Cell-type-specific manifold analysis discloses independent geometric transformations in the hippocampal spatial code.

Integrating analyses of genetically defined cell types with population-level approaches remains poorly explored. We investigated this question by focusing on hippocampal spatial maps and the contribution of two genetically defined pyramidal cell types in the deep and superficial CA1 sublayers. Using single- and dual-color miniscope imaging in mice running along a linear track, we found that population activity from these cells exhibited three-dimensional ring manifolds that encoded the animal position and running direction.

The role of electroencephalography in epilepsy research-From seizures to interictal activity and comorbidities.

Electroencephalography (EEG) has been instrumental in epilepsy research for the past century, both for basic and translational studies. Its contributions have advanced our understanding of epilepsy, shedding light on the pathophysiology and functional organization of epileptic networks, and the mechanisms underlying seizures. Here we re-examine the historical significance, ongoing relevance, and future trajectories of EEG in epilepsy research.

Brain oscillations: Hippocampal-prefrontal ripples unfolded.

Memory consolidation is the process of translating memory traces from the hippocampus to the cortex. Hippocampal ripples are key in driving this transfer. A new study now shows that independent cortical ripples can suppress this communication.

A machine learning toolbox for the analysis of sharp-wave ripples reveals common waveform features across species.

The study of sharp-wave ripples has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy is considered a biomarker of dysfunction. Sharp-wave ripples exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine-learning models for automatic detection and analysis of these events.

Immunohistochemical field parcellation of the human hippocampus along its antero-posterior axis.

The primate hippocampus includes the dentate gyrus, cornu ammonis (CA), and subiculum. CA is subdivided into four fields (CA1-CA3, plus CA3h/hilus of the dentate gyrus) with specific pyramidal cell morphology and connections. Work in non-human mammals has shown that hippocampal connectivity is precisely patterned both in the laminar and longitudinal axes.

Quantifying the distribution of feature values over data represented in arbitrary dimensional spaces.

Identifying the structured distribution (or lack thereof) of a given feature over a point cloud is a general research question. In the neuroscience field, this problem arises while investigating representations over neural manifolds (e.g.

Topological analysis of sharp-wave ripple waveforms reveals input mechanisms behind feature variations.

The reactivation of experience-based neural activity patterns in the hippocampus is crucial for learning and memory. These reactivation patterns and their associated sharp-wave ripples (SWRs) are highly variable. However, this variability is missed by commonly used spectral methods.

From cell types to population dynamics: Making hippocampal manifolds physiologically interpretable.

The study of the hippocampal code is gaining momentum. While the physiological approach targets the contribution of individual cells as determined by genetic, biophysical and circuit factors, the field pushes for a population dynamic approach that considers the representation of behavioural variables by a large number of neurons. In this alternative framework, neuronal activity is projected into low-dimensional manifolds.

A machine learning toolbox for the analysis of sharp-wave ripples reveal common features across species.

The study of sharp-wave ripples (SWRs) has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy and Alzheimer's disease is considered a biomarker of dysfunction. SWRs exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine learning (ML) models for automatic detection and analysis of SWRs.

Aberrant survival of hippocampal Cajal-Retzius cells leads to memory deficits, gamma rhythmopathies and susceptibility to seizures in adult mice.

Cajal-Retzius cells (CRs) are transient neurons, disappearing almost completely in the postnatal neocortex by programmed cell death (PCD), with a percentage surviving up to adulthood in the hippocampus. Here, we evaluate CR's role in the establishment of adult neuronal and cognitive function using a mouse model preventing Bax-dependent PCD. CRs abnormal survival resulted in impairment of hippocampus-dependent memory, associated in vivo with attenuated theta oscillations and enhanced gamma activity in the dorsal CA1.

A consensus statement on detection of hippocampal sharp wave ripples and differentiation from other fast oscillations.

Decades of rodent research have established the role of hippocampal sharp wave ripples (SPW-Rs) in consolidating and guiding experience. More recently, intracranial recordings in humans have suggested their role in episodic and semantic memory. Yet, common standards for recording, detection, and reporting do not exist.

Deep learning-based feature extraction for prediction and interpretation of sharp-wave ripples in the rodent hippocampus.

Local field potential (LFP) deflections and oscillations define hippocampal sharp-wave ripples (SWRs), one of the most synchronous events of the brain. SWRs reflect firing and synaptic current sequences emerging from cognitively relevant neuronal ensembles. While spectral analysis have permitted advances, the surge of ultra-dense recordings now call for new automatic detection strategies.

Inhibitory conductance controls place field dynamics in the hippocampus.

Hippocampal place cells receive a disparate collection of excitatory and inhibitory currents that endow them with spatially selective discharges and rhythmic activity. Using a combination of in vivo intracellular and extracellular recordings with opto/chemogenetic manipulations and computational modeling, we investigate the influence of inhibitory and excitatory inputs on CA1 pyramidal cell responses. At the cell bodies, inhibition leads and is stronger than excitation across the entire theta cycle.

Sex-specific regulation of inhibition and network activity by local aromatase in the mouse hippocampus.

Cognitive function relies on a balanced interplay between excitatory and inhibitory neurons (INs), but the impact of estradiol on IN function is not fully understood. Here, we characterize the regulation of hippocampal INs by aromatase, the enzyme responsible for estradiol synthesis, using a combination of molecular, genetic, functional and behavioral tools. The results show that CA1 parvalbumin-expressing INs (PV-INs) contribute to brain estradiol synthesis.

Holographic Manipulation of Nanostructured Fiber Optics Enables Spatially-Resolved, Reconfigurable Optical Control of Plasmonic Local Field Enhancement and SERS.

Integration of plasmonic structures on step-index optical fibers is attracting interest for both applications and fundamental studies. However, the possibility to dynamically control the coupling between the guided light fields and the plasmonic resonances is hindered by the turbidity of light propagation in multimode fibers (MMFs). This pivotal point strongly limits the range of studies that can benefit from nanostructured fiber optics.

A protocol to extract cell-type-specific signatures from differentially expressed genes in bulk-tissue RNA-seq.

Bulk-tissue RNA-seq is widely used to dissect variation in gene expression levels across tissues and under different experimental conditions. Here, we introduce a protocol that leverages existing single-cell expression data to deconvolve patterns of cell-type-specific gene expression in differentially expressed gene lists from highly heterogeneous tissue. We apply this protocol to interrogate cell-type-specific gene expression and variation in cell type composition between the distinct sublayers of the hippocampal CA1 region of the brain in a rodent model of epilepsy.

Explorers of the cells: Toward cross-platform knowledge integration to evaluate neuronal function.

In this issue of Neuron, Petersen et al. (2021) introduce CellExplorer, an open-source tool to integrate neurophysiological metrics of neuronal activity from circuits to behavior. Together with other neuroinformatic resources, it may facilitate community-based multidisciplinary characterization of brain cell types.

The continued need for animals to advance brain research.

Policymakers aim to move toward animal-free alternatives for scientific research and have introduced very strict regulations for animal research. We argue that, for neuroscience research, until viable and translational alternatives become available and the value of these alternatives has been proven, the use of animals should not be compromised.

Sublayer- and cell-type-specific neurodegenerative transcriptional trajectories in hippocampal sclerosis.

Hippocampal sclerosis, the major neuropathological hallmark of temporal lobe epilepsy, is characterized by different patterns of neuronal loss. The mechanisms of cell-type-specific vulnerability and their progression and histopathological classification remain controversial. Using single-cell electrophysiology in vivo and immediate-early gene expression, we reveal that superficial CA1 pyramidal neurons are overactive in epileptic rodents.

An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo.

Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal-hippocampal function, but data are dispersed and diverse.

Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations.

Theta oscillations play a major role in temporarily defining the hippocampal rate code by translating behavioral sequences into neuronal representations. However, mechanisms constraining phase timing and cell-type-specific phase preference are unknown. Here, we employ computational models tuned with evolutionary algorithms to evaluate phase preference of individual CA1 pyramidal cells recorded in mice and rats not engaged in any particular memory task.