Biology subjects

Herman, P.

Publications and source records attributed to Herman, P..

14 recordsLinked to original sources

bioRxiv2025

Behavioral deficits and exacerbated hemodynamics during lifespan of a mouse model of late onset Alzheimer's disease expressing humanized APOEϵ4 and Trem2*R47H

Alzheimers Disease (AD) poses a significant global health challenge, being the most prominent cause of dementia with prevalence increasing as the population ages. While the majority of AD cases are late-onset (LOAD), current animal models predominantly represent the more aggressive, faster progressing early-onset AD (EOAD), limiting their ability in assessing early biomarkers and gaining deeper understanding of LOAD progression. This study explores a promising translatable model, the APOE4.TREM2 mouse, which combines the APOE4 allele and the Trem2 p.R47H mutation, both linked to increased AD risk in the human population. We performed behavioral phenotyping and measured hemodynamics in dorsal olfactory bulbs (dOB) during odor stimulation of the APOE4.TREM2 mouse line. Experimental evidence of olfactory dysfunction prior to clinical symptoms suggests the opportunity of utilizing smell testing and fMRI as tools for screening of AD, both for preclinical and clinical studies. Here we assess and confirm the translatability of the APOE4.TREM2 mouse LOAD model, reporting exacerbated anxiety, deficits in odor-based foraging and spatial memory, and exacerbated odor-evoked dOB intrinsic responses in an age-dependent manner.

neuroscience↗

bioRxiv2023

Ketamine Effects on Energy Metabolism, Functional Connectivity and Working Memory in Healthy Humans

Working memory (WM) is a crucial resource for temporary memory storage and the guiding of ongoing behavior. N-methyl-D-aspartate glutamate receptors (NMDARs) are thought to support the neural underpinnings of WM. Ketamine is an NMDAR antagonist that has cognitive and behavioral effects at subanesthetic doses. To shed light on subanesthetic ketamine effects on brain function, we employed a multimodal imaging design, combining gas-free calibrated functional magnetic resonance imaging (fMRI) measurement of oxidative metabolism (CMRO2), resting-state cortical functional connectivity assessed with fMRI, and WM-related fMRI. Healthy subjects participated in two scan sessions in a randomized, double-blind, placebo-controlled design. Ketamine increased CMRO2 and cerebral blood flow (CBF) in prefrontal cortex (PFC) and other cortical regions. However, resting-state cortical functional connectivity was not affected. Ketamine did not alter CBF-CMRO2 coupling brain-wide. Higher levels of basal CMRO2 were associated with lower task-related PFC activation and WM accuracy impairment under both saline and ketamine conditions. These observations suggest that CMRO2 and resting-state functional connectivity index distinct dimensions of neural activity. Ketamines impairment of WM-related neural activity and performance appears to be related to its ability to produce cortical metabolic activation. This work illustrates the utility of direct measurement of CMRO2 via calibrated fMRI in studies of drugs that potentially affect neurovascular and neurometabolic coupling.

neuroscience↗

bioRxiv2022

Functional network organization of the mouse cortex determined by wide-field fluorescence imaging shares some --but not all-- properties revealed with simultaneous fMRI-BOLD

Work in humans and animals shows that the brain can be decomposed into large-scale functional networks. Whereas most studies, especially in humans, use the blood-oxygenation-level-dependent (BOLD) signal, the relationship between BOLD and neuronal activity is complex and incompletely understood. This limits our ability to interpret and apply measures derived from fMRI-BOLD. Here, we employ wide-field Ca2+ imaging simultaneously recorded with fMRI-BOLD in highly-sampled mice expressing GCaMP6f in excitatory neurons. These unique data enabled us to characterize the similarities and differences between networks discoverable by each modality. Importantly, we applied a network partitioning approach that uses a mixed-membership algorithm, which allows brain regions to participate in multiple networks with varying strengths. This contrasts with assuming regions belong to only one network. Our findings demonstrate that (1) most BOLD networks are detected via Ca2+ signals. (2) There is considerable overlapping--as opposed to disjoint--network organization that is evident from both modalities. (3) Large-scale networks determined by Ca2+ signals at low temporal frequencies (0.01 - 0.5 Hz)--as opposed to higher frequencies (0.5 - 5 Hz)--are more similar to those determined by BOLD. (4) Despite many similarities, differences emerge across modes including the spatial distribution of membership diversity (the extent to which regions affiliate with multiple networks). In sum, Ca2+ imaging of excitatory neurons confirms that the mouse cortex is functionally organized into overlapping large-scale networks in a manner that reflects many, but not all, properties observable with simultaneous fMRI-BOLD; affirming the neural origins of patterns of brain organization that are evident in a clinically accessible neuroimaging modality.

neuroscience↗

bioRxiv2022

A preprocessing and functional connectivity analysis pipeline for mesoscale calcium imaging

To improve bench-to-bedside translation, it is integral that knowledge flow bidirectionally--from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data--an emerging mode applicable in animal models--as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.

neuroscience↗

bioRxiv2022

StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows comparison with invasive or terminal procedures. To date, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. We introduce StandardRat, a consensus rat functional MRI acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired in rats from 46 centers. We developed a reproducible pipeline for the analysis of rat data acquired with diverse protocols and determined experimental and processing parameters associated with a more robust functional connectivity detection. We show that the standardized protocol enhances biologically plausible functional connectivity patterns, relative to pre-existing acquisitions. The protocol and processing pipeline described here are openly shared with the neuroimaging community to promote interoperability and cooperation towards tackling the most important challenges in neuroscience.

neuroscience↗

bioRxiv2021

Traces of semantization - from episodic to semantic memory in a spiking cortical network model

Episodic memory is the recollection of past personal experiences associated with particular times and places. This kind of memory is commonly subject to loss of contextual information or "semantization", which gradually decouples the encoded memory items from their associated contexts while transforming them into semantic or gist-like representations. Novel extensions to the classical Remember/Know behavioral paradigm attribute the loss of episodicity to multiple exposures of an item in different contexts. Despite recent advancements explaining semantization at a behavioral level, the underlying neural mechanisms remain poorly understood. In this study, we suggest and evaluate a novel hypothesis proposing that Bayesian-Hebbian synaptic plasticity mechanisms might cause semantization of episodic memory. We implement a cortical spiking neural network model with a Bayesian-Hebbian learning rule called Bayesian Confidence Propagation Neural Network (BCPNN), which captures the semantization phenomenon and offers a mechanistic explanation for it. Encoding items across multiple contexts leads to item-context decoupling akin to semantization. We compare BCPNN plasticity with the more commonly used spike-timing dependent plasticity (STDP) learning rule in the same episodic memory task. Unlike BCPNN, STDP does not explain the decontextualization process. We also examine how selective plasticity modulation of isolated salient events may enhance preferential retention and resistance to semantization. Our model reproduces important features of episodicity on behavioral timescales under various biological constraints whilst also offering a novel neural and synaptic explanation for semantization, thereby casting new light on the interplay between episodic and semantic memory processes.

neuroscience↗

bioRxiv2021

Decreased overall neuronal activity in a rodent model of impaired consciousness during absence seizures

Absence seizures are characterized by a brief behavioural impairment including apparent loss of consciousness. Neuronal mechanisms determining the behavioural impairment of absence seizures remain unknown, and their elucidation might highlight therapeutic options for reducing seizure severity. However, recent studies have questioned the similarity of animal spike-wave-discharges (SWD) to human absence seizures both behaviourally and neuronally. Here, we report that Genetic Absence Epilepsy Rats from Strasbourg recapitulate the decreased neuroimaging signals and loss of consciousness characteristic of human absence seizures. Overall neuronal firing is decreased but rhythmic in the somatosensory cortex and thalamus during these seizures. Interestingly, individual neurons in both regions tend to consistently express one of four distinct patterns of seizure-associated activity. These patterns differ in firing rate dynamics and in rhythmicity during seizure. One group of neurons showed a transient initial peak in firing at SWD onset, accounting for the brief initial increase in overall neuronal firing seen in cortex and thalamus. The largest group of neurons in both cortex and thalamus showed sustained decreases in firing during SWD. Other neurons showed either sustained increases or no change in firing. These findings suggest that certain classes of cortical and thalamic neurons may be particularly responsible for the paroxysmal oscillations and consequent loss of consciousness in absence epilepsy.

neuroscience↗

bioRxiv2021

A Hot-Coal theory of Working Memory

Working memory (WM) allows us to selectively remember and flexibly control a limited amount of information. Earlier work has suggested WM control is achieved by interactions between bursts of beta and gamma oscillations. The emerging question is how beta and gamma bursting, reflecting coherent activity of hundreds of thousands of neurons, can underlie selective control of individual items held in WM? Here, we propose a principle for how such selective control might be achieved on the neural network level. It relies on spatial computing, which suggests that beta and gamma interactions cause item-specific activity to flow spatially across the network over the course of a task. This way, control-related information about, for instance, item order can be retrieved from the spatial activity independent of the detailed recurrent connectivity that gives rise to the item-specific activity itself. The spatial flow should in turn be reflected in low-dimensional activity shared by many neurons. We test predictions of the proposed spatial computing paradigm by analysing control-related as well as item-specific activity in local field potentials and neuronal spiking from prefrontal cortex of rhesus macaques performing four WM tasks. As predicted, we find that the low-dimensional activity has a spatial component from which we can read out control-related information. These spatial components were stable over multiple sessions and did not depend on the specific WM items being used. We hypothesize that spatial computing can facilitate generalization and zero-shot learning by utilizing spatial component as an additional information encoding dimension. This offers a new perspective on the functional role of low-dimensional activity that tends to dominate cortical activity.

neuroscience↗

bioRxiv2020

NSC348884 cytotoxicity is not mediated by inhibition of nucleophosmin oligomerization

Oligomerization of the nucleolar phosphoprotein nucleophosmin (NPM) is mediated by its N-terminal domain. In acute myeloid leukemia, a frequent NPM mutation occurring at the C-terminus causes NPM delocalization to the cytoplasm. Due to formation of NPM heterooligomers, the wild-type NPM as well as many of NPM interaction partners are also delocalized. Proper localization and function of mislocalized proteins in the cells with mutated NPM may be restored by targeting NPM oligomerization. We introduce a reliable set of complementary methods for monitoring NPM oligomerization in both cell lysates and live cells. Using this methodological background we show that a putative inhibitor of NPM oligomerization, NSC348884, does not prevent formation of NPM oligomers in leukemia cells. Instead, we reveal that the observed cytotoxic effect of NSC348884 is associated with changes in cell adhesion signaling.

cell biology↗

bioRxiv2020

Delivery mode impacts newborn gut colonization efficiency

Delivery mode is the variable with the greatest influence on the infant gut microbiome composition in the first few months of life. Children born by Cesarean section (C-section) lack species from the Bacteroides genus in their gut microbial community, and this difference can be detectable until 6-18 months of age. One hypothesis is that these differences stem from lack of exposure to the maternal vaginal microbiome, as children born by C-section do not pass through the birth canal; however, Bacteroides species are not common members of the vaginal microbiome, thus this explanation seems inadequate. Here, we set out to re-evaluate this hypothesis by collecting rectal and vaginal samples before delivery from 73 mothers with paired stool from their infants in the first two weeks of life. We compared microbial profiles of infants born by planned, pre-labor C-section to those born by emergent, post-labor surgery (where the child was in the birth canal, but eventually delivered through an abdominal incision), and found no significant differences in the microbiome between these two groups. Both groups showed the characteristic signature lack of Bacteroides species, despite their difference in exposure to the birth canal. Surprisingly, this signature was only evident in samples from week two of life, but not in the first week. Children born by C-section often had high abundance of Bacteroides in their first few days of life, but these were not stable colonizers of the infant gut, as they were not detectable by week two. Finally, we used metagenomic sequencing to compare microbial strains in maternal vaginal and rectal samples and samples from their infants; we found evidence for mother-to-child transmission of rectal rather than vaginal strains. These results challenge birth canal exposure as the dominant factor in infant gut microbiome establishment and implicate colonization efficiency rather than exposure as a dictating factor of the newborn gut microbiome composition.

microbiology↗

bioRxiv2019

Probabilistic associative learning suffices for learning the temporal structure of multiple sequences

AO_SCPLOWBSTRACTC_SCPLOWMany brain phenomena both at the cognitive and behavior level exhibit remarkable sequential characteristics. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-scale, in this work we attempt to characterize to what degree some of this properties can be explained as a consequence of simple associative learning. To this end, we employ a parsimonious firing-rate attractor network equipped with the Hebbian-like Bayesian Confidence Propagating Neural Network (BCPNN) learning rule relying on synaptic traces with asymmetric temporal characteristics. The proposed network model is able to encode and reproduce temporal aspects of the input, and offers internal control of the recall dynamics by gain modulation. We provide an analytical characterisation of the relationship between the structure of the weight matrix, the dynamical network parameters and the temporal aspects of sequence recall. We also present a computational study of the performance of the system under the effects of noise for an extensive region of the parameter space. Finally, we show how the inclusion of modularity in our network structure facilitates the learning and recall of multiple overlapping sequences even in a noisy regime.

neuroscience↗

bioRxiv2018

Spanning spatiotemporal scales with simultaneous mesoscopic Ca2+ imaging and functional MRI

Neuroscience encompasses the investigation of brain function across multiple spatiotemporal scales. Yet, most research is confined to Ca2+ one spatiotemporal milieu limiting the integration of knowledge across scales. Here we describe an imaging and analytic approach that spans spatiotemporal scales by combining simultaneous wide field mesoscopic 1-photon Ca2+ imaging and functional magnetic resonance imaging (fMRI) at 11.7T. Given the confined space within the magnet, that metal is prohibited, and the unique/conflicting needs of each methodology, these techniques have never before been combined. In addition to describing the new hardware and software, we present evoked and spontaneous activity measurements made in lightly anesthetized animals. We have three findings: (1) for both evoked and spontaneous activity the magnitude of the Ca2+ and fMRI signals show correspondence, (2) connectivity matrices derived from Ca2+ and fMRI measurements are stable throughout an imaging session, and (3) there is correspondence between Ca2+ and fMRI spontaneous activity patterns.

neuroscience↗

bioRxiv2018

Fast Hebbian Plasticity explains Working Memory and Neural Binding

Working memory (WM) is a key component of human memory and cognition. Computational models have been used to study the underlying neural mechanisms, but neglected the important role of short- and long-term memory interactions (STM, LTM) for WM. Here, we investigate these using a novel multi-area spiking neural network model of prefrontal cortex (PFC) and two parieto-temporal cortical areas based on macaque data. We propose a WM indexing theory that explains how PFC could associate, maintain and update multi-modal LTM representations. Our simulations demonstrate how simultaneous, brief multi-modal memory cues could build a temporary joint memory representation as an \"index\" in PFC by means of fast Hebbian synaptic plasticity. This index can then reactivate spontaneously and thereby reactivate the associated LTM representations. Cueing one LTM item rapidly pattern-completes the associated un-cued item via PFC. The PFC-STM network updates flexibly as new stimuli arrive thereby gradually over-writing older representations.

neuroscience↗

bioRxiv2017

Gamma and beta bursts during working memory read-out suggest roles in its volitional control

Working memory (WM) activity is not as stationary or sustained as previously thought. There are brief bursts of gamma ([~]55-120 Hz) and beta ([~]20-35 Hz) oscillations, the former linked to stimulus information in spiking. We examine these dynamics in relation to read-out from WM, which is still not well understood. Monkeys held a sequence of two objects and had to decide if they matched a subsequent sequence. Changes in the balance of beta/gamma suggested their role in WM control. In anticipation of having to use an object for the match decision, there was an increase in spiking information about that object along with an increase in gamma and a decrease in beta. When an object was no longer needed, beta increased and gamma as well as spiking information about that object decreased. Deviations from these dynamics predicted behavioral errors. Thus, turning up or down beta could regulate gamma and the information in working memory.

neuroscience↗