Function Plasticity in Cognitive Aging

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Table of Contents

Abstract
Introduction
Hypothesis
Purpose and importance of research
Methodology
Results
Implications for future research
References

Abstract

Currently, the amount of literature that is still being researched concerning the cognitive functioning-aging relationship is increasing at such a fast pace that it is gradually becoming difficult not only to assimilate all the new findings but to also to tell the difference on whether or not progress is being made in the process of shading more light on the fundamental issues concerning cognitive aging.

Given that research on issues of cognitive aging is rapidly increasing in different directions, cognitive research is now made up of numerous topics that contain a wide range of subtopics one of which entails the study of the relationship between the human brain’s functional plasticity and cognitive aging.

The brain of an adult human being has the capability of undergoing plastic changes and this research paper will examine different works of literature that cover the relationship between functional plasticity and cognitive aging.

Introduction

When talking about an aging mind, the common mental dimensions that come to mind are a range declining human cognitive abilities including attention, processing speed, learning, memory, and reaction time, just to mention but a few.

The aforementioned deterioration in the functioning of the brain has led to a perspective that is commonly referred to as the “wear and tear” hypothesis of cognitive decline due to aging (Aldwin and Gilmer, 2004). According to this perspective, the brain’s activities simply wear down as an individual advance age-wise.

The observed anatomical and consequent functional changes occur naturally in any biological organism or mechanical machine that has been in operation for a lengthy time and therefore, the natural conclusion of the tear and wear hypothesis is that it not only normal but also irreversible and inevitable to decline in cognitive activities.

While it is rather obvious that the brain’s physical aging plays a vital role in age-related cognitive decline, it is increasingly becoming lucid that the inevitable physical deterioration associated with an aging brain cannot completely account for the numerous changes in brain functioning that is observed in adults especially the aged ones (Friedan, 1993).

The common association of the aging mind with widespread and cognitive decline is slowly sidelined owing to the recognition that some aging individuals maintain their mental acuity well into very advanced ages.

Recent findings by scientific researchers are providing a growing number of reasons that tend to suggest that there are ways through which older individuals can be assisted to maintain more of their cognitive functions into later years.

Research has revealed that the adult human brain has, in fact, a much higher capacity for plasticity that had been believed before given that it still grows new dendrites and maybe, even new neurons. Moreover, an adult brain is known to positively respond to a myriad of biochemical interventions and life experiences.

The extensive available literature covering plasticity of the brain and the perceptual psychophysics of aging strongly emphasize that the negative consequences of brain plasticity is a significant contributor to cognitive decline related to advancements in age.

As individuals grow older, their strengths of brain engagement and their schedules change substantially and occur simultaneously by the active degradation of the functions of their brains. Research has given reasons to believe that such changes in the utilization of the brain and engagement are direct and vital contributors to the cognitive decline associated with advancements in age.

Hypothesis

The decline the cognitive functions of the brain are not only as a result of advancement in age but also as functional brain plasticity.

Purpose and importance of research

It is a well known fact that the fraction of the US population classified as aged is on the increase. As this proportion of older individuals grows, it is increasingly becoming very important to understand the changes in cognitive functioning that occur in these individuals due to their advancements in age.

For the numerous aging individuals who are still in good physical condition, decline in cognitive functioning can pose big threats to their ability to continue participating and enjoying their favorite activities while for those whose physical activity is limited, a decline in cognitive functioning can be a significant threat to their quality of life.

It is for these reasons that this paper will explore literature covering scientific findings that reveal ways through which the cognitive functions of aged individuals deteriorate.

Methodology

The findings of this research paper were derived from numerous secondary sources which have documented on the relationship between brain plasticity and cognitive functioning of the brain.

Results

The term brain plasticity is used to refer to the life-long functional and physical capacity of the brain. It is this capacity that explains how the experiences that one goes through in life induces the individuals learning ability.

As noted by Tonga (2000), the concept of plasticity of the human brain has been the subject of extensive studies for more than a century and its study is still continuing. Traditionally, the concept of brain plasticity is mostly discussed in detail in the contexts of recovery from strokes, early childhood development and perceptual learning than in regard to the process of aging.

Before the introduction of this concept on life-long plasticity, numerous researchers held the belief that the human brain was hard-wired in early life (Bruer, 2000). The evidence that supported this view pointed out that the human brain developed the physical structures and long-range interconnections that determine the neurological brain functioning during the early critical period of child development.

Researchers in those days established that, during this critical period, the brain had the capability of substantial remodeling in response to alterations in input, but after the critical period elapsed, it was generally observed that the brain was incapable of any significant further growth, elaboration or remodeling.

This idea that the brain developed in its immutable long-range interconnections in early life contributed to the belief that age-related cognitive decline was inevitable and irreversible and this observation, according to Wright and Sugarmann (2009), has since been proved to be inaccurate.

Today, after several decades of accumulated cross-disciplinary research, a new and very different view has emerged about the maintenance and origin of human abilities.

This view proposes that the brain is plastic and that it is capable of several functions at any period throughout adult life, including the capability of reorganization which includes the ability to develop short-range interconnections. Numerous brain plasticity experiments have illustrated in several essential ways in which progressive learning alters brain machinery.

Brain plasticity has several positive consequences, as shown through the examination of competitive processes, which generally underlie all brain plasticity. In cognitive-perceptual and motor skill learning tasks competitive processes result in the narrowing of time and space constants that define the selectivity of processing in cortical networks.

In this manner, the selective responses of cortical neurons specialize to meet the specific demands of the task. In behaviors or tasks that require a high level of skills, the brain machinery is progressively refined in its specificity, fidelity and selectivity through competitive processes.

Competitive processes increase the representative power of behaviorally significant sensory input and motor outputs as manifested by increased response magnitude and distributed response coherence. This is largely achieved by plasticity responses that increase cortical connectional strengths between neurons in nearly simultaneously exited cortical networks.

A notable effect of this learning-induced change is to strengthen the signal-to-noise ratio of relevant cortical activity. Enhancement of the signal-to-noise ratio is likely to be an essential mechanism by which learning improves brain function.

The outcome of these competitive processes is positive because, through the locally adaptive processes by which the brain specializes to represent salient input, the brains processing machinery becomes more locally and globally adapted to perform important behavioral tasks. As a general principle, brain plasticity with positive consequences is likely to underlie virtually all forms of perceptual and skill learning in the brain.

Brain plasticity also has some negative consequences that can be explained by examining how brain plasticity underlies all forms of learning, as illustrated above. Given that plasticity processes are inherently competitive, there will always be a competitive “winner” or “loser”, which appears in the form of excitatory and inhibitory synaptic changes, respectively.

This, therefore, implies that plastic changes with negative consequences are just as common as those that have positive consequences. Plasticity can be manipulated by adjusting the learning context. This is illustrated by the fact that it is possible to actively degrade and weaken brain processing machinery by just as quickly as it is possible to elaborate, refine and elaborate the processing machinery.

Even though there are several examples that elaborate how negative plastic changes can be actively induced, these changes are most likely to occur naturally in later stages of life. For instance, as people grow older, they commonly begin to stereotype and simplify behaviors that previously were quite complex and elaborated.

The brain is likely to automatically adjust to these less complex behaviors by simplifying its representations that represent them. These changes are referred to as brain plasticity with negative consequences because, through the locally adaptive processes by which the brain specializes to represent salient input, the brain’s processing machinery becomes less locally and globally adapted to carry out critical behavioral tasks.

Brain plasticity has negative consequences which can be related to cognitive decline related to aging. This can be described by examining the functioning of the human forebrain processing machinery which is sustained in a powerful, refined and efficient powerful state of operation by its intensive utilization under challenging situations.

During adulthood, the constant active interaction with areas that are demanding to cognitive, sensory and motor systems is essential in maintaining cognitive fitness and brain health. As individuals grow older, a self-reinforcing decline in interaction with challenging environments and reduction in brain health considerably contributes to the decline in cognitive activities.

There are two conditions that may lead to this downward spiral of brain activities namely a reduction in the engagement and schedule of the brain and the initial loss in some functions of the brain which may be driven by a degradation of sensory inputs.

In most cases, both conditions result in the downward spiraling of the brain’s activities. In either situation, once the downward trend begins, it goes on through a series of interrelated events that strengthen a cascade of negative interactions which in turn result in a condition of worsened cognitive fitness and brain health. Research has identified four interrelated factors are both central and mutually reinforcing namely:

Reduction in schedules of carrying out activities
Noisy processing
A weakened control of neuromodulatory functions
Negative learning

The reduction of schedules of activities is the reduction in the schedules of inputs and actions that engage the brain and are necessary in refining existing skills and driving the process of new learning. It is also often referred to as the disuse of the brain.

According to the findings by Hultsch, Hertzog, Small and Dixon (1999), as individuals advance in age, they typically change their patterns of doing activities in such a way that there is a reduction in their level of engagement in activities that are cognitively demanding.

Even those individuals who normally possess a high level of cognitive activities typically scale down their stimulation levels either by making a conscious choice such as retirement or by unconsciously choosing to continues with only those activities in which they excel.

This result in a reduced overall stimulation of cognitive, sensory and motor systems and most importantly reduces the stimulation for novelty-detecting, reward, and attention neuromodulatory systems.

Noisy processing can be described as brain processing that produces weakly-salient, unreliable, low-fidelity cortical representations of sensory actions and inputs. This takes place when the deteriorated brain produces poor quality of brain signals and has to, therefore, adjust its time and space constants if it is to process these degraded signals, thus creating a noisy processing machine.

The weakened neuromodulatory control is the downward regulation of metabolism and connectivity of neuromodulatory control systems that is caused by age-related physical deterioration and the reduction of schedules of activity.

Aging normally results in the deterioration of activities such as metabolism, connectivity and the neuromodulatory control systems. A weakened neuromodulatory system weakens the brain’s control over its plasticity, therefore, reducing its learning rates and trapping the brain in unhelpful and inappropriate patterns of activation.

Negative learning is illustrated by behavior changes that accelerate cognitive decline, typically chosen when ordinary behaviors more difficult. As the reduction of activity schedules, noisy schedules and weakened neuromodulatory control interacts to make it more challenging for the aging individual to carry on with challenging activities.

These individuals normally adapt their habits in such a manner as to reinforce negative aspects of the sensory output and motor output. For instance, should the aging individual start experiencing difficulties in hearing the sound from certain devices such as a radio of telephone, the individual turn up the volume in these devices and this may increase signal distortion in the process of increasing loudness. This at times may result in frustrations since the individual may still not clearly hear the sounds being made.

Implications for future research

The findings explored in this research paper have revealed that indeed, there are ways of maintaining good brain health into old age. Future research should, therefore, focus on seeking ways of capturing the brain’s huge capacity which will enable scientists find ways of preventing and even reversing the negative effects that occur due to aging

References

Aldwin, C.M. & Gilmer, D.F. (2004). Health, illness and optimal ageing: biological and psychological perspectives. Thousand Oaks, CA: SAGE.

Bruer, J.T. (2000). The myths of the first three years: a new understanding of the early brain development and lifelong learning. New York, NY: Simon & Schuster Inc.

Friedan, B. (1993). The fountain of age. Virginia VA: Simon & Schuster.

Hultsch, D.F., Hertzog, C., Small,B.J., & Dixon, R.A. (1999) in Pushkar et. Al. (Sept 1999). Models of intelligence in late life. Psychology and ageing. 14(3)520-527.

Wright, R. & Sugarman, L. (2009). Occupational Therapy and Life Course Development: A Work Book for Professional Practice. West Sussex: John Willey and Sons.

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