CLP1 founder mutation links tRNA splicing and maturation to cerebellar development and neurodegeneration.

Neurodegenerative diseases can occur so early as to affect neurodevelopment. From a cohort of more than 2,000 consanguineous families with childhood neurological disease, we identified a founder mutation in four independent pedigrees in cleavage and polyadenylation factor I subunit 1 (CLP1). CLP1 is a multifunctional kinase implicated in tRNA, mRNA, and siRNA maturation. Kinase activity of the CLP1 mutant protein was defective, and the tRNA endonuclease complex (TSEN) was destabilized, resulting in impaired pre-tRNA cleavage. Germline clp1 null zebrafish showed cerebellar neurodegeneration that was rescued by wild-type, but not mutant, human CLP1 expression. Patient-derived induced neurons displayed both depletion of mature tRNAs and accumulation of unspliced pre-tRNAs. Transfection of partially processed tRNA fragments into patient cells exacerbated an oxidative stress-induced reduction in cell survival. Our data link tRNA maturation to neuronal development and neurodegeneration through defective CLP1 function in humans.

Involvement of superior colliculus in complex figure detection of mice.

Object detection is an essential function of the visual system. Although the visual cortex plays an important role in object detection, the superior colliculus can support detection when the visual cortex is ablated or silenced. Moreover, it has been shown that superficial layers of mouse SC (sSC) encode visual features of complex objects, and that this code is not inherited from the primary visual cortex. This suggests that mouse sSC may provide a significant contribution to complex object vision. Here, we use optogenetics to show that mouse sSC is involved in figure detection based on differences in figure contrast, orientation, and phase. Additionally, our neural recordings show that in mouse sSC, image elements that belong to a figure elicit stronger activity than those same elements when they are part of the background. The discriminability of this neural code is higher for correct trials than for incorrect trials. Our results provide new insight into the behavioral relevance of the visual processing that takes place in sSC.

Cell-type-specific hypothalamic pathways to brainstem drive context-dependent strategies in response to stressors.

Adaptive behavioral responses to stressors are critical for survival. However, which brain areas orchestrate switching the appropriate stress responses to distinct contexts is an open question. This study aimed to identify the cell-type-specific brain circuitry governing the selection of distinct behavioral strategies in response to stressors. Through novel mouse behavior paradigms, we observed distinct stressor-evoked behaviors in two psycho-spatially distinct contexts characterized by stressors inside or outside the safe zone. The identification of brain regions activated in both conditions revealed the involvement of the dorsomedial hypothalamus (DMH). Further investigation using optogenetics, chemogenetics, and photometry revealed that glutamatergic projections from the DMH to periaqueductal gray (PAG) mediated responses to inside stressors, while GABAergic projections, particularly from tachykinin1-expressing neurons, played a crucial role in coping with outside stressors. These findings elucidate the role of cell-type-specific circuitry from the DMH to the PAG in shaping behavioral strategies in response to stressors. These findings have the potential to advance our understanding of fundamental neurobiological processes and inform the development of novel approaches for managing context-dependent and anxiety-associated pathological conditions such as agoraphobia and claustrophobia.

A parameter-free statistical test for neuronal responsiveness.

Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that (1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations and (2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.

Connectomic Analysis of Brain Networks: Novel Techniques and Future Directions.

Brain networks, localized or brain-wide, exist only at the cellular level, i.e., between specific pre- and post-synaptic neurons, which are connected through functionally diverse synapses located at specific points of their cell membranes. "Connectomics" is the emerging subfield of neuroanatomy explicitly aimed at elucidating the wiring of brain networks with cellular resolution and a quantified accuracy. Such data are indispensable for realistic modeling of brain circuitry and function. A connectomic analysis, therefore, needs to identify and measure the soma, dendrites, axonal path, and branching patterns together with the synapses and gap junctions of the neurons involved in any given brain circuit or network. However, because of the submicron caliber, 3D complexity, and high packing density of most such structures, as well as the fact that axons frequently extend over long distances to make synapses in remote brain regions, creating connectomic maps is technically challenging and requires multi-scale approaches, Such approaches involve the combination of the most sensitive cell labeling and analysis methods available, as well as the development of new ones able to resolve individual cells and synapses with increasing high-throughput. In this review, we provide an overview of recently introduced high-resolution methods, which researchers wanting to enter the field of connectomics may consider. It includes several molecular labeling tools, some of which specifically label synapses, and covers a number of novel imaging tools such as brain clearing protocols and microscopy approaches. Apart from describing the tools, we also provide an assessment of their qualities. The criteria we use assess the qualities that tools need in order to contribute to deciphering the key levels of circuit organization. We conclude with a brief future outlook for neuroanatomic research, computational methods, and network modeling, where we also point out several outstanding issues like structure-function relations and the complexity of neural models.