Hippocampus

…subcortical white matter, ventricles, hippocampus, fornix, basal ganglia and thalamus, with further exploration of the brainstem and cerebellum. Traditional blunt dissection reveals major pathways, while axial, sagittal and coronal MRI comparisons connect anatomy to imaging. Consolidation and self-assessment sessions help participants test their recognition of structures. Live online via Zoom

…and neurogenic changes in the human hippocampus involving microglia, astrocytes and immature neurons. The candidate runs single-nucleus RNA sequencing pipelines on postmorte

…uses the history of research on the hippocampus to illustrate both ideas: the hippocampus has two parallel research histories, one treating it as the seat

Nick Turk-Browne presents research using infant functional MRI to investigate how the hippocampus supports learning and memory early in life. The seminar connects neural development, memory formation and infantile amnesia through new methods for studying awake infants.

Daniel Levenstein discusses spontaneous activity in the hippocampus and cortex, especially during sleep, and its relationship to learning, memory and navigation. He explains how AI models can help investigate these dynamics, alongside questions about model systems, cognitive maps and the relationship between neuroscience experiments and theory.

Much is known about the neural representations of current environmental location and direction within the hippocampal formation, but use of such a “cognitive map” requires the online representation of desired locations and how to get there, and the neural basis for this function has been more elusive. I will discuss how “theta sweeps” of place and grid cell firing encode the current location (at early phases of each theta cycle) while, at later phases, sampling around the forward direction during exploration and indicating the direction to desired locations during goal-directed navigation. I w

The hippocampus is thought to build a cognitive map that supports navigation, memory, and planning, but what defines such a map and how it is used remain debated. In this talk, I will present computational models in which hippocampal-like representations emerge in recurrent neural networks trained to predict sequences of sensory observations. While spatially tuned units reliably arise, they are not sufficient to form a cognitive map. Instead, map-like representations emerge when recurrent dynamics support multi-step prediction, yielding a population-level encoding of environmental geometry. On

…Learning Systems, with the hippocampus rapidly encoding individual episodes and the neocortex slowly extracting regularities over days, months, and years. But this do

The human medial temporal lobe contains neurons that respond selectively to the semantic contents of a presented stimulus. These "concept cells" may respond to very different pictures of a given person and even to their written or spoken name. Their response latency is far longer than necessary for object recognition, they follow subjective, conscious perception, and they are found in brain regions that are crucial for declarative memory formation. It has thus been hypothesized that they may represent the semantic "building blocks" of episodic memories. In this talk I will present data from

…Chickadee hippocampus produces sparse, high-dimensional patterns ("barcodes") that uniquely specify each caching event. Unexpectedly, the same neurons that participate in barcodes als

The canonical model of the dentate gyrus (DG) of the hippocampus suggests the DG performs pattern separation, orthogonalizing similar input patterns [1, 2] aided by an approximate 5-fold expansion of the cell population relative to its entorhinal cortex inputs [3]. However, more recent experimental results challenge this standard model, suggesting the DG also supports the precise binding of objects and events to space and the integration of information across episodes [4]. Very recent studies attribute pattern separation and pattern integration to anatomically distinct parts of the DG, the sup

…The hippocampus, a key brain region for these maps, exhibits neural population activity that often evolves along nonlinear, low-dimensional manifolds. While cognitive maps have been characterized at the level of cell tunings to spatial location and decorrelations over time, a precise, unsupervised, and quantitative model of how this map forms and morphs at the population level remains elusive due to the large dimensionality and nonlinearity of neural activity. Current dimensionality reduction t

…[e.g., medial entorhinal cortex (MEC), hippocampus] encode the self's position and trajectory. However, it has only recently been discovered that MEC and hippocampus are modulated by the positions and trajectories of others. To understand how encoding spatial information of multiple agents shapes neural representations, we train

…maps have been observed in the hippocampus, but their algorithmic form and the processes by which they are learned remain obscure. We employed large-scale, longitudinal two-photon calcium imaging to record activity from thousands of neurons in the CA1 region of the hippocampus while mice learned to efficiently collect rewards from two subtly different linear tracks in virtual reality. The results provide a de

The hippocampus is widely known for spatially-selective responses in individual cells. However, many of its cells do not have easily-interpretable spatial tuning curves or are selective for other task-relevant variables. To better understand the computations played by this structure, it may be necessary to look to population-level features of neural activity and the distributed computations they enable. Here, we focus on two such features: 1) a continuous neural manifold that maps spatial and task structure, 2) spatial representations that “sweep” ahead of the animal as it moves through the en

The hippocampus is a key player in learning and memory. However, the microcircuit logic that endows the hippocampus with these capabilities remains virtually unknown. Hippocampal neurons exhibit tremendous diversity in terms of their gene expression, connectivity, and intrinsic properties. Recent work suggests that this diversity is rooted in the temporal progression of embryonic development, with neurons born at the same gestational timepoint exhibiting shared input and output connectivity, as well as correlated activity in-vivo. In this work, we combined embryonic birthdating of CA3-CA1 neur

Animals can learn to repeat actions that lead to rewards (model-free learning). However, animals can also learn about environmental structure without receiving immediate and explicit rewards (latent learning), and then use this knowledge to guide future reward-seeking behavior efficiently. How the brain accomplishes this is not clear, in part due to limitations in existing behavioral tasks to study latent learning in rodents. In particular, traditional latent learning tasks suffer from their “one-shot” characteristics, such that learning is typically performed and tested in one environment, pr

Hippocampus in mammals is hypothesized to support formation of episodic memory. Bedrock of this is based on the evidence of functional cell types related to immediate space, such as place cells. We aimed to test whether hippocampus, known for supporting spatial maps in physical environments, can localize the source of remote auditory signal and rewards associated with its spatial position. Given previous evidence for auditory sensitivity in the hippocampus [1-2], we recorded extracellular electrophysiological activity from auditory cortex and intermediate-ventral hippocampus simultaneously, us

Abstraction and generalization are essential for flexible decision-making in novel situations. Recent work in humans and monkeys has shown how abstract variables are encoded by the representational geometry of single-neuron population activity in a format that supports generalization. However, these observations typically are made after learning has converged, leaving open the question of how these representations form. We designed the present study to tackle this question. We developed a factorized model of temporal abstraction that builds on the successor representation and is motivated by r

…focusing on the role of the hippocampus in this unsupervised learning process. The study leverages a novel comparative behavioural paradigm, termed X-detection, to manipulate the statistics of embedded tone sequences (patterns) in an auditory cover task: subjects s

Hippocampus and primary visual cortex (V1) have been shown to represent self-location in a coordinated manner during navigation. Moreover, during rest, spatially-modulated cells in the hippocampus are known to replay past trajectories. These recapitulations of previous experiences are proposed to spread across cortical areas, constituting a hallmark of system-level consolidation theories and providing clear predictions about how hippocampus and cortex coordinate during sleep. We aimed to test these predictions by answering the following questions: 1) Can replay be detected in V1 during sleep?

…in structural learning is the hippocampus. Specifically, neurons in the CA1 area of the hippocampus have been shown to represent variables such as cue configurations and their order in space and time. To investigate the

The centre of memory is the medial temporal lobe (MTL) and especially the hippocampus. In our research, a more flexible brain-inspired computational microcircuit of the CA1 region of the mammalian hippocampus was upgraded and used to examine how information retrieval could be affected under different conditions. Six models (1-6) were created by modulating different excitatory and inhibitory pathways. The results showed that the increase in the strength of the feedforward excitation was the most effective way to recall memories. In other words, that allows the system to access stored memories m

The hippocampus is presumably involved in spatial navigation, the formation of long-term memories in mammals, and the construction of a cognitive map of space using a prominent feature – place cells [1] (PCs). It is unclear how PCs’ neural codes are related to memory: turnover of neural representations could be involved in learning, while codes’ stability may support long-term storage and retrieval of memories [2]. In this work, we focus on the analysis of one-photon (1P) calcium imaging data recorded from mouse CA1 during free foraging in a two-dimensional arena with the help of a miniature