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Garrett, M.

Publications and source records attributed to Garrett, M..

At least 19 recordsLinked to original sources

Map of spiking activity underlying change detection in the mouse visual system

Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here we present a database of spiking activity across the mouse visual system--including thalamus, cortex, and midbrain--while mice perform an image change detection task. Using Neuropixels probes, we record from >75,000 high-quality units in 54 mice, mapping area-, cortical layer-, and cell type-specific coding of sensory and motor information. Modulation by task-engagement increased across the thalamocortical hierarchy but was strongest in the midbrain. Novel images modulated cortical (but not thalamic) responses through delayed recurrent activity. Population decoding and optogenetics identified a critical decision window for change detection and revealed that mice use an adaptation-based rather than image-comparison strategy. This comprehensive resource provides a valuable substrate for understanding sensorimotor computations in neural networks.

neuroscience↗

Diverse ssRNA viruses associated with Karenia brevis harmful algal blooms in Southwest Florida

Harmful algal blooms (HABs) caused by the dinoflagellate Karenia brevis frequently occur in the eastern Gulf of Mexico, where they negatively impact the environment, human health, and economy. Very little is known about viruses associated with K. brevis blooms, although viral infection of other HAB-forming phytoplankton species can play an important role in bloom dynamics. We used viral metagenomics to identify viruses in 11 pooled seawater samples collected from Southwest Florida, USA in 2021 during a severe, spatiotemporally dynamic K. brevis bloom. Assembled viral genomes were similar to published genomes from the order Picornavirales, family Marnaviridae, and genera Sogarnavirus, Bacillarnavirus, and Marnarnavirus. Viruses from these groups infect bloom-forming diatoms (Chaetoceros sp. and Rhizosolenia setigera) and the raphidophyte Heterosigma akashiwo. We also recovered unclassified Riboviria genomes related to a Symbiodinium positive-sense ssRNA virus sequenced from coral dinoflagellate symbionts. Reverse-transcriptase PCR assays were performed to monitor the occurrence of seven representative virus genomes in these 2021 samples and 43 seawater samples collected during a subsequent, typical bloom between November 2022 and May 2023. Over half of the samples contained multiple viruses, and at least one viral genome was detected in 44 of 54 samples, collected across seasons and years, highlighting the ubiquity of these viruses in this region. Alpha diversity was highest in the summer months and positively correlated with K. brevis cell counts. Multiple regression revealed month and the presence of unclassified Riboviria sequences most similar to dinoflagellate viruses as significant predictors of K. brevis cellular abundance. ImportanceHarmful algal blooms caused by the dinoflagellate Karenia brevis negatively impact the tourism, fisheries, and public health sectors. Anticipated impacts of climate change, nutrient pollution, and ocean acidification may sustain and/or exacerbate K. brevis blooms in the future, underscoring the need for proactive monitoring, communication, and mitigation strategies. This study represents a pioneering effort in monitoring viruses associated with K. brevis blooms. The findings lay the groundwork for studying the effects of environmental drivers on K. brevis blooms and their associated viruses, as well as for exploring the roles of viruses in bloom dynamics and potential applications of viruses as biocontrol agents for K. brevis blooms. Furthermore, the comparison of viral dynamics relative to local and regional bloom dynamics in this study helps inform future monitoring and modeling needs.

microbiology↗

CPI203, a BET inhibitor, down-regulates a consistent set of DNA synthesis genes across a wide array of glioblastoma lines.

IntroductionGlioblastomas utilize malignant gene expression pathways to drive growth. Many of these gene pathways are not directly accessible with molecularly targeted pharmacological agents. Chromatin-modifying compounds can alter gene expression and target glioblastoma growth pathways. In this study, we utilize a systematic screen of chromatin-modifying compounds on a panel of patient-derived glioblastoma lines to identify promising compounds and their associated gene targets. MethodsFive glioblastoma cell lines were subjected to a drug screen of 106 chromatin-modifying compounds representing 36 unique drug classes to determine the twelve most promising drug classes and the best candidate inhibitors in each class. These twelve drugs were then tested with a panel of twelve patient-derived gliomasphere lines to identify growth inhibition and corresponding gene expression patterns. Overlap analysis and weighted co-expression network analysis (WCGNA) were utilized to determine potential target genes and gene pathways. ResultsThe initial drug screen identified twelve candidate pharmacologic agents for further testing. Drug sensitivity testing indicated an overall high degree of variability between gliomasphere lines. However, CPI203 was the most consistently effective compound, and the BET inhibitor class was the most consistently effective class of compounds across the gliomasphere panel. Correspondingly, most of the compounds tested had highly variable effects on gene expression between gliomasphere lines. CPI203 stood out as the only compound to induce a consistent effect on gene expression across different gliomasphere lines, specifically down-regulation of DNA-synthesis genes. Amongst the twelve tested cell lines, high expression of CDKN2A and CDKN2B distinguished more drug sensitive from more drug resistant lines. WCGNA identified two oncogenic gene modules (FBXO5 and MELK) that were effectively downregulated by CPI203 (FBXO5) and ML228 (FBXO5 and MELK). ConclusionsThe bromodomain inhibitor CPI203 induced relatively consistent effects on gene expression and growth across a variety of glioblastoma lines, specifically down-regulating genes associated with DNA replication. We propose that clinically effective BET inhibitors have the potential to induce consistent beneficial effects across a spectrum of glioblastomas.

cancer biology↗

Resistance patterns in drug-adapted cancer cell lines reflect complex evolution in clinical tumors

BackgroundHere, we introduce a novel set of triple-negative breast cancer (TNBC) cell lines consisting of MDA-MB-468, HCC38, and HCC1806 and their sublines adapted to cisplatin, doxorubicin, eribulin, paclitaxel, gemcitabine, or 5-fluorouracil. MethodsThe cell lines were characterized by whole exome sequencing and the determination of drug-response profiles. Moreover, genes harbouring resistance-associated mutations were investigated using TCGA data for potential clinical relevance. ResultSequencing combined with TCGA-derived patient data resulted in the identification of 682 biomarker candidates in the pan-cancer analysis. Thirty-five genes were considered the most promising candidates because they harboured resistance-associated variants in at least two resistant sublines, and their expression correlated with TNBC patient survival. Exome sequencing and response profiles to cytotoxic drugs and DNA damage response inhibitors identified revealed remarkably little overlap between the resistant sublines, suggesting that each resistance formation process follows a unique route. All of the drug-resistant TNBC sublines remained sensitive or even displayed collateral sensitivity to a range of tested compounds. Cross-resistance levels were lowest for the CHK2 inhibitor CCT241533, the PLK1 inhibitor SBE13, and the RAD51 recombinase inhibitor B02, suggesting that CHK2, PLK1, and RAD51 are potential drug targets for therapy-refractory TNBC. ConclusionsWe present novel preclinical models of acquired drug resistance in TNBC and many novel candidate biomarkers for further investigation. The finding that each cancer cell line adaptation process follows an unpredictable route reflects recent findings on cancer cell evolution in patients, supporting the relevance of drug-adapted cancer cell lines as preclinical models of acquired resistance.

cancer biology↗

De novo lipogenesis pathway is a vulnerability in IDH1 mutant glioma

Histone deacetylases (HDACs) have a wide range of targets and can rewire both the chromatin and lipidome of cancer cells. In this study, we show that valproic acid (VPA), a brain penetrant anti-epileptic and histone deacetylase inhibitor, inhibits the growth of IDH1 mutant tumors in vivo and in vitro, with at least some selectivity over IDH1 wild type tumors. Surprisingly, genes upregulated by VPA showed no change in chromatin accessibility at the promoter, but there was a correlation between VPA downregulated genes and diminished promoter chromatin accessibility. VPA inhibited the transcription of lipogenic genes and these lipogenic genes showed significant decrease in promoter chromatin accessibility only in the IDH1 MT glioma cell lines tested. VPA targeted a key lipogenic gene, fatty acid synthase (FASN), via inhibition of the mTOR pathway and both VPA and a selective FASN inhibitor TVB-2640 rewired the lipidome and promoted apoptosis in an IDH1 MT but not in an IDH1 WT glioma cell line. We further find HDACs are involved in the regulation of lipogenic genes and in particular HDAC6 is important for regulation of FASN in IDH1 MT glioma. Finally, we show that FASN knockdown alone and VPA in combination with FASN knockdown significantly improved the survival of mice in a IDH1 MT primary orthotopic xenograft model in vivo. We conclude that targeting fatty acid metabolism through HDAC inhibition and/or FASN inhibition may be a novel therapeutic option in IDH1 mutant gliomas.

cancer biology↗

Coordinated changes in a cortical circuit sculpt effects of novelty on neural dynamics

Recent studies have found dramatic cell-type specific responses to stimulus novelty, highlighting the importance of analyzing the cortical circuitry at the cell-type specific level of granularity to understand brain function. Although initial work classified and characterized activity for each cell type, the specific alterations in cortical circuitry--particularly when multiple novelty effects interact--remain unclear. To address this gap, we employed a large-scale public dataset of electrophysiological recordings in the visual cortex of awake, behaving mice using Neuropixels probes and designed population network models to investigate the observed changes in neural dynamics in response to a combination of distinct forms of novelty. The model parameters were rigorously constrained by publicly available structural datasets, including multi-patch synaptic physiology and electron microscopy data. Our systematic optimization approach identified tens of thousands of model parameter sets that replicate the observed neural activity. Analysis of these solutions revealed generally weaker connections under novel stimuli, as well as a shift in the balance e between SST and VIP populations. Along with this, PV and SST populations experienced overall more excitatory influences compared to excitatory and VIP populations. Our results also highlight the role of VIP neurons in multiple aspects of visual stimulus processing and altering gain and saturation dynamics under novel conditions. In sum, our findings provide a systematic characterization of how the cortical circuit adapts to stimulus novelty by combining multiple rich public datasets.

neuroscience↗

Genome-wide association study and sequence similarity analysis for unilateral renal agenesis using heterogeneous stock rats undercovers the KIT gene and AHR, ATF3, GATA3, HNF1B, POU2F2, and TFCP2 transcription factors as potential candidates to explain incomplete penetrance

1Human unilateral renal agenesis is a congenital urinary tract malformation. Affected individuals have only one kidney, which is often an asymptomatic developmental defect. A total of 5,585 male and female HS rats were assessed for unilateral renal agenesis and genotyped for 3513,321 markers. The R package SAIGEgds was used for the association analysis. The adjusted p-value threshold for the association analysis determined by permutation was equal to 5.6 (-log10). Two additional datasets were used as validation tests. Population two included 1,577 rats genotyped for 7,425,889 markers and a case-control imbalance equal to 1:174; population three included 1,407 rats, genotyped for 254,932 markers and case-control ratio equal to 1:38. The python package GxTheta was used to perform a polygenic epistasis analysis for the analyzed HS rat population. A founder haplotype mosaic determination was performed using the R package QTL2. Associated regions were selected for further analysis, including long-read PacBio sequencing for founder individuals and a founder haplotype prediction test. A similarity analysis at a genomic level and for loci encoding transcription factors predicted to interact with selected sequences inside the associated loci were accomplished. A total of 1,181 polymorphisms were associated with URA. All associated polymorphisms were located on chromosome 14 between 32.9 and 36.6 Mb. The most significant polymorphism was chr14:36,411,266, a G/T transversion. The same associated region was identified in population three. Polygenic epistasis was determined as not predominant for the presentation of URA. Based on the haplotype mosaic probability estimation, cases display a higher probability of inheriting the ACI allele. The long-read sequencing analysis showed the presence of an Erv insertion inside the intron one of the KIT gene located inside the associated region. The Erv insertion comprises one Erv sequence and two Ltr sequences located downstream and upstream of the former. No Erv insertion was identified for the founder strain BN. For ACI and HSRA, only one Ltr sequence was identified. One hundred and seven genes encoding TFs that recognize binding sites on the Erv insertion were analyzed for sequence similarity against the reference HSRA. The TF similarity score analysis for the interaction genotype and phenotype showed significance after FDR correction for 20 TFs, including AHR, HNF1B, JUNB, RARG, and RXRA. A mechanism identifying URA as a threshold phenotype is suggested in HS rats. It implies the existence of a minimum threshold for the final number of nephrons and kidney associated structures required for stalling the apoptotic process of the metanephric rudiments. Animals exhibiting a quantitative cumulative defect would express URA, being this malformation identified as a phenotype with decreased penetrance in the assessed population of HS rats. All these processes are described as mediated by KIT and TFs able to interact with sequences of the Erv insertion.

genetics↗

Familiarity-modulated synapses model visual cortical circuit novelty responses

Since environments are constantly in flux, the brains ability to identify novel stimuli that fall outside its own internal representation of the world is crucial for an organisms survival. Within the mammalian neocortex, inhibitory microcircuits are proposed to regulate activity in an experience-dependent manner and different inhibitory neuron subtypes exhibit distinct novelty responses. Discerning the function of diverse neural circuits and their modulation by experience can be daunting unless one has a biologically plausible mechanism to detect and learn from novel experiences that is both understandable and flexible. Here we introduce a learning mechanism, familiarity modulated synapses (FMSs), through which a network response that encodes novelty emerges from unsupervised multiplicative synaptic modifications depending only on the presynaptic or both the pre- and postsynaptic activity. FMSs stand apart from other familiarity mechanisms in their simplicity: they operate under continual learning, do not require specialized architecture, and can distinguish novelty rapidly without requiring feedback. Implementing FMSs within an experimentally-constrained model of a visual cortical circuit, we demonstrate the generalizability of FMSs by reproducing three distinct novelty effects recently observed in experiments: absolute, contextual (or oddball), and omission novelty. Additionally, our model reproduces functional diversity within cell subpopulations, leading to experimentally testable predictions about connectivity and synaptic dynamics that can produce both population-level novelty responses and heterogeneous individual neuron signals. Altogether, our findings demonstrate how simple plasticity mechanisms within the cortical circuit structure can give rise to qualitatively distinct novelty responses. The flexibility of FMSs opens the door to computationally and theoretically investigating how distinct synapse modulations can lead to a variety of experience-dependent responses in a simple, understandable, and biologically plausible setup.

neuroscience↗

Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex

In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model we find individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find the diversity of neural correlates of strategy can be understood parsimoniously as increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy which facilitates task appropriate responses.

neuroscience↗

Stimulus novelty uncovers coding diversity in visual cortical circuits

Detecting novel stimuli in the environment is critical for learning and survival, yet the neural basis of novelty processing is not understood. To characterize cell type-specific novelty processing, we surveyed the activity of [~]15,000 excitatory and inhibitory neurons in mice performing a visual task with novel and familiar stimuli. Clustering revealed a dozen functional neuron types defined by experience-dependent encoding. Vasoactive-intestinal-peptide (Vip) expressing inhibitory neurons were diverse, encoding novel stimuli, omissions of familiar stimuli, or behavioral features. Distinct Somatostatin (Sst) expressing inhibitory neurons encoded either familiar or novel stimuli. Subsets of excitatory neurons co-clustered with specific Vip or Sst subpopulations, while Sst and Vip inhibitory clusters were non-overlapping. This study establishes that novelty processing is mediated by diverse functional neuron types in the visual cortex.

neuroscience↗

The Geometry of Representational Drift in Natural and Artificial Neural Networks

Neurons in sensory areas encode/represent stimuli. Surprisingly, recent studies have suggested that, even during persistent performance, these representations are not stable and change over the course of days and weeks. We examine stimulus representations from fluorescence recordings across hundreds of neurons in the visual cortex using in vivo two-photon calcium imaging and we corroborate previous studies finding that such representations change as experimental trials are repeated across days. This phenomenon has been termed "representational drift". In this study we geometrically characterize the properties of representational drift in the primary visual cortex of mice in two open datasets from the Allen Institute and propose a potential mechanism behind such drift. We observe representational drift both for passively presented stimuli, as well as for stimuli which are behaviorally relevant. Across experiments, the drift most often occurs along directions that have the most variance, leading to a significant turnover in the neurons used for a given representation. Interestingly, despite this significant change due to drift, linear classifiers trained to distinguish neuronal representations show little to no degradation in performance across days. The features we observe in the neural data are similar to properties of artificial neural networks where representations are updated by continual learning in the presence of dropout, i.e. a random masking of nodes/weights, but not other types of noise. Therefore, we conclude that a potential reason for the representational drift in biological networks is driven by an underlying dropout-like noise while continuously learning and that such a mechanism may be computational advantageous for the brain in the same way it is for artificial neural networks, e.g. preventing overfitting.

neuroscience↗

Towards personalized auditory models: predicting individual sensorineural-hearing-loss profiles from recorded human auditory physiology

Over the past decades, different types of auditory models have been developed to study the functioning of normal and impaired auditory processing. Several models can simulate frequency-dependent sensorineural hearing loss (SNHL), and can in this way be used to develop personalized audio-signal processing for hearing aids. However, to determine individualized SNHL profiles, we rely on indirect and non-invasive markers of cochlear and auditory-nerve (AN) damage. Our progressive knowledge of the functional aspects of different SNHL subtypes stresses the importance of incorporating them into the simulated SNHL profile, but has at the same time complicated the task of accomplishing this on the basis of non-invasive markers. In particular, different auditory evoked potential (AEP) types can show a different sensitivity to outer-hair-cell (OHC), inner-hair-cell (IHC) or AN damage, but it is not clear which AEP-derived metric is best suited to develop personalized auditory models. This study investigates how simulated and recorded AEPs can be used to derive individual AN- or OHC-damage patterns and personalize auditory processing models. First, we individualized the cochlear-model parameters using common methods of frequency-specific OHC-damage quantification, after which we simulated AEPs for different degrees of AN-damage. Using a classification technique, we determined the recorded AEP metric that best predicted the simulated individualized CS profiles. We cross-validated our method using the dataset at hand, but also applied the trained classifier to recorded AEPs from a new cohort to illustrate the generalisability of the method.

bioengineering↗

Epitope profiling reveals binding signatures of SARS-CoV-2 immune response and cross-reactivity with endemic HCoVs

A major goal of current SARS-CoV-2 vaccine efforts is to elicit antibody responses that confer protection. Mapping the epitope targets of the SARS-CoV-2 antibody response is critical for innovative vaccine design, diagnostics, and development of therapeutics. Here, we developed a phage display library to map antibody binding sites at high resolution within the complete viral proteomes of all human-infecting coronaviruses in patients with mild or moderate/severe COVID-19. The dominant immune responses to SARS-CoV-2 were targeted to regions spanning the Spike protein, Nucleocapsid, and ORF1ab. Some epitopes were identified in the majority of samples while others were rare, and we found variation in the number of epitopes targeted by different individuals. We also identified a set of cross-reactive sequences that were bound by antibodies in SARS-CoV-2 unexposed individuals. Finally, we uncovered a subset of enriched epitopes from commonly circulating human coronaviruses with significant homology to highly reactive SARS-CoV-2 sequences.

immunology↗

Speech-in-noise intelligibility difficulties with age: the role of cochlear synaptopathy

Speech intelligibility declines with age and sensorineural hearing damage (SNHL). However, it remains unclear whether cochlear synaptopathy (CS), a recently discovered form of SNHL, significantly contributes to this issue. CS refers to damaged auditory-nerve synapses that innervate the inner hair cells and there is currently no go-to diagnostic test available. Furthermore, age-related hearing damage can comprise various aspects (e.g., hair cell damage, CS) that each can play a role in impaired sound perception. To explore the link between cochlear damage and speech intelligibility deficits, this study examines the role of CS for word recognition among older listeners. We first validated an envelope-following response (EFR) marker for CS using a Budgerigar model. We then applied this marker in human experiments, while restricting the speech materials frequency content to ensure that both the EFR and the behavioral tasks engaged similar cochlear frequency regions. Following this approach, we identified the relative contribution of hearing sensitivity and CS to speech intelligibility in two age-matched (65-year-old) groups with clinically normal (n=15, 8 females) or impaired audio-grams (n=13, 8 females). Compared to a young normal-hearing control group (n = 13, 7 females), the older groups demonstrated lower EFR responses and impaired speech reception thresholds. We conclude that age-related CS reduces supra-threshold temporal envelope coding with subsequent speech coding deficits in noise that cannot be explained based on hearing sensitivity alone. Significance StatementTemporal bone histology reveals that cochlear synaptopathy (CS), characterized by damage to inner hair cell auditory nerve fiber synapses, precedes sensory cell damage and hearing sensitivity decline. Despite this, clinical practice primarily evaluates hearing status based on audiometric thresholds, potentially overlooking a prevalent aspect of sensorineural hearing damage due to aging, noise exposure, or ototoxic drugs--all of which can lead to CS. To address this gap, we employ a novel and sensitive EEG-based marker of CS to investigate its relationship with speech intelligibility. This study addresses a crucial unresolved issue in hearing science: whether CS significantly contributes to degraded speech intelligibility as individuals age. Our study-outcomes are pivotal for identifying the appropriate target for treatments aimed at improving impaired speech perception.

neuroscience↗

Enhancing the sensitivity of the envelope-following response for cochlear synaptopathy screening in humans: the role of stimulus envelope

Auditory de-afferentation, a permanent reduction in the number of innerhair-cells and auditory-nerve synapses due to cochlear damage or synaptopathy, can reliably be quantified using temporal bone histology and immunostaining. However, there is an urgent need for non-invasive markers of synaptopathy to study its perceptual consequences in live humans and to develop effective therapeutic interventions. While animal studies have identified candidate auditory-evoked-potential (AEP) markers for synaptopathy, their interpretation in humans has suffered from translational issues related to neural generator differences, unknown hearing-damage histopathologies or lack of measurement sensitivity. To render AEP-based markers of synaptopathy more sensitive and differential to the synaptopathy aspect of sensorineural hearing loss, we followed a combined computational and experimental approach. Starting from the known characteristics of auditory-nerve physiology, we optimized the stimulus envelope to stimulate the available auditory-nerve population optimally and synchronously to generate strong envelope-following-responses (EFRs). We further used model simulations to explore which stimuli evoked a response that was sensitive to synaptopathy, while being maximally insensitive to possible co-existing outer-hair-cell pathologies. We compared the model-predicted trends to AEPs recorded in younger and older listeners (N=44, 24f) who had normal or impaired audiograms with suspected age-related synaptopathy in the older cohort. We conclude that optimal stimulation paradigms for EFR-based quantification of synaptopathy should have sharply rising envelope shapes, a minimal plateau duration of 1.7-2.1 ms for a 120-Hz modulation rate, and inter-peak intervals which contain near-zero amplitudes. From our recordings, the optimal EFR-evoking stimulus had a rectangular envelope shape with a 25% duty cycle and a 95% modulation depth. Older listeners with normal or impaired audiometric thresholds showed significantly reduced EFRs, which were consistent with how (age-induced) synaptopathy affected these responses in the model. Significance StatementCochlear synaptopathy was in 2009 identified as a new form of sensorineural hearing loss (SNHL) that also affects primates and humans. However, clinical practice does not routinely screen for synaptopathy, and hence its consequences for degraded sound and speech perception remain unclear. Cochlear synaptopathy may thus remain undiagnosed and untreated in the aging population who often report self-reported hearing difficulties. To enable an EEG-based differential diagnosis of synaptopathy in humans, it is crucial to develop a recording method that evokes a robust response and emphasizes inter-individual differences. These differences should reflect the synaptopathy aspect of SNHL, while being insensitive to other aspects of SNHL (e.g. outer-hair-cell damage). This study uniquely combines computational modeling with experiments in normal and hearing-impaired listeners to design an EFR stimulation and recording paradigm that can be used for the diagnosis of synaptopathy in humans.

neuroscience↗

The Derived-Band Envelope Following Response and its Sensitivity to Sensorineural Hearing Deficits

The envelope following response (EFR) has been proposed as a non-invasive marker of synaptopathy in animal models. However, its amplitude is affected by the spread of basilar-membrane excitation and other coexisting sensorineural hearing deficits. This study aims to (i) improve frequency specificity of the EFR by introducing a derived-band EFR (DBEFR) technique and (ii) investigate the effect of lifetime noise exposure, age and outer-hair-cell (OHC) damage on DBEFR magnitudes. Additionally, we adopt a modelling approach to validate the frequency-specificity of the DBEFR and test how different aspects of sensorineural hearing loss affect peripheral generators. The combined analysis of simulations and experimental data proposes that the DBEFRs extracted from the [2-6]-kHz frequency band is a sensitive and frequency-specific measure of synaptopathy in humans. Individual variability in DBEFR magnitudes among listeners with normal audiograms was explained by their self-reported amount of experienced lifetime noise-exposure and corresponded to amplitude variability predicted by synaptopathy. Older listeners consistently had reduced DBEFR magnitudes in comparison to young normal-hearing listeners, in correspondence to how age-induced synaptopathy affects EFRs and compromises temporal envelope encoding. Lastly, OHC damage was also seen to affect the DBEFR magnitude, hence this marker should be combined with a sensitive marker of OHC-damage to offer a differential diagnosis of synaptopathy in listeners with impaired audiograms.

bioengineering↗

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↗