Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology.

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.

VIP interneurons in mouse primary visual cortex selectively enhance responses to weak but specific stimuli.

Vasoactive intestinal peptide-expressing (VIP) interneurons in the cortex regulate feedback inhibition of pyramidal neurons through suppression of somatostatin-expressing (SST) interneurons and, reciprocally, SST neurons inhibit VIP neurons. Although VIP neuron activity in the primary visual cortex (V1) of mouse is highly correlated with locomotion, the relevance of locomotion-related VIP neuron activity to visual coding is not known. Here we show that VIP neurons in mouse V1 respond strongly to low contrast front-to-back motion that is congruent with self-motion during locomotion but are suppressed by other directions and contrasts. VIP and SST neurons have complementary contrast tuning. Layer 2/3 contains a substantially larger population of low contrast preferring pyramidal neurons than deeper layers, and layer 2/3 (but not deeper layer) pyramidal neurons show bias for front-to-back motion specifically at low contrast. Network modeling indicates that VIP-SST mutual antagonism regulates the gain of the cortex to achieve sensitivity to specific weak stimuli without compromising network stability.

Rapid Learning of Odor-Value Association in the Olfactory Striatum.

Rodents can successfully learn multiple novel stimulus-response associations after only a few repetitions when the contingencies predict reward. The circuits modified during such reinforcement learning to support decision-making are not known, but the olfactory tubercle (OT) and posterior piriform cortex (pPC) are candidates for decoding reward category from olfactory sensory input and relaying this information to cognitive and motor areas. Through single-cell recordings in behaving male and female C57BL/6 mice, we show here that an explicit representation for reward category emerges in the OT within minutes of learning a novel odor-reward association, whereas the pPC lacks an explicit representation even after weeks of overtraining. The explicit reward category representation in OT is visible in the first sniff (50-100 ms) of an odor on each trial, and precedes the motor action. Together, these results suggest that the coding of stimulus information required for reward prediction does not occur within olfactory cortex, but rather in circuits involving the olfactory striatum.SIGNIFICANCE STATEMENT Rodents are olfactory specialists and can use odors to learn contingencies quickly and well. We have found that mice can readily learn to place multiple odors into rewarded and unrewarded categories. Once they have learned the rule, they can do such categorization in a matter of minutes (<10 trials). We found that neural activity in olfactory cortex largely reflects sensory coding, with very little explicit information about categories. By contrast, neural activity in a brain region in the ventral striatum is rapidly modified in a matter of minutes to reflect reward category. Our experiments set up a paradigm for studying rapid sensorimotor reinforcement in a circuit that is right at the interface of sensory input and reward areas.

A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex.

To understand how the brain processes sensory information to guide behavior, we must know how stimulus representations are transformed throughout the visual cortex. Here we report an open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset. This publicly available dataset includes the cortical activity of nearly 60,000 neurons from six visual areas, four layers, and 12 transgenic mouse lines in a total of 243 adult mice, in response to a systematic set of visual stimuli. We classify neurons on the basis of joint reliabilities to multiple stimuli and validate this functional classification with models of visual responses. While most classes are characterized by responses to specific subsets of the stimuli, the largest class is not reliably responsive to any of the stimuli and becomes progressively larger in higher visual areas. These classes reveal a functional organization wherein putative dorsal areas show specialization for visual motion signals.

Aberration-free multi-plane imaging of neural activity from the mammalian brain using a fast-switching liquid crystal spatial light modulator.

We report a novel two-photon fluorescence microscope based on a fast-switching liquid crystal spatial light modulator and a pair of galvo-resonant scanners for large-scale recording of neural activity from the mammalian brain. The spatial light modulator is used to achieve fast switching between different imaging planes in multi-plane imaging and correct for intrinsic optical aberrations associated with this imaging scheme. The utilized imaging technique is capable of monitoring the neural activity from large populations of neurons with known coordinates spread across different layers of the neocortex in awake and behaving mice, regardless of the fluorescent labeling strategy. During each imaging session, all visual stimulus driven somatic activity could be recorded in the same behavior state. We observed heterogeneous response to different types of visual stimuli from ∼ 3,300 excitatory neurons reaching from layer II/III to V of the striate cortex.

Identification of genetic markers for cortical areas using a Random Forest classification routine and the Allen Mouse Brain Atlas.

The mammalian neocortex is subdivided into a series of cortical areas that are functionally and anatomically distinct and are often distinguished in brain sections using histochemical stains and other markers of protein expression. We searched the Allen Mouse Brain Atlas, a database of gene expression, for novel markers of cortical areas. To screen for genes that change expression at area borders, we employed a random forest algorithm and binary region classification. Novel genetic markers were identified for 19 of 39 areas and provide code that quickly and efficiently searches the Allen Mouse Brain Atlas. Our results demonstrate the utility of the random forest algorithm for cortical area classification and we provide code that may be used to facilitate the identification of genetic markers of cortical and subcortical structures and perhaps changes in gene expression in disease states.

Decrease in gamma-band activity tracks sequence learning.

Learning novel sequences constitutes an example of declarative memory formation, involving conscious recall of temporal events. Performance in sequence learning tasks improves with repetition and involves forming temporal associations over scales of seconds to minutes. To further understand the neural circuits underlying declarative sequence learning over trials, we tracked changes in intracranial field potentials (IFPs) recorded from 1142 electrodes implanted throughout temporal and frontal cortical areas in 14 human subjects, while they learned the temporal-order of multiple sequences of images over trials through repeated recall. We observed an increase in power in the gamma frequency band (30-100 Hz) in the recall phase, particularly in areas within the temporal lobe including the parahippocampal gyrus. The degree of this gamma power enhancement decreased over trials with improved sequence recall. Modulation of gamma power was directly correlated with the improvement in recall performance. When presenting new sequences, gamma power was reset to high values and decreased again after learning. These observations suggest that signals in the gamma frequency band may play a more prominent role during the early steps of the learning process rather than during the maintenance of memory traces.

The maturation of GABAergic transmission in visual cortex requires endocannabinoid-mediated LTD of inhibitory inputs during a critical period.

Endocannabinoids are widely regarded as negative modulators of presynaptic release. Here, we present evidence that in visual cortex endocannabinoids are crucial for the maturation of GABAergic release. We found that between eye opening and puberty, release changes from an immature state with high release probability, short-term depression (STD), and high release variability during irregular patterned activity, to a mature state with reduced release probability, STD, and variability. This transition requires visual experience and stimulation of CB1 cannabinoid receptors as it is mimicked by administration of CB1 agonists, blocked by antagonists, and is absent in CB1R KO mice. In immature slices, activation of CB1 receptors induces long-term depression of inhibitory responses (iLTD) and a reduction in STD and response variability. Based on these findings, we propose that visually induced endocannabinoid-dependent iLTD mediates the developmental decrease in release probability, STD, and response variability, which are characteristic of maturation of cortical GABAergic inhibition.

Self-organized criticality occurs in non-conservative neuronal networks during Up states.

During sleep, under anesthesia and in vitro, cortical neurons in sensory, motor, association and executive areas fluctuate between Up and Down states (UDS) characterized by distinct membrane potentials and spike rates [1, 2, 3, 4, 5]. Another phenomenon observed in preparations similar to those that exhibit UDS, such as anesthetized rats [6], brain slices and cultures devoid of sensory input [7], as well as awake monkey cortex [8] is self-organized criticality (SOC). This is characterized by activity "avalanches" whose size distributions obey a power law with critical exponent of about [Formula: see text] and branching parameter near unity. Recent work has demonstrated SOC in conservative neuronal network models [9, 10], however critical behavior breaks down when biologically realistic non-conservatism is introduced [9]. We here report robust SOC behavior in networks of non-conservative leaky integrate-and-fire neurons with short-term synaptic depression. We show analytically and numerically that these networks typically have 2 stable activity levels corresponding to Up and Down states, that the networks switch spontaneously between them, and that Up states are critical and Down states are subcritical.