bioRxiv Subject Collection: Neuroscience's Journal
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Wednesday, August 13th, 2025
| Time |
Event |
| 8:32a |
Short-term synaptic dynamics in the ventrolateral and dorsomedial periaqueductal gray
The ability to assess and rapidly respond to predator threats in the environment is necessary for survival and requires dedicated neural circuits for threat detection, sensorimotor integration, and execution of ethologically appropriate behavioral responses. Although numerous brain circuits are involved in these processes, the midbrain periaqueductal gray (PAG) serves as an important central hub to generate ethologically appropriate passive and/or active defensive behaviors. Despite its central role in generating defensive behaviors, little is known about the intrinsic and synaptic properties of neurons across columns in the PAG. To address this knowledge gap, we made whole-cell voltage- and current-clamp recordings from unlabeled neurons in the vl- and dmPAG of mice. Consistent with in vivo work, our data highlights the relative importance of synaptic inhibition in both columns. Further, our results suggest that neurons in both the vl- and dmPAG prioritize frequency-invariant coding strategies, showing remarkably stable paired pulse ratios across interstimulus intervals. Despite this common theme, the underlying mechanism each column utilizes to achieve such frequency invariant coding is distinct, reflecting important differences in synaptic processing across columns. More specifically, while the vlPAG is relatively resistant to phasic short-term depression across stimulation frequencies, neurons in the dmPAG show a pronounced buildup of tonic/slow current during high frequency stimulation trains, which counteracts short-term depression of the phasic current amplitude observed during high frequency stimulation trains. This prolonged tonic current observed in the dmPAG prolongs the period of spike elevation, suggesting that high frequency stimulation may drive sustained activity in the dmPAG. Together, these results provide fundamental information of synaptic integration and network properties across columns in the PAG, which ultimately support their distinct roles in threat processing. | | 8:32a |
Tactile stimulation transiently disrupts encoding of whisker position by cerebellar molecular layer interneuron ensembles
Molecular layer interneurons (MLIs) within the cerebellar cortex mediate feed-forward inhibition onto Purkinje cells, positioning them as pivotal modulators of cerebellar output. We asked how motor patterns and salient sensory input influence MLI population activity during active whisking and tactile interactions. Utilizing two-photon calcium imaging combined with high-speed videography, we examined MLI population dynamics in awake, behaving mice engaged in voluntary whisker movements. Our results demonstrate that during free whisking, MLI population activity reliably tracks whisker position, yielding uniform graded responses that provide stable and precise representations over time. Tactile contact with external stimuli evokes additional activation in a subset of MLIs. Sensory input transiently disrupts the linear relationship between MLI activity and whisker position and may account for rapid synchronous inhibition of Purkinje cell spiking activity following tactile stimulation. These findings indicate that MLIs in Crus 1 maintain an accurate internal model of whisker position which is perturbed upon encountering obstacles. This disruption likely reflects the integration of sensory feedback, disrupting predictive signals that are subsequently passed forward to Purkinje cells. Such signals can alert the brain to novel happenings and be used to update motor commands, thereby contributing to cerebellar function in response to environmental changes. | | 8:32a |
Dynamic Neural Encoding of Prior Expectations and Auditory Evidence Drive Perceptual Decision-Making
Perceptual decision-making has been studied extensively as the integration of evidence over time. Yet how moment-to-moment fidelity of sensory encoding interacts with prior expectations in shaping our choices remains poorly understood--particularly in the auditory domain. Here we quantify how priors act at the stage of sensory encoding and how these fluctuations predict behaviour. In a human model-based EEG study, we augmented a canonical click-train evidence accumulation task with probabilistic cues to shape prior expectations and analysed all activity with trial-resolved linear encoding models. Probabilistic cues drove alpha-oscillatory EEG patterns and induced symmetric shifts in response bias but did not change temporal integration dynamics. Neural encoding strength in lateralised auditory cortex uniquely predicted single-trial choice and confidence beyond what was explained by evidence strength or cueing alone. These findings identify sensory encoding fidelity as a mechanistic, behaviourally relevant link between priors and perceptual choice, offering new understanding how neural noise and expectations jointly shape decisions under uncertainty. | | 9:47a |
From Wiring to Firing: Collapse of embryonic identities and emergence of functional diversity during motor neuron maturation
Neurons born in the embryo undergo a protracted process of maturation during which time they project axons to their specific targets, integrate into circuits, refine synapses, and acquire unique electrophysiological properties. The molecular strategies that individual neuron types deploy to complete this complex process remain poorly understood. In this work, we used single nucleus multiome sequencing (RNA-seq and ATAC-seq) to track the transition from specification to functional maturation in mouse skeletal motor neurons (SMNs). Our data show that individual SMNs undergo significant transcriptional changes as they mature, but more strikingly, we find that diversity within SMNs fluctuates dramatically as the functional needs of these cells change over time. At embryonic day E15.5, when motor axons are innervating their specific muscle targets, SMNs can be subdivided into dozens of transcriptional subclusters. These embryonic subclusters represent known motor columns and pools, which utilize column- and pool-specific genes to innervate unique muscle targets. About a week later, at postnatal day 3 (P3) many column- and pool-specific genes are downregulated or become broadly expressed and SMNs coalesce on the molecular level into a more homogenous state. These neurons then undergo a second round of diversification during the first two weeks of postnatal life (P3-P13), acquiring gene expression patterns that divide them into the functionally distinct alpha, gamma, and type3 subtypes found in adults. The fluctuations in SMN diversity go hand-in-hand with changes in accessible chromatin regions and transcription factor (TF) expression. Differential ATAC-seq peaks that define embryonic diversity are lost over time while new peaks that control expression in adult subtypes are gained. TFs that are known to regulate embryonic diversity are also downregulated over time, as a separate set of TFs that likely regulate adult subtype identities are upregulated. Our work uncovers a novel maturation trajectory for postmitotic neurons where extensive spatial diversity is first acquired in the embryo to ensure proper circuit wiring; this diversity is then lost as maturing neurons re-diversify into functional identities required for proper circuit firing in postnatal life. Therefore, all aspects of a neurons identity - its morphology, circuitry, and electrophysiologically - may not be fully described by its gene expression program at adulthood, but instead is a culmination of transcriptional events that occur throughout its specification and maturation trajectory as the functional needs of the cells evolve. | | 9:47a |
δ-catenin haploinsufficiency is sufficient to alter behaviors and glutamatergic synapses in mice
{delta}-catenin (also known as CTNND2) functions as an anchor for the glutamatergic AMPA receptor (AMPARs) to regulate synaptic activity in excitatory synapses. Alteration in the gene coding {delta}-catenin has been implicated in many neurological disorders. Some of these genetic alterations exhibit a profound loss of {delta}-catenin functions in excitatory synapses. We have shown that {delta}-catenin deficiency induced by the homozygous {delta}-catenin knockout (KO) and autism-associated missense glycine 34 to serine (G34S) mutation significantly alters AMPAR-mediated synaptic activity in cortical neurons and disrupts social behavior in mice. Importantly, many genetic disorders are caused by haploinsufficiency. Indeed, {delta}-catenin haploinsufficiency contributes to severe autism and learning disabilities in humans. However, previous studies have used only homozygous {delta}-catenin deficiency models. Therefore, it is important to examine the effects of {delta}-catenin haploinsufficiency on animals behaviors and excitatory synapses. Here, we use heterozygous {delta}-catenin KO and G34S mice as a {delta}-catenin haploinsufficiency model to examine this idea. Multiple behavioral assays, a social behavior test, contextual fear conditioning, and an open field test, reveal that both {delta}-catenin KO and G34S haploinsufficiency significantly disrupt animals social behavior and fear learning and memory. Interestingly, only KO haploinsufficiency mice show anxiety-like behavior. A biochemical assay using brain extracts demonstrates that {delta}-catenin haploinsufficiency significantly affects the levels of synaptic {delta}-catenin and AMPARs. Our findings thus suggest that {delta}-catenin haploinsufficiency affects animals behaviors via altering glutamatergic synaptic activity. | | 9:47a |
Acetylcholine Enhances Deviance Detection in Hodgkin-Huxley Neuronal Networks
The brains ability to detect unexpected events, deviance detection (DD), is critical for survival. While DD has been computationally explained by synaptic plasticity, the role of neuromodulators like acetylcholine (ACh) remains less understood. Here, we examine how ACh modulates DD without invoking additional plasticity mechanisms. Using a cholinergic-sensitive Hodgkin-Huxley network of 200 neurons arranged in 2D space and stimulated via five spatially distinct inputs (A-E), we implemented an oddball paradigm with three conditions: standard (80% A, 20% B), deviant (20% A, 80% B), and a multi-standard control (20% each of A-E). ACh levels were controlled by the conductance of the slow K+ current. In the absence of ACh, the network already exhibited DD, responding more strongly to deviant A compared to control A. Notably, introducing a small amount of ACh amplified DD, while further increases suppressed it. Maximal DD occurred when strong spike frequency adaptation to standard B reduced competition, and enhanced phase-locking synchronized the networks response to deviant A. These findings reveal how neuromodulation can shape context-sensitive neural computation, optimizing detection of salient events through a dynamic balance of suppression and synchronization. | | 9:47a |
A Computational Model of Action Specification in the Basal Ganglia
The basal ganglia has traditionally been modelled as a system that represents the available, discrete action space using a finite set of distinct and non-overlapping representational units. This limits these models from addressing questions around how the basal ganglia is involved in action specification: the selection of continuously valued action dynamics such as speed and vigor. In this article we present a novel computational model of the basal ganglia which incorporates vector-symbolic algebras in order to represent continuous action spaces. The stages of model development are presented along with simulation experiments to test the basic properties of the model. This work represents a promising foundational step in providing a mechanistic account for neuroscientific and behavioural evidence implicating the basal ganglia in action specification, thereby filling a gap in the literature. | | 9:47a |
Evaluating scientific theories as predictive models in language neuroscience
Modern data-driven encoding models are highly effective at predicting brain responses to language stimuli. However, these models struggle to explain the underlying phenomena, i.e. what features of the stimulus drive the response? We present Question Answering encoding models, a method for converting qualitative theories of language selectivity into highly accurate, interpretable models of brain responses. QA encoding models annotate a language stimulus by using a large language model to answer yes-no questions corresponding to qualitative theories. A compact QA encoding model that uses only 35 questions outperforms existing baselines at predicting brain responses in both fMRI and ECoG data. The model weights also provide easily interpretable maps of language selectivity across cortex; these maps show quantitative agreement with meta-analyses of the existing literature and selectivity maps identified in a follow-up fMRI experiment. These results demonstrate that LLMs can bridge the widening gap between qualitative scientific theories and data-driven models. | | 10:17a |
Disentangling the influences of pre- and postnatal periods on human cortical microstructure
During late gestation and early postnatal development a combination of intrinsic and extrinsic factors drive the maturation of the human cortex. This process is regionally heterogeneous, with cortical areas developing at different paces and trajectories. Leveraging submillimetre T1-weighted/T2w-weighted (T1w/T2w) magnetic resonance imaging (MRI) from pre- and full-term neonates (n = 599, 0-7 weeks), we sampled intracortical microstructure profiles across the cortex and characterised the profiles shapes according to their central moments. We found that gestational age at birth dominated the effects on early cortical development, with significant, global increases in microstructural density, increasing intracortical homogeneity and a bimodal change of the microstructural balance between superficial and deeper cortical layers. On the other hand, weeks since birth (i.e. postnatal age) exhibited different effects on microstructure, with density increasing at a slower pace, increasing intracortical heterogeneity, and intracortical balance only shifting towards deeper layers in posterior temporal, occipital, medial parietal areas and some prefrontal areas. These effects align with low spatial-frequency geometric eigenmodes of the human cortex, specifically the anterior-posterior, superior-inferior and central-polar axes. Our findings demonstrate that separating prenatal from postnatal influences, and analysing intracortical profiles rather than macroscale features, provides finer-grained insights into how human cortical microstructure changes during perinatal development and lays the groundwork for investigating the biological underpinnings that govern normative cortical maturation. | | 11:35p |
Decoding intended speech with an intracortical brain-computer interface in a person with longstanding anarthria and locked-in syndrome
Intracortical brain-computer interfaces (iBCIs) for decoding intended speech have provided individuals with ALS and severe dysarthria an intuitive method for high-throughput communication. These advances have been demonstrated in individuals who are still able to vocalize and move speech articulators. Here, we decoded intended speech from an individual with longstanding anarthria, locked-in syndrome, and ventilator dependence due to advanced symptoms of ALS. We found that phonemes, words, and higher-order language units could be decoded well above chance. While sentence decoding accuracy was below that of demonstrations in participants with dysarthria, we are able to attain an extensive characterization of the neural signals underlying speech in a person with locked-in syndrome and through our results identify several directions for future improvement. These include closed-loop speech imagery training and decoding linguistic (rather than phonemic) units from neural signals in middle precentral gyrus. Overall, these results demonstrate that speech decoding from motor cortex may be feasible in people with anarthria and ventilator dependence. For individuals with longstanding anarthria, a purely phoneme-based decoding approach may lack the accuracy necessary to support independent use as a primary means of communication; however, additional linguistic information embedded within neural signals may provide a route to augment the performance of speech decoders. |
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