NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brain regions.

Scalable electronic brain implants with long-term stability and low biological perturbation are crucial technologies for high-quality brain-machine interfaces that can seamlessly access delicate and hard-to-reach regions of the brain. Here, we created "NeuroRoots," a biomimetic multi-channel implant with similar dimensions (7 µm wide and 1.5 µm thick), mechanical compliance, and spatial distribution as axons in the brain. Unlike planar shank implants, these devices consist of a number of individual electrode "roots," each tendril independent from the other. A simple microscale delivery approach based on commercially available apparatus minimally perturbs existing neural architectures during surgery. NeuroRoots enables high density single unit recording from the cerebellum in vitro and in vivo. NeuroRoots also reliably recorded action potentials in various brain regions for at least 7 weeks during behavioral experiments in freely-moving rats, without adjustment of electrode position. This minimally invasive axon-like implant design is an important step toward improving the integration and stability of brain-machine interfacing.

Time for a Reframe: Shifting Focus From Continuous Glucose Monitor Uptake to Sustainable Use to Optimize Outcomes.

Continuous glucose monitors (CGMs) improve glycemic outcomes and quality of life for many people with diabetes. Research and clinical practice efforts have focused on CGM initiation and uptake. There is limited understanding of how to sustain CGM use to realize these benefits and limited consideration for different reasons/goals for CGM use. Therefore, we apply the Information-Motivation-Behavioral Skills (IMB) model as an organizing framework to advance understanding of CGM use as a complex, ongoing self-management behavior. We present a person-centered, dynamic perspective with the central thesis that IMB predictors of optimal CGM use vary based on the CGM use goal of the person with diabetes. This reframe emphasizes the importance of identifying and articulating each person's goal for CGM use to inform education and support.

Systemic pharmacological suppression of neural activity reverses learning impairment in a mouse model of Fragile X syndrome.

The enhancement of associative synaptic plasticity often results in impaired rather than enhanced learning. Previously, we proposed that such learning impairments can result from saturation of the plasticity mechanism (Nguyen-Vu et al., 2017), or, more generally, from a history-dependent change in the threshold for plasticity. This hypothesis was based on experimental results from mice lacking two class I major histocompatibility molecules, MHCI H2-Kb and H2-Db (MHCI KbDb-/-), which have enhanced associative long-term depression at the parallel fiber-Purkinje cell synapses in the cerebellum (PF-Purkinje cell LTD). Here, we extend this work by testing predictions of the threshold metaplasticity hypothesis in a second mouse line with enhanced PF-Purkinje cell LTD, the Fmr1 knockout mouse model of Fragile X syndrome (FXS). Mice lacking Fmr1 gene expression in cerebellar Purkinje cells (L7-Fmr1 KO) were selectively impaired on two oculomotor learning tasks in which PF-Purkinje cell LTD has been implicated, with no impairment on LTD-independent oculomotor learning tasks. Consistent with the threshold metaplasticity hypothesis, behavioral pre-training designed to reverse LTD at the PF-Purkinje cell synapses eliminated the oculomotor learning deficit in the L7-Fmr1 KO mice, as previously reported in MHCI KbDb-/-mice. In addition, diazepam treatment to suppress neural activity and thereby limit the induction of associative LTD during the pre-training period also eliminated the learning deficits in L7-Fmr1 KO mice. These results support the hypothesis that cerebellar LTD-dependent learning is governed by an experience-dependent sliding threshold for plasticity. An increased threshold for LTD in response to elevated neural activity would tend to oppose firing rate stability, but could serve to stabilize synaptic weights and recently acquired memories. The metaplasticity perspective could inform the development of new clinical approaches for addressing learning impairments in autism and other disorders of the nervous system.

Synaptic weight dynamics underlying memory consolidation: implications for learning rules, circuit organization, and circuit function.

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit. Significance Statement: How are memories transformed over time? We propose a simple organizing principle for how long term memories are moved from an initial to a final site of storage. We show that successful transfer occurs when the late site of memory storage is endowed with synaptic plasticity rules that stably accumulate changes in activity occurring at the early site of memory storage. We instantiate this principle in a simple computational model that is representative of brain circuits underlying a variety of behaviors. The model suggests how a neural circuit can store new memories while preserving core features of older ones, and suggests novel roles for core elements of the cerebellar circuit.

Interactions between circuit architecture and plasticity in a closed-loop cerebellar system.

Determining the sites and directions of plasticity underlying changes in neural activity and behavior is critical for understanding mechanisms of learning. Identifying such plasticity from neural recording data can be challenging due to feedback pathways that impede reasoning about cause and effect. We studied interactions between feedback, neural activity, and plasticity in the context of a closed-loop motor learning task for which there is disagreement about the loci and directions of plasticity: vestibulo-ocular reflex learning. We constructed a set of circuit models that differed in the strength of their recurrent feedback, from no feedback to very strong feedback. Despite these differences, each model successfully fit a large set of neural and behavioral data. However, the patterns of plasticity predicted by the models fundamentally differed, with the direction of plasticity at a key site changing from depression to potentiation as feedback strength increased. Guided by our analysis, we suggest how such models can be experimentally disambiguated. Our results address a long-standing debate regarding cerebellum-dependent motor learning, suggesting a reconciliation in which learning-related changes in the strength of synaptic inputs to Purkinje cells are compatible with seemingly oppositely directed changes in Purkinje cell spiking activity. More broadly, these results demonstrate how changes in neural activity over learning can appear to contradict the sign of the underlying plasticity when either internal feedback or feedback through the environment is present.

Decline in case rates of youth onset type 2 diabetes in year three of the COVID-19 pandemic.

OBJECTIVES: To determine changes in case rates of youth onset type 2 diabetes in the three years following the COVID-19 pandemic. METHODS: A single-center, retrospective medical record review was conducted for patients newly diagnosed with T2D between 3/1/18 and 2/28/23 at a pediatric tertiary care center. The number of patients referred to CHLA with a T2D diagnosis date between 3/1/2020 and 2/28/2023 was compared to historical rates between 3/1/2018 and 2/29/2020. χ2 or Fisher's exact test was used to compare categorical variables between each year and 2019. RESULTS: Compared to prepandemic baseline (3/1/19-2/29/20, 11.8±3.7 cases/month), there was a significant increase in new T2D monthly case rates in pandemic year 1 (3/1/20-2/28/21, 20.1±6.0 cases/month, 171 %, p=0.005) and pandemic year 2 (3/1/21-2/28/22, 25.9±8.9 cases/month, 221 %, p=0.002). Case rates declined in pandemic year 3 to 14.5±4.1 cases/month (3/1/22-2/28/23, p=0.43). Compared to prepandemic year 1, the frequency of DKA at diagnosis was higher in pandemic year 1 (13.3 vs. 5.0 %, p=0.009). The DKA rate in pandemic years 2 (6.8 %) and 3 (3.4 %) were comparable to prepandemic year 1 (p=0.53 and 0.58, respectively). CONCLUSIONS: Youth onset type 2 diabetes cases and DKA rates in year 3 of the pandemic have returned to prepandemic level.

Young Adults with Type 1 Diabetes.

Young adults experience multiple developmental transitions across social, educational, vocational, residential, and financial life domains. These transitions are potential competing priorities to managing a chronic condition such as type 1 diabetes and can contribute to poor psychosocial and medical outcomes. In this narrative review, we describe population outcomes of young adult populations and the unique considerations associated with managing type 1 diabetes in young adulthood. We provide an overview of the current evidence-based strategies to improve care for young adults with type 1 diabetes and recommendations for future directions in the field.