Recent advances in tissue processing, labeling, and fluorescence microscopy are providing unprecedented views of the structure of cells and tissues at sub-diffraction resolutions and near single molecule sensitivity, driving discoveries in diverse fields of biology, including neuroscience. Biological tissue is organized over scales of nanometers to centimeters. Harnessing molecular imaging across intact, three-dimensional samples on this scale requires new types of microscopes with larger fields of view and working distance, as well as higher throughput. We present a new expansion-assisted selective plane illumination microscope (ExA-SPIM) with aberration-free 1×1×3 μm optical resolution over a large field of view (10.6×8.0 mm 2 ) and working distance (35 mm) at speeds up to 946 megavoxels/sec. Combined with new tissue clearing and expansion methods, the microscope allows imaging centimeter-scale samples with 250×250×750 nm optical resolution (4× expansion), including entire mouse brains, with high contrast and without sectioning. We illustrate ExA-SPIM by reconstructing individual neurons across the mouse brain, imaging cortico-spinal neurons in the macaque motor cortex, and visualizing axons in human white matter.

Synaptic heterogeneity is a hallmark of nervous systems that enables complex and adaptable communication in neural circuits. To understand circuit function, it is thus critical to determine the factors that contribute to the functional diversity of synapses. We investigated the contributions of voltage-gated calcium channel (VGCC) abundance, spatial organization, and subunit composition to synapse diversity among and between synapses formed by two closely related Drosophila glutamatergic motor neurons with distinct neurotransmitter release probabilities (Pr). Surprisingly, VGCC levels are highly predictive of heterogeneous Pr among individual synapses of either low- or high-Pr inputs, but not between inputs. We find that the same number of VGCCs are more densely organized at high-Pr synapses, consistent with tighter VGCC-synaptic vesicle coupling. We generated endogenously tagged lines to investigate VGCC subunits in vivo and found that the α2δ-3 subunit Straightjacket along with the CAST/ELKS active zone (AZ) protein Bruchpilot, both key regulators of VGCCs, are less abundant at high-Pr inputs, yet positively correlate with Pr among synapses formed by either input. Consistently, both Straightjacket and Bruchpilot levels are dynamically increased across AZs of both inputs when neurotransmitter release is potentiated to maintain stable communication following glutamate receptor inhibition. Together, these findings suggest a model in which VGCC and AZ protein abundance intersects with input-specific spatial and molecular organization to shape the functional diversity of synapses.

To fully understand how the human brain works, knowledge of its structure at high resolution is needed. Presented here is a computationally intensive reconstruction of the ultrastructure of a cubic millimeter of human temporal cortex that was surgically removed to gain access to an underlying epileptic focus. It contains about 57,000 cells, about 230 millimeters of blood vessels, and about 150 million synapses and comprises 1.4 petabytes. Our analysis showed that glia outnumber neurons 2:1, oligodendrocytes were the most common cell, deep layer excitatory neurons could be classified on the basis of dendritic orientation, and among thousands of weak connections to each neuron, there exist rare powerful axonal inputs of up to 50 synapses. Further studies using this resource may bring valuable insights into the mysteries of the human brain.

The fine control of synaptic function requires robust trans-synaptic molecular interactions. However, it remains poorly understood how trans-synaptic bridges change to reflect the functional states of the synapse. Here, we develop optical tools to visualize in firing synapses the molecular behavior of two trans-synaptic proteins, LGI1 and ADAM23, and find that neuronal activity acutely rearranges their abundance at the synaptic cleft. Surprisingly, synaptic LGI1 is primarily not secreted, as described elsewhere, but exo- and endocytosed through its interaction with ADAM23. Activity-driven translocation of LGI1 facilitates the formation of trans-synaptic connections proportionally to the history of activity of the synapse, adjusting excitatory transmission to synaptic firing rates. Accordingly, we find that patient-derived autoantibodies against LGI1 reduce its surface fraction and cause increased glutamate release. Our findings suggest that LGI1 abundance at the synaptic cleft can be acutely remodeled and serves as a critical control point for synaptic function.

Here we report a novel suite of magnetogenetic tools, based on a single anti-ferritin nanobody-TRPV1 receptor fusion protein, which regulated neuronal activity when exposed to magnetic fields. AAV-mediated delivery of a floxed nanobody-TRPV1 into the striatum of adenosine 2a receptor-cre driver mice resulted in motor freezing when placed in an MRI or adjacent to a transcranial magnetic stimulation (TMS) device. Functional imaging and fiber photometry both confirmed activation of the target region in response to the magnetic fields. Expression of the same construct in the striatum of wild-type mice along with a second injection of an AAVretro expressing cre into the globus pallidus led to similar circuit specificity and motor responses. Finally, a mutation was generated to gate chloride and inhibit neuronal activity. Expression of this variant in subthalamic nucleus in PitX2-cre parkinsonian mice resulted in reduced local c-fos expression and motor rotational behavior. These data demonstrate that magnetogenetic constructs can bidirectionally regulate activity of specific neuronal circuits non-invasively in-vivo using clinically available devices.

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. MN activity is coordinated by complex premotor networks that allow individual muscles to contribute to many different behaviors. Here, we use connectomics to analyze the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. In contrast, wing premotor networks lack proportional synaptic connectivity, which may allow wing steering muscles to be recruited with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows to automate a variety of tasks that would otherwise require extensive manual effort, such as state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and computation of other features. These features enable many downstream analyses of neural morphology and connectivity, making these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Neurons have the unique capacity to adapt output in response to changes in their environment. Within seconds, sensory nerve endings can become hypersensitive to stimuli in response to potentially damaging events. The underlying behavioral response is well studied, but several of the key signaling molecules that mediate sensory hypersensitivity remain unknown. We previously discovered that peripheral voltage-gated CaV2.2 channels in nerve endings in skin are essential for the rapid, transient increase in sensitivity to heat, but not to mechanical stimuli, that accompanies intradermal capsaicin. Here we report that the cytokine interleukin-1α (IL-1α), an alarmin, is necessary and sufficient to trigger rapid heat and mechanical hypersensitivity in skin. Of 20 cytokines screened, only IL-1α was consistently detected in hind paw interstitial fluid in response to intradermal capsaicin and, similar to behavioral sensitivity to heat, IL-1α levels were also dependent on peripheral CaV2.2 channel activity. Neutralizing IL-1α in skin significantly reduced capsaicin-induced changes in hind paw sensitivity to radiant heat and mechanical stimulation. Intradermal IL-1α enhances behavioral responses to stimuli and, in culture, IL-1α enhances the responsiveness of Trpv1-expressing sensory neurons. Together, our data suggest that IL-1α is the key cytokine that underlies rapid and reversible neuroinflammatory responses in skin.

A cornerstone of human intelligence is the ability to flexibly adjust our cognition and behavior as our goals change. For instance, achieving some goals requires efficiency, while others require caution. Adapting to these changing goals require corresponding adjustments in cognitive control (e.g., levels of attention, response thresholds). However, adjusting our control to meet new goals comes at a cost: we are better at achieving a goal in isolation than when transitioning between goals. The source of these control adjustment costs remains poorly understood, and the bulk of our understanding of such costs comes from settings in which participants transition between discrete task sets, rather than performance goals. Across four experiments, we show that adjustments in continuous control states incur a performance cost, and that a dynamical systems model can explain the source of these costs. Participants performed a single cognitively demanding task under varying performance goals (e.g., to be fast or to be accurate). We modeled control allocation to include a dynamic process of adjusting from one's current control state to a target state for a given performance goal. By incorporating inertia into this adjustment process, our model accounts for our empirical findings that people under-shoot their target control state more (i.e., exhibit larger adjustment costs) when (a) goals switch rather than remain fixed over a block (Study 1); (b) target control states are more distant from one another (Study 2); (c) less time is given to adjust to the new goal (Study 3); and (d) when anticipating having to switch goals more frequently (Study 4). Our findings characterize the costs of adjusting control to meet changing goals, and show that these costs can emerge directly from cognitive control dynamics. In so doing, they shed new light on the sources of and constraints on flexibility in human goal-directed behavior.

The primary visual cortex (V1) is one of the most studied regions of the brain and is characterized by its specialized and laminated layer 4 in human and non-human primates. However, studies aiming to harmonize the definition of the cortical layers and borders of V1 across rodents and primates are very limited. This article attempts to identify and harmonize the molecular markers and connectional patterns that can consistently link corresponding cortical layers of V1 and borders across mammalian species and ages. V1 in primates has at least two additional and unique layers (L3b2 and L3c) and two sublayers of layer 4 (L4a and L4b) compared to rodent V1. In all species examined, layers 4 and 3b of V1 receive strong inputs from the (dorsal) lateral geniculate nucleus, and V1 is mostly surrounded by the secondary visual cortex except for one location where V1 directly abuts area prostriata. The borders of primate V1 can also be clearly identified at mid-gestational ages using gene markers. In rodents, a novel posteromedial extension of V1 is identified, which expresses V1 marker genes and receives strong inputs from the lateral geniculate nucleus. This V1 extension was labeled as the posterior retrosplenial cortex and medial secondary visual cortex in the literature and brain atlases. Layer 6 of the rodent and primate V1 originates corticothalamic projections to the lateral geniculate, lateral dorsal, and reticular thalamic nuclei and the lateroposterior-pulvinar complex with topographic organization. Finally, the direct geniculo-extrastriate (particularly the strong geniculo-prostriata) projections are probably major contributors to blindsight after V1 lesions. Taken together, compared to rodents, primates, and humans, V1 has at least two unique middle layers, while other layers are comparable across species and display conserved molecular markers and similar connections with the visual thalamus with only subtle differences.