Biology subjects

Denman, D. J.

Publications and source records attributed to Denman, D. J..

9 recordsLinked to original sources

bioRxiv2025

Neural population dynamics of direct electrical stimulation of neocortex

Intracranial electrical stimulation is foundational in neuroscience and clinical neuromodulation, yet how applied electrical fields engage neural tissue and influences perception remains unclear. Using three orthogonal Neuropixels probes in mouse visual areas, we recorded extracellular voltages and spikes with sub-millisecond resolution in three dimensions around a stimulation source. The evoked potential extended asymmetrically and grew sub-linearly with amplitude, influenced by anatomical heterogeneity. Increasing amplitude increased the density, but not spatial extent, of directly responsive neurons, but fewer than 5% of neurons within the evoked potential were activated. Fast-spiking interneurons were recruited nearer the source, whereas pyramidal neurons showed anisotropic activation. Direct responses were polarity- and amplitude-selective. Sparse direct spiking drove large, asymmetric cortical responses and modulated >50% of neurons at higher amplitudes. Perceptually, mice weakly detected single pulses, and performance did not improve with amplitude. Thus, anatomy and spatiotemporal patterning--not spike counts--govern physiological and perceptual impact, informing biomimetic, multi-contact prostheses.

neuroscience↗

bioRxiv2025

Separable neural population representations are constructed from mixed single neuron selectivity in the mouse early visual system

Both sensory and non-sensory brain regions receive mixed inputs from single neurons which require decomposition and integration before proceeding through a processing hierarchy. Whether mixed input signals are used in biological neural networks to derive pure single neuron representations, or distributed as new population representations from mixed single neurons, is not clear. In this study, we measured the distribution of single neuron hue and luminance tuning in the dorsolateral geniculate nucleus (dLGN) and primary visual cortex (V1) of mice, as well as the information about and structure of hue and luminance representations in populations of hundred of simultaneously sampled neurons. We compare single neuron and population encoding to null models expected for random integration and extraction of pure categorical single neuron representation. Using both univariate and multivariate regression techniques, we consistently noted that tuning for hue and luminance, rather than clustering into categorical response structures, formed uniform distributions. While the distribution of single neuron selectivity varied across the thalamocortical circuit, we found no evidence of categorical tuning organization emerging in the hierarchy. Nevertheless, populations contained complete information, in either high-dimensional linear representations or low-dimensional non-linear representations. In summary, we find that as early as primary sensory cortex and thalamus single neurons that have mixed selectivity for hue and luminance form a high dimensional representation of those variables, which can be non-linearly embedded in multiple separable representations.

neuroscience↗

bioRxiv2025

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies

1In 1949, Donald Hebb proposed that groups of neurons that activate stereotypically form the organizational building blocks of perception, cognition, and behavior. Finding the structural underpinning of such assemblies has been technically challenging, due to a lack of large-scale structure-activity maps. Here, we analyze this relation using a novel dataset that links in vivo optical physiology to connectivity using postmortem elec-tron microscopy (EM). From the fluorescence traces, we extract neural assemblies from higher-order correlations in neural activity. Physiologically, we show that these assemblies exhibit properties consistent with Hebbs theory, including more reliable responses to repeated natural movie inputs than size-matched random ensembles and superior decoding of visual stimuli. Structurally, we find that neurons that participate in assemblies are significantly more integrated into the structural network than those that do not. Contrary to Hebbs original prediction, we do not observe a marked increase in the strength of monosynaptic excitatory connections between cells participating in the same assembly. However, we find significantly stronger indirect feed-forward inhibitory connections targeting cells in other assemblies. These results show that assemblies can be useful components of perception, and, surprisingly, they are delineated by mutual inhibition.

neuroscience↗

bioRxiv2024

Deciphering neuronal variability across states reveals dynamic sensory encoding

Influenced by factors such as brain states and behavior, neurons exhibit substantial response variability even to identical stimuli. Because these factors are non-stationary, they dynamically impact the fidelity of sensory processing. However, it remains unclear how their relative impact on neuronal variability evolves over time. To address this question, we designed an encoding model with latent states to partition visual cortical variability across three crucial categories of sources: internal brain dynamics, behavior, and external visual stimulus. Applying a hidden Markov model to the rhythmic patterns of cortical local field potentials, we consistently identified three distinct oscillation states. Each state revealed a unique variability profile and a consistent descending trend of stimulus modulation across the visual hierarchy. Regression models within each state revealed a dynamic composition of factors contributing to the observed spiking variability, with the primary influencing factor switching within seconds. In the state dominated by high-frequency oscillations, sensory inputs and behavior exerted the most influence on population dynamics. Conversely, internal brain activity explained most of the variance in the state dominated by low-frequency oscillations. This heterogeneity across states underscores the importance of partitioning variability over time, particularly when considering the dynamic influence of non-stationary factors on sensory processing.

neuroscience↗

bioRxiv2024

Incomplete remyelination via endogenous or therapeutically enhanced oligodendrogenesis is sufficient to recover visual cortical function

Myelin loss induces deficits in action potential propagation that result in neural dysfunction and contribute to the pathophysiology of neurodegenerative diseases, injury conditions, and aging. Because remyelination is often incomplete, better understanding endogenous remyelination and developing remyelination therapies that seek to restore neural function are clinical imperatives. Here, we used in vivo two-photon microscopy and electrophysiology to study the dynamics of endogenous and therapeutic-induced cortical remyelination and functional recovery after cuprizone-mediated demyelination in mice. We focused on the visual pathway, which is uniquely positioned to provide insights into structure-function relationships during de/remyelination. We show that endogenous remyelination is driven by recent oligodendrocyte loss and is highly efficacious following mild demyelination, but fails to restore the oligodendrocyte population when high rates of oligodendrocyte loss occur too quickly. Testing a novel thyromimetic compared to clemastine fumarate, we find it better enhances oligodendrocyte gain during remyelination and hastens recovery of neuronal function. Surprisingly, its therapeutic benefit was temporally restricted, and it acted exclusively following moderate to severe demyelination to eliminate endogenous remyelination deficits. However, complete remyelination is unnecessary as partial oligodendrocyte restoration was sufficient to recover visual neuronal function. These findings advance our understanding of remyelination and its impact on functional recovery to inform future therapeutic strategies.

neuroscience↗

bioRxiv2020

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of neurons in the brain. While these two modalities have distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging or electrophysiology. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging. This work explores which data transformations are most useful for explaining these modality-specific discrepancies. We show that the higher selectivity in imaging can be partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could not reconcile differences in responsiveness without sub-selecting neurons based on event rate or level of signal contamination. This suggests that differences in responsiveness more likely reflect neuronal sampling bias or cluster-merging artifacts during spike sorting of electrophysiological recordings, rather than flaws in event detection from fluorescence time series. This work establishes the dominant impacts of the two modalities respective biases on a set of functional metrics that are fundamental for characterizing sensory-evoked responses.

neuroscience↗

bioRxiv2019

Synergistic population encoding and precise coordinated variability across interlaminar ensembles in the early visual system

Sensory stimuli are represented by the joint activity of large populations of neurons across the mammalian cortex. Information in such responses is limited by trial-to-trial variability. Because that variability is not independent between neurons, it has the potential to improve or degrade the amount of sensory information in the population response. How visual information scales with population size remains an open empirical question. Here, we use Neuropixels to simultaneously record tens to hundreds of single neurons in primary visual cortex (V1) and lateral geniculate nucleus (LGN) of mice and estimate population information. We found a mix of synergistic and redundant coding: synergy predominated in small populations (2-12 cells) before giving way to redundancy. The shared variability of this coding regime included global shared spike count variability at longer timescales, layer specific shared spike count variability at finer timescales, and shared variability in spike timing (jitter) that linked ensembles that span layers. Such ensembles defined by their shared variability carry more information. Our results suggest fine time scale stimulus encoding may be distributed across physically overlapping but distinct ensembles in V1.

neuroscience↗

bioRxiv2019

A survey of spiking activity reveals a functional hierarchy of mouse corticothalamic visual areas

The mammalian visual system, from retina to neocortex, has been extensively studied at both anatomical and functional levels. Anatomy indicates the cortico-thalamic system is hierarchical, but characterization of cellular-level functional interactions across multiple levels of this hierarchy is lacking, partially due to the challenge of simultaneously recording activity across numerous regions. Here, we describe a large, open dataset (part of the Allen Brain Observatory) that surveys spiking from units in six cortical and two thalamic regions responding to a battery of visual stimuli. Using spike cross-correlation analysis, we find that inter-area functional connectivity mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas. Classical functional measures of hierarchy, including visual response latency, receptive field size, phase-locking to a drifting grating stimulus, and autocorrelation timescale are all correlated with the anatomical hierarchy. Moreover, recordings during a visual task support the behavioral relevance of hierarchical processing. Overall, this dataset and the hierarchy we describe provide a foundation for understanding coding and dynamics in the mouse cortico-thalamic visual system.

neuroscience↗

bioRxiv2017

Mouse hue and wavelength-specific luminance contrast sensitivity are non-uniform across visual space

Mammalian visual behaviors, as well as responses in the neural systems thought to underlie these behaviors, are driven by luminance and hue contrast. With tools for measuring activity in cell-type specific populations in the mouse during visual behavior gaining traction, it is important to define the extent of luminance and hue information that is behaviorally-accessible to the mouse. A non-uniform distribution of cone opsins in the mouse potentially complicates both luminance and hue sensitivity: opposing gradients of short (UV-shifted) and middle (blue/green) cone opsins suggest that hue discrimination and wavelength-specific luminance contrast sensitivity may differ depending on retinotopic location. Here we ask if, and how well, mice can discriminate color and wavelength-specific luminance across visuotopic space. We found that mice were able to discriminate hue, and were able to do so more broadly across visuotopic space than expected from the cone-opsin distribution. We also found wavelength-band specific differences in luminance sensitivity.

neuroscience↗