Rich Pang
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View article: Learning neural dynamics through instructive signals
Learning neural dynamics through instructive signals Open
Rapid learning is essential for flexible behavior, but its basis in the brain remains unknown. Here we introduce the PRISM plasticity rule, a unifying mechanistic model of three well-established, fast-acting synaptic plasticity rules---in …
View article: Balanced state of networks of winner-take-all units
Balanced state of networks of winner-take-all units Open
Irregularly timed action potentials, or spikes, are pervasively observed in the brain activity of awake mammals. However, the role of this temporal irregularity in neural computation is still not well understood. In canonical network model…
View article: Optimization and variability can coexist.
Optimization and variability can coexist. Open
Many biological systems perform close to their physical limits, but promoting this optimality to a general principle seems to require implausibly fine tuning of parameters. Using examples from a wide range of systems, we show that this int…
View article: Inferring neural population codes for <i>Drosophila</i> acoustic communication
Inferring neural population codes for <i>Drosophila</i> acoustic communication Open
Social communication between animals is often mediated by sequences of acoustic signals, sometimes spanning long timescales. How auditory neural circuits respond to extended input sequences to guide behavior is not understood. We address t…
View article: Exactly solvable statistical physics models for large neuronal populations
Exactly solvable statistical physics models for large neuronal populations Open
Maximum-entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations of N∼100 neurons. As N increases in new experiments,…
View article: A non-Hebbian code for episodic memory
A non-Hebbian code for episodic memory Open
Hebbian plasticity has long dominated neurobiological models of memory formation. Yet, plasticity rules operating on one-shot episodic memory timescales rarely depend on both pre- and postsynaptic spiking, challenging Hebbian theory in thi…
View article: A non-Hebbian code for episodic memory
A non-Hebbian code for episodic memory Open
Hebbian plasticity has long dominated neurobiological models of memory formation. Yet plasticity rules operating on one-shot episodic memory timescales rarely depend on both pre- and postsynaptic spiking, challenging Hebbian theory in this…
View article: Inferring neural dynamics of memory during naturalistic social communication
Inferring neural dynamics of memory during naturalistic social communication Open
Memory processes in complex behaviors like social communication require forming representations of the past that grow with time. The neural mechanisms that support such continually growing memory remain unknown. We address this gap in the …
View article: Exact minimax entropy models of large-scale neuronal activity
Exact minimax entropy models of large-scale neuronal activity Open
In the brain, fine-scale correlations combine to produce macroscopic patterns of activity. However, as experiments record from larger and larger populations, we approach a fundamental bottleneck: the number of correlations one would like t…
View article: Exactly solvable statistical physics models for large neuronal populations
Exactly solvable statistical physics models for large neuronal populations Open
Maximum entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations of $N\sim 100$ neurons. As $N$ increases in new expe…
View article: Precision motor timing via scalar input fluctuations
Precision motor timing via scalar input fluctuations Open
Complex motor skills like playing piano require precise timing over long periods, without errors accumulating between subprocesses like the left and right hand movements. While biological models can produce motor-like sequences, how the br…
View article: Path vectors: a neural code for sequential memory
Path vectors: a neural code for sequential memory Open
While recalling lists of unrelated items is highly challenging we can recall much longer sequences structured as an episode or story. It is unknown why these patterns have such a striking influence on memory. We introduce a model where the…
View article: Flexible Circuit Mechanisms for Context-Dependent Song Sequencing
Flexible Circuit Mechanisms for Context-Dependent Song Sequencing Open
Many sequenced behaviors, including locomotion, reaching, and vocalization, are patterned differently in different contexts, enabling animals to adjust to their current environments. However, how contextual information shapes neural activi…
View article: Neural Network Organization for Courtship Song Feature Detection in<i>Drosophila</i>
Neural Network Organization for Courtship Song Feature Detection in<i>Drosophila</i> Open
Animals communicate using sounds in a wide range of contexts, and auditory systems must encode behaviorally relevant acoustic features to drive appropriate reactions. How feature detection emerges along auditory pathways has been difficult…
View article: A crossover code for high-dimensional composition
A crossover code for high-dimensional composition Open
We present a novel way to encode compositional information in high-dimensional (HD) vectors. Inspired by chromosomal crossover, random HD vectors are recursively interwoven, with a fraction of one vector's components masked out and replace…
View article: Fast and flexible sequence induction in spiking neural networks via rapid excitability changes
Fast and flexible sequence induction in spiking neural networks via rapid excitability changes Open
Cognitive flexibility likely depends on modulation of the dynamics underlying how biological neural networks process information. While dynamics can be reshaped by gradually modifying connectivity, less is known about mechanisms operating …
View article: Fast and Flexible Sequence Induction In Spiking Neural Networks Via Rapid Excitability Changes
Fast and Flexible Sequence Induction In Spiking Neural Networks Via Rapid Excitability Changes Open
Cognitive flexibility, the adaptation of mental processing to changes in task demands, is thought to depend on biological neural networks’ ability to rapidly modulate the dynamics governing how they process information. While extensive wor…
View article: History dependence in insect flight decisions during odor tracking
History dependence in insect flight decisions during odor tracking Open
Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advecte…
View article: A simple generative model of the mouse mesoscale connectome
A simple generative model of the mouse mesoscale connectome Open
Recent technological advances now allow for the collection of vast data sets detailing the intricate neural connectivity patterns of various organisms. Oh et al. (2014) recently published the most complete description of the mouse mesoscal…
View article: Author response: A simple generative model of the mouse mesoscale connectome
Author response: A simple generative model of the mouse mesoscale connectome Open
Full text Figures and data Side by side Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Recent technol…