David W. Tank

The paper shows that neural manifolds in the medial prefrontal cortex and hippocampus represent task variables as smooth gradients in low-dimensional space, with time-aligned geometry across brain areas.

This study shows that hippocampal engrams can configure prefrontal cortex representations to guide flexible decision-making in mice during context-dependent tasks.

The paper investigates how cortical connectivity changes during different phases of a decision-making task in mice, finding phase-specific modulation of causal connectivity.

The paper develops two neural circuit models for evidence accumulation through sequential neuronal activity and tests them against neural recordings from four brain regions during a decision-making task.

The paper shows that working memory tasks involve a shared low-dimensional neural structure with more disjoint firing fields compared to simpler tasks, supporting cognitive processes.

The paper maps large-scale neuronal connections in mouse hippocampal CA3, revealing spatially graded mossy fiber inputs and a feedforward inhibitory circuit targeting specific pyramidal cells.

The paper presents a multi-region brain model to study how hippocampal circuits contribute to spatial decision-making, finding that a specific architecture optimizes learning and matches experimental data.

The paper shows error-driven drift in hippocampal representations enables flexible re-learning by allowing new associations to form while maintaining previous ones in synaptic weights.

This paper improves TEM imaging speed by using beam deflection to capture multiple image tiles, increasing efficiency for millimeter-scale brain tissue imaging.

The paper introduces a magnetic voluntary head-fixation system for longitudinal imaging of hippocampal neurons in transgenic rats.

This paper introduces an in situ X-ray assisted staining method for electron microscopy, enabling real-time observation of staining kinetics and development of a diffusion-reaction-advection model for osmium accumulation in large biological samples.

This paper introduces a probabilistic model to analyze multi-region neural dynamics and communication, showing it outperforms existing models on mouse neural datasets.

This paper links oculomotor plant dynamics to neural integrator activity in larval zebrafish, showing that gaze stabilization requires integration across multiple distributed timescales.

The paper investigates how different cortical areas contribute to sensory evidence accumulation by manipulating their activity and observing changes in decision-making.

The paper identifies and corrects misattribution errors in calcium imaging by developing a metric, visualization tool, and robust estimator for large datasets.

The paper shows that passive exposure to images increases sparseness in primary visual cortex neural activity by reducing responses of less active neurons.

The paper investigates how neural populations encode complex task information efficiently and sequentially in mice, finding that task variables are represented by uncorrelated neural modes and that encoding is multiplexed with sequential dynamics.

The paper introduces NAOMi, a simulation framework for evaluating calcium imaging methods using in silico mouse cortex data, comparing segmentation algorithms and optical designs.

The paper investigates how mice accumulate visual evidence during decision-making and finds that neural responses show amplitude modulations and deviations from Weber's Law, suggesting a feedback-based accumulation mechanism.

The paper identifies a new cell class in the mouse medial entorhinal cortex that encodes visual cue information to correct path integration errors during navigation.

This study shows that disrupting cerebellar Purkinje cells during somatosensory evidence accumulation impairs working memory accuracy and reduces the weighting of prior information in mice.

The paper investigates how midbrain dopamine neurons encode sensory, motor, and cognitive variables during a complex decision-making task, finding that neurons are functionally and spatially organized into clusters specialized for specific behavioral variables.

The paper shows that V1 neurons encode not only the current visual stimulus but also information from up to five previous images, with effects lasting up to 1000 msec.

The paper shows that neural activity in visual cortices during navigation tasks encodes cognitive variables and is modulated by accumulated evidence, explaining deviations from Weber-Fechner Law.

CaImAn, an open-source library, automates motion correction, source extraction, deconvolution and cross-session registration for calcium imaging, detecting neurons near human level (F1 0.75 batch, 0.76 online).

An unsupervised algorithm with temporal dynamics recovers hippocampal activity manifolds in rats from neural activity alone, recasting trial-to-trial variability as movement along an extra manifold dimension.

This paper introduces a new evidence-accumulation task for mice in virtual reality, showing they accumulate visual evidence to make decisions, with performance influenced by evidence magnitude but not duration.

The paper identifies a hippocampal neuron population that consistently encodes reward locations across environments, suggesting a context-invariant mechanism for goal-directed navigation.

The paper investigates predictive coding in the primary visual cortex by analyzing neural responses to novel and familiar stimuli in mice, finding a two-channel code for stimulus identity.

This paper introduces vTwINS, a volumetric two-photon calcium imaging method that increases the number of neurons recorded while maintaining high frame-rate in mouse brain regions.