Faculty Bibliography

Sensory systems transform the external world into time-varying spike trains. What features of spiking activity are used to guide behavior? In the mouse olfactory bulb, inhalation of different odors leads to changes in the set of neurons activated, as well as when neurons are activated relative to each other (synchrony) and the onset of inhalation (latency). To explore the relevance of each mode of information transmission, we probed the sensitivity of mice to perturbations across each stimulus dimension (i.e., rate, synchrony, and latency) using holographic two-photon optogenetic stimulation of olfactory bulb neurons with cellular and single-action-potential resolution. We found that mice can detect single action potentials evoked synchronously across <20 olfactory bulb neurons. Further, we discovered that detection depends strongly on the synchrony of activation across neurons, but not the latency relative to inhalation.

Gain-of-function (GOF) variants in K⁺ channels cause severe childhood epilepsies, but there are no mechanisms to explain how increased K⁺ currents lead to network hyperexcitability. Here, we introduce a human Na⁺-activated K⁺ (K_Na) channel variant (KCNT1-Y796H) into mice and, using a multiplatform approach, find motor cortex hyperexcitability and early-onset seizures, phenotypes strikingly similar to those of human patients. Although the variant increases K_Na currents in cortical excitatory and inhibitory neurons, there is an increase in the K_Na current across subthreshold voltages only in inhibitory neurons, particularly in those with non-fast-spiking properties, resulting in inhibitory-neuron-specific impairments in excitability and action potential (AP) generation. We further observe evidence of synaptic rewiring, including increases in homotypic synaptic connectivity, accompanied by network hyperexcitability and hypersynchronicity. These findings support inhibitory-neuron-specific mechanisms in mediating the epileptogenic effects of KCNT1 channel GOF, offering cell-type-specific currents and effects as promising targets for therapeutic intervention.

The thalamus engages in sensation, action, and cognition, but the structure underlying these functions is poorly understood. Thalamic innervation of associative cortex targets several interneuron types, modulating dynamics and influencing plasticity. Is this structure-function relationship distinct from that of sensory thalamocortical systems? Here, we systematically compared function and structure across a sensory and an associative thalamocortical loop in the mouse. Enhancing excitability of mediodorsal thalamus, an associative structure, resulted in prefrontal activity dominated by inhibition. Equivalent enhancement of medial geniculate excitability robustly drove auditory cortical excitation. Structurally, geniculate axons innervated excitatory cortical targets in a preferential manner and with larger synaptic terminals, providing a putative explanation for functional divergence. The two thalamic circuits also had distinct input patterns, with mediodorsal thalamus receiving innervation from a diverse set of cortical areas. Altogether, our findings contribute to the emerging view of functional diversity across thalamic microcircuits and its structural basis.

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individual differences. However, test-retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test-retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test-retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed - a process likely to be limited for most due to the lack of test-retest samples to enable parameter optimization.

Synaptic vesicles (SVs) can be pooled across multiple synapses, prompting questions about their dynamic allocation for neurotransmission and plasticity. We find that the axonal traffic of recycling vesicles is not supported by ubiquitous microtubule-based motility but relies on actin instead. Vesicles freed from synaptic clusters undergo ~1 µm bouts of active transport, initiated by nearby elongation of actin filaments. Long distance translocation arises when successive bouts of active transport were linked by periods of free diffusion. The availability of SVs for active transport can be promptly increased by protein kinase A, a key player in neuromodulation. Vesicle motion is in turn impeded by shutting off axonal actin polymerization, mediated by nitric oxide-cyclic GMP signaling leading to inhibition of RhoA. These findings provide a potential framework for coordinating post-and pre-synaptic strength, using retrograde regulation of axonal actin dynamics to mobilize and recruit presynaptic SV resources.

Photo-switchable lipids are synthetic lipid molecules used in photo-pharmacology to alter membrane lateral pressure and thus control opening and closing of mechanosensitive ion channels. The molecular picture of how photo-switchable lipids interact with membranes or ion channels is poorly understood. To facilitate all-atom simulations that could provide a molecular picture of membranes with photo-switchable lipids, we derived force field parameters for atomistic computations of the azobenzene-based fatty acid FAAzo-4. We implemented a Phyton-based algorithm to make the optimization of atomic partial charges more efficient. Overall, the parameters we derived give good description of the equilibrium structure, torsional properties, and non-bonded interactions for the photo-switchable lipid in its trans and cis intermediate states, and crystal lattice parameters for trans-FAAzo-4. These parameters can be extended to all-atom descriptions of various photo-switchable lipids that have an azobenzene moiety.

Sequential activation of neurons has been observed during various behavioral and cognitive processes, but the underlying circuit mechanisms remain poorly understood. Here, we investigate premotor sequences in HVC (proper name) of the adult zebra finch forebrain that are central to the performance of the temporally precise courtship song. We use high-density silicon probes to measure song-related population activity, and we compare these observations with predictions from a range of network models. Our results support a circuit architecture in which heterogeneous delays between sequentially active neurons shape the spatiotemporal patterns of HVC premotor neuron activity. We gauge the impact of several delay sources, and we find the primary contributor to be slow conduction through axonal collaterals within HVC, which typically adds between 1 and 7.5 ms for each link within the sequence. Thus, local axonal "delay lines" can play an important role in determining the dynamical repertoire of neural circuits.

OBJECTIVE:Deep Learning (DL) image reconstruction has the potential to disrupt the current state of MR imaging by significantly decreasing the time required for MR exams. Our goal was to use DL to accelerate MR imaging in order to allow a 5-minute comprehensive examination of the knee, without compromising image quality or diagnostic accuracy. METHODS:A DL model for image reconstruction using a variational network was optimized. The model was trained using dedicated multi-sequence training, in which a single reconstruction model was trained with data from multiple sequences with different contrast and orientations. Following training, data from 108 patients were retrospectively undersampled in a manner that would correspond with a net 3.49-fold acceleration of fully-sampled data acquisition and 1.88-fold acceleration compared to our standard two-fold accelerated parallel acquisition. An interchangeability study was performed, in which the ability of 6 readers to detect internal derangement of the knee was compared for the clinical and DL-accelerated images. RESULTS:The study demonstrated a high degree of interchangeability between standard and DL-accelerated images. In particular, results showed that interchanging the sequences would result in discordant clinical opinions no more than 4% of the time for any feature evaluated. Moreover, the accelerated sequence was judged by all six readers to have better quality than the clinical sequence. CONCLUSIONS:An optimized DL model allowed for acceleration of knee images which performed interchangeably with standard images for the detection of internal derangement of the knee. Importantly, readers preferred the quality of accelerated images to that of standard clinical images.

Hippocampus-engaged behaviors stimulate neurogenesis in the adult dentate gyrus by largely unknown means. To explore the underlying mechanisms, we used tetrode recording to analyze neuronal activity in the dentate gyrus of freely moving adult mice during hippocampus-engaged contextual exploration. We found that exploration induced an overall sustained increase in inhibitory neuron activity that was concomitant with decreased excitatory neuron activity. A mathematical model based on energy homeostasis in the dentate gyrus showed that enhanced inhibition and decreased excitation resulted in a similar increase in neurogenesis to that observed experimentally. To mechanistically investigate this sustained inhibitory regulation, we performed metabolomic and lipidomic profiling of the hippocampus during exploration. We found sustainably increased signaling of sphingosine-1-phosphate, a bioactive metabolite, during exploration. Furthermore, we found that sphingosine-1-phosphate signaling through its receptor 2 increased interneuron activity and thus mediated exploration-induced neurogenesis. Taken together, our findings point to a behavior-metabolism circuit pathway through which experience regulates adult hippocampal neurogenesis.