Biology subjects

Amador, A.

Publications and source records attributed to Amador, A..

5 recordsLinked to original sources

bioRxiv2026

Neural-vocal phase coupling reveals structured timing in birdsong production

Understanding how neural population activity is temporally coordinated with behavior remains a central challenge in neuroscience. Songbirds provide a powerful model system for addressing this question because learned vocal production requires precise coordination among neural dynamics, temporally structured motor output, and auditory feedback. However, quantifying neural-vocal interactions is challenging because both neural and acoustic signals are rhythmic, noisy, and highly nonstationary. Here, we investigate neural-vocal coordination during spontaneous canary singing using simultaneous recordings of neural population activity in a forebrain region of the song system and vocal behavior. Using a phase-resolved cross-correlation framework combined with surrogate-based statistical validation, we quantify neural-vocal interactions in short and highly variable song segments. Our analysis reveals that neural-vocal interactions are organized into distinct temporal regimes comprising positive, near-zero, and negative lags, consistent with neural activity preceding, accompanying, or following vocal output. The coexistence of these regimes is consistent with the integrative role of the recorded region, which receives auditory input, contributes to premotor control, and participates in the neural circuitry supporting song learning and the ongoing maintenance of adult song. We further find that correlated and anticorrelated interactions coexist throughout singing, with anticorrelated interactions consistently concentrated around near-zero lags. These anticorrelations identify periods in which decreases in neural population activity are closely aligned with sound production, revealing biologically relevant information that is obscured by analyses performed over complete song renditions. Together, these results uncover a robust temporal structure linking neural population activity to vocal behavior and provide a broadly applicable framework for extracting transient neural-behavioral interactions from complex biological signals. Author summaryModern neuroscience can simultaneously record the activity of large neural populations, yet extracting meaningful relationships between neural activity and behavior remains challenging because natural behaviors are highly variable. Songbirds provide a unique opportunity to study this problem because their learned vocalizations share key features with human speech while remaining experimentally accessible. Here, we analyzed simultaneous recordings of neural population activity and vocal behavior in freely singing canaries. Instead of averaging neural activity across entire songs, we examined brief time windows and combined local correlation analysis with statistical tests to identify reliable interactions between the brain and behavior. We found that these interactions switch among several preferred timing patterns: neural activity can precede vocal output, occur at nearly the same time, or follow acoustic events. This diversity is consistent with the combined roles of the recorded brain region. Our work provides an intuitive and broadly applicable framework for uncovering transient neural-behavioral interactions that remain hidden by traditional time-averaged approaches. Because it requires only simultaneous recordings of two time series and makes minimal assumptions about their dynamics, the framework can be applied to many biological systems involving complex temporal signals.

neuroscience↗

bioRxiv2026

Low-dimensional neural dynamics underlying rhythmic vocal behavior in songbirds

Birdsong is a complex learned behavior that requires millisecond-scale precision in the coordinated activation of respiratory and vocal muscles to generate sound. Canary song consists of sequences of syllables organized into phrases, in which each syllable type is repeated at a characteristic rate, giving rise to a well-defined rhythmic vocal behavior. Here, we analyze neural population activity in the telencephalic song system nucleus HVC of singing adult male canaries (Serinus canaria), in relation to both vocal output and the underlying respiratory motor gestures. To uncover structure in these high-dimensional neural recordings, we used an unsupervised autoencoder. We found that a three-dimensional latent space was sufficient to reconstruct the data with minimal information loss, revealing a low-dimensional representation of HVC population activity. The oscillation frequencies of the latent modes closely matched both the syllabic repetition rate and the corresponding respiratory motor patterns. These results show that multiunit activity in HVC captures key rhythmic features of song at the population level, providing a dynamical representation of behaviorally relevant motor structure. More broadly, our findings highlight how data-driven dimensionality reduction can reveal structured, low-dimensional neural dynamics underlying complex learned motor behaviors.

neuroscience↗

bioRxiv2024

Beta-barrel proteins dictate the effect of core oligosaccharide composition on outer membranemechanics

The outer membrane is the defining structure of Gram-negative bacteria. We previously demonstrated that it is critical for the mechanical integrity of the cell envelope and therefore to the robustness of the bacterial cell as a whole. Here, to determine the key molecules and moieties within the outer membrane that underlie its contribution to cell envelope mechanics, we measured cell-envelope stiffness across several sets of mutants with altered outer-membrane sugar content, protein content, and electric charge. To decouple outer membrane stiffness from total cell envelope stiffness, we developed a novel microfluidics-based "osmotic force extension" assay. In tandem, we developed a simple method to increase throughput of microfluidics experiments by performing them on color-coded pools of mutants. Using Escherichia coli as a model Gram-negative bacterium, we found that truncating the core oligosaccharide, deleting the {beta}-barrel protein OmpA, or deleting lipoprotein outer membrane-cell wall linkers all had the same modest, convergent effect on total cell-envelope stiffness but had large, varying effects on the ability of the cell wall to transfer tension to the outer membrane during large hyperosmotic shocks. Surprisingly, altering lipid A charge had little effect on the mechanical properties of the envelope. Importantly, the presence or absence of OmpA determined whether truncating the core oligosaccharide decreased or increased envelope stiffness (respectively), revealing sign epistasis between these components. Based on these data we propose a specific structural model in which the chemical interactions between lipopolysaccharides, {beta}-barrel proteins, and phospholipids coordinately determine cell envelope stiffness, and the ability of the outer membrane to functionally share mechanical loads with the cell wall. Statement of SignificanceThe outer membrane is the defining cellular structure of Gram-negative bacteria, a group that contains many important pathogens like Escherichia coli, Vibrio cholerae, and Pseudomonas aeruginosa. One role of the outer membrane is to block the uptake of small molecules like antibiotics. However, it is becoming increasingly clear that it also functions as a structural exoskeleton that is critical for the cells ability to cope with internal and external mechanical forces. Here, we carefully dissect the molecular basis for the load-bearing capacity of the outer membrane by screening a set of mutants with a new cell biophysics assay.

biophysics↗

bioRxiv2019

Arfgef1 haploinsufficiency in mice alters neuronal endosome composition and decreases membrane surface postsynaptic GABAA receptors

ARFGEF1 encodes a guanine exchange factor involved in intracellular vesicle trafficking, and is a candidate gene for childhood genetic epilepsies. To model ARFGEF1 haploinsufficiency observed in a recent Lennox Gastaut Syndrome patient, we studied a frameshift mutation (Arfgef1fs) in mice. Arfgef1fs/+ pups exhibit signs of developmental delay, and Arfgef1fs/+ adults have a significantly decreased threshold to induced seizures but do not experience spontaneous seizures. Histologically, the Arfgef1fs/+ brain exhibits a disruption in the apical lining of the dentate gyrus and altered spine morphology of deep layer neurons. In primary hippocampal neuron culture, dendritic surface and synaptic but not total GABAA receptors (GABAAR) are reduced in Arfgef1fs/+ neurons with an accompanying decrease in GABAAR-containing recycling endosomes in cell body. Arfgef1fs/+ neurons also display differences in the relative ratio of Arf6+:Rab11+:TrfR+ recycling endosomes. Although the GABAAR-containing early endosomes in Arfgef1fs/+ neurons are comparable to wildtype, Arfgef1fs/+ neurons show an increase in GABAAR-containing lysosomes in dendrite and cell body. Together, the altered endosome composition and decreased neuronal surface GABAAR results suggests a mechanism whereby impaired neuronal inhibition leads to seizure susceptibility.\n\nHighlightsO_LIArfgef1fs/+ mice have lower seizure threshold but no spontaneous seizure.\nC_LIO_LIArfgef1fs/+ neurons show reduced dendritic surface GABAAR.\nC_LIO_LIArfgef1fs/+ neurons have decreased GABAAR-containing recycling endosome accompanied with an increase in GABAAR-containing lysosomes.\nC_LI

genetics↗

bioRxiv2019

Modeling and treating GRIN2A developmental and epileptic encephalopathy in mice

NMDA receptors (NMDAR) play crucial roles in excitatory synaptic transmission. Rare variants of GRIN2A, which encodes the GluN2A NMDAR subunit, are associated with several intractable neurodevelopmental disorders, including developmental and epileptic encephalopathy (DEE). A de novo missense variant, p.Ser644Gly (c.1930A>G), was identified in a child with DEE, and Grin2a knockin mice were generated to model and extend understanding of this intractable childhood disease. Homozygous and heterozygous mutant mice exhibit altered hippocampal morphology at two weeks of age, and homozygotes exhibit lethal tonic-clonic seizures in the third week. Heterozygous adult mice display a variety of distinct features, including resistance to electrically induced partial seizures, as well as hyperactivity and repetitive and reduced anxiety behaviors. Multielectrode recordings of mutant neuronal networks reveal hyperexcitability and altered bursting and synchronicity. When expressed in heterologous cells, mutant receptors exhibit enhanced NMDAR agonist potency and slow deactivation following rapid removal of glutamate, as occurs at synapses. Consistent with these observations, NMDAR-mediated synaptic currents in hippocampal slices from mutant mice show a prolonged deactivation time course. Standard antiepileptic drug monotherapy was ineffective in the patient, but combined treatment of NMDAR antagonists with antiepileptic drugs substantially reduced the seizure burden albeit without appreciable developmental improvement. Chronic treatment of homozygous mutant mouse pups with NMDAR antagonists delayed the onset of lethal seizures but did not prevent them. These studies illustrate the power of modeling severe neurodevelopmental seizure disorders using multiple experimental modalities and suggest their extended utility in identifying and evaluating new therapies.

neuroscience↗