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 ...

Bridging integrator 1 ( BIN1 ) is one of the strongest genetic risk factors for Alzheimer’s disease (AD), yet its function in the brain and role in AD remain unclear. Neuronal BIN1 isoform levels are decreased in AD, and recent data show an important role of BIN1 in inhibitory neurons. Inhibitory neurons are key regulators of cognition and network excitability, with parvalbumin-expressing (PV) neurons as the most abundant subtype. We tested the hypothesis that loss of BIN1 from PV neurons contributes to AD-related cognitive dysfunction and network hyperexcitability. We generated a cell type–specific conditional knock-out mouse line, Bin1- pvKO, and examined mice of both sexes. These mice showed few behavioral differences when assessed with traditional or machine learning–based behavioral tests, with only a slight reduction in exploratory behavior in aged cohorts. Bin1- pvKO mice showed no significant differences in network excitability on measures of induced seizure susceptibility and spiking on cortical e...

Molecular tools available for rodent research enable detailed interrogation of the neural cell types and circuits that give rise to perception and decision-making during complex behaviors. To take full advantage of these molecular tools and successfully define causal relationships between neural function and overt actions during learning, there is a need for low-cost behavioral platforms with inherent flexibility in the implementation of task details. We present a behavioral platform capable of executing both head-fixed and freely moving task designs. The platform incorporates a user-interactive GUI that allows parameters to be adjusted online, during an acquisition session. Task metrics and performance indicators are acquired and organized into a standardized output, enabling single users to quickly master data analysis across a variety of task designs. To demonstrate the flexibility of the platform, mice of either sex were trained in two discrimination tasks: a head-fixed two-choice task as well as a fre...

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...

Terry Dean and Vittorio Gallo discuss their paper, “Endogenous Circadian Clock Machinery in Cortical NG2-Glia Regulates Cellular Proliferation,” published in Vol. 9, Issue 5 of eNeuro, with Editor-in-Chief Cristophe Bernard. 

“Rigor” is the vaguest sought-after quality of research. If you attach a license to your work, you can say it’s open. If you guide a collaborator through a protocol, your work is reproducible.

The current treatment for drug-resistant epilepsy is surgical intervention, which relies on accurate identification of the seizure onset zone (SOZ) using intracranial EEG (iEEG) data. iEEG analysis with computational epileptogenic zone identification algorithms (CEZIAs) is a promising step towards 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. We describe a set of three R packages to achieve this goal. Our ecosystem of seizure localization methods involves a straightforward analysis pipeline, standardized data formatting and storage, and completely documented and open-source code. The TableContainer package allows for easy storage and manipulation of table data, serving as groundwork for the Epoch package, which is specifically geared towards iEEG data. The Epoch package allows for cropping, resampling, and visualization of iEEG data and provides publicly downloadable iEEG data for...

Harmonicity is a property of complex sounds such as vocalizations or music, but it remains unclear how harmonicity is processed in the auditory cortex (ACtx). Subregions of ACtx are thought to process harmonic stimuli differently. Selective responses to sound features in ACtx emerge hierarchically from primary ACtx (A1) L4 and secondary ACtx (A2) layer (L) 2/3, which is believed to be the most responsive to harmonic sounds. Since harmonic stacks can range from two to more than ten components, being more similar to naturalistic vocalizations, harmonic sensitivity might also arise hierarchically across layers and areas. We studied responses to harmonic stacks of two to ten frequencies across A1 L4, A1 L2/3, and A2 L2/3 in adult male and female mice using in vivo two-photon microscopy. We found harmonic-sensitive neurons (HN) responding only to harmonic stacks but not to individual frequencies in all areas at similar proportions. HNs showed highly nonlinear spectral integration of harmonic frequencies that de...

Consumption varies across the stages (metestrus, diestrus, proestrus, estrus) of a rat’s estrous cycle, changing in ways that might be expected to reflect, in part, a direct impact of hormones on taste palatability. Evidence regarding this hypothesis has been mixed, however, and critical within-subject experiments comparing consumption of multiple tastes with distinct valences across all estrous phases have been few. Here, we assayed female rats’ licking of palatable (saccharin, sucrose, NaCl) and aversive (quinine-HCl, citric acid) tastes in brief-access trials, while tracking their estrous cycles through vaginal cytology. We observed sucrose palatability to be high at metestrus, the same phase at which the palatability of the aversive citric acid was low. These patterns were consistent across tastes of similar palatability, despite vast differences between the substances’ receptor mechanisms and central impacts. Together, these results reveal a general (i.e., independent of particular tastant identity) m...