Biology subjects

King, A. J.

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

At least 19 recordsLinked to original sources

bioRxiv2026

Predictive dendrites as a foundation for biological learning

A fundamental challenge for neuroscience is to identify laws of synaptic plasticity that are consistent with experimental observations at the level of individual neurons, whilst also explaining the ability of neural networks to learn complex tasks. Here we investigate a candidate law in which neurons adjust synaptic strengths to minimize the mismatch between somatic and dendritic activity. We demonstrate that models based on this rule can effectively adjust synaptic weights across network layers to learn non-linear tasks. Moreover, minimizing mismatch between spiking activity and dendritic inputs leads to integrate-and-fire dynamics and spike-timing-dependent plasticity. The model reproduces the experimentally observed dependencies of plasticity upon initial synaptic weights and spike patterns, whilst also generating a series of testable predictions. Our results show that a single principle - minimization of somato-dendritic mismatch - links learning at the network level with fundamental properties of individual neurons, including membrane potential dynamics and canonical features of synaptic plasticity.

neuroscience↗

bioRxiv2026

Sleep immediately after noise overexposure worsens tinnitus in mice

Subjective tinnitus is the most common auditory phantom perception in the absence of an acoustic stimulus yet there is no cure nor widely effective treatment to date. Previously, we suggested that sleep may contribute to tinnitus development after a triggering event, such as noise overexposure (NOE). Here, we investigated the effect of natural sleep on tinnitus development following NOE in mice. One group of mice was kept awake for 6 hours immediately after NOE, whereas a control group could sleep ad libitum. Tinnitus and hearing loss were assessed before and after NOE by determining gap prepulse inhibition of the acoustic startle reflex (GPIAS) and by recording auditory brainstem responses (ABRs). Only mice that were allowed to sleep in the first six hours after NOE developed a significant change in the GPIAS ratio one week after NOE, indicative of tinnitus. Habituation to the startle stimulus was largely similar between both groups, except that at eight weeks after NOE, when GPIAS ratio had returned to baseline levels in both groups, the sleep deprived group showed less habituation to the startle stimulus. Notably, animals in neither group showed significantly elevated ABR thresholds after NOE, yet the control group showed signs of elevated evoked activity in the auditory brainstem one week after NOE. These findings demonstrate that sleep early after noise overexposure may amplify subsequent tinnitus development. Our results suggest that sleep represents a temporal window that may be harnessed for potential modulation or mitigation of noise-induced hearing loss and tinnitus-related impairments.

neuroscience↗

bioRxiv2026

Allele-specific splicing modulates protein isoforms and Alzheimer's risk

Despite growing catalogs of genetic variation linked to human traits and diseases, the functional impact of most genetic variants remains poorly understood. Alternative splicing, particularly in the human brain, represents a key layer of post-transcriptional regulation that may mediate genetic effects on gene expression and protein diversity. In this study, we systematically map allele-specific alternative splicing (ASAS) events in postmortem brain tissues from the Mount Sinai Brain Bank cohort, identifying hundreds of genetically regulated splicing events across four brain regions. Using a concordance-based method, we nominate over 500 putative functional SNPs associated with ASAS, many of which overlap splicing QTLs (sQTLs), RNA-binding protein binding sites, and GWAS loci for Alzheimers disease (AD), brain traits, and immune phenotypes. ASAS events are enriched in genes involved in mitochondrial function and frequently occur in 5' untranslated regions (5' UTRs), where they are associated with protein quantitative trait loci (pQTLs), alternative start codons, and isoform-specific domain changes - highlighting an underappreciated mechanism through which noncoding variants can influence translation and proteome complexity. Importantly, we also identify a subset of ASAS events exhibiting disease-specific splicing patterns in AD brains, including functional SNPs with opposing splicing effects between AD and control groups in genes implicated in mitochondrial function and neuronal signaling. Together, our results provide a brain-specific, splicing-resolved map of regulatory variation and uncover novel mechanisms linking genetic variation to transcript and protein-level changes in AD. This work highlights the importance of allele-specific splicing analysis for interpreting noncoding variation in complex human disorders.

genomics↗

bioRxiv2026

Allele-specific alternative polyadenylation links noncoding genetic variation to Alzheimer's disease risk

BackgroundAlternative polyadenylation (APA) is a crucial post-transcriptional mechanism generating isoform diversity in the nervous system. While genetic variants significantly influence gene expression, the extent to which they regulate 3 UTR usage in the human brain remains underexplored. We aimed to characterize the landscape of allele-specific alternative polyadenylation (asAPA) and investigate its role in neurodevelopmental and neurodegenerative disorders. ResultsAnalyzing 1,047 RNA-seq data from 293 Alzheimers disease (AD) and control donors across four brain regions, we identified 4,462 asAPA events involving 3,432 SNPs. We prioritized a core set of putative functional variants that drive consistent cis-regulatory effects across individuals. These functional SNPs are enriched for RNA-binding protein motifs, particularly those recognized by FMRP. In Fragile X Syndrome brains lacking FMRP, we observed widespread 3 UTR shortening, with FMRP motifs enriched in the 3 UTR extension regions of shortened transcripts, suggesting FMRP normally protects against proximal site usage. Integrating these data with population genetics, we found that asAPA SNPs significantly overlap GWAS risk loci for autism spectrum disorder (ASD), ADHD, and AD. Furthermore, comparing AD to control brains within our cohort revealed 77 asAPA genes exhibiting condition-specific shifts in allelic bias, affecting key synaptic genes including CAMK2G. ConclusionsOur study uncovers a pervasive layer of cis-regulatory variation in the human brain that links noncoding genetics to transcript structure via RBP interactions. We identify FMRP as a key regulator of this process and demonstrate that asAPA provides a mechanistic bridge connecting genetic risk to neuronal pathology in both neurodevelopment and neurodegeneration.

genomics↗

bioRxiv2025

Corticofugal gated recurrency captures auditory cortical responses

Memory is essential for the neural processing of natural sounds. It has been proposed that cortical memory is subserved by gated recurrency, a powerful machine learning method that enables memory of sequential dependencies. However, standard forms lack biological realism. We built a computational model using a subtractive form of gated recurrency, consistent with cortical circuitry and feedback that resembles corticofugal projections. This architecture outperformed state-of-the-art models with delay lines or non-biological gated recurrency at predicting auditory cortical responses to natural sounds. Its performance was further improved by incorporating a network layer that mirrors the high neuronal density in superficial cortical layers. Analyzing the model, we found that memory retention is longer in secondary than in primary auditory cortex, and that gated recurrency particularly helps capture responses during abrupt changes and quiet periods in the sounds. This work lays out the fundamental functional circuitry of the auditory pathway for processing the sequential dependencies in natural sounds.

neuroscience↗

bioRxiv2025

Social relationships promote access to food and information in wild jackdaws

Many social animals form differentiated social relationships that can influence fitness, yet the mechanisms behind these benefits are often unclear. Does the presence of social partners during foraging enhance access to food or information? Might individuals also incur short-term costs, for example by foregoing feeding opportunities to remain with and support social partners? Here, we investigated how social relationships shape foraging decisions and outcomes in wild jackdaws (Corvus monedula) using automated RFID feeding stations where two birds could perch, but only one could feed with the other queueing behind ("dyadic events"). Bonded social partners (pair-bonded mates and direct kin) engaged in these dyadic events more frequently and coordinated their visits, as shown by shorter dyadic arrival latencies. Bonded partners also showed higher social tolerance, with feeding individuals benefitting from increased food intake when their partner was present, while queuing individuals accepted short-term opportunity costs to remain with them. For juveniles, queuing with parents promoted social learning about feeder use. These findings show that social relationships influence decision-making and foraging performance in the wild, revealing both benefits and costs of maintaining close bonds. Short-term effects on foraging success may therefore contribute to long-term fitness advantages of strong social relationships.

animal behavior and cognition↗

bioRxiv2025

Auditory midbrain encodes training-induced plasticity in soundlocalization behavior

The ability of the brain to learn from experience and to compensate for changes in sensory inputs is usually associated with plasticity in the cerebral cortex. Descending corticofugal pathways have been implicated in learning but there is limited evidence that subcortical processing is shaped by training. We show that sound-source location can be accurately decoded from neuronal populations recorded in the inferior colliculus of one or both hemispheres while ferrets perform a localization task. Furthermore, changes in neural decoding performance matched improvements in localization accuracy of individual animals when ferrets were trained to adapt to abnormal spatial cues resulting from reversible occlusion of one ear. These findings demonstrate that the activity patterns of populations of neurons in the inferior colliculus can account for sound localization behavior in different hearing contexts, and that training-dependent plasticity in the auditory midbrain may support spatial learning following monaural hearing loss.

neuroscience↗

bioRxiv2025

Hierarchical recurrent temporal prediction as a model of the mammalian dorsal visual pathway

A major goal of neuroscience is to identify whether there are generalized principles that can explain the diverse structures and functions of the brain. The principle of temporal prediction provides one approach, arguing that the sensory brain is optimized to represent stimulus features that efficiently predict the immediate future input. Previous work has demonstrated that feedforward hierarchical temporal prediction models can capture the tuning properties of neurons along the visual pathway, and that recurrent temporal prediction models can explain local functional connectivity within primary visual cortex. However, the visual system is also characterized by extensive inter-areal feedback recurrency, which existing models lack. We aimed to better account for the dynamic features of neurons in the visual cortex by incorporating both local recurrency and inter-areal feedback connectivity into a hierarchical temporal prediction model. The resulting model captured tuning for pattern motion, surround suppression and elements of inter-areal functional connectivity in visual cortex. Moreover, compared with several alternative normative models, the hierarchical recurrent temporal prediction model provided the closest fit to these tuning properties and was best able to explain the emergence of neuronal response properties across the visual cortex. Accordingly, temporal prediction can account for information processing throughout the visual pathway. Author summaryTask-driven artificial neural networks have provided valuable insights into the computational operations performed by neurons in the brain. In particular, models trained on various normative principles have been shown to capture some of the feature selectivity of neurons in the visual system. However, these models generally ignore the substantial role of inter-areal feedback connectivity in neural function. This study presents an alternative approach to understanding the neural computations underlying the functional organization of the visual system, by providing compelling evidence that networks trained for temporal prediction can explain the emergence of higher-level response properties across the visual cortex and relating these features to both local and inter-areal feedback connectivity.

neuroscience↗

bioRxiv2025

More dominant baboons have less and lower quality sleep

The amount and quality of sleep individuals get can impact various aspects of human and non-human animal health, ultimately affecting fitness. For wild animals that sleep in groups, individuals may disturb one another, influencing sleep quality and quantity, but this aspect of social sleep has been understudied due to methodological challenges. Here, using nighttime rest (absence of bodily movements) as a proxy for sleep, we test the hypothesis that individuals social dominance can affect sleep opportunities by studying a troop of wild chacma baboons (Papio ursinus), a species with a strong hierarchical social structure. First, we show that the troops night-time rest (determined by 40Hz acceleration data) is highly synchronised. Next, we link night-time rest dynamics to daytime spatial networks and dominance hierarchy (from 1Hz GPS data and direct observations). We show that baboon rest synchrony is higher between similarly ranked individuals, and unexpectedly, more dominant baboons experience less and lower-quality rest. We propose that this hierarchy effect is explained by higher-ranked baboons resting closer to more group members, which also leads them exerting greater influence on each others night-time behaviour compared to lower-ranked individuals. Our study provides the first empirical evidence for the impact of social hierarchies on sleep in a wild primate, suggesting that dominance status may impose trade-offs between social rank and the quality and quantity of sleep.

animal behavior and cognition↗

bioRxiv2024

Comprehensive Characterization of BTK Inhibitor Specificity, Potency, and Biological Effects: Insights into Covalent and Non-covalent Mechanistic Signatures

AbstractUncovering a drugs mechanism of action and possible adverse effects are critical components in drug discovery and development. Moreover, it provides evidence for why some drugs prove more effective than others, and how to design better drugs altogether. Here we demonstrate the utility of a high- throughput in vitro screening platform along with a comprehensive panel to aid in the characterization of fifteen BTK inhibitors that are either approved by the FDA or presently under clinical evaluation. To compare the potency of these drugs, we measured the binding affinity of each to wild-type BTK, as well as a clinically relevant resistance mutant of BTK (BTK C481S). In doing so, we discovered a considerable difference in the selectivity and potency of these BTK inhibitors to the wild-type and mutant proteins. Some of this potentially contributes to the adverse effects experienced by patients undergoing therapy using these drugs. Overall, non-covalent BTK inhibitors showed stronger potency for both the wild-type and mutant BTK when compared with that of covalent inhibitors, with the majority demonstrating a higher specificity and less off-target modulation. Additionally, we compared biological outcomes for four of these inhibitors in human cell-based models. As expected, we found different phenotypic profiles for each inhibitor. However, the two non-covalent inhibitors had fewer off-target biological effects when compared with the two covalent inhibitors. This and similar in-depth preclinical characterization of drug candidates can provide critical insights into the efficacy and mechanism of action of a compound that may affect its safety in a clinical setting. Table of Contents/Abstract Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/611550v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@744cf2org.highwire.dtl.DTLVardef@167cf2forg.highwire.dtl.DTLVardef@5326c4org.highwire.dtl.DTLVardef@1163b29_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2024

Prediction of future input explains lateral connectivity in primary visual cortex

Neurons in primary visual cortex (V1) show a remarkable functional specificity in their pre- and postsynaptic partners. Recent work has revealed a variety of wiring biases describing how the short- and long-range connections of V1 neurons relate to their tuning properties. However, it is less clear whether these connectivity rules are based on some underlying principle of cortical organization. Here, we show that the functional specificity of V1 connections emerges naturally in a recurrent neural network optimized to predict upcoming sensory inputs for natural visual stimuli. This temporal prediction model reproduces the complex relationships between the connectivity of V1 neurons and their orientation and direction preferences, the tendency of highly connected neurons to respond more similarly to natural movies, and differences in the functional connectivity of excitatory and inhibitory V1 populations. Together, these findings provide a principled explanation for the functional and anatomical properties of early sensory cortex.

neuroscience↗

bioRxiv2024

Temporal prediction captures key differences between spiking excitatory and inhibitory V1 neurons

Neurons in primary visual cortex (V1) respond to natural scenes with a sparse and irregular spike code that is carefully balanced by an interplay between excitatory and inhibitory neurons. These neuron classes differ in their spike statistics, tuning preferences, connectivity statistics and temporal dynamics. To date, no single computational principle has been able to account for these properties. We developed a recurrently connected spiking network of excitatory and inhibitory units trained for efficient temporal prediction of natural movie clips. We found that the model exhibited simple and complex cell-like tuning, V1-like spike statistics, and, notably, also captured key differences between excitatory and inhibitory V1 neurons. This suggests that these properties collectively serve to facilitate efficient prediction of the sensory future.

neuroscience↗

bioRxiv2024

Cortical evoked activity is modulated by the sleep state in a ferret model of tinnitus. A case study.

Subjective tinnitus is a phantom auditory perception in the absence of an actual acoustic stimulus. It affects 15% of the global population and can be associated with disturbed sleep, poor mental health and quality of life. To date, there is no effective treatment for tinnitus. We used adult ferrets exposed to mild noise trauma as an animal model of tinnitus. We assessed the phantom percept using two operant paradigms sensitive to tinnitus, silent gap detection and silence detection, before and up to six months after the mild acoustic trauma. The integrity of the auditory brainstem was assessed over the same period using auditory brainstem response recordings. Following noise overexposure, ferrets developed lasting, frequency-specific impairments in operant behaviour and evoked brainstem activity. To explore the interaction between sleep and tinnitus, in addition to tracking the behavioural markers of noise-induced tinnitus and hearing impairment after noise overexposure, we evaluated sleep-wake architecture and spontaneous and auditory-evoked EEG activity across vigilance states. Behavioural performance and auditory-evoked activity measurements after noise overexposure suggested distinct degrees of tinnitus and hearing impairment between individuals. Animals that developed signs of tinnitus consistently developed sleep impairments, suggesting a link between the emergence of noise-induced tinnitus and sleep disruption. However, neural markers of tinnitus were reduced during sleep, suggesting that sleep may transiently mitigate tinnitus. These results reveal the importance of sleep-wake states in tinnitus and suggest that understanding the neurophysiological link between sleep and tinnitus may provide a new angle for research into the causes of phantom percepts and inform future treatments.

neuroscience↗

bioRxiv2024

Temporal prediction captures retinal spiking responses across animal species

The retinas role in visual processing has been viewed as two extremes: an efficient compressor of incoming visual stimuli akin to a camera, or as a predictor of future stimuli. Addressing this dichotomy, we developed a biologically-detailed spiking retinal model trained on natural movies under metabolic-like constraints to either encode the present or to predict future scenes. Our findings reveal that when optimized for efficient prediction[~] 100 ms into the future, the model not only captures retina-like receptive fields and their mosaic-like organizations, but also exhibits complex retinal processes such as latency coding, motion anticipation, differential tuning, and stimulus-omission responses. Notably, the predictive model also more accurately predicts the way retinal ganglion cells respond across different animal species to natural images and movies. Our findings demonstrate that the retina is not merely a compressor of visual input, but rather is fundamentally organized to provide the brain with foresight into the visual world.

neuroscience↗

bioRxiv2024

Subcortical origin of nonlinear sound encoding in auditory cortex

A major challenge in neuroscience is to understand how neural representations of sensory information are transformed by the network of ascending and descending connections in each sensory system. By recording from neurons at several levels of the auditory pathway, we show that much of the nonlinear encoding of complex sounds in auditory cortex can be explained by transformations in the midbrain and thalamus. Modeling cortical neurons in terms of their inputs across these subcortical populations enables their responses to be predicted with unprecedented accuracy. In contrast, subcortical responses cannot be predicted from descending cortical inputs, indicating that ascending transformations are irreversible, resulting in increasingly lossy, higher-order representations across the auditory pathway. Rather, auditory cortex selectively modulates the nonlinear aspects of thalamic auditory responses and the functional connectivity between subcortical neurons, without affecting the linear encoding of sound. These findings reveal the fundamental role of subcortical transformations in shaping cortical responses.

neuroscience↗

bioRxiv2023

Auditory training alters the cortical representation of both learned and task irrelevant sound features

Auditory learning is supported by long-term changes in the neural processing of sound. We examined these task-depend changes in auditory cortex by mapping neural sensitivity to timbre, pitch and location cues in trained ferrets (n = 5), and untrained control ferrets (n = 5). Trained animals either identified vowels in a two-alternative forced choice task (n = 3) or discriminated when a repeating vowel changed in identity or pitch (n = 2). Neural responses were recorded under anesthesia in two primary auditory cortical fields and two tonotopically organized non-primary fields. In trained animals, the overall sensitivity to sound timbre was reduced across three cortical fields compared to control animals, but maintained in a non-primary field (the posterior pseudosylvian field). While training did not increase sensitivity to timbre across auditory cortex, it did change the way in which neurons integrated spectral information with neural responses in trained animals increasing their sensitivity to first and second formant frequencies,, whereas in control animals cortical sensitivity to spectral timbre depends mostly on the second formant. Animals trained on timbre identification were required to generalize across pitch when discriminating timbre and their neurons became less modulated by fundamental frequency relative to control animals. Finally, both trained groups showed increased spatial sensitivity and an enhanced response to sound source locations close to the midline, where the loudspeaker was located in the training chamber. These results demonstrate that training elicited widespread alterations in the cortical representation of complex sounds.

neuroscience↗

bioRxiv2023

Cochlear tuning characteristics arise from temporal prediction of natural sounds

The cochlea decomposes incoming sound waveforms into different frequency components along the length of its basilar membrane. The receptor hair cells at the apical end of this resonant membrane are tuned to the lowest sound frequencies, with the preferred sound frequency of hair cell tuning increasing near-exponentially along the length of the membrane towards its basal end. This frequency composition of the sound is then transmitted to the brain by the auditory nerve fibers that innervate the inner hair cells. Hair cells respond to a sound impulse with a temporally asymmetric envelope and the sharpness of their tuning changes as the frequency to which they are most sensitive varies with their position along the basilar membrane. We ask if there is a normative explanation for why the cochlea decomposes sounds in this manner. Inspired by findings in the retina, we propose that cochlear tuning properties may be optimized for temporal prediction. This principle states that the sensory features represented by neurons are optimized to predict immediate future input from recent past input. We show that an artificial neural network optimized for temporal prediction of the immediate future of raw waveforms of natural sounds from their recent past produces tuning properties that resemble those observed in the auditory nerve. Specifically, the model captures the temporally asymmetric impulse responses, the tonotopic distribution and variation in tuning sharpness along the cochlea, and the frequency glide polarity of the impulse responses. These characteristics are not captured by a similar model optimized for compression of the sound waveform, rather than prediction. Given its success in accounting for the tuning properties at various processing levels in the auditory and visual systems, this finding for the cochlea provides further evidence that temporal prediction may be a general principle of sensory processing.

neuroscience↗

bioRxiv2023

Midbrain encodes sound detection behavior without auditory cortex

Hearing involves analyzing the physical attributes of sounds and integrating the results of this analysis with other sensory, cognitive and motor variables in order to guide adaptive behavior. The auditory cortex is considered crucial for the integration of acoustic and contextual information and is thought to share the resulting representations with subcortical auditory structures via its vast descending projections. By imaging cellular activity in the corticorecipient shell of the inferior colliculus of mice engaged in a sound detection task, we show that the majority of neurons encode information beyond the physical attributes of the stimulus and that the animals behavior can be decoded from the activity of those neurons with a high degree of accuracy. Surprisingly, this was also the case in mice in which auditory cortical input to the midbrain had been removed by bilateral cortical lesions. This illustrates that subcortical auditory structures have access to a wealth of non-acoustic information and can, independently of the auditory cortex, carry much richer neural representations than previously thought.

neuroscience↗