Losing Ground, Just By Having a Birthday! How, more exactly, do mental and physical performance abilities change as we grow older?
Several hundred studies have documented changes in processing speed associated with aging. There are many measured brain process “speeds;” they ALL slow down. See Salthouse TA (2000) Aging and measures of processing speed. Biol Psychol 45:35; (1996) The processing-speed theory of adult age differences in cognition. Psychol Rev 103;403. We have recorded processing speed as it relates to specific tasking in human populations (successive-signal masking and recognition for stationary, moving and divided-attention delivered stimuli; a variety of fluency tasks, in both vision and hearing). Average speeds always decline on the statistical average with age, but variability in performance also grows markedly with age—and some older individuals retain relatively impressive fast-speed operations.
When we analyze the bases of changes in speed, we see that almost every neurological time constant is longer in the average (but not every individual) older brain. In Salthouse’s analysis, again, every (average) operational speed measured behaviorally was similarly slowed (see ibid). Speed changes stem a) from the greater temporal dispersion of inputs feeding cortical areas; b) from longer time constants expressed by excitatory and especially inhibitory processes; c) from a growing weakening of faster vs slower-acting transmitter receptor subtypes; d) from a prolongation of post-excitatory suppression in elemental synaptic processes; and e) from changes in local and long-range demyelination. It is quite clear that when brain speed changes, almost everything (if not everything) that contributes to that speed changes, in a slowing direction. There is one interesting exception: The strength of fast inhibitory processes normally weaken, to the extent that the modulatory response characteristics of neurons in the cortex support faster successive-signal responding (because post-excitatory inhibition is weaker). This change confers no behavioral advantage because the responding in such an inhibition-impaired brain is so noisy that information that comes from signal processing with such degradation declines dramatically. See de Villers-Sidani et al (2010) Recovery of functional and structural age-related changes in the primary auditory cortex with operant training. PNAS 107:13900.About 30 years ago, the great comparative neurobiologist Ted Bullock asked the simple biological question “Why are sloths slow”. The answer: Because every timed biological process in the brain and in their body that he measured operated with a longer time constant than in the rest of we mammals (begin with Toole JF, Bullock TH (1973) Neuromuscular responses of sloths. J Comp Neurol 149:259). What was astounding to me at the time that I read this work and heard the marvelous professor Bullock talk about it is that ALL of these processes could change in a slowing direction together—which seemed to require an impossible number of underlying genetic revisions! It is no longer a mystery, because for all of we mammals, just getting older results in changes in gene expression that contributes to an equivalent almost-universal-process slowing. Perhaps getting older really IS all about getting more slothful! [A question for any scientist who might be interested: What is the level of background chatter in play in the sloth’s brain? Are these complex, linked biological changes resulting in slothfulness a consequence of a unique positive or a not-so-unique negative source that distinguishes them functionally from the rest of we mammals? Of course some of you readers might see this as a question that is only of interest to another sloth, but……..]
As we have earlier repeatedly cited, we and others have documented a change in the time constants controlling stimulus recognition as a function of age, or in different chronically ill or brain-injured cohorts. The extensions of time required to identify successively presented inputs, for example, are, on the average, substantially longer in older (or in every other cognitively impaired) populations.It might be noted that many impaired populations also lose the ability of time-keeping itself. The neurological ability to know whether one or two or four or six seconds have passed by is a little complicated to talk about mechanistically. Suffice it to say that we believe that we understand this science, and have created training instruments to help recover this special high-level ability based on that understanding.Many individuals have tried to document changes in reflexive or explorative eye movements to visual stimuli to reconstruct how the eyes are attracted to or explore objects of interest, as a function of age. See, for example, Munoz DP et al (1998) Age-related performance of human subjects on saccadic eye movement tasks. Exp Brain Res 121:391; Irving EL (2006) Horizontal saccade dynamics across the human lifespan. IOVS 47:1478; Warabi T et al (2004) Effect of aging on the accuracy of visually guided saccadic eye movements. Ann Neurol 16:449; Daffner K et al (1994) The impact of aging on curiosity as measured by exploratory eye movements. Arch Neurol 1994; Abel LA, Douglas J (2007) Effects of age on latency and error generation in internally mediated saccades. Neurobiol aging 28:627; Beurskens R, Bock O (2012) Age-related decline in peripheral visual processing: the role of eye movements. Exp Brain Res 217:117.I identify the MIT professor Jim DiCarlo as making the most convincing arguments that the richer exploration of stimuli via repeated eye movements—more strongly expressed in young vs older individual—is a key to accurate recognition. For example, see DiCarlo JJ et al (2012) How does the brain solve visual object recognition? Neuron 73:415. The repeated re-sampling of visual inputs via rapid peri-object saccades appears to be substantially influenced/controlled by working memory; see, for example, Mannan SK et al (2010) Early oculomotor capture by new onsets driven by the contents of working memory. Vision Res 50:1590.
Speed is one of the primary factors that has been argued to underlie intelligence. See, e.g., Carrol JB (1997) The three-stratum theory of cognitive abilities. IN: Contemporary Intellectual Assessment: Theories, Tests, and Issues. Flanagan DP, Genshaft JL, eds., Guilford, New York. These arguments stem back to the measurement of response time by the 19th Century genius, Francis Galton. In the factor analysis approach to defining the bases of intelligence, a number of the “independent factors” are (as shown by neuroscience studies) also clearly dependent on neural processing speed. Indeed, Jensen has shown that speed of processing accounts for 50% or more of the variance of IQ (g). See Jensen R (1980) Chronometric analysis of intelligence. J Soc Biol Struct 3:103.
We commonly record correlated changes in representational accuracy and speed in variously impaired (including aging) brains. For a human example (which also relates these representational qualities to memory), see, e.g., Schneider BA et al (2002) Listening in aging adults: from discourse comprehension to psychoacoustics. Can J exp Psychol 56:139. Our general explanation: The less accurate the brain’s neurological representation of what it sees or hears or feels, the longer it takes to “get the answer right,” i.e., to resolve what it is being seen or heard or felt. By adjusting its processing speed on the basis of its “getting the answer right” (which, remember, results in the release of chemical modulators of brain change) that crucial accuracy-speed relationship is maintained.
Hundreds of studies document (and no one needs to be told about) memory losses—which apply to different extents for all aspects of remembering—with aging. See, e.g., Salthouse TA (2003) Memory aging from 28 to 80. Alz Dis Assoc DISORD !&;162; Kausler DH (1994) Learning and Memory in Normal Aging. Academic Press; Naveh-Benjamin M, Ohta N (2012) Memory and Aging: Current Issues and Future Directions. Psychology Press.
Scientists have repeated shown that memory is degraded when information is represented in noisier forms. For example, Seichepine DR et al (2012) Luminance affects age-related deficits in object detection: implications for computerized psychological assessments. Psychol Aging 27:522; Pichora-Fuller MK (2003) Cognitive aging and auditory information processing. Int J Audiology 42:26.
Many authorities publically claim that crossword puzzles, Sudoku, et alia are a very good thing to engage in for sustaining your brain health. Alas, large population studies determining which life-style factors contribute to successful aging have NOT been able to show much if any benefit attributable to regular puzzling—as compared, for example, to more formal computer controlled training or to different forms of physical or physical/cognitive (e.g., dance) exercise. In a recent study document benefits of our training approach, spending daily time doing crossword puzzles was the ‘control condition’. No gains in cognitive ability could be attributed to it (see Wolinsky F et al (2013) A randomized controlled trial of cognitive training using a visual speed of processing intervention in middle-aged and older adults. PLoS One 8:361624).Regular puzzle-hounds just don’t do much better—if any better—than other age-matched folk.
The degradation of our ability to suppress distractors of either external or internal origin with age has been repeatedly documented in behavioral and brain imaging studies; and the susceptibility to distractors has been shown to directly contribute to forgetfulness in older and otherwise-impaired individuals. See, as an introduction to this rapidly growing literature, Gazzaley A, D’Esposito M (2007) Top-down modulation and normal aging. Ann NY Acad Sci 1097:67.
Many studies have shown that the strength of modulation of brain activity by attention is weaker in most neurologically and psychiatrically impaired populations. That modulation is largely controlled by the release of the neuromodulator acetylcholine. On the statistical average, acetylcholine-based modulation progressively weakens as the decades pass by. For an introduction to this literature, see, for example, Pekkonen E et al (2005) Cholinergic modulation of preattentive auditory processing in aging. Neuroimage 27:387; Sarter M, Bruno JP (2004) Developmental origins of the age-related decline in cortical cholinergic function and associated cognitive abilities. Neurobiol Aging 25:1127. As I point out later, by the time you receive a MCI diagnosis, there is so little acetycholine being produced in the brain that it is quantitatively unmeasurable. Needless to say, rising to the occasion attentionally is no longer quite so strong or easy or useful as it used to be!
Many studies have documented the differential weakening of inhibitory processes paralleling age-related decline. For an entry to this literature, see, e.g., Leventhal AG et al (2003) GABA and its agonists improved visual cortical function in senescent monkeys. Science 300:312; or for another cortical system, see a study conducted by two former research colleagues, Hickmott P, Dinse H (2012) Effects of aging on properties of the local circuit in rat primary somatosensory cortex (S1) in vitro. Cereb Cortex (epub ahead of print). As described earlier, we have recorded the selective degradation of parvalbumin inhibitory neuron power in several animal models of developmental or acquired-adult impairment, or of aging itself. The inhibitory impacts of these specific neuron subtypes (especially “chandelier cells”) are especially crucial for controlling local and long range response coordination. See, for example, de Villers-Sidani E, Merzenich MM (2011) Lifelong plasticity in the rat auditory cortex: basic mechanisms and role of sensory experience. Prog Brain Res 191:119.
For a description of the contraction of the useful field of view with age, see Edwards J et al (2006) The useful field of view test: Normative data for older adults. Arch Clin Neuropsychol 21:275.
For changes in driving abilities with age, you might begin with a summary from the CDC: http://www.cdc.gov/Motorvehiclesafety/Older_Adult_Drivers/adult-drivers_factsheet.htmlFor an introduction to a compelling literature relating the up-tick in accidents in older drivers attributable to poorer reception and slower responding to events in your visual periphery, see one of the studies by Karlene Ball and colleagues, e.g., Ball KK et al (2006) Can high-risk older drivers be identified through performance-based measures in a Department of Motor Vehicles Setting? J Amer Geriat Soc 54:77.
For reports that show that hearing loss is endemic in elder populations, see a data summary from the American Speech and Hearing Association, http://www.asha.org/public/hearing/disorders/prevalence_adults.htm or for another demographic, Roth TN et al (2011) Prevalence of age-related hearing loss in Europe: A review. Eur Arch Otorhinolaryngol 268:1101.Many studies have shown that communication deficits cannot be accounted for by hearing loss alone; plastic neurological changes in hearing loss patients are a major contributor to speech reception and language deficits. See, for example, Leger AC et al (2012) Abnormal speech processing in frequency regions where thresholds are normal for listeners with high-frequency hearing loss. Hearing Res 294:95; Leigh-Paffenroth ED, Elangovan S (2011) Temporal processing in low-frequency channels. Effects of age and hearing loss in middle-aged listeners. J Am acad Audiol 22:393; or for another interesting difference that has impacted how we have thought about training hearing recovery in impaired elder populations, see Sabin AT et al (2012) Different patterns of perceptual learning on spectral modulation detection between older hearing-impaired and younger normal-hearing adults. J Assoc Res Otolaryngol (epub ahead of print).
For a review summarizing changes in vestibular control with age, see, e.g., Barin K, Dodson EE (2011) Dizziness in the elderly. Otolaryngol Clin North Am 44:437.
Hundreds of studies have documented losses associated with “executive control” that contribute to a simplification of formerly-more-complex cognitive control operations in elder and other impaired human populations. Many of these studies have a brain imaging side revealing functional degradation in the frontal, inferotemporal, cingulate or posterior parietal cortex (and in some sub-cortical nuclei) paralleling loss of complex cognitive operations. For an introduction to this extensive literature, see Verhaeghen P, Cerelia J (2002) Aging, executive control, and attention: a review of meta-analyses. Neurosci Biobehav Rev 26:849; or Riddle DR (2007) Brain Aging. CRC Press, Boca Raton.Vocabulary stabilizes over the 6th or 7th decade of live (in the average individual) then slowly declines. Changes in word usage in conversation are more substantial, with word choice contracting to the “more familiar.” For an introduction to this literature, start with Kemper S et al (2001) Longitudinal change in language production: Effects of aging and dementia on grammatical complexity and propositional content. Psychol Aging 16:600.
For documentation of the multifaceted decline into a more egocentric older life, see, for example, Orth U et al (2010) Tracking the trajectory of shame, guilt and pride across the life span. J Per Soc Psychol 99:1061; or McFarland C et al (1992) Biased recollections in older adults: The role of implicit theories of aging. J Pers Soc Psychol 62:837. To get into the extensive literature describing changes in emotional control in aging, e.g., Charles ST (2010) Strength and vulnerability integration: a model of emotional well-being across adulthood. Psychol Bul 136:1068; or, from another perspective, see Enkvist A et al (2012) What factors affect life satisfaction (LS) among the oldest-old? Arch Gerontol Geriatr 54:140.
For changes in social cognition with age, see, for example, Henry JD et al (2012) A meta-analytic review of age differences in theory of mind. Psychol Aging (epub ahead of print); or from another perspective, Mather M (2012) The emotion paradox in the aging brain. Ann NY Acad Sci 1251:33.
As pointed out earlier, there are many studies in which younger vs older adults were given a task to learn, when the rate of acquisition of the ability was measured. I know of no study of this class where older was faster. On the other hand, we have found old animals to make more errors, to be slower to learn and to reach lower achievement levels in learning BEFORE we specifically trained them to a) up-regulate their learning-control machinery, and b) control the many things that could distract them while they are learning the task. THOSE animals learned as fast and achieved the same ultimate performance levels as did animals in the prime of life. We’ll discuss this in more detail in the notes following Chapter 31 (www.soft-wired.com/31).
There are many reviews and scientific reports documenting the deterioration of the brain’s control of normal sleeping patterns as you grow older. For an early important summary, for example, see Prinz PN et al (1990) Sleep disorders and aging. NEJM 323:520; for a more modern turn, see Altena E et al (2010) Do sleep complaints contribute to age-related cognitive decline? Prog Brain Res 185:181.
