eneuro

GapAutomated spike sorting algorithms have revolutionized the way neuronal activity is extracted from extracellular recordings, yet they remain imperfect. Specifically, inaccurate acceptance of noise-based units not only leaves researchers with clusters that require extensive manual curation, an essential but time-consuming process, that also leads to significant subjectivity in the selection of units. In an era of high-density probes like Neuropixels, where an hour of data can exceed 80 GB, manual curation is no longer scalable, automation of standard criteria can speed data curation and ensure quality of datasets. Here, we developed a semi-automated curation pipeline to label the quality of units after automated curation by Kilosort. ApproachOur algorithm standardizes criteria for labeling of Noise, Multi-Unit Activity (MUA), and Good Units using a combination of spike rate, spike timing metrics (from autocorrelogram), and waveform-based physiological features such as peak amplitude, slopes, half-width, and inter-channel correlation. Based on these features, clusters are assigned standardized labels (good, noise, multi-unit activity) that can be imported directly into Phy, where they serve as curation aids rather than absolute classifications, supporting but not replacing expert judgment. Heuristically, "noise" units are those unlikely to be neuronal in origin; "MUA" includes units with significant neural contribution (i.e., neuronal waveform) but with some degree of clear imperfection to be further cleaned, and "good" units are those without any clear deviation from ideal unit criteria. By ensuring accurate selection of acceptable units, we enable robust downstream analyses such as neural decoding and longitudinal tracking of neuron identity. Thresholds for all metrics were chosen to maximize the matching of algorithm output to that of 2 expert manual curators. Of note, users may alter thresholds either based on their own judgment or using an included tool to semi-automatically find thresholds that optimize SpikeCleaner with their own expert curation. Results: To benchmark, we compared the outputs of our algorithm to expert-labels curated in Phy by two expert users across three recordings. SpikeCleaner achieved an average of 97% accuracy vs. experts & 92% F1 score in classifying Single Units. It achieved an accuracy of 97% & 92% F1 score in full-category agreement (SU, MUA, Noise), and 97% accuracy & 95% F1 score in distinguishing Neuronal vs. Non-Neuronal units.

Activity of the mesolimbic dopamine system has long been implicated in encoding primary rewards and contributing to the addictive properties of drugs of abuse. Dopamine neurons in the ventral tegmental area (VTADA) of the midbrain typically show patterns of spontaneous burst activity that align with the onset of salient events or rewarding stimuli, resulting in phasic dopamine release in the nucleus accumbens (NAc). Fiber photometry is increasingly being used as an accessible technique to quantify neural activity with high temporal resolution at sensors offering signal specificity in stable recordings over extended periods of time. It has been well established by multiple techniques that opioids increase mesolimbic dopamine activity, likely through disinhibition of VTADA neurons. Here we used fiber photometry to compare sub-second transient events from VTADA neurons with GCaMP6f and dopamine release in the lateral shell of the NAc with dLight1.3b and GRABDA2h in response to morphine treatment. In weekly sessions, one dose of morphine was administered in escalating order (2.5, 5,7.5, and 10 mg/kg, intraperitoneal). Consistent with prior literature, both GCaMP6f in VTADA neurons and dLight1.3b in NAc showed patterns of increased signal following morphine treatment. In contrast, morphine suppressed transient activity at GRABDA2h sensors. Further analyses of whole signal streams from each sensor showed a generalized increase, but reduction in variability of the GRABDA2h signal, consistent with the interpretation of sensor saturation. Such results emphasize the importance of the inclusion of appropriate controls to contextualize the interpretation of biosensor responses, particularly in response to pharmacological treatment. HIGHLIGHTSO_LIMorphine elicited increased signaling in VTADA GCaMP6f and NAc dLight1.3b, consistent with prior literature C_LIO_LIMorphine suppressed NAc GRABDA2h signaling of transient events, suggesting saturation of GRABDA2h sensor C_LIO_LISensor validation with pharmacological challenges is critical for interpretation of data C_LI

We investigated the dimensions of output zones affecting specific combinations of forelimb muscles in the precentral "motor" cortex of macaque monkeys. Single-pulse intracortical microstimulation (S-ICMS) was used to evoke subthreshold effects in multiple wrist and finger muscles. Results indicate that each motor cortex site represents a different combination of muscles. The effects evoked from cortical sites separated by several hundred microns invariably involved different profiles of muscle activity. The muscle fields of remote CM cells were rarely identical, while the fields of neighboring CM cells were often similar. Given the number of unrecorded muscles, we conclude that primate motor cortex is a mosaic of output sites representing forelimb muscles in different combinations.

Whether and how various visual sensory areas contribute to the perceived location of visual stimuli remains unknown. To test the role of neurons in extrastriate area V4 in generating alterations in spatial perception during saccadic eye movements (saccades), we examined perisaccadic mislocalization--the perceptual phenomenon in which visual stimuli appearing around the time of a saccade are perceived at a different position than their actual location. We designed and implemented a combined behavioral and electrophysiological framework in non-human primates to directly relate trial-by-trial spatial perception reports during saccades to neuronal firing rates in V4 populations. We measured monkeys perception of stimulus location behaviorally and found perisaccadic mislocalization opposite to the saccade direction. We also quantified population responses by computing the center of mass of firing rate activity across probe locations for V4 neurons with receptive fields close to the saccade target. While perisaccadic neuronal responses showed shifts toward the saccade target, these shifts did not systematically vary with the magnitude of perceptual mislocalization across trials. In conclusion, receptive field shifts based on the perisaccadic firing rate of V4 neurons are not sufficient to account for the magnitude of perceptual mislocalization in each trial, suggesting that more complex neural representation of perisaccadic visual information may be critical for linking extrastriate neural activity to saccade-induced perception.

A major challenge in behavioral neuroscience is the lack of a unified software framework capable of implementing diverse paradigms across species and experimental setups. Researchers currently face a trade-off: they must either spend significant time developing custom, siloed solutions that hinder reproducibility, or incur substantial costs purchasing inflexible, closed systems. Here, we present Neurokraken, an open-source, Python-native platform designed to overcome these limitations. Neurokraken allows writing experiment progression entirely in standard python, while its core architecture automatically sets up a microcontroller for the connected hardware components and enables python side access with millisecond-precision timing and automatic logging. The system prioritizes ease of use and flexibility, enabling advanced series of events and conditions, the usage of python ecosystem code and packages within experiments, and the addition of any arduino-compatible electronic devices for custom experiments. As a result, users can easily create interactive virtual and real environments to engage, monitor, and record subjects. We present Neurokraken's versatility across a wide range of paradigms, for human and non-human primate psychophysics, and complex rodent behavior in both head-fixed and freely moving paradigms. Its modular design allows for rapid hardware reconfiguration, while a fully customizable user interface enables real-time monitoring and interactive experimental control without compromising timing precision. By uniting laboratory-grade precision with an accessible and flexible open-source philosophy, Neurokraken provides a single, powerful solution to design and execute next-generation behavioral experiments. We hope Neurokraken helps accelerate research, improve reproducibility throughout the neuroscience community, and make advanced behavioral experimentation more accessible through its substantial cost-efficiency.

Hypothalamic A11 dopamine neurons provide the only known source of spinal dopamine and critically modulate pain and motor systems. Yet, the electrophysiological properties of A11 neurons were unknown. Here, we characterized A11 dopamine neurons in mice using brain slice immunohistochemistry, and fluorescence-guided whole-cell patch-clamp and cell-attached electrophysiology. A11 dopamine neurons contained the enzymes necessary to synthesize dopamine, projected to the spinal cord, and were small, morphologically simple, and high resistance. Additionally, they received excitatory glutamatergic and inhibitory GABAergic synaptic input. Most A11 dopamine neurons fired action potentials spontaneously in a rhythmic pacemaker manner at [~]5 Hz, while the remainder were quiescent at rest, but fired readily with somatic current injection. Pacemaking A11 dopamine neurons were differentiated from quiescent neurons by a net inward current at subthreshold potentials. Activation of mu-opioid receptors reduced the net inward current at subthreshold potentials via activation of potassium current but also decreased GABAergic synaptic currents onto A11 dopamine neurons. Using cell-attached recording to preserve the natural chloride gradient, we found mu-opioid receptor agonism reduced spontaneous action potential firing of A11 dopamine neurons. The results lay the necessary framework for future studies investigating synaptic and ion channel mechanisms underlying the excitability in A11 dopamine neurons in physiological and pathological conditions.

Neurophysiology datasets are becoming increasingly complex, combining behavioral measurements with high-dimensional neuronal activity recordings coming from optical and/or electrophysiological measurements. The Neurodata Without Borders (NWB) standard has emerged in the community as the format of record. While standardized and widely used preprocessing tools generating NWB files have been developed, extensible frameworks for scientific analysis downstream of the NWB ecosystem are still under-represented. We present CICADA, a Python framework dedicated to analysis of neurophysiological data in the standardized NWB format. The toolbox is built as three hierarchically-organized packages: cicada-nwb (NWB access layer), cicada-analysis (plugin-based analysis engine and tool library), and cicada-gui (PyQt5 desktop application at the head of the pipeline). Beyond this architectural separation, CICADA is built around a central design principle: supporting a continuum from turnkey use to full modularity. Researchers can use the complete GUI-driven cicada-gui workflow without writing code, programmatically use existing analysis plugins from cicada-analysis, contribute to new analysis plugins, reuse utilities from cicada-tools, or build entirely custom pipelines on top of the cicada-nwb access layer alone. The same analysis plugin runs identically in interactive GUI and parameter-configured headless modes, enabling reproducible multi-session, multi-animal group analyses. We illustrate the versatility of CICADA with example analyses of behavioral, calcium imaging (two-photon and widefield) and extracellular electrophysiology datasets from rodent laboratories. CICADA is open source, actively maintained, and designed so that any laboratory can contribute at any level of the stack without modifying the core framework.

The main olfactory epithelium (MOE) is the primary site of olfaction and consists of multiple cell types including olfactory sensory neurons (OSNs), sustentacular cells, and immune cells. Neuroimmune interactions in epithelial tissues are critical in maintaining tissue function, but how OSNs and immune cells interact in the MOE in healthy and diseased states is largely unknown. Cellular responses in the MOE determine how and whether OSNs maintain olfactory function and are repaired or replenished following inflammatory environmental exposures. We hypothesized that acute nasal aeroallergen exposure alters immune cell function in the MOE to elicit a neuroprotective response, thereby preserving OSN function. We developed an environmental aeroallergen exposure consisting of one week of daily intranasal house dust mite extract (HDM) instillations. Spectral flow cytometry indicated only subtle changes in resident immune cells proportions and phenotypes in the MOE. Immunohistochemical evaluation did not reveal extensive changes in immune cell distribution in the sensory epithelium or lamina propria, but instead we observed increases in axonal olfactory marker protein (OMP) expression in the lamina propria, where resident immune cells are most abundant. To evaluate the effects of HDM exposure on OSN function, we performed live ex vivo Ca2+ imaging of MOEs from HDM- and sham-exposed transgenic mice using objective-coupled planar illumination (OCPI) microscopy. OSN responses to multiple odorants revealed increased chemosensory sensitivity and decreased across-trial adaptation in HDM-treated epithelia. These results indicate that short-term nasal aeroallergen exposure minimally alters immune cell phenotypes, and instead induces functional changes in OSN physiology that preserve olfactory function.

Psychoactive and psychotoxic drugs are particularly harmful, if their use coincides with critical developmental windows of brain maturation. Methamphetamine is one such stimulant with developmental exposure increasing seizure susceptibility and long-term neuronal maladaptation in children. Nevertheless, the extent at which infant and adult vulnerability to methamphetamine could differ in time-course and severity remains incompletely understood. Here, we developed a method to monitor methamphetamine-induced hyperactivity in infant mice at high temporal resolution, differentiate it from a biphasic response in adults, and link it to activity changes in cortical areas executing goal-directed (escape) behaviors in infant subjects when using Fos expression as a molecular surrogate. Subsequently, we hypothesized that methamphetamine could alter the expression and cellular distribution of inhibitory neuropeptides, which, when co-released with fast neurotransmitters, could protect circuit plasticity by counteracting methamphetamine-induced hyperexcitability. Methamphetamine differentially altered somatostatin, cholecystokinin, and galanin expression in corticolimbic areas. These data suggest that methamphetamine can evoke age-specific neurocircuit modifications, at least in mice.

The hippocampal CA3 subfield is central to associative learning and memory consolidation. The principal cells of the CA3, pyramidal neurons, execute these functions by generating hypersynchronous bursts that feed forward to the CA1. Extensive recurrent collateral connections within the CA3 neuron population are crucial for the generation of this burst activity. Double C2 domain-containing protein (Doc2) and synaptotagmin 7 (Syt7) are high-affinity calcium sensors implicated in asynchronous synaptic vesicle (SV) release and in the exocytosis of dense-core vesicles (DCVs). Additionally, Doc2 is a sensor for miniature neurotransmission, whereas Syt7 is involved in synaptic facilitation and SV replenishment. Both Doc2 and Syt7 are expressed in the hippocampus, but their potential roles in spontaneous excitatory network activity remain unanswered. Using whole-cell recordings in disinhibited acute hippocampal slices obtained from juvenile Doc2- and Syt7- knockout (KO) mice (P15-21), we report increased CA3 burst generation without changes in spontaneous excitatory postsynaptic current (sEPSC) frequency or amplitude. Moreover, the intrinsic properties of CA3 pyramidal neurons, such as the resting membrane potential, firing rate and input resistance, are unchanged. We propose that this novel burst phenotype in Doc2- and Syt7- KO mice is unrelated to changes in SV release but might be mediated by changes in neuropeptide release from DCVs. Regardless of the underlying mechanisms, this work reveals that both proteins act to regulate network activity. The hippocampal CA3 subfield is central to associative learning and memory consolidation. The principal cells of the CA3, pyramidal neurons, execute these functions by generating hypersynchronous bursts that feed forward to the CA1. Extensive recurrent collateral connections within the CA3 neuron population are crucial for the generation of this burst activity. Double C2 domain-containing protein (Doc2) and synaptotagmin 7 (Syt7) are high-affinity calcium sensors implicated in asynchronous synaptic vesicle (SV) release and in the exocytosis of dense-core vesicles (DCVs). Additionally, Doc2 is a sensor for miniature neurotransmission, whereas Syt7 is involved in synaptic facilitation and SV replenishment. Both Doc2 and Syt7 are expressed in the hippocampus, but their potential roles in spontaneous excitatory network activity remain unanswered. Using whole-cell recordings in disinhibited acute hippocampal slices obtained from juvenile Doc2- and Syt7- knockout (KO) mice (P15-21), we report increased CA3 burst generation without changes in spontaneous excitatory postsynaptic current (sEPSC) frequency or amplitude. Moreover, the intrinsic properties of CA3 pyramidal neurons, such as the resting membrane potential, firing rate and input resistance, are unchanged. We propose that this novel burst phenotype in Doc2- and Syt7- KO mice is unrelated to changes in SV release but might be mediated by changes in neuropeptide release from DCVs. Regardless of the underlying mechanisms, this work reveals that both proteins act to regulate network activity.

Alcohol use disorder (AUD) is marked by substantial heterogeneity in drinking behaviors and health outcomes, underscoring the need for preclinical models that capture interindividual variability. We recently developed open-source capacitive lickometer systems for high-resolution monitoring of mouse fluid intake. Using LIQ PARTI and LIQ HD, we found substantial individual differences in alcohol intake that varied across sex and housing status in C57Bl6/J mice. Here, we conducted a secondary analysis of this continuous access ethanol drinking data to quantify behavioral variability in group and singly housed mice. We introduce a fluid "meal" pattern analysis that integrates drinking across ethanol and water sippers to define discrete drinking episodes. Using this approach, we observed sex- and housing-dependent reorganization of drinking structure across group and single-housed settings, with group-housed male mice exhibiting fewer but faster liquid meals. To further characterize multidimensional drinking patterns, we applied principal component analysis to meal variables and identified a "distributed meal" phenotype defined by increased meal number, reduced meal size, earlier onset of drinking, and higher ethanol preference. Considering factors that influence behaviors in a social environment, we next examined whether social hierarchy was associated with these patterns using a tube test dominance assay. Social rank was unrelated to ethanol and meal measures; however, offensive dominance behavior positively correlated with principal component scores in males. Together, these findings demonstrate that high-resolution, longitudinal analysis of ethanol drinking reveals distinct behavioral phenotypes that are associated with key components of social behaviors, providing a potential framework for understanding heterogeneity in AUD-related drinking. HighlightsO_LILIQ PARTI and HD enable high-resolution analysis of ethanol drinking patterns. C_LIO_LIFluid meal analysis captures sex- and housing-dependent drinking structures. C_LIO_LIBehavioral phenotyping reveals individual differences beyond total ethanol intake. C_LIO_LIPCA identifies a meal phenotype associated with male offensive dominance behavior. C_LI

The aperiodic, 1/f-like component of electrophysiological activity is increasingly recognized as a meaningful feature of neural function, rather than background noise. In parallel, many EEG studies report transient changes in oscillatory power following stimulus onset and interpret these effects as signatures of attention, salience, or cognitive control. However, such conclusions usually rely on baseline normalization procedures that assume aperiodic activity remains stable from pre-to post-stimulus periods. Using high-density EEG recordings from typically developing children, we tested this assumption in two paradigms: an audiovisual simple reaction-time task (n = 36) and a visual oddball task (n = 38). For each task, conventional spectral analyses were compared with analyses that explicitly modeled and removed the aperiodic component in both pre- and post-stimulus windows. Across tasks, stimulus onset was associated with robust increases in aperiodic exponent and offset, indicating systematic changes in the 1/f component of the spectrum. In the audiovisual task, these changes were modality-specific, with central, parieto-occipital, or combined topographies depending on stimulus type. These effects were reduced but remained significant after ERP removal, indicating that they were not fully explained by phase-locked activity. Critically, once aperiodic activity was accounted for, the apparent post-stimulus increase in theta power was largely abolished in both tasks, including the canonical fronto-central theta enhancement to infrequent targets in the oddball paradigm. The conventional method also overestimated the magnitude of beta desynchronization, particularly in the induced (ERP-removed) signal. The apparent gamma desynchronization detected by conventional analyses was reversed after aperiodic correction, revealing either synchronization or no change, indicating that it reflects a spurious consequence of spectral slope steepening rather than a true suppression of gamma oscillatory activity. In contrast, alpha desynchronization remained robust after aperiodic correction and was in fact enhanced, suggesting it reflects genuine oscillatory suppression. Together, these findings indicate that a substantial portion of conventional time-frequency effects, particularly apparent theta synchronization, may reflect changes in aperiodic activity in response to stimulation rather than genuine periodic oscillations, challenging core assumptions of conventional time-frequency analyses. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=123 SRC="FIGDIR/small/732609v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1d25f43org.highwire.dtl.DTLVardef@6c476aorg.highwire.dtl.DTLVardef@c4a02aorg.highwire.dtl.DTLVardef@ef417d_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

Motor planning and control is executed by different motor areas within the neocortex. Despite their distinct functions these areas are built by the same archetypes of neurons as the rest of the cortex, with the pyramidal neurons (PNs) as their principal building blocks. Recent results suggest that the synapses of the PNs are modeled and adapted to their required functions in an area specific manner. PN synapses in a cortical area engaged in higher order functions, the prefrontal cortex (PFC), were found to operate with loose microdomain calcium-influx-to-release coupling and showed short-term facilitation, whereas synapses processing sensory information in a lower order cortical area, the primary somatosensory cortex (S1), featured tight nanodomain coupling and showed short-term depression. In the present study, we asked for the functional coupling configuration of an intermediate processing area. We focused on PN synapses in the premotor cortex M2 and compared their properties to those of PN synapses in the primary motor cortex M1. In both areas we found tight nanodomain coupling and high release probability, but a significant difference in short-term plasticity. Synapses in M1 showed paired-pulse depression similar to S1. In contrast, synapses in M2 exhibited paired-pulse facilitation. Our data suggest that this facilitation results from an accelerated recruitment of synaptic vesicles to the readily releasable pool from an enlarged replenishment pool. Thus, PN synapses in M2 appear to have properties intermediate between those in PFC and M1.

ObjectiveThe Lab Streaming Layer (LSL) protocol, widely adopted for synchronized multimodal biosignal recording in neuroscience research, transmits all data in plaintext, exposing sensitive neural and physiological recordings to interception and tampering and creating regulatory liability for clinical and commercial deployments across most major international jurisdictions. We present Secure LSL, the unified encryption architecture for the protocol: a novel security layer that authenticates devices and encrypts biosignal streams through transparent, drop-in modifications to the core library, requiring no application changes and no recompilation for dynamically linked clients. ApproachWe implement encryption at the liblsl core library level using a shared keypair authorization model with ChaCha20-Poly1305 authenticated encryption. All authorized devices share a common Ed25519 keypair, and public key verification during connection establishment ensures only authorized devices communicate. The architecture enforces network-wide security consensus, requiring all connected devices to operate in either secure or insecure mode, eliminating vulnerable mixed environments, and operates transparently with zero code changes to existing applications. Main ResultsThe architecture preserves application programming interface (API) transparency, so existing applications need no code changes (legacy devices must update to connect to secured outlets). Across five hardware platforms spanning x86 desktop, Apple Silicon laptop, embedded ARM single-board, and Xtensa microcontroller targets, encryption adds sub-millisecond latency in all desktop and embedded ARM configurations, with overhead in the single-digit percent range (approximately 4 to 9%, the lowest values within measurement noise of zero) for typical 64-channel, 1000-Hz configurations. A clean-room ESP32 implementation extends transparent encryption to dual-core microcontrollers with no measurable push-path overhead and approximately 2 kB additional static random-access memory (SRAM) consumption, enabling secured wearable and ambulatory biosensor deployments. SignificanceBy implementing security within the protocol core rather than requiring application-level changes, we transform LSL from a research-only protocol to a security-capable platform for clinical settings, multi-institution collaborations, and commercial products, while preserving its zero-configuration philosophy.

Face-to-face communication requires listeners to attend, integrate, and weigh multiple communicative signals, including auditory speech, mouth movements, and co-speech gestures. The contribution of these signals may depend on the reliability of auditory input and the informativeness of the available signals. We utilized rapid invisible frequency tagging (RIFT) with EEG to examine how participants attend to and integrate these different signals in clear and adverse listening conditions. Participants watched videos of an actress producing clear or noise-vocoded sentences. Auditory speech was amplitude-modulated at 58Hz, while the luminance of the gesture and mouth regions was frequency-tagged at 63Hz and 65Hz. Degraded speech elicited stronger responses at the auditory tagged frequency, suggesting increased attentional gain to the auditory signal when listening was challenging. In contrast, clear speech elicited stronger responses at the gesture tagged frequency and a stronger 2Hz intermodulation response (65-63Hz), reflecting enhanced nonlinear coupling between mouth movements and gestures. Finally, in degraded speech, the informativeness of mouth movement, but not gesture, was associated with intermodulation strength, suggesting that the informativeness of mouth movements plays a greater role in multisensory interaction when listening is challenging. Our findings demonstrate that both signal reliability and informativeness shape multisensory integration during spoken language comprehension.

It has been demonstrated that people who stutter exhibit atypical motor control not only in speech tasks but also movements in the non-speech effector system, such as finger or arm motion. Notably, studies have reported that people who stutter show limited sensorimotor adaptation (i.e., updating subsequent movements in response to sensory errors) in both speech auditory-motor (i.e., updating speech movements in response to altered auditory feedback) and upper limb visuo-motor (i.e., updating arm movements in response to altered visual feedback) tasks. Given that speech auditory-motor adaptation is mostly if not entirely implicit (i.e., participants are unaware of the learning), it is thought that people who stutter have limited implicit adaptation in the speech effector system. It remains unclear however, whether such limited implicit learning also extends to upper limb visuomotor adaptation. Here, we examined implicit visuomotor learning in adults who stutter through the means of arm reaching adaptation to clamped visual feedback which provides a cursor that is fixed in direction (8{degrees} counterclockwise from targets) regardless of the participants actual hand location. All participants gradually adjusted their reach angle towards the clockwise direction, adapting in response to clamped feedback, but adults who stutter showed less adaptation compared to adults who do not stutter. In addition, computational modeling suggests that this implicit adaptation difficulties in stuttering individuals may reflect reduced error sensitivity. Together, our findings suggest that implicit sensorimotor learning difficulties in adults who stutter may generalize across multiple effector systems, providing important implications for understanding sensorimotor mechanisms underlying stuttering. Significance statementBy employing the clamped visual feedback paradigm during arm reaching movements, we demonstrated that adults who stutter showed less implicit visuomotor adaptation compared to adults who do not stutter. This study provides the first evidence that implicit sensorimotor adaptation limitations in developmental stuttering generalize across multiple effector systems. Our findings not only add to a growing body of evidence that stuttering is associated with domain-general sensorimotor difficulties but also point to specific underlying processes that may lead to stuttering.

Segregation of speech into syllables is a key step in neural speech processing. It relies on the alignment of neural activity with the rhythmic structure of speech. Two competing hypotheses explain this neural speech tracking, phase-resetting and evoked responses. While phenomenological modelling of these hypotheses has been successful, we still lack understanding of the underlying cortical circuits. To investigate these mechanisms, we evaluate whether a biophysical next-generation neural mass model can reproduce several features of neural speech tracking, using phenomenological models of the competing hypotheses as algorithmic baselines. We investigate the models dynamics with four tests: recreating in-silico an EEG experiment that identified a correlation between tracking strength and phoneme sharpness, computing the Phase Concentration Metric, testing the effect of varying syllabic rates, and evaluating the Inter Event Phase Coherence across phoneme onsets. While all of the models that we study reproduce the sharpness-tuned rhythmic speech tracking, the evoked model requires a pre-processed acoustic edge impulse stimulus. We demonstrate that the neural mass model is performing thresholded phase-resetting triggered by sharp onsets in the continuous speech envelope. This produces cross-frequency nested oscillations that qualitatively match an experimentally-observed dual-peak signature in the Inter Event Phase Coherence. Our results indicate that the biophysical neural mass model provides a mechanistic bridge between generic oscillatory dynamics in cortical populations and the cognitive computations of speech tracking. Indeed, the non-linear dynamics of the neural mass model offer an explanation for how peak-rate event representations in auditory cortex activity arise in response to continuous acoustic input. Significance StatementSyllable segregation is crucial but challenging as natural speech lacks clear boundaries, yet humans perform this computation effortlessly. Speech aligns neural activity to syllabic rhythms, predicting syllable timing, but the underlying cortical mechanisms remain unknown. Relating this macroscopic behaviour to neurobiology is challenging; however, next-generation neural mass models promise to resolve this. We demonstrate that these models reproduce sharpness-tuned tracking and acoustic edge extraction. Dynamical analyses indicate this occurs through thresholded phase-resetting to phoneme onsets, triggering cross-frequency nested oscillations. Our results both advance biophysical understanding of syllable segregation and validate the models capacity for simulating macroscopic neural activity. These models offer a bridge between the neurobiology of the auditory cortex and speech processing dynamics that phenomenological models cannot provide.

Primate brain function relies on distributed cortical networks. These networks are commonly identified through fMRI functional connectivity, defined as the spatial correlation of hemodynamic fluctuations measured at rest. To assess the contribution of distinct neuronal populations to fMRI functional connectivity, we obtained concurrent fMRI and dense single-unit recordings at rest in the macaque. Then, using standard waveform-based classification of action potential shape, we compared the activity of different neural subtypes to the local and brain-wide patterns of fMRI activity. Putative excitatory neurons were functionally intermixed, with approximately half having positive and half negative correlation with the local fMRI signal. By contrast, all putative inhibitory interneurons were positively correlated, with one subclass exhibiting brain-wide correlation that closely matched conventional seed-based functional connectivity. These findings indicate that, although excitatory projection neurons may underpin long-range network communication interneuron activity most closely matches the fMRI fluctuations at the heart of resting functional connectivity.

Mitochondrial calcium uniporter (MCU) uptakes calcium into mitochondria to maintain intracellular calcium homeostasis, malfunction of which has been implicated in altered neuronal signaling and disease. Its role in synaptic transmission remains understudied, especially in intact neural circuits. We investigated MCU function at the auditory nerve endbulb of Held synapse and postsynaptic bushy neurons in the cochlear nucleus, using age-matched control and MCU knockout (KO) mice of either sex. Whole-cell voltage- and current-clamp recordings were acquired from acute brain slices to examine synaptic transmission and postsynaptic responses. We found that basal synaptic properties at the endbulb of Held were unchanged in MCU KO mice, whereas synaptic transmission during sustained high-rate activity was significantly altered with a shift toward increased asynchronous release. Similarly, MCU deficiency did not change the intrinsic membrane properties of postsynaptic bushy neurons, but significantly reduced the temporal precision of auditory nerve evoked spikes trains at high rates. These results demonstrate that MCU is largely dispensable under low-rate activity, presumably because its activation requires relatively high calcium concentrations. In contrast, during sustained high-rate activity, MCU becomes an important regulator of synaptic function by reducing asynchronous neurotransmitter release under elevated intracellular calcium. Particularly in the auditory system, where neurons routinely fire at high rates, MCU promotes temporal processing and thereby plays a key role in supporting auditory function. It suggests that impaired MCU function under pathological conditions may be an important mechanism underlying central auditory processing deficits, and consequently contributes to hearing loss

Spontaneous synaptic transmission has been established as essential for the maintenance of synaptic weights during action potential-induced transmission. However, spontaneous transmission also changes during synaptic plasticity and has been shown to, in part, mediate changes in synaptic weights. Despite decades of research, a coherent framework for understanding the complex molecular processes that support presynaptic spontaneous transmission during maintenance and plasticity has remained elusive. We show here that presynapses modulate spontaneous transmission frequency during the early time-course of plasticity following entropic force theory. We use live primary hippocampal cultures as a model system and induce plasticity using an established Long-Term Potentiation (LTP) protocol. We then use a combination of electron microscopy, fluorescence microscopy, and computational modeling to show how spontaneous release frequency dynamically changes during early plasticity. We use our entropic force theory to show how the dynamically changing synaptic vesicle pool structure mediates spontaneous release changes. Lastly, we show how these changes are altered in the presence of P301L tau leading to degeneration. The results from this study provide new insights that not only help understand normal synaptic function but also aid in understanding neurodegeneration.