Brain excitability and connectivity of neuronal assemblies in Alzheimer's disease: From animal models to human findings

https://doi.org/10.1016/j.pneurobio.2012.07.001Get rights and content

Abstract

The human brain contains about 100 billion neurons forming an intricate network of innumerable connections, which continuously adapt and rewire themselves following inputs from external and internal environments as well as the physiological synaptic, dendritic and axonal sculpture during brain maturation and throughout the life span.

Growing evidence supports the idea that Alzheimer's disease (AD) targets selected and functionally connected neuronal networks and, specifically, their synaptic terminals, affecting brain connectivity well before producing neuronal loss and compartmental atrophy.

The understanding of the molecular mechanisms underlying the dismantling of neuronal circuits and the implementation of ‘clinically oriented’ methods to map-out the dynamic interactions amongst neuronal assemblies will enhance early/pre-symptomatic diagnosis and monitoring of disease progression. More important, this will open the avenues to innovative treatments, bridging the gap between molecular mechanisms and the variety of symptoms forming disease phenotype.

In the present review a set of evidence supports the idea that altered brain connectivity, exhausted neural plasticity and aberrant neuronal activity are facets of the same coin linked to age-related neurodegenerative dementia of Alzheimer type.

Investigating their respective roles in AD pathophysiology will help in translating findings from basic research to clinical applications.

Highlights

► Early synaptic loss and dysfunction preceding plaque, tangle formation and neuronal loss, are the probable basis of cognitive impairment in AD. ► The pathological accumulation of oligomeric induces synaptic dysfunction and it elicits aberrant patterns of neuronal circuit activity. ► AD as disconnection syndrome. ► Functional neuroimaging techniques as promising diagnostic tools in the detection of AD.

Introduction

Alzheimer's disease (AD) represents the most common cause of dementia, accounting for 50–60% of all cases (Ferri et al., 2005), stemming from an age-related brain degeneration leading to progressive cognitive and behavioral impairments.

According to the World Alzheimer Report 2011 more than 36 million people in the world are presently affected by dementia, most suffering from AD. This number is expected to increase and the Alzheimer's Disease International estimated an escalation up to 115 million by 2050 with enormous social cost on both patient's families and National Health Service.

One of the most frightening aspects is that the cohort of initial symptoms heralding AD condition is preceded for a long time by a pre-symptomatic stage during which the disease hallmarks are already operative in destroying synapses and connections. The duration of pre-symptomatic stages is quite variable depending on the individual variability in the extent of defense properties including the amount of silent synapses for neuroplasticity mechanisms (for a review see Savioz et al., 2009). Along this track of reasoning, a paramount significance is represented by the Mild Cognitive Impairment (MCI; Petersen et al., 2001), a prodromal stage of the aging-related brain degeneration characterized by a measurable memory impairment (in this case is defined amnestic MCI), in some other cases associated with deficits in other cognitive domains, but not overt dementia (Petersen et al., 2001, Lautenschlager et al., 2005). For instance, the MCI subject is slightly cognitively impaired, but such impairment is not yet impacting with daily life skills and therefore the overall condition is not fulfilling the diagnosis of dementia. The estimated prevalence of MCI condition ranges from 10 to 20% in person older than 65 years of age (Petersen, 2011), and several longitudinal studies have shown that most persons with MCI are at increased risk for the development of dementia, with an annual MCI-to-AD conversion rate ranging from 6 to 40%, according to different series (Petersen et al., 2001, Jack et al., 2005). Indeed, in the MCI subjects the rate to AD progression is several tens of times higher than in the age/sex matched non-MCI elderly population. Recently (Albert et al., 2011), new criteria for MCI have been developed and the diagnosis – even in presence of little clinical deficits – is prompted when neuropsychological tests are associated to instrumental signs of neurodegeneration as revealed by cerebrospinal fluid (CSF), blood/flow brain measurements (PET/SPET) and volumetric Magnetic Resonance Imaging (MRI) markers combined to independent genetic risk factors (Rasquin et al., 2005, Alexopoulos et al., 2006, Dubois et al., 2007).

The most validated histopathological feature of AD brain is the presence of NeuroFibrillary Tangles (NFTs), intra-cellular fibers constituted by hyperphosphorylated aggregates of the microtubule-associated protein tau and extra-cellular deposition composed of amyloid-β (Aβ) peptide, neuritic plaques, somewhat triggering a progressive, selective and massive neuronal loss, primarily impacting on the hippocampal, mesial temporal and parietal cortices (Hardy and Revesz, 2012). These pathological features are based on animal models, follow-up studies in AD and autopsy studies performed on brains of patients in the advanced disease stage.

Now, neuroscientists are asking: What happens in the brain of a patient during early-stage of the disease, namely the pre-symptomatic one?

The classical amyloid hypothesis, which states that AD is caused by the accumulation of deposits containing pathological Aβ peptides, is partly challenged by the demonstrations that in experimental models Aβ induces disruption of connectivity within the neural circuitry, loss of synapses and reduction of synaptic plasticity in key brain regions well before plaque formation/deposition and death of neurons (Hsia et al., 1999, Chapman et al., 1999).

More recently, it has been investigated the effects of Aβ at the level on neuronal circuits (D’Amelio et al., 2011, Ma et al., 2010). In transgenic mice – harboring human Amyloid Precursor Protein (APP) mutant allele linked to familial AD – the accumulation of Aβ causes alterations of glutamatergic synaptic transmission and plasticity, which correlate with dendritic spine degeneration and deficit in hippocampal-dependent memory (D’Amelio et al., 2011).

The dendritic spine organization and its continuous modulation is the anatomical basis of the transient and time-varying connectivity among the neuronal assemblies when they cooperate within a given cognitive (e.g. learning), behavioral, sensory-motor and emotional tasks. This connectivity amongst different neuronal assemblies and networks is dynamically modulated in time (from a time window of weeks or days down to very brief one in the order of tens of milliseconds or even less) and plays a critical role in sustaining brain functions.

Growing evidence derived from neurophysiological studies on functional organization of human brain suggests that connectivity derangement largely contributes to the clinical AD phenotype (Minoshima et al., 1997, Kapogiannis and Mattson, 2011).

In this review, we will discuss recent findings of basic and clinical research indicating the effect of Aβ on neural networks and synaptic function in animal models, as well as the dynamic modifications of the neural network connectivity reported in early stages of AD as addressed via electroencephalographic recordings and other modern neurophysiological techniques.

Section snippets

Anatomy of neuronal circuits affected in AD

The hippocampal formation, including the hippocampus proper and the anatomically related regions (dentate gyrus, subiculum, presubiculum, parasubiculum and entorhinal cortex, Fig. 1), have been identified as the brain structure essential for memory function (Wang and Morris, 2010).

One of the most captivating features of hippocampal formation is its neuroanatomical organization (Amaral and Lavenex, 2007). It shows a highly dense associational intrinsic (Fig. 1) and extrinsic connections with

Lesson from animal models of AD

Animal models of human disease are an invaluable tool in basic and biomedical research being indispensable to closely follow-up in time the evolution of pathological processes that lead to specific AD-like phenotypes with a slow progression.

The mouse is the major species used in AD research, but significant additional insight has been provided from species such as the fruit fly Drosophila melanogaster, Caenorhabidtis elegans and two types of fish, the sea lamprey and the zebrafish (Götz and

How Aβ and tau attack the synapses?

The search for molecular mechanisms by which Aβ impairs synaptic transmission and plasticity and contributes to neurodegeneration, including synapse dysfunction, behavioral deficits and, ultimately, neuronal cell death, is the main interest among the basic and clinically oriented neuroscientists, and this field has grown over the last 10 years from a collection of tantalizing observations.

Here, we focus on the pathogenic interplay between Aβ, tau and synaptic ion channels, that all play a

Evidence for aberrant activity in neuronal networks of AD patients

The nature of AD symptomatology, which eventually affects many aspects of brain functions, in particular complex cognitive processes such as attention, visuospatial orientation, and language in addition to episodic memory, as well as the selective involvement of multiple cortical “convergence zones” (Arnold et al., 1991) have led to the conceptualization of AD syndrome as a disease of multiple, large-scale neural networks (Seeley et al., 2009).

By the time AD dementia is diagnosed clinically,

Acknowledgments

MDA is financially supported by PRIN 2009 (Projects for Research of National Interest) and by a grant from the Alzheimer's Association (NIRG-11-204588).

We are grateful to Dr. Annalisa Nobili for helpful discussion and revision of manuscript.

References (262)

  • B.D. Drever et al.

    The cholinergic system and hippocampal plasticity

    Behavioural Brain Research

    (2011)
  • B. Dubois et al.

    Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria

    The Lancet Neurology

    (2007)
  • S.K. Esser et al.

    A direct demonstration of cortical LTP in humans: a combined TMS/EEG study

    Brain Research Bulletin

    (2006)
  • P. Fernández-Tomé et al.

    Beta-amyloid25–35 inhibits glutamate uptake in cultured neurons and astrocytes: modulation of uptake as a survival mechanism

    Neurobiology of Disease

    (2004)
  • F. Ferreri et al.

    Motor cortex excitability in Alzheimer's disease: a transcranial magnetic stimulation follow-up study

    Neuroscience Letters

    (2011)
  • C.P. Ferri et al.

    Global prevalence of dementia: a Delphi consensus study

    Lancet

    (2005)
  • R. Ferri et al.

    Small-world network organization of functional connectivity of EEG slow-wave activity during sleep

    Clinical Neurophysiology

    (2007)
  • P.B. Fitzgerald et al.

    A comprehensive review of the effects of rTMS on motor cortical excitability and inhibition

    Clinical Neurophysiology

    (2006)
  • R. Freunberger et al.

    Alpha phase coupling reflects object recognition

    Neuroimage

    (2008)
  • K.J. Friston et al.

    Dynamic causal modelling

    Neuroimage

    (2003)
  • J. Gross et al.

    Task-dependent oscillations during unimanual and bimanual movements in the human primary motor cortex and SMA studied with magnetoencephalography

    Neuroimage

    (2005)
  • J. Hardy et al.

    Region-specific loss of glutamate innervation in Alzheimer's disease

    Neuroscience Letters

    (1987)
  • F. Hernández et al.

    GSK3: a possible link between beta amyloid peptide and tau protein

    European Neurology

    (2010)
  • K. Hofmann et al.

    The CARD domain: a new apoptotic signalling motif

    Trends in Biochemical Sciences

    (1997)
  • J.F. Hou et al.

    Intracellular amyloid induces impairments on electrophysiological properties of cultured human neurons

    Neuroscience Letters

    (2009)
  • Y.Z. Huang et al.

    Theta burst stimulation of the human motor cortex

    Neuron

    (2005)
  • G. Adler et al.

    EEG coherence in Alzheimer's dementia

    Journal of Neural Transmission

    (2003)
  • R. Albert et al.

    Error and attack tolerance of complex networks

    Nature

    (2000)
  • P. Alexopoulos et al.

    Progression to dementia in clinical subtypes of mild cognitive impairment

    Dementia and Geriatric Cognitive Disorders

    (2006)
  • D.G. Amaral et al.
  • S.E. Arnold et al.

    The topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer's disease

    Cerebral Cortex

    (1991)
  • P.V. Arriagada et al.

    Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer's disease

    Neurology

    (1992)
  • C. Babiloni et al.

    Global functional coupling of resting EEG rhythms is related to white-matter lesions along the cholinergic tracts in subjects with amnesic mild cognitive impairment

    Journal of Alzheimer's Disease

    (2010)
  • C.H. Bailey et al.

    Toward a molecular definition of long-term memory storage

    Proceedings of the National Academy of Sciences of the United States of America

    (1996)
  • A.L. Barabasi et al.

    Emergence of scaling in random networks

    Science

    (1999)
  • R.T. Bartus et al.

    The cholinergic hypothesis of geriatric memory dysfunction

    Science

    (1982)
  • D.S. Bassett et al.

    Small-world brain networks

    Neuroscientist

    (2006)
  • L.I. Binder et al.

    The distribution of tau in the mammalian central nervous system

    Journal of Cell Biology

    (1985)
  • S. Boccaletti et al.

    Synchronization in dynamical networks: evolution along commutative graphs

    Physical Review E: Statistical, Nonlinear, and Soft Matter Physics

    (2006)
  • H. Braak et al.

    On areas of transition between entorhinal allocortex and temporal isocortex in the human brain. Normal morphology and lamina-specific pathology in Alzheimer's disease

    Acta Neuropathologica

    (1985)
  • L. Bracco et al.

    Mild cognitive impairment: loss of linguistic task-induced changes in motor cortex excitability

    Neurology

    (2009)
  • S. Brassen et al.

    Late-onset depression with mild cognitive deficits: electrophysiological evidences for a preclinical dementia syndrome

    Dementia and Geriatric Cognitive Disorders

    (2004)
  • S.L. Bressler et al.

    Episodic multiregional cortical coherence at multiple frequencies during visual task performance

    Nature

    (1993)
  • P. Broca

    Localisation des fonctions cérébrales. Siège du langage articulé

    Bulletins de la Société d’Anthropologie

    (1863)
  • A. Brovelli et al.

    Beta oscillations in a large-scale sensorimotor cortical network: directional influences revealed by Granger causality

    Proceedings of the National Academy of Sciences of the United States of America

    (2004)
  • P. Brown et al.

    Cortical network resonance and motor activity in humans

    Neuroscientist

    (2001)
  • S.D. Buckingham et al.

    Nicotinic acetylcholine receptor signalling: roles in Alzheimer's disease and amyloid neuroprotection

    Pharmacological Reviews

    (2009)
  • E.A. Buffalo et al.

    Laminar differences in gamma and alpha coherence in the ventral stream

    Proceedings of the National Academy of Sciences of the United States of America

    (2011)
  • J.M. Buldú et al.

    Reorganization of functional networks in mild cognitive impairment

    PLoS One

    (2011)
  • M. Buscema et al.

    The I.F.A.S.T. model allows the prediction of conversion to Alzheimer disease in patients with mild cognitive impairment with high degree of accuracy

    Current Alzheimer Research

    (2010)
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