Biology subjects

Anderson, A. J.

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

18 recordsLinked to original sources

bioRxiv2026

Aging reveals domain-specific vulnerability to the chronic behavioral consequences of repetitive mild traumatic brain injury

Older adults are among the fastest growing groups of traumatic brain injury (TBI) patients and sustain disproportionately poor chronic outcomes. Despite this, the preclinical aging-TBI literature is limited. Beyond the limited presence of aging TBI studies, most studies published in this domain use moderate-to-severe, open head models of TBI, rather than closed head models of mild TBI (mTBI) and repetitive mTBI (rmTBI), the most clinically prevalent presentation. Whether age modulates the chronic behavioral consequences of rmTBI is unknown. In the current study, young (3-4 months) and aged (18-19 months) male C57BL/6 mice received either five mTBIs on alternating days to model rmTBI or sham procedures and underwent behavioral testing in the chronic phase for spatial memory and anxiety-related behavior. Because cross-age behavioral comparisons are confounded by age-related declines in activity and by large sample sizes necessary to detection interaction effects, we applied a three-tier analytical framework combining within-age comparisons, sham-normalized inter-age comparisons, and factorial two-way ANOVA. Contrary to our hypothesis that aging would worsen rmTBI behavioral deficits, age produced domain-divergent effects. Spatial memory deficits were directionally consistent in both young and aged mice but was attenuated in the aged group. Conversely, anxiety-related behavior emerged selectively in the aged mice showing increased thigmotaxis. Locomotion was driven by age alone, with no injury effect, confirming that the aged anxiety signal was not a locomotor artifact. A post-hoc sensitivity analysis indicated that resolving the Age x Injury interaction effect would require at least 44 animals per group. These findings show that age shapes the affective, but not the cognitive, consequences of chronic rmTBI, and underscoring that statistical strategy is inseparable from design in factorial injury studies.

neuroscience↗

bioRxiv2026

Microtubule Stabilization and Biomaterial Guidance Synergize to Enhance CST Regeneration and Motor Recovery After Chronic SCI.

Spinal cord injury (SCI) results in loss of sensory and motor function below the level of damage, with chronic injuries presenting unique challenges for regenerative therapies. While multichannel biomaterial interventions have shown promise in promoting axonal regeneration, circuit restoration, and motor recovery in acute SCI, achieving similar outcomes in chronic injury models remains challenging due to a combination of intrinsic and extrinsic factors. These include the reduced capacity of the neuronal cell body to sustain a growth-activated state and the formation of a physical and chemical barrier at the injury site, preventing axonal growth. To address these challenges and promote motor recovery after chronic injury, we investigated the combinatorial effect of two regenerative approaches: 1) the implantation of poly (lactide-co-glycolide) (PLG) biomaterial bridge to guide axonal growth through the injury site, and 2) the delivery of Epothilone B (EpoB), a microtubule stabilizer that strengthens axons to promote regrowth. We used a transgenic mouse model that selectively expresses a red fluorescent protein variant (tdTomato) reporter throughout the corticospinal tract (CST) under control of the Crym promoter (Crym-tdTomato). We demonstrated that the combination of bridge implantation 60 days after surgical hemisection at C5 with EpoB improved locomotor function. At 12 weeks post-bridge implantation, immunohistology revealed axon regeneration in mice receiving implantation, but not EpoB or no-implant controls. The addition of EpoB significantly increased the volume of both total and CST axons regenerating through the biomaterial channels. Diffusion tensor magnetic resonance imaging (DTI) analysis identified enhanced fractional anisotropy (FA), axial diffusivity (AD), and mean diffusivity (MD) in the bridge region in the combination treatment group, consistent with new intact axons. Furthermore, EpoB enhanced the myelination of regenerated axons in the bridge. Finally, we investigated the proteomic profile of corticospinal neurons ipsilateral and contralateral to the SCI lesion and bridge, comparing the effect of EpoB treatment. Mass spectrometry-based analysis of laser-captured cells in this paradigm identified activation of a regeneration program by corticospinal neurons. These findings present a novel approach to enhance regenerative neural repair and locomotor recovery in chronic SCI.

neuroscience↗

bioRxiv2025

Medial Temporal Default Mode Network Selectively Encodes Autobiographical Visual Imagery

The human brains capacity to imagine visual scenes from memory is thought to rely on the medial temporal subsystem of the default mode network (MT-DMN), yet the neural codes supporting this ability remain poorly understood. We combined functional magnetic resonance imaging (fMRI) with vision and language artificial intelligence models to characterize neural codes during autobiographical imagination. Fifty participants imagined reexperiencing twenty natural scenarios while undergoing fMRI, when cued by generic text prompts (e.g., wedding, exercising, driving). Individual scenes were modeled using Stable Diffusion to generate personalized synthetic images from verbal descriptions of the scenarios imagined, collected beforehand. These depictions were then transformed into image-recognition network embeddings. Representational Similarity Analysis revealed that the MT-DMN encoded the participant-specific representational structure of image embeddings, even when controlling for semantic features derived from a large language model. This effect was absent in other networks and during reading without imagination, identifying the MT-DMN as a core substrate for the visual reconstruction of autobiographical experiences.

neuroscience↗

bioRxiv2025

A default-control network cortical gradient differentiates the imagination of social and solitary experiences

Understanding the neural basis of spontaneous thought - when attention shifts from external tasks to internally generated content such as reminiscing or planning - remains a central challenge in cognitive neuroscience. Progress in this area has lagged studies of externally driven cognition, in part because self-generated thought is difficult to control and measure. Recent work suggests that transitions between externally and internally focused cognitive states follow a continuous neural activation gradient that reflects opposing patterns of engagement of the frontoparietal control network versus the default mode network. To characterize internally focused cognitive states that prospectively engage the default mode network, we used functional Magnetic Resonance Imaging (fMRI) to measure brain activity while participants imagined a range of personal scenarios prompted by generic text cues (e.g., party, housework) to mimic natural thought. Before scanning, participants described each scenario verbally and rated its experiential feature content. Gradient-space analysis revealed a cognitive transition within imagined states: solitary activities (e.g., housework) preferentially recruited the frontoparietal network relative to the default mode network, whereas social activities (e.g., a party) showed the opposite pattern. Because all cognitive states were internally focused (imagined) and elicited via the same non-interactive task, these results refine interpretations of the frontoparietal-default mode gradient. They show that this gradient does not simply differentiate external task-positive from internal task-negative states but also tracks semantic differences between internal cognitive states.

neuroscience↗

bioRxiv2025

A common representational code for event and object concepts in the brain

Events and objects are two fundamental ways in which humans conceptualize their experience of the world. Despite the significance of this distinction for human cognition, it remains unclear whether the neural representations of object and event concepts are categorically distinct or, instead, can be explained in terms of a shared representational code. We investigated this question by analyzing fMRI data acquired from human participants (males and females) while they rated their familiarity with the meanings of individual words (all nouns) denoting object and event concepts. Multivoxel pattern analyses indicated that both categories of lexical concepts are represented in overlapping fashion throughout the association cortex, even in the areas that showed the strongest selectivity for one or the other type in univariate contrasts. Crucially, in these areas, a feature-based model trained on neural responses to individual event concepts successfully decoded object concepts from their corresponding activation patterns (and vice versa), showing that these two categories share a common representational code. This code was effectively modeled by a set of experiential feature ratings, which also accounted for the mean activation differences between these two categories. These results indicate that neuroanatomical dissociations between events and objects emerge from quantitative differences in the cortical distribution of more fundamental features of experience. Characterizing this representational code is an important step in the development of theory-driven brain-computer interface technologies capable of decoding conceptual content directly from brain activity. Significance StatementWe investigated how word meaning is encoded in the brain by examining the neural representations of individual lexical concepts from two distinct categories--objects and events. We found that both kinds of concepts were encoded in neural activity patterns in terms of a shared representational space characterized by different modalities of perceptual and emotional experience. This indicates that individual concepts from a wide variety of semantic categories can, at least in principle, be decoded from neural activity using a generative model of concept representation based on interpretable semantic features. Furthermore, both object and event concepts could be decoded from cortical regions previously hypothesized to encode category-specific representations, suggesting that the two categories are jointly represented in these areas.

neuroscience↗

bioRxiv2024

Mouse brain organoids model in vivo neurodevelopment and function and capture differences to human

In the last decade since their emergence, brain organoids have offered an increasingly popular and powerful model for the study of early development and disease in humans. These 3D stem cell-derived models exist in a newer space at the intersection of in vivo and 2D in vitro models. Functional benchmarking has so far remained largely uncharacterised however, leaving the extent to which these models may accurately portray in vivo processes still yet to be fully realised. Here we present a standardised unguided protocol to generate brain organoids from mice, the most commonly-used in vivo mammalian model; and in parallel establish a guided protocol for generating region-specific choroid plexus mouse organoids. Both unguided and guided mouse organoids progress through neurodevelopmental stages with an in vivo-like tempo and recapitulate species-specific characteristics of neural and choroid plexus development, respectively. Neuroepithelial cells generate neural progenitors that give rise to different neural subtypes including deep-layer neurons, upper-layer neurons, and glial cells. We further adapted protocols to prolong mouse cerebral organoid (CO) cultures as slices at the air-liquid interface (ALI), enhancing accessibility for long-term studies and functional investigations. In mature mouse ALI-COs, we observed mature glia, as well as synaptic structures and long-range axon tracts projecting to distant regions, suggesting an establishment and maturation of neural circuitry. Indeed, functional analyses with high-density multi-electrode arrays (HD-MEAs) indicate comparable activity to ex vivo organotypic mouse brain slices. Having established protocols for both region-specific and unpatterned mouse brain organoids, we demonstrate that their neurodevelopmental trajectories, and resultant mature features, closely mimic the in vivo models to which they are benchmarked across multiple biochemical, morphological, and functional read-outs. We propose that mouse brain organoids are a valuable model for functional studies, and provide insight into how closely brain organoids of other species, such as human, may recapitulate their own respective in vivo development.

neuroscience↗

bioRxiv2024

Dynamic modeling of EEG responses to natural speech reveals earlier processing of predictable words

In recent years, it has become clear that EEG indexes the comprehension of natural, narrative speech. One particularly compelling demonstration of this fact can be seen by regressing EEG responses to speech against measures of how individual words in that speech linguistically relate to their preceding context. This approach produces a so-called temporal response function that displays a centro-parietal negativity reminiscent of the classic N400 component of the event-related potential. One shortcoming of previous implementations of this approach is that they have typically assumed a linear, time-invariant relationship between the linguistic speech features and the EEG responses. In other words, the analysis typically assumes that the response has the same shape and timing for every word - and only varies (linearly) in terms of its amplitude. In the present work, we relax this assumption under the hypothesis that responses to individual words may be processed more rapidly when they are predictable. Specifically, we introduce a framework wherein the standard linear temporal response function can be modulated in terms of its amplitude, latency, and temporal scale based on the expectedness of the current and prior words. We use the proposed approach to model EEG recorded from a set of participants who listened to an audiobook narrated by a single talker, and a separate set of participants who attended to one of two concurrently presented audiobooks. We show that expected words are processed faster - evoking lower amplitude N400-like responses with earlier peaks - and that this effect is driven both by the words own predictability and the predictability of the immediately preceding word. Additional analysis suggests that this finding is not simply explained based on how quickly words can be disambiguated from their phonetic neighbors. As such, our study demonstrates that the timing and amplitude of brain responses to words in natural speech depend on their predictability. By accounting for these effects, our framework also improves the accuracy with which neural responses to natural speech can be modeled.

neuroscience↗

bioRxiv2024

Minimally invasive serial collection of cerebrospinal fluid reveals sex-dependent differences in neuroinflammation in a rat model of mild traumatic brain injury

Traumatic brain injuries (TBI) are the seventh leading cause of disability globally with 48.99 million prevalent cases and 7.08 million years lived with diability. Approximately 80% of TBI patients are diagnosed with mild TBI (mTBI), or concussion, caused by nonpenetrating mechanical trauma to the head or body along with sudden rotational motion of the head. Studies investigating the temporal dynamics of neuroinflammation after mTBI are greatly needed. Without longitudinal studies, translating preclinical studies to clinical studies remains challenging as the difference in timing remains poorly understood. In this study, we describe a method of minimally invasive serial cerebrospinal fluid (CSF) collection that enables longitudinal investigation of CSF inflammation. The method described in this study can easily be adapted by any laboratory prepared for animal studies. Multiplex immunoassay of serially collected and singly collected CSF samples show collection frequency does not alter protein expression in the CSF. Further, sex-dependent differences in TBI have been reported, but remain poorly understood. This study establishes a framework for assessing sex difference in neuroinflammation after a concussion. We showed that results vary based on the framing of the statistical test. However, it is evident that males experience a more robust inflammatory response to a single concussion than females.

neuroscience↗

bioRxiv2023

Context and Attention Shape Electrophysiological Correlates of Speech-to-Language Transformation

To transform speech into words, the human brain must accommodate variability across utterances in intonation, speech rate, volume, accents and so on. A promising approach to explaining this process has been to model electroencephalogram (EEG) recordings of brain responses to speech. Contemporary models typically invoke speech categories (e.g. phonemes) as an intermediary representational stage between sounds and words. However, such categorical models are typically hand-crafted and therefore incomplete because they cannot speak to the neural computations that putatively underpin categorization. By providing end-to-end accounts of speech-to-language transformation, new deep-learning systems could enable more complete brain models. We here model EEG recordings of audiobook comprehension with the deep-learning system Whisper. We find that (1) Whisper provides an accurate, self-contained EEG model of speech-to-language transformation; (2) EEG modeling is more accurate when including prior speech context, which pure categorical models do not support; (3) EEG signatures of speech-to-language transformation depend on listener-attention.

neuroscience↗

bioRxiv2023

Mapping the architecture of the initiating phosphoglycosyl transferase from S. enterica O-antigen biosynthesis in a liponanoparticle.

Bacterial cell surface glycoconjugates are critical for cell survival and for interactions between bacteria and their hosts. Consequently, the pathways responsible for their biosynthesis have untapped potential as therapeutic targets. The localization of many glycoconjugate biosynthesis enzymes to the membrane represents a significant challenge for expressing, purifying, and characterizing these enzymes. Here, we leverage cutting-edge methods to stabilize, purify, and structurally characterize WbaP, a phosphoglycosyl transferase (PGT) from Salmonella enterica (LT2) O-antigen biosynthesis without detergent solubilization from the lipid bilayer. From a functional perspective, these studies establish WbaP as a homodimer, reveal the structural elements responsible for oligomerization, shed light on the regulatory role of a domain of unknown function embedded within WbaP, and identify conserved structural motifs between PGTs and functionally unrelated UDP-sugar dehydratases. From a technological perspective, the strategy developed here is generalizable and provides a toolkit for studying small membrane proteins embedded in liponanoparticles beyond PGTs.

biochemistry↗

bioRxiv2023

Electrophysiological indices of hierarchical speech processing differentially reflect the comprehension of speech in noise

The past few years have seen an increase in the use of encoding models to explain neural responses to natural speech. The goal of these models is to characterize how the human brain converts acoustic energy into distinct linguistic representations that enable everyday speech comprehension. For example, researchers have shown that electroencephalography (EEG) data can be modeled in terms of acoustic features of speech, such as its amplitude envelope or spectrogram, linguistic features such as phonemes and phoneme probability, and higher-level linguistic features like context-based word predictability. However, it is unclear how reliably EEG indices of these speech feature representations reflect comprehension in different listening conditions. To address this, we recorded EEG from neurotypical adults who listened to segments of an audiobook in various levels of background noise. We modeled how their EEG responses reflected a range of acoustic and linguistic speech features and how this tracking varied with behavior across noise levels. EEG tracking of nearly all examined features showed SNR-dependent changes in unique variance explained, with the largest changes occurring for linguistic features. We hypothesized that only higher-level feature tracking would predict behavior but instead found that both high and low-level features were associated with behavioral scores depending on the noise level. EEG markers of the influence of top-down, context-based prediction on bottom-up acoustic processing also correlated with behavior. These findings help characterize the relationship between brain and behavior by comprehensively linking hierarchical indices of neural speech processing to language comprehension metrics. SIGNIFICANCE STATEMENTAcoustic and linguistic features of speech have been shown to be consistently tracked by neural activity even in noisy conditions. However, it is unclear how signatures of low- and high-level features covary with one another and relate to behavior across these listening conditions. Here, we find that linguistic (phonetic feature and word probability-based feature) processing is affected by noise more than low-level acoustic feature processing. We also find that behavioral performance is associated with acoustic, phonetic, and lexical surprisal tracking, and that these associations depend on background noise levels. These results extend our understanding of how various speech features are comparatively reflected in electrical brain activity and how they relate to perception in challenging listening conditions.

neuroscience↗

bioRxiv2020

More than Words: Neurophysiological Correlates of Semantic Dissimilarity Depend on Comprehension of the Speech Narrative

Speech comprehension relies on the ability to understand the meaning of words within a coherent context. Recent studies have attempted to obtain electrophysiological indices of this process by modelling how brain activity is affected by a words semantic dissimilarity to preceding words. While the resulting indices appear robust and are strongly modulated by attention, it remains possible that, rather than capturing the contextual understanding of words, they may actually reflect word-to-word changes in semantic content without the need for a narrative-level understanding on the part of the listener. To test this possibility, we recorded EEG from subjects who listened to speech presented in either its original, narrative form, or after scrambling the word order by varying amounts. This manipulation affected the ability of subjects to comprehend the narrative content of the speech, but not the ability to recognize the individual words. Neural indices of semantic understanding and low-level acoustic processing were derived for each scrambling condition using the temporal response function (TRF) approach. Signatures of semantic processing were observed for conditions where speech was unscrambled or minimally scrambled and subjects were able to understand the speech. The same markers were absent for higher levels of scrambling when speech comprehension dropped below chance. In contrast, word recognition remained high and neural measures related to envelope tracking did not vary significantly across the different scrambling conditions. This supports the previous claim that electrophysiological indices based on the semantic dissimilarity of words to their context reflect a listeners understanding of those words relative to that context. It also highlights the relative insensitivity of neural measures of low-level speech processing to speech comprehension.

neuroscience↗

bioRxiv2020

Freshly Thawed Cryobanked Human Neural Stem Cells Engraft within Endogenous Neurogenic Niches and Restore Cognitive Function Following Chronic Traumatic Brain Injury

Human neural stem cells (hNSCs) have potential as a cell therapy following traumatic brain injury (TBI). While various studies have demonstrated the efficacy of NSCs from on-going culture, there is a significant gap in our understanding of freshly thawed cells from cryobanked stocks - a more clinically-relevant source. To address these shortfalls, the therapeutic potential of our previously validated Shef-6.0 human embryonic stem cell (hESC)-derived hNSC line was tested following long-term cryostorage and thawing prior to transplant. Immunodeficient athymic nude rats received a moderate unilateral controlled cortical impact (CCI) injury. At 4-weeks post-injury, 6x105 freshly thawed hNSCs were transplanted into six injection sites (2 ipsi- and 4 contra-lateral) with 53.4% of cells surviving three months post-transplant. Interestingly, most hNSCs were engrafted in the meninges and the lining of lateral ventricles, associated with high CXCR4 expression and a chemotactic response to SDF1alpha (CXCL12). While some expressed markers of neuron, astrocyte, and oligodendrocyte lineages, the majority remained progenitors, identified through doublecortin expression (78.1%). Importantly, transplantation resulted in improved spatial learning and memory in Morris water maze navigation and reduced risk-taking behavior in an elevated plus maze. Investigating potential mechanisms of action, we identified an increase in ipsilateral host hippocampus cornu ammonis (CA) neuron survival, contralateral dentate gyrus (DG) volume and DG neural progenitor morphology as well as a reduction in neuroinflammation. Together, these findings validate the potential of hNSCs to restore function after TBI and demonstrate that long-term bio-banking of cells and thawing aliquots prior to use may be suitable for clinical deployment. Significance StatementThere is no cure for chronic traumatic brain injury (TBI). While human neural stem cells (hNSCs) offer a potential treatment, no one has demonstrated efficacy of thawed hNSCs from long-term cryobanked stocks. Frozen aliquots are critical for multisite clinical trials, as this omission impacted the use of MSCs for graft versus host disease. This is the first study to demonstrate the efficacy of thawed hNSCs, while also providing support for novel mechanisms of action - linking meningeal and ventricular engraftment to reduced neuroinflammation and improved hippocampal neurogenesis. Importantly, these changes also led to clinically relevant effects on spatial learning/memory and risk-taking behavior. Together, this new understanding of hNSCs lays a foundation for future work and improved opportunities for patient care.

neuroscience↗

bioRxiv2020

Calibration and Evaluation of a Force Measurement Glove for Field-Based Monitoring of Manual Wheelchair Users

Manual wheelchair users exhibit pain related to repetitive and demanding shoulder activities of daily living. Wearable sensing systems like force measurement gloves can provide insights about upper extremity loading in the community and home environments. We calibrated and evaluated the accuracy of a novel force measurement glove with a body-worn data logger. The device was calibrated with loads of 0-800 N applied to the palmar surface of the glove. Calibration conditions were tested that varied the stiffness of the material in the glove, the temperature, and the curvature of the force applicator. Calibration equations from each condition were evaluated by comparing the gloves force prediction with the output of an instrumented wheelchair rim during propulsion and weight relief exercises. The force measurement glove detected 72.7% of 355 propulsion peaks and had a strong linear correlation with the instrumented rim force measurements (r=0.80). The most accurate calibration equation was constructed using data from all conditions, with an RMS force measurement error of 64.7 N and 31.7 N for weight relief exercise and propulsion, respectively. The force measurement glove design described here may serve as a useful tool for detection of loading events and relative magnitude changes.

bioengineering↗

bioRxiv2020

Lentiviral interleukin-10 gene therapy preserves fine motor circuitry and function after a cervical spinal cord injury in male and female mice

In mammals, spinal cord injuries often result in muscle paralysis through the apoptosis of lower motor neurons and denervation of neuromuscular junctions. Previous research shows that the inflammatory response to a spinal cord injury can cause additional tissue damage after the initial trauma. To modulate this inflammatory response, we delivered lentiviral anti-inflammatory interleukin-10, via loading onto an implantable biomaterial scaffold, into a left-sided hemisection at the C5 vertebra in mice. We hypothesized that improved behavioral outcomes associated with anti-inflammatory treatment are due to the sparing of fine motor circuit components. We examined behavioral recovery using a ladder beam, lower motor neuron apoptosis and muscle innervation using histology, and electromyogram recordings using intraspinal optogenetic stimulation at 2 weeks post-injury. Ladder beam analysis shows interleukin-10 treatment results in significant improvement of behavioral recovery at 2 and 12 weeks post-injury when compared to mice treated with a control virus. Histology shows interleukin-10 results in greater numbers of lower motor neurons and muscle innervation at 2 weeks post-injury. Furthermore, electromyogram recordings suggest that interleukin-10-treated animals have signal-to-noise ratios and peak-to-peak amplitudes more similar to that of uninjured controls than to that of control injured animals at 2 weeks post-injury. These data show that gene therapy using anti-inflammatory interleukin-10 can significantly reduce lower motor neuron loss, muscle denervation, and subsequent motor deficits after a spinal cord injury. Together, these results suggest that early modulation of the injury response can preserve muscle function with long-lasting benefits.

neuroscience↗

bioRxiv2020

Dissociable electrophysiological measures of natural language processing reveal differences in comprehension strategy in healthy ageing

Healthy ageing leads to changes in the brain that impact upon sensory and cognitive processing. It is not fully clear how these changes affect the processing of everyday spoken language. Prediction is thought to play an important role in language comprehension, where information about upcoming words is pre-activated across multiple representational levels. However, evidence from electrophysiology suggests differences in how older and younger adults use context-based predictions, particularly at the level of semantic representation. We investigate these differences during natural speech comprehension by presenting older and younger subjects with continuous, narrative speech while recording their electroencephalogram. We use linear regression to test how distinct computational measures of 1) semantic dissimilarity and 2) lexical surprisal are processed in the brains of both groups. Our results reveal dissociable neural correlates of these two measures that suggest differences in how younger and older adults successfully comprehend speech. Specifically, our results suggest that, while younger and older subjects both employ context-based lexical predictions, older subjects are significantly less likely to pre-activate the semantic features relating to upcoming words. Furthermore, across our group of older adults, we show that the weaker the neural signature of this semantic pre-activation mechanism, the lower a subjects semantic verbal fluency score. We interpret these findings as prediction playing a generally reduced role at a semantic level in the brains of older listeners during speech comprehension and that these changes may be part of an overall strategy to successfully comprehend speech with reduced cognitive resources.

neuroscience↗

bioRxiv2019

Neuronal-specific function of hTim8a in Complex IV assembly provides insight into the molecular mechanism underlying Mohr-Tranebjaerg syndrome

Human Tim8a is a member of an intermembrane space chaperone network, known as the small TIM family, which transport hydrophobic membrane proteins through this compartment. Mutations in TIMM8A cause a neurodegenerative disease, Mohr-Tranebjaerg syndrome (MTS), which is characterised by sensorineural hearing loss, dystonia and blindness. Nothing is known about the function of hTim8a in neuronal cells and consequently how lack of hTim8a leads to a neurodegenerative disease. We identified a novel cell-specific function of hTim8a in the assembly of Complex IV, which is mediated through a transient interaction with the copper chaperone COX17. Complex IV assembly defects in cells lacking hTim8a leads to oxidative stress and changes to key apoptotic regulators, including cytochrome c and Bax, which primes cells for cell death. Alleviation of oxidative stress using Vitamin E rescues cells from apoptotic vulnerability. We hypothesis that enhanced sensitivity of neuronal cells to apoptosis is the underlying mechanism of MTS.

cell biology↗

bioRxiv2017

Electrophysiological correlates of semantic dissimilarity reflect the comprehension of natural, narrative speech.

Understanding natural speech requires that the human brain convert complex spectrotemporal patterns of acoustic input into meaning in a rapid manner that is reasonably tightly time-locked to the incoming speech signal. However, neural evidence for such a time-locked process has been lacking. Here, we sought such evidence by using a computational model to quantify the meaning carried by each word based on how semantically dissimilar it was to its preceding context and then regressing this quantity against electroencephalographic (EEG) data recorded from subjects as they listened to narrative speech. This produced a prominent negativity at a time-lag of 200- 600 ms on centro-parietal EEG electrodes. Subsequent EEG experiments involving time-reversed speech, cocktail party attention and audiovisual speech-in-noise demonstrated that this response was exquisitely sensitive to whether or not subjects were understanding the speech they heard. These findings demonstrate that, when successfully comprehending natural speech, the human brain encodes meaning as a function of the amount of new information carried by each word in a relatively time-locked fashion.

neuroscience↗