Ten-eleven translocation (TET) proteins are crucial epigenetic regulators highly conserved in multicellular organisms. TETs’ enzymatic function in demethylating 5-methyl cytosine in DNA is required for proper development and TETs are frequently mutated in cancer. Recently, Drosophila melanogaster Tet (dTet) was shown to be highly expressed in developing fly brains and discovered to play an important role in brain and muscle development as well as fly behavior. Furthermore, dTet was shown to have different substrate specificity compared with mammals. However, the exact role dTet plays in glial cells and how ectopic TET expression in glial cells contributes to tumorigenesis and glioma is still not clear. Here, we report a novel role for dTet specifically in glial cell organization and number. We show that loss of dTet affects the organization of a specific glia population in the optic lobe, the “optic chiasm” glia. Additionally, we find irregularities in axon patterns in the ventral nerve cord (VNC) both, in...

In the article “MEYE: Web App for Translational and Real-Time Pupillometry,” by Raffaele Mazziotti, Fabio Carrara, Aurelia Viglione, Leonardo Lupori, Luca Lo …

The perirhinal cortex (PER) and postrhinal cortex (POR) in the medial temporal lobe are commonly described as two distinct systems that process nonspatial and spatial information, respectively. Recent findings suggest that the two regions exhibit functional overlap when processing stimulus information, especially when associative responses are required in goal-directed behavior. However, we lack the neural correlates of this. In the current study, we recorded spiking activities for single units of the PER and POR as rats were required to choose a response associated with the identity of a visual object or scene stimulus. We found that similar proportions of cells fired selectively for either scene or object between the two regions. In the PER and POR, response-selective neurons showed higher contrast for different responses than stimulus-selective cells did for stimuli. More cells fired selectively for specific choice response in the POR than in the PER. The differential firing patterns of the PER and POR ...

The opioid crisis has contributed to a growing population of children exposed to opioids during fetal development; however, many of the long-term effects of opioid exposure on development are unknown. We previously demonstrated that opioids have deleterious effects on endocannabinoid plasticity at glutamate synapses in the dorsal striatum of adolescent rodents, but it is unclear whether prenatal opioid exposure produces similar neuroadaptations. Using a mouse model of prenatal methadone exposure (PME), we performed proteomics, phosphoproteomics, and patch-clamp electrophysiology in the dorsolateral striatum (DLS) and dorsomedial striatum (DMS) to examine synaptic functioning in adolescent PME offspring. PME impacted the proteome and phosphoproteome in a region- and sex-dependent manner. Many proteins and phosphorylated proteins associated with glutamate transmission were differentially abundant in PME offspring, which was associated with reduced glutamate release in the DLS and altered the rise time of exc...

Electron microscopy (EM)-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of the lobula, a neuropil putatively dedicated to detecting object-like features, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity-based and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously und...

As you know, the raison d’être of eNeuro is to serve the neuroscience community. The main mission of the journal is to publish excellent and reliable results, while making sure that authors, reviewers, and reviewing editors have a great experience. But eNeuro offers other services to the community, as well: it is a forum open to all if the message you want to convey can help us neuroscientists, teach us something, question us, or make us reflect on important matters. The present state of neuroscience is not only the result of the knowledge that is being accumulated over time but also strongly influenced by …

θ-Scale coordination of prelimbic medial prefrontal cortex (mPFC) local field potentials (LFPs) and its influence via direct or indirect projections to the ventral hippocampus (vHC) and dorsal hippocampus (dHC) during spatial learning remains poorly understood. We hypothesized that θ frequency coordination dynamics within and between the mPFC, dHC, and vHC would be predetermined by the level of connectivity rather than reflecting differing circuit throughput relationships depending on cognitive demands. Moreover, we hypothesized that coherence levels would not change during learning of a complex spatial avoidance task. Adult male rats were bilaterally implanted with EEG electrodes and LFPs recorded in each structure. Contrary to predictions, θ coherence averaged across “Early” or “Late” training sessions in the mPFC-HC, mPFC-mPFC, and HC-HC increased as a function of task learning. Coherence levels were also highest between the indirectly connected mPFC-dHC circuit, particularly during early training. Alth...

Intracranial electroencephalographic (icEEG) recordings provide invaluable insights into neural dynamics in humans because of their unmatched spatiotemporal resolution. Yet, such recordings reflect the combined activity of multiple underlying generators, confounding the ability to resolve spatially distinct neural sources. To empirically quantify the listening zone of icEEG recordings, we computed correlations between signals as a function of distance (full width at half maximum; FWHM) between 8752 recording sites in 71 patients (33 female) implanted with either subdural electrodes (SDEs), stereo-encephalography electrodes (sEEG), or high-density sEEG electrodes. As expected, for both SDEs and sEEGs, higher frequency signals exhibited a sharper fall off relative to lower frequency signals. For broadband high γ (BHG) activity, the mean FWHM of SDEs (6.6 ± 2.5 mm) and sEEGs in gray matter (7.14 ± 1.7 mm) was not significantly different; however, FWHM for low frequencies recorded by sEEGs was 2.45 mm smaller ...

In the article, “Biophysical Modeling of Dopaminergic Denervation Landscapes in the Striatum Reveals New Therapeutic Strategy,” by Mathias L. Heltberg, Hussein N. Awada, Alessandra Lucchetti, Mogens H. Jensen, Jakob K. Dreyer, and Rune N. Rasmussen, which was published online February 14, 2022, Mathias L. Heltberg’s and Hussein N. Awada’s affiliations …

Humans deftly parse statistics from sequences. Some theories posit that humans learn these statistics by forming cognitive maps, or underlying representations of the latent space which links items in the sequence. Here, an item in the sequence is a node, and the probability of transitioning between two items is an edge. Sequences can then be generated from walks through the latent space, with different spaces giving rise to different sequence statistics. Individual or group differences in sequence learning can be modeled by changing the time scale over which estimates of transition probabilities are built, or in other words, by changing the amount of temporal discounting. Latent space models with temporal discounting bear a resemblance to models of navigation through Euclidean spaces. However, few explicit links have been made between predictions from Euclidean spatial navigation and neural activity during human sequence learning. Here, we use a combination of behavioral modeling and intracranial encephalo...