Head direction, place, and movement correlates for cells in the rat retrosplenial cortex.

Cho, Jeiwon; Sharp, Patricia E.

doi:10.1037/0735-7044.115.1.3

Cited by 352 publications

(379 citation statements)

References 34 publications

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“…We hypothesize that posterior parietal cortex contains a representation of the animal's velocity relative to current head direction (likely in MSTd), and that this signal is projected to posterior cingulate cortex, where the global head direction signal from postsubiculum is used to resolve the velocity vector into allocentric map components. Posterior cingulate cortex is also connected to motor cortex (Cho and Sharp 2001) which supports the idea that it may be involved in path integration or navigational motor planning. We thus propose that our required velocity input reaches parasubiculum via posterior cingulate cortex.…”

Section: Role Of the Head Direction System And Availability Of Velocisupporting

confidence: 57%

A Controlled Attractor Network Model of Path Integration in the Rat

2005

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Cells in several areas of the hippocampal formation show place specific firing patterns, and are thought to form a distributed representation of an animal's current location in an environment. Experimental results suggest that this representation is continually updated even in complete darkness, indicating the presence of a path integration mechanism in the rat. Adopting the Neural Engineering Framework (NEF) presented by Eliasmith and Anderson (2003) we derive a novel attractor network model of path integration, using heterogeneous spiking neurons. The network we derive incorporates representation and updating of position into a single layer of neurons, eliminating the need for a large external control population, and without making use of multiplicative synapses. An efficient and biologically plausible control mechanism results directly from applying the principles of the NEF. We simulate the network for a variety of inputs, analyze its performance, and give three testable predictions of our model.

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Section: Role Of the Head Direction System And Availability Of Velocisupporting

confidence: 57%

A Controlled Attractor Network Model of Path Integration in the Rat

2005

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“…ATI is almost absent for the dorsal tegmental nucleus of Gudden; it is highly-expressed at the next hierarchical level in the mammillary bodies (40-75 ms) and less-expressed at the next hierarchical level of thalamic cells ( $ 25 ms). Further, at the neocortical level, the ATI in the retrosplenial cortex ( $25 ms) differs from the ATI of postsubicular cortex with values close to 0 (Blair and Sharp, 1995;Blair et al, 1998;Cho and Sharp, 2001;Sharp et al, 2001;Stackman et al, 2003;Taube and Muller, 1998). There is no evidence showing a link between ATI and the vestibular signal, which is proposed to follow a bottom-up direction (Taube, 2007), or between ATI and the motor efference copy (Bassett et al, 2005).…”

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confidence: 86%

Decoding signal processing in thalamo-hippocampal circuitry: implications for theories of memory and spatial processing

Tsanov

O’Mara

2015

Brain Research

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a b s t r a c tA major tool in understanding how information is processed in the brain is the analysis of neuronal output at each hierarchical level through which neurophysiological signals are propagated. Since the experimental brain operation performed on Henry Gustav Molaison (known as patient H.M.) in 1953, the hippocampal formation has gained special attention, resulting in a very large number of studies investigating signals processed by the hippocampal formation. One of the main information streams to the hippocampal formation, vital for episodic memory formation, arises from thalamo-hippocampal projections, as there is extensive connectivity between these structures. This connectivity is sometimes overlooked by theories of memory formation by the brain, in favour of theories with a strong corticohippocampal flavour. In this review, we attempt to address some of the complexity of the signals processed within the thalamo-hippocampal circuitry. To understand the signals encoded by the anterior thalamic nuclei in particular, we review key findings from electrophysiological, anatomical, behavioural and computational studies. We include recent findings elucidating the integration of different signal modalities by single thalamic neurons;we focus in particular on the propagation of two prominent signals: head directionality and theta rhythm. We conclude that thalamo-hippocampal processing provides a centrally important, substantive, and dynamic input modulating and moderating hippocampal spatial and mnemonic processing. This article is part of a Special Issue entitled SI: Brain and Memory.& 2014 Published by Elsevier B.V. IntroductionThe purpose of the present review is to dissect some of the complexity of the signals propagated from anterior thalamus to the hippocampal formation in order to try and understand the importance of this information processing for the coding properties of individual neurons in the hippocampus. "Anterior thalamus" includes the anterodorsal, anteroventral and dorsolateral thalamic nuclei, which form the thalamic component of the limbic system (the 'thalamic

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“…A further evidence for the above processing pathway is provided by a series of studies that have investigated the temporal properties of HD cells in LMN, ADN, and PoSC. During head turns, LMN neurons tend to anticipate the future head direction by approximately 40-75 ms (Stackman and Taube, 1998;Blair et al, 1998), ADN cells show a smaller anticipatory time delay of about 25 ms (Taube and Muller, 1998;Cho and Sharp, 2001), and PoSC cells tend to encode the current directional heading (Blair and Sharp, 1995). The DTN-LMN circuit seems also well suited to account for the additional property of the HD cell system of integrating the head angular velocity.…”

Section: Introductionmentioning

confidence: 99%

A Continuous Attractor Network Model Without Recurrent Excitation: Maintenance and Integration in the Head Direction Cell System

2005

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Abstract. Motivated by experimental observations of the head direction system, we study a three population network model that operates as a continuous attractor network. This network is able to store in a short-term memory an angular variable (the head direction) as a spatial profile of activity across neurons in the absence of selective external inputs, and to accurately update this variable on the basis of angular velocity inputs. The network is composed of one excitatory population and two inhibitory populations, with inter-connections between populations but no connections within the neurons of a same population. In particular, there are no excitatory-to-excitatory connections. Angular velocity signals are represented as inputs in one inhibitory population (clockwise turns) or the other (counterclockwise turns). The system is studied using a combination of analytical and numerical methods. Analysis of a simplified model composed of threshold-linear neurons gives the conditions on the connectivity for (i) the emergence of the spatially selective profile, (ii) reliable integration of angular velocity inputs, and (iii) the range of angular velocities that can be accurately integrated by the model. Numerical simulations allow us to study the proposed scenario in a large network of spiking neurons and compare their dynamics with that of head direction cells recorded in the rat limbic system. In particular, we show that the directional representation encoded by the attractor network can be rapidly updated by external cues, consistent with the very short update latencies observed experimentally by Zugaro et al. (2003) in thalamic head direction cells.

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Head direction, place, and movement correlates for cells in the rat retrosplenial cortex.

Cited by 352 publications

References 34 publications

A Controlled Attractor Network Model of Path Integration in the Rat

A Controlled Attractor Network Model of Path Integration in the Rat

Decoding signal processing in thalamo-hippocampal circuitry: implications for theories of memory and spatial processing

A Continuous Attractor Network Model Without Recurrent Excitation: Maintenance and Integration in the Head Direction Cell System

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