Biology subjects

Kanold, P. O.

Publications and source records attributed to Kanold, P. O..

27 records · Page 2Linked to original sources

bioRxiv2021

Sequential Transmission of Task-Relevant Information in Cortical Neuronal Networks

During auditory task performance, cortical processing of task-relevant information enables mammals to recognize sensory input and flexibly select behavioral responses. In mouse auditory cortex, small neuronal networks encode behavioral choice during a pure-tone detection task, but it is poorly understood how neuronal networks encode behavioral choice during a pure-tone discrimination task where tones have to be categorized into targets and non-targets. While the interactions between networked neurons are thought to encode behavioral choice, it remains unclear how patterns of neuronal network activity indicate the transmission of task-relevant information within the network. To this end, we trained mice to behaviorally discriminate target vs. non-target pure-tones while we used in vivo 2-photon imaging to record neuronal population activity in primary auditory cortex layer 2/3. We found that during task performance, a specialized subset of neurons transiently encoded intersection information, i.e., sensory information that was used to inform behavioral choice. Granger causality analysis showed that these neurons formed functional networks in which task-relevant information was transmitted sequentially between neurons. Differences in network structure between target and non-target sounds encoded behavioral choice. Correct behavioral choices were associated with shorter timescale communication between neurons. In summary, we find that specialized neuronal populations in auditory cortex form functional networks during auditory task performance whose structures depend on both sensory input and behavioral choice.

neuroscience↗

bioRxiv2020

Hypomyelination leads to alterations in inhibitory function and parvalbumin-positive neuron density in the auditory cortex

For a long time, myelin was thought to be restricted to excitatory neurons, and studies on dysmyelination focused primarily on excitatory cells. Recent evidence showed that axons of inhibitory neurons in the neocortex are also myelinated, but the role of myelin on inhibitory circuits remains unknown. Here we studied the impact of mild hypomyelination on both excitatory and inhibitory connectivity in the primary auditory cortex (A1) with well-characterized mouse models of hypomyelination due to loss of oligodendrocyte ErbB receptor signaling. Using laser-scanning photostimulation, we found that mice with mild hypomyelination have reduced functional inhibitory connections to A1 L2/3 neurons without changes in excitatory connections, resulting in altered excitatory/inhibitory balance. These effects are not associated with altered expression of GABAergic and glutamatergic synaptic components, but with reduced density of parvalbumin-positive (PV+) neurons, which reflects reduced PV expression by interneurons rather than PV+ neuronal loss. While immunostaining shows that hypomyelination occurs in both PV+ and PV- axons, there is a strong correlation between MBP and PV expression suggesting that myelination influences PV expression. Together, the results demonstrate that mild hypomyelination impacts A1 neuronal networks, reducing inhibitory activity, and shifting networks towards excitation.

neuroscience↗

bioRxiv2020

Transient coupling between subplate and subgranular layers to L1 neurons before and during the critical period

Cortical layer 1 (L1) contains a diverse population of interneurons which can modulate processing in superficial cortical layers but the intracortical sources of synaptic input to these neurons and how these inputs change over development is unknown. We here investigated the changing intracortical connectivity to L1 in primary auditory cortex (A1) in slices of mouse A1 across development using laser-scanning photostimulation. Before P10 L1 cells receive most excitatory input from within L1, L2/3, L4 and L5/6 as well as the subplate. Excitatory inputs from all layers increase and peak during P10-P16, the peak of the critical period. Inhibitory inputs followed a similar pattern. Functional circuit diversity in L1 emerges after P16. In adult, L1 neurons receive ascending inputs from superficial L2/3 and subgranular L5/6, but only few inputs from L4. A subtype of L1 neurons, NDNF+ neurons, follow a similar pattern, suggesting that transient hyperconnectivity is a universal feature of developing cortical circuits. Our results demonstrate that deep excitatory and superficial inhibitory circuits are tightly linked in early development and might provide a functional scaffold for the layers in between. These results suggest that early thalamic driven spontaneous and sensory activity in subplate can be relayed to L1 from the earliest ages on, that the critical period is characterized by high transient columnar hyperconnectivity, and that in particular circuits originating in L5/6 and subplate might play a key role.

neuroscience↗

bioRxiv2019

Functional Organization of Mouse Primary Auditory Cortex in adult C57BL/6 and F1 (CBAxC57) mice

The primary auditory cortex (A1) plays a key role for sound perception since it represents one of the first cortical processing stations for sounds. Recent studies have shown that on the cellular level the frequency organization of A1 is more heterogeneous than previously appreciated. However, many of these studies were performed in mice on the C57BL/6 background which develop high frequency hearing loss with age making them a less optimal choice for auditory research. In contrast, mice on the CBA background retain better hearing sensitivity in old age. Since potential strain differences could exist in A1 organization between strains, we performed comparative analysis of neuronal populations in A1 of adult (~10 weeks) C57BL/6 mice and CBAxC57 F1 mice. We used in vivo 2-photon imaging of pyramidal neurons in cortical layers L4 and L2/3 of awake mouse primary auditory cortex (A1) to characterize the populations of neurons that were active to tonal stimuli. Pure tones recruited neurons of widely ranging frequency preference in both layers and strains with neurons in CBA mice exhibiting a wider range of frequency preference particularly to higher frequencies. Frequency selectivity was slightly higher in C57BL/6 mice while neurons in CBA mice showed a greater sound-level sensitivity. The spatial heterogeneity of frequency preference was present in both strains with CBA mice exhibiting higher tuning diversity across all measured length scales. Our results demonstrate that the tone evoked responses and frequency representation in A1 of adult C57BL/6 and CBAxC57 F1 mice is largely similar.

neuroscience↗

bioRxiv2019

Homeostatic regulation of perisynaptic MMP9 activity in the amblyopic visual cortex

Dark exposure (DE) followed by light reintroduction (LRx) reactivates robust synaptic plasticity in adult mouse V1, which allows recovery from amblyopia. Previously we showed that LRx-induced perisynaptic proteolysis of extracellular substrates by MMP9 mediates the enhanced plasticity in binocular adult mice (Murase et al., 2017). However, it is unknown if a visual system compromised by amblyopia could engage this pathway. Here we show that LRx to adult amblyopic mice induces perisynaptic MMP2/9 activity and degradation of ECM in the deprived and non-deprived V1. LRx restricted to the amblyopic eye induces equally robust MMP2/9 activity at thalamo-cortical synapses and ECM degradation in deprived V1. Two-photon live imaging demonstrates that the history of visual experience regulates MMP2/9 activity in V1, and that DE lowers the threshold for the proteinase activation. This homeostatic reduction of MMP2/9 activation threshold by DE enables the visual input from the amblyopic pathway to trigger robust perisynaptic proteolysis.

neuroscience↗

bioRxiv2019

Enduring consequences of perinatal fentanyl exposure in mice

Opioid use by pregnant women is an understudied consequence associated with the opioid epidemic, resulting in a rise in the incidence of neonatal opioid withdrawal syndrome (NOWS), and lifelong neurobehavioral deficits that result from perinatal opioid exposure. There are few preclinical models that accurately recapitulate human perinatal drug exposure, and few focus on fentanyl, a potent synthetic opioid that is a leading driver of the opioid epidemic. To investigate the consequences of perinatal opioid exposure, we administered fentanyl to mouse dams in their drinking water throughout gestation and until litters were weaned at postnatal day (PD) 21. Fentanyl-exposed dams delivered smaller litters, and had higher litter mortality rates compared to controls. Metrics of maternal care behavior were not affected by the treatment, nor were there differences in dams weight or liquid consumption throughout gestation and 21 days postpartum. Twenty-four hours after weaning and drug cessation, perinatal fentanyl-exposed mice exhibited signs of spontaneous somatic withdrawal behavior, and sex-specific weight fluctuations that normalized in adulthood. At adolescence (PD 35) they displayed elevated anxiety-like behaviors and decreased grooming, assayed in the elevated plus maze and sucrose splash tests. Finally, by adulthood (PD 55) they displayed impaired performance in a two-tone auditory discrimination task. Collectively, our findings suggest that perinatal fentanyl exposed mice exhibit somatic withdrawal behavior and changes across the lifespan reminiscent of humans born with NOWS.

neuroscience↗

bioRxiv2019

Neuronal avalanches in input and associative layers of auditory cortex

The primary auditory cortex processes acoustic sequences for the perception of behaviorally meaningful sounds such as speech. Sound information arrives at its input layer 4 from where activity propagates to associative layer 2/3. It is currently not known whether there is a particular organization of neuronal population activity that is stable across layers and sound levels during sound processing. We used in vivo 2-photon imaging of pyramidal neurons in cortical layers L4 and L2/3 of mouse A1 to characterize the populations of neurons that were active spontaneously, i.e. in the absence of a sound stimulus, and those recruited by single-frequency tonal stimuli at different sound levels. Single-frequency sounds recruited neurons of widely ranging frequency selectivity in both layers. We defined neural ensembles as neurons being active within or during successive temporal windows at the temporal resolution of our imaging. For both layers, neuronal ensembles were highly variable in size during spontaneous activity as well as during sound presentation. Ensemble sizes distributed according to power laws, the hallmark of neuronal avalanches, and were similar across sound levels. Avalanches activated by sound were composed of neurons with diverse tuning preference, yet with selectivity independent of avalanche size. Thus, spontaneous and evoked activity in both L4 and L2/3 of A1 are composed of neuronal avalanches with similar power law relationships. Our results demonstrate network principles linked to maximal dynamic range, optimal information transfer and matching complexity between L4 and L2/3 to shape population activity in auditory cortex.

neuroscience↗

bioRxiv2017

Spatial organization of the mouse auditory cortex to sound dynamics revealed using automated image segmentation

Sound stimuli are characterized by their rich spectral and temporal dynamic properties. Individual neurons in auditory cortex (ACX) encode both spectral and temporal aspects of sounds e.g. sound onset and/or offset. While the different fields of the ACX show gradients of frequency selectivity the large-scale organization of sound dynamics is unknown. We used widefield imaging of GCaMP6s in awake mouse ACX combined with a novel unsupervised image segmentation technique to investigate the spatiotemporal representation of sound onset and offset. Using this technique, we identified known auditory fields but also detected novel ACX areas. Furthermore, we found that ACX areas differed in their responses to tone onset and offset. Multiple areas were preferentially activated by tone offset, and on-response areas were more spatially localized than off-response areas. We also found tonotopy in off-responses. Together our results demonstrate a different spatial distribution of neurons across ACX for processing sound onsets versus offsets.

neuroscience↗

bioRxiv2016

Fast and Stable Signal Deconvolution via Compressible State-Space Models

Abstract-Objective:Common biological measurements are in the form of noisy convolutions of signals of interest with possibly unknown and transient blurring kernels. Examples include EEG and calcium imaging data. Thus, signal deconvolution of these measurements is crucial in understanding the underlying biological processes. The objective of this paper is to develop fast and stable solutions for signal deconvolution from noisy, blurred and undersampled data, where the signals are in the form of discrete events distributed in time and space. Methods: We introduce compressible state-space models as a framework to model and estimate such discrete events. These state-space models admit abrupt changes in the states and have a convergent transition matrix, and are coupled with compressive linear measurements. We consider a dynamic compressive sensing optimization problem and develop a fast solution, using two nested Expectation Maximization algorithms, to jointly estimate the states as well as their transition matrices. Under suitable sparsity assumptions on the dynamics, we prove optimal stability guarantees for the recovery of the states and present a method for the identification of the underlying discrete events with precise confidence bounds. Results: We present simulation studies as well as application to calcium deconvolution and sleep spindle detection, which verify our theoretical results and show significant improvement over existing techniques. Conclusion: Our results show that by explicitly modeling the dynamics of the underlying signals, it is possible to construct signal deconvolution solutions that are scalable, statistically robust, and achieve high temporal resolution. Significance: Our proposed methodology provides a framework for modeling and deconvolution of noisy, blurred, and undersampled measurements in a fast and stable fashion, with potential application to a wide range of biological data.

bioengineering↗