1. UNIVERSIDAD PABLO DE OLAVIDE, SEVILLA
DEPARTAMENTO DE FISIOLOGÍA, ANATOMIA
Y BIOLOGÍA CELULAR
TESIS DOCTORAL
BASIC MECHANISMS OF SOMATOSENSORY
PROCESSING BY THE HIPPOCAMPUS
Elisa Bellistri
Sevilla, 2012

3. MINISTERIO
DE CIENCIA
E INNOVACIÓN
Instituto Cajal
Avda Doctor Arce 37
28002 Madrid ESPAÑA
CONSEJO SUPERIOR DE
INVESTIGACIONES CIENTÍFICAS
D. Liset Menéndez de la Prida, Cientifico Titular de Consejo Superior de Investigaciones
Científicas e Investigador Principal del Laboratorio de Circuitos Neuronales del Instituto
Cajal
CERTIFICA
Que el presente trabajo de investigación titulado: Basic Mechanisms of Somatosensory
Processing by the Hippocampus , ha sido realizado bajo mi co-dirección y co-supervisión
por la doctoranda D. Elisa Bellistri, licenciada en Ingeniería Biomédica por el Politecnico di
Milano (Italia) y Máster en Neurociencia y Biología del Comportamiento por la Universidad
Pablo de Olavide de Sevilla (España).
Este trabajo reúne las condiciones de calidad y rigor científico para ser presentado e
defendido como Tesis en opción al Grado Científico de Doctor.
Madrid, 10 de Septiembre de 2012
Fdo: Dr. Liset Menéndez de la Prida
Dr. L. Menendez de la Prida
Instituto Cajal - CSIC
c/ Doctor Arce 37
Madrid 28002
Tel: 91 585 4359
Fax: 91 585 4754
lmprida@cajal.csic.es
http://www.hippo-circuitlab.es/

5. Finca La Peraleda s/n 45071 Toledo.
Tfno. 925 247700, Fax 925 247745
D. Guglielmo Foffani y D. Juan Aguilar, Investigadores Principales del Laboratorio de
Bioingeniería y Neurofisiología Experimental del Hospital Nacional de Parapléjicos
CERTIFICAN
Que el presente trabajo de investigación titulado: Basic Mechanisms of Somatosensory
Processing by the Hippocampus, ha sido realizado bajo nuestra co-dirección y co-supervisión
por la doctoranda D. Elisa Bellistri, licenciada en Ingeniería Biomédica por el Politecnico di
Milano (Italia) y Máster en Neurociencia y Biología del Comportamiento por la Universidad Pablo
de Olavide de Sevilla (España).
Este trabajo reúne las condiciones de calidad y rigor científico para ser presentado e defendido
como Tesis en opción al Grado Científico de Doctor.
Toledo, 3 de Septiembre de 2012
Fdo: Dr. Guglielmo Foffani
Fdo: Dr. Juan Aguilar

7. D. Javier Márquez Ruiz, Investigador de la División de Neurociencias y Profesor del
Departamento de Fisiología, Anatomía y Biología Celular de la Universidad Pablo de Olavide de
Sevilla
CERTIFICA
Que el presente trabajo de investigación titulado: Basic Mechanisms of Somatosensory
Processing by the Hippocampus, ha sido realizado bajo mi tutela por la doctoranda Dª. Elisa
Bellistri, licenciada en Ingeniería Biomédica por el Politecnico di Milano (Italia) y Máster en
Neurociencia y Biología del Comportamiento por la Universidad Pablo de Olavide de Sevilla
(España).
Este trabajo reúne las condiciones de calidad y rigor científico para ser presentado e defendido
como Tesis en opción al Grado Científico de Doctor.
Sevilla, 10 de Septiembre de 2012
Fdo: Dr. Javier Márquez Ruiz

9. !"#$%&'() *+&!,$%-.+
Dedicata ai miei anni a Toledo
!

11. Acknowledgements
All the work in this thesis was carried out under the constant teaching,
discussion and leading of my supervisors, Dr. Guglielmo Foffani, Dr. Juan
Aguilar and Dra. Liset Menendez de la Prida. They gave me a lot of
opportunities in this work and I gratefully remember them.
A mention also to all my labmates and colleagues (actually more friends
than colleagues) who gave me any kind of help or suggestion during the
development of this research.
A special thanks to Liset, who has been not only a professional, but also a
personal example. In other words, the kind of scientist I would like to be.
This work was supported by grants from the Spanish Ministry Ministerio de
Ciencia e Innovación (MICINN) (BFU2009-07989), from La Fundación para
la Investigación Sanitaria en Castilla la Mancha (PI-2006/49), Gobierno de
Castilla-La Mancha and by a PhD fellowship from Fundación para la
Investigación Sanitaria en Castilla la Mancha (MOV-2010_JI/004).

13. Index
List of abbreviations ……………………………………………………………………. page 1
Resumen [Spanish] ……………………………………………………………………. page 3
1. Introduction ……………………………………………………………………. page 5
1.1. Anatomical structure of the hippocampus
1.2. The rat hippocampal formation
1.2.1. The dentate gyrus
1.2.2. The CA3 region
1.2.3. CA1 area of the hippocampus
1.2.4. The less famous CA2 and CA4 sectors of the
Cornu Ammonis
1.2.5. The subiculum
1.2.6. Major fiber systems: the angular bundle
1.2.7. Major fiber systems: the fimbria – fornix
pathway
1.2.8. Major fiber systems: the dorsal and
ventral commisures
1.3. Structural and functional organization of entorhinal cortex
1.4. Functional role of the hippocampus
1.5. The somatosensory system
1.6. Neuronal mechanisms of episodic memory: a link between
the mesial temporal lobe and the somatosensory system?
2. Objectives …………………………………………………………………… page 36
3. Material and Methods …………………………………………………………. page 37
3.1. Animals
3.2. Surgical procedures
3.3. Somatosensory stimulation
3.4. Stimulation of input pathways
3.5. Local field potential recordings
3.6. Recordings of single cell activity: tetrode and sharp recordings
3.7. Histology
3.8. Single-unit isolation and sorting
3.9. Data analysis
3.9.1. Software and tools for data analysis
3.9.2. Current source density analysis

14. 3.9.3. ICA analysis
3.9.4. Analysis of multi-unit activity
3.9.5. Spectral analysis of the local field potential
3.9.6. Statistic analysis
4. Results …………………………………………………………………… page 49
4.1. Hippocampal local field potential responses to somatosensory
stimulation
4.2. Current source density analysis of local field potential responses
4.3. Independent component analysis of CSD responses
4.4. Topographical distribution of hippocampal responses to
somatosensory stimulation
4.5. Lemniscal stimulation
4.6. Distinct patterns of multi-unit somatosensory responses in CA1 and
DG
4.7. Single-cell somatosensory responses in CA1 and DG
4.8. Intracellular correlates of hippocampal responses to somatosensory
stimulation
4.9. State-dependence of somatosensory-evoked hippocampal responses
4.10. Cortical modulation of hippocampal responses to somatosensory
stimulation
5. Discussion ………………………………………………………………….. page 67
5.1. Summary of results
5.2. Early studies and more recent works
5.3. A system level perspective of somatosensory evoked hippocampal
responses
5.4. A single-cell level perspective of somatosensory evoked hippocampal
responses
5.5. Dependence of the ongoing state in the cortex and in the
hippocampus
5.6. Significance of the study of somatosensory-evoked hippocampal
responses for understanding episodic memory
6. Conclusiones [Spanish] ……………………………………………………… page 79
7. References ……………………………………………………… page 81

15. Abbreviations
1
List of Abbreviations
ANOVA ANalysis Of VAriance
CA Cornus Ammonis
CA1, CA2, CA3 Cornus Ammonis sectors 1, 2 and 3
DG Dentate Gyrus
DL DorsoLateral nucleus
EPSP Excitatory Post Synaptic Potential
GABA Gamma Ammino Butirrico Acyd
GC Granule Cells
i.p. intra-peritoneal
ICA Independent Component Analysis
IPSP Inhibitory Post Synaptic Potential
Kg kilo
LEC Lateral Entorhinal Cortex
LIA Large Irregular Activity
MEC Medial Entorhinal Cortex
ML Molecular Layer
mm millimiters
ms milliseconds
PoM Posterior Medial nucleus
sec seconds
SI primary somatosensory area
SII secondary somatosensory area
SLM Stratum Lacunosum Moleculare
SP Stratum Piramidale
SR Stratum Oriens
VPL VentroPosterior Lateral nucleus
VPM VentroPosterior Medial nucleus
ZI Zona Incerta

16. Abbreviations
2

17. Resumen
3
Resumen
Una de las funciones del hipocampo que atrae más interés investigador es comprender
su papel en la formación de la memoria episódica. Para llevar a cabo este proceso, el
hipocampo necesita recibir de forma continua la información sensorial de diferentes
modalidades (visual, olfativa, auditiva) sobre las características de los objetos y
eventos del mundo exterior y procesar esta información para que encaje en un marco
espacial y temporal. Cada especie posee una o más modalidades sensoriales
preferidas para la exploración del entorno. Si en humano tal vez el sistema visual es
predominante, en el caso de ratas y ratones, que son animales principalmente
nocturnos, predominan el sistema olfativo y el somatosensorial. A pesar de la gran
importancia que tiene este último en el comportamiento de los roedores, los
mecanismos básicos del procesamiento de la información somatesensorial en el
hipocampo de estos animales de laboratorio permanecen aún poco estudiados.
El propósito de esta tesis fue investigar los mecanismos básicos que subyacen a la
respuesta ante estímulos somatosensoriales en diferentes regiones hipocampales en el
modelo de rata anestesiada, desde un nivel de sistema hasta un nivel de neurona
individual, y con varias herramientas de registro electrofisiológico (multi-registros con
sondas de silicio, tetrodos y registros intracelulares).
La estimulación periférica bien de las garras delanteras y traseras así como de los
bigotes genera una respuesta característica en el stratum lacunosum moleculare y en
el giro dentado (capa molecular) del hipocampo dorsal. A través de un análisis de
densidad de fuentes de corriente se pudo confirmar cómo los sumideros asociados a
esta respuesta coincidían con los producidos por la activación de la vía perforante. El
estímulo somatosensorial produce un aumento del disparo en el giro dentado, mientras
en CA1 predomina su inhibición, registrado en forma de actividad multi-unitaria.
Registros intracelulares y con tetrodos confirman la diferente modulación del disparo de
las neuronas según se localicen en CA1 o en giro dentado. Finalmente, se relacionó la
amplitud de la respuesta celular con el estado oscilatorio de la actividad de campo, bien
local (en hipocampo) o distal (en la corteza). En conclusión, la información
somatosensorial llega al hipocampo principalmente a través de la corteza entorrinal y
activa un procesamiento interno bajo la modulación de estructuras corticales y
subcorticales.

18. Resumen
4

19. Introduction
5
1. Introduction
1.1. Introduction
The hippocampus is a critical structure involved in the formation of episodic memories
(Eichenbaum, 2004). To this purpose, information from the individual attributes of items
and events has to be associated to form a meaningful representation of the whole
spatio-temporal context. Such a process takes place as a continuous updating of
visual, auditory, olfactory and somatosensory information that are modulated by the
spatial and temporal frameworks (O’Keefe and Nadle, 1978; Eacott and Norman,
2004). Understanding how sensory information from different modalities reaches the
hippocampus is therefore obliged in order to uncover specific mechanisms of memory
function.
Previous studies on evoked-responses examined the effect of sensory stimulation
entering the hippocampal formation in freely moving animals (Deawyler et al. 1981;
Brankack and Buzsaki, 1986; Vinogradova, 2001). Unit recordings revealed that
multimodal responses (visual, auditory and tactile) occur at the single-cell level
(Vinogradova et al., 1993; Vinogradova, 2001), probably served by projections from
the primary sensory cortices converging onto the parahippocampal region (Burwell
and Amaral, 1998). Interestingly, hippocampal cell responses to sensory stimuli of
different modalities were found to be strongly modulated by ongoing theta oscillations
(Vinogradova et al., 1993; Brankack and Buzsaki, 1986; Pereira et al., 2007), and in
close relationship with the level of arousal (Vinogradova, 2001). Indeed, sensory
stimulation per se is known to induce a type of theta oscillations different from motor
theta activity (Sainsbury et al., 1987), thus suggesting a complex interaction between
hippocampal responses and the cortical and subcortical control of brain state
(Vinogradova, 2001).
Amongst the different sensory modalities (visual, auditory, somatosensory, olfactory),
the somatosensory system is, together with olfaction, probably the most important
system for exploration in rodents. As animals collect information from the environment,
they actively use their whiskers and limbs to explore objects and surfaces. Recent
work has revealed a hippocampal representation of tactile information occurring in rats
while they perform whisker discrimination tasks (Pereira et al., 2007; Itskov et al.,

20. Introduction
6
2011). According to these data, CA1 neurons form a representation of textures and
objects that is highly dependent on the context and the vigilance state of the animal.
However, basic mechanisms underlying somatosensory processing by the
hippocampus still remain unclear. Equally unknown is how somatosensory information
integrates into the hippocampus, as a detailed analysis of the extracellular and
intracellular neuronal processes is lacking. This dissertation is focused on the basic
processes and mechanisms underlying hippocampal responses to somatosensory
stimuli. I will discuss and analyze these hippocampal responses from a circuit
perspective, by simultaneously recording from different hippocampal regions namely
CA1 and the dentate gyrus (DG), to a single cell level, using tetrode recordings of
firing activity and intracellular recordings of membrane potential changes. I will provide
an integrated view of the elementary processes involved before proposing a general
schema to understand the way in which somatosensory information reach the
hippocampus. This introduction provides a brief summary of the anatomical and
cellular structure of the hippocampus and its connectivity to other brain regions with a
particular emphasis on the parahippocampal cortical areas. I will also present a
functional description of the hippocampus and of the somatosensory system to finally
connect with basic concepts that potentially define the role of these structures in
episodic memory.
1.2. Anatomical structure of the hippocampus
The beautiful neuronal architecture of the hippocampal formation and the simplicity of
its major connections have attracted our attention for decades. A comprehensive
definition of hippocampal anatomy is an important step for understanding its function.
Hence, the hippocampus proper has three subdivisions: CA3, CA2 and CA1, named
after Lorente de Nó. The other regions of the hippocampal formation include the
dentate gyrus (DG), subiculum, presubiculum and the enthorhinal cortex, but these are
typically considered as para-hippocampal regions.
In spite that neuronal organization of some portions of the hippocampus resembles
other cortical areas, the neuroanatomy of this structure is unique. For example a
common feature of neocortical connections is reciprocity; so that one cortical region
projects to another, which then sends projections back (Felleman and Van Essen,
1991). In contrast, there is an important directionality of hippocampal connections,

21. Introduction
7
known as the tri-synaptic circuit. In this circuit, connections originate in the superficial
layers of the enthorhinal cortex, passing through the DG, CA3, CA1 and the subiculum
before closing the look back to the deep layers of the entorhinal cortex (first described
by Ramon y Cajal, 1983). These principal anatomical features are common across
mammalian species, in particular referring to the rat, the monkey and the human
(Swanson, 2000). Some differences occur mainly due to the different volume, that is
10 times larger in monkeys than in rats and 100 times larger in humans, and also due
to the more complex organization of the primate enthorhinal cortex, which is
associated with stronger interconnections with the associational neocortical areas
(Holloway, 1973 ; Caspari, 1979 ; Jolly, 1985; Foley, 1987).
Figure 1.1. The human hippocampus. A, Schematic representation of the localization of the
hippocampus and the parahippocampal areas in the human brain. B. The Hungarian neuroscientist László
Seress' 1980 preparation of the human hippocampus and fornix compared with a seahorse. Laszlo

22. Introduction
8
Seress; Wikipedia C. Three-dimensional model of the hippocampus showing the anterior-posterior
distribution of hippocampal CA1 lesions in temporal lobe epilepsy (color dots). From Bartsch et al. PNAS
2011. Template modified after http://www9.biostr.washington.edu/da.html, used with permission, copyright
1997 University of Washington, USA D. The anterior portion of the human hippocampus as resected from
a temporal lobe epileptic patient. Transverse slices are prepared for in vitro recordings. Images from the
Dietrich lab. E. Coronal sections through rostral (top image) and caudal (bottom image) portions of Nissl-
stained human hippocampal formation. Calibration marker, 2 mm CA1, CA2, CA3, hippocampal
fields; DG, dentate gyrus; EC, entorhinal cortex; f, fimbria; PaS, parasubiculum; PrS, presubiculum; PRC,
perirhinal cortex; S, subiculum. From David G. Amaral, Handbook of Physiology, The Nervous System,
Higher Functions of the Brain. 1987. Wiley online Library
1.3. The rat hippocampal formation
From the ancient times, anatomists were interested in this peculiar structure of the
lateral ventricle. The name hippocampus was introduced in the sixteenth century due
to similarities with the seahorse when dissected in the human brain (Fig.1.1). The
origin of the acronymus CA used to name the regions CA1, CA2, CA3 is even older; it
was adopted by the anatomists in the Alexandrian school of medicine in Egypt, who
observed that the two half of this structure strongly resembles the coiled horns of a
ram, or cornu ammonis in Latin.
In spite of some major differences with the human hippocampus, rodent hippocampus
share several features with those at primates probably reflecting a common ancestral
origin as the most primitive brain cortex. Indeed, the hippocampus, together with the
entorhinal cortex, is typically considered to be a type of archicortex, being clearly
differentiated from the neocortex in superior animals (Nieuwenhuys, 1994). In the
following sections I will describe the major features of the rat hippocampus.
1.3.1 The dentate gyrus
The dentate gyrus (DG) is comprised of three layers, i.e. the molecular layer, the
granular layer and the polymorphic cell layer. The molecular layer starts close to the
hippocampal fissure, and it is a relatively cell-free layer that hosts mostly the dendrites
of granule cells. In the rat, this layer has a thickness of about 250 µm. Deep inside the
DG is the principal cell layer which is made up of densely packed four to eight rows of
granule cells. The granule and molecular layers (sometimes called fascia dentate from
its typical dentate appereance in the human hippocampus) form a U- shaped structure
that encloses the polymorphic cell layer, also known as the hilus.

23. Introduction
9
Figure 1.2. The rat hippocampus. A, Representation of the rat hippocampus and para-hippocampal
regions within the brain. From Hjornevik et al. Frontiers NeuroInformatics, 2007. B, Lateral view of the rat
brain (left), and the ventral view of the rhesus monkey (middle) and human brains (right) depicting the
location and extent of selected structures. From Murray et al. 2007. Annu Rev Neurosci C, Coronal
section of the adult rat brain showing the parts of the hippocampus. D, Transverse slice from the mid-
septotemporal level indicating the topographical organization of the temporo-ammonic and perforant
pathways and the lateral (LEC) and medial entorhinal cortex (MEC).
The granule cell is the principal cell type of the DG. These cells have ovoid cell bodies
of about 10 µm width and 18 µm high and are positioned closely to other. A major
characteristic is the cone-shaped tree of spiny dendrites with all their branches toward
the outer molecular layer. Granule cells are glutamatergic, therefore exciting their main

24. Introduction
10
targets at the CA3 region and the polymorphic layer. Granule cells dendrites extend
into the molecular layer and terminate near the hippocampal fissure. The calculated
sum of the dendritic lengths ranges from 2.3 to 4.6 mm. These dendritic lengths are
significantly shorter than those of the CA1 pyramidal neurons. Dendritic morphology
also varies depending on the position in the DG (Desmond and Levy 1982, 1985;
Claiborne et al., 1990).
Granule cells synapses are divided into segments that receive different inputs
(Blackstad 1958; Amaral and Witter, 1995). So it is possible to distinguish a proximal
third part that receives input from the commissural/associational fibers, which consist
primarily of axons from the mossy cells. A second third receives input from relatively
medial regions of the entorhinal cortex, and the distal third receives input from the
lateral entorhinal cortex (Blackstad 1958; Amaral and Witter, 1995). Inputs to the
dentate gyrus from layer II of the entorhinal cortex arrive via the perforant pathway.
Granule cells have a typically hyperpolarized resting membrane potential, around -85
mV, and action potential thresholds similar to CA1 and CA3 pyramidal cells (Henze et
al., 2000; Scharfman 1991). This means larger depolarizations are required to fire a
single action potential and consequently granule cells exhibit low spontaneous firing
rate even when the animal is in a place field (Jung and McNaughton, 1993; Skaggs et
al., 1996). Upon reaching threshold for action potential, granule cells typically fire
trains of action potentials with accommodation (Staley et al., 1992; Penttonen et al.,
1997). As in pyramidal cells, spike accommodation in granule cells is largely due to the
activation of Ca2+
-dependent, voltage-gated K+
conductances (Staley et al., 1992).
Recently, a novel cell type was discovered in the rat DG and named semilunar granule
cells, due to their particular cell body shape (Williams et al., 2007). They present
several different features from granule cells. In contrast to them, these neurons have
axon collaterals in the molecular layer and extend their dendrites over larger lateral
distances. Semilunar granule cells have extensive dendrites in all three molecular
layers and appear to receive excitatory inputs from the perforant pathway along with
granule cells. Similar to granule cells, semilunar neurons have hyperpolarized
membrane potentials but differ dramatically from granule cells in their responses to
long-duration current steps. They discharge throughout 2 s depolarizing steps with
poor adaptation whereas granule cells tend to fire predominately only during the initial

25. Introduction
11
50–100 ms of the response. Semilunar cells receive stronger excitatory inputs after
hilar stimulation than granule cells, suggesting that they are major synaptic targets of
mossy cells, and therefore could be potentially involved in epilepsy-related
reorganization after seizure-induced loss of mossy cells.
The other DG cell type is GABAergic inhibitory interneurons, which are interspersed
within the granule cell layer and the hilus (Ribak et al., 1978; Ribak and Seress, 1983;
Freund et Buzsaki, 1996). As in many brain regions, the most intensively studied
interneuron of the DG is the basket cell, so called because their axons surround the
cell bodies of principal cells (Ramón y Cajal, 1893). There are many types of other
interneurons in this hippocampal subfield, which presumably perform different
functions. Most of these cell types are distinguished and classified based on the
distribution of their axonal arborization (Freund and Buzsaki, 1996).
Mossy cells are the most common cell type in the polimorphic layer (Amaral, 1978).
They are glutamatergic neurons providing the major source of excitatory
associational/commissural projections to the DG (Amaral, 1978; Scharfman, 1995).
Another hilar type is fusiform cells that have axons ascending into the outer two-thirds
of the molecular layer and terminate with symmetrical inhibitory synapses on the
dendrite of granule cells. This intrincate network of interneurons suggest that these
cells do not relay activity but they work as components of normal information
processing in the hippocampal formation (Andersen et al., 2007).
Regarding extrinsic connections, DG receives its major inputs from the entorhinal
cortex through the perforant pathway. The projection to the DG arises mainly from cells
located in layer II, whereas only a minor component comes from layers V and VI
(Steward and Scoville, 1976). Depending on the origin in the entorhinal cortex, the
perforant pathway can be divided into two branches, called lateral and medial
perforant pathway (Tamamaki and Nojyo, 1993). Fibers originating in the lateral
entorhinal area terminate in the most superficial third of the molecular layer (outer
molecular layer), whereas fibers from the medial entorhinal cortex terminate in the
middle third, or inner molecular layer. Other entorhinal inputs to the DG arise from the
presubiculum and parasubiculum (Kohler, 1985). Since the presubiculum receives
direct inputs from the anterior thalamic nucleus, this pathway might potentially convey
thalamic information to the DG (Kloosterman et al., 2003; Naber et al., 1999).

26. Introduction
12
From the basal forebrain, the DG receives only few inputs, the most studied of which
that originating in the septal nuclei. A large portion of this projection is cholinergic, but
also GABAergic cells have been recently studied (Lubke et al, 1997). The DG also
receives projections from the hypothalamus, via a population of large cells that
terminate only in a narrow zone of the molecular layer located just superficial to the
granule cell layer, close to the proximal dendrites.
Regarding intrinsic hippocampal connections to the DG, the principal projection comes
from the polymorphic layer and CA3, both the ipsilateral and contralateral sides, so it is
called the associational/commissural projection (Laurberg and Sorensen, 1981;
Buckmaster et al., 1992, 1996; Frotscher, 1992). Only a small portion of the temporal
CA3 sends collaterals into the molecular layer. This connection represents an
exception to the rule of unidirectionality of the tri-synaptic patway (Leung, 1979) and
has several interesting features. First, axons from any particular septotemporal point in
the DG may innervate as much as 75% of the long axis of the DG (Amaral and Witter,
1989). Second, the weak projection to the molecular layer at the septotemporal level
becomes stronger at more distante levels (Andersen et al., 2007). Hence, this pattern
could work both as a feedforward excitatory pathway to distant granule cells and as a
disynaptic feedforward inhibitory pathway, through the intermediary of the pyramidal
basket cells.
As previously commented, the DG is a major step of the tri-synaptic circuit. Granule
cells give rise a dense axonal plexus, i.e. the mossy fibers, that terminate in a narrow
zone just above the CA3 pyramidal cell layer called stratum lucidum (Blackstad et
al.,1970; Gaarskjaer,1978b; Swanson et al.,1978; Claiborne et al., 1986). Due to the
large size of their presynaptic terminals, mossy fibers have been largely used for patch
studies of transmitter release (Bischofberger et al., 2006). Another distinctive feature is
the large number of synaptic boutons, so that a single mossy fiber can make as many
as 37 synaptic contacts with a single CA3 pyramidal cell dendrite. Based on this
anatomical data, it has been estimated that each granule cell communicates with
about 15 CA3 pyramidal cells (Henze et al., 2000). The presence of many release
sites of mossy fiber boutons might ensure highly efficient depolarization of the
innervated pyramidal cells (von Kitzing et al., 1994; Geiger and Jonas, 2000). This
pattern has attracted considerable interest among computational neuroscientists.

27. Introduction
13
1.3.2. The CA3 region
The hippocampus proper is composed of three main regions, called CA1, CA2 and
CA3 by Lorente de Nó sharing a laminar organization, with a cell layer mainly formed
by pyramidal cells. The principal afferent to CA3 are from the same CA3 region by
collaterals of their own axons (associational connections) and from axons of the
contralateral CA3 (commissural connections) (Witter and Amaral, 1995; Blackstad,
1965; Swanson and Cowan, 1977). This creates an extensive network of recurrent
collaterals suggesting that CA3 may function as an autoassociative network involved
in memory storage and recall (Bennett et al., 1994; Rolls, 1996). Another important
input comes from the enthorhinal cortex. Entorhinal terminals are distributed
throughout the width of the stratum lacunosum moleculare (SLM). This input pathway
is better known as the temporo-ammonic pathway and originates in layer III cells of the
entorhinal cortex (Gloveli et al., 1997). The temporo-ammonic pathway is proposed to
be involved in relaying memory cues that initiate retrieval in CA3 (Rolls, 2010).
Tracing methods have shown that CA3, in particular its temporal parts, receives input
from the amygdaloid complex, which was previously thought to send projections only
to CA1 and the subiculum (Pikkarainen et al., 1999; Pitkanen et al., 2000). From the
subcortical regions, the septum is the major projection to CA3 (Andersen et al. 2007).
The CA3 projection to the lateral septal nucleus travels bilaterally via the fimbria and
precommissural fornix (Swanson and Cowan, 1977). In addition, this pathway has a
topographical organization, medial portions of CA3 give rise projection to lateral septal
nucleus, while lateral portion of CA3 are connected to more ventral portion of the
septum.
Regarding the morphology and electrophysiological properties of CA3 cells, the most
well studied type is pyramidal cell. They are very similar to CA1 pyramidal neurons,
even with some differences, such as the bifurcation of the dendritic tree which comes
closer to the soma typically at the limit with the stratum lucidum which hosts the mossy
fiber pathway. A major feature of CA3 pyramidal cells is their characteristic spine
morphology known as thorny excrescences (Blackstad and Kjaerheim, 1961; Chicurel
and Harris, 1992; Amaral and Witter, 1995; Gonzales et al., 2001). As in other
hippocampal regions, CA3 contains several types of interneurons (Andersen et al.,

28. Introduction
14
2007).
Due to different ionic channel conductances, CA3 pyramidal neurons have the ability
to respond to a stimulus, either with a single spike or a burst (Kandel and Spencer,
1961; Spencer and Kandel, 1961; Wong and Prince, 1978). This has been described
as a major characteristic of CA3 pyramidal cells in vitro, in contrast to CA1 pyramidal
cells which rarely burst under similar recording conditions. It is worth noting that
bursting is more prominent in vivo than in vitro (Kandel and Spencer, 1961; Spencer
and Kandel, 1961; Wong and Prince, 1978). Bursts in CA3 neurons typically consist of
several action potentials riding on a depolarizing waveform, often accompanied by
smaller calcium-dependent spikes. Each burst is an all-or-none event lasting about 30
to 50 ms, with the frequency of action potentials in the range of 100 to 300 Hz (Wong
et al., 1979; Wong and Prince, 1981; Traub and Miles, 1991). Bursts can be triggered
in several ways in CA3 neurons. The most effective burst are generated CA3 neurons
when the entire network becomes synchronously active, usually when synaptic
inhibition is blocked or extracellular K+ is increased (Prince and Connors, 1986).
1.3.3. CA1 area of the hippocampus
CA1, mostly dorsal CA1, is one of the most studied regions of the hippocampus. As in
CA3, in CA1 the principal cell layer is called the pyramidal layer. However, the
hippocampal cell layer is more apparent in this sector than in the CA3 area. The
narrow, relatively cell-free layer above the pyramidal cell layer is called the stratum
oriens (SO). This layer contains the basal dendrites of pyramidal cells and several
classes of interneurons. Just above the stratum oriens is the fiber-containing alveus.
Immediately below the pyramidal cells there is the stratum radiatum (SR) that is
defined as the region where associational connections and Schaffer collateral (SC)
connections are located. The deepest CA1 layer is called the stratum lacunosum
moleculare (SLM). This is the layer where temporo-ammonic fibers terminate together
with fibers from the nucleus reuniens of the midline thalamus (Andersen et al. 2007).
Both SR and SLM contain a variety of interneurons.
The principal neuronal cell type of CA1 region is the pyramidal cell. Several recent
observations suggest that there are distinct subgroups of CA1 principal neurons with
different properties, projections and local interactions (Nelson et al., 2006, Deguchi et

29. Introduction
15
al., 2011). Functional differences in various groups of deep and superficial CA1
pyramidal cells have been described according to different physiological and
electrophysiological properties (Mizuseki et al., 2011). These cells show a topography
in the propensity of emitting bursts (Jarsky et al., 2008) and spatial specificity
(Henriksen et al., 2010). Pyramidal cells also have a functional segregation, showing
bimodality both in the magnitude of the response to the somatodendritic
backpropagation, different firing rates and different phase modulation strengths (Senior
et al., 2008). Finally, from an anatomical and molecular perspective, CA1 pyramidal
cells have a sub-layer specific expression of zinc and calbindin (Baimbridge et al.,
1991; Slomianka, 1992; Somogyi, 1994). (Fig.1.3)
Figure 1.3. Cellular type diversity in the rat CA1 regions. Image from Klausberger and Somogyi 2008.
Note the three different types of pyramidal cells that are accompanied by at least 21 classes of
interneurons. VIP, vasoactive intestinal polypeptide; VGLUT, vesicular glutamate transporter; O-LM, oriens
lacunosum moleculare.
The basal dendrites of pyramidal cells grow into the stratum oriens, while the apical
dendrites extend into the stratum radiatum (proximal apical) and stratum lacunosum
moleculare (distal apical). The morphology is quite homogeneous along the whole
region, even if some cells have one apical dendrite, some others have two (Pyapali et

30. Introduction
16
al., 1998). The number of dendritic spines that cover pyramidal neurons is huge, and
most of them receive excitatory synaptic inputs, so it is common practice using spine
density as a measure of synaptic excitability. This density is higher in the strata
radiatum and oriens and lower in the stratum lacunosum moleculare (Bannister and
Larkman, 1995). Anyway spine structure is not static but may change in response to
neurotransmitter receptor activation or environmental and hormonal signals (Hering
and Sheng 2001; Bonhoeffer and Yuste, 2002; Nikonenko et al., 2002; Nimchinsky et
al., 2002). Moreover, the mechanisms of synaptic transmission at single synapses and
the morphological and functional plasticity are modulated by several factors; including
calcium entry, buffering and extrusion (Yuste and Denk, 1995; Yuste et al., 1999;
Majewska et al., 2000).
At synaptic level there are some differences between the temporo-ammonic pathway
and the Schaffer collateral inputs on CA1 pyramidal cells. First, synapses of the
temporo-ammonic pathway are located far from the soma at the SLM, having a weaker
effect on action potential initiation than Schaffer synapses (Mainen et al., 1996;
Andreasen and Lambert, 1998; Golding et al., 2005). The second difference is the
greater proportion of synapses in the SLM that is formed on dendrite shafts instead of
spines (Megias et al., 2001). This fact has to be considering when using spine density
as the only measure of synaptic connectivity. Regarding connections between CA1
pyramidal neurons, while they are present only during developing stage of the brain
(Tamamaki et al., 1987; Amaral et al., 1991; Aniksztejn et al., 2001), the CA1-
interneuron connectivity is very high, and the strength of excitatory postsynaptic
potentials (EPSPs) on interneurons is powerful (Gulyás et al., 1993; Ali et al., 1998;
Csicsvari et al., 1998; Marshall et al., 2002). These connections occur mainly on basal
dendrites, since the CA1 axons do not enter the stratum radiatum.
Data on synaptic activity in CA1 pyramidal cells suggests powerful voltage attenuation
and filtering occurring in normal conditions (Golding et al., 2005). There is an intrinsic
compensation that occurs by two mechanisms: synaptic conductance scaling and
voltage-gated channels. Voltage-gated channels are involved in action potential back
propagation and dendritic spike integration (Golding et al., 2005). The presence of
voltage-gated channels in dendrites is likely to have profound effects on synaptic
integration and synaptic scaling (Magee, 1999).

31. Introduction
17
CA1 interneurons are very heterogeneous through all layers, even if more diffused in
the strata oriens and radiatum (Freund and Buzsaki, 1996) (Fig.1.3).
Regarding connections with other regions, the heaviest input to CA1 comes from CA3
through the Schaffer collateral (Li et al., 1994). The other important connection is the
entorhinal cortex that projects both to CA3/CA2 and CA1 sections. The projection to
CA1 that occurs into the stratum lacunosum moleculare layer, originates from layer III
of entorhinal cortex and shows a topographical organization (Dolorfo and Amaral,
1998). Hence, depending on where a CA1 pyramidal cell is located in the transverse
axis, it receives inputs from a different portion of the entorhinal cortex (Witter et al.,
1988; Naber et al., 2001; Kloosterman et al., 2003). On the other side, the return
projection to the entorhinal cortex only arises from cells located in the CA1 region and
the subiculum.
Besides the entorhinal cortex other cortical connections are documented; the best-
studied is that of the perirhinal and postrhinal cortices (Burwell et Amaral, 1998).
Interestingly, the temporal two-thirds of the distal portion of CA1 are reciprocally
connected with the amygdaloid complex. From the basal forebrain, the main
connection arises from the septum and from the thalamic nucleus reuniens in the
stratum lacunosum moleculare on both principal neurons and GABAergic interneurons
(Herkenham, 1978; Wouterlood et al., 1990; Dolleman-Van der Weel and Witter,
1996). From the brain stem nuclei, CA1 receives noradrenergic and serotonergic
inputs (Andersen et al, 2007). Besides the projection of CA1 to entorhinal cortex, the
one into the subiculum is the other important projection that CA1 gives rise to. Axons
of CA1 pyramidal cells descend into the stratum oriens or the alveus and bend sharply
toward the subiculum (Amaral et at., 1991).
1.3.4. The less famous CA2 and CA4 sectors of the Cornu Ammonis
The CA2 field has been the subject of substantial controversy. As originally defined by
Lorente de Nó, it is a narrow zone of cells interposed between CA3 and CA1. CA2 has
large pyramidal cell bodies similar to those in CA3 but, like CA1, it is not innervated by
the mossy fibers from the dentate gyrus (Mercer et al. 2007).

32. Introduction
18
The poor interest for the CA2 field is probably due to its small dimension and because
it was considered as a transition zone between the two major fields CA3 and CA1. In
spite of its small size, more recent studies demonstrate that it plays an important
functional role. For some authors, CA2 field plays the same role with respect to CA1
as granule cells do with respect to CA3 (Bartesaghi et al., 2006). Interestingly, the well-
known trisynaptic circuit should be actually divided into two disynaptic circuits:
entorhinal-DG-CA3 and entorhinal-CA2-CA1, that operate in parallel and where CA2
region plays a connection role (Bartesaghi et al., 2006). It has been proposed that the
entorhinal-DG-CA1 circuit may communicate and enforce the entorhinal-CA2-CA1
circuit, through the connections from CA3 to CA1 (Bartesaghi et al., 2006). In addition,
some collaterals also arise from CA2 region (Amaral and Witter, 1995), in order to
mediate the activation of CA1 coming from the CA3 connection. Recently, it was
shown that CA2 neurons are strongly excited by their distal dendritic inputs from
entorhinal cortex but only weakly activated by their more proximal dendritic inputs from
hippocampal CA3 neurons (Chevaleyre and Siegelbaum 2010). In turns, CA2 neurons
make strong excitatory synaptic contacts with CA1 neurons. In this manner, CA2
neurons form the nexus of a highly plastic disynaptic circuit linking the cortical input to
the hippocampus to its CA1 neuronal output.
Lorente de Nó also defined a CA4 field. As originally clarified by Theodor Blackstad
(1956) and then by David Amaral (1978), the region that Lorente de Nó called CA4 is
one part of the deep, or polymorphic, layer of the dentate gyrus. There is still poor
understanding on the role of this sector.
1.3.5. The subiculum
The subiculum is a structure that follows the CA1 region and is considered the major
cortical output of the hippocampus. Its main cell type is pyramidal cells that can be
divided into at least two types based on their firing characteristics: regular spiking cells
and intrinsically weak and strong bursting cells (Greene and Totterdell, 1997;
Menendez de la Prida et al. 2003). Although these two cell types do not exhibit distinct
morphological characteristics, they show a differential distribution in the pyramidal cell
layer. Bursting cells tend to be more numerous deep in the pyramidal cell layer,
whereas regular spiking cells are more common superficially (Funahashi and Stewart,
1997; Harris et al., 2001).

33. Introduction
19
Bursting is much more prominent in the subiculum than in CA1. Given the large
number of brain areas innervated by subicular neurons, it is tempting to speculate that
strong bursting cells target different areas than weaker bursting or regular spiking
cells. Some evidence supports this hypothesis, as it has been shown that bursting
cells project preferentially to the presubiculum and parasubiculum, whereas regular-
spiking cells project preferentially to the entorhinal cortex (Stewart, 1997; Funahashi et
al., 1999). Another important feature of pyramidal neurons in the subiculum is their
ability to generate subthreshold membrane potential oscillations in the theta frequency
range of 4 to 9 Hz (Mattia et al., 1997b). Subicular bursting neurons fire doublets of
action potentials during these oscillations, which likely promote the spread of network
activity (Stanford et al., 1998; Staff et al., 2000; Menendez de la Prida and Gal, 2004).
Among the two major cell types, small neurons are present, possibly interneurons,
even if little is known about their similarity to hippocampal neurons (Menendez de la
Prida, 2006). About intrinsic connections, available data suggest that these are
different from that of CA3 and CA1, they have both columnar and laminar organization,
such that the bursting cells form a set of columns and the regular spiking neurons
integrate columnar activity along the transverse axis (Greene and Totterdell, 1997).
The extrinsic connections are more largely studied, since the subiculum is the major
source of efferent projections of the hippocampus. It can be viewed, therefore, as the
last step in the large loop of processing through the hippocampal formation.
1.3.6. Major fiber systems: the angular bundle
A major fiber pathway associated with the hippocampal formation is the angular
bundle, a fiber bundle located between the enthorhinal cortex and the pre/para-
subiculum. The angular bundle is the major route taken by fibers originating from the
entorhinal cortex, i.e. the perforant pathway and the temporo-ammonic pathway, as
they travel to all septo-temporal levels of the hippocampus. In addition, the angular
bundle contains commisural fibers of enthorhinal and presubicular origin and fibers
that are interconnected with the entorhinal cortex. Enthorhinal fibers also enter the

34. Introduction
20
hippocampus via the alveus at temporal levels, where they reach the CA1 region after
perforating the subiculum (Deller et al.,1996). The alveus is therefore also a major
route by which enthorhinal fibers reach their targets at CA1.
1.3.7. Major fiber systems: the fimbria – fornix pathway
This system constitutes a major conduit for subcortical afferent and efferent
connections. For some authors, the fimbria-fornix has analogy with the corticospinal
fiber system in the sense that along the pathway from the motor cortex to the spinal
cord different names are given to the bundle of fibers. In the same way, subcortical
afferent and efferent fibers from the hippocampal formation to the forebrain or the brain
stem receive the name of fimbria in a tract and fornix in another. In addition, the exact
transition between two tracts is difficult to define, so the name fimbria-fornix is used to
indicate the entire tract and also to emphasize the continuity of the fibers in the bundle.
At temporal levels of the hippocampal formation, the subcortically directed output
fibers extend obliquely in the alveus over the surface of the hippocampus and collect
in a bundle called fimbria (Wyss et al.,1980). The fornix is the continuation of this
bundle of hippocampal output fibers to the subcortical target structures. Both fimbria
and fornix carry fibers from the hippocampus and subiculum, together with fibers that
are travelling to the hippocampal formation (Daitz and Powell, 1954; Powell et al.,
1957). Many of the subcortical inputs to the hippocampal formation, including those
from the septal nuclei, the locus coeruleus, and the raphe nuclei enter via the fimbria-
fornix pathway (Andersen et al., 2007).
1.3.8. Major fiber systems: the dorsal and ventral commisures
A third major hippocampal fiber system is the commissural system, containing
connections to both homotopic and heterotopic fields in the contralateral hippocampus.
There is a minor group of fibers that are not considered as commissural, since they
are directed into the contralateral descending column of the fornix and innervate the
same structures on the contralateral side of the brain that receive the ispilateral pre-
and postcommissural fornix (Blackstad, 1956; Raisman et al., 1966; Laatsch and
Cowan, 1966; Laurberg, 1979). The dorsal hippocampal commisure is the route by
which the presubiculum contributes a major projection to the contralateral entorhinal
cortex.

35. Introduction
21
1.4. Structural and functional organization of entorhinal cortex
The enthorhinal cortex plays an important role in the flow of information through the
hippocampus. Is the beginning and the end in the loop that takes place in the
hippocampus, being the entry point for much of the sensory information and the main
circuit for processed information to be relayed back to the neocortex.
Even though historically divided into 7 laminar areas, in more recent studies six layer
subdivision is used (Burwell et Amaral, 1998). According to the latter description, there
are four cellular layers (II, III and V, VI) and two plexiform layers (I and IV). Another
subdivision that is commonly used classify the entorhinal cortex into two main regions,
the lateral enthorhinal area (LEA) and the medial enthorhinal area (MEA) (Witter,
1993; Insausti et al., 1997; Witter et al., 2000; Burwell et al., 1995) (Fig.1.2.D). LEA
occupies the rostrolateral part of the entorhinal cortex, next to the rhinal fissure. MEA
occupies the remaining triangular area with its tip medial to the LEA.
Regarding different neuronal types, layer II is populated by stellate and pyramidal
cells, both of which project to the dentate gyrus and CA3 (Hamam et al., 2000, 2002).
In layer III, most neurons are pyramidal cells, which give rise to the temporo-ammonic
and alvear projections to CA1 and the subiculum. Layer III also contains multipolar,
stellate, fusiform, horizontal, and bipolar cells, a large, heterogeneous group that also
contributes to the perforant pathway (Andersen et al, 2007). Layer V contains three
main classes of neurons: pyramidal cells, small spherical cells, and fusiform neurons.
All three types of layer V neuron should be considered projection neurons (Burwell et
Amaral, 1998). They also may function as local circuit neurons, connecting the deep
layers to the superficial layers. Layer VI contains a wide variety of neuron types
grouped according to the predominant distribution of their axonal plexus. Several of
the smaller cell types are generally classified as interneuron, especially on the basis of
their restricted axonal distribution. Most of these interneurons are likely GABAergic.
GABAergic neurons are found in all layers of the entorhinal cortex, although they are
most abundant in the superficial layers (Hamam et al., 2000, 2002).
The entorhinal cortex contains a large system of associational connections (Dolorfo
and Amaral, 1998). Different parts of the entorhinal cortex project to different
septotemporal levels of the dentate gyrus. Thus, these connections appear to relay

36. Introduction
22
information into a particular septotemporal level of the dentate gyrus (Dolorfo and
Amaral, 1998).
The lateral and medial components of the perforant and temporo-ammonic pathways
terminate along a superficial-to-deep gradient in the molecular layer of the dentate
gyrus and the stratum lacunosum moleculare of CA3 and along the transverse axis of
CA1 and the subiculum. Layer II cells give rise to the projection to the dentate gyrus
and CA3, and layer III cells project to CA1 and the subiculum (Dolorfo and Amaral,
1998b).
Although traditional usage applies the term perforant path to all entorhino-hippocampal
projections, they can be divided in the different branches including the perforant
pathway itself and the temporo-ammonic pathway previously cited. Entorhinal fibers
also reach CA1 via the alveus (i.e., the alvear pathway originally described by Ramón
y Cajal). In the temporal portion of the hippocampus, most of the entorhinal fibers
reach CA1 after perforating the subiculum (the temporo-ammonic pathway) (Gloveli et
al., 1997). In the septal portion of the hippocampus, most of the entorhinal fibers reach
CA1 via the alvear pathway (Deller et al., 1996). These fibers make a sharp turn in the
alveus, perforate the pyramidal cell layer, and terminate in the stratum lacunosum
moleculare (Deller et al., 1996) Both pathways demonstrate the same septotemporal
organization of their projections. Thus, certain portions of the entorhinal cortex project
to certain septotemporal levels of the other hippocampal fields.
The neocortical inputs to the entorhinal cortex of the rat comprise two groups: those
that terminate in the superficial layers (I–III) and those that terminate in the deep
layers (IV–VI). The first category delivers information to the superficially located
entorhinal neurons, which are the source of the projections to the dentate gyrus,
hippocampus, and subiculum (Burwell and Amaral, 1998). The second group has
greater influence on the deeply located cells of the entorhinal cortex, which receive
processed information from the other hippocampal fields and give rise to feedback
projections to certain cortical regions (Andersen et al, 2007). In general, the cortical
afferents that reach the deep layers terminate diffusely, whereas those that terminate
superficially have a more restricted mediolateral and/or rostrocaudal distribution. A
hypothesis proposes that the first group may constitute a set of information-bearing
inputs, whereas the second group may have more of a modulatory influence on the

37. Introduction
23
output of the hippocampal formation (Burwell and Amaral, 1998).
A substantial input to the superficial layers of the entorhinal cortex originates from
olfactory structures such as the olfactory bulb, the anterior olfactory nucleus, and the
piriform cortex. A second prominent cortical input to the superficial layers of the
entorhinal cortex arises from the laterally adjacent perirhinal and postrhinal cortices
(Andersen et al., 2007).
The entorhinal cortex receives its cholinergic innervations mainly from the septum, in a
topographically organized manner (Andersen et al., 2007). The major thalamic inputs
to the entorhinal cortex originate in the nucleus reuniens and the nucleus centralis
medialis (Van der Werf et al., 2002).
1.5. Functional role of the hippocampus
Typically, the hippocampus has been involved in memory. Data supporting this idea
derived from a very famous clinical case, the H.M. patient (Scoville, 1954). This patient
suffered from a form of intractable epilepsy, affecting both hippocampi and was treated
by a bilateral resection of the medial portion of the temporal lobes. Surgery produced a
profound memory loss. Reports by Scoville and Milner (1957) presented a detailed
neuropsycological assessment of H.M. and nine other patients with varying degrees
and locations of resection. These studies of pathological and surgical cases allowed a
better definition of the hippocampal role in memory functions.
First, Milner noted that damage to the medial portions of the temporal lobe affects long
term memory for new facts and events (anterograde amnesia) while memories from
early life remain intact. This suggested the medial temporal lobe as a transition zone in
the long term memory formation and not a permanent repository for memory.
Apparently, surgical resection produces no loss in general intellect or perceptual ability,
suggesting dissociation between memory and other features of cognition. Moreover,
the fact that other types of memory remained intact indicated that mesiotemporal
structures including the hippocampus and the parahippocampal region, were not
required for some forms of long-term memory. Today there is general consensus that
the hippocampal formation is mainly devoted to the formation of episodic memory
(Lavenex and Amaral, 2000; Suzuki and Eichenbaum, 2000; Stark et al., 2002;

38. Introduction
24
Norman and O’Reilly, 2003).
Biomedical research has increased our interesting in using animals for a better
understanding of hippocampal function in health and disease. Amongst the different
hypothesis of hippocampal function derived from animal research the most
outstanding is that of consider the hippocampus as a neural representation of the
space, or as a spatial cognitive map (O'Keefe and Nadel, 1978). In their seminal work,
O’Keefe and Nadel noted that some hippocampal CA1 neurons increased firing rate
when the rat was at a particular location in the environment (O'Keefe and Dostrovsky
1971; O'Keefe and Nadel, 1978). These place cells appear to perfectly match with
findings of behavioral deficits and much work accumulate in the following years. We
can summarize the hippocampal spatial correlates into three classes of cells: 1) place
cells in the hippocampus (O’Keefe and Conway, 1978), 2) head direction cells in the
dorsal presubiculum (Taube and Schwartzkroin, 1987; Taube, 1998) and 3) grid cells
in the medial enthorhinal cortex (Fyhn et al., 2004; Hafting et al., 2005). There is also
another type of spatial cells, that combines two of the previous ones, and it is the
place-by-directions cells in the presubiculum (Cacucci et al., 2004). The role of place
cells is signal the animal’s location, head-direction cells code for the direction of
heading and grid cells indicate the distance moved in a particular direction (Cacucci et
al., 2004). Altogether these cells provide the necessary information to build a neuronal
representation of the space. Adding to this spatial processing is also the temporal
coding. A true episodic memory system would incorporate the time of occurrence of
events as well as their location (Tulving and Markowitsch, 1998).
Regarding how convergence between spatial and temporal information is performed at
the neuronal level, it is believed that individual neurons behave as computing
elements, interacting one with each other by passing discrete packets of information
along their axons. The effect of large groups of cells acting in concert then produces
an integrated representation. Coordinated activity of all those neuronal ensembles can
be recorded as rhythmical EEG activity.
According to this conceptual framework, hippocampal rhythms play major functional
roles (Vanderwolf, 1969; Whishaw and Vanderwolf, 1973; Vanderwolf, 2000). The
hippocampal electroencephalographic signal (EEG) could be classified into four
different states, depending on the principal frequency band: theta, beta, gamma and

39. Introduction
25
high frequency ripples (Buzsaki et al., 2003). Each state correlate to a particular
behavior and is reflected by different firing patterns of hippocampal pyramidal cells and
interneurons. Theta oscillations (4-12 Hz) can also be divided into two different types,
the one that occurs during period of arousal and attention known as sensory theta
(Kramis et al., 1975; Sainsbury, 1998), and theta activity that is related to movements
(Rivas et al., 1996; Slawinska and Kasicki, 1998; Buzsaki, 2002). Pyramidal cells and
interneurons fire preferentially on specific phases of theta waves (O’Keefe and Recce,
1993; Skaggs et al., 1996; Harris et al., 2002; Mehta et al., 2002; Yamaguchi et al.,
2002; Huxter et al., 2003) (Fig.1.4). It has been proposed that the function of the
hippocampal theta rhythm is to coordinate and bind together neuronal activity (Skaggs
et al., 1996). Thus each theta cycle acts as a timing cycle against which the phase of
hippocampal pyramidal cell firing can be measured. There is ample evidence that part
of the spatial code involves the timing of cell firing relative to a clock wave,
represented by the EEG theta wave and associated interneurons (Traub et al., 1999).
On this view, each pyramidal cell acts as an oscillator that results from a sophisticated
set of mechanisms. Furthermore, different patterns of electrical activity can be
correlated with behavioral or psychological states.
The other major hippocampal rhythm, high-frequency ripples (100-200 Hz) (Fig.1.4),
occurs in conjunction with large irregular activity (LIA) state of the hippocampal EEG,
which are dominant during activities that do not imply movement, such as sleeping,
quiet resting, grooming, drinking, and eating (Ranck, 1973). Theta and LIA/ripples
appear to be mutually exclusive, never occurring at the same time (Andersen et al,
2007). It has been suggested that synchronized bursts of activity that occur in
hippocampal neurons during the ripples reflect the transfer of information from the
hippocampus to the neocortex as part of a memory consolidation process (O’Neill et
al., 2010; Mölle et Born, 2011). Interestingly, recent evidence supports this role of
ripple oscillations in memory consolidation. Using feedback-controlled stimulation
protocols, it was shown that selective elimination of SPW-ripples occurring during post-
training periods resulted in performance impairment in rats trained on a hippocampus-
dependent spatial memory task (Girardeau et al. 2009; Diba and Buzsaki, 2007;
Ahmed et al., 2008). More recently, optogenetic strategies have been incorporated to
better search for the role of specific populations of cells in brain oscillations and
behavior (Sohal 2009; Cardin 2009; Witten 2011).

40. Introduction
26
Figure 1.4. Differential role of hippocampal cell types during theta and ripple oscillations.
Schematic representation of neuronal firing profile in pyramidal cells (P), PV-expressing basket, axo-
axonic, bistratified, O-LM, and three classes of CCK-expressing interneurons, as studied in the
anesthetized rat. Image from Klausberger and Somogyi 2008
1.6. The somatosensory system
Perceiving the surrounding world involves collecting information using different
sensory modalities. One of these modalities forms the somatosensory system, which
groups all the peripheral afferent nerve fibers, and specialized receptors to convey
physical and mechanical information. In addition, there is also a type of inner
perception termed proprioceptive sensitivity, which includes all information from joints,
muscles and the inner part of the body. This information is used to monitor limb
movements and to guarantee execution of planned action or movement (Sarlegna et
al. 2006). Thus, sensory modalities operate within interconnecting, intermodal and
crossmodal networks, ensuring that the interactions with the environment are generally
multisensory, but initial steps of each different modality are well delimited within the
central nervous system.
The main input of the somatosensory perception is the skin, a highly complex organ,
innervated by a wide array of specialized sensory neurons sensitive to heat, cold,

41. Introduction
27
pressure, and pain (McGlone et Reilly, 2010). The different types of neurons provide
the classical definition of four sensitive modalities: tactile, thermal, pain and
proprioception.
Sensory receptors that are located on the entire body have their cell bodies situated
outside the spinal cord in the dorsal root ganglion, with one ganglion for every spinal
nerve (McGlone and Reilly, 2010). The axons of these cells form two pathways, the
dorsal columns tract (Fig.1.5A) and the spinothalamic tract (Willis and Westlund, 1997)
(Fig.1.5B). Receptors on the face form the trigeminal pathway (Welker and Van der
Loos, 1986), and these neurons have their cell bodies outside the CNS in the
trigeminal ganglion, with their proximal processes entering the brainstem (McGlone
and Reilly, 2010) and joining both the lemniscal and the spinothalamic tract (Fig.1.5C).
The degree of myelination of the axons determines the speed with which the axon can
conduct nerve impulses, and hence the nerve’s conduction velocity. The largest and
fastest neurons are called A, the proprioceptive neurons, such as the muscle stretch
receptors (Houk and Henneman, 1967; Lynn, 1975). The second largest group, called
A, include all the discriminative touch receptors (Lynn, 1975). The third group is the
Aδ and a fourth group includes C fibers, both of which convey temperature and pain
sensations (Darian-Smith, 1984; Lynn, 1975) (Table 1.1).
Figure 1.5. Somatosensory ascending pathways. A, The dorsal column-medial lemniscal pathway. B,
The spinothalamic tract. B and C taken from Pearson Education. C, The trigeminal pathway, from Felten
and Shetty Netter’s Atlas of Neuroscience, Second Edition, 2009.

42. Introduction
28
Table 1.1. Conduction velocity and diameter of different types of nervous fibers.
Diameter Conduction Velocity Function
A 13-22 m 70-120 m/s proprioceptive
A 8-13 m 40-70 m/s Tactile, pressure
A 1-4 m 5-30 m/s Pain, temperature, itch
C 0.2-1 m 0.2-2 m/s Pain, temperatura, itch
Most sensory systems en route to the cerebral cortex decussate at some point, as
projections are mapped contralaterally (Davidson, 1965; Emmers, 1965; Wall & Egger,
1971). Tactile and proprioceptive primary afferents, or first order neurons, immediately
turn up the spinal cord towards the brain, ascending in the dorsal white matter and
forming the dorsal columns (Lund and Webster, 1967). At the cervical level two
separated tracts can be distinguished: the midline tracts comprise the gracile
fasciculus conveying information from the lower half of the body (legs and trunk) and
the outer tracts comprise the cuneate fasciculus conveying information from the upper
part (arms and trunk) (Lund and Webster, 1967). The first synapse of primary tactile
afferents occurs in with the dorsal column nuclei, where the second order neurons are
located (Lund and Webster, 1967; Giesler et al., 1979). These neurons provide the
secondary afferents and cross the midline immediately to form a tract on the
contralateral side of the brainstem - the medial lemniscus – which ascends through the
brainstem to the next relay station in the midbrain, the thalamus (Lund and Webster,
1967).
The spinothalamic pathway is originated in the neurons of the superficial layers of
dorsal horn in the spinal cord. These neurons mainly receive synapses from neurons
located in the dorsal root ganglion, which convey information about pain and
temperature. The type of fibers from dorsal root ganglia making synapse onto dorsal
horn are Aδ and C. Once within the dorsal horn, the neurons located in the lamina I
(or the marginal zone) lamina II (or the substantia gelatinosa) and lamina V, which are

43. Introduction
29
named laminae of Rexed, send their ascending axons crossing the middle line at
spinal cord level and finally forming the spinothalamic tract. This pathway makes
synapses onto different structures on the brainstem and thalamus (Wall & Dubner,
1972; Welker, 1973).
Somatosensory information from the face is conveyed by the trigeminal nerve into the
trigeminal ganglion (Paxinos, 2004; Aronoff et al., 2010), the trigeminal nuclei
extending from the midbrain to the medulla. The large diameter fibers (A) enter
directly into the main sensory nucleus of the trigeminal nuclei and as with the
somatosensory neurons of the body, make synapse and decussate, joining the medial
lemniscus (Jones and Pons, 1998; McGlone and Reilly, 2010). The small diameter
fibers conveying pain and temperature enter the midbrain with the V cranial nerve, but
then descend through the brainstem to the caudal medulla, make synapse into the
spinal trigeminal complex, which comprises three regions: the subnucleus oralis,
interpolaris and caudalis and cross the midline (Paxinos 2004; McGlone and Reilly,
2009). The secondary afferents arising from the spinal trigeminal complex (mainly the
interpolaris and caudualis regions) cross to the opposite site and join the
spinothalamic tract, finally entering the thalamus, reaching different nuclei as the
ventroposterior medial nucleus (VPM) the posterior medial nucleus (PoM), zona
incerta (ZI) and the laterodorsal nucleus (LD). (Veinante et al. 2000; Dum et al. 2009;
Apkarian and Hodge 1989; Jones, 1998; Stewart and King, 1963).
The target of the lemniscal and spinothalamic pathways is the thalamus, which is
considered a gateway to the cerebral cortex, a relay structure also for all the other
senses (Harris, 1986; Ralston, 1991). The thalamus has not only the relay role: it plays
a major integrative role prior to projecting to the overlying primary sensory cortices.
The somatosensory thalamus can be divided into two major regions, the ventrobasal
complex including VPL and VPM, and the high order nuclei as PoM and ZI, where third
order synapses take place and drive afferents to the primary somatosensory cortex
(Jones, 1985; Steriade and Timofeev, 1997; Sherman, 2007). The somatosensory
cortex is mapped in a somatotopic manner, as described by Penfield in human
(Rasmussen and Penfield, 1947). Cortical areas involved in the somatosensation can
be divided up to eight different regions (McGlone and Reilly, 2010): a) primary
somatosensory cortex (SI), which is divided into four subregions, b) secondary
somatosensory cortex (SII) (Woolsey, 1946; Maeda et al., 1999; Coghill et al., 1994;

44. Introduction
30
Francis et al., 2000); c) the insular cortex and d) the posterior parietal cortex.
The primary cortical area (SI), is the main target for the thalamocortical inputs; from
this area the information reaches other secondary area (SII) and associative areas (as
the insular cortex). From thalamus the tactile and proprioceptive information reaches
SI, right after the information spreads to other cortical areas, through cortico-cortical
connections. These parallel connections take place in the layers II/III and in the
infragranular layers, and reaches association areas and high level processing. The
information of pain and temperature, at the same time that reaches SI from thalamus,
arrives directly to other cortical areas as the insular cortex (Dum et al., 2009)
SII receives inputs mainly from SI and projects back to the fields in the insular regions
(Schneider et al., 1993). The posterior parietal lobe is another cortical region that
receives somatic inputs similar in function to an association cortex; it combines
sensory and motor processing and integrates different somatic sensory modalities that
are necessary for perception (Gescheider et al., 2003, Ionta et al., 2011).
Basic principles of the somatosensory system are common amongst mammalians,
even if species developed particular features depending on evolutive adaptations.
Regarding the rat somatosensory system, the most distinctive feature is the wide
representation of the whisker in the neocortex (Petersen, 2007; Chapin and Lin, 1984).
Obviously this is due their mainly nocturnal behavior as they must gather information
concerning their surroundings without use of vision (Petersen, 2007).
The lemniscal pathway of the whisker sensory system starts in the whisker pad (Ebara
et al., 2002) (Fig.1.6). The primary afferents reach the principal nucleus of the
trigeminal ganglion (PrV) where the receptive field is well organized in structures
called barreletes (Nord, 1967; Arvidsson, 1982). These neurons fire action potentials in
response to a whisker movement and project to the ventral posterior medial thalamus
(VPM), repeating the same organized structure in a fashion that is called barreloids
(Veinante and Deschenes, 1999). The VPM barreloid neurons project to primary
somatosensory cortex, where they terminate in somatotopically arranged clusters in
layer 4 forming barrels. The layer 4 barrel neurons thus form the first layer of cortical
processing of sensory information (Woolsey and Van der Loos, 1970). The increasing

45. Introduction
31
complexity of sensory processing in higher brain areas is likely to be mediated, in part,
through interactions of parallel ascending pathways for processing whisker-related
information, is the paralemniscal pathway, or trigeminothalamic pathway, which
correlates with the spinothalamic tract.
Figure 1.6. The rat whisker
system. A,B, Body
representations in the primary
somatosensory cortex (SI),
modified from Welker (1971)
and represented in Hjornevik et
al. 2007. C, Schematic summary
of the vibrissal system of the rat.
Whiskers on the rats snout (rows
A, B, C, D, E and arcs 1, 2) is
represented by arrays of cellular
aggregates in the brainstem,
thalamus (VPm and Po)
and somatosensory cortex (S1).
Part of the schema was modified
by Durham and Woolsey.
In spite of the importance of the whisker system in the rat, the information from the
extremities (forepaw and hindpaw) is not less relevant in the study of the
somatosensory system. All the three modalities share similar structure and pathways,
but in particular they show the same magnitude/latency response structure for
hindpaw neurons, forepaw neurons, and whisker neurons (Aguilar et al., 2008). VPM
and VPL are neurophysiological homogeneous, even if there is a peripheral difference
between the discrete whisker pad and the continuous skin. The physiological
equivalence between the VPM and VPL is anatomically supported by the existence of
angular tuning maps in thalamic barreloids (Timofeeva et al., 2003), just as different
locations on the skin correspond to different spatial coordinates within a VPL cluster in
the ventrobasal complex. In the same way, the somatosensory cortex shows similar
physiological properties for the entire body surface. So in the rat, the properties of the
barrels cortex are not different from the cortex related to extremities and trunk (Chapin
and Lin, 1984, Seelke et al. 2012).

46. Introduction
32
Compared to the human somatosensory system, there are some relevant differences.
First, a different organization of the dorsal column tract includes both ascending
sensory axons and descending motor axons (Li et al., 1990; Kaas, 2008). As in
primates, the primary sensory afferents that project to the cuneate and gracilis nuclei
occupy the dorsal portion of the dorsal columns. In addition, corticospinal fibers from
motor cortex cross the brainstem midline at the caudal end of the medulla and in large
part traverse along the base of the dorsal columns filling the region between the grey
matter and the sensory tracts (Fig.1.7). Smaller portions of the corticospinal fibers form
separate funiculi that descend in the lateral and ventral spinal cord. Thus, complete
section of the dorsal columns alone results in both a sensory loss and a motor loss in
rats (Miller, 1987).
Figure 1.7. The rat paws ascending
system. A Ascending somatosensory
pathyways from the rat paws. (Science
Photo Library). B, Schematic
representation of the first synapse in the
spinal cord. From Fischbach and Nelson
Handbook of Physiology, 1977. Wiley
Online, 2011. C, Coronal section of the rat
medulla. A: Nucleus motorius n.vagi. B:
area postrema. C: Nucleus tractus solitarii.
D: Nucleus gracilis. E: Nucleus cuneatus.
F: Tractus spinalis n. trigemini. G: Nucleus
spinalis n. trigemini. H: Nucleus dorsalis
corporis trapezoidei. I: Reticular alba. J:
Nucleus olivaris. K: Tractus pyramidalis. L:
Nucleus reticularis lateralis. M: Nucleus
ambiguus. Modified from Ibe et al. Int. J.
Morphol. 2011.
Regarding the spinothalamic tract, a major difference in rat occurs at the overlapping
with the lemniscal pathway in the lateral ventrobasal complex (Peschanski and
Ralston, 1985). This overlap is somatotopically organized, that means that the same
area of the thalamus receives inputs from an area of the body through the both
pathways (Sherman and Guillery, 2002). Functionally, this means that in the rat,
neurons responding to noxious stimulation are intermingled with neurons exclusively

47. Introduction
33
responding to non-noxious stimulation (Yu et al., 2006). As in other mammalians,
representation of the trunk and the limbs is somatotopically organized in the rat, both
at the thalamic and at the cortical level. The forelimb has the major representation in
the ventrobasal thalamic complex and in the somatosensory primary cortex (Emmers,
1965). In mammals, the two different pathways for the somatosensory system show
some differences and similarities. But, an important issue is the existence of structures
for convergence between both pathways. One of these structures is the spinal cord,
because the axons of lemniscal pathway send collateral branches to the dorsal horn,
where they make synapses onto the superficial laminae. The peripheral fibers A and
C carrying information about pain and temperature make synapse onto the same
superficial layers in the dorsal horn. The neurons located in the dorsal horn are the
place for convergence between both pathways. The second structure for convergence
is the thalamus, the lemniscal pathway make synapses mainly onto the ventrobasal
complex (VPM and VPL), and the spinothalamic pathway make synapses over
different nuclei including ventrobasal complex (Ma et al. 1987). This convergence
increases the complexity of processing of somatosensory information that reaches the
cortex in a next step. Hence, the distributed processing of data at cortical level, in
different regions, produces a whole perception of the somatosensory inputs. Last but
not least, the somatosensory signals must be included in the neural network for
learning and memory, which intuitively include the hippocampus as key structure for
this purpose.
1.7. Neuronal mechanisms of episodic memory: a link between the mesial
temporal lobe and the somatosensory system?
Memory function is vital for animals to learn, adapt and react to environmental
challenges that impact on their survival. Some forms of memory are basic, involving
simple feedback mechanisms of reflex behaviors in invertebrate (Kandel and Tauc
1963; Alkon 1974) while others, like working memory or episodic memory, appears still
enigmatic. Amongst the different types of memory, perhaps episodic memory is the
more intimately related with human nature. Episodic memory is the memory of
autobiographical events (times, places, associated emotions, and other contextual
knowledge) that can be explicitly stated. This need for language in defining episodic
memory has become an insurmountable gap to better understand the neuronal
mechanisms. However, experimental paradigms have been devised to test for

48. Introduction
34
episodic-like memory in non-verbal animals (Clayton and Dickinson, 1998) so that the
specific attributes of an episode are separated into the ‘what’ happened ‘where’ and
‘when’ components. The ability to simultaneously integrate these features of unique
experiences is considered a valid definition of this memory type (Griffiths and
Dickinson, 1999).
Figure 1.8. A model system to study basic
principles of episodic memory. A, Both in
monkeys and rats, processed multi-sensory
information from neocortical association
areas (blue) projects to one or more
subdivisions of the parahippocampal region
(purple), before entering the hippocampus
itself (green). B, Current conceptual frame-
work for understanding the neuronal basis of
episodic memory (Eichenbaum et al, 2007).
Neocortical inputs regarding object features
(‘what') converges in the perirhinal cortex
(PRC) and lateral entorhinal area (LEA),
whereas details about location (‘where')
converge in the parahippocampal cortex
(PHC) and medial entorhinal area (MEA).
These streams then converge in the
hippocampus, which represents items in the
context in which they were experienced.
Modified from Eichenbaum 2010.
Basic information from different sensory modalities passes through different levels of
processing as it flows from the periphery to the different associative cortical areas
(Fig.1.8A). In the case of somatosensory information, the anatomy and physiology of
the pathway is very well known. However, less is known about how processing occurs
after the initial bunch of information diverges into various cortical streams, and how
they are fully integrated into a meaningful neuronal representation of the whole.
Apparently, this separation is still maintained within the parahippocampal region until it
is combined within the hippocampus (Burwell et al, 1995; Suzuki, 1996; Eichenbaum,
2010). Therefore, it seems that the parahippocampal region acts as a site of
convergence for cortical inputs and mediates the distribution of cortical afferents to the

49. Introduction
35
hippocampus so that it has been proposed as a major component of the circuitry
involved in neuronal formation of episodic memories (Eichenbaum, 2010; Fig.1.8A). In
turn, as we have previously discussed all along this introduction, the lateral and the
medial entohinal cortex from the parahippocampal region send separate projections to
the hippocampus itself. The pattern in which the fibers from both pathways terminate in
hippocampal targets differs between those arriving in CA3 and dentate gyrus and
those in CA1 and subiculum, in the way that information passing through entorhinal
cortex is combined on the same neurons in the dentate gyrus and CA3 but arrives in
separate neuronal populations in the subiculum and CA1. This supports the idea that
the hippocampus is able to either associate or distinguishes the different features of
the sensory stimuli from the context in which they occur (Witter et al, 2000). Thus,
understanding the neuronal mechanism that underlies these skills could provide a
better comprehension of how episodic memory works (Fig.1.8B).
We propose that understanding how somatosensory information invades the
hippocampus is essential in order to disentangle basic processes underlying episodic
memory. We envisage that better knowing the elementary response of the
hippocampus to somatosensory stimulation will broad our view to understand its
function in a wider perspective. We aim to provide a novel conceptual framework to
examine and understand the neuronal route that follows from encoding specific
aspects of items through the primary sensory systems to the most highly elaborated
representation at the temporal lobe, as a basis for episodic-like memory. This thesis
constitutes a first attempt in this endeavor.

50. Objectives
36
2. Objectives
In order to analyze neuronal mechanisms that underlie somatosensory information
processing by the hippocampus, we looked at the elementary somatosensory
responses from various perspectives. Therefore this dissertation is divided into three
principal sections that define three major scientific objectives:
 To understand the mechanisms of the hippocampal responses to peripheric
somatosensory stimulation from a system level perspective
 To analyze, at the individual cellular level, hippocampal somatosensory responses
in different hippocampal regions
 To understand the modulatory action of the brain state on hippocampal
somatosensory responses, by analyzing how the hippocampal and cortical states
change the response to a stimulus

51. Material and methods
37
3. Material and methods
3.1. Animals
We used adult Wistar rats (250-400 g) obtained from Harlan Laboratories and from our
animal facilities (Instituto Cajal). Rats were housed in groups of four animals per cage
under controlled conditions (temperature of 22±2°C and 12:12 light–dark cycle, lights on
at 7 a.m). The animals were given free access to food and water. All procedures met the
European guidelines for animal experiments (86/609/EEC). Protocols were approved by
the Ethics Committee at the Instituto Cajal and at the Hospital de Parapléjicos de
Toledo.
3.2. Surgical procedures
Rats were anesthetized with urethane (1.1–1.5 g/kg, i.p.). Urethane injection takes
approximately 30 minutes to induce a stage III-3, III-3/4 (Friedberg et al, 1999) of
anesthesia (deep anaesthesia). This state was monitored with the reflex responses
(pinch withdrawal, corneal, eyelid). Urethane anesthesia assures an almost constant
stage as long as the experiment is completed. Body temperature was kept constant at
37°C with a heating blanket.
Once the desired stage of anesthesia was obtained, the animal was fastened to a
stereotaxic frame and a cranial surgery was performed to place recording and
stimulation electrodes. Small holes of 2.0 mm diameter were drilled in the skull above
the hippocampus for extra- and intracellular recordings (AP: −3.9 mm from bregma, ML:
2.8-3.6 mm). In addition, in some experiments we obtained simultaneous cortical
recordings using either tungsten electrodes or saline-filled glass pipettes at 1.1-1.5 mm
depth (infragranular layers) within the primary somatosensory cortex (AP: 1 mm, ML: 3
mm).
Cortical recording was also used to monitor anesthesia, since EEG at stage III-3/4
corresponds to an oscillatory activity between activated states (UP) and silent states
(DOWN) in the cortical LFP. Two other small holes were drilled to place the CA3
stimulation electrode (AP: −1.2 mm, ML: 2.9 mm, angle 30º in the sagittal plane, 3.5
mm deep) at the contralateral hemisphere and the ipsilateral perforant pathway
stimulation electrode (AP: -7.0, ML: 3.5 mm from bregma, 3-3.5 mm deep). In some

52. Material and methods
38
animals, another hole was drilled at AP: -5.0 mm, ML: 1 mm, P: 7.3 mm for lemniscal
stimulation ipsilateral to hippocampal recording. (Fig.3.1)
Figure 3.1. Anatomical localization of
electrode recording/stimulation sites. A, 16-
channel recording probe covered the entire
hippocampus in a dorsoventral direction. The
same coordinate was used also for tetrode and
intracellular recording. B, The medial lemniscus
was recorded and stimulated by parallel stainless
steel electrodes. C, The perforant pathway was
stimulated by a concentric electrode. D,
Coordinated used for recording activity at the
somatosensory cortex, hind paw in this example.
3.3. Somatosensory stimulation
Somatosensory stimulation was delivered by inserting stainless steel needles in the
wrist of the paws and in the whisker pad. Stimulation consisted of biphasic electric
pulses of 1 ms of duration. Stimulation intensity was 4-6 mA. All responses correspond
to averages of 100 individual stimuli applied at a frequency from 0.5 to 0.1 Hz. Such a
peripheral stimulation can activate both the lemniscal pathway, which primarily conveys
faster tactile and proprioceptive information, and the non-lemniscal pathway, which
primarily conveys slower pain and temperature information (Khanna and Sinclair, 1992).
Nonetheless, we previously showed that with these high-intensity electrical stimuli any
contribution of the paralemniscal pathway to the short-latency responses (<50ms) in the
primary somatosensory cortex is at most redundant to the contribution of the lemniscal
pathway (Yague et al. 2011).
3.4. Stimulation of input pathways
CA3 and perforant pathway stimulation were performed with bipolar electrodes
(stainless steel). It consisted of biphasic square pulses of 0.2 ms duration and

53. Material and methods
39
amplitudes of 0.1–0.6 mA every 15 s. In order to verify that hippocampal responses
described in our experiment could be relevant for tactile processing, we also delivered
electrical stimuli (0.3-0.6 mA, 0.2 ms) directly to the medial lemniscus. Medial lemniscus
stimulation was delivered by bipolar electrdoes, to better embrace the bunch of fibers of
the lemniscal pathway.
Figure 3.2. Image of the
experimental recording
approach in one the the typical
configurations used. Two bipolar
concentric electrodes were used
for stimulation of the contralateral
CA3 (cCA3 stim) and the
ipsilateral perforant pathway
(iPP). Local field potentials were
recorded using a 16-channel
silicon array (16ch probe).
Intracellular signals were
recorded with glass pipettes.
3.5. Local field potential recordings
Multisite recordings of the local field potentials were obtained with linear silicon probe
arrays of 16 or 32 sites at 50 and 100 μm vertical spacing (NeuroNexus Tech) (Fig.3.2).
A subcutaneous Ag/AgCl wire was placed in the neck as a reference electrode. Silicon
probes were positioned to record from all strata simultaneously, from the CA1 to the
dentate gyrus, and the position was optimized by its characteristic population spike
response to suprathreshold CA3 stimulation. Extracellular signals were preamplified
(4× gain) and recorded with a 16- or 32-channel AC amplifier (Multichannel Systems,
models ME16-FAI-µPA-System and USB-ME32-FAI-System, respectively), further
amplified by 100, filtered by analog means at 1 Hz to 5 kHz, and sampled at 20
kHz/channel with 12 bit precision. Silicon probes were positioned guided by CA3 and
perforant pathway stimulation and their position was later confirmed using the red
fluorescent dye 1,1′-dioctadecyl-3,3,3′,3′-tetramethylindocarbocyanine perchlorate (DiI)
(Invitrogen) at the end of the recording session by retracting and reinserting the probe.
3.6. Recordings of single cell activity: tetrode and sharp recordings
Single-unit recordings were obtained using commercially available tetrodes (Thomas

54. Material and methods
40
Recording). Tetrodes were advanced through the different hippocampal strata and
guided by CA3 and perforant pathway stimulation. Intracellular recordings were
obtained with sharp electrodes and using a dual intracellular amplifier (Axoclamp 2B,
Molecular Devices). Sharp electrodes were made from capillary tubes with intraluminal
glass fibers (borosilicate, o.d. 1.5 mm, i.d. 0.86 mm; Sutter Inst) pulled with a Brown–
Flaming horizontal puller (Model P-97; Sutter Inst.), and filled with 2.5M potassium
acetate (electrode resistances: 40–100 MΩ). These recordings were included only if
membrane potentials were more negative than -60 mV and overshooting action
potentials were detected. Tetrode and intracellular data were continuously acquired at
20 kHz (CED1401 and Digidata 1440, respectively) together with at least one
extracellular channel. For both tetrode and intracellular recordings, the cisterna magna
was opened and the cerebrospinal fluid was drained to decrease pulsation of the brain
and favour stability.
3.7. Histology
At the end of the experiment the rat received an extra dose of urethane to induce a
deep state of anesthesia and proceed to the transcardial perfusion. Perfusion was done
through left ventricle. Animals were transcardially perfused through the ventricular
catheter with saline (PBS) followed by a fixative (formaldehyde). Brain was extracted
and stored in formaldehyde for a following histology. Histological preparations were
performed in order to verify the positions of both stimulation and recording electrodes.
Nissl staining protocol was carried out coronal brain slices, 40m thick. In some
experiments the recording probe was stained with red fluorescent dye and the
histological preparation was later visualized with fluorescent microscopy. This allowed a
better visualization of the electrode track.
3.8. Single-unit isolation and sorting
Single units activity was extracted from tetrode extracellular recording using a spike
sorting algorithm. For spike sorting, signals were high-pass filtered >300 Hz using FIR-
type digital filters and exported to Offline Sorter (OFS, Plexon Inc). Continuous data
were then thresholded at 4-5 standard deviations. Recording epochs exceeding this
value were stored obtaining spike waveforms of 1.4 ms duration (0.4 ms pre-threshold
and 1 ms post threshold) for each of the four channels of the tetrode (Figure 3.3A).
Units were sorted using a combination of an automatic clustering algorithm (K-means)
and manual refinement using OFS. Multiple approaches were used to optimize unit

55. Material and methods
41
isolation, including principal components analysis of the spike amplitude, the slide
amplitude (the waveform amplitude at a particular time) and other waveform parameters
such as interval between the peak and the trough (Figure 3.3B). Abnormal spike
waveforms were systematically discarded from the clusters. Both the autocorrelogram
and the cross-correlogram between units were carefully inspected for contamination of
the refractory period (2 ms), central bins asymmetries, abnormal interactions and other
possible artifacts. Cells with low firing rate (less than 100 spikes detected in the whole
stimulation session) were not sorted and were included in the multi-unit pool. We used a
MANOVA analysis to check for significant cluster separation (Hill et al. 2011).
Single units were classified in different categories that putatively represent different cell
types, i.e. pyramidal cells, granule cells and interneurons. Several waveform
parameters were used for cell type classification (Csicsvari et al., 1999; Sirota et al.,
2008), including:
a) the trough-to-peak duration
b) background firing rate histogram
c) the first moment of the autocorrelogram
d) an asymmetry index calculated from the relative amplitude of the positive peaks
that flank the action potential: Ai = (b-a)/(b+a) (Figure 3.3 C)
Figure 3.3. Unit sorting. A, Tetrode recordings (top) were high-pass filtered (>360Hz, bottom) to isolate
unit activity. Single units were subsequently identified using semi-automatic sorting algorithms which
allowed us to isolate a group of them (red, green and blue) as well as the stimulation artifact (green-yellow).
B, Example of the cluster plot obtained from the tetrode recording shown in A, by using the slice amplitude
(the waveform amplitude at a particular time) of two channels of the tetrode. Some individual units were
clearly separated from each other. Low rate firing cells were all included in background multi-unit activity
(MUA). C, Parameters used to calculate the asymmetry index.

56. Material and methods
42
CA1 pyramidal cells often fire complex-spike burst of 2 to 5 action potentials (Ranck,
1973) yielding a characteristic autocorrelogram, which together with other waveform
features further help to separate CA1 principal cells from interneurons. For granule cells
however, separation criteria are not straightforward and we mainly relied on the
asymmetry index, trough-to-peak duration and the modulation (theta, gamma) of the
background firing rate histogram. A number of sorted units (86/262) remained
unclassified.
3.9. Data analysis
3.9.1. Software and tools for data analysis
Local field potentials, unit activity and waveforms were all analyzed by routines written
in Matlab (The Mathworks, USA). Intracellular data was analyzed using tools from Spike
2 (CED, Cambridge) and Clampfit (Molecular devices).
3.9.2. Current source density analysis
Local field potentials can be decomposed into their local current generators by current
source density analysis (CSD). Using this approach we examined the associated
synaptic current sinks directly, while excluding volume-conducted effects. Hence, CSD
analysis (Nicholson and Freeman, 1974; Mitzdorf 1985) provides a significant
improvement in the ability to resolve how currents flow within a circuitry, according to
the location and time course of neuronal activity. The hypothesis is that sources and
sinks of the neuronal activity are related to the net transmembrane current Im of the
population of cellular elements enclosed in an arbitrarily small volume of tissue, defined
by the points (x,y,z) in rectangular coordinates. In this approximation the tissue is
considered isotropic and the second spatial derivative is calculated along the three
principal axes.
In our study, variation of currents is examined only in one direction, corresponding to
the dorso-ventral axis in which the 16-ch probe is inserted. In addition, the derivative is
calculated in a discrete domain, so the formula is reduced to the second spatial
derivative of the local field potentials (LFP) in one dimension of local field potentials

57. Material and methods
43
where y is the vertical coordinate and h is the distance between two electrodes.
The LFP signal is pre-processed subtracting the baseline average value, to avoid offset
artifacts. One-dimensional current source density (CSD) profiles were subsequently
interpolated using the function spline from Matlab and the color scale was optimized at
the highest and lowest values. Defective sites from the silicon probe and CSD signals
centered on defective sites were all excluded. These requirements resulted in different
reduction of data sample size depending on methodological demands.
3.9.3. ICA analysis
ICA has been used to identify and separate EEG signals (Bell and Sejnowski 1995;
Makeig et al. 2004). A challenging problem of signal processing is separating different
sources in a signal when only the mixture of them is given. This is possible when the
sources are statistically independent, and the result is a mixing matrix of weights for
each channel of recorded signal and for each source. Independent component analysis
(ICA) is a widely used approach to extract spatially distinct independent sources of
activity from mixed signals (Choi et al., 2005). Simultaneous multisite recordings are
required to estimate the different impact of several spatially localized and distant
generators into each sensor.
Recently, an ICA-based method was proposed for blind source separation of LFPs in
the hippocampal CA1 region (Makarov et al., 2010). This method focuses on the major
local LFP generators that are propose to capture the CSD profile of each independent
contributing pathway. We therefore choose to implement ICA analysis of LFP in order to
compare independent components underlying hippocampal somatosensory responses
with known CSD responses (Figure 3.4 A1, A2).
ICA components were extracted using the EEGlab toolbox for MatLab (Delorme and
Makeig, 2004). The ICA of u(t) returns the generator’s activation (or time courses) and
the voltage loadings (or spatial weights) of all LFP-generators
Where Vn is the matrix of the voltage loadings, sn(t) are the time course activation,
sigma is a conductivity of the extracellular space and In are the CSD loadings.

58. Material and methods
44
ICA analysis was applied to 16-channel recordings, virtually obtaining sixteen different
generators (figure 3.4 B). Usually only a few of them have significant amplitude and
different spatial distributions (voltage loadings, Figure 3.4 C1). The significance of a
component could be scored by the explained variance (figure 3.4 C2) and a threshold of
EV ≥ 0.05 was considered (Korovaichuk et al., 2010). The voltage loadings and
activations are given in arbitrary units (which mean that there is an ambiguity of the sign
considering the individual matrix, but it disappears when the matrix product is
computed).
Once LFP-generators have been extracted from the raw LFPs, we can analyze them as
if they were active alone. For example, we can construct virtual LFPs produced by a
single generator, say , from its voltage loading and activation. Therefore the CSD
analysis was performed for each of the virtually reconstructed signals (figure 3.4 E1),
obtaining a spatiotemporal map of the stream of currents generated by that specific
component (figure 3.4 E2).
Figure 3.4. ICA analysis. From a
multichannel LFP signal (A1, A2 is the
correspondent CSD) two matrices are
extracted by ICA analysis, the time
course for each generator (B) and the
voltage loading for each generator at
each channel (C1). The significance of
each generator is expressed by a
variance value (C2) and a voltage
loading curve (D). The matrix product
between one generator’s time course
and its voltage loading curve allows to
reconstruct a virtual signal in the two
variables, temporal and spatial (E1).
CSD analysis was applied to the
voltage loading curve for each
component to virtually reconstruct each
generator (E2)
In order to extract only stable and significant components, not only the EV coefficient
was evaluated, but also the reliability of results, comparing the components obtained
from two different time windows. At the first iteration the algorithm was applied to the

59. Material and methods
45
entire signal, at the second only a time windows of 300ms around the response interval
was extracted and concatenated to obtain a continuous signal.
The two groups of components were compared, measuring the distance between each
pair of component. The distance was calculated as the absolute cosine distance
between two vectors Vk and Vm, according to the formula
where
A total difference between two components gives values of 1, meaning they are
orthogonal. If the distance between two components was 0, it means that the two
components are parallel and could be overlapped (Makarov et al., 2010). Only
components that do not change depending on the time window are considered.
Cosine distance was further used to compare the voltage loading CSD of significative
components to the instantaneous CSD profile of the original signal. Distance values at
each time point were plotted in order to identify the time point of maximum
correspondence between the two signals.
3.9.4. Analysis of multi-unit activity
Multi-unit activity (MUA), which represents firing activity from a group of neurons near to
the recording site, was extracted from the 16ch silicon probes by high-pass FIR filtering
(>300 Hz) local field potential signals from the sites located at the stratum pyramidale of
the CA1 region and the granular layer of the DG. Peri-stimulus time histograms (PSTH)
were obtained by binning the MUA inter-spike interval data. Two different binning sizes
were used, at 5ms and 20ms. PSTH histograms from individual sorted neurons were
similarly obtained. PSTH from intracellulary recorded cells were calculated from the
corresponding inter-spike interval data after action potential detection. We used paired
t-test to evaluate whether the PSTH response in the first 100 ms after stimulation
(excluding any stimulus artifact) was significantly different than the baseline firing
occurring in the last 100 ms before the stimulation. The cases of no significant changes
were classified as no change group. In the cases of significant changes, we defined a