Ivan Fernandez-Lamo’s research while affiliated with Cajal Institute and other places

What is this page?


This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.

Publications (10)


Figure 1. Differential responses of CA1 pyramidal cells during epileptiform activities (A) Intracellular and multi-site local field potential (LFP) recordings from epileptic rats. Cells were identified with streptavidin and tested against Calbindin. Scale bar, 100 mm. SO, stratum oriens; SP, stratum pyramidale; SR; stratum radiatum. (B) Intracellular activity during IID at different membrane potentials (gray traces). Traces are aligned by the peak of IID recorded at the SR. HFOs were recorded at the SP. (C) Responses of the cell shown in (A) during SPW fast ripples. (D) Deviation from the resting membrane potential (RMP) recorded in individual cells during IIDs (n = 12 cells). Red colors reflect depolarization and blue hyperpolarization. Cells are ranked by their distance to the SR and classified as deep and superficial (Sup) (subplot at right). The discontinuous line marks sublayer limits. (E) Same as in D for SPW-fast ripples (n = 19 cells). (F) Mean membrane potential responses around IID events showed differences between deep and Sup cells (Friedman c 2 [1,333] = 28.7, p < 0.001). Data are from 6 deep and 6 Sup CA1 pyramidal cells. (G) Same as in (G) for SPW fast ripple events. Note the larger after-event depolarization in Sup cells (Friedman c 2 [1,333] = 14.67, p < 0.0001). Data are from 8 deep and 11 Sup CA1 pyramidal cells. (H) cFos immunoreactivity in representative CA1 sections from one rat exhibiting bilateral forelimb clonus after sound stimulation (seizure) versus a non-stimulated epileptic rat with no observed seizure (basal). Scale bar, 80 mm. (I) Intensity of c-Fos from all pyramidal cells in one confocal section per rat (small dots) and mean data per animal (larger dots). Significant interaction was confirmed for animals between groups and sublayers (p = 0.0044; n = 4 epileptic basal, n = 3 epileptic seizures). Post hoc differences: *p < 0.05. (J) Schematic of electrophysiological and histopathological findings.
Figure 2. Bulk tissue gene expression profiling of the epileptic hippocampal area CA1 reveals regionalized transcriptional response (A) Representative laser capture microdissection (LCM) sampling of the Sup CA1 sublayer. Scale bar, 100 mm. (B) Heatmaps of DEGs in deep (left) and Sup CA1 sublayers (right) in three replicates from control (C) and epileptic (E) rats (FC > 0.5, adj. p < 0.01). Arrowheads point to bona fide gene markers of Sup (Calb1, Grm1, and Syt17) and deep (Ndst4 and Nr4a2) pyramidal neurons. Note the presence of gene markers for interneurons (e.g., Vip, Sst, Sema3c, and Kit) and oligodendrocytes (Plp1, Mbp, Mobp, Mal, Enpp2, Cldn11, and Ermn). (C) Scatterplot of DEGs between Sup and deep CA1 sublayers in control or epileptic rats (FC > 0.5, adj. p < 0.01). Bona fide gene markers of Sup (Calb1, Grm1, and Syt17) and deep (Ndst4, Nr4a2, and Col11a1) pyramidal neurons are highlighted (black text and bold font). Also shown are marker genes for interneurons (Sst, Vip, and Kit), oligodendrocytes (Mbp, Mobp, and Plp1), astrocytes (Aqp4 and Gja1), and microglia (Tgfbr1). Note the presence of a subset of uncorrelated transcripts, including canonical markers of microglia cells (Trem2, Irf8, Fcgr2b, and Cd68), at the Sup sublayer in epileptic rats (red). MLE, maximum-likelihood estimate. (D) MA plots showing epilepsy-associated significantly upregulated (red) and downregulated (blue) genes in deep and Sup CA1 sublayers (FC > 0.5, adj. p < 0.01) (left). Venn diagrams show the overlap of upregulated (top) and downregulated (bottom) genes between epileptic and control in Sup and deep sublayers of CA1. (E) GO analysis of the top 250 upregulated and downregulated genes in deep and Sup sublayers in epilepsy (adj. p < 0.1 and then ranked by FC).
Figure 3. Microglia subpopulations underlie the transcriptional signature of Sup CA1 in epilepsy (A and B) Subpopulation signatures inferred by deconvolution of bulk tissue transcriptome profiles. Gene sets were the top 250 DEGs between Sup and deep CA1 sublayers in epileptic and control rats (as indicated) identified in bulk tissue RNA-seq. For the selected genes, normalized expression was retrieved from publicly available scRNA-seq data from the mouse CA1 hippocampal region (Zeisel et al., 2015) (A) or the Allen Brain Map portal (Mouse Whole Cortex and Hippocampus SMART-seq [2019] with 10x-SMART-seq taxonomy [2020]) (B), and single cells were summarized by linear dimensionality reduction using principal-component (legend continued on next page)
Figure 4. Hippocampal sclerosis is sublayer and cell type specific (A) Immunostaining against the CA1 marker Wfs1 co-localized with Calb at proximal, intermediate, and distal segments in control and epileptic rats. Scale bar, 50 mm. (B) CA1 linear cell density confirmed neuronal loss affecting mainly Calb+ cells. Data are from 10 control and 10 kainate-treated epileptic rats (1 section per rat, À3.2 to À4.8 mm from the bregma, 203). Significant 3-way ANOVA for group (F1,120) = 32.6, p < 0.0001; proximodistal (F(2,120) = 11.7, p < 0.0001) and sublayer (F(1,120) = 424,1; p < 0.0001). Post hoc Tukey test: **p < 0.01, ***p < 0.005. Scale bar, 50 mm. (C) Hippocampal sections from representative control and epileptic transgenic (TG) mice expressing G-GaMP7-DsRed2 in CalbÀ deep Pyrs. (D) Linear density data from 3 control and 5 epileptic TG mice (1 section per mouse at 203). Significant 3-way ANOVA for groups (F(1,36) = 7.8, p = 0.008) and sublayers (F(1,36) = 8.9, p = 0.0051), no proximodistal effect. Post hoc t test: **p < 0.01, ***p < 0.005. (E) Left: experimental timeline. Right: mean density of Calb+ and CalbÀ CA1 Pyrs as a function of time fitted by linear trends. Data are from 10 control, 10 epileptic (kainate), and 5 epileptic (lithium-pilocarpine) rats. Arrowheads point to a lithium-pilocarpine rat with full cell loss in CA1 10 weeks after status. (F) CA1 mean cell loss in rats quantified as deep versus Sup using Wfs1. Sup CA1 cells are more affected than deep cells. Significant effect for group in a 2-way ANOVA, F(2,48) = 5.9, p = 0.005. Post hoc unpaired t test: *p < 0.01, **p < 0.01. (G) Fluoro-Jade signal co-localized with Wfs1 and quantification of Fluoro-Jade+ cells across sublayers; n = 8 epileptic rats. Paired t test, *p < 0.01. Scale bar, 40 mm. (H) Density of deep (CalbÀ, left) and Sup (Calb+, right) Pyrs against the density of Micros (Iba1+) counted at deep and Sup sublayers (data are from 6 epileptic rats). Significant Spearman decreasing monotonic trend only for Sup cells (r = À0.87, p = 0.0236). (I) Schematic of epilepsy-associated histopathological findings indicating larger neuronal loss (blue ramp) and increased Micro cells (red) in the Sup sublayer.
Figure 5. snRNA-seq profiling of the normal and epileptic CA1 area (A) Nuclei were isolated from the CA1 region of adult mice and purified by flow cytometry for single-nucleus RNA-seq (snRNA-seq). (B) Uniform manifold approximation and projection (UMAP) plots of CA1 Pyrs subtypes segregated by condition (control and epileptic). Pyr_ES, epilepsy specific. (C) Heatmap showing normalized expression for principal gene markers for deep and Sup neurons in control and epileptic mice (96 enriched genes: 62 deep, 34 Sup; absolute log FC > 0.25; min.pct = 0.5; adj. p < 10 À30 ). Note the presence of a subset of cells with differential gene expression corresponding to the Pyr_ES cell population (green). (D) Significantly enriched genes in Sup and deep CA1 neurons in control mice and their relative level of enrichment in epileptic animals (adj. p < 0.05, 493 genes). Gene expression levels of CA1 neuronal subtype-specific enriched genes are preserved in epilepsy. (E) Venn diagram and heatmap of DEGs upregulated in epilepsy (adj. p < 0.05, Wilcoxon rank sum test). The heatmap shows normalized expression levels for upregulated DEGs that are common (34 genes), specific to deep (29 genes), or Sup (59 genes) CA1 neurons. Representative genes and associated significant GO terms are shown. FDR *adj. p < 0.05 (Fisher's exact test). (F) Same as in (E) for downregulated genes. (G) Violin plot of normalized expression value for selected genes in deep and Sup neurons in epilepsy (blue) and control (black). Wilcoxon rank-sum test; *p < 0.05, **p < 10 À10 , ***p < 10 À50 , #p < 10 À100 . Expression levels in Pyr_ES cells are also shown (green). (H) FC (left) and significance (right) for most upregulated genes in Pyr_ES compared with epileptic CA1 Pyrs (absolute log FC > 0.5 and min.pct = 0.5). (I) Immunostaining against the CA1 marker Wfs1 and multiplexed RNAscope for Dcc and Spag5 transcripts. Cells with their somata in the confocal plane are outlined. Note significant accumulation of Spag5 in an epileptic cell (green arrowhead). Scale bar, 10 mm. (J) Same as in (I) for Dapk1 and Spag5 transcripts. (K) Quantification of Dcc, Dapk1, and Spag5 per cell (small dots) and mouse (5 control and 5 epileptic); post hoc paired t tests, *p < 0.05.

+1

Sublayer- and cell-type-specific neurodegenerative transcriptional trajectories in hippocampal sclerosis
  • Article
  • Full-text available

June 2021

·

309 Reads

·

31 Citations

Cell Reports

·

Angel Marquez-Galera

·

·

[...]

·

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. Bulk tissue and single-nucleus expression profiling disclose sublayer-specific transcriptomic signatures and robust microglial pro-inflammatory responses. Transcripts regulating neuronal processes such as voltage channels, synaptic signaling, and cell adhesion are deregulated differently by epilepsy across sublayers, whereas neurodegenerative signatures primarily involve superficial cells. Pseudotime analysis of gene expression in single nuclei and in situ validation reveal separated trajectories from health to epilepsy across cell types and identify a subset of superficial cells undergoing a later stage in neurodegeneration. Our findings indicate that sublayer- and cell-type-specific changes associated with selective CA1 neuronal damage contribute to progression of hippocampal sclerosis.

Download

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

May 2021

·

124 Reads

·

35 Citations

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. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) and complemented the dataset with our own new data. By confronting the effect of brain state and recording methods, we highlight the equivalences and differences across conditions and offer a number of novel observations. We show how a heuristic approach based on oscillatory features of morphologically identified neurons can aid in classifying extracellular recordings of single cells and discuss future opportunities and challenges towards integrating single-cell phenotypes with circuit function.


Fig.S6. Equivalence between LCM-RNAseq and snRNAseq sublayer-specific results. A, Venn 069 diagram showing overlap in genes identified as significantly enriched in superficial 070 (Sup_LCM_RNAseq) and deep sublayer (Deep_LCM-RNAseq) by bulk CA1 sublayer-specific 071 tissue gene expression profiling (LCM-RNAseq) or snRNAseq. Many sublayer-and cell-subtype 072 significantly enriched transcripts were common across species (rat, mouse) and technologies (bulk 073 RNAseq, snRNAseq). B, Functional GO analysis of genes significantly enriched in deep (top) or 074 superficial (bottom) CA1 neurons (snRNAseq) in the control animals. 075
Sublayer- and cell-type-specific neurodegenerative transcriptional trajectories in hippocampal sclerosis

February 2021

·

120 Reads

·

2 Citations

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, their progression and histopathological classification remain controversial. Here using single-cell electrophysiology in vivo and immediate early gene expression, we reveal that superficial CA1 pyramidal neurons are overactive in epileptic rats and mice. Bulk tissue and single-nucleus expression profiling disclosed sublayer-specific transcriptomic signatures and robust microglial pro-inflammatory responses. Transcripts regulating neuronal processes such as voltage-channels, synaptic signalling and cell adhesion molecules were deregulated by epilepsy differently across sublayers, while neurodegenerative signatures primarily involved superficial cells. Pseudotime analysis of gene expression in single-nuclei and in situ validation revealed separated trajectories from health to epilepsy across cell types, and identified a subset of superficial cells undergoing a later stage in neurodegeneration. Our findings indicate sublayer- and cell type-specific changes associated with selective CA1 neuronal damage contributing to progression of hippocampal sclerosis




Figure 1. Characteristic Features of Local Field Potentials around CA2
Figure 2. Cell-Type-Specific Heterogeneity around CA2
Figure 3. Proximodistal Differences of Theta and Gamma Activity of CA2 Pyramidal Cells (A) Intracellular recordings obtained simultaneously to multisite LFP signals allowed evaluation of oscillatory behavior of different cell types around CA2. Note the poor theta rhythmicity of spontaneous firing in a proximal PCP4+ CA2 cell but consistent phase-locking preference with theta cycles at SLM. Note also clear hyperpolarization during sharp-wave (SPW) ripples. (B) Neurochemical classification of cells shown in (A) and (C). (C) Single-cell and LFP recordings from head-restrained rats. (D) Power spectrum of the intracellular membrane potential recorded during LFP theta in different cell types. Cells are ranked according to their proximodistal location within each group. Data from n = 5 CA3 cells (green), n = 10 CA2 cells (red), and n = 9 CA1 cells (blue). (E) Individual single-cell data of theta and gamma power of membrane potential oscillations. (F) Representative examples of single-cell autocorrelation and phase-locking firing to theta and gamma waves recorded at SLM. Cells are ranked according to their proximodistal location. (G) Proximodistal distribution of the modulatory strength for theta and gamma for cells recorded under urethane (filled circles; 24 cells) and in drug-free conditions (open circles; 3 cells). The discontinuous line indicates the 95% confidence interval. Note the separate cluster of poorly modulated cells (arrowhead). (H) Distribution of the modulatory strength as a function of the cell distance within SP (0 is the superficial limit). (I) Theta phase firing preference of single cells measured against the SLM signal. The circular distribution significance is indicated. (J) Theta phase firing preference of cells plotted as a function of their deep-superficial location. (K) Phase firing preference of single cells represented against the CA1 SP signal (note the reversal of the theta wave along the CA1 layers). (L) Potential mechanisms may include proximodistal and deep-superficial microcircuit organization and the influence of different theta generators. See also Figure S3 and Table S2.
Figure 4. Influence of Different Proximodistal Theta Drives along CA2 (A) Intracellular membrane oscillations recorded at different holding potentials simultaneously to extracellular LFP signals in one PCP4+ pyramidal cell. CSD local sinks and sources are shown, together with LFPs (color map). Note attenuated theta oscillations around À70 mV in this cell, near the reversal potential of g-aminobutyric acid a (GABAa) receptors. LFP and CSD signals were recorded simultaneously to the À70 mV trace. The inset shows validation of probe penetration through the distal CA2 region. (B) Power spectrum of membrane potential oscillations of traces shown in (A). Note the reduced theta power for a holding potential near À70 mV. (C) Relationship between theta power of membrane potential oscillations and holding potential for the cell shown in A. A minimum theta power is estimated at À70 mV (arrowhead). The thick line shows the best polynomial fit. (D) Significant gradients of minimal power potential along the proximodistal axis. Data from n = 10 PCP4+ CA2 cells. (E) Phase relationship between the membrane oscillation peak at RMP and the proximodistal location of CA2 cells. (F) Example of a proximal PCP4+ CA2 cell (a). Note the maximal depolarization and firing at the falling phase of theta recorded at SP. Example of a distal cell (b) with maximal depolarization and firing at the SP theta trough. In both cases, LFP signals were recorded from the distal CA2. (G) Proximodistal distribution of theta coherence between membrane potential oscillations at RMP and the local CSD signal at SO, SR, and SLM from the distal CA2 region. Data from cells recorded simultaneously to CA2 extracellular LFP signals (n = 1 CA3, n = 5 CA2, n = 1 CA1). In one CA2 cell, the SLM CSD signal did not meet the inclusion criteria.
Figure 5. Proximodistal Gradients of Synaptic Responses along CA2 (A) Intracellular responses to contralateral CA3 (cCA3) and PP stimulation were examined in vivo. The amplitudes of evoked EPSPs and IPSPs were evaluated at different latencies from stimulation (arrowheads). Cell types are identified by colors. (B) Synaptic responses to cCA3 stimulation (n = 20 cells) and PP stimulation (n = 12 cells). Data are plotted as a function of the cell distance to MF. (C) Mean group responses (±SD) and individual data per cell type. Because of their location, cell-type differences reflect a proximodistal gradient along CA2. cCA3 stimulation: EPSP is non-significant; IPSP F(19) = 9.1, p = 0.011, one-way ANOVA; *p < 0.05, **p < 0.005, post hoc Tukey test. PP stimulation: EPSP F(11) = 8.9, p = 0.007; IPSP F(11) = 6.1, p = 0.021; *p < 0.05, post hoc Tukey test. (D) I/E ratio of different cell types. cCA3 stimulation: F(19) = 6.5, p = 0.008, one-way ANOVA; *p < 0.05, **p < 0.005, post hoc Tukey test. PP simulation: F(11) = 41.1, p < 0.0001; **p < 0.005, ***p < 0.0001, post hoc Tukey test. (E) In vitro recordings were obtained to evaluate synaptic currents in response to CA3 or SLM stimulation. Cells were filled with Alexa 568 for posterior identification. Evoked excitatory postsynaptic currents (EPSCs) and inhibitory postsynaptic currents (IPSCs) from the PCP+ pyramidal cell are shown. (F) Synaptic currents evoked by CA3 stimulation. Wfs1+ CA1 cells (n = 8) and PCP4+ CA2 cells (n = 7) are shown in blue and red, respectively. Cells not confirmed neurochemically are indicated in black (n = 6). Significant proximodistal trend for IPSC and the I/E ratio are indicated. (G) Spontaneous IPSC frequency from n = 12 PCP4+, n = 9 Wfs1+, and n = 9 not confirmed. (H) Synaptic currents evoked by stimulation of entorhinal inputs at SLM (n = 7 PCP4+ CA2 cells, n = 6 Wfs1+ CA1 cells, n = 7 not-confirmed cells). (I) Schematic representation of a proximodistal microcircuit organization of CA2. Intra-hippocampal (CA3 and dentate gyrus [DG]) and extra-hippocampal input pathways (entorhinal cortex [EC] and possibly septum or the supramammillary nucleus) relay different theta current generators at different layers along the proximodistal axis of CA2. Local GABAergic inputs also exhibit a proximodistal distribution, consistent with gamma oscillations. See also Figures S4-S7.
Proximodistal Organization of the CA2 Hippocampal Area

February 2019

·

254 Reads

·

35 Citations

Cell Reports

The proximodistal axis is considered a major organizational principle of the hippocampus. At the interface between the hippocampus and other brain structures, CA2 apparently breaks this rule. The region is involved in social, temporal, and contextual memory function, but mechanisms remain elusive. Here, we reveal cell-type heterogeneity and a characteristic expression gradient of the transcription factor Sox5 within CA2 in the rat. Using intracellular and extracellular recordings followed by neurochemical identification of single cells, we find marked proximodistal trends of synaptic activity, subthreshold membrane potentials, and phase-locked firing coupled to theta and gamma oscillations. Phase-shifting membrane potentials and opposite proximodistal correlations with theta sinks and sources at different layers support influences from different current generators. CA2 oscillatory activity and place coding of rats running in a linear maze reflect proximodistal state-dependent trends. We suggest that the structure and function of CA2 are distributed along the proximodistal hippocampal axis.


Figure 3. Proximodistal differences of theta and gamma activity of CA2 pyramidal cells. A, Intracellular recordings obtained simultaneously to multi-site LFP signals allowed evaluating oscillatory behavior of different cell types around CA2. Note poor theta rhythmicity of spontaneous firing of a prototypical PCP4+ CA2 cell, but consistent phase-locking preference with theta cycles at SLM. Note also clear hyperpolarization during SPW-ripples. B, Neurochemical classification of cells shown in A and C. C, Single-cell and LFP recordings from head-restrained rats. D, Power spectrum of the intracellular membrane potential recorded during theta in different cell types. Cells are ranked according to their proximodistal location within each group. Data from n=5 CA3 cells (green), n=10 CA2 cells (red) and n=9 CA1 cells (blue). E, Individual data of theta and gamma power of membrane potential oscillations. F, Representative examples of single-cell autocorrelation and phase-locking firing to theta and gamma waves recorded at the SLM. Cells are ranked according to their proximodistal location. G, Proximodistal distribution of the modulatory strength for theta and gamma for cells recorded under urethane (filled circles; 24 cells) and in drug-free conditions (open circles; 3 cells). Note separate cluster of poorly modulated cells (arrowhead). H, Distribution of the modulatory strength as a function of the cell distance within SP (0 is the superficial limit). I, Theta phase firing preference of single-cells measured against the SLM signal. J, Theta phase firing preference of cells plotted as a function of their deep-superficial location. K, Phase firing preference of single-cells represented against the CA1 SP signal (note reversal of theta wave along CA1 layers). L, Potential mechanisms may include proximodistal and deep-superficial microcircuit organization and influence of different theta generators. 
Figure 4. CA2 pyramidal cells couple to different theta generators along the proximodistal axis. A, Intracellular membrane oscillations recorded at different holding potentials simultaneously to extracellular LFP signals in one PCP4+ pyramidal cell. CSD local sinks and sources are shown together with LFPs (color map). Note attenuated theta oscillations at about-70 mV in this cell, near the reversal potential of GABAa receptors. LFP and CSD signals recorded simultaneously to the-70 mV trace are shown. B, Power spectrum of membrane potential oscillations of traces shown in panel A. Note reduced theta power for a holding potential near-70 mV. C, Relationship between theta power of membrane potential oscillations and the holding potential for the cell shown before. A minimum theta power is estimated at-70 mV (arrowhead). The thick line shows the best polymonial fit. D, Significant gradients of minimal power potential along the proximodistal axis. Data from n=10 PCP4+ CA2 cells. E, Phase relationship between membrane oscillation peak at RMP and the proximodistal location of CA2 cells. F, Proximodistal distribution of theta coherence between membrane potential oscillations at RMP and the local CSD signal at SO, SR and SLM. Data from cells recorded simultaneously to CA2 extracellular LFP signals (n=1 CA3, n=5 CA2, n=1 CA1). Inset shows schematically an intrahippocampal (SR) and entorhinal (SLM) theta generators (1 and 2, respectively). A third independent generator likely contributes at SO (3). 
Figure 6. Proximodistal variability and heterogeneous composition of CA2 engrams. A, Rats were tested for their recognition memory of a familiar versus a novel conspecific. -Actinin2 and VGAT signals are shown in the same false color to facilitate interpretation. Arrowheads indicate regions expanded in B. Note cfos expression in interneurons at SO. B, Enlarged view of regions indicated in A by arrowheads. Note cell-type specific heterogeneity of social memory engrams: -Actinin2+/VGAT+ cell 1; -Actinin2-/VGAT-cell 2; -Actinin2+/VGAT-cell 3 and -Actinin2-/VGAT+ SO interneuron 4. C, Distribution of single-cell cfos normalized intentisy as a function of the proximodistal position (one optical section). A threshold was defined for cfos counting (discontinuous line). The CA2 region was defined by -Actinin2 immunoreactivity (shadowed area). D, Correlation between social recognition memory and the percentage of cells expressing cfos in one optical section per animal. E, Quantification of the linear density of cfos+ cells (one stack of 70 µm thickness per animal). Significant effects F(3)=9.6, p=0.0223 Kruskal-Wallis. *, p<0.05 and **, p<0.01 for a post-hoc Wilcoxon test. Data from n=8 rats. F, Percentage of cfos+ per cell type as identified in VGAT-VenusA rats (n=6). No statistical effects for VGAT+ interneurons. Significant effects for -Actinin2+ cells: F(3)=19.2, p=0.0002 (Kruskal-Wallis). *, p<0.05 for post-hoc Wilcoxon test. Data from CA3 and CA1 was not tested statistically, as trends reflect regional distribution of each cell type. 
Proximodistal organization of the CA2 hippocampal area

May 2018

·

123 Reads

·

1 Citation

The proximodistal axis is considered a major organizational principle of the hippocampus. Interfacing between the hippocampus and other brain systems, the CA2 region apparently breaks this rule. Apart from its specific role in social memory, CA2 has been involved in temporal and contextual memory but mechanisms remain elusive. Here, we used intracellular and extracellular recordings followed by neurochemical identification of single-cells to evaluate CA2 and surrounding areas in the rat. We found marked proximodistal trends of synaptic activity, as well as in subthreshold membrane potentials and phase-locked firing coupled to theta and gamma oscillations. Opposite proximodistal correlations between membrane potential fluctuations and theta sinks and sources at different layers revealed influences from up to three different generators. CA2 memory engrams established after a social memory task reflected these trends. We suggest that the structure and function of CA2 is segregated along the proximodistal hippocampal axis.



Mechanisms for Selective Single-Cell Reactivation during Offline Sharp-Wave Ripples and Their Distortion by Fast Ripples

June 2017

·

106 Reads

·

97 Citations

Neuron

Memory traces are reactivated selectively during sharp-wave ripples. The mechanisms of selective reactivation, and how degraded reactivation affects memory, are poorly understood. We evaluated hippocampal single-cell activity during physiological and pathological sharp-wave ripples using juxtacellular and intracellular recordings in normal and epileptic rats with different memory abilities. CA1 pyramidal cells participate selectively during physiological events but fired together during epileptic fast ripples. We found that firing selectivity was dominated by an event- and cell-specific synaptic drive, modulated in single cells by changes in the excitatory/inhibitory ratio measured intracellularly. This mechanism collapses during pathological fast ripples to exacerbate and randomize neuronal firing. Acute administration of a use- and cell-type-dependent sodium channel blocker reduced neuronal collapse and randomness and improved recall in epileptic rats. We propose that cell-specific synaptic inputs govern firing selectivity of CA1 pyramidal cells during sharp-wave ripples.


Altered Oscillatory Dynamics of CA1 Parvalbumin Basket Cells during Theta–Gamma Rhythmopathies of Temporal Lobe Epilepsy

November 2016

·

725 Reads

·

60 Citations

eNeuro

Recent reports in human demonstrate a role of theta–gamma coupling in memory for spatial episodes and a lack of coupling in people experiencing temporal lobe epilepsy, but the mechanisms are unknown. Using multisite silicon probe recordings of epileptic rats engaged in episodic-like object recognition tasks, we sought to evaluate the role of theta–gamma coupling in the absence of epileptiform activities. Our data reveal a specific association between theta–gamma (30–60 Hz) coupling at the proximal stratum radiatum of CA1 and spatial memory deficits. We targeted the microcircuit mechanisms with a novel approach to identify putative interneuronal types in tetrode recordings (parvalbumin basket cells in particular) and validated classification criteria in the epileptic context with neurochemical identification of intracellularly recorded cells. In epileptic rats, putative parvalbumin basket cells fired poorly modulated at the falling theta phase, consistent with weaker inputs from Schaffer collaterals and attenuated gamma oscillations, as evaluated by theta-phase decomposition of current–source density signals. We propose that theta–gamma interneuronal rhythmopathies of the temporal lobe are intimately related to episodic memory dysfunction in this condition.

Citations (6)


... We implement UMAP because of its increasing use to analyze life science data 48,68 and its ability to capture non-linear relationships. UMAP has been shown to capture complex patterns to visualize and cluster data in very low dimensions 47 , though the technique remains untested on calcium recordings. ...

Reference:

Nonnegative matrix factorization for analyzing state dependent neuronal network dynamics in calcium recordings
Sublayer- and cell-type-specific neurodegenerative transcriptional trajectories in hippocampal sclerosis

Cell Reports

... Hippocampome.org provides for each neuron type experimental data regarding the expression of specific molecules (White et al., 2020), biophysical membrane properties (Ascoli & Wheeler, 2016), electrophysiological firing patterns in vitro and in vivo Sanchez-Aguilera et al., 2021) and population size (Attili et al., 2019(Attili et al., , 2022. Additionally, Hippocampome.org ...

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

... This deep PN class includes morphologically identified 'athorny' neurons (Hunt et al., 2018), but we find that complete lack of thorny excrescences is not a strict requirement for subclass identity. Genetic determination of how this 'deep' subclass maps onto previously identified genetic divisions in CA3 sublayers (Thompson et al., 2008;Yao et al., 2021), or how sparse PCP4+ cells in CA3 relate to this population (Fernandez-Lamo et al., 2019) is required for complete subclass characterization. Deep and superficial layer organization is reminiscent of CA1, in which superficial and deep cells can be distinguished based on morphological properties, calbindin expression, and synaptic connectivity (Lorente de Nó, 1934;Celio, 1990;Mizuseki et al., 2011;Navas-Olive et al., 2020;Soltesz and Losonczy, 2018;Danielson et al., 2016;Morris et al., 1995;Lee et al., 2014). ...

Proximodistal Organization of the CA2 Hippocampal Area

Cell Reports

... Consistent with this idea, DGC recruitment of FFI in CA3/CA2 is randomly wired so as to provide blanket inhibition and govern network excitability in CA3 and CA2, rather than couple individual DGC-dependent excitation with inhibition onto distinct populations of pyramidal neurons (Neubrandt et al., 2017). Loss of PV IN mediated inhibition may disrupt neuronal ensembles and network oscillations by impairing neuronal spiking, recurrent excitation in CA3 networks (Sadeh and Clopath, 2021), reciprocal inhibition between CA3 and CA2 (Boehringer et al., 2017;Fernandez-Lamo et al., 2019;Lehr et al., 2021;Middleton and McHugh, 2020;Nasrallah et al., 2019;Stober et al., 2020) and/or the balance between subcortical and entorhinal inputs to CA3/CA2 during encoding of social stimuli (Chen et al., 2020;Lopez-Rojas et al., 2022;Robert et al., 2021;Wu et al., 2021). Future studies will edify how PV inhibition of CA3/CA2 facilitates encoding of social stimuli in CA3 and CA2 neuronal ensembles and network oscillations. ...

Proximodistal Organization of the CA2 Hippocampal Area
  • Citing Article
  • January 2018

SSRN Electronic Journal

... Indeed, we noticed a large spread in the amplitude of these events across recordings PYRs. This selective firing is consistent with what occurs in vivo, which could be explained by differences in synaptic weights in PYRs from the underlying circuitry (58). Along these lines, fear learning results in potentiated cortical inputs to BLA PYRs (59) as well as reduced PV-mediated inhibition (60). ...

Mechanisms for Selective Single-Cell Reactivation during Offline Sharp-Wave Ripples and Their Distortion by Fast Ripples
  • Citing Article
  • June 2017

Neuron

... Accordingly, we aim to identify distinctive EEG patterns that reliably distinguish patients with DS from age-matched controls. Based on published preclinical results, [8][9][10] we hypothesize that macroscale EEG power and phase-amplitude coupling (PAC) will be adversely affected (i.e., reduced by compromised PV+ interneuron firing that should result in microscale network dysfunction due to SCN1A haploinsufficiency). ...

Altered Oscillatory Dynamics of CA1 Parvalbumin Basket Cells during Theta–Gamma Rhythmopathies of Temporal Lobe Epilepsy

eNeuro