Upon degeneration of photoreceptors in the adult retina, interneurons, including bipolar cells, exhibit a plastic response leading to their aberrant rewiring. Photoreceptor reintroduction has been suggested as a potential approach to sight restoration, but the ability of deafferented bipolar cells to establish functional synapses with photoreceptors is poorly understood. Here we use photocoagulation to selectively destroy photoreceptors in adult rabbits while preserving the inner retina. We find that rods and cones shift into the ablation zone over several weeks, reducing the blind spot at scotopic and photopic luminances.

Psychological stress affects a wide spectrum of brain functions and poses risks for many mental disorders. However, effective therapeutics to alleviate or revert its deleterious effects are lacking. A recently synthesized psychedelic analog tabernanthalog (TBG) has demonstrated anti-addictive and antidepressant potential. Whether TBG can rescue stress-induced affective, sensory, and cognitive deficits, and how it may achieve such effects by modulating neural circuits, remain unknown. Here we show that in mice exposed to unpredictable mild stress (UMS), administration of a single dose of TBG decreases their anxiety level and rescues deficits in sensory processing as well as in cognitive flexibility. Post-stress TBG treatment promotes the regrowth of excitatory neuron dendritic spines lost during UMS, decreases the baseline neuronal activity, and enhances whisking-modulation of neuronal activity in the somatosensory cortex. Moreover, calcium imaging in head-fixed mice performing a whisker-dependent texture discrimination task shows that novel textures elicit responses from a greater proportion of neurons in the somatosensory cortex than do familiar textures. Such differential response is diminished by UMS and is restored by TBG. Together, our study reveals the effects of UMS on cortical neuronal circuit activity patterns and demonstrate that TBG combats the detrimental effects of stress by modulating basal and stimulus-dependent neural activity in cortical networks.

The prevalent use of antibiotics in pregnant women and neonates raises concerns about long-term risks for children’s health, but their effects on the central nervous system is not well understood. We studied the effects of perinatal penicillin exposure (PPE) on brain structure and function in mice with a therapeutically relevant regimen. We used a battery of behavioral tests to evaluate anxiety, working memory, and sensory processing, and immunohistochemistry to quantify changes in parvalbumin-expressing inhibitory interneurons (PV+ INs), perineuronal nets (PNNs), as well as microglia density and morphology. In addition, we performed mesoscale calcium imaging to study neural activity and functional connectivity across cortical regions, and two-photon imaging to monitor dendritic spine and microglial dynamics. We found that adolescent PPE mice have abnormal sensory processing, including impaired texture discrimination and altered prepulse inhibition. Such behavioral changes are associated with increased spontaneous neural activities in various cortical regions, and delayed maturation of PV+ INs in the somatosensory cortex. Furthermore, adolescent PPE mice have elevated elimination of dendritic spines on the apical dendrites of layer 5 pyramidal neurons, as well as increased ramifications and spatial coverage of cortical microglia. Finally, while synaptic defects are transient during adolescence, behavioral abnormalities persist into adulthood. Our study demonstrates that early-life exposure to antibiotics affects cortical development, leaving a lasting effect on brain functions.

Recording neuronal group activity across the cortical hemispheres from awake, behaving mice is essential for understanding information flow across cerebral networks. Video recordings of cerebral function comes with challenges, including optical and movement-associated vessel artifacts, and limited references for time series extraction. Here we present a data-driven workflow that isolates artifacts from calcium activity patterns, and segments independent functional units across the cortical surface. Independent Component Analysis utilizes the statistical interdependence of pixel activation to completely unmix signals from background noise, given sufficient spatial and temporal samples. We also utilize isolated signal components to produce segmentations of the cortical surface, unique to each individual’s functional patterning. Time series extraction from these maps maximally represent the underlying signal in a highly compressed format. These improved techniques for data pre-processing, spatial segmentation, and time series extraction result in optimal signals for further analysis.

Functional imaging of neural cell populations is critical for mapping intra- and inter-regional network dynamics across the neocortex. Recently we showed that an unsupervised machine learning decomposition of densely sampled recordings of cortical calcium dynamics results in a collection of components comprised of neuronal signal sources distinct from optical, movement, and vascular artifacts. Here we build a supervised learning classifier that automatically separates neural activity and artifact components, using a set of extracted spatial and temporal metrics that characterize the respective components. We demonstrate that the performance of the machine classifier matches human identification of signal components in novel data sets. Further, we analyze control data recorded in glial cell reporter and non-fluorescent mouse lines that validates human and machine identification of functional component class. This combined workflow of data-driven video decomposition and machine classification of signal sources will aid robust and scalable mapping of complex cerebral dynamics.