Coherent control of purposive actions emerges from the coordination of multiple brain circuits during learning. Dissociable brain circuits and cell-types are thought to preferentially participate in distinct learning mechanisms. For example, the activity of midbrain dopamine (mDA) neurons is proposed to primarily, or even exclusively, reflect reward prediction error signals in well-trained animals. To study the specific contribution of individual circuits requires observing changes before tight functional coordination is achieved. However, little is known about the detailed timing of the emergence of reward-related representations in dopaminergic neurons. Here we recorded activity of identified dopaminergic neurons as naive mice learned a novel stimulus-reward association. We found that at early stages of learning mDA neuron activity reflected both external (sensory) and internal (action initiation) causes of reward expectation. The increasingly precise correlation of action initiation with sensory stimuli rather than an evaluation of outcomes governed mDA neuron activity. Thus, our data demonstrate that mDA neuron activity early in learning does not reflect errors, but is more akin to a Hebbian learning signal - providing new insight into a critical computation in a highly conserved, essential learning circuit.

On evolutionary timescales, brain circuits adapt to support survival in each species’ ecological niche. While some anatomical aspects of neural circuitry are conserved across species with distant evolutionary origins, each species also exhibits specific circuit adaptations that enable its behavioral repertoire. It remains unclear whether homologous brain regions leverage analogous neural computations as different species perform common behaviors such as reaching and manipulating objects. Here, we directly assessed conservation of neural computations using intracortical recordings from mouse, monkey, and human motor cortex—a homologous region across many mammals—during motor behaviors crucial for survival. We hypothesized that, despite their phylogenetic distance, rodents and primates produce movements through conserved neural computations implemented by motor cortical population dynamics. Remarkably, we found that movement-related neural dynamics were highly conserved across species, while variations in behavioral output were uniquely captured in neural trajectory geometries. Strikingly, neural dynamics during movement across species were more conserved than those across brain regions in the same human and between motor preparation and execution in the same monkeys. Lastly, through manipulation of neural network models trained to perform reaching movements, we reinforce that conservation of neural dynamics across species likely stems from shared circuit constraints. We thus assert that evolution maintains neural computations across phylogeny even as behavioral repertoires expand.

Targeted manipulation of activity in specific populations of neurons is important for investigating the neural circuit basis of behavior. Optogenetic approaches using light-sensitive microbial rhodopsins have permitted manipulations to reach a level of temporal precision that is enabling functional circuit dissection. As demand for more precise perturbations to serve specific experimental goals increases, a palette of opsins with diverse selectivity, kinetics, and spectral properties will be needed. Here, we introduce a novel approach of "topological engineering"-inversion of opsins in the plasma membrane-and demonstrate that it can produce variants with unique functional properties of interest for circuit neuroscience. In one striking example, inversion of a Channelrhodopsin variant converted it from a potent activator into a fast-acting inhibitor that operates as a cation pump. Our findings argue that membrane topology provides a useful orthogonal dimension of protein engineering that immediately permits as much as a doubling of the available toolkit.

The study of foraging is central to a renewed interest in naturalistic behavior in neuroscience. Applying a foraging framework grounded in behavioral ecology has enabled probing of the mechanisms underlying cognitive processes such as decision-making within a more ecological context. Yet, foraging also involves myriad other aspects, including navigation of complex environments, sensory processing, and social interactions. Here, we first provide a brief overview of the neuroscience of foraging decisions, and then combine insights from behavioral ecology and neuroscience to review the role of these additional dimensions of foraging. We conclude by highlighting four opportunities for the continued development of foraging as an ethological framework for neuroscience: integrating normative and implementation-level models, developing new tools, enabling cross-species comparisons, and fostering interdisciplinary collaboration.

HCN1 hyperpolarization-activated cation channels act as an inhibitory constraint of both spatial learning and synaptic integration and long-term plasticity in the distal dendrites of hippocampal CA1 pyramidal neurons. However, as HCN1 channels provide an excitatory current, the mechanism of their inhibitory action remains unclear. Here we report that HCN1 channels also constrain CA1 distal dendritic Ca2+ spikes, which have been implicated in the induction of LTP at distal excitatory synapses. Our experimental and computational results indicate that HCN1 channels provide both an active shunt conductance that decreases the temporal integration of distal EPSPs and a tonic depolarizing current that increases resting inactivation of T-type and N-type voltage-gated Ca2+ channels, which contribute to the Ca2+ spikes. This dual mechanism may provide a general means by which HCN channels regulate dendritic excitability.

Whereas recent studies have elucidated principles for representation of information within the entorhinal cortex, less is known about the molecular basis for information processing by entorhinal neurons. The HCN1 gene encodes ion channels that mediate hyperpolarization-activated currents (I(h)) that control synaptic integration and influence several forms of learning and memory. We asked whether hyperpolarization-activated, cation nonselective 1 (HCN1) channels control processing of information by stellate cells found within layer II of the entorhinal cortex. Axonal projections from these neurons form a major component of the synaptic input to the dentate gyrus of the hippocampus. To determine whether HCN1 channels control either the resting or the active properties of stellate neurons, we performed whole-cell recordings in horizontal brain slices prepared from adult wild-type and HCN1 knock-out mice. We found that HCN1 channels are required for rapid and full activation of hyperpolarization-activated currents in stellate neurons. HCN1 channels dominate the membrane conductance at rest, are not required for theta frequency (4-12 Hz) membrane potential fluctuations, but suppress low-frequency (<4 Hz) components of spontaneous and evoked membrane potential activity. During sustained activation of stellate cells sufficient for firing of repeated action potentials, HCN1 channels control the pattern of spike output by promoting recovery of the spike afterhyperpolarization. These data suggest that HCN1 channels expressed by stellate neurons in layer II of the entorhinal cortex are key molecular components in the processing of inputs to the hippocampal dentate gyrus, with distinct integrative roles during resting and active states.

Optical imaging has become a powerful tool for studying brains . The opacity of adult brains makes microendoscopy, with an optical probe such as a gradient index (GRIN) lens embedded into brain tissue to provide optical relay, the method of choice for imaging neurons and neural activity in deeply buried brain structures. Incorporating a Bessel focus scanning module into two-photon fluorescence microendoscopy, we extended the excitation focus axially and improved its lateral resolution. Scanning the Bessel focus in 2D, we imaged volumes of neurons at high-throughput while resolving fine structures such as synaptic terminals. We applied this approach to the volumetric anatomical imaging of dendritic spines and axonal boutons in the mouse hippocampus, and functional imaging of GABAergic neurons in the mouse lateral hypothalamus .

Animals learn trajectories to rewards in both spatial, navigational contexts and relational, non-navigational contexts. Synchronous reactivation of hippocampal activity is thought to be critical for recall and evaluation of trajectories for learning. Do hippocampal representations differentially contribute to experience-dependent learning of trajectories across spatial and relational contexts? In this study, we trained mice to navigate to a hidden target in a physical arena or manipulate a joystick to a virtual target to collect delayed rewards. In a navigational context, calcium imaging in freely moving mice revealed that synchronous CA1 reactivation was retrospective and important for evaluation of prior navigational trajectories. In a non-navigational context, reactivation was prospective and important for initiation of joystick trajectories, even in the same animals trained in both contexts. Adaptation of trajectories to a new target was well-explained by a common learning algorithm in which hippocampal activity makes dissociable contributions to reinforcement learning computations depending upon spatial context.

Optogenetic reagents allow for depolarization and hyperpolarization of cells with light. This provides unprecedented spatial and temporal resolution to the control of neuronal activity both in vitro and in vivo. In the intact animal this requires strategies to deliver light deep into the highly scattering tissue of the brain. A general approach that we describe here is to implant optical fibers just above brain regions targeted for light delivery. In part due to the fact that expression of optogenetic proteins is accomplished by techniques with inherent variability (e.g., viral expression levels), it also requires strategies to measure and calibrate the effect of stimulation. Here we describe general procedures that allow one to simultaneously stimulate neurons and use photometry with genetically encoded activity indicators to precisely calibrate stimulation.

Responses to threat-related stimuli are influenced by conscious and unconscious processes, but the neural systems underlying these processes and their relationship to anxiety have not been clearly delineated. Using fMRI, we investigated the neural responses associated with the conscious and unconscious (backwardly masked) perception of fearful faces in healthy volunteers who varied in threat sensitivity (Spielberger trait anxiety scale). Unconscious processing modulated activity only in the basolateral subregion of the amygdala, while conscious processing modulated activity only in the dorsal amygdala (containing the central nucleus). Whereas activation of the dorsal amygdala by conscious stimuli was consistent across subjects and independent of trait anxiety, activity in the basolateral amygdala to unconscious stimuli, and subjects’ reaction times, were predicted by individual differences in trait anxiety. These findings provide a biological basis for the unconscious emotional vigilance characteristic of anxiety and a means for investigating the mechanisms and efficacy of treatments for anxiety.