Biology subjects

Koch, C.

Publications and source records attributed to Koch, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Psilocybin collapses visual change detection and drives cortical dynamics toward a state of surprise

Psilocybin profoundly alters visual perception, yet the neuronal mechanisms underlying these effects remain unclear. Here we combined large-scale Neuropixels recordings with cell-type specific optogenetics in head-fixed mice performing a visual change-detection task. Psilocybin severely impaired task performance without overt motor deficits. In cortex, the drug modestly suppressed activity of layer 5 neurons while preserving representations of image identity. By contrast, psilocybin imposed a 4-Hz oscillation on visually evoked activity that preferentially affected neurons encoding image change rather than image identity. Under psilocybin, expected image repetitions aberrantly recruited change-encoding ensembles and shifted cortical population dynamics towards trajectories normally evoked by genuine stimulus changes. These effects were strongest in somatostatin-expressing (SST) interneurons in visual cortex. The strength of this modulation depended on image structure and was greatest for images with clear, continuous contours, which preferentially recruited change-encoding ensembles. These findings demonstrate that psilocybin drives internally generated cortical surprise signals, providing a circuit mechanism for altered perception in the acute psychedelic state.

neuroscience↗

bioRxiv2026

Selective gating of neural modulation through frequency- and behavior-dependent modes during cortical electrical stimulation

Electrical stimulation is widely used to modulate neuronal activity, yet its effects on neuronal circuits in vivo remain poorly understood. This, in turn, has hindered the principled design of stimulation protocols and raised questions about reproducibility that constrain the field's translational impact. Here we combine cortical sinusoidal electrical stimulation (sES) with Neuropixels recordings to characterize stimulation-driven responses in more than 2,700 well-isolated neurons across 53 brain areas in 14 behaving, head-fixed mice. We uncover two distinct, concurrent modes of neural modulation. First is a sustained, brain-wide spike-phase entrainment effect that depends on stimulation frequency: entrainment to slow stimulation is supported by non-synaptic electric field propagation while anatomical connectivity dominates entrainment to higher stimulation frequencies. Second, we find a transient, spatially localized spike-rate modulation mainly mediated through anatomical connectivity that only emerges at high stimulation frequencies by selectively recruiting inhibitory neurons. We show that the two distinct modes are differentially shaped by behavior. By identifying how stimulation frequency governs the mechanism of neural engagement and how behavioral state selectively gates brain-wide entrainment but not local inhibitory recruitment, our results provide a mechanistic foundation for designing targeted, reproducible neuromodulation strategies.

neuroscience↗

bioRxiv2026

Brain-wide reconfiguration of burst firing by psilocybin reveals 5-HT2A-dependent circuit dynamics

Psilocybin produces rapid and lasting therapeutic effects, yet how 5-HT2A receptor activation reshapes brain-wide circuit dynamics during acute drug administration remains poorly understood. Using simultaneous multi-region Neuropixels recordings of 46,360 single units from 35 mice, together with scalp electroencephalography (EEG), pupillometry, and locomotion monitoring, we provide a brain-wide, single-unit and field-potential characterization of psilocybin's acute effects, with pharmacological dissection using the 5-HT2A antagonist ketanserin. Psilocybin selectively reconfigured burst coding, rather than mean firing rate, across cortical, thalamic, and hippocampal circuits: burst firing decreased in hippocampal CA1-CA3 and was bidirectionally modulated in the thalamus, with the reticular nucleus bursting more and first-order geniculate nuclei bursting less. Critically, most of these burst effects were abolished by ketanserin, consistent with at least partial 5-HT2A receptor dependence. These data suggest that the psychedelic state is not simply a matter of how much neurons fire, but of how they fire, pointing to a region-specific, 5-HT2A-associated reconfiguration of burst coding that may underlie the acute phenomenology of the psilocybin experience.

neuroscience↗

bioRxiv2026

Pupil-DLC: an open-source deep learning pipeline for scalable, markerless tracking of pupil dynamics across conscious and unconscious states

BackgroundPupil diameter is a non-invasive biomarker of brain state, correlating with arousal, attention, cognitive processing, and consciousness. However, existing pupillometry software often lacks scalability and robustness across diverse experimental conditions and species. New methodWe introduce Pupil-DLC, an open-source, offline, DeepLabCut-based pipeline for scalable, marker-less pupil tracking, primarily designed for mice. Trained on 21,750 manually annotated frames from over 140 videos of head-fixed mice spanning wakefulness and drug-induced states, including psychedelics and anesthesia, the dataset was deliberately selected to maximize pupil size variability and model generalization. Pupil-DLC implements a dual-model architecture: a General Model (GM) for high-throughput analysis and an Individual Model (IM) for session-specific optimization. ResultsPupil-DLC captures pupil dynamics across awake, psychedelic, and anesthetized conditions with high agreement with ground truth and equal tracking fidelity during active locomotion and quiet rest. Confidence metrics aligned with human frame quality assessments, enabling principled tuning of accuracy-retention trade-offs. As a secondary demonstration, Pupil-DLC extends to unseen human videos across diverse conditions and frame rates, including daylight and smartphone recordings, without retraining. Comparison with existing methodsPupil-DLC outperforms existing automated methods in accuracy and frame retention while maintaining computational efficiency comparable to real-time tools. These improvements stem from a learned keypoint-based representation robust to pupil shape variability, occlusions, reflections, and imaging artifacts. The GM/IM framework supports a tiered strategy balancing throughput and precision. ConclusionsPupil-DLC provides a reproducible, adaptable platform for quantifying pupil-linked brain state dynamics across experimental paradigms and species, bridging basic mouse neuroscience and translational human applications.

neuroscience↗

bioRxiv2025

Different data analysis models for detecting miRNAs using nanopores

Nanopore sensors offer exceptional sensitivity for detecting single molecules, making them ideal for early disease diagnostics. In this study, we present a multiplexed nanopore-based assay that combines DNA-barcoded probes with advanced computational analysis to detect microRNAs (miRNAs) with high specificity and quantitative accuracy. Each probe binds selectively to its target biomarker and generates a characteristic delay in the ionic current signal upon translocation through the nanopore, enabling label-free detection. We evaluated three analytical strategies for classifying delayed versus non-delayed events: (1) moving standard deviation (MSD), (2) spectral entropy (SE), and (3) a convolutional neural network (CNN). While MSD and SE rely on manually defined thresholds and exhibit limited sensitivity, the CNN model, trained on image representations of raw current traces, achieved near-perfect classification performance across all metrics. Grad-CAM visualisation confirmed that the CNN focused on biophysically relevant signal regions, enhancing interpretability and generalisability. All methods produced sigmoidal concentration-response curves consistent with expected binding kinetics, and nanopore-derived delay metrics closely matched RT-qPCR validation data. All three methods were capable of distinguishing between signal classes; however, the CNN model demonstrated superior sensitivity and robustness. This work highlights the importance of data interpretation in nanopore sensing and presents a comparative framework for binary event classification. The findings pave the way for the development of machine learning-driven nanopore diagnostics capable of detecting diverse biomarker types at the single-molecule level.

biophysics↗

bioRxiv2025

Assessing PARP trapping dynamics in ovarian cancer using a CRISPR-engineered FRET biosensor

Poly(ADP-ribose) polymerase inhibitors (PARPi) have revolutionised the treatment of ovarian high grade serous carcinoma (HGSC), especially those with defective homologous recombination. However, the emergence of resistance poses a critical challenge, as over 50% of patients relapse within three years. The mechanisms underlying changes in PARP trapping, a central aspect of PARPi efficacy, are not well understood due to limitations in current experimental methodologies. Existing techniques lack resolution and throughput, impeding efforts to study PARP trapping dynamics over time with single-cell resolution. Effective tools to study PARP trapping in live cells are urgently needed to elucidate resistance mechanisms and inform therapeutic strategies. To address this, we used CRISPR-Cas9 gene editing to dual-label endogenous PARP1 with EGFP and mCherryFP in OVCAR4 cells to develop a novel intramolecular FRET-based biosensor that enables real-time, single-cell visualization of PARP trapping dynamics in live cells. High-content fluorescence lifetime imaging microscopy (FLIM) revealed dose dependent PARP trapping upon exposure to PARP inhibitor and distinguished between the trapping efficiencies of four different PARPi (veliparib, olaparib, rucaparib, talazoparib). Moreover, we found reduced PARP trapping in PARPi-resistant models, both in vitro and in vivo, providing critical evidence for altered PARP trapping as a resistance mechanism and illustrating the potential of this FRET biosensor to interrogate resistance mechanisms quantitatively. This PARP trapping biosensor represents a transformative advance, enabling dynamic, high-resolution analysis of mechanisms underlying cancer drug resistance. It provides critical insights into the heterogeneity of PARPi resistance, with implications for developing more effective therapies and improving personalised treatment strategies for ovarian cancer patients. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=58 SRC="FIGDIR/small/642798v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@1c5ee67org.highwire.dtl.DTLVardef@1a6d101org.highwire.dtl.DTLVardef@e3a2bborg.highwire.dtl.DTLVardef@d0ba03_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Neuropixels Opto: Combining high-resolution electrophysiology and optogenetics

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 70 m wide, 1 cm long shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

neuroscience↗

bioRxiv2025

An area-resolved phylogeography of bulbous barley (Hordeum bulbosum; Poaceae)

Hordeum bulbosum, the closest relative of barley (H. vulgare), is an important source of resistance genes for cereals in the Triticeae. This perennial and mainly outcrossing species occurs with two cytotypes: diploids thrive in the western and central parts of the Mediterranean, while autotetraploids extend from Greece mainly eastwards to western Asia. To elucidate H. bulbosums origin, colonization patterns, population relationships, and distinctions between the two cytotypes, we determined ploidy and performed genotyping-by-sequencing analyses on 314 individuals from across the species distribution range. Our results revealed two distinct lineages within diploid H. bulbosum: individuals from Libya vs. all other diploids. Southeastern Italian populations were the origin for the species expansion eastward into Albania/Greece and westward into mainland Italy, Sicily/Sardinia, Tunisia, and Spain. The tetraploid cytotype originated early in the evolution of the species, thus retaining alleles found in extant Libyan diploids. Tetraploids underwent local introgression from diploids in Greece, where also a secondary origin of tetraploids was detected. We found that ecoclimatic conditions alone cannot account for the clear geographic separation of the cytotypes, as habitats across much of the central Mediterranean would be suitable for both. We conclude that minority cytotype exclusion is the most plausible explanation for the distinct distribution patterns observed. While both cytotypes are morphologically indistinguishable, diploid populations typically occur in scattered stands within their range, while tetraploids tend to form larger, often contiguous populations.

evolutionary biology↗

bioRxiv2025

Local erythropoiesis directs oxygen availability in bone fracture repair

Oxygen tension dynamically regulates stem cell fate and tissue regeneration, yet how local oxygen availability is controlled within the bone marrow niche remains poorly understood. While bone marrow injury, such as by bone fracture, disrupts marrow vasculature, the consequences on local oxygen tension remain unclear. Here, we show in mice that while the tissue oxygen tension in bone marrow is low (25 mmHg, [~]4% O2), intracellular oxygenation is heterogeneous and erythroid cells are high in oxygen. Bone fracture elevates oxygen tension in the injured bone marrow (>55 mmHg, [~]8%), which persists for over a week post-injury. This oxygen elevation results not from angiogenesis, but rather from localized expansion of erythroid precursor cells in the injured bone marrow. The activated erythroid precursors synthesize hemoglobin and accumulate oxygen, acting as local modulators of oxygen tension. Blocking transferrin receptor 1 (CD71)-mediated iron uptake impairs hemoglobin synthesis, reduces local oxygen levels, and enhances bone regeneration through increased angiogenesis and osteogenesis. These findings identify erythroid precursors as active regulators of local oxygen availability in the bone marrow niche, which may be targetable to enhance tissue regeneration.

cell biology↗

bioRxiv2024

Spatial transcriptomic data reveals pure cell types via the mosaic hypothesis

Neurons display remarkable diversity in their anatomical, molecular, and physiological properties. Although observed stereotypy in subsets of neurons is a pillar of neuroscience, clustering in high-dimensional feature spaces, such as those defined by single-cell RNA-seq data, is often inconclusive, with cells seemingly occupying continuous, rather than discrete, regions. In the retina, a layered structure, neurons of the same discrete type avoid spatial proximity with each other. While this principle, which is independent of clustering in feature space, has been a gold standard for retinal cell types, its applicability to the cortex has been only sparsely explored. Here, we provide evidence for such a mosaic hypothesis by developing a statistical point process analysis framework for spatial transcriptomic data. We demonstrate spatial avoidance across many excitatory and inhibitory neuronal types. Spatial avoidance disappears when cell types are merged, potentially offering a gold standard metric for evaluating the purity of putative cell types. Significance statementWhile morphologically or molecularly-defined cell types and their taxonomy are a pillar of modern neuroscience, the extent to which their discrete treatment reflects biology is far from settled. A functional hypothesis concerning cortical neuronal cell types with roots in retina research suggests an anatomical test for the existence and identification of pure, discrete cell types. We describe evidence for this decades-old hypothesis in the mouse neocortex and detail the associated computational methodology based on spatial point processes.

neuroscience↗

bioRxiv2024

Understanding Electric Brain Stimulation Through the Reciprocity Theorem

Electrical stimulation of nervous tissue is grounded in well-established biophysical principles, yet understanding its precise effect on neural activity remains challenging. This represents a major obstacle to both scientific and clinical applications of electrical brain stimulation. We here show that the reciprocity theorem of electromagnetism can be applied more broadly than previously acknowledged, providing a framework for elucidating the effects of electrical brain stimulation on neurons. Through this new perspective, we account for the observed weak frequency-dependence of extracellular electrical stimulation-induced membrane potential changes, and demonstrate a 1/r falloff for nearby and 1/r2 falloff for distant neurons. We also show that for transcranial electrical stimulation, the susceptibility of a neuron to the stimulation is directly proportional to the size of the current dipole moment resulting from somatic current input. The induced somatic membrane potential changes are small and exhibit weak spatial but strong orientation dependency across human neocortex. The reciprocity-based approach to electrical stimulation reproduces a large body of previous experimental data, and provides new insights into how ES affects neurons.

neuroscience↗

bioRxiv2024

Transition to chaos separates learning regimes and relates to measure of consciousness in recurrent neural networks

AbstractRecurrent neural networks exhibit chaotic dynamics when the variance in their connection strengths exceed a critical value. Recent work indicates connection variance also modulates learning strategies; networks learn "rich" representations when initialized with low coupling and "lazier"solutions with larger variance. Using Watts-Strogatz networks of varying sparsity, structure, and hidden weight variance, we find that the critical coupling strength dividing chaotic from ordered dynamics also differentiates rich and lazy learning strategies. Training moves both stable and chaotic networks closer to the edge of chaos, with networks learning richer representations before the transition to chaos. In contrast, biologically realistic connectivity structures foster stability over a wide range of variances. The transition to chaos is also reflected in a measure that clinically discriminates levels of consciousness, the perturbational complexity index (PCIst). Networks with high values of PCIst exhibit stable dynamics and rich learning, suggesting a consciousness prior may promote rich learning. The results suggest a clear relationship between critical dynamics, learning regimes and complexity-based measures of consciousness.

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

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subjects behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subjects behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/578243v2_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@cae203org.highwire.dtl.DTLVardef@1bc5223org.highwire.dtl.DTLVardef@b48e43org.highwire.dtl.DTLVardef@1e7fe34_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Complete genome of the Medicago anthracnose fungus, Colletotrichum destructivum, reveals a mini-chromosome-like region within a core chromosome.

Colletotrichum destructivum (Cd) is a phytopathogenic fungus causing significant economic losses on forage legume crops (Medicago and Trifolium species) worldwide. To gain insights into the genetic basis of fungal virulence and host specificity, we sequenced the genome of an isolate from M. sativa using long-read (PacBio) technology. The resulting genome assembly has a total length of 51.7 Mb and comprises 10 core chromosomes and two accessory chromosomes, all of which were sequenced from telomere to telomere. A total of 15,631 gene models were predicted, including genes encoding potentially pathogenicity-related proteins such as candidate secreted effectors (484), secondary metabolism key enzymes (110) and carbohydrate-active enzymes (619). Synteny analysis revealed extensive structural rearrangements in the genome of Cd relative to the closely-related Brassicaceae pathogen, C. higginsianum. In addition, a 1.2 Mb species-specific region was detected within the largest core chromosome of Cd that has all the characteristics of fungal accessory chromosomes (transposon-rich, gene-poor, distinct codon usage), providing evidence for exchange between these two genomic compartments. This region was also unique in having undergone extensive intra-chromosomal segmental duplications. Our findings provide insights into the evolution of accessory regions and possible mechanisms for generating genetic diversity in this asexual fungal pathogen. Impact statementColletotrichum is a large genus of fungal phytopathogens that cause major economic losses on a wide range of crop plants throughout the world. These pathogens vary widely in their host specificity and may have either broad or narrow host ranges. Here, we report the first complete genome of the alfalfa (Medicago sativa) pathogen, Colletotrichum destructivum, which will facilitate the genomic analysis of host adaptation and comparison with other members of the Destructivum species complex. We identified a species-specific 1.2 Mb region within chromosome 1 displaying all the hallmarks of fungal accessory chromosomes, which may have arisen through the integration of a mini-chromosome into a core chromosome and could be linked to the pathogenicity of this fungus. We show this region is also a focus for segmental duplications, which may contribute to generating genetic diversity for adaptive evolution. Finally, we report infection by this fungus of the model legume, Medicago truncatula, providing a novel pathosystem for studying fungal-plant interactions. Data summaryAll RNA-seq data were submitted to the NCBI GEO portal under the GEO accession GSE246592. C. destructivum genome assembly and annotation are available under the NCBI BioProject PRJNA1029933 with sequence accessions CP137305-CP137317. Supplementary data (genomic and annotation files, genome browser) are available from the INRAE BIOGER Bioinformatics platform (https://bioinfo.bioger.inrae.fr/). Transposable Elements consensus sequences are also available from the French national data repository, research.data.gouv.fr with doi 10.57745/TOO1JS.

genomics↗

bioRxiv2023

Ultra-high density electrodes improve detection, yield, and cell type specificity of brain recordings

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density ([~]10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neurons electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to [~]3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.

neuroscience↗

bioRxiv2023

The ER-SURF pathway uses ER-mitochondria contact sites for protein targeting to mitochondria

Most mitochondrial proteins are synthesized on cytosolic ribosomes and imported into mitochondria in a post-translational reaction. Mitochondrial precursor proteins which use the ER-SURF pathway employ the surface of the endoplasmic reticulum (ER) as an important sorting platform. How they reach the mitochondrial import machinery from the ER is not known. Here we show that mitochondrial contact sites play a crucial role in the ER-to-mitochondria transfer of precursor proteins. The ER encounter structure (ERMES) and Tom70 are part of two parallel and partially redundant ER-to-mitochondria transfer routes. When ER-to-mitochondria transfer is prevented, many mitochondrial precursor proteins associate with ER membranes, resulting in mitochondrial dysfunction. Our observations support an active role of the ER in mitochondrial protein biogenesis.

biochemistry↗

bioRxiv2023

An adversarial collaboration to critically evaluate theories of consciousness

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, yet, confirmation bias and dependence on design choices hamper progress in the field3. Here, we present an open science adversarial collaboration which directly juxtaposes Integrated Information Theory (IIT)4,5 and Global Neuronal Workspace Theory (GNWT)6-10, employing a theory-neutral consortium approach11,12. We investigate neural correlates of the content and duration of visual experience. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes, and their interpretation12. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography, and electrocorticography. We find information about conscious content in visual, ventro-temporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results confirm some predictions of IIT and GNWT, while substantially challenging both theories: for IIT, a lack of sustained synchronization within posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in prefrontal cortex. Beyond challenging the theories themselves, we present an alternative approach to advance cognitive neuroscience through a principled, theory-driven, collaborative effort. We highlight the challenges to change peoples mind 13 and the need for a quantitative framework integrating evidence for systematic theory testing and building.

neuroscience↗