Action-driven remapping of hippocampal neuronal populations in jumping rats

Diversity of omission responses to visual images across brain-wide regions

An organism's survival depends on its ability to anticipate forthcoming events and detect discrepancies between the expected and actual sensory inputs. We analyzed data from mice performing a visual go/no-go change-detection task where the sequence of stimulus presentations was intermittently interrupted by omission of a stimulus. The omission of a visual stimulus did not elicit discernable spiking responses in visual cortical neurons. Instead, firing rates between image presentations, including the omission period, ramped linearly and without interruption at the time of the omitted image. Several neuron types in visual cortex neurons were identified with various responses to images and their omissions. A minority of cells in nonvisual areas, including the hippocampus, increased their firing rates at the omitted stimulus onset even when these neurons did not respond to the images. Our study elucidates the origin of omission responses in the visual cortex and sheds light on the role of hippocampal and subcortical circuits in omission detection.

ThermoMaze behavioral paradigm for assessing immobility-related brain events in rodents

Brain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organism's responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animal's natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, we observed that mice avoided the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of mice. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions, and open new options for studying behavior-mediated temperature homeostasis.

Hippocampal neuronal activity is aligned with action plans

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards and actions, in which the extent of tuning depends on ongoing task demands1-8. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or whether a more generic computation can account for these observations9. Here, to disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice in which space, auditory tones, rewards and context were juxtaposed with changing relevance. High-density electrophysiological recordings revealed that neurons were tuned to each of these modalities. By comparing movement paths and action sequences, we observed that external variables had limited direct influence on hippocampal firing. Instead, spiking was influenced by online action plans and modulated by goal uncertainty. Our results suggest that internally generated cell assembly sequences are selected and updated by action plans towards deliberate goals. The apparent tuning of hippocampal neuronal spiking to different sensory modalities might emerge due to alignment to the afforded action progression within a task rather than representation of external cues.

Hippocampal neuronal activity is aligned with action plans

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards, and actions, where the extent of tuning depends on ongoing task demands. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or if a more generic computation can account for these observations. To disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice where space, auditory tones, rewards, and context were juxtaposed with changing relevance. High-density electrophysiological recordings revealed that neurons were tuned to each of these modalities. By comparing movement paths and action sequences, we observed that external variables had limited direct influence on hippocampal firing. Instead, spiking was influenced by online action plans modulated by goal uncertainty. Our results suggest that internally generated cell assembly sequences are selected and updated by action plans toward deliberate goals. The apparent tuning of hippocampal neuronal spiking to different sensory modalities might emerge due to alignment to the afforded action progression within a task rather than representation of external cues.

Remapping revisited: how the hippocampus represents different spaces

The representation of distinct spaces by hippocampal place cells has been linked to changes in their place fields (the locations in the environment where the place cells discharge strongly), a phenomenon that has been termed 'remapping'. Remapping has been assumed to be accompanied by the reorganization of subsecond cofiring relationships among the place cells, potentially maximizing hippocampal information coding capacity. However, several observations challenge this standard view. For example, place cells exhibit mixed selectivity, encode non-positional variables, can have multiple place fields and exhibit unreliable discharge in fixed environments. Furthermore, recent evidence suggests that, when measured at subsecond timescales, the moment-to-moment cofiring of a pair of cells in one environment is remarkably similar in another environment, despite remapping. Here, I propose that remapping is a misnomer for the changes in place fields across environments and suggest instead that internally organized manifold representations of hippocampal activity are actively registered to different environments to enable navigation, promote memory and organize knowledge.

ThermoMaze: A behavioral paradigm for readout of immobility-related brain events

Brain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organism's responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animal's natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, mice avoid the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of the animal. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions and open new options for studying behavior-mediated temperature homeostasis.

Barcoding of episodic memories in the hippocampus of a food-caching bird

The hippocampus is critical for episodic memory. Although hippocampal activity represents place and other behaviorally relevant variables, it is unclear how it encodes numerous memories of specific events in life. To study episodic coding, we leveraged the specialized behavior of chickadees-food-caching birds that form memories at well-defined moments in time whenever they cache food for subsequent retrieval. Our recordings during caching revealed very sparse, transient barcode-like patterns of firing across hippocampal neurons. Each "barcode" uniquely represented a caching event and transiently reactivated during the retrieval of that specific cache. Barcodes co-occurred with the conventional activity of place cells but were uncorrelated even for nearby cache locations that had similar place codes. We propose that animals recall episodic memories by reactivating hippocampal barcodes. Similarly to computer hash codes, these patterns assign unique identifiers to different events and could be a mechanism for rapid formation and storage of many non-interfering memories.

Local prediction-learning in high-dimensional spaces enables neural networks to plan

Planning and problem solving are cornerstones of higher brain function. But we do not know how the brain does that. We show that learning of a suitable cognitive map of the problem space suffices. Furthermore, this can be reduced to learning to predict the next observation through local synaptic plasticity. Importantly, the resulting cognitive map encodes relations between actions and observations, and its emergent high-dimensional geometry provides a sense of direction for reaching distant goals. This quasi-Euclidean sense of direction provides a simple heuristic for online planning that works almost as well as the best offline planning algorithms from AI. If the problem space is a physical space, this method automatically extracts structural regularities from the sequence of observations that it receives so that it can generalize to unseen parts. This speeds up learning of navigation in 2D mazes and the locomotion with complex actuator systems, such as legged bodies. The cognitive map learner that we propose does not require a teacher, similar to self-attention networks (Transformers). But in contrast to Transformers, it does not require backpropagation of errors or very large datasets for learning. Hence it provides a blue-print for future energy-efficient neuromorphic hardware that acquires advanced cognitive capabilities through autonomous on-chip learning.

The bumpy road ahead: the role of substrate roughness on animal walking and a proposed comparative metric

Outside laboratory conditions and human-made structures, animals rarely encounter flat surfaces. Instead, natural substrates are uneven surfaces with height variation that ranges from the microscopic scale to the macroscopic scale. For walking animals (which we define as encompassing any form of legged movement across the ground, such as walking, running, galloping, etc.), such substrate 'roughness' influences locomotion in a multitude of ways across scales, from roughness that influences how each toe or foot contacts the ground, to larger obstacles that animals must move over or navigate around. Historically, the unpredictability and variability of natural environments has limited the ability to collect data on animal walking biomechanics. However, recent technical advances, such as more sensitive and portable cameras, biologgers, laboratory tools to fabricate rough terrain, as well as the ability to efficiently store and analyze large variable datasets, have expanded the opportunity to study how animals move under naturalistic conditions. As more researchers endeavor to assess walking over rough terrain, we lack a consistent approach to quantifying roughness and contextualizing these findings. This Review summarizes existing literature that examines non-human animals walking on rough terrain and presents a metric for characterizing the relative substrate roughness compared with animal size. This framework can be applied across terrain and body scales, facilitating direct comparisons of walking over rough surfaces in animals ranging in size from ants to elephants.