Elsevier

Neural Networks

Volume 62, February 2015, Pages 73-82
Neural Networks

2015 Special Issue
Computational model of visual hallucination in dementia with Lewy bodies

https://doi.org/10.1016/j.neunet.2014.09.001Get rights and content

Abstract

Patients with dementia with Lewy bodies (DLB) frequently experience visual hallucination (VH), which has been aptly described as people seeing things that are not there. The distinctive character of VH in DLB necessitates a new theory of visual cognition. We have conducted a series of studies with the aim to understand the mechanism of this dysfunction of the cognitive system. We have proposed that if we view the disease from the internal mechanism of neurocognitive processes, and if also take into consideration recent experimental data on conduction abnormality, at least some of the symptoms can be understood within the framework of network (or disconnection) syndromes.

This paper describes the problem from a computational aspect and tries to determine whether conduction disturbances in a computational model can in fact produce a “computational” hallucination under appropriate assumptions.

Introduction

Patients with dementia with Lewy bodies (DLB) frequently experience visual hallucination (VH), which Collerton, Perry, and McKeith (2005) aptly described as the phenomenon where “people see things that are not there”.

The distinctive character of VH in DLB appears at first glance to challenge the conventional theory of visual cognition. In DLB, hallucinatory images are mostly single entities, for example, an integrated image of a human or animal, and appear at the center of attention. The persistence of VH images is typically on the order of minutes but can sometimes be seconds or even hours, depending on the patient (Mosimann et al., 2006). What is most distinctive is that the image appears on a normal background scene, and at only the center of attention, a non-existing image is additionally superimposed. Also, the figure is consistent with the context and setting in which it appears (Collerton et al., 2005, McKeith et al., 2005, Perry and Perry, 1995). Hence, some cognitive functions appear intact, whereas others are hallucinatory.

We have conducted a series of studies aiming to understand the core mechanism of this dysfunction of the cognitive system, and to make experimentally testable predictions that may lead to a plausible etiology.

We have proposed that if we view the disease from the internal mechanism of neurocognitive processes, and if we also take into consideration recent experimental data on conduction abnormality (Catani and de Schotten, 2012, Catani and ffytche, 2005), at least some of the symptoms can be understood within the framework of network (or disconnection) syndromes, that is, hodotopical dysfunctions1 (Catani & ffytche, 2005). VH in DLB may have homology with some of other cognitive dysfunctions, including the conduction aphasia reported by Geshwind (1965), Rykhlevskaia, Uddin, Kondos, and Menon (2009); for a much earlier account, see Lichtheim (1885).

In VH of DLB, the prefrontal cortex (PFC) might be disturbed, but without intrinsic pathology; hence, one or more of the fasciculi connecting the PFC with the visual or temporal areas might be damaged but other connections could remain intact (Goedert, Spillantini, Del Tredici, & Braak, 2013).

Recent imaging technology provides a means of experimentally studying the possible deficits (Catani & de Schotten, 2012) of connecting fasciculi. Further discussion of the pathophysiology of VH associated with DLB will be a focus of future studies.

The present study describes the problem of VH in DLB from a computational aspect, and seeks to determine whether conduction disturbances in our computational model can produce a “computational” hallucination under appropriate assumptions. The main part of this proposal was presented in Fujii, Tsukada, Tsuda, and Aihara (2014).

Section snippets

Orbitofrontal cortex triggers top-down facilitation

The content and character of VH in DLB primarily reflect the nature of visual processing (Collerton et al., 2005), and VH is a consequence of dysfunction of the normal visual cognitive system. Thus, understanding the brain mechanisms underlying normal object recognition is of crucial importance.

Prefrontal network for object-related semantic knowledge

The role of the PFC–VLPFC/OFC in object recognition is, first, to generate a guess on the identity of the object. In the present context, the PFC receives, among others, the following three main streams of projections to create such a guess on the identity:

  • I.

    Pathway I, as shown in Fig. 1, conveys rapid visual information, probably via iFOF from the occipital visual systems (such as V2/V4) (Bar, 2003, Fenske et al., 2006, Thiebaut de Schotten et al., 2012).

  • II.

    Pathway II conveys expectancy and

Core mechanism of recurrent complex visual hallucination: a working hypothesis

We have proposed the following working hypothesis on the core mechanism of recurrent complex VH (RCVH) (Fujii et al., 2014):

Principal disorder: “Temporary conduction disturbance occurs somewhere along Pathway I”.

Consequently, the OFC’s prediction on object identity is made essentially on the basis of only the context input and the expectancy—emotion inputs.

In addition, we proposed that the following complementary disorder may occur at the same time:

Complementary disorder—“Conduction disturbance

Object representation in the IT with top-down facilitation

The IT network receives an index from the PFC, and this biasing signal could activate object representation even without inputs from the visual cortices (Bar, 2004, Bar, 2006, Kastner and Ungerleider, 2001, Tomita et al., 1999). We postulate that this situation may occur in VH associated with DLB. We emphasize that IT neurons are activated by top-down signals without bottom-up sensory input (Bar, 2004, Tomita et al., 1999). Moreover, attentional biasing signals can be generated in the absence

Computational model of visual hallucination

This section presents a computational model of RCVH. An overall structure of the present model is shown in Fig. 3; the model is a unidirectionally coupled system of two neural networks.

The PFC–IT interaction has been postulated to be bidirectional in that the two cortices may communicate as a process such as biased competition in object recognition (Desimone, 1998, Fink et al., 1996, Fink et al., 2000, Grill-Spector, 2003, Henderson and Hollingworth, 1999, Shimamura, 2000). However, our

Summary and discussions

In this paper, we proposed a computational model of the PFC–IT complex to elucidate the neural mechanism of RCVH in DLB. Simulation results suggest the possibility that deficits of visual information in the PFC bring about a hallucinatory index, which in turn cause the production of a mismatched visual object image in the IT.

As stated in Section  4, the hallucinations in DLB may occur due to the two disconnection events, the principal and complementary disorders. The PFC–VLPFC and OFC are

Acknowledgments

We would like to express our special thanks to Daniel Collerton for valuable discussions and offering a number of critical improvements on RCVH of DLB. Thanks are also due to Guy Sandner and Yuichi Katori for their valuable discussions. The first, second and fourth authors (HT, HF, and IT) were supported by a Grant-in-Aid for Scientific Research on Innovative Areas (No. 4103) (21120002) from Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan, and partially supported

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