Biology subjects

Heimel, J. A.

Publications and source records attributed to Heimel, J. A..

12 recordsLinked to original sources

bioRxiv2026

Divisive normalization in mouse V1 is unchanged by increased thalamocortical short-term depression

Divisive normalization describes how neuronal responses are scaled by the activity of a broader pool of inputs and accounts for several nonlinear response properties in primary visual cortex (V1). It accurately describes contrast gain control, as well as the response to overlapping gratings. Nevertheless, how this computation is performed by the brain is unclear. One mechanism suggested to underlie divisive normalization in V1 is short-term depression (STD) at thalamocortical synapses. Here, we used a Vglut2-Cre dependent heterozygous deletion of Stxbp1 in mice as an in vivo model for increased STD. This enabled us to test whether STD is responsible for divisive normalization in V1. As expected, responses were shorter in the mutant mice compared to wild-type siblings. Although we did find other differences in visual responses, notably in direction selectivity and response linearity, neither the contrast response function, nor the amount of cross orientation suppression differed between the two groups. We conclude that STD is likely not involved in divisive normalization of visual responses in mouse V1. Instead, short-term plasticity shapes the temporal integration through which selective cortical responses are constructed.

neuroscience↗

bioRxiv2025

LatenZy, non-parametric, binning-free estimation of latencies from neural spiking data

Precisely estimating the onset of neural spiking responses and the timing at which activity begins to diverge between conditions is crucial for understanding temporal dynamics in brain information processing. Conventional methods require arbitrary parameter choices such as bin widths and response thresholds, limiting reproducibility and comparability. Here, we present latenZy and latenZy2, two non-parametric, binning-free methods that directly analyze spike times using cumulative statistics and iterative refinement, without assumptions about response shape. LatenZy estimates neuronal response onset latency, while latenZy2 detects when spiking activity diverges between conditions. We validate these methods on electrophysiological datasets from mouse and macaque visual cortex, and show that they outperform standard approaches in precision, robustness, sensitivity, and statistical power. LatenZy captures contrast-dependent latency shifts and hierarchical timing across visual areas, and latenZy2 reveals earlier attentional modulation in higher visual cortex consistent with top-down feedback. Together, they offer scalable, parameter-free tools for reliable latency estimation in large-scale neural recordings. Open-source implementations are available in Python and MATLAB.

neuroscience↗

bioRxiv2025

A multiomic network approach uncovers disease modifying mechanisms of inborn errors of metabolism

For many inborn errors of metabolism (IEM) the understanding of disease mechanisms remains limited in part explaining their unmet medical needs. We hypothesize that the expressivity of IEM disease phenotypes is affected by the activity of specific modifier pathways, which is controlled by rare and common polygenic variation. To identify these modulating pathways, we used RNA sequencing to generate molecular signatures of IEM in disease relevant tissues. We then integrated these disease signatures with multiomic data and gene regulatory networks generated from animal and human populations without overt IEM. We identified and subsequently validated glucocorticoid signaling as a candidate modifier of mitochondrial fatty acid oxidation disorders, and we re-capitulated complement signaling as a modifier of inflammation in Gaucher disease. Our work describes a novel approach that can overcome the rare disease-rare data dilemma, and reveal new IEM pathophysiology and potential drug targets using multiomics data in seemingly healthy populations. Take-home message: Multiomic data and gene regulatory networks derived from animal and human populations without overt IEM can be used to study disease mechanisms in inborn errors of metabolism.

genetics↗

bioRxiv2024

Structured neural fluctuations can generate noise invariance and inter-areal gating at distinct timescales

The brain processes, computes, and categorizes sensory input. But even in sensory brain areas, the relationship between input signals and neuronal spiking activity is complex and non-linear. Fast subsecond fluctuations in neuronal population responses dominate the temporal dynamics of neural circuits. Traditional approaches have treated this activity as "noise" that can be averaged away by taking the mean spiking rate over wide time bins or over multiple trial repetitions, but this ignores much of the temporal dynamics that naturally occur in neural systems. We find that subsecond flares of increased population activity are layer- and cell-type specific, and large-scale computational modelling suggests they may serve as an inter-areal gating mechanism. Moreover, we find that most of the neural variability is restricted to a population-gain axis. This observation explains why neural systems can function in the presence of excessive variability: population-level spiking dynamics generate invariance to the majority of neural noise.

neuroscience↗

bioRxiv2023

A new family of statistical tests for responses in point-event and time-series data for one- and two-sample comparisons

Quantifying whether and when signals are modulated by autonomous or external events is ubiquitous in the field of neuroscience. Existing statistical approaches, however, are not ideally suited to do this, especially when the signals under scrutiny show temporal autocorrelations. For example, a standard approach in the analysis of calcium imaging data is to use a t-test on predetermined time-windows to quantify whether neurons respond (differently) to an event of interest. While this is attractive because of its simplicity, only average signal differences can be detected. In practice, neurons often show complex response dynamics which are missed by conventional statistical tests. More advanced methods, such as bin-wise ANOVAs, do not share this drawback, but can suffer from high false-positive rates or "ghost correlations" when applied to temporally autocorrelated data. To solve this issue, we have developed three novel statistical tests extending the original ZETA-test to other use cases: 1) a test for time-series data; 2) a two-sample test to detect differences in neural responses between two conditions; and 3) a two-sample test to detect differences in time-series data between two conditions. In addition, we have improved upon the original ZETA-test. We show that our methods have a statistical sensitivity superior to t-tests and ANOVAs and work well with temporally autocorrelated data where other approaches fail. Our methods are widely applicable and we present example applications to Neuropixels data, two-photon GCaMP imaging data, and human electrocorticogram data. Open-source code for implementations in MATLAB and Python is available on GitHub and PyPi. Significance StatementNeurophysiology involves the detection of weak signals in a noisy background. Often these signals, as well as the background, are temporally autocorrelated. This means that many statistical methods, such as the ANOVA, are inappropriate. In some cases, these statistical tests produce "ghost" signals that mislead researchers into thinking there is an effect of their experiment, when in reality there is none. We have therefore developed a new family of statistical tests, the ZETA-tests, that are not negatively impacted by temporal autocorrelations. They do not use arbitrary (hyper)parameters, like bin size, and show superior statistical sensitivity compared to other methods like t-tests and ANOVAs. We provide easy-to-use implementations and expect our methods to be useful for many neuroscientists from various disciplines.

neuroscience↗

bioRxiv2023

Spatiotemporal resonance in mouse primary visual cortex

Human primary visual cortex (V1) responds more strongly, or resonates, when exposed to [~]10, [~]15-20, [~]40-50 Hz rhythmic flickering light. Full-field flicker also evokes perception of hallucinatory geometric patterns, which mathematical models explain as standing-wave formations emerging from periodic forcing at resonant frequencies of the simulated neural network. However, empirical evidence for such flicker-induced standing waves in the visual cortex was missing. We recorded cortical responses to flicker in awake mice using high spatial resolution widefield imaging in combination with high temporal resolution glutamate-sensing fluorescent reporter (iGluSnFR). The temporal frequency tuning curves in the mouse V1 were similar to those observed in humans, showing a banded structure with multiple resonance peaks (8 Hz, 15 Hz, 33 Hz). Spatially, all flicker frequencies evoked responses in V1 corresponding to retinotopic stimulus location, but some evoked additional peaks. These flicker-induced cortical patterns displayed standing wave characteristics and matched linear wave equation solutions in an area restricted to the visual cortex. Taken together, the interaction of periodic traveling waves with cortical area boundaries leads to spatiotemporal activity patterns that may affect perception.

neuroscience↗

bioRxiv2023

Thalamic regulation of ocular dominance plasticity in adult visual cortex

Experience-dependent plasticity in the adult visual system is generally thought of as a cortical process. However, several recent studies have shown that perceptual learning or monocular deprivation can also induce plasticity in the adult dorsolateral geniculate nucleus (dLGN) of the thalamus. How plasticity in the thalamus and cortex interact in the adult visual system is ill understood. To assess the influence of thalamic plasticity on plasticity in primary visual cortex (V1), we made use of our previous finding that during the critical period, ocular dominance (OD) plasticity occurs in dLGN and requires thalamic synaptic inhibition. Using multielectrode recordings we find that this is also true in adult mice, and that in the absence of thalamic inhibition and plasticity, OD plasticity in adult V1 is absent. To study the influence of V1 on thalamic plasticity we silenced V1 and show that during the critical period, but not in adulthood, the OD shift in dLGN is partially caused by feedback from V1. We conclude that during adulthood, the thalamus plays an unexpectedly dominant role in experience-dependent plasticity in V1. Our findings highlight the importance of considering the thalamus as a potential source of plasticity in learning events that are typically thought of as cortical processes.

neuroscience↗

bioRxiv2023

Psycho-spatially distinct stressors prompt distinct behavioral strategies through a cell type-specific brain circuit

Adaptive behavioral responses to stressors are critical for survival. However, which brain areas orchestrate switching the appropriate stress responses to distinct contexts is an open question. This study aimed to identify the cell type-specific brain circuitry governing the selection of distinct behavioral strategies in response to stressors. Through novel mouse behavior paradigms, we observed distinct stressor-evoked behaviors in two psycho-spatially distinct contexts, characterized by stressors inside or outside the safe zone. The identification of brain regions activated in both conditions revealed the involvement of the dorsomedial hypothalamus (DMH). Further investigation using optogenetics, chemogenetics, and photometry uncovered that glutamatergic projections from the DMH to periaqueductal gray (PAG) mediated responses to inside-stressors, while GABAergic projections, particularly from tachykinin1-expressing neurons, played a crucial role in coping with outside-stressors. These findings elucidate the role of cell type-specific circuitry from the DMH to the PAG in shaping behavioral strategies in response to stressors. These findings have the potential to advance our understanding of fundamental neurobiological processes and inform the development of novel approaches for managing context-dependent and anxiety-associated pathological conditions such as agoraphobia and claustrophobia.

neuroscience↗

bioRxiv2022

Involvement of superior colliculus in complex figure detection of mice

Object detection is an essential function of the visual system. Although the visual cortex plays an important role in object detection, the superior colliculus can support detection when the visual cortex is ablated or silenced. Moreover, it has been shown that superficial layers of mouse SC (sSC) encode visual features of complex objects, and that this code is not inherited from the primary visual cortex. This suggests that mouse sSC may provide a significant contribution to complex object vision. Here, we use optogenetics to show that mouse sSC is causally involved in figure detection based on differences in figure contrast, orientation and phase. Additionally, our neural recordings show that in mouse sSC, image elements that belong to a figure elicit stronger activity than those same elements when they are part of the background. The discriminability of this neural code is higher for correct trials than incorrect trials. Our results provide new insight into the behavioral relevance of the visual processing that takes place in sSC.

neuroscience↗

bioRxiv2022

A universal pipeline for the alignment of electrode tracks with slice histology and electrophysiological data

Modern electrophysiological experiments in neuroscience typically measure the activity of hundreds of neurons across multiple brain regions. Each recorded neuron has to be assigned its correct area of origin, which can be estimated using histological reconstructions of electrode tracks. However, this approach has a limited accuracy with which the probe position can be determined. While some tools exist to assist in this process in mice, such tools are scarce for other species, such as rats or macaques. Moreover, even in mice, a more reliable brain area assignment may be achieved by using spiking response properties to delineate area boundaries along the recording probe. Here we present the Universal Probe Finder, which provides multi-species support for reconstructing a probes brain area per spike-sorted cluster or recording site. It can use various data formats and can calculate neuronal responsiveness to experimental interventions with only event times and spike times to provide further neurophysiological markers that simplify and improve the reliability of assigning brain areas to neurons. The program can be downloaded here: https://github.com/JorritMontijn/UniversalProbeFinder.

neuroscience↗

bioRxiv2020

A parameter-free statistical test that improves the detection of neuronal responsiveness

Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that 1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations; and 2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.

neuroscience↗

bioRxiv2020

Visual stimulus-specific habituation of innate defensive behaviour in mice

Innate defensive responses such as freezing or escape are essential for animal survival. Mice show defensive behaviour to stimuli sweeping overhead, like a bird cruising the sky. Here, we found that mice reduced their defensive freezing after sessions with a stimulus passing overhead repeatedly. This habituation is stimulus-specific, as mice freeze again to a novel shape. This allows us to investigate the invariances in the mouse visual system. The mice generalize over retinotopic location and over size and shape, but distinguish objects when they differ in both size and shape. Innate visual defensive responses are thus strongly influenced by previous experience as mice learn to ignore specific stimuli. This form of learning occurs at the level of a location-independent representation.

neuroscience↗