Biology subjects

Schultz, S. R.

Publications and source records attributed to Schultz, S. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Arousal-informed neuronal avalanches operate near criticality

Cortical networks are thought to operate near a "critical point" that optimizes information processing, but this has been difficult to test at single-cell resolution across large brain areas, as narrow fields of view miss overlapping neural avalanches, causing subcritical estimates, Using mesoscopic two-photon calcium imaging in awake mouse visual cortex, we recorded thousands of neurons and applied convolutional non-negative matrix factorization to decompose population activity into distinct, overlapping spatiotemporal avalanches. Rather than occupying a single dynamical state, we find that the cortex hosts multiple overlapping subnetworks distributed across a phase diagram at varying distances from the critical point. Arousal-linked avalanches propagate widely and operate nearest the critical point, showing optimized dynamic range, minimized algorithmic complexity, and maximized temporal entropy. Our results reveal how the awake brain tunes parallel near-critical subnetworks to support robust sensory computation.

neuroscience↗

bioRxiv2026

Prefrontal activation predicts response latency and is shaped by age and lifestyle

Neurological and neuropsychiatric conditions affect 43% of the global population, many shaped by modifiable lifestyle exposures, yet their relationship to cortical haemodynamics is poorly characterised. The dorsolateral prefrontal cortex (dlPFC) is a particularly tractable target: it underpins executive function, is disrupted across neuropsychiatric and age-related conditions, and lies on the cortical surface, within reach of scalable, wearable-grade optical neuroimaging. We present LUCID, a longitudinal study of 92 healthy adults combining consumer wearable sleep and physical activity metrics with task-evoked dlPFC haemodynamics, measured by time-domain functional near-infrared spectroscopy (TD-fNIRS). Log-transformed peak dlPFC activation was negatively associated with reaction time (RT) across the 2N-Back and Stroop tasks and both hemispheres (r = -0.37 to -0.53), greater activation accompanying faster responses, consistent with a capacity/recruitment account. Activation showed moderate test-retest reliability (intraclass correlation coefficient, ICC = 0.56-0.71), with between-person variance exceeding within-person fluctuation, indicating stable individual differences. Demographic and lifestyle features incrementally predicted activation, with age the strongest predictor and modest contributions from sleep and physical activity. These findings establish TD-fNIRS dlPFC activation as a longitudinally stable, behaviourally relevant functional neural marker for scalable tracking of modifiable risk.

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bioRxiv2025

Synergy mediates Long-Range Correlations in the Visual Cortex Near Criticality

Long-range correlations are a key signature of systems operating near criticality, indicating spatially-extended interactions across large distances. These extended dependencies underlie other emergent properties of critical dynamics, such as high susceptibility and multi-scale coordination. In the brain, along with other signatures of criticality, long-range correlations have been observed across various spatial scales, suggesting that the brain may operate near a critical point to optimise information processing and adaptability. However, the mechanisms underlying these long-range correlations remain poorly understood. Here, we investigate the role of synergistic interactions in mediating long-range correlations in the visual cortex of awake mice. We leverage recent advances in mesoscale two-photon calcium imaging to analyse the activity of thousands of neurons across a wide field of view, allowing us to confirm the presence of long-range correlations at the level of neuronal populations. By applying the Partial Information Decomposition (PID) framework, we decompose the correlations into synergistic and redundant information interactions. Our results reveal that the increase in long-range correlations during visual stimulation is accompanied by a significant increase in synergistic rather than redundant interactions among neurons. Furthermore, we analyse a combined network formed by the union of synergistic and redundant interaction networks, and find that both types of interactions complement each other to facilitate efficient information processing across long distances. This complementarity is further enhanced during the visual stimulation. These findings provide new insights into the computational mechanisms that give rise to long-range correlations in neural systems and highlight the importance of considering different types of information interactions in understanding correlations in the brain.

neuroscience↗

bioRxiv2025

Astrocytes and neurons encode natural stimuli with partially shared but distinct composite receptive fields

Astrocytes are increasingly recognized as active participants in sensory processing, but whether they show selective responses to stimulus features, analogous to neuronal receptive fields, is not yet established. To address this, we used two-photon calcium imaging in the auditory cortex of anesthetized mice during presentation of natural ultrasonic vocalizations. Our aim was to compare astrocytic responses with those of neighboring neurons and to determine whether astrocytes exhibit feature-selective receptive fields. Event detection showed that astrocytic calcium activity is highly heterogeneous, but only a minority of events were consistently stimulus-linked. To examine this stimulus-driven subset, we estimated receptive field features using maximum noise entropy modeling and compared them with those of concurrently recorded neurons. Despite qualitative similarities in receptive-field features, analysis of modulation spectra and principal angles showed that astrocytic and neuronal receptive fields overlap but occupy distinct regions of feature space. This indicates that astrocytes and neurons encode partially shared, but not identical, dimensions of the sensory stimulus. Our findings indicate that astrocytes encode diverse sensory features, providing an additional contribution to neuronal encoding. This suggests that astrocytic calcium activity is not simply a reflection of neuronal firing, but instead represents a distinct component of cortical sensory processing. New and noteworthyWe used two-photon imaging to record calcium activity in astrocytes and neighboring neurons during presentation of natural ultrasonic vocalizations. We show that astrocyte activity is highly heterogeneous across spatial and temporal scales. Further analyses indicate that a subset of astrocyte calcium activity is stimulus-linked and encodes dimensions of the stimulus that partially overlap but are not identical to those encoded by neurons.

neuroscience↗

bioRxiv2025

Longitudinal three-photon imaging for tracking amyloid plaques and vascular degeneration in a mouse model of Alzheimer's disease

SignificanceVascular abnormalities may contribute to amyloid-beta accumulation and neurotoxicity in Alzheimers disease (AD). Monitoring vascular degeneration as AD progresses is essential. Three-photon fluorescence microscopy (3PM) enables high-resolution deep tissue imaging with minimal invasiveness and photodamage. AimThis proof-of-concept study established a longitudinal 3P imaging pipeline to quantify vascular and amyloid plaque changes in the APPNL-G-F mouse model. ApproachA cranial window allowed repeated 3P imaging at four-week intervals beginning at five weeks after surgery. Vessels labelled with Texas-Red were segmented using DeepVess, while plaques labelled with methoxy-XO4 were segmented using custom scripts. Quantitative analyses assessed vascular parameters (diameter, tortuosity, length, inter-vessel distance, total volume) and plaque metrics (radius, total volume). ResultsWe imaged the same field over 4 weeks quantifying an overall decrease in vasculature and increase in amyloid plaques between two sessions. Significant changes in vessel diameter, inter-vessel distance, as well as alterations in vessel length and plaques radius were observed. Changes in vessel tortuosity were not significant. ConclusionsWe demonstrate the potential of three-photon imaging to track vascular and amyloid-related changes in deep cortical structures. It offers a tool for studying the interplay between vascular and amyloid pathologies in AD, supporting future research into disease mechanisms and therapeutic strategies.

neuroscience↗

bioRxiv2025

Amyloid pathology reduces dynamic range and disrupts neural coding in a mouse model of Alzheimer's Disease

Alzheimers disease (AD) disrupts neural circuits vital for memory and cognition. Using two-photon calcium imaging in behaving 5xFAD mice, we examined how amyloid pathology alters hippocampal CA1 activity and spatial coding. We found elevated baseline activity but reduced locomotion-driven firing, leading to a diminished neuronal dynamic range. To our knowledge, this is the first direct experimental evidence for reduced dynamic range in an AD model. These abnormalities were strongest near amyloid plaques and became more widespread with age. We also observed altered network synchrony, degraded spatial coding and increased neuronal response variability. Furthermore, place fields emerged more slowly in both familiar and novel environments, indicating impaired recall and learning. By showing a link between local plaque pathology and impaired flexible modulation of CA1 activity and progressive deficits in spatial memory coding, our study offers new insights into the circuit basis of cognitive decline in AD.

neuroscience↗

bioRxiv2025

Ultra-wide-field, deep, adaptive two-photon microscopy

Observing the activity patterns of large neural populations throughout the brain is essential for understanding brain function. However, capturing neural interactions across widely distributed brain regions from both superficial and deep cortical layers remains challenging with existing microscopy technologies. Here, we introduce a state-of-the-art two-photon microscopy system, ULTRA, capable of single-cell resolution imaging across an ultra-large field of view (FOV) exceeding 50 mm{superscript 2}, enabling deep and very wide field in vivo imaging. To demonstrate its capabilities, we conducted a series of experiments under multiple imaging conditions, successfully visualizing brain structures and neuronal activities spanning a spatial range of over 7 mm from superficial layers to depths of up to 900 m, while covering a volume of 45.24 mm3 in the mouse brain. This versatile imaging platform overcomes traditional spatial constraints, providing a powerful tool for comprehensive exploration of neuronal circuitry over extensive spatial scales with cellular resolution.

neuroscience↗

bioRxiv2025

Hippocampal reactivation of planned trajectories is required for effective goal choice in an allocentric memory task

Hippocampal activity provides a representation of the world around us, as well as our position within that world. However, it is not known if and to what extent the chosen navigational reference frame can influence hippocampal representations during memory-based tasks, including those focused on future activity. Here, we develop and employ two naturalistic, carefully controlled variants of the everyday memory task to model the use of egocentric and allocentric coordinates in the same arena. By recording hippocampal neural activity through miniature microscopes in male rats performing each of the two tasks, we uncover differences in the representation of space, and in the features of memory-based action planning. By also deploying optogenetic inactivation during navigational decision making, we find that hippocampal representations observed during the planning phase are necessary for solving the allocentric, but not the egocentric version of the task. Overall, our findings reveal a functional link between non-local hippocampal representations and allocentric navigation.

neuroscience↗

bioRxiv2025

Disrupted spatial and contextual memory encoding in the hippocampus of 5xFAD mice precedes cognitive impairment

Alzheimers disease (AD) is characterized by progressive memory decline, yet how hippocampal representations change at early AD stages remains largely unknown. In this study, we utilized a real-world head-fixed spatial alternation task combined with in vivo two-photon imaging to investigate hippocampal CA1 representations in 5xFAD mice. While 7-9 month old 5xFAD mice showed significant deficits in task learning, 2-4 month old mice performed normally, enabling assessment of hippocampal coding prior to behavioral decline. At this early stage, CA1 neurons exhibited intact global spatial encoding but demonstrated impaired task-related place cell representations. Contextual representations revealed by trajectory-dependent coding were weakened at both the population and single cell levels, accompanied by a notable shift from predominantly retrospective to more prospective encoding during behavioral choices. During task learning, longitudinally unstable place cells showed greater impairments in spatial coding, whereas stable place cells remained largely preserved in early-stage AD mice. Additionally, chemogenetic activation of basal forebrain cholinergic neurons increased spatial information and within-session stability, while promoting trajectory-dependent coding in these early-stage 5xFAD mice. Together, these findings reveal selective early impairments in hippocampal task-related spatial and contextual representations in AD that precede overt deficits in spatial alternation performance and remains amenable to cholinergic modulation.

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bioRxiv2024

Hierarchical Bayesian modeling of multi-region brain cell count data

We can now collect cell-count data across whole animal brains quantifying recent neuronal activity, gene expression, or anatomical connectivity. This is a powerful approach since it is a multi-region measurement, but because the imaging is done post-mortem, each animal only provides one set of counts. Experiments are expensive and since cells are counted by imaging and aligning a large number of brain sections, they are time-intensive. The resulting datasets tend to be under-sampled with fewer animals than brain regions. As a consequence, these data are a challenge for traditional statistical approaches. We present a standard partially-pooled Bayesian model for multi-region cell-count data and apply it to two example datasets. These examples demonstrate that hierarchical Bayesian methods are well suited to these data. In both cases the Bayesian model outperformed standard parallel t-tests. Overall, inference for cell-count data is substantially improved by the ability of the Bayesian approach to capture nested data and by its rigorous handling of uncertainty in under-sampled data.

neuroscience↗

bioRxiv2022

Two-photon targeted, quad whole-cell patch clamping robot

We present an automated quad-channel patch-clamp technology platform for ex vivo brain slice electrophysiology, capable of both blind and two-photon targeted robotically automated patching. The robot scales up the patch-clamp singlecell recording technique to four simultaneous channels, with seal success rates for two-photon targeted and blind modes of 54% and 68% respectively. In 50% of targeted trials (where specific cells were required), at least 2 simultaneous recordings were obtained. For blind mode, most trials yielded dual or triple recordings. This robot, a milestone on the path to a true in vivo robotic multi-patching technology platform, will allow numerous studies into the function and connectivity patterns of both primary and secondary cell types.

bioengineering↗

bioRxiv2020

Quadratic Mutual Information estimation of mouse dLGN receptive fields reveals asymmetry between ON and OFF visual pathways

The longstanding theory of "parallel processing" predicts that, except for a sign reversal, ON and OFF cells are driven by a similar pre-synaptic circuit and have similar visual field coverage, direction/orientation selectivity, visual acuity and other functional properties. However, recent experimental data challenges this view. Here we present an information theory based receptive field (RF) estimation method - quadratic mutual information (QMI) - applied to multi-electrode array electrophysiological recordings from the mouse dorsal lateral geniculate nucleus (dLGN). This estimation method provides more accurate RF estimates than the commonly used Spike-Triggered Average (STA) method, particularly in the presence of spatially correlated inputs. This improved efficiency allowed a larger number of RFs (285 vs 189 cells) to be extracted from a previously published dataset. Fitting a spatial-temporal Difference-of-Gaussians (ST-DoG) model to the RFs revealed that while the structural RF properties of ON and OFF cells are largely symmetric, there were some asymmetries apparent in the functional properties of ON and OFF visual processing streams - with OFF cells preferring higher spatial and temporal frequencies on average, and showing a greater degree of orientation selectivity.

neuroscience↗

bioRxiv2020

Place cells in head-fixed mice navigating a floating real-world environment

The hippocampal place cell system in rodents has provided a major paradigm for the scientific investigation of memory function and dysfunction. Place cells have been observed in area CA1 of the hippocampus of both freely moving animals, and of head-fixed animals navigating in virtual reality environments. However, spatial coding in virtual reality preparations has been observed to be impaired. Here we show that the use of a real-world environment system for head-fixed mice, consisting of a track floating on air, provides some advantages over virtual reality systems for the study of spatial memory. We imaged the hippocampus of head-fixed mice injected with the genetically encoded calcium indicator GCaMP6s while they navigated circularly constrained or open environments on the floating platform. We observed consistent place tuning in a substantial fraction of cells with place fields remapping when animals entered a different environment. When animals re-entered the same environment, place fields typically remapped over a time period of multiple days, faster than in freely moving preparations, but comparable with virtual reality. Spatial information rates were within the range observed in freely moving mice. Manifold analysis indicated that spatial information could be extracted from a low-dimensional subspace of the neural population dynamics. This is the first demonstration of place cells in head-fixed mice navigating on an air-lifted real-world platform, validating its use for the study of brain circuits involved in memory and affected by neurodegenerative disorders.

neuroscience↗

bioRxiv2020

A computational grid-to-place-cell transformation model indicates a synaptic driver of place cell impairment in early-stage Alzheimer's Disease

Alzheimers Disease (AD) is characterized by progressive neurodegeneration and cognitive impairment. Synaptic dysfunction is an established early symptom, which correlates strongly with cognitive decline, and is hypothesised to mediate the diverse neuronal network abnormalities observed in AD. However, how synaptic dysfunction contributes to network pathology and cognitive impairment in AD remains elusive. Here, we present a grid-cell-to-place-cell transformation model of long-term CA1 place cell dynamics to interrogate the effect of synaptic loss on network function and environmental representation. Synapse loss modelled after experimental observations in the APP/PS1 mouse model was found to induce firing rate alterations and place cell abnormalities that have previously been observed in AD mouse models, including enlarged place fields and lower across-session stability of place fields. Our results support the hypothesis that synaptic dysfunction underlies cognitive deficits, and demonstrate how impaired environmental representation may arise in the early stages of AD. We further propose that dysfunction of excitatory and inhibitory inputs to CA1 pyramidal cells may cause distinct impairments in place cell function, namely reduced stability and place map resolution. Author SummaryCognitive decline in Alzheimers Disease (AD) correlates most strongly with dysfunction and loss of synapses in affected brain regions. While synaptic dysfunction is a well-established early symptom of AD, how impaired synaptic transmission may lead to progressive cognitive decline, remains subject to active research. In this study, we examine the effect of synapse loss on neuronal network function using a computational model of place cells in the hippocampal network. Place cells encode a cognitive map of an animals environment, enabling navigation and spatial memory. This provides a useful indicator of cognitive function, as place cell function is well characterized and abnormalities in place cell firing have been shown to underlie navigational deficits in rodents. We find that synapse loss in our network is sufficient to produce progressive impairments in place cell function, which resemble those observed in mouse models of the disease, supporting the hypothesis that synaptic dysfunction may underlie the cognitive impairment in AD. Furthermore, we observe that loss of excitatory and inhibitory synapses produce distinct spatial impairments. Future experiments investigating the relative contribution of different synaptic inputs may thus allow new insights into the neuronal network alterations in AD and potentially enable the identification of new therapeutic targets.

neuroscience↗

bioRxiv2020

Subcellular resolution 3D light field imaging with genetically encoded voltage indicators

Light field microscopy (LFM) enables high signal-to-noise ratio (SNR), light efficient volume imaging at fast frame rates, and has been successfully applied to single-cell resolution functional neuronal calcium imaging. Voltage imaging with genetically encoded voltage indicators (GEVIs) stands to particularly benefit from light field microscopys volumetric imaging capability due to high required sampling rates, and limited probe brightness and functional sensitivity. Previous LFM studies have imaged GEVIs to track population-level interactions only in invertebrate preparations and without single cell resolution. Here we demonstrate sub-cellular resolution GEVI light field imaging in acute mouse brain slices resolving dendritic voltage signals localized in three dimensions. We characterize the effects of different light field reconstruction techniques on the SNR and signal localization and compare the SNR to fluorescence transients imaged in wide field. Our results demonstrate the potential of light field voltage imaging for studying dendritic integration and action potential propagation and backpropagation in 3 spatial dimensions.

neuroscience↗

bioRxiv2019

Bladder pressure encoding by near-independent fibre subpopulations - implications for decoding

ObjectiveWe aim at characterising the encoding of bladder pressure (intravesical pressure) by a population of sensory fibres. This research is motivated by the possibility to restore bladder function in elderly patients or after spinal cord injury using implanted devices, so called bioelectronic medicines. For these devices, nerve-based estimation of intravesical pressure can enable a personalized and on-demand stimulation paradigm, which will be more effective and efficient. In this context, a better understanding of the encoding strategies employed by the body might in the future be exploited by informed decoding algorithms that enable a precise and robust bladderpressure estimation. ApproachTo this end, we apply information theory to microelectrode-array recordings from the cat sacral dorsal root ganglion while filling the bladder, conduct surrogate data studies to augment the data we have, and finally decode pressure in a simple informed approach. Main resultsWe find an encoding scheme by different main bladder neuron types that we divide into three response types (slow tonic, phasic, and derivative fibres). We show that an encoding by different bladder neuron types, each represented by multiple cells, offers reliability through within-type redundancy and high information rates through near-independence of different types. Our subsequent decoding study shows a potentially more robust decoding from mean responses of homogeneous cell pools. SignificanceWe have here, for the first time, analysed the encoding of intravesical pressure by a population of sensory neurons in a principled way using information theory. We show that even a simple adapted decoder can exploit the redundancy in the population to be more robust against cell loss. This work thus paves the way towards principled encoding studies in the periphery and towards a new generation of informed peripheral nerve decoders for bioelectronic medicines.

bioengineering↗

bioRxiv2019

Neural ensemble activity depends on stimulus type in mouse primary visual cortex

Early cortical processing of visual information has long been investigated by describing the response properties such as receptive fields or orientation selectivity of individual neurons to moving gratings. However, thanks to recent technological advances, it has been become easier to record from larger neuronal populations which allow us to analyse the population responses to probe visual information processing at the population level. In the end, it is unlikely that sensory processing is a single-neuron effort but that of an entire population. Here we show how different stimulus types evoke distinct binary activity patterns (words) of simultaneous events on different sites in the anaesthetised mouse. Spontaneous activity and natural scenes indicated lower word distribution divergences than each to drifting gratings. Accounting for firing rate differences, spontaneous activity was linked to more unique patterns than stimulus-driven responses. Multidimensional scaling conveyed that pattern probability distributions clustered for spatial frequencies but not for directions. Further, drifting gratings modulated the Shannon entropy estimated on spatial patterns in a similar fashion as classical directional and spatial frequency tuning functions of neurons. This was supported by a distinct sublinear relationship between Shannon entropy and mean population firing rate.

neuroscience↗

bioRxiv2019

Temporo-nasally biased moving grating selectivity in mouse primary visual cortex

Orientation tuning in mouse primary visual cortex (V1) has long been reported to have a random or \"salt-and-pepper\" organisation, lacking the structure found in cats and primates. Laminar in-vivo multi-electrode array recordings here reveal previously elusive structure in the representation of visual patterns in the mouse visual cortex, with temporo-nasally drifting gratings eliciting consistently highest neuronal responses across cortical layers and columns, whilst upward moving gratings reliably evoked the lowest activities. We suggest this bias in direction selectivity to be behaviourally relevant as objects moving into the visual field from the side or behind may pose a predatory threat to the mouse whereas upward moving objects do not. We found furthermore that direction preference and selectivity was affected by stimulus spatial frequency, and that spatial and directional tuning curves showed high signal correlations decreasing with distance between recording sites. In addition, we show that despite this bias in direction selectivity, it is possible to decode stimulus identity and that spatiotemporal features achieve higher accuracy in the decoding task whereas spike count or population counts are sufficient to decode spatial frequencies implying different encoding strategies.\n\nSignificance statementWe show that temporo-nasally drifting gratings (i.e. opposite the normal visual flow during forward movement) reliably elicit the highest neural activity in mouse primary visual cortex, whereas upward moving gratings reliably evoke the lowest responses. This encoding may be highly behaviourally relevant, as objects approaching from the periphery may pose a threat (e.g. predators), whereas upward moving objects do not. This is a result at odds with the belief that mouse primary visual cortex is randomly organised. Further to this biased representation, we show that direction tuning depends on the underlying spatial frequency and that tuning preference is spatially correlated both across layers and columns and decreases with cortical distance, providing evidence for structural organisation in mouse primary visual cortex.

neuroscience↗