Biology subjects

Scott, B. B.

Publications and source records attributed to Scott, B. B..

10 recordsLinked to original sources

bioRxiv2025

A State-Dependent Drift Diffusion Model Reveals Mice Actively Explore A Speed-Accuracy Continuum During Decision-Making

Understanding how animals shift between different decision-making strategies is critical for bridging normative models with naturalistic behavior. While drift diffusion models (DDMs) provide a powerful framework for describing evidence accumulation in two-alternative forced choice (TAFC) tasks, they assume fixed parameters across trials--an assumption often violated in practice. Here, we intro- duce a state-dependent DDM framework in which discrete latent states modulate decision parameters from trial to trial. This approach reveals that mice dynamically switch between impulsive and deliberative decision states that differ in accuracy and response latency, suggesting active exploration of the speed-accuracy trade-off. We uncover rare high-bound states in which mice exhibit deliberation times and ac- curacies approaching those observed in humans. These results raise new questions about the cognitive flexibility of rodent decision-making and offer a foundation for studying how internal states and external variables--such as reward history or uncertainty--influence strategy selection. Our method provides a natural interface for integration with neural recordings and dynamical systems models, offering a path toward identifying the circuit-level mechanisms underlying adaptive decision behavior.

animal behavior and cognition↗

bioRxiv2025

Altered perceptual integration and learning in autism revealed by games inspired by rodent operant tasks

Altered perception is a key feature of autism spectrum disorder (ASD), yet its precise nature and variability across individuals remain unclear. We developed an online video game, inspired by rodent operant tasks, to assess visual evidence integration. The game employs nonverbal, reward-based training and a pulsed stimulus design for precise control of sensory input, enabling detailed individual-level behavioral analysis. It was playable by typically developing adolescents and their autistic siblings, who spanned the spectrum, including those with profound autism. Game performance correlated with standard ASD survey scores, with ASD participants exhibiting slower learning and altered perceptual integration. Behavioral data were well fit by computational models in which perceptual and learning deficits in ASD arose from increased noise in higher- order visual processing. Our findings reveal that deficits in perceptual integration are widespread across ASD, correlate with symptom severity in social and adaptive domains, and may arise from instability of sensory representations.

neuroscience↗

bioRxiv2025

Three-photon population imaging of subcortical brain regions

Recording activity from large cell populations in deep neural circuits is essential for understanding brain function. Three-photon (3P) imaging is an emerging technology that allows for imaging of structure and function in subcortical brain structures. However, increased tissue heating, as well as the low repetition rate sources inherent to 3P imaging, have limited the fields of view (FOV) to areas of [≤] 0.3 mm2. Here we present a Large Imaging Field of view Three-photon (LIFT) microscope with a FOV of >3 mm2. LIFT combines high numerical aperture (NA) optimized sampling, using a custom scanning module, with deep learning-based denoising, to enable population imaging in deep brain regions. We demonstrate non-invasive calcium imaging in the mouse brain from >1500 cells across CA1, the surrounding white matter, and adjacent deep layers of the cortex, and show population imaging with high signal-to-noise in the rat cortex at a depth of 1.2 mm. The LIFT microscope was built with all off-the-shelf components and allows for a flexible choice of imaging scale and rate.

neuroscience↗

bioRxiv2024

CA1 Engram Cell Dynamics Before and After Learning

A fundamental question in neuroscience is how memory formation shapes brain activity at the level of neuronal populations. Recent studies of hippocampal engram cells--neurons identified by learning-induced immediate early gene (IEG) expression--propose that these populations form the cellular substrate for memory. Previous experimental work suggests that cells are recruited into engrams via elevated intrinsic excitability and that learning drives coactivity among these cells to support retrieval. Despite this, an understanding of how engram dynamics evolve across learning and recall remains incomplete. Here, we combined activity-dependent genetic tagging with longitudinal two-photon calcium imaging to track CA1 engram population dynamics before and after fear conditioning. Our results reveal that engram activity is modulated by intrinsic dynamics, behavioral state, and stimulus-cued reactivation. Consistent with the idea that intrinsic dynamics bias engram allocation, spontaneous activity during rest predicted future engram membership--up to two days prior to Fos expression. In parallel, we found sequential activity during locomotion recruited both engram and non-engram cells, but that engram cells were less modulated by velocity. Furthermore, after fear conditioning, within the engram population, we identified a subset of cells that increased their correlations after fear learning, specifically during quiet rest. We also used a trace fear conditioning paradigm to show that conditioned stimulus presentation drove elevated activity and stable correlations amongst engram cells, demonstrating learning-dependent reactivation. Finally, computational modeling of CA3-CA1 circuit dynamics demonstrated that a network with strong excitatory-inhibitory balance, capable of CA3-driven reactivation, is consistent with our experimental results. Together, these results show that engram population dynamics are shaped by spontaneous states, behavior, and memory.

neuroscience↗

bioRxiv2024

Ramping dynamics in the frontal cortex unfold over multiple timescales during motor planning

Plans are formulated and refined over the period leading to their execution, ensuring that the appropriate behavior is enacted at just the right time. While existing evidence suggests that memory circuits convey the passage of time through diverse neuronal responses, it remains unclear whether the neural circuits involved in planning behavior exhibit analogous temporal dynamics. Using publicly available data, we analyzed how activity in the frontal motor cortex evolves during motor planning. Individual neurons exhibited diverse ramping activity throughout a delay interval that preceded a planned movement. The collective activity of these neurons was useful for making temporal predictions that became increasingly precise as the movement time approached. This temporal diversity gave rise to a spectrum of encoding patterns, ranging from stable to dynamic representations of the upcoming movement. Our results indicate that neural activity unfolds over multiple timescales during motor planning, suggesting a shared mechanism in the brain for processing temporal information related to both past memories and future plans.

neuroscience↗

bioRxiv2023

Rat movements reflect internal decision dynamics in an evidence accumulation task.

Perceptual decision-making involves multiple cognitive processes, including accumulation of sensory evidence, planning, and executing a motor action. How these processes are intertwined is unclear; some models assume that decision-related processes precede motor execution, whereas others propose that movements reflecting on-going decision processes occur before commitment to a choice. Here we develop and apply two complementary methods to study the relationship between decision processes and the movements leading up to a choice. The first is a free response pulse-based evidence accumulation task, in which stimuli continue until choice is reported. The second is a motion-based drift diffusion model (mDDM), in which movement variables from video pose estimation constrain decision parameters on a trial-by-trial basis. We find the mDDM provides a better model fit to rats decisions in the free response accumulation task than traditional DDM models. Interestingly, on each trial we observed a period of time, prior to choice, that was characterized by head immobility. The length of this period was positively correlated with the rats decision bounds and stimuli presented during this period had the greatest impact on choice. Together these results support a model in which internal decision dynamics are reflected in movements and demonstrate that inclusion of movement parameters improves the performance of diffusion-to-bound decision models. HighlightsO_LIDevelopment and validation of a free response pulse-based accumulation task for rats C_LIO_LIResponse times are well described by drift diffusion models C_LIO_LIIncorporating movement data into diffusion models improves inference of latent decisions variables C_LIO_LIRats weight sensory evidence most strongly prior to movement C_LI

animal behavior and cognition↗

bioRxiv2023

Magnetic voluntary head-fixation in transgenic rats enables lifetime imaging of hippocampal neurons

The precise neural mechanisms within the brain that contribute to the remarkable lifetime persistence of memory remain unknown. Existing techniques to record neurons in animals are either unsuitable for longitudinal recording from the same cells or make it difficult for animals to express their full naturalistic behavioral repertoire. We present a magnetic voluntary head-fixation system that provides stable optical access to the brain during complex behavior. Compared to previous systems that used mechanical restraint, there are no moving parts and animals can engage and disengage entirely at will. This system is failsafe, easy for animals to use and reliable enough to allow long-term experiments to be routinely performed. Together with a novel two-photon fluorescence collection scheme that increases two-photon signal and a transgenic rat line that stably expresses the calcium sensor GCaMP6f in dorsal CA1, we are able to track and record activity from the same hippocampal neurons, during behavior, over a large fraction of animals lives.

neuroscience↗

bioRxiv2023

In vivo imaging in transgenic songbirds reveals superdiffusive neuron migration in the adult brain

Neuron migration is a key phase of neurogenesis, critical for the assembly and function of neuronal circuits. In songbirds, this process continues throughout life, but how these newborn neurons disperse through the adult brain is unclear. We addressed this question using in vivo two-photon imaging in transgenic songbirds that express GFP in young neurons. In juvenile and adult birds, migratory cells were present at a high density, traveled in all directions, and made frequent course changes. Notably, these dynamic migration patterns were well fit by a superdiffusive model. Simulations revealed that these diffusion-like dynamics were sufficient to disperse new neurons throughout the song nucleus HVC. These results suggest that diffusion-like migration may underlie the formation and maintenance of nuclear brain structures in the postnatal brain and indicate that transgenic songbirds are a useful resource for future studies into the mechanisms of adult neurogenesis. HighlightsO_LITransgenic songbirds express GFP in a neurogenic lineage C_LIO_LIGFP expression is strong and sparse enough to track single cells in vivo C_LIO_LIAdult neuron migration is well fit by a superdiffusive model C_LIO_LISuperdiffusive migration is sufficient to populate HVC in simulation C_LI

neuroscience↗

bioRxiv2022

Assessing evidence accumulation and rule learning in humans with an online game

Evidence accumulation, how the brain integrates sensory information over time, is an essential component of perception and decision making. In humans, evidence accumulation is commonly modeled as a diffusion process in which noise accumulates linearly with the incoming evidence. However, recent studies in rodents have shown that during perceptual decision making, noise scales non-linearly with the strength of accumulated evidence. The question of whether nonlinear noise scaling also holds for humans has been clouded by differences in the methodologies typically used to collect and analyze human and rodent data. For example, whereas humans are typically given explicit instructions in these tasks, rodents are trained using feedback. Therefore, to evaluate how perceptual noise scales with accumulated evidence, we developed an online evidence accumulation game and nonverbal training pipeline for humans inspired by pulse-based evidence accumulation tasks for rodents. Using this game, we collected and analyzed behavioral data from hundreds of participants trained either with an explicit description of the relevant decision rule or merely with experiential feedback. Across all participants, performance was well described by an accumulation process, in which stimuli were integrated equally across time. Participants trained using feedback alone learned the game rules rapidly and used similar strategies to those who received explicit instructions. Decisions in both groups were influenced in similar ways by biases and perceptual noise, suggesting that explicit instructions did not reduce bias or noise in pulse-based accumulation tasks. Finally, by leveraging data across all participants, we show that perceptual noise during evidence accumulation was best described by a non-linear model of noise scaling, consistent with previous animal studies, but inconsistent with diffusion models widely used in human studies. These results challenge the conventional description of humans accumulation process and suggest that online games inspired by evidence accumulation tasks provide a valuable large-scale behavioral assessment platform to examine perceptual decision making and learning in humans. In addition, the feedback-based training pipeline developed for this game may be useful for evaluating perceptual decision making in human populations with difficulty following verbal instructions. HighlightsO_LIDevelopment and validation of an online video game to measure perceptual decision making. C_LIO_LIHumans trained using a feedback-based pipeline exhibit similar strategies and performance compared with those receiving instructions. C_LIO_LIPerceptual noise increases superlinearly with sensory evidence. C_LI

animal behavior and cognition↗

bioRxiv2021

A miniature kinematic coupling device for mouse head fixation

Head-fixation is a common technique in the preparation of subjects for neuroscience experiments. Accurate alignment, stability, and repeatability during fixation provide experimental consistency, thus enabling the subject to return to the same position over time to provide meaningful data. Head restraint systems inspired by kinematic clamps have been developed to allow micron scale repositioning across imaging epochs in rats. Here we report the development of a light-weight, implantable kinematic coupling (clamp) system that is wearable by mice, and enables repeated positioning to submicron accuracy across imaging epochs. This system uses a stainless steel headplate and a Maxwell-style three-groove kinematic mounting system with magnetic force clamping load. Spheres on the dorsal surface of the headplate provide contact points for vee-groove kinematic features machined into a tabletop mount. Evaluation of the clamp using multiphoton microscopy revealed submicron precision in registration accuracy and stability, allowing cellular resolution calcium imaging in awake, behaving mice. These results indicate that miniaturized implantable kinematic clamps for mice could be valuable for future experiments which require repositioning of subjects across time and different instruments. HighlightsO_LIDevelopment of a kinematic clamp for mice for precise repositioning in chronic studies. C_LIO_LIHeadplate and clamp provide stability for cellular resolution imaging during behavior. C_LIO_LIRuby contact features enable submicron registration repeatability. C_LI

neuroscience↗