@article {70284, title = {Astrocyte-induced internal state transitions reshape brainwide sensory, integrative, and motor computations}, journal = {bioRxiv}, year = {2026}, month = {2026 Feb 05}, abstract = {

Animals rapidly adapt to changing circumstances by shifting how they perceive, integrate, and act. Such flexibility is often attributed to transitions between internal states that exert widespread influence across the brain. Yet the mechanisms that drive state transitions and how they reconfigure brainwide computation remain unclear. Larval zebrafish, when actions are rendered futile by decoupling visual flow feedback from swimming in virtual reality, enter a temporary passive, energy-preserving state. In this state, astrocyte calcium levels are elevated, and swim reinitiation requires greater accumulated visual motion. Using whole-brain, cellular-resolution activity imaging, we observed widespread circuit alterations underlying this disengaged state: neuronal visual responses weakened, visual motion integration over time became dramatically leakier, motor inhibition increased, and motor preparation slowed, together suppressing conversion of sensory evidence into action. Astrocyte calcium rose during futile swimming, tracked the emergence and resolution of these brainwide changes, and was both necessary and sufficient to drive them. Thus, astrocytes orchestrate internal states that profoundly reshape neural computations, most powerfully at intermediate integrative processing stages, to meet changing demands.

}, doi = {10.64898/2026.02.05.704034}, url = {https://www.biorxiv.org/content/early/2026/02/05/2026.02.05.704034}, author = {Lim, Jing-Xuan and Wei, Ziqiang and Narayan, Sujatha and Zhang, Yan and Hasseman, Jeremy P. and Kolb, Ilya and Zheng, Jihong and Sheikhattar, Alireza and Mi, Xuelong and Zheng, Wei and Yang, Xueying and Beriashvili, Mariam and Fleishman, Greg and Wee, Caroline L. and de Zeeuw, Chris and Yu, Guoqiang and Babadi, Behtash and Rubinov, Mikail and Looger, Loren L. and Bergles, Dwight E. and Fitzgerald, James E. and Ahrens, Misha B.} } @article {69614, title = {Voltage imaging reveals circuit computations in the raphe underlying serotonin-mediated motor vigor learning}, journal = {Neuron}, year = {2025}, month = {2025 Jun 06}, abstract = {

As animals adapt to new situations, neuromodulation is a potent way to alter behavior, yet mechanisms by which neuromodulatory nuclei compute during behavior are underexplored. The serotonergic raphe supports motor learning in larval zebrafish by visually detecting distance traveled during swims, encoding action effectiveness, and modulating motor vigor. We found that swimming opens a gate for visual input to cause spiking in serotonergic neurons, enabling encoding of action outcomes and filtering out learning-irrelevant visual signals. Using light-sheet microscopy, voltage sensors, and neurotransmitter/modulator sensors, we tracked millisecond-timescale neuronal input-output computations during behavior. Swim commands initially inhibited serotonergic neurons via GABA, closing the gate to spiking. Immediately after, the gate briefly opened: voltage increased consistent with post-inhibitory rebound, allowing swim-induced visual motion to evoke firing through glutamate, triggering serotonin secretion and modulating motor vigor. Ablating GABAergic neurons impaired raphe coding and motor learning. Thus, serotonergic neuromodulation arises from action-outcome coincidence detection within the raphe, suggesting the existence of similarly fast and precise circuit computations across neuromodulatory nuclei.

Preprint:\ https://doi.org/10.1101/2024.09.15.613083

}, doi = {10.1016/j.neuron.2025.05.017}, url = {https://doi.org/10.1016/j.neuron.2025.05.017}, author = {Kawashima, Takashi and Wei, Ziqiang and Haruvi, Ravid and Shainer, Inbal and Narayan, Sujatha and Baier, Herwig and Ahrens, Misha B} } @article {69839, title = {Whole-brain, all-optical interrogation of neuronal dynamics underlying gut interoception in zebrafish}, journal = {bioRxiv}, year = {2025}, month = {2025 Mar 30}, abstract = {

Internal signals from the body and external signals from the environment are processed by brain-wide circuits to guide behavior. However, the complete brain-wide circuit activity underlying interoception{\textemdash}the perception of bodily signals{\textemdash}and its interactions with sensorimotor circuits remain unclear due to technical barriers to accessing whole-brain activity at the cellular level during organ physiology perturbations. We developed an all-optical system for whole-brain neuronal imaging in behaving larval zebrafish during optical uncaging of gut-targeted nutrients and visuo-motor stimulation. Widespread neural activity throughout the brain encoded nutrient delivery, unfolding on multiple timescales across many specific peripheral and central regions. Evoked activity depended on delivery location and occurred with amino acids and D-glucose, but not L-glucose. Many gut-sensitive neurons also responded to swimming and visual stimuli, with brainstem areas primarily integrating gut and motor signals and midbrain regions integrating gut and visual signals. This platform links body-brain communication studies to brain-wide neural computation in awake, behaving vertebrates.

}, doi = {10.1101/2025.03.26.645305}, url = {https://www.biorxiv.org/content/early/2025/03/30/2025.03.26.645305}, author = {Chen, Weiyu and James, Ben and Ruetten, Virginia M. S. and Banala, Sambashiva and Wei, Ziqiang and Fleishman, Greg and Rubinov, Mikail and Fishman, Mark C. and Engert, Florian and Lavis, Luke D. and Fitzgerald, James E. and Ahrens, Misha B.} } @article {68665, title = {Fast and sensitive GCaMP calcium indicators for imaging neural populations.}, journal = {Nature}, year = {2023}, month = {2023 Mar 15}, abstract = {

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting {\textquoteright}jGCaMP8{\textquoteright} sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.

}, issn = {1476-4687}, doi = {10.1038/s41586-023-05828-9}, author = {Zhang, Yan and Rozsa, Marton and Liang, Yajie and Bushey, Daniel and Wei, Ziqiang and Zheng, Jihong and Reep, Daniel and Broussard, Gerard Joey and Tsang, Arthur and Tsegaye, Getahun and Narayan, Sujatha and Obara, Christopher J and Lim, Jing-Xuan and Patel, Ronak and Zhang, Rongwei and Ahrens, Misha B and Turner, Glenn C and Wang, Samuel S-H and Korff, Wyatt L and Schreiter, Eric R and Svoboda, Karel and Hasseman, Jeremy P and Kolb, Ilya and Looger, Loren L} } @article {67828, title = {A brainstem integrator for self-localization and positional homeostasis}, journal = {Cell}, volume = {185}, year = {2022}, month = {2022 Dec 22}, pages = {5011-5027.e20}, abstract = {

To accurately track self-location, animals need to integrate their movements through space. In amniotes, representations of self-location have been found in regions such as the hippocampus. It is unknown whether more ancient brain regions contain such representations and by which pathways they may drive locomotion. Fish displaced by water currents must prevent uncontrolled drift to potentially dangerous areas. We found that larval zebrafish track such movements and can later swim back to their earlier location. Whole-brain functional imaging revealed the circuit enabling this process of positional homeostasis. Position-encoding brainstem neurons integrate optic flow, then bias future swimming to correct for past displacements by modulating inferior olive and cerebellar activity. Manipulation of position-encoding or olivary neurons abolished positional homeostasis or evoked behavior as if animals had experienced positional shifts. These results reveal a multiregional hindbrain circuit in vertebrates for optic flow integration, memory of self-location, and its neural pathway to behavior.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2021.11.26.468907}, url = {https://www.biorxiv.org/content/early/2021/11/27/2021.11.26.468907}, author = {Yang, En and Zwart, Maarten F. and Rubinov, Mikail and James, Benjamin and Wei, Ziqiang and Narayan, Sujatha and Vladimirov, Nikita and Mensh, Brett D. and Fitzgerald, James E. and Ahrens, Misha B.} } @article {65726, title = {A comparison of neuronal population dynamics measured with calcium imaging and electrophysiology.}, journal = {PLoS Computational Biology}, volume = {16}, year = {2020}, month = {2020 Sep 15}, pages = {e1008198}, abstract = {

Calcium imaging with fluorescent protein sensors is widely used to record activity in neuronal populations. The transform between neural activity and calcium-related fluorescence involves nonlinearities and low-pass filtering, but the effects of the transformation on analyses of neural populations are not well understood. We compared neuronal spikes and fluorescence in matched neural populations in behaving mice. We report multiple discrepancies between analyses performed on the two types of data, including changes in single-neuron selectivity and population decoding. These were only partially resolved by spike inference algorithms applied to fluorescence. To model the relation between spiking and fluorescence we simultaneously recorded spikes and fluorescence from individual neurons. Using these recordings we developed a model transforming spike trains to synthetic-imaging data. The model recapitulated the differences in analyses. Our analysis highlights challenges in relating electrophysiology and imaging data, and suggests forward modeling as an effective way to understand differences between these data.

}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1008198}, author = {Wei, Ziqiang and Lin, Bei-Jung and Chen, Tsai-Wen and Daie, Kayvon and Svoboda, Karel and Druckmann, Shaul} } @article {51792, title = {An orderly single-trial organization of population dynamics in premotor cortex predicts behavioral variability.}, journal = {Nature Communications}, volume = {10}, year = {2019}, month = {2019 Jan 15}, pages = {216}, abstract = {

Animals are not simple input-output machines. Their responses to even very similar stimuli are variable. A key, long-standing question in neuroscience is to understand the neural correlates of such behavioral variability. To reveal these correlates, behavior and neural population activity must be related to one another on single trials. Such analysis is challenging due to the dynamical nature of brain function (e.g., in decision making), heterogeneity across neurons and limited sampling of the relevant neural population. By analyzing population recordings from mouse frontal cortex in perceptual decision-making tasks, we show that an analysis approach tailored to the coarse grain features of the dynamics is able to reveal previously unrecognized structure in the organization of population activity. This structure is similar on error and correct trials, suggesting dynamics that may be constrained by the underlying circuitry, is able to predict multiple aspects of behavioral variability and reveals long time-scale modulation of population activity.

}, issn = {2041-1723}, doi = {10.1038/s41467-018-08141-6}, author = {Wei, Ziqiang and Inagaki, Hidehiko and Li, Nuo and Svoboda, Karel and Druckmann, Shaul} } @article {65162, title = {Single-cell reconstruction of emerging population activity in an entire developing circuit.}, journal = {Cell}, volume = {179}, year = {2019}, month = {2019 Sep 23}, abstract = {

Animal survival requires a functioning nervous system to develop during embryogenesis. Newborn neurons must assemble into circuits producing activity patterns capable of instructing behaviors. Elucidating how this process is coordinated requires new methods that follow maturation and activity of all cells across a developing circuit. We present an imaging method for comprehensively tracking neuron lineages, movements, molecular identities, and activity in the entire developing zebrafish spinal cord, from neurogenesis until the emergence of patterned activity instructing the earliest spontaneous motor behavior. We found that motoneurons are active first and form local patterned ensembles with neighboring neurons. These ensembles merge, synchronize globally after reaching a threshold size, and finally recruit commissural interneurons to orchestrate the left-right alternating patterns important for locomotion in vertebrates. Individual neurons undergo functional maturation stereotypically based on their birth time and anatomical origin. Our study provides a general strategy for reconstructing how functioning circuits emerge during embryogenesis.

}, issn = {1097-4172}, doi = {10.1016/j.cell.2019.08.039}, author = {Wan, Yinan and Wei, Ziqiang and Looger, Loren L and Koyama, Minoru and Druckmann, Shaul and Keller, Philipp J} } @article {49518, title = {Visual physiology of the layer 4 cortical circuit in silico.}, journal = {PLoS Computational Biology}, volume = {14}, year = {2018}, month = {2018 Nov 12}, pages = {e1006535}, abstract = {

Despite advances in experimental techniques and accumulation of large datasets concerning the composition and properties of the cortex, quantitative modeling of cortical circuits under in-vivo-like conditions remains challenging. Here we report and publicly release a biophysically detailed circuit model of layer 4 in the mouse primary visual cortex, receiving thalamo-cortical visual inputs. The 45,000-neuron model was subjected to a battery of visual stimuli, and results were compared to published work and new in vivo experiments. Simulations reproduced a variety of observations, including effects of optogenetic perturbations. Critical to the agreement between responses in silico and in vivo were the rules of functional synaptic connectivity between neurons. Interestingly, after extreme simplification the model still performed satisfactorily on many measurements, although quantitative agreement with experiments suffered. These results emphasize the importance of functional rules of cortical wiring and enable a next generation of data-driven models of in vivo neural activity and computations.

}, issn = {1553-7358}, doi = {10.1371/journal.pcbi.1006535}, author = {Arkhipov, Anton and Gouwens, Nathan W and Billeh, Yazan N and Gratiy, Sergey and Iyer, Ramakrishnan and Wei, Ziqiang and Xu, Zihao and Abbasi-Asl, Reza and Berg, Jim and Buice, Michael and Cain, Nicholas and da Costa, Nuno and de Vries, Saskia and Denman, Daniel and Durand, Severine and Feng, David and Jarsky, Tim and Lecoq, Jerome and Lee, Brian and Li, Lu and Mihalas, Stefan and Ocker, Gabriel K and Olsen, Shawn R and Reid, R Clay and Soler-Llavina, Gilberto and Sorensen, Staci A and Wang, Quanxin and Waters, Jack and Scanziani, Massimo and Koch, Christof} } @article {46900, title = {Confidence estimation as a stochastic process in a neurodynamical system of decision making.}, journal = {Journal of Neurophysiology}, volume = {114}, year = {2015}, month = {2015 Jul}, pages = {99-113}, abstract = {

Evaluation of confidence about one{\textquoteright}s knowledge is key to the brain{\textquoteright}s ability to monitor cognition. To investigate the neural mechanism of confidence assessment, we examined a biologically realistic spiking network model and found that it reproduced salient behavioral observations and single-neuron activity data from a monkey experiment designed to study confidence about a decision under uncertainty. Interestingly, the model predicts that changes of mind can occur in a mnemonic delay when confidence is low; the probability of changes of mind increases (decreases) with task difficulty in correct (error) trials. Furthermore, a so-called "hard-easy effect" observed in humans naturally emerges, i.e., behavior shows underconfidence (underestimation of correct rate) for easy or moderately difficult tasks and overconfidence (overestimation of correct rate) for very difficult tasks. Importantly, in the model, confidence is computed using a simple neural signal in individual trials, without explicit representation of probability functions. Therefore, even a concept of metacognition can be explained by sampling a stochastic neural activity pattern.

}, issn = {1522-1598}, doi = {10.1152/jn.00793.2014}, author = {Wei, Ziqiang and Wang, Xiao-Jing} } @article {5078, title = {From distributed resources to limited slots in multiple-item working memory: a spiking network model with normalization.}, journal = {Journal of Neuroscience}, volume = {32}, year = {2012}, month = {2012 Aug 15}, pages = {11228-40}, abstract = {

Recent behavioral studies have given rise to two contrasting models for limited working memory capacity: a "discrete-slot" model in which memory items are stored in a limited number of slots, and a "shared-resource" model in which the neural representation of items is distributed across a limited pool of resources. To elucidate the underlying neural processes, we investigated a continuous network model for working memory of an analog feature. Our model network fundamentally operates with a shared resource mechanism, and stimuli in cue arrays are encoded by a distributed neural population. On the other hand, the network dynamics and performance are also consistent with the discrete-slot model, because multiple objects are maintained by distinct localized population persistent activity patterns (bump attractors). We identified two phenomena of recurrent circuit dynamics that give rise to limited working memory capacity. As the working memory load increases, a localized persistent activity bump may either fade out (so the memory of the corresponding item is lost) or merge with another nearby bump (hence the resolution of mnemonic representation for the merged items becomes blurred). We identified specific dependences of these two phenomena on the strength and tuning of recurrent synaptic excitation, as well as network normalization: the overall population activity is invariant to set size and delay duration; therefore, a constant neural resource is shared by and dynamically allocated to the memorized items. We demonstrate that the model reproduces salient observations predicted by both discrete-slot and shared-resource models, and propose testable predictions of the merging phenomenon.

}, issn = {1529-2401}, doi = {10.1523/​JNEUROSCI.0735-12.2012}, author = {Wei, Ziqiang and Wang, Xiao-Jing and Wang, Da-Hui} } @article {4441, title = {The phase diagram and the pathway of phase transitions for traffic flow in a circular one-lane roadway.}, journal = {Physica A: Statistical Mechanics and its Applications}, volume = {388}, year = {2009}, month = {2009 Apr 15}, pages = {1665-72}, abstract = {

This paper demonstrates that patient driving habits lead to homogenous congested flow while impatient driving habits lead to wide-moving jam flow in the high density region based on the numerical simulation of the intelligent driver model proposed by M.Treiber [M. Treiber, A.Hennecke, D. Helbing, Phys. Rev. E 62 (2) (2000), 1805{\textendash}1824]. In a circular one lane traffic system which includes homogeneous drivers, we obtain the stable condition of homogenous flow and the phase diagram of traffic flow based on the linearization analysis. The phase diagram shows three possible pathways of phase transition along with the increase of global density: from the homogenous free flow to the homogenous congested flow directly, from the homogenous free flow to the synchronized flow then to the homogenous congested flow, or from the homogenous free flow to synchronized flow then to the wide-moving jam flow. The paper also analyzes the traffic flow including heterogenous drivers, and the results indicate that homogenous congested flow will lose its stability when the proportion of impatient drivers reaches a critical value and some new kinds of traffic flow emerge: wide-moving jam flow or a mixture of synchronized flow and wide-moving jam flow.

}, author = {Wei, Ziqiang and Hong, Yiguang and Wang, Dahui} }