Lisa Marie Giocomo

Yasser eRoudi

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Frontiers in Neural Circuits

The neural encoding of space in parahippocampal cortices

Lisa M. Giocomo

Yasser Roudi

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NEURAL CIRCUITS
the complexity of various models. As proposed by Zilli (2012), 
an alternative perspective may be to classify models based on 
the mechanisms they use to encode, update, and read out posi-
tion locations.
A prominent feature of grid cells is their spatial scale, which is 
organized topographically, increasing progressively from dorsal 
to ventral medial entorhinal cortex (mEC; Hafting et al., 2005). 
Grid scale is characterized by two spatial measures; the distance 
between the grid nodes (spacing) and the size of the grid nodes 
(field size; Hafting et al., 2005). Soon after the discovery of the 
topographical organization in grid scale, a series of complemen-
tary in vitro studies described a myriad of biophysical prop-
erties which also showed a strong dorsal-ventral organization 
in mEC (Giocomo et al., 2007; Garden et al., 2008; Giocomo 
and Hasselmo, 2008; Boehlen et al., 2010 and for a review see 
Pastoll et al., 2012). The correlative changes in entorhinal cells 
at the systems and cellular level has resulted in several computa-
tional models utilizing single-cell mechanisms to determine the 
organization of grid scale (Hasselmo et al., 2007; Burgess, 2008; 
Navratilova et al., 2011). Some versions of oscillatory interference 
models have focused specifically on the in vitro finding that theta 
band oscillations measured in single mEC neurons decrease in 
frequency along the dorsal-ventral axis (Giocomo et al., 2007). 
These oscillatory interference models utilize elements of the 
intrinsic oscillatory activity, such as the oscillation frequency, 
to directly determine grid size and spacing. Barry et al. (2012) 
reviews how a cholinergic decrease in the frequency of theta band 
oscillations may mediate the expansion of grid scale observed 
in novel environments (Barry, et al., 2012), an idea supported 
by in vitro slice recordings showing a decrease in the frequency 
of the theta band resonance after the application of cholinergic 
agonists (Heys et al., 2010). However, as an alternative or even 
complementary mechanism, cholinergic activation may induce 
a change in grid scale by modulating the temporal spiking or 
integrative properties of layer II mEC neurons (see Pastoll et al., 
2012; Yoshida et al., 2012).
Spatial representations are thought to depend not only on 
grid cells but also on a multitude of other functionally special-
ized neurons in the parahippocampus. One of these specialized 
neuronal classes is head direction cells, which respond strongest 
when an animal faces a particular direction in the environment, 
irrespective of their behavior or location at the time (Taube 
et al., 1990; for a review see Clark and Taube, 2012). In mEC, 
head direction cells exist independently and co-localized with 
grid cells (Sargolini et al., 2006). This co-localization of head 
direction signals with grid cells raises the possibility that these 
The neural encoding of space in parahippocampal cortices
Lisa M. Giocomo* and Yasser Roudi
Kavli Institute for Systems Neuroscience and Centre for the Biology of Memory, Norwegian University of Science and Technology, Trondheim, Norway
*Correspondence: giocomo@gmail.com
Edited by:
Rafael Yuste, Columbia University, USA
Reviewed by:
Rafael Yuste, Columbia University, USA
As animals navigate through the environment, they use internal 
and external sensory cues to update their movements and suc-
cessfully locate food or nest sites. The rich repertoire of spatial 
behaviors characteristic of many species has spurred intense 
research into the neural basis for representing external space. 
For many years, the mammalian hippocampus has been consid-
ered a structure crucial for supporting the creation or storage of 
spatial information (O’Keefe and Dostrovsky, 1971; Eichenbaum 
et al., 1999). Yet recent research on other functionally special-
ized neurons, such as medial entorhinal grid cells, has indicated 
a wider brain circuit is likely involved in the neurobiology of 
spatial encoding. Grid cells are neurons that fire in spatially spe-
cific locations and form a hexagonal pattern of firing activity 
that covers the entire environment (Fyhn et al., 2004; Hafting 
et al., 2005). Despite frequent changes in the animal’s running 
speed and direction, the grid pattern remains periodic, suggest-
ing that the grid population may enable a coordinate system 
for metric based navigation (Hafting et al., 2005; McNaughton 
et al., 2006). The discovery of grid cells stimulated a wide vari-
ety of experimental and theoretical work aimed at elucidating 
the neural circuit underlying spatial representations in parahip-
pocampal cortices. In this Research Topic new experimental data, 
computational modeling, and discussion are presented with a 
focus on the mechanisms underlying the neural encoding of 
space. Here, we provide a brief overview of the different types 
of neurons in the spatial circuit and the relevant context for the 
papers included in this Topic.
Since the discovery of grid cells, computational modeling 
has been a key tool in generating hypotheses and theories to 
explain the origin of periodic and hexagonal firing patterns 
(For a review see Giocomo et al., 2011; Zilli, 2012). Generally, 
computational models of grid formation have been grouped into 
one of two classes; oscillatory interference models and network 
attractor models. Oscillatory interference models propose that 
multiple, velocity driven oscillators combine to generate peri-
odic patterns. Attractor network models depend on excitatory 
or inhibitory recurrent activity and use velocity signals to move 
a bump of activity across a neural sheet of grid cells. Models 
in both of these broadly defined categories have significantly 
evolved since their first inception (O’Keefe and Burgess, 2005; 
Fuhs and Touretzky, 2006; McNaughton et al., 2006; Burgess 
et al., 2007) and recent computational models have integrated 
a combination of elements from oscillatory interference and 
network attractor classes (see Hasselmo and Brandon, 2012). As 
computational work on grid cell formation continues to evolve, 
classification into two broadly defined groups may oversimplify 
Frontiers in Neural Circuits www.frontiersin.org August 2012 | Volume 6 | Article 53 | 1
Editorial
published: 17 August 2012
doi: 10.3389/fncir.2012.00053
(1999). The hippocampus, memory, 
and place cells: is it spatial memory 
or a memory space. Neuron 23, 
209–226.
Fuhs, M. C., and Touretzky, D. S. (2006). 
A spin glass model of path integra-
tion in rat medial entorhinal cortex. 
J. Neurosci. 26, 4266–4276.
Fyhn, M., Molden, S., Witter, M. P., Moser, 
E. I., and Moser, M. B. (2004). Spatial 
representation in the entorhinal cor-
tex. Science 305, 1258–1264.
Garden, D. L., Dodson, P. D., O’Donnell, 
C., White, M. D., and Nolan, M. F. 
(2008). Tuning of synaptic integra-
tion in the medial entorhinal cortex 
to the organization of grid cell firing 
fields. Neuron 60, 875–889.
Giocomo, L. M., and Hasselmo, M. E. 
(2008). Time constants of h current 
in layer II stellate cells differ along the 
dorsal to ventral axis of medial entorhi-
nal cortex. J. Neurosci. 28, 9414–9425.
Giocomo, L. M., Moser, M. B., and Moser, 
E. I. (2011). Computational models of 
grid cells. Neuron 71, 589–603.
Giocomo, L. M., Zilli, E. A., Fransen, E., 
and Hasselmo, M. E. (2007). Temporal 
frequency of subthreshold oscillations 
scales with entorhinal grid cell field 
spacing. Science 315, 1719–1722.
Hafting, T., Fyhn, M., Molden, S., 
Moser, M. B., and Moser, E. I. (2005). 
Microstructure of a spatial map in 
two neural populations may interact to some degree. A paper by 
Kubie and Fenton (2012) proposes that the head direction signal 
may support the computation, by grid cells, of serial locations in 
the direction the animal is facing. While the “prospective cod-
ing” modeled by Kubie and Fenton highlights a potential influ-
ence of head direction signals onto grid cells, experimental data 
suggests this relationship may be unidirectional. Whitlock and 
Derdikman (2012) present new data suggesting that the encod-
ing of direction by head direction cells does not depend on the 
calculation of position by grid cells. The authors demonstrate 
that, while the fragmentation of the spatial environment results 
in a break-down of the hexagonal firing patterns of grid cells, 
head direction cells retain their preferred tuning direction. The 
stability of head direction with spatial fragmentation may reflect 
the hierarchical nature of directional signals, which potentially 
arise from deep brain structures where vestibular cues, rather 
than spatial cues, dominate the neural response (see Clark and 
Taube, 2012).
The apparent flexibility in grid scale under conditions of novelty, 
experience, or fragmentation of the spatial environment may be 
reflected by hippocampal place cell signals, which have been pro-
posed as downstream targets for the grid cell output (Solstad et al., 
2006). Place cells are neurons in the hippocampus that tend to have 
higher firing rates when the rat is located in a specific portion of 
the environment (O’Keefe and Dostrovsky, 1971). Navratilova et al. 
(2012) presents experimental work showing that the directional 
selectivity of hippocampal place cells develops with experience. 
Initially, place cell firing on a linear track is determined by allocen-
tric position. With continued experience however, firing changes 
to respond to sensory information or behavioral cues, raising the 
possibility that these place cell representations undergo experience-
dependent plasticity.
One way to gain a deeper understanding of how these different 
spatial signals interact in the parahippocampal circuit is to study 
and compare their developmental time course. Work in very young 
animals has already demonstrated that specific features of place 
cells reach adult levels at an earlier age than grid cells (Langston 
et al., 2010; Wills et al., 2010). However, once grid cells are pre-
sent, they contain all of the essential features of the adult grid cell 
population (Wills et al., 2012). The developmental timeline of 
place and grid cells is also consistent with new data, in this Topic, 
suggesting that different types of spatial memories follow dis-
sociated timelines. While memory for objects alone develops at a 
very young age, memory for more complex associations between 
objects and spatial locations comes online at a later age (Ainge 
and Langston, 2012).
This Research Topic provides a unique collection of new data 
and discussion covering a broad scope of questions aimed at under-
standing the neural representation of external space. We encourage 
the reader to sample the full range of articles.
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Giocomo and Roudi The neural encoding of space
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Received: 28 June 2012; accepted: 27 July 
2012; published online: 17 August 2012.
Citation: Giocomo LM and Roudi Y (2012) 
The neural encoding of space in parahip-
pocampal cortices. Front. Neural Circuits 
6:53. doi: 10.3389/fncir.2012.00053
Copyright © 2012 Giocomo and Roudi. 
This is an open-access article distributed 
under the terms of the Creative Commons 
Attribution License, which permits use, dis-
tribution and reproduction in other forums, 
provided the original authors and source are 
credited and subject to any copyright notices 
concerning any third-party graphics etc.
Frontiers in Neural Circuits www.frontiersin.org August 2012 | Volume 6 | Article 53 | 3
Giocomo and Roudi The neural encoding of space
