dynamics of phase-synchronization. In 20 Hz activity, unifo...
Article
In a visual task using 12 healthy subjects, spread of evoked phase-synchronized activity was studied in local cortical areas. The areas were identified in a previous study of the same data set using event-related potentials (ERP). Chains of closely spaced (∼2 cm) scalp electrodes covering these areas were selected for phase synchronization analysis...
Article
Dynamical properties of large-scale phase synchronization of human EEG were analyzed in the alpha frequency band. On the time scale of few seconds synchronized epochs were in- termittently interrupted by desynchronized ones, and this behavior was found to have an underlying spatiotemporal ordering. Fluctuations in duration of synchronized episodes...
Article
Synchronous population discharges in immature neurons, or giant depolarizing potentials (GDPs), are considered to have an important role in the development of the functional network in hippocampus and other neural tissue before or briefly after birth. Recently, theoretical models have emphasized the possible role of chaotic, nonlinear activity at c...
Article
Full-text available
To study the evolution of complex network with dynamical units, in this paper we consider the development of the network with chaotic units. By the addition of new nodes continuously and the adaptive rewiring of the connections according to the dynamic coherence of the activity patterns in the network, we can obtain that the growing network self-or...
Article
Full-text available
The dynamical properties of large-scale, long-term phase synchronization behavior in the alpha range of electroencephalographic signals were investigated. We observed dynamical phase synchronization and presented evidence of an underlying spatiotemporal ordering. Fluctuations in the duration of episodes of intermittent synchrony are scale-invariant...
Article
We consider growth of a network, of which the units are characterized by chaotic activity. New nodes are randomly attached one-by-one, while connections are being rewired in adaptation to the dynamic clustering patterns in the units' activity. The network self-organizes into a complex network of which the connectivity distribution reveals a power l...

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