Faculty Bibliography

Chemotherapy results in a frequent yet poorly understood syndrome of long-term neurological deficits. Neural precursor cell dysfunction and white matter dysfunction are thought to contribute to this debilitating syndrome. Here, we demonstrate persistent depletion of oligodendrocyte lineage cells in humans who received chemotherapy. Developing a mouse model of methotrexate chemotherapy-induced neurological dysfunction, we find a similar depletion of white matter OPCs, increased but incomplete OPC differentiation, and a persistent deficit in myelination. OPCs from chemotherapy-naive mice similarly exhibit increased differentiation when transplanted into the microenvironment of previously methotrexate-exposed brains, indicating an underlying microenvironmental perturbation. Methotrexate results in persistent activation of microglia and subsequent astrocyte activation that is dependent on inflammatory microglia. Microglial depletion normalizes oligodendroglial lineage dynamics, myelin microstructure, and cognitive behavior after methotrexate chemotherapy. These findings indicate that methotrexate chemotherapy exposure is associated with persistent tri-glial dysregulation and identify inflammatory microglia as a therapeutic target to abrogate chemotherapy-related cognitive impairment. VIDEO ABSTRACT.

The rules governing cerebellar output are not fully understood, but must involve Purkinje cell (PC) activity, as PCs are the major input to deep cerebellar nuclear (DCN) cells (which form the majority of cerebellar output). Here, the influence of PC complex spikes (CSs) was investigated by simultaneously recording DCN activity with CSs from PC arrays in anesthetized rats. Crosscorrelograms were used to identify PCs that were presynaptic to recorded DCN cells (presynaptic PCs). Such PCs were located within rostrocaudal cortical strips and displayed synchronous CS activity. CS-associated modulation of DCN activity included a short-latency post-CS inhibition and long-latency excitations before and after the CS. The amplitudes of the post-CS responses correlated with the level of synchronization among presynaptic PCs. A temporal precision of ≤10 ms was generally required for CSs to be maximally effective. The results suggest that CS synchrony is a key control parameter of cerebellar output.

Glial cells serve as fundamental regulators of the central nervous system in development, homeostasis, and disease. Discoveries into the function of these cells have fueled excitement in glial research, with enthusiastic researchers addressing fundamental questions about glial biology and producing new scientific tools for the community. Here, we outline the pros and cons of in vivo and in vitro techniques to study astrocytes and microglia with the goal of helping researchers quickly identify the best approach for a given research question in the context of glial biology. It is truly a great time to be a glial biologist.

Neuronal hyperexcitability is one of the major characteristics of Fragile X syndrome (FXS), yet the molecular mechanisms of this critical dysfunction remain poorly understood. Here we report a major role of voltage-independent K⁺ channel dysfunction in hyperexcitability of CA3 pyramidal neurons in Fmr1 KO mice. We observed a reduction of voltage-independent small conductance Ca²⁺-activated K⁺ (SK) currents in both male and female mice leading to decreased AP threshold and reduced medium afterhyperpolarization (mAHP). These SK channel-dependent deficits led to markedly increased AP firing and abnormal input-output signal transmission of CA3 pyramidal neurons. The SK current defect was mediated, at least in part, by loss of FMRP interaction with the SK channels (specifically the SK2 isoform), without changes in the channel expression. Intracellular application of selective SK channel openers or a genetic reintroduction of an N-terminal FMRP fragment lacking the ability to associate with polyribosomes normalized all observed excitability defects in CA3 pyramidal neurons of Fmr1 KO mice. These results suggest that dysfunction of voltage-independent SK channels is the primary cause of CA3 neuronal hyperexcitability in Fmr1 KO mice and support the critical translation-independent role for FMRP as a regulator of neural excitability. Our findings may thus provide a new avenue to ameliorate hippocampal excitability defects in FXS.SIGNIFICANCE STATEMENTDespite two decades of research, no effective treatment is currently available for Fragile X syndrome (FXS). Neuronal hyperexcitability is widely considered as one of the hallmarks of FXS. Excitability research in the FXS field has thus far focused primarily on voltage-gated ion channels, while contributions from voltage-independent channels have been largely overlooked. Here we report that voltage-independent SK channel dysfunction causes hippocampal neuron hyperexcitability in the FXS mouse model. Our results support a major role for translation-independent FMRP function in regulating ion channel activity, and specifically the SK channels, in hyperexcitability defects in FXS. Our findings may thus open a new direction to ameliorate hippocampal excitability defects in FXS.

Neuronal signals in the prefrontal cortex have been reported to predict upcoming decisions. Such activity patterns are often coupled to perceptual cues indicating correct choices or values of different options. How does the prefrontal cortex signal future decisions when no cues are present but when decisions are made based on internal valuations of past experiences with stochastic outcomes? We trained rats to perform a two-arm bandit-task, successfully adjusting choices between certain-small or possible-big rewards with changing long-term advantages. We discovered specialized prefrontal neurons, whose firing during the encounter of no-reward predicted the subsequent choice of animals, even for unlikely or uncertain decisions and several seconds before choice execution. Optogenetic silencing of the prelimbic cortex exclusively timed to encounters of no reward, provoked animals to excessive gambling for large rewards. Firing of prefrontal neurons during outcome evaluation signals subsequent choices during gambling and is essential for dynamically adjusting decisions based on internal valuations.

Sensory perception depends on neocortical computations that contextually adjust sensory signals in different internal and environmental contexts. Neocortical layer 1 (L1) is the main target of cortical and subcortical inputs that provide "top-down" information for context-dependent sensory processing. Although L1 is devoid of excitatory cells, it contains the distal "tuft" dendrites of pyramidal cells (PCs) located in deeper layers. L1 also contains a poorly characterized population of GABAergic interneurons (INs), which regulate the impact that different top-down inputs have on PCs. A poor comprehension of L1 IN subtypes and how they affect PC activity has hampered our understanding of the mechanisms that underlie contextual modulation of sensory processing. We used novel genetic strategies in male and female mice combined with electrophysiological and morphological methods to help resolve differences that were unclear when using only electrophysiological and/or morphological approaches. We discovered that L1 contains four distinct populations of INs, each with a unique molecular profile, morphology, and electrophysiology, including a previously overlooked IN population (named here "canopy cells") representing 40% of L1 INs. In contrast to what is observed in other layers, most L1 neurons appear to be unique to the layer, highlighting the specialized character of the signal processing that takes place in L1. This new understanding of INs in L1, as well as the application of genetic methods based on the markers described here, will enable investigation of the cellular and circuit mechanisms of top-down processing in L1 with unprecedented detail.SIGNIFICANCE STATEMENT Neocortical layer 1 (L1) is the main target of corticocortical and subcortical projections that mediate top-down or context-dependent sensory perception. However, this unique layer is often referred to as "enigmatic" because its neuronal composition has been difficult to determine. Using a combination of genetic, electrophysiological, and morphological approaches that helped to resolve differences that were unclear when using a single approach, we were able to decipher the neuronal composition of L1. We identified markers that distinguish L1 neurons and found that the layer contains four populations of GABAergic interneurons, each with unique molecular profiles, morphologies, and electrophysiological properties. These findings provide a new framework for studying the circuit mechanisms underlying the processing of top-down inputs in neocortical L1.

A genetic pathway that times development works together with the sex-determination pathway to control the timing of sexually dimorphic neural development in C. elegans.

Learning to detect content-independent transformations from data is one of the central problems in biological and artificial intelligence. An example of such problem is unsupervised learning of a visual motion detector from pairs of consecutive video frames. Rao and Ruderman formulated this problem in terms of learning infinitesimal transformation operators (Lie group generators) via minimizing image reconstruction error. Unfortunately, it is difficult to map their model onto a biologically plausible neural network (NN) with local learning rules. Here we propose a biologically plausible model of motion detection. We also adopt the transformation-operator approach but, instead of reconstruction-error minimization, start with a similarity-preserving objective function. An online algorithm that optimizes such an objective function naturally maps onto an NN with biologically plausible learning rules. The trained NN recapitulates major features of the well-studied motion detector in the fly. In particular, it is consistent with the experimental observation that local motion detectors combine information from at least three adjacent pixels, something that contradicts the celebrated Hassenstein-Reichardt model.