The neuron as a direct data-driven controller.

In the quest to model neuronal function amid gaps in physiological data, a promising strategy is to develop a normative theory that interprets neuronal physiology as optimizing a computational objective. This study extends current normative models, which primarily optimize prediction, by conceptualizing neurons as optimal feedback controllers. We posit that neurons, especially those beyond early sensory areas, steer their environment toward a specific desired state through their output. This environment comprises both synaptically interlinked neurons and external motor sensory feedback loops, enabling neurons to evaluate the effectiveness of their control via synaptic feedback. To model neurons as biologically feasible controllers which implicitly identify loop dynamics, infer latent states, and optimize control we utilize the contemporary direct data-driven control (DD-DC) framework. Our DD-DC neuron model explains various neurophysiological phenomena: the shift from potentiation to depression in spike-timing-dependent plasticity with its asymmetry, the duration and adaptive nature of feedforward and feedback neuronal filters, the imprecision in spike generation under constant stimulation, and the characteristic operational variability and noise in the brain. Our model presents a significant departure from the traditional, feedforward, instant-response McCulloch-Pitts-Rosenblatt neuron, offering a modern, biologically informed fundamental unit for constructing neural networks.

Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3.

Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.

Task-selective place cells show behaviorally driven dynamics during learning and stability during memory recall.

Decades of work propose that hippocampal activity supports internal representation of learned experiences and contexts, allowing individuals to form long-term memories and quickly adapt behavior to changing environments. However, recent studies insinuate hippocampal representations can drift over time, raising the question: how could the hippocampus hold stable memories when activity of its neuronal maps fluctuates? We hypothesized that task-dependent hippocampal maps set by learning rules and structured attention stabilize as a function of behavioral performance. To test this, we imaged hippocampal CA1 pyramidal neurons during learning and memory recall phases of a new task where mice use odor cues to navigate between two reward zones. Across learning, both orthogonal and overlapping task-dependent place maps form rapidly, discriminating trial context with strong correlation to behavioral performance. Once formed, task-selective place maps show increased long-term stability during memory recall phases. We conclude that memory demand and attention stabilize hippocampal activity to maintain contextually rich spatial representations.

Assessing Local and Branch-specific Activity in Dendrites.

Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.

Linking hippocampal multiplexed tuning, Hebbian plasticity and navigation.

Three major pillars of hippocampal function are spatial navigation1, Hebbian synaptic plasticity2 and spatial selectivity3. The hippocampus is also implicated in episodic memory4, but the precise link between these four functions is missing. Here we report the multiplexed selectivity of dorsal CA1 neurons while rats performed a virtual navigation task using only distal visual cues5, similar to the standard water maze test of spatial memory1. Neural responses primarily encoded path distance from the start point and the head angle of rats, with a weak allocentric spatial component similar to that in primates but substantially weaker than in rodents in the real world. Often, the same cells multiplexed and encoded path distance, angle and allocentric position in a sequence, thus encoding a journey-specific episode. The strength of neural activity and tuning strongly correlated with performance, with a temporal relationship indicating neural responses influencing behaviour and vice versa. Consistent with computational models of associative and causal Hebbian learning6,7, neural responses showed increasing clustering8 and became better predictors of behaviourally relevant variables, with the average neurometric curves exceeding and converging to psychometric curves. Thus, hippocampal neurons multiplex and exhibit highly plastic, task- and experience-dependent tuning to path-centric and allocentric variables to form episodic sequences supporting navigation.

Dynamics of cortical dendritic membrane potential and spikes in freely behaving rats.

Neural activity in vivo is primarily measured using extracellular somatic spikes, which provide limited information about neural computation. Hence, it is necessary to record from neuronal dendrites, which can generate dendritic action potentials (DAPs) in vitro, which can profoundly influence neural computation and plasticity. We measured neocortical sub- and suprathreshold dendritic membrane potential (DMP) from putative distal-most dendrites using tetrodes in freely behaving rats over multiple days with a high degree of stability and submillisecond temporal resolution. DAP firing rates were several-fold larger than somatic rates. DAP rates were also modulated by subthreshold DMP fluctuations, which were far larger than DAP amplitude, indicating hybrid, analog-digital coding in the dendrites. Parietal DAP and DMP exhibited egocentric spatial maps comparable to pyramidal neurons. These results have important implications for neural coding and plasticity.

Causal Influence of Visual Cues on Hippocampal Directional Selectivity.

Hippocampal neurons show selectivity with respect to visual cues in primates, including humans, but this has never been found in rodents. To address this long-standing discrepancy, we measured hippocampal activity from rodents during real-world random foraging. Surprisingly, ∼ 25% of neurons exhibited significant directional modulation with respect to visual cues. To dissociate the contributions of visual and vestibular cues, we made similar measurements in virtual reality, in which only visual cues were informative. Here, we found significant directional modulation despite the severe loss of vestibular information, challenging prevailing theories of directionality. Changes in the amount of angular information in visual cues induced corresponding changes in head-directional modulation at the neuronal and population levels. Thus, visual cues are sufficient for-and play a predictable, causal role in-generating directionally selective hippocampal responses. These results dissociate hippocampal directional and spatial selectivity and bridge the gap between primate and rodent studies.

Impaired spatial selectivity and intact phase precession in two-dimensional virtual reality.

During real-world (RW) exploration, rodent hippocampal activity shows robust spatial selectivity, which is hypothesized to be governed largely by distal visual cues, although other sensory-motor cues also contribute. Indeed, hippocampal spatial selectivity is weak in primate and human studies that use only visual cues. To determine the contribution of distal visual cues only, we measured hippocampal activity from body-fixed rodents exploring a two-dimensional virtual reality (VR). Compared to that in RW, spatial selectivity was markedly reduced during random foraging and goal-directed tasks in VR. Instead we found small but significant selectivity to distance traveled. Despite impaired spatial selectivity in VR, most spikes occurred within ∼2-s-long hippocampal motifs in both RW and VR that had similar structure, including phase precession within motif fields. Selectivity to space and distance traveled were greatly enhanced in VR tasks with stereotypical trajectories. Thus, distal visual cues alone are insufficient to generate a robust hippocampal rate code for space but are sufficient for a temporal code.