Sparse labeling techniques are essential for morphological analysis of the central nervous system. Various sophisticated strategies have been developed, but conventional methods, such as Golgi–Cox staining and biocytin injection, remain widely used. Recent advances in adeno-associated virus (AAV) technology have enabled sparse neuronal labeling in rodents, either through postnatal AAV injection or by coinjecting a dilute Cre recombinase-expressing driver with a Cre-dependent amplifier. However, postnatal AAV injection requires prior preparation, and Cre-dependent systems are incompatible with Cre-expressing or floxed genetic backgrounds. Here, we present a Cre-orthogonal AAV–based sparse labeling method that utilizes Supernova technology in male and female mice. We employed Flpe recombinase to achieve Cre-independent labeling. A retro-orbital injection of PHP.eB AAVs failed to label neurons, whereas local injection enabled the bright and sparse labeling of multiple neuronal types, including cerebellar neur...

A central approach in neuroscience is to analyze neural representations as a means to understand a system's function, through the use of methods like principal component analysis, regression, and representational similarity analysis. These analyses often rest on a tacit “linking assumption”: that the features explaining the most variance in neural activity are the most important for the system's computation. Here, we challenge this assumption. We review recent work in machine learning demonstrating “representation biases”—the fact that learned representations can be biased toward certain features over others. For example, learned representations heavily overrepresent simple (linear) features while representing complex (nonlinear) features much more weakly, even when both are equally critical for the system's computations. We review the origins of these biases in learning dynamics and patterns of computation. We then discuss their consequences for neuroscience. We show that if a subset of features dominates...

Presbycusis, a prevalent neurodegenerative disorder, is characterized by declining speech recognition and has been associated with cognitive impairments across multiple domains. However, the underlying neurobiological mechanisms between presbycusis and cognitive impairments remain unclear. We assessed pure-tone audiometry thresholds (PTA), speech recognition thresholds (SRT), and cognitive abilities in individuals with presbycusis (24 males and 31 females) and healthy controls (23 males and 32 females). Using magnetic resonance imaging, we calculated the amplitude of low-frequency fluctuations (ALFF) to characterize function and gray matter volume (GMV) to characterize structure. Based on ALFF and GMV, we calculated functional-structural ratio (FSR) to measure the functional-structural coupling. Significant correlations between GMV atrophy and ALFF changed in the putamen, fusiform gyrus, precuneus, and medial superior frontal gyrus in presbycusis group, and these changes were significantly associated with ...

Rapid advancements in artificial intelligence (AI) have enabled text-to-speech (TTS) systems to produce voices increasingly indistinguishable from humans, posing significant societal risks, particularly through potential misuse in fraud and deception. To address this concern, this study combined behavioral assessments and neural measures using electroencephalography (EEG) to examine whether short-term perceptual training enhances people's ability to distinguish AI-generated from human speech. Thirty participants (of either sex) listened to sentences produced by human speakers and corresponding AI-generated clones, judging each sentence as either human or AI-generated before and after a brief (∼12 min) training session, during which voices were explicitly labeled as “human” or “AI.” Behaviorally, participants showed consistently poor discrimination before and after training, with only minimal improvement. However, neural analyses revealed substantial training-induced changes. Specifically, temporal response...

Rodent hippocampal power spectra comprise periodic and aperiodic components. The periodic components (brain rhythms) contain information about the behavioral or cognitive state of the animal. The aperiodic components are rarely studied, and their functionality is not well understood, though they have shown to be correlated with animal's age or the excitation–inhibition ratio of the brain region. To study these components in the mouse hippocampus, we modified the existing open-source FOOOF toolbox, which was originally optimized for EEG data. First, using simulated data, we show that our modifications decrease the error in assessment of the low frequency periodic components from 3 to 0.1%. Second, using tetrode electrophysiological signals from adult males, we compare the aperiodic activity within mice hippocampal subregions, CA1 and dentate gyrus (DG). Our optimization of FOOOF improved the aperiodic assessment errors by ∼50% and were critical in making the first assessment of the aperiodic components in t...

Charcot–Marie–Tooth disease (CMT) is an inherited peripheral neuropathy characterized by sensory dysfunction and muscle weakness, manifesting in the most distal limbs first and progressing more proximal. Over a hundred genes are currently linked to CMT with enrichment for activities in myelination, axon transport, and protein synthesis. Mutations in tRNA synthetases cause dominantly inherited forms of CMT, and animal models with CMT-linked mutations in these enzymes display defects in neuronal protein synthesis. Rescuing protein synthesis in CMT-mutant neurons could offer exciting therapeutic options beyond symptom management. To address this need, we expressed CMT-linked variants of tyrosyl-tRNA synthetase (YARS–CMT) in primary mouse sensory neurons derived from both male and female embryos and evaluated impacts on protein synthesis and cell viability. YARS–CMT expression reduced protein synthesis in these neurons prior to the onset of caspase-dependent axon degeneration and cell death. To determine how Y...

Forming a long-term memory requires changes in neuronal transcription. What happens, though, as the memory is forgotten? And how does the transcriptional state relate to the maintenance and recall of the long-term memory? To answer these questions, we have been systematically tracing the time course of transcriptional changes evoked by long-term sensitization in the marine mollusk Aplysia californica . Our approach captures transcriptional changes in neurons of known behavioral relevance using a within-subject design, delineating patterns of transcriptional change that are comprehensive and reproducible. We have previously reported that within 1 d of long-term sensitization training, there is a widespread transcriptional response involving robust changes in over 5% of tested transcripts (1,198 of ∼22 k; [Conte et al., 2017][1]). Within 1 week, however, memory strength fades, and nearly all transcriptional changes relapse to baseline ( [Perez et al., 2018][2]). Here we report microarray analysis ( N  = 16) ...

A possible mechanism of temporal lobe epilepsy is insufficient inhibition of hippocampal dentate granule cells. Precipitating injuries that kill interneurons in the dentate gyrus might result in fewer inhibitory synapses with granule cells. To test this hypothesis, previous studies evaluated numbers or densities of interneurons, γ-amino butyric acid (GABA)ergic boutons, and inhibitory synapses in tissue from human patients with temporal lobe epilepsy and rodent models. However, those studies have limitations. Some of those limitations can be addressed by a large animal model. Sea lions ( Zalophus californianus ) can develop temporal lobe epilepsy naturally. Like humans, epileptic sea lions exhibit bilateral or unilateral hippocampal sclerosis (neuron loss) with granule cell vulnerability, but sea lions permit optimal tissue preservation and sampling, and good control subjects. To label interneuron cell bodies and GABAergic synaptic boutons, sea lion hippocampal tissue from both sexes was processed with imm...

The current treatment for drug-resistant epilepsy is surgical intervention, which relies on accurate identification of the seizure onset zone (SOZ) using intracranial electroencephalography (iEEG) data. iEEG analysis with computational epileptogenic zone identification algorithms (CEZIAs) is a promising step toward better SOZ localization and surgical outcomes. A key step in validation and adoption of CEZIAs is to allow for widespread shared development and validation of code and data. To achieve this, we developed an ecosystem of seizure localization methods that includes a straightforward analysis pipeline, standardized data formatting and storage, and completely documented and open-source code. The TableContainer package provides standardized storage of tabular data and serves as a foundational data structure for the ecosystem. Building on this, the Epoch package enables cropping, resampling, and visualization of iEEG data and provides publicly downloadable datasets for reproducibility. The public iEEG ...

Social media (SM) use is typically regarded as a technological tool which might negatively impact physical fitness and cognitive function, especially in critical developmental stages. In this opinion paper, we argue that specific forms of SM content might be beneficial for promoting motor skill acquisition and function. Furthermore, we suggest that SM use might be a promising innovative tool for educational purposes in optimizing skills not only in sports but also in academia. As a prerequisite, future research is needed to clarify the optimal type of content, its use, and how these parameters are affected by age. Therefore, longitudinal studies across the lifespan are necessary for a thorough understanding of the potential beneficial effects of SM use. The use of social media (SM) has rapidly accelerated due to technological progress and the release of the first SM platforms such as Facebook in the early 2000s. During the Covid-19 pandemic, lockdowns and social distancing acted as catalysts, contributing...