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Identification of the structural connections between neurons is a prerequisite to understanding brain function. We developed a pipeline to systematically map brain-wide monosynaptic inputs to specific neuronal populations using Cre-driver mouse lines and the recombinant rabies tracing system. We first improved the rabies virus tracing strategy to accurately identify starter cells and to efficiently quantify presynaptic inputs. We then mapped brain-wide presynaptic inputs to different excitatory and inhibitory neuron subclasses in the primary visual cortex and seven higher visual areas. Our results reveal quantitative target-, layer- and cell-class-specific differences in the retrograde connectomes, despite similar global input patterns to different neuronal populations in the same anatomical area. The retrograde connectivity we define is consistent with the presence of the ventral and dorsal visual information processing streams and reveals further subnetworks within the dorsal stream. The hierarchical organization of the entire visual cortex can be derived from intracortical feedforward and feedback pathways mediated by upper- and lower-layer input neurons, respectively. This study expands our knowledge of the brain-wide inputs regulating visual areas and demonstrates that our improved rabies virus tracing strategy can be used to scale up the effort in dissecting connectivity of genetically defined cell populations in the whole mouse brain.

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of cortical neurons. While each of these two modalities has distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging of genetically expressed GCaMP6f or electrophysiology with silicon probes. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging, which was partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could only reconcile differences in responsiveness when restricted to neurons with low contamination and an event rate above a minimum threshold. This work established how the biases of these two modalities impact functional metrics that are fundamental for characterizing sensory-evoked responses.

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of neurons in the brain. While these two modalities have distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging or electrophysiology. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging. This work explores which data transformations are most useful for explaining these modality-specific discrepancies. We show that the higher selectivity in imaging can be partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could not reconcile differences in responsiveness without sub-selecting neurons based on event rate or level of signal contamination. This suggests that differences in responsiveness more likely reflect neuronal sampling bias or cluster-merging artifacts during spike sorting of electrophysiological recordings, rather than flaws in event detection from fluorescence time series. This work establishes the dominant impacts of the two modalities’ respective biases on a set of functional metrics that are fundamental for characterizing sensory-evoked responses.

To study the mechanisms of perception and cognition, neural measurements must be made during behavior. A goal of the Allen Brain Observatory is to map the activity of distinct cortical cell classes underlying visual and behavioral processing. Here we describe standardized methodology for training head-fixed mice on a visual change detection task, and we use our paradigm to characterize learning and behavior of five GCaMP6-expressing transgenic lines. We used automated training procedures to facilitate comparisons across mice. Training times varied, but most transgenic mice learned the behavioral task. Motivation levels also varied across mice. To compare mice in similar motivational states we subdivided sessions into over-, under-, and optimally motivated periods. When motivated, the pattern of perceptual decisions were highly correlated across transgenic lines, although overall performance (d-prime) was lower in one line labeling somatostatin inhibitory cells. These results provide important context for using these mice to map neural activity underlying perception and behavior.