Teaching Old Dogs New Tricks How the scientist writing this book began to realize that there are very good uses for one of God’s (Mother Nature’s) greatest gifts: Your plastic brain!
Our initial plasticity studies conducted more than 30 years ago documented progressive representational remodeling following median nerve transection deafferenting the skin in the palmar surfaces on the thumbward side of the hand, with or without repair (see, for example, Merzenich MM et al, 1983, Progression of change following median nerve section in the cortical representation of the hand in Areas 3b and 1 in adult owl and squirrel monkeys. Neurosci 10:639; Wall JT et al (1986) Functional organization in somatosensory cortical areas 3b and 1 of adult monkeys after median nerve repair: Possible relationships to sensory recovery in humans. J Neurosci 6:218). The latter studies compellingly showed that the recorded plasticity was almost certainly a product of competitive Hebbian-network plasticity. Later studies specifically designed to determine if plasticity followed the Hebb rule answered this question in the affirmative (see Clark SA et al (1988) Receptive fields in the body-surface map in adult cortex defined by temporally correlated inputs. Nature 332:444; Allard T et al, 1991, Reorganization of somatosensory area 3b representations in adult owl monkeys after digital syndactyly. J Neurophysiol 66:1048; Jenkins WM et al, 1990, Functional reorganization of primary somatosensory cortex in adult owl monkeys after behaviorally controlled tactile stimulation. J Neurophysiol 63:82; Wang X et al, 1995, Remodeling of hand representation in adult cortex determined by timing of tactile stimulation. Nature 378:71; Merzenich MM, Jenkins WM, 1993, Reorganization of cortical representations of the hand following alterations of skin inputs induced by nerve injury, skin island transfers, and experience. J Hand Ther 6:89; among others). A theoretical model of Hebbian plasticity demonstrated that the Hebbian model could account for at least most of the phenomenology of change recorded in this extensive series of plasticity-related studies; see Grajski KS, Merzenich MM (1990) Neuronal network simulation of somatosensory representational plasticity. In: Neural Information Processing Systems, Vol. 2, Touretzky DI (ed), Morgan Kaufman, San Mateo. [Note that in “Hebbian network plasticity,” beyond the Hebb rule itself, the plastic network is driven to change by integrated effects of relatively local excitatory and more widely distributed inhibitory network contributions.)
One early outcome in these studies was the appreciation that Hebbian network plasticity could result in positive or negative neurological changes that could plausibly account for functional changes paralleling—and in many cases very plausibly accounting for—neurological and psychiatric illness. I have earlier cited the Recanzone et al studies published as a series of 4 articles in an issue of the Journal of Neurophysiology in 1992 (volume 67; pp. 1015-1091) as providing a compelling early demonstration. The outcomes of thousands of other more elemental and even-more-complicated studies in animals and humans (including another 60 or so published studies coming from my own research laboratory) support this grand conclusion. See Buonomano D, Merzenich MM (1998) Cortical plasticity: From synapses to maps. Ann Rev Neurosci 21:149 for review.
For early reviews in which we attempted to point out the obvious clinical extensions of plasticity-related research, see Merzenich MM et al (1990) Adaptive mechanisms in cortical networks underlying cortical contributions to learning and non-declarative memory. Cold Spring Harb Symp Quant Biol 55:863; Jenkins WM, Merzenich MM (1990) Cortical representational plasticity: Some implications for the bases of recovery from brain damage. In: Brain Damage and Rehabilitation. Dramon V, Poppel E, Steinbuchel NV, eds, Springer, Berlin; Merzenich MM et al (1993) Neural mechanisms underlying temporal integration, segmentation and input sequence representation: Some implications for the origin of learning disabilities. Ann NY Acad Sci 682:1; Merzenich MM, Jenkins WM (1993) Reorganization of cortical representations of the hand following alterations of skin inputs induced by nerve injury, skin island transfers, and experience. J Hand Ther 6:89; Merzenich MM et al (1997) Cortical plasticity underlying perceptual, motor and cognitive skill development. Implications for neuro-rehabilitation. Cold Spring Harb Symp Quant Biol 61:1. Alas, it has taken a long time before the medical research community really understood or bought into these arguments, and viewed them as a call to action. Millions of medical specialists and ancillary health professionals in the world are still inadequately informed about this sea change in how we should think about neurological and psychiatric impairment or illness. If you know one, encourage them to read this book!
We realized, in about 1990, that emergent focal dystonias were an expected failure mode of a plastic, self-organizing brain. That prediction from Hebbian plasticity models led to studies in which we induced dystonias by training adult monkeys. For example, see Byl N et al (1996) A primate genesis model of focal dystonia and repetitive strain injury. Neurology 47:508; and Sanger TD, Merzenich MM (2000) Computational model of the role of sensory disorganization in focal task-specific dystonia. J Neurophysiol 84:2458. In the same period, we began to realize that schizophrenia, OCD, addiction and other psychiatric ‘illnesses’ (as clinical depression had already been described to be, by other scientists; and as a number clinical scientists had earlier posited) were expected ‘failure modes’ of our self-organizing human brains.
On that top ten list of things that we can plasticity modify by appropriate training:
Synaptic strengths; new synapses. See www.soft-wired.com/10, rules 1,2. Tens of thousands of studies document our lifelong capacity for adult connectional remodeling.
Improving the health and vigor of the machinery supporting positive brain change. A long history of study of modulatory control nuclei has shown that they are sustained in their metabolic health, in the levels of production of their neurotransmitters and the “transporter” molecules that deliver them to their synaptic terminals, in the elaboration of their cortical and subcortical axonal arbors, and in the genesis of new neurons, BY ACTIVITY within them, which leads to the up-regulation of trophic factors that sustain (or recover) a high-performance status. See, for example, Woodlee MT, Schallert T 92004) The interplay between behavior and neurodegeneration in rat models of Parkinson’s disease and stroke. Restor Neurol Neurosci 22:153.; Steiner B et al (2006) Enriched environment induced cellular plasticity in the adult substantia nigra and improved motor behavior function in the 6-OHDA rat model of Parkinson’s disease. Exptl Neurol 299:291.We took another approach to address these issues by first sharply down-regulating the function of modulatory control nuclei in early life—then training the animals as adults, to determine whether or not the integrity of these nuclei could be restored. THEY WERE. See Zhou X et al, 2013, Behavioral training recovers distortions in neuro-modulatory control induced by perinatal antidepressant exposure (ms in review; reference to be updated).Note that when you shut down these nuclei or when they become disengaged because of the progressive disengagement of the frontal and other cortical areas that activate them, in animals or in humans, they are functionally inactivated and they die. In general, these nuclei are engaged by activity in attended/learning behavioral contexts. See, for example, Richardson RT, DeLong MR (1991) Electrophysiological studies of the functions of the nucleus basalis in primates. Adv Exp Med Biol 295:233; Sarter M et al (2005) Unraveling the attentional functions of cortical cholinergic inputs: interactions between signal-driven and cognitive modulation of signal detection. Brain Res Brain Res Rev 48:98; Schultz W (2007) Multiple dopamine functions at different time courses. Ann Rev Neurosci 30:259; Aston-Jones G, Cohen JD (2005) Adaptive gain and the role of the locus coeruleus-norepinephrine system in optimal performance. J Comp Neurol 493:99.There are many studies that show that brain engagement via learning or “environmental enrichment” results in the up-regulation of trophic factors that sustain the health of this crucial brain machinery. We have taken these studies a step further by showing that we can drive positive changes in BDNF (brain-derived neurotrophic factor) in animal training studies and in trained adult human patients (but in the latter case, NOT in control subjects playing video games) that, in both cases, recover BDNF expression from an impaired to a normal level (see, for example, Vinogradov S et al (2009) Is serum brain-derived neurotrophic factor a biomarker for cognitive enhancement in schizophrenia? Biol Psychiatry 66:549; Zhou X, Merzenich MM (2009) Developmentally degraded cortical temporal processing restored by training. Nat Neurosci 12:26.
Physically re-growing your brain. I have earlier cited references documenting a long history of animal studies in which the cerebral cortex was shown to grow thicker by engaging the animal in “enriched environments” or by engaging them in learning. E.g., see Rosenzweig MR, Bennett EL (1996) Psychobiology of plasticity: effects of training and experience on brain and behavior. Behav Brain Res 78:57. As I explained earlier, that thickening was primarily accounted for by the elaboration of dendrites and axons and synapses and glial processes, collectively described as “growth of neuropil.”More recently, a number of human training studies have described changes in cortical thickness in specific brain regions attributable to appropriately targeted training. You might begin with Bermudez P et al (2009) Neuroanatomical correlates of musicianship as revealed by cortical thickness and voxel-based morphometry (Cereb Cortex 29:1583; or Engvig A et al (2010) Effects of memory training on cortical thickness in the elderly. Neuroimage 52:1667.
Regaining your brain’s encoding accuracy. We have conducted more than 30 studies in animal models, and we and many others (over a period of more than a hundred years) have conducted thousands of studies in human children and adults in which we have large-scale changes in the accuracy of listening or visual or tactual reception operations, by appropriate forms of progressive training. Accuracy training can relate to the different parametric dimensions of listening or looking or feeling; all are subject to large-scale improvements. For example, we could easily increase your accuracy in making fine pitch or loudness or duration or modulation rate or frequency-modulation or amplitude-modulation or timbre distinctions via progressive listening training; and we could easily extend those improvements to increase your accuracy in distinguishing different simultaneously- or serially-presented sounds. We conducted such studies to try to understand the limits of “what is..” and “what is not trainable.” Every aspect of accuracy of your receptive abilities, these studies show, can be improved for most of us, by training. Why isn’t everyone equally improvable? If you measure the time-keeping abilities of the average person, they’re sloppy, and large-scale gains in accuracy in fine time-keeping (e.g., in distinguishing differences in durations, intervals, modulation rate) are achievable. For a professional musician, who practices making these distinctions every day, the brain is operating with near-optimal efficiency for such an ability, and improvement achieved through training is much more of a challenge. We have also found that a small percentage of impaired children or adults with particularly great training needs can have genetic faults that impact plasticity itself (see, e.g., Panizzutti R et al (2013) Genetic correlate of cognitive training response in schizophrenia. Neuropharm 64:264.)
Overcoming memory loss. Gains in short term memory or in delayed recall parallel gains in speech reception or visual reception accuracy and speed, in both children or adults. The basis for these gains in memory are obvious: With improvements in the clarity of “encoding,” permanent recording is correspondingly enabled. That relationship is expressed, in many studies, by strong correlations between speed & accuracy gains and memory gains. See, for example, Merzenich M, et al. (1998) Some neurological principles relevant to the origins of—and the cortical plasticity-based remediation of—language learning impairments. In: Neuroplasticity: Building a Bridge from the Laboratory to the Clinic. Grafman J, Cristen Y, eds., Springer-Verlag, New York; Mahncke HW et al (2006) Memory enhancement in healthy older adults using a brain plasticity-based training program: a randomized, controlled study. PNAS 103:12523; Ball K et al (2002) Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA 288:2271; Smith GE et al (2009) A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. J Am Geriatr Soc 57:594; Berry AS et al (2010) The influence of perceptual training on working memory in older adults. PLoS ONE 5:e11537.
Recovering your brain speed. In our own studies, we have driven improvements in processing speed in 25-30 different training experiments in animal models; there are many other related studies reported in the wider literature. See, for example, Bao S et al (2004) Temporal plasticity in the primary auditory cortex induced by operant perceptual learning. Nat Neurosci 7:974; or Zhou X, Merzenich MM (2009) Developmentally degraded cortical temporal processing restored by training. Nat Neurosci 12:26. Several dozen human studies have documented changes in processing speed attributable to learning. See, for example, Ball K et al (2002) Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA 288:2271; or Smith GE et al (1009) A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. J Am Geriatr Soc 57:594. We have improved the processing speed of about 5 million people in the world by intensively training them in speed- and accuracy-challenged tasks. Note that the magnitudes of speed-of-processing changes are large (improved 2- to 10-fold) for visual and auditory operations related to signal resolution, successive-signal recognition/masking, or object recognition.
Re-myelinating your brain. We have repeatedly recorded re-myelination induced in training (as marked by a histochemical marker-measured increase in myelin basic protein) in our animal training studies. In general, training in animals that are impaired from birth, or are demyelinated in their age resulted in a complete or near-complete restoration of myelination to peak-of-life levels. See, for example, de Villers-Sidani E et al (2010) Recovery of functional and structural age-related changes in the rat primary auditory cortex with operant training. PNAS 107:13900. An increasing number of studies have also documented myelination attributable to training in the adult cortex. For example, see Scholz J et al (2009) Training induces changes in white-matter architecture. Nat Neurosci 12:1370; or Engvig A et al (2012) Memory training impacts short-term changes in aging white matter: a longitudinal diffusion tensor imaging study. Hum Brain Mapp 33:2390.
Recovering from deficits in focused attention and distraction interference. Focused attention results in the positive modulation of activities represented “attended” inputs achieved via the operations of cholinergic inputs modulated from working memory. In attentional-impaired (ADHD) individuals, a weakness of these modulatory effects is attributable to a combination of weaker-than-normal feedback from working memory (which is often impaired in impaired children or adults) and/or from weaker-than-normal feed-forward effects from the cholinergic projections form the basal nucleus of Meynert. See, for example, Posner MI et al (1988) Structures and function of selective attention In: Clinical Neuropsychology and Brain Function., Vol. 7, APA Washington; Sarter M et al (2000) The cognitive neuroscience of sustained attention: where top-down meets bottom-up. Brain Res Rev 35:146; Yantis S (2008) The neural basis of selective attention. Curr Dir Psychol Sci 17:86.Training can relatively easily recover the effective operation of this attention-driven modulation of response power in the inattentive (AD) child. After training, modulation strength was found to be greater than in normal kids—who had to be trained to equal the neurological power of formally inattentive children. See Stevens C et al (2008) Neural mechanisms of selective auditory attention are enhanced by computerized training: electrophysiological evidence from language-impaired and typically developing children. Brain Res 1205:55. A second aspect of attention control is attributed to a parallel suppression of non-attended (irrelevant) internal or external “distractors” that may disrupt long-term (sustained) attention. Gazzaley A, d’Esposito M (2007)Top-down modulation and normal aging. Ann NY Acad Sci 1097:67. The inability to suppress distractors is a crucial second problem, beyond inattentiveness, for the ADHD child and the attentionally impaired adult. Notably, when children in the Stevens et al study just cited recovered the neurological modulation in selectively attending to what they heard, they were STILL hyperactive because their sustained attention was still continuously disrupted by their susceptibility to intruding “distraction.” We have recently developed strategies to suppress non-attended distractors in training. See Mishra J et al (2013) Multiscale neuroplasticity underlying training based remediation of interference suppression deficits in aging. PNAS (in review).
Sustaining your independence. Training in ways that sustain accurate visual reception and high-speed responding result in driver’s license and driving retention (x). Keeping your driver’s license and the mobility it confirms is a key to sustaining your independence, and (it turns out) to sustaining life itself. See xx. When we measure quality of life indices that correlate with the ability of given patient populations to sustain their independence, we generally record positive impacts of training.
Savoir faire (self confidence) is up-regulated. Measures of self confidence have been shown to grow in a half-dozen studies conducted in trained child and adult population. For example, Wolinsky FD et al (2009) Does cognitive training improve internal locus of control among older adults? J Gerontol B Psychol Sci Soc Sci 65:491.
One “old monkey” described in this chapter was judged, on the basis of its dentition, to be about 25 years old—which, for this species (Aotus trivirgatus), qualified as late old age. This monkey was a subject in Jenkins WM et al (1990) Functional reorganization of primary somatosensory cortex in adult owl monkeys after behaviorally controlled tactile stimulation. J Neurophysiol 63:82. Plastic changes driven by training in this oldster, to our considerable surprise, were as large in magnitude as those driven in other much-younger monkeys.
For a review of the studies by Hubert Dinse and colleagues on reversing aging effects via environmental enrichment, see Godde B et al (2002) Age-related changes in primary somatosensory cortex of rats: evidence for parallel degenerative and plastic-adaptive processes. Neurosci Biobehav Rev 26:743
There are many studies documenting a reduced learning rate attributable to aging. For a human example (among many) see Howard DV & Howard JH (1992) Adult age differences in the rate of learning serial patterns. Psychol Aging 7:232; for an animal model example (among many) see Buchanan SL, Powell DA (1988) Age-related changes in associative learning: studies in rabbits and rats. Neurobiol Aging 9:523.We have studied animal models in which learning rates that were initially lower than normal in impaired or aged animals were recovered by specific forms of training designed a) to up-regulate modulatory control processes controlling learning-induced plasticity; and/or b) to suppress background noise or distractors that add to ‘false positive’ responses in learning trials (and thereby attenuate learning rates). See, for example, Mlshra J et al (2013) Multiscale neuroplasticity underlying training based remediation of interference suppression deficits in aging. PNAS (in review).
