Faculty Bibliography

The causal connectivity of a network is often inferred to understand network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the network's underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity. Here, we focus on nonlinear networks with pulse signals as measured output, e.g., neural networks with spike output, and address the above issues based on four commonly utilized causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We theoretically show how these causality measures are related to one another when applied to pulse signals. Taking a simulated Hodgkin-Huxley network and a real mouse brain network as two illustrative examples, we further verify the quantitative relations among the four causality measures and demonstrate that the causal connectivity inferred by any of the four well coincides with the underlying network structural connectivity, therefore illustrating a direct link between the causal and structural connectivity. We stress that the structural connectivity of pulse-output networks can be reconstructed pairwise without conditioning on the global information of all other nodes in a network, thus circumventing the curse of dimensionality. Our framework provides a practical and effective approach for pulse-output network reconstruction.

Over the past few decades, daily exposure to radiofrequency (RF) fields has been increasing due to the rapid development of wireless and medical imaging technologies. Under extreme circumstances, exposure to very strong RF energy can lead to heating of body tissue, even resulting in tissue injury. The presence of implanted devices, moreover, can amplify RF effects on surrounding tissue. Therefore, it is important to understand the interactions of RF fields with tissue in the presence of implants, in order to establish appropriate wireless safety protocols, and also to extend the benefits of medical imaging to increasing numbers of people with implanted medical devices. This study explored the neurological effects of RF exposure in rodents implanted with neuronal recording electrodes. We exposed freely moving and anesthetized rats and mice to 950 MHz RF energy while monitoring their brain activity, temperature, and behavior. We found that RF exposure could induce fast onset firing of single neurons without heat injury. In addition, brain implants enhanced the effect of RF stimulation resulting in reversible behavioral changes. Using an optical temperature measurement system, we found greater than tenfold increase in brain temperature in the vicinity of the implant. On the one hand, our results underline the importance of careful safety assessment for brain-implanted devices, but on the other hand, we also show that metal implants may be used for neurostimulation if brain temperature can be kept within safe limits.

Norepinephrine (NE) is an essential biogenic monoamine neurotransmitter. The first-generation NE sensor makes in vivo, real-time, cell-type-specific and region-specific NE detection possible, but its low NE sensitivity limits its utility. Here, we developed the second-generation GPCR-activation-based NE sensors (GRAB_NE2m and GRAB_NE2h) with a superior response and high sensitivity and selectivity to NE both in vitro and in vivo. Notably, these sensors can detect NE release triggered by either optogenetic or behavioral stimuli in freely moving mice, producing robust signals in the locus coeruleus and hypothalamus. With the development of a novel transgenic mouse line, we recorded both NE release and calcium dynamics with dual-color fiber photometry throughout the sleep-wake cycle; moreover, dual-color mesoscopic imaging revealed cell-type-specific spatiotemporal dynamics of NE and calcium during sensory processing and locomotion. Thus, these new GRAB_NE sensors are valuable tools for monitoring the precise spatiotemporal release of NE in vivo, providing new insights into the physiological and pathophysiological roles of NE.

OBJECTIVES/OBJECTIVE:Despite performing well in standard clinical assessments of speech perception, many cochlear implant (CI) users report experiencing significant difficulties when listening in real-world environments. We hypothesize that this disconnect may be related, in part, to the limited ecological validity of tests that are currently used clinically and in research laboratories. The challenges that arise from degraded auditory information provided by a CI, combined with the listener's finite cognitive resources, may lead to difficulties when processing speech material that is more demanding than the single words or single sentences that are used in clinical tests. DESIGN/METHODS:Here, we investigate whether speech identification performance and processing effort (indexed by pupil dilation measures) are affected when CI users or normal-hearing control subjects are asked to repeat two sentences presented sequentially instead of just one sentence. RESULTS:Response accuracy was minimally affected in normal-hearing listeners, but CI users showed a wide range of outcomes, from no change to decrements of up to 45 percentage points. The amount of decrement was not predictable from the CI users' performance in standard clinical tests. Pupillometry measures tracked closely with task difficulty in both the CI group and the normal-hearing group, even though the latter had speech perception scores near ceiling levels for all conditions. CONCLUSIONS:Speech identification performance is significantly degraded in many (but not all) CI users in response to input that is only slightly more challenging than standard clinical tests; specifically, when two sentences are presented sequentially before requesting a response, instead of presenting just a single sentence at a time. This potential "2-sentence problem" represents one of the simplest possible scenarios that go beyond presentation of the single words or sentences used in most clinical tests of speech perception, and it raises the possibility that even good performers in single-sentence tests may be seriously impaired by other ecologically relevant manipulations. The present findings also raise the possibility that a clinical version of a 2-sentence test may provide actionable information for counseling and rehabilitating CI users, and for people who interact with them closely.

BACKGROUND:Myocardial infarction and heart failure are major cardiovascular diseases that affect millions of people in the US with the morbidity and mortality being highest among patients who develop cardiogenic shock. Early recognition of cardiogenic shock allows prompt implementation of treatment measures. Our objective is to develop a new dynamic risk score, called CShock, to improve early detection of cardiogenic shock in cardiac intensive care unit (ICU). METHODS:We developed and externally validated a deep learning-based risk stratification tool, called CShock, for patients admitted into the cardiac ICU with acute decompensated heart failure and/or myocardial infarction to predict onset of cardiogenic shock. We prepared a cardiac ICU dataset using MIMIC-III database by annotating with physician adjudicated outcomes. This dataset that consisted of 1500 patients with 204 having cardiogenic/mixed shock was then used to train CShock. The features used to train the model for CShock included patient demographics, cardiac ICU admission diagnoses, routinely measured laboratory values and vital signs, and relevant features manually extracted from echocardiogram and left heart catheterization reports. We externally validated the risk model on the New York University (NYU) Langone Health cardiac ICU database that was also annotated with physician adjudicated outcomes. The external validation cohort consisted of 131 patients with 25 patients experiencing cardiogenic/mixed shock. RESULTS:CShock achieved an area under the receiver operator characteristic curve (AUROC) of 0.821 (95% CI 0.792-0.850). CShock was externally validated in the more contemporary NYU cohort and achieved an AUROC of 0.800 (95% CI 0.717-0.884), demonstrating its generalizability in other cardiac ICUs. Having an elevated heart rate is most predictive of cardiogenic shock development based on Shapley values. The other top ten predictors are having an admission diagnosis of myocardial infarction with ST-segment elevation, having an admission diagnosis of acute decompensated heart failure, Braden Scale, Glasgow Coma Scale, Blood urea nitrogen, Systolic blood pressure, Serum chloride, Serum sodium, and Arterial blood pH. CONCLUSIONS:The novel CShock score has the potential to provide automated detection and early warning for cardiogenic shock and improve the outcomes for the millions of patients who suffer from myocardial infarction and heart failure.

Homeostatic regulation of synapses is vital for nervous system function and key to understanding a range of neurological conditions. Synaptic homeostasis is proposed to operate over hours to counteract the destabilizing influence of long-term potentiation (LTP) and long-term depression (LTD). The prevailing view holds that synaptic scaling is a slow first-order process that regulates postsynaptic glutamate receptors and fundamentally differs from LTP or LTD. Surprisingly, we find that the dynamics of scaling induced by neuronal inactivity are not exponential or monotonic, and the mechanism requires calcineurin and CaMKII, molecules dominant in LTD and LTP. Our quantitative model of these enzymes reconstructs the unexpected dynamics of homeostatic scaling and reveals how synapses can efficiently safeguard future capacity for synaptic plasticity. This mechanism of synaptic adaptation supports a broader set of homeostatic changes, including action potential autoregulation, and invites further inquiry into how such a mechanism varies in health and disease.

Glial cells in the peripheral nervous system (PNS), which arise from the neural crest, include axon-associated Schwann cells (SCs) in nerves, synapse-associated SCs at the neuromuscular junction, enteric glia, perikaryon-associated satellite cells in ganglia, and boundary cap cells at the border between the central nervous system (CNS) and the PNS. Here, we focus on axon-associated SCs. These SCs progress through a series of formative stages, which culminate in the generation of myelinating SCs that wrap large-caliber axons and of nonmyelinating (Remak) SCs that enclose multiple, small-caliber axons. In this work, we describe SC development, extrinsic signals from the axon and extracellular matrix (ECM) and the intracellular signaling pathways they activate that regulate SC development, and the morphogenesis and organization of myelinating SCs and the myelin sheath. We review the impact of SCs on the biology and integrity of axons and their emerging role in regulating peripheral nerve architecture. Finally, we explain how transcription and epigenetic factors control and fine-tune SC development and myelination.

A postulated role of subcortical neuromodulators is to control brain states. Mechanisms by which different neuromodulators compete or cooperate at various temporal scales remain an open question. We investigated the interaction of acetylcholine (ACh) and oxytocin (OXT) at slow and fast timescales during various brain states. Although these neuromodulators fluctuated in parallel during NREM packets, transitions from NREM to REM were characterized by a surge of ACh but a continued decrease of OXT. OXT signaling lagged behind ACh. High ACh was correlated with population synchrony and gamma oscillations during active waking, whereas minimum ACh predicts sharp-wave ripples (SPW-Rs). Optogenetic control of ACh and OXT neurons confirmed the active role of these neuromodulators in the observed correlations. Synchronous hippocampal activity consistently reduced OXT activity, whereas inactivation of the lateral septum-hypothalamus path attenuated this effect. Our findings demonstrate how cooperative actions of these neuromodulators allow target circuits to perform specific functions.

Early-life stress has been linked to multiple neurodevelopmental and neuropsychiatric deficits. Our previous studies have linked maternal presence/absence from the nest in developing rat pups to changes in prefrontal cortex (PFC) activity. Furthermore, we have shown that these changes are modulated by serotonergic signaling. Here we test whether changes in PFC activity during early life affect the developing cortex leading to behavioral alterations in the adult. We show that inhibiting the PFC of mouse pups leads to cognitive deficits in the adult comparable to those seen following maternal separation. Moreover, we show that activating the PFC during maternal separation can prevent these behavioral deficits. To test how maternal separation affects the transcriptional profile of the PFC we performed single-nucleus RNA-sequencing. Maternal separation led to differential gene expression almost exclusively in inhibitory neurons. Among others, we found changes in GABAergic and serotonergic pathways in these interneurons. Interestingly, both maternal separation and early-life PFC inhibition led to changes in physiological responses in prefrontal activity to GABAergic and serotonergic antagonists that were similar to the responses of more immature brains. Prefrontal activation during maternal separation prevented these changes. These data point to a crucial role of PFC activity during early life in behavioral expression in adulthood.

Axons undergo striking changes in their content and distribution of cell adhesion molecules (CAMs) and ion channels during myelination that underlies the switch from continuous to saltatory conduction. These changes include the removal of a large cohort of uniformly distributed CAMs that mediate initial axon-Schwann cell interactions and their replacement by a subset of CAMs that mediate domain-specific interactions of myelinated fibers. Here, using rodent models, we examine the mechanisms and significance of this removal of axonal CAMs. We show that Schwann cells just prior to myelination locally activate clathrin-mediated endocytosis (CME) in axons, thereby driving clearance of a broad array of axonal CAMs. CAMs engineered to resist endocytosis are persistently expressed along the axon and delay both PNS and CNS myelination. Thus, glia non-autonomously activate CME in axons to downregulate axonal CAMs and presumptively axo-glial adhesion. This promotes the transition from ensheathment to myelination while simultaneously sculpting the formation of axonal domains.