Closed-loop modulation of remote hippocampal representations with neural feedback
Humans can remember specific remote events without acting on them and influence which memories are retrieved based on internal goals. However, animal models typically present sensory cues to trigger memory retrieval and then assess retrieval based on action. Thus, it is difficult to determine whether measured neural activity patterns relate to the cue(s), the memory, or the behavior. Therefore, in Coulter et al., 2025, we asked whether retrieval-related neural activity could be generated in animals without cues or a behavioral report. We focused on hippocampal "place cells," which primarily represent the animal's current location (local representations) but can also represent locations away from the animal (remote representations). We developed a neurofeedback system to reward expression of remote representations and found that rats could learn to generate specific spatial representations that often jumped directly to the experimenter-defined target location. Thus, animals can deliberately engage remote representations, enabling direct study of retrieval-related activity in the brain.
Dynamic synchronization between hippocampal representations and stepping
The hippocampus is a mammalian brain structure that expresses spatial representations and is crucial for navigation. Navigation, in turn, intricately depends on locomotion; however, current accounts suggest a dissociation between hippocampal spatial representations and the details of locomotor processes. Specifically, the hippocampus is thought to represent mainly higher-order cognitive and locomotor variables such as position, speed and direction of movement, whereas the limb movements that propel the animal can be computed and represented primarily in subcortical circuits, including the spinal cord, brainstem and cerebellum. Whether hippocampal representations are actually decoupled from the detailed structure of locomotor processes remains unknown. To address this question, in Joshi et al., 2023, we simultaneously monitored hippocampal spatial representations and ongoing limb movements underlying locomotion at fast timescales. We found that the forelimb stepping cycle in freely behaving rats is rhythmic and peaks at around 8 Hz during movement, matching the approximately 8 Hz modulation of hippocampal activity and spatial representations during locomotion. We also discovered precisely timed coordination between the time at which the forelimbs touch the ground ('plant' times of the stepping cycle) and the hippocampal representation of space. Notably, plant times coincide with hippocampal representations that are closest to the actual position of the nose of the rat, whereas between these plant times, the hippocampal representation progresses towards possible future locations. This synchronization was specifically detectable when rats approached spatial decisions. Together, our results reveal a profound and dynamic coordination on a timescale of tens of milliseconds between central cognitive representations and peripheral motor processes. This coordination engages and disengages rapidly in association with cognitive demands and is well suited to support rapid information exchange between cognitive and sensory-motor circuits.
Hippocampal replay reflects specific past experiences rather than a plan for subsequent choice
Executing memory-guided behavior requires storage of information about experience and later recall of that information to inform choices. Awake hippocampal replay, when hippocampal neural ensembles briefly reactivate a representation related to prior experience, has been proposed to critically contribute to these memory-related processes. However, it remains unclear whether awake replay contributes to memory function by promoting the storage of past experiences, facilitating planning based on evaluation of those experiences, or both. In Gillespie et al., (2021), we designed a dynamic spatial task that promotes replay before a memory-based choice and assessed how the content of replay related to past and future behavior. We found that replay content was decoupled from subsequent choice and instead was enriched for representations of previously rewarded locations and places that had not been visited recently, indicating a role in memory storage rather than in directly guiding subsequent behavior.
"Constant cycling" of hippocampal activity encoding mutually exclusive hypotheticals
Cognitive abilities such as planning, imagination, and decision-making depend on the brain’s ability to represent hypothetical, rather than actual, experience. Despite this critical insight, the neurobiology underlying hypothetical representation remained poorly understood. In Kay et al., (2020), we report the discovery that hippocampal neural activity encoding mutually exclusive hypotheticals – here, divergent future paths in a maze – can alternate between hypotheticals every ~125 ms (8 Hz); a pattern we termed “constant cycling.” This finding establishes that neural representation of hypotheticals can have remarkable temporal organization: a combination of rapid expression (<1 s) and regularity (constant operation over successive 8 Hz cycles). We further found that cycle-to-cycle switching is most strongly expressed in specific hippocampal sub-regions, indicating that neural representation of hypotheticals has discrete structural organization within the hippocampus. Lastly, we found that constant cycling generalizes across multiple representations: constant cycling occurs not only for representations of position but also for representations of heading direction, a classical correlate of hippocampal activity that was first established more than 25 years ago. This raises the intriguing possibility that the brain uses a common mechanism to generate other types of hypotheticals, not only those of location or direction. Our findings also raise the possibility that neural processes that evaluate and choose among different possible futures in fact operate at the sub-second timescale, in contrast to the seconds-long timescale traditionally studied in decision-making. We are actively pursuing this possibility in current work. We believe that the wider scientific impact of our results will be to shift the study of complex cognition to short timescales and to shift focus to the brain’s capacity to generate representations of possible (vs. actual) experience.
Dinstinct hippocampal-nucleus accumbens networks support distinct cognitive functions
The hippocampus is critical for storing and then retrieving memories for the events of daily life. This process engages many other structures outside the hippocampus, but whether different parts of the hippocampus act together or separately to engage these structures was not clear. Specifically, the dorsal-ventral axis of the rodent hippocampus is associated with profound differences in gene expression and anatomical connectivity, but how those differences might translate into different patterns of engagement with other structures was not known. In Sosa, Joo, and Frank (2020) we addressed this question in the context of hippocampal interactions with the nucleus accumbens (NAc). Previous work using artificial stimulation or inactivation separately implicated either dorsal hippocampal (dHPC) or ventral hippocampal (vHPC) input to the NAc in linking spatial information to reward. These disparate results made it impossible to know whether one or both pathways were actually engaged during as animals navigated to rewarded locations. We recorded simultaneously from dHPC, vHPC, and NAc and used hippocampal sharp-wave ripples (SWRs) (markers of memory reactivation) to identify times of inter-regional information processing. We found that many NAc neurons are modulated at the times of SWRs, but that dHPC SWRs and vHPC SWRs occur at different times and engage distinct networks of neurons in the NAc. Further, we showed that only the NAc network associated with the dHPC encodes information relevant to reward and the traversal of spatial paths in an appetitive task. The NAc neurons associated with the dHPC also showed similar firing across different paths, suggesting generalization across experiences. Our results suggest that dHPC and vHPC and their associated downstream NAc neuronal networks support distinct cognitive functions, with the dHPC primarily engaged in spatial-reward learning. The opposition we observe between these networks during SWRs may support the encoding and recall of distinct aspects of experience at different times.
High density, long-term recordings in multiple brain areas
Brain functions engage activity across distributed networks of neurons spanning multiple brain structures. A critical barrier to understanding these brain functions, which include memory formation and memory-guided decision making, was the lack of tools capable of measuring millisecond timescale patterns of neural activity across these networks. Specifically, the available electrophysiological technologies were limited in their ability to access large numbers of neurons across multiple brain regions and to do so over the extended time scales (weeks to months) that characterize memory processes. We therefore developed a new methodology that overcomes these limitations. Our system uses electrode arrays fabricated of polyimide, a flexible and biocompatible substrate. These arrays are integrated with a modular headstage that supports up to 1024 recording channels in freely behaving rats. With this system we were able to carry out simultaneous recordings from hundreds of single units (putative single neurons) across a set of a spatially distributed brain regions (medial prefrontal cortex, orbitofrontal cortex, and nucleus accumbens). Our technology also allows very long-lasting, high-quality recordings (over 160 days), continuous recordings (24 hours/day, 7 days a week), and exceptional stability, allowing us to measure spiking activity from large numbers of individual units (247 of 1150 measured) for at least a week. This technology has enabled studies in my laboratory where, for the first time, we can measure the activity of many hundreds of neurons from multiple brain structures as animals learn and perform memory-guided behaviors across days, weeks, and months (Chung et al., 2018). We are also working to distribute this technology to the community. Finally, I note that this technology is complementary to the HHMI/Welcomme/IMEC Neuropixels arrays, in that it permits much closer spacing of recording devices and produces much more stable recordings in freely behaving animals.
A hippocampal-cortical loop of information flow during sleep sharp-wave ripple events
Hippocampal replay during sharp-wave ripple events (SWRs) is thought to drive memory consolidation in hippocampal and cortical circuits. This is most often discussed as a process whereby the hippocampus replays memories to drive neocortical activity patterns that would reinforce a distributed memory representation. Here we asked whether that description is accurate. Specifically, previous work had shown that changes in neocortical activity can precede SWR events, but whether and how these changes influence the content of replay was not clear. In Rothschild et. al. (2017), we showed that during sleep there is actually a rapid cortical–hippocampal–cortical loop of information flow around the times of SWRs. We recorded neural activity in auditory cortex (AC) and hippocampus of rats as they learned a sound-guided task and during sleep. We found that patterned activation in AC precedes and predicts the subsequent content of hippocampal activity during SWRs, while hippocampal patterns during SWRs predict subsequent AC activity. Delivering sounds during sleep biased AC activity patterns, and sound-biased AC patterns predicted subsequent hippocampal activity. These findings provide a potential mechanism to explain observations from other laboratories that stimuli presented during sleep can enhance subsequent task performance. These results also suggest that activation of specific cortical representations during sleep influences the identity of the memories that are consolidated into long-term stores. We hypothesize that coordinated reactivation across sensory cortical regions immediately preceding SWRs facilitates a flow of reactivated sensory information into the hippocampus. This incoming information biases hippocampal reactivation, which then broadcasts an integrated representation back to the reactivated cortical networks, linking the patterns of activity across multiple cortical areas to consolidate a coherent memory representation.
Coordinated hippocampal-prefrontal reactivation during awake sharp-wave ripple events
If, as we have hypothesized, awake SWRs could support memory processes like retrieval or consolidation, they should engage a broad network of areas that are involved in representing different aspects of a memory. In Jadhav, Rothschild et. al. (2016) we asked whether that was the case by carrying out dual site recordings from hippocampus and medial prefrontal cortex (mPFC) in animals learning spatial tasks. We found that a surprisingly large proportion of mPFC cells showed spiking modulation during SWRs (~35%). Unlike in hippocampal area CA1, however, SWR-related activity in PFC comprised both excitation and inhibition of distinct populations. Within individual SWRs, excitation activated PFC cells with representations related to the concurrently reactivated hippocampal representation, while inhibition suppressed PFC cells with unrelated representations. These findings demonstrate that awake SWRs mark times of strong coordination between hippocampus and PFC that reflects structured reactivation of representations related to ongoing experience. More broadly, the patterns of excitation and inhibition in the mPFC during SWRs suggested that upon the initiation of an SWR, the representation in PFC related to the current state can be suppressed and replaced with a representation of recent active behavior consistent with the representation reactivated in the hippocampus. In conjunction with our observation described above that a similar pattern of suppression is seen in CA2 cells, we hypothesize that this could be important maintaining the separation between current experience and retrieved memories.
A hippocampal network for spatial location during immobility and sleep
Previous studies of hippocampal place representations have focused largely on the spatially specific activity seen when animals are moving from place to place. Normal behavior involves both movement as well as periods of immobility, leading us to ask the question “how does an animal know where it is when it stops moving?” In Kay et. al. (2016), we examined patterns of neural activity across multiple hippocampal subregions and identified a population of cells in area CA2 that preferentially encoded current location during periods of immobility. Interestingly, these cells, unlike all other previously identified principle cells in the hippocampus, are inhibited during the sharp-wave ripple events where we see memory replay. As a result, these cells come on as animals slow down and approach a stopping point. Their activity then continues, but is transiently interrupted by SWRs, indicating that the representation of current location is suppressed during memory replay events. We also saw this same sort of suppression in the prefrontal cortex (see below). We also identified a low frequency (~1-4 Hz) local field potential event that is associated with the activity of these CA2 cells, and using that event as a probe, we found a set of cells in other hippocampal subregions that also maintain a representation of current location during immobility. Further, these representations of current location resurfaced during sleep, specifically in a sleep phase known as SIA. These findings indicate that the hippocampal place code is maintained across states, and suggest that there are rapid alternations between representations of current experiences and replay related to past experiences.