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Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer’s Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aβ pathology. PV-IN CIBOP in early stages of Aβ pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis. Native state proteomics of PV interneurons revealed unique molecular features of high translational and metabolic activity, and enrichment of Alzheimer’s risk genes. Early amyloid pathology exerted unique effects on mitochondria, mTOR signaling and neurotransmission in PV neurons.

Preventative treatment for Alzheimer’s Disease (AD) is dire, yet mechanisms underlying early regional vulnerability remain unknown. In AD, one of the earliest pathophysiological correlates to cognitive decline is hyperexcitability, which is observed first in the entorhinal cortex. Why hyperexcitability preferentially emerges in specific regions in AD is unclear. Using regional, cell-type-specific proteomics and electrophysiology in wild-type mice, we uncovered a unique susceptibility of the entorhinal cortex to human amyloid precursor protein (hAPP). Entorhinal hyperexcitability resulted from selective vulnerability of parvalbumin (PV) interneurons, with respect to surrounding excitatory neurons. This effect was partially replicated with an APP chimera containing a humanized amyloid-beta sequence. EC hyperexcitability could be ameliorated by co-expression of human Tau with hAPP at the expense of increased pathological tau species, or by enhancing PV interneuron excitability in vivo. This study suggests early interventions targeting inhibitory neurons may protect vulnerable regions from the effects of APP/amyloid and tau pathology. In this study using an adult-onset mouse model of Alzheimer’s pathology, we uncovered a neuron-type-specific mechanism responsible for region-specific circuit dysfunction. Short-term expression of human amyloid precursor protein (hAPP) led to hyperexcitability in the entorhinal cortex, but not in isocortex, due to a distinct vulnerability of PV interneurons in the entorhinal region.

Understanding the activity of the mammalian brain requires an integrative knowledge of circuits at distinct scales, ranging from ion channel gating to circuit connectomics. Computational models are regularly employed to understand how multiple parameters contribute synergistically to circuit behavior. However, traditional models of anatomically and biophysically realistic neurons are computationally demanding, especially when scaled to model local circuits. To overcome this limitation, we trained several artificial neural network (ANN) architectures to model the activity of realistic multicompartmental cortical neurons. We identified an ANN architecture that accurately predicted subthreshold activity and action potential firing. The ANN could correctly generalize to previously unobserved synaptic input, including in models containing nonlinear dendritic properties. When scaled, processing times were orders of magnitude faster compared with traditional approaches, allowing for rapid parameter-space mapping in a circuit model of Rett syndrome. Thus, we present a novel ANN approach allowing for rapid, detailed network experiments using inexpensive and commonly available computational resources.

In Alzheimer’s disease (AD), a multitude of genetic risk factors and early biomarkers are known. Nevertheless, the causal factors responsible for initiating cognitive decline in AD remain controversial. Toxic plaques and tangles correlate with progressive neuropathology, yet disruptions in circuit activity emerge before their deposition in AD models and patients. Parvalbumin (PV) interneurons are potential candidates for dysregulating cortical excitability as they display altered action potential (AP) firing before neighboring excitatory neurons in prodromal AD. Here, we report a novel mechanism responsible for PV hypoexcitability in young adult familial AD mice. We found that biophysical modulation of K v 3 channels, but not changes in their mRNA or protein expression, were responsible for dampened excitability in young 5xFAD mice. These K + conductances could efficiently regulate near-threshold AP firing, resulting in gamma-frequency-specific network hyperexcitability. Thus, biophysical ion channel alterations alone may reshape cortical network activity prior to changes in their expression levels. Our findings demonstrate an opportunity to design a novel class of targeted therapies to ameliorate cortical circuit hyperexcitability in early AD.

The signals in cerebellar Purkinje cells sufficient to instruct motor learning have not been systematically determined. Therefore, we applied optogenetics in mice to autonomously excite Purkinje cells and measured the effect of this activity on plasticity induction and adaptive behavior. Ex vivo, excitation of channelrhodopsin-2-expressing Purkinje cells elicits dendritic Ca 2+ transients with high-intensity stimuli initiating dendritic spiking that additionally contributes to the Ca 2+ response. Channelrhodopsin-2-evoked Ca 2+ transients potentiate co-active parallel fiber synapses; depression occurs when Ca 2+ responses were enhanced by dendritic spiking. In vivo, optogenetic Purkinje cell activation drives an adaptive decrease in vestibulo-ocular reflex gain when vestibular stimuli are paired with relatively small-magnitude Purkinje cell Ca 2+ responses. In contrast, pairing with large-magnitude Ca 2+ responses increases vestibulo-ocular reflex gain. Optogenetically induced plasticity and motor adaptation are dependent on endocannabinoid signaling, indicating engagement of this pathway downstream of Purkinje cell Ca 2+ elevation. Our results establish a causal relationship among Purkinje cell Ca 2+ signal size, opposite-polarity plasticity induction, and bidirectional motor learning. Plastic reweighting of parallel fiber synaptic strength is a mechanism for the acquisition of cerebellum-dependent motor learning. Here, the authors found that optogenetic activation of PCs generates dendritic Ca2+ signals that induce plasticity in vitro and instruct learned changes to coincident eye movements in vivo.

Significant technical challenges exist when measuring synaptic connections between neurons in living brain tissue. The patch clamping technique, when used to probe for synaptic connections, is manually laborious and time-consuming. To improve its efficiency, we pursued another approach: instead of retracting all patch clamping electrodes after each recording attempt, we cleaned just one of them and reused it to obtain another recording while maintaining the others. With one new patch clamp recording attempt, many new connections can be probed. By placing one pipette in front of the others in this way, one can ‘walk’ across the mouse brain slice, termed ‘patch-walking.’ We performed 136 patch clamp attempts for two pipettes, achieving 71 successful whole cell recordings (52.2%). Of these, we probed 29 pairs (i.e. 58 bidirectional probed connections) averaging 91 μm intersomatic distance, finding three connections. Patch-walking yields 80–92% more probed connections, for experiments with 10–100 cells than the traditional synaptic connection searching method.

A common electrophysiology technique used in neuroscience is patch clamp: a method in which a glass pipette electrode facilitates single cell electrical recordings from neurons. Typically, patch clamp is done manually in which an electrophysiologist views a brain slice under a microscope, visually selects a neuron to patch, and moves the pipette into close proximity to the cell to break through and seal its membrane. While recent advances in the field of patch clamping have enabled partial automation, the task of detecting a healthy neuronal soma in acute brain tissue slices is still a critical step that is commonly done manually, often presenting challenges for novices in electrophysiology. To overcome this obstacle and progress towards full automation of patch clamp, we combined the differential interference microscopy optical technique with an object detection-based convolutional neural network (CNN) to detect healthy neurons in acute slice. Utilizing the YOLOv3 convolutional neural network architecture, we achieved a 98% reduction in training times to 18 min, compared to previously published attempts. We also compared networks trained on unaltered and enhanced images, achieving up to 77% and 72% mean average precision, respectively. This novel, deep learning-based method accomplishes automated neuronal detection in brain slice at 18 frames per second with a small data set of 1138 annotated neurons, rapid training time, and high precision. Lastly, we verified the health of the identified neurons with a patch clamp experiment where the average access resistance was 29.25 M Ω (n = 9). The addition of this technology during live-cell imaging for patch clamp experiments can not only improve manual patch clamping by reducing the neuroscience expertise required to select healthy cells, but also help achieve full automation of patch clamping by nominating cells without human assistance.

The cerebellar system helps modulate and fine-tune motor action. Purkinje cells (PCs) provide the sole output of the cerebellar cortex, therefore, any cerebellar involvement in motor activity must be driven by changes in PC firing rates. Several different cell types influence PC activity including excitatory input from parallel fibers and inhibition from molecular layer interneurons (MLIs). Similar to PCs, MLI activity is driven by parallel fibers, therefore, MLIs provide feed-forward inhibition onto PCs. To aid in the experimental assessment of how molecular layer inhibition contributes to cerebellar function and motor behavior, we characterized a new knock-in mouse line with Cre recombinase expression under control of endogenous c-kit transcriptional machinery. Using these engineered c-Kit mice, we were able to obtain high levels of conditional MLI transduction in adult mice using Cre-dependent viral vectors without any PC or granule cell labeling. We then used the mouse line to target MLIs for activity perturbation in vitro using opto- and chemogenetics.

Motor learning involves neural circuit modifications in the cerebellar cortex, likely through re-weighting of parallel fiber inputs onto Purkinje cells (PCs). Climbing fibers instruct these synaptic modifications when they excite PCs in conjunction with parallel fiber activity, a pairing that enhances climbing fiber-evoked Ca2+ signaling in PC dendrites. In vivo, climbing fibers spike continuously, including during movements when parallel fibers are simultaneously conveying sensorimotor information to PCs. Whether parallel fiber activity enhances climbing fiber Ca2+ signaling during motor behaviors is unknown. In mice, we found that inhibitory molecular layer interneurons (MLIs), activated by parallel fibers during practiced movements, suppressed parallel fiber enhancement of climbing fiber Ca2+ signaling in PCs. Similar results were obtained in acute slices for brief parallel fiber stimuli. Interestingly, more prolonged parallel fiber excitation revealed latent supralinear Ca2+ signaling. Therefore, the balance of parallel fiber and MLI input onto PCs regulates concomitant climbing fiber Ca2+ signaling.

Synapse loss is associated with cognitive decline in Alzheimer’s disease, and owing to their plastic nature, synapses are an ideal target for therapeutic intervention. Oligomeric amyloid beta around amyloid plaques is known to contribute to synapse loss in mouse models and is associated with synapse loss in human Alzheimer’s disease brain tissue, but the mechanisms leading from Aβ to synapse loss remain unclear. Recent data suggest that the fast-activating and -inactivating voltage-gated potassium channel subtype 3.4 (Kv3.4) may play a role in Aβ-mediated neurotoxicity. Here, we tested whether this channel could also be involved in Aβ synaptotoxicity. Using adeno-associated virus and clustered regularly interspaced short palindromic repeats technology, we reduced Kv3.4 expression in neurons of the somatosensory cortex of APP/PS1 mice. These mice express human familial Alzheimer’s disease-associated mutations in amyloid precursor protein and presenilin-1 and develop amyloid plaques and plaque-associated synapse loss similar to that observed in Alzheimer’s disease brain. We observe that reducing Kv3.4 levels ameliorates dendritic spine loss and changes spine morphology compared to control virus. In support of translational relevance, Kv3.4 protein was observed in human Alzheimer’s disease and control brain and is associated with synapses in human induced pluripotent stem cell–derived cortical neurons. We also noted morphological changes in induced pluripotent stem cell neurones challenged with human Alzheimer’s disease-derived brain homogenate containing Aβ but, in this in vitro model, total mRNA levels of Kv3.4 were found to be reduced, perhaps as an early compensatory mechanism for Aβ-induced damage. Overall, our results suggest that approaches to reduce Kv3.4 expression and/or function in the Alzheimer’s disease brain could be protective against Aβ-induced synaptic alterations.