NEUROSCIENCE

Merzenich et al. Brain plasticity-based therapeutics

of disease is perhaps only matched by the magnitude of its actual
crudity, in neurobehavioral terms.
Beginning about four decades ago, a third vision began to
emerge (see Merzenich, 2013, for review). Studies in neuroscience

began to elucidate, in progressively more complete form, the neu-
rological origins of behavior. Those studies have now provided us

with a first-level understanding of the rules of the processes that
govern brain change, both as they account for a progression of

the brain in a degrading, “aging,” or distorting—or a strength-
ening, “rejuvenating,” or corrective neurological direction. This

science has also elucidated, in neurological terms, a number of
important “failure modes” of the self-organizing brain that have

long been given medical labels, like “depression” or “schizophre-
nia” or “oppositional-defiance disorder” or “Alzheimer’s Disease”

(see below, and Merzenich, 2013).

Importantly, after a Century of empirical studies by behav-
iorists trying to understand the origins of neurobehavioral lim-
itations or distortions in humans with neurological impair-
ment or illness, the explosively developing scientific domains of

“integrative neuroscience” and “cognitive neuroscience” began
to document, with increasing clarity, how and why emergent
brain system alterations—expressed by plasticity itself—appear

to account for functional human degradation, failure, and dis-
aster. This science has also revealed, with increasing clarity, how

limited or distorted neurological processes could be driven, via
those same plasticity processes, in strengthening and correcting
directions.

Because this evolving science provides a more complete under-
standing of the origins of—and potentially effective treatment

modes for—neurological impairment and illness, we believe that
it shall evolve into a foundation science for neurological and
psychiatric medicine. Here, the goal is to describe the state of
its current scientific development, as a platform for describing

what steps can be taken to bring the rapidly developing sci-
entific field of brain plasticity-based therapeutics into medical

reality. Our brief review of core principles of neuroplasticity is
followed by several practical examples of how the translation
of this neurological (and behavioral) science is optimized for
therapeutics.
THE SCIENCE OF NEUROPLASTICITY
Studies conducted principally over the past 40 years have allowed

us to collectively establish the following principles of neuroplas-
ticity:

THE BRAIN IS CONTINUOUSLY PLASTIC

Not so many years ago, mainstream neuroscience and neurolog-
ical medicine contended that plasticity was limited to an early

childhood epoch—a “critical” or “sensitive period.” We now
know that brain remodeling can be induced on a large scale at
any age in life (see Swain and Thompson, 1993; Merzenich and de
Charms, 1996; Merzenich, 2001, 2013; Weinberger, 2004; Gilbert
et al., 2009). What differs as a function of age is the way in which
the brain regulates plasticity. In the very young brain, almost all
inputs continuously engage competitive plasticity processes. In
older brains, plasticity is regulated as a function of behavioral
context and outcomes.

IN THE OLDER BRAIN, A CONTEXT- AND OUTCOMES-DEPENDENT
RELEASE OF NEUROMODULATORS FROM SUBCORTICAL LIMBIC
SYSTEM NUCLEI ENABLE AND TRIGGER BRAIN CHANGE

In the perinatal and early-childhood “critical period,” plasticity-
enabling conditions are always “on.” In the older child and adult

brain, changes in the control of the release of “neuro-modulatory
neurotransmitters”—and in the properties of the receptors in
the brain that govern their actions—enable the older brain’s
moment-by-moment control of change; it is permitted only when
the specific contextual conditions that enable or trigger plasticity

are met, with changes arising under those special contextual-
enabling conditions “saved” (driving enduring changes in con-
nection strengths) as a function of behavioral outcome (e.g., see

Merzenich, 2001, 2013 for reviews).
For example, under conditions of focused attention, any
stimulus excites acetylcholine (ACh) releasing neurons in the
basal nucleus of Meynert (Richardson and DeLong, 1990; Sarter
et al., 2001, 2006). In the cortex, ACh inputs positively enable

plasticity by (a) selectively amplifying only anticipated (“selec-
tively attended”) and (b) selectively weakening non-anticipated

inputs—including those at any given cortical location that may
have most effectively excited neurons before learning-induced
changes were initiated (Sarter et al., 2006; Froemke et al., 2007).
By this action, brain circuits enable plasticity by advantaging
input strengths for those specific activities that the brain can
gain in ability by changing to, and disadvantage behaviorally
non-contributing inputs that they shall change from.
As a second example, noradrenaline (NA) releasing neurons in

the locus coeruleus (LC) (and in nucleus accumbens and amyg-
dala) broadly amplify neuronal activity, increasing the general

level of excitability (arousal, or baseline level of attention) in sub-
cortical and cortical structures in any closely-attended context

(for example, in stimulus- or goal-seeking or other “motivated”
states) (see, e.g., Aston-Jones and Cohen, 2005; Sara, 2009; Sara
and Bouret, 2012). NA is also released to selectively amplify the
activities evoked by unexpected (novel) input (Aston-Jones et al.,

1999), conferring special powers for the representation of “sur-
prising” inputs or activities for driving enduring representational

change.
Dopamine (DA) releasing neurons in the ventral tegmental
area and substantia nigra are highly specific plasticity enablers
(see, e.g., Bao et al., 2001, 2003; Winder et al., 2002; Lisman et al.,
2011). They are excited when the brain receives—or first predicts
the occurrence of—a hedonic input (reward), or when the brain
achieves or first predicts behavioral success (for which it “rewards
itself”) in a learning cycle (Schultz, 2007). With their release,
inputs that “predict” that reward (i.e., are highly correlated with
its occurrence) are selectively strengthened; competitive inputs

uncorrelated with reward prediction arriving in a short post-
reward epoch are selectively weakened (see Ahissar et al., 1992;

Bao et al., 2003).
We now have a first-level understanding of the “rules” that

control the release and the actions of these (and other) neuro-
modulators in learning, and of the modulator-specific ways that

they nuance brain changes in experience and learning.

It should be noted that this crucial neuromodulatory machin-
ery, controlling learning and memory abilities throughout life, is

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Merzenich et al. Brain plasticity-based therapeutics

also plastic (Nakamura and Sakaguchi, 1990; Sara and Segal, 1991;
Steiner et al., 2006; Smith et al., 2011; Zhou et al., in review). The

strengths, selectivity, and reliability of its actions can be signifi-
cantly improved via intensive training in most individuals with

neurological or psychiatric impairment or disability.
MANY ASPECTS OF THE NEUROLOGICAL REPRESENTATIONS OF
INPUTS AND ACTIONS CAN BE MODIFIED BY APPROPRIATE
NEUROBEHAVIORAL TRAINING
In early studies of plasticity processes, we and others conducted
studies designed to reveal which aspects of the representations of
inputs or actions could be improved by training, under the right
contextual conditions, in the adult brain (see Merzenich, 2013, for
review). It was quickly shown that we could change the selectivity

of neuronal responses (i.e., receptive field sizes); the member-
ships of competing populations of neurons (“mini-columns;”

Buxhoeveden and Casanova, 2002) that represent those selec-
tive inputs; the detailed representation of stimulus magnitudes;

stimulus modulation rates; successive-signal segmentation and
integration (“masking;” “sampling rate”); stimulus duration and

inter-stimulus interval resolution and estimation; spectrotempo-
ral or spatiotemporal stimulus complexity; stimulus sequencing;

stimulus source location or identification; signal-to-noise con-
ditions for stimulus representation, and response reliability—

among other parameters of inputs (see, e.g., Merzenich and
de Charms, 1996; Gilbert et al., 2009; de Villers-Sidani et al.,

2010; Merzenich, 2013). In the domain of action, we could sim-
ilarly drive improvements in response reliability; response speed;

replication of timing in responding; response accuracy; response
sequence reconstruction; and response fluency; among other
parameters of action control. Many other scientists have extended

these studies to demonstrate plasticity in other perceptual, work-
ing memory, associative memory, selective attention, sustained

attention, distractor suppression, among other functional neuro-
logical abilities.

It should be noted that these studies have also shown that all

of these same (and many other) aspects of the neurological repre-
sentations of inputs and actions can be driven by training, just as

easily, in a degrading direction (e.g., see Merzenich and Jenkins,
1993; Zhou et al., 2011)—again by the action of normal brain
plasticity processes.
THE PRIMARY PLASTIC CHANGE IS IN THE STRENGTHS OF
CONNECTIONS (SYNAPSES) IN BRAIN CIRCUITS

Neuroplasticity research has extensively documented the phe-
nomenology of—and the cellular and molecular processes

underlying—the plastic remodeling of the “wiring” in brain cir-
cuits. The central governing rule was postulated by the Canadian

psychologist Donald Hebb in the 1940’s: “What fires together,
wires together” (Hebb, 1949). This coincident-input-dependent
co-strengthening of synaptic connections occurring moment by
moment in time in a learning context is achieved through both

a multiplicity of physical changes in synapses that amplify con-
nection strength, and by synaptogenesis. The magnitude of such

changes under near-optimum learning contexts can be remark-
able: a large proportion of synapses in any directly engaged

cortical zone (commonly, many millions to billions of synapses)

are altered in their connection strengths as you acquire any sig-
nificant skill or ability (e.g., Kleim et al., 2002). As we master any

skill or ability through experience or progressive learning, these
changes in brain circuitry result in the specialization of the brain
as a master receiver and master controller of all of the inputs and
actions supporting that mastery.
Nonetheless, the same processes that confer growth in synaptic
power for inputs that contribute to neurobehavioral advance are
also driven backward, for other non-behaviorally-contributing

synapses, in a synaptic weakening and synapse elimination direc-
tion (see below). This “normalization” of collective synaptic input

power has been extensively studied in other experimental mod-
els by depriving neurons of a major source of their inputs; in

that event, synaptic strengths are rapidly adjusted to sustain neu-
rons within a narrow electrical potential window that assures their

ongoing functional viability (Horng and Sur, 2006; Cooper and
Bear, 2012; Feldman, 2012).
PLASTICITY CONTROLS FUNCTIONAL RELIABILITY VIA ITS
GENERATION OF NEURONAL COOPERATIVITY
Through Hebbian network plasticity, the extensively cross-wired

neurons in the cerebral cortex also strengthen their connec-
tions with their nearest neighbors. When the brain is engaged

behaviorally, inputs that are activated nearly simultaneous in

time strengthen together, increasing their cooperativity to gen-
erate more salient (i.e., more collectively powerful, more reliable)

responses. That plasticity-driven growth in local “teamwork” is

a critical aspect of the improvement in the processing of infor-
mation supporting learning-based advances in behavior (see

Edelman, 1987; Merzenich and Jenkins, 1993; Merzenich and de
Charms, 1996; Merzenich, 2013).
Learning-driven increases in neuronal response coordination
are a primary determinant of the feed-forward power of any
plastically strengthening cortical process. Cortical neurons at all
“higher” system levels are integrators operating with short time
constants. Their plasticity processes are also coincident-input
dependent. The greater the coordination of neurons in the lower
levels of the network that feeds them, the greater their selective
powers and selectivity, and the greater the power of that input
to drive plastic remodeling at higher system levels. Moreover, at
the “top” of our great brain systems, coordination of activity is a
primary determinant of the ability of cortical networks to sustain
the reverberant activities that are selective for behavioral targets
or goals (i.e., working memory) (see Wang et al., 2004; Compte,
2006). The strengths of these key plasticity-gating processes “at
the top” are crucially dependent upon the strengths, i.e., collective
coordination, of the inputs that feed them.
NEUROPLASTICITY DRIVES CHANGES THAT BROADLY REMODEL THE
PHYSICAL BRAIN

Changing synaptic strengths and synaptogenesis involves com-
plex physical change processes resulting from changes in genetic

expression of several hundred well-described molecular pro-
cesses. At the same time, there are many other physical changes

induced by brain plasticity processes, collectively involving sev-
eral thousand known molecular processes. The physical processes

of neurons (the receiving “dendrites” and their synaptic “spines;”

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Merzenich et al. Brain plasticity-based therapeutics

the transmitting “axons” and the elaboration of their terminal

arbors; the distributions of collateral axons that richly inter-
connect neurons within cortical networks; the processes and

cell-to-cell contacts of closely coupled non-neuron glial cells)
can be plastically altered on a large scale, resulting in changes
in cortical thickness, neuropil volumes, and cortical area and
subcortical nucleus volumes (see Merzenich, 2013, for review).
Specific cell types can shrink or greatly expand in size, and can
be greatly metabolically reduced or invigorated—all expressed

through easily-documented, controlled, plastically-induced phys-
ical change. The insulating myelin can be thickened—or

thinned—under plastic control (de Villers-Sidani et al., 2010;
Zhou et al., 2012). Chemical factors controlling the health
and vigor and operational characteristics or brain systems, or
contributing to the regulation of plasticity itself—including

“trophic factors,” transporters, excitatory, inhibitory and neuro-
modulatory neurotransmitters and receptors are all altered phys-
ically, when the brain advances, or retreats, by the action of adult

neuroplasticity processes (Merzenich, 2013).
BRAIN SYSTEMS ACCOUNT FOR OUR EXPLICIT BEHAVIORS

A large body of science has now shown that our expressive behav-
iors are a product of complex, multi-level recurrent networks

(for further discussion and review, see Merzenich, 2013; Nahum
et al., 2013c). In these networks, information is represented with

greatest resolution in detail in place, feature, and time at low-
est network (“system”) levels. At successively higher levels, there

is an integration of representation to progressively more com-
plex objects, relationships and actions, as they apply in the “real

world.” At the “top” of brain systems, those most-completely-
integrated neurological representations generate enduring neural

activity that is selective for their representation. That persistent
reverberant activity, providing the neurological basis of working
memory, can be sustained in the human brain for tens of seconds
to minutes of time (see Goldman-Rakic, 1995; Compte, 2006;

Merzenich, 2013). It is important to understand that representa-
tional information is continuously fed backward from this highest

(and from all other) level(s). In these recursive recurrent net-
works, the operational levels contributing to the representation

of any aspect of input or action in brain systems are inseparable;
in other words, all explicit behaviors are a product of the system.
Therefore, when evident behaviors are distorted or impaired, as
they are in the many ways that define the fundamental deficits
and nuances of different specific neurological and psychiatric

clinical indications, we necessarily target neurological renormal-
ization at all system levels when designing therapeutic training

programs.
IN A BRAIN SYSTEM, PLASTICITY IS CONTROLLED “FROM THE TOP”

Recent neuroscience studies have shown that through recur-
sive re-entrant feedback (see Edelman, 1987; Grossberg, 2013;

and Merzenich, 2013, for review), the representation of infor-
mation “at the top” of our forebrain processing systems selec-
tively enables plastic changes contributing to the progressive

behavioral success of brain systems (see Hochstein and Ahissar,
2002). At highest system levels, behavioral targets are held,
as described, via sustained target-specific activities, in working

memory. That sustained persistently reverberant activity is pro-
jected backward down to “lower” system levels, where it positively

enables plasticity for any fed-forward activity that can potentially
contribute to a progressively improving resultant. Scientists often

call the opening of this window that controls, through this top-
down biasing, what the brain can change to, a “selective attention”

process. In fact, “working memory” and “selective attention” can

be considered to be two descriptors of the same persistent rever-
berant activity-based representation/feedback process (see Fuster,

2008). This process also provides the neurological basis of the
brain’s predictive, associative memory, sequencing construction,
and syntactic powers.
The neurological processes by which feedback “from the top”
biases plasticity in learning at all lower network levels are now
understood, at a first level. Biasing is achieved, neurologically, by

dis-inhibition processes in cortical networks controlled by con-
vergent modulation “from the top” on the one hand (through

a selective attention process), and from a cholinergic subcortical
input source engaged under conditions of focused attention, the
basal nucleus of Meynert (see Sarter et al., 2001, 2006; Froemke
et al., 2007; Weinberger, 2007; Carcea and Froemke, 2013; also
see Zhou et al., 2010), on the other hand.
Ahissar and Hochstein (Hochstein and Ahissar, 2002; Ahissar
et al., 2009) have described this feedback plasticity-enabling

biasing, in psychological science terms, as “the reverse hier-
archy theory.” According to this perspective, the brain holds

a model of a behavioral event or training goal in work-
ing memory; that model, fed back to lower system levels,

selectively amplifies activities (through dis-inhibition) that the
brain can change to, as it progressively sharpens and refines,
through learning, the resultant—its working memory-sustained
models.
PLASTICITY ENGAGES BOTH SYNAPTIC STRENGTHENING AND
SYNAPTIC WEAKENING PROCESSES
Fundamental studies of plasticity mechanisms have shown that
every brief change cycle invokes a synapse-strengthening moment
(e.g., strengthening all inputs whose coordinated actions moment
by moment in time are correlated with a positive behavioral

outcome), followed by a synapse-weakening moment (e.g., weak-
ening all inputs occurring within a brief, following epoch of

time) (Dan and Poo, 2006; Cooper and Bear, 2012). As noted
earlier, this synapse weakening can be viewed as an electrically
homeostatic process that contributes to the ongoing weakening
of behaviorally non-meaningful intrinsic activities or inputs—
that is, to a normalization of internal or background external
(environmental) noise.
Viewed from another perspective, plasticity processes can be

viewed as continuously competitive. Through these two-way plas-
ticity processes, neurons in coupled “mini-columns” are contin-
uously competing with their neighbors for the domination on

neurons on their mutual boundaries (see Merzenich and Jenkins,

1993; Merzenich, 2013). By giving one coupled group the com-
petitive advantage over their neighbors, it is easy to expand

their team a 1000-fold—or, if they are a competitive loser, to
reduce its “membership” many times over. By giving any one
source of input a competitive advantage or disadvantage, the

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Merzenich et al. Brain plasticity-based therapeutics

territory it comes to dominate in the brain can be dramat-
ically enlarged, or contracted; every moment of gain for the

“winner” is a moment of loss for “losers.” By these two-way pro-
cesses, one can easily both refine (for some inputs) and degrade

(other inputs)—even the most-fundamental aspects of represen-
tation of visual or auditory or somatosensory inputs in the adult

brain.
AT LEAST MOST (POSSIBLY ALL) PLASTICITY-INDUCED CHANGES ARE,
BY THEIR NATURE, REVERSIBLE
Plasticity engages fundamentally reversible neurological change
processes. We have conducted a number of studies that have
demonstrated that neuroplasticity follows Hebbian principles: the
representations of inputs and actions are competitively sorted
on the basis of the temporal distributions of inputs (Merzenich
and Jenkins, 1993; Merzenich and de Charms, 1996). Following
these principles, it is just as easy to degrade the brain’s processing

abilities as it is to strengthen or refine them. In the designs of ther-
apeutic training regimes, the Hebbian “rule” must be considered,

to assure that training-driven changes are always in the positive,
strengthening, recovering, re-normalizing direction.
We have recently conducted a number of studies in animals
that show that plasticity processes are very broadly reversible.
For example, after documenting many aspects of the function,
anatomy and chemistry in the brains of aged vs. young adult
animals, it was shown that every measure differed markedly (de
Villers-Sidani et al., 2010; de Villers-Sidani and Merzenich, 2011;

Mishra et al., under review). In the aged rats’ auditory cor-
tices, time and space constants were longer and greater; response

selectivity was poorer; reliability of sound feature representation

was poorer; response correlation was weaker; the neuron pop-
ulations representing sensory inputs were less strongly coupled,

operating with far weaker cooperativity; inhibitory processes con-
trolling “top-down” modulation were weaker; local and long

range connections were more poorly myelinated; level-to-level
(system) coordination (in gamma and theta frequency ranges)

was less sharply localized and more weakly persistent; representa-
tional topographies were degraded; trophic factors contributing

to metabolic and physical maintenance and plasticity were only
weakly expressed; the normally strong adaptation to repeated
identical stimuli and responses to unexpected stimuli against
a continuous or repeated background were sharply reduced;
the strong suppression of non-attended distractors was reduced;
receptor subunits for inhibitory and excitatory processes were

altered in a degrading direction; and the modulatory control pro-
cesses controlling plasticity were all more weakly operating in very

old vs. prime-of-life animals. After recording these manifold, sig-
nificant differences between aged and young rats’ brains, animals

were intensively behaviorally trained in operant tasks to deter-
mine which of these operational characteristics of the brain could

be “rejuvenated.” Somewhat to our surprise, with training limited
in these aged rats to approximately 1 h/day for about 1 month,

all of these degraded operational and physical-chemical charac-
teristics of the aged brain could be substantially if not completely

restored to a “youthful” state, in aged animals (de Villers-Sidani
et al., 2010; de Villers-Sidani and Merzenich, 2011; Mishra et al.,
under review).

Given its reversible nature, plasticity processes can just as
easily be engaged in a young prime-of-life animal in ways that

drive their brains in an increasingly uncorrelated pattern activ-
ity (as seen in aged animals). That has also been achieved for

the auditory brain by a simpler environmental exposure strategy.

By housing young, vigorous adults in an environment of non-
correlated noise (believed to increase the level of internal noise

in the hearing brain) for a period of several weeks, all of the
functional and physical characteristics of the machinery of the
brain noted above altered as if the animal had advanced over
those several weeks to an “old age” status (Zhou et al., 2012;
Kamal et al., 2013).

Because these reversible change processes can drive neuro-
logical changes in either an advancing or degrading direction,

driving the processing and physical characteristics of the brain
rapidly “forward” to simulate aging is equivalent to driving the
animal backward in age: The physical and functional properties
of the brain near the end of life closely correspond to those same
characteristics in the brain recorded near the beginning of life

(Zhou et al., 2012). That conclusion is supported by document-
ing the operational and physical characteristics of the machinery

of the brain in very old and very young animals: they closely
match one another. It is also manifested by the fact that key
accelerated changes leading to “premature aging” achieved by
noise exposure or by “negative” training, carried forward far
enough, similarly result in the re-opening of the “critical period”
(Zhou et al., 2012).
THE NEUROSCIENCE OF BRAIN PLASTICITY PROVIDES NEW INSIGHTS
INTO THE ORIGINS OF THE EXPRESSIONS AND NATURES OF
ACQUIRED NEUROLOGICAL AND PSYCHIATRIC IMPAIRMENT AND
“DISEASE”—AND IN HOW TO DRIVE “CORRECTIVE” CHANGES IN
IMPAIRED BRAINS VIA INTENSIVE TRAINING
From the study of all of these complex aspects of brain change,
neuroscientists have defined the “rules” that govern them, in the
terms of the brain processes that account for these aspects of brain
change. We now understand necessary and optimal conditions

for driving positive changes in most dimensions of brain pro-
cessing, as well as the behavioral functionality that they account

for. This rule-based training represents an important refinement

of the more-empirically based development of “cognitive train-
ing” program designs, in several important respects. First, with

this understanding, we can more directly target neurological (not
merely behavioral) improvement or re-normalization. Second,
this science is progressively resolving long-standing arguments
about “best practices.” There is a best way: following the brain’s
rules for learning-based remodeling.
Neuroplasticity research, with related studies in fundamental
and integrative neuroscience conducted in animal and human
models, has provided us with a new level of understanding of the
neurological bases of representation of behavior. It has shown us,
at a deeper level, the natures of the neurological distortions that
underlie function impairment, loss, or dysfunction, specifically
defined in neurological (not limited to descriptive behavioral)
terms. Fundamental recovery, which addresses the central deficit

underlying the disorder, must result in neurological improve-
ment or restoration. With this rapidly growing science, we can

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Merzenich et al. Brain plasticity-based therapeutics

potentially extend our targeting of neurological dysfunction to
the more elemental processes in brain systems that account for
behaviorally expressed impairments.
To understand how this differs from the currently
predominant approaches to neurological and psychiatric
medicine, consider two simple examples: First, scientists have
studied alterations in many disease states by documenting which
genes are up-regulated—and which are down-regulated—in
specific diseases (Gilman et al., 2012; Calciano et al., 2013;
Fass et al., 2014; among several hundred citable examples).
One of their goals has been to determine what specific change
processes could account for the disease’s emergence, on the path
to the potential pharmaceutical treatment of the illness. With
remarkable repetition, study after study has recorded: (1) several
to many hundreds of genes that are significantly up-regulated and

down-regulated in the disease or condition; and (2) a broad over-
lap in this pattern of change for brains studied from patients with

even strikingly different clinical indications (like schizophrenia or
autism or Alzheimer’s disease or multiple sclerosis). For example,
genetic variation in encoding brain derived neurotrophic factor
(BDNF) has been implicated in neuropsychiatric disorders such
as Alzheimer’s disease, affective disorders, schizophrenia, and
substance dependence (e.g., Zhang et al., 2006).
From a brain plasticity perspective, these gene chip results are

unsurprising: any struggling brain undergoes broad-scale “plas-
tic” revision. It is highly probable that most of the recorded

changes in gene expression are a reflection of plastic remodel-
ing; in the face of growing “noise” in neurological processes, the

brain plastically adapts to retain some level of functional control
(see Merzenich, 2013). Given the chemical complexity of these
changes contributing to disease expression, no single drug or
limited drug combination, and no simple training of an explicit

behavioral ability(ies) can be expected to drive the myriad of cou-
pled plastically-adjusting processes to correction. On the other

hand, animal studies indicate that it may be possible to achieve
broad-scale “reversals” in targeted brain systems via relatively
simple intensive training programs repertoires.

To cite a second example, cognitive psychologists have identi-
fied the ability of brain systems to sustain reverberant activities

representing specific information “held in working memory” as a
primary cause of many problems, extending from ADHD through
schizophrenia to mild cognitive impairment. Their predominant
treatment solution has been to directly exercise this failing faculty;
medically useful gains are achieved by such training (Klingberg,
2010). However, as in any form of explicit skills training, benefits

do not broadly generalize to other task domains that engage work-
ing memory in real-life behaviors (Melby-Lervåg and Hulme,

2013; Rapport et al., 2013).
A brain plasticity perspective addresses this kind of problem
from a deeper level of understanding. “What is the cause of the
inability of the brain to generate strong, persistent activities? How

and why is the system not generating the highly correlated feed-
forward inputs and/or neuromodulatory inputs both known to be

crucial for its genesis?” From that perspective, broader training

designed to increase the salience (correlated power) of repre-
sentation of the details of inputs and actions at every system

level and the assured or corrected function of neuromodulatory

contributors to working memory processing would be deemed
to also be important for achieving stronger far-transfer training
impacts (see, for example, Strenziok et al., 2014).
ADVANCES IN COGNITIVE NEUROSCIENCE HAVE ALSO
PROFOUNDLY CHANGED THE THERAPEUTIC LANDSCAPE
A rapid expansion and elaboration of human brain recording
and imaging studies have paralleled the phenomenal growth of
neuroplasticity-related neuroscience. An increasing number of
those studies document aspects of training-driven plasticity itself.
Still, the primary focus of this research has been the mapping
of patterns of activity in brain systems that account for specific

human abilities. That science provides a basis for defining alter-
ations in abnormal brain systems accounting for almost every

class of functional impairment or “illness.” This science has been
limited with respect to the completeness with which it records

abnormality in specific neurological-process terms. Still, it pro-
vides great insights into the origins of and the bases of behav-
ioral expressions of every important neurologically-based clinical

indication—and is a crucial source of information for our designs

of impairment- and disease-targeted plasticity-based therapeu-
tic programs. It also provides an increasingly definitive basis for

documenting therapeutic outcomes, where the primary goal in

therapy is shifting beyond behavioral improvement to the poten-
tial re-normalization of dysfunctional brain systems. Examples of

how we apply this key source of information in program designs
are described below.
TRANSLATING NEUROLOGICAL (AND BEHAVIORAL)
SCIENCE INTO OPTIMIZED THERAPEUTICS

Based on the neuroscience of brain plasticity, therapeutic train-
ing strategies have been created that target a growing number

of clinical conditions. Here, three examples illustrate how these
programs are created and validated for therapeutic use.
TARGETING NEUROLOGICAL AND BEHAVIORAL IMPAIRMENTS IN
SCHIZOPHRENIA

A growing body of literature points to pervasive neurocogni-
tive and social cognitive impairments as fundamental aspects of

the expression of schizophrenia (e.g., Cirillo and Seidman, 2003;
Brewer et al., 2005; Keefe et al., 2006; Eastvold et al., 2007; Becker
et al., 2010; Kim et al., 2011). Deficits in perception, speed of
processing, working memory, attention, executive function, social
cue perception, and social and action control are recorded even

before illness onset, and are associated with poor functional, soci-
etal and occupational outcome (Green et al., 2000, 2012; Edwards

et al., 2001; Lencz et al., 2006; Niendam et al., 2006; Seidman et al.,
2006; Simon et al., 2007; Chan et al., 2010; Kohler et al., 2010;
Billeke and Aboitiz, 2013). Because the perceptual, cognitive and
social cognitive deficits are generally dissociated from psychotic

symptoms in schizophrenia, they are not significantly amelio-
rated by antipsychotic medication (e.g., Goldberg et al., 2007;

Green, 2007). Specifically, second-generation dopamine-agonists
antipsychotic did not show any advantage over first-generation
agents in treatment of cognitive deficits in schizophrenia (Keefe
et al., 2007). Similar negative effects for cognitive deficits in
schizophrenia have been reported for clinical trials involving

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Merzenich et al. Brain plasticity-based therapeutics

glutamate-related or serotonergic agents (see Goff et al., 2011, for
recent review).
At the same time, we hypothesize that these weaknesses in
perceptual and cognitive processing underlie the catastrophic
breakdown of working memory operations, which are at the heart
of psychoses genesis (see Merzenich, 2013). By that interpretation,
training that improves the neurological abilities that contribute
to working memory and neuro-modulatory system functionality
in these great brain systems should have substantial prophylactic
power in at-risk individuals.
From a neurological perspective, schizophrenic brains are:
poor signal resolvers, operate sluggishly, struggle to generate
sustained activities supporting top-down (working memory,
selective attention, associative memory, predictive) processes in

prefrontal cortex (Minzenberg et al., 2009), and in frontal, pos-
terior parietal and inferior and medial temporal areas (Heckers,

2001); have distortions in language, visual, source-reference and
other operations related to psychotic symptoms (Modinos et al.,
2013); have impairments in social cognition that greatly impact
quality of life (see Couture et al., 2006); and have changes in
fundamental neuronal processes that we associate (along with
working memory degradation) with very noisy brain system
processing (e.g., Hinkley et al., 2011).
Perceptual, cognitive, social, and motor control deficits along
with modulatory system abnormalities are obvious, important
targets for treatment in schizophrenia. From a brain plasticity
perspective, fundamental neurocognitive recovery shall require
brain system remodeling: high-speed, high-fidelity processing
with systems engaged by progressively more complex inputs and
more difficult challenges should be combined with more-explicit
cognitive re-training to achieve system re-normalization. As a
part of a brain plasticity-based recovery strategy, it is important

to re-normalize neuro-modulatory processes controlling plastic-
ity itself. Core deficits expressed in the illness—the usually-severe

degradation of working memory processes and magnified levels
of arousal and intensity—are attributable in part to abnormally

high levels of expressions of dopamine and NA in these individ-
uals (Tost et al., 2010). By that dysregulation, the contribution

of these systems to plasticity itself can be significantly altered—
with further distortions induced by the psychoactive drugs that
target the expressions of these neuro-modulators to ameliorate
this self-poisoning.
Our computerized cognitive training programs are designed
to drive the brain of the schizophrenic patient broadly in the
normal-ward direction, in: auditory/aural speech, visual, social
cognition, executive, social, and action control domains, attention
and focus, and in neuro-modulatory system control domains.
In these targeted brain system, training extends from low-level

perceptual processing to higher-level working memory, atten-
tion and executive and motor control processes. Subjects are

trained to refine representational fidelity and operate at speed,
in ways designed to reduce internal brain noise and restore
more normal physico-chemical processing. Training of implicit

abilities is designed to assure that all fundamental processing abil-
ities are refined in ways that support more reliable and more

sophisticated explicit operations. All exercises are progressive
and adaptive, adjusting in difficulty to assure a continuously

successful-but-challenging level of ongoing training. The general-
ization of gains to all processing that engages the targeted systems

is a universal program goal.

Specific attention has been given in our exercise suite to train-
ing of social cognition, which has been recently pointed out as

a particularly important target for intervention in schizophrenia.
Specifically, social cognition deficits have been directly linked to
poor functional outcome in schizophrenia (Couture et al., 2006)
and have been found to underlie critical factors affecting daily
living in schizophrenia, such as occupational status, community
functioning, independent living skills, and quality of life (e.g.,
Couture et al., 2006; Bell et al., 2009; Fett et al., 2011). Our Social
cognitive training (“SocialVille;” Nahum et al., 2013a,b) deploys
socially-relevant stimuli in tasks that target affect perception,
social cue perception, theory of mind and attributional style. The

SocialVille exercises require progressively more complex discrim-
ination and identification of socially-valid stimuli, while again

driving progressive improvements in processing speed, working
memory, and attention control. We have recently successfully
completed a pilot feasibility study of SocialVille in early-phase
schizophrenia patients, who completed training remotely from
home using internet-connected laptops (Nahum et al., 2014).

Through collaboration with university-based scientists, differ-
ent combinations of these forms of brain plasticity-based training

have been applied in a large population of chronic schizophre-
nia and first-episode patients (e.g., Adcock et al., 2009; Fisher

et al., 2009a,b; Dale et al., 2010; Popov et al., 2011; Subramaniam
et al., 2012; Keefe et al., 2012; Sacks et al., 2013; see reviews
by Biagianti and Vinogradov, 2013 and Fisher et al., 2013).

For example, following 50 h of plasticity-based auditory train-
ing, chronic schizophrenia patients made significant gains in

global cognition, processing speed, verbal working memory, and
learning and memory metrics (e.g., Fisher et al., 2009a,b). In

parallel, brains of trained subjects compared with controls recov-
ered more normal M100 responses to successive signals consis-
tent with recovery of more normal perceptual abilities resulting

from training (Adcock et al., 2009; Dale et al., 2010); recovered
more strongly correlated (recovered) gamma frequency responses
in the lower gamma frequency (Popov et al., 2012); recovered
stronger responses to rapidly successive stimuli in the gamma
high-frequency domain (Dale et al., under review); more strongly
synchronized alpha frequency responses for target stimuli, and
more strongly de-synchronized non-target domain alpha-band
responses in an attention-controlled task (Popov et al., 2012;
Dale et al., under review); recovered more normal sensory gating
(Popov et al., 2011); recovered more normal dorsolateral frontal
responses in a working memory task (Dale et al., under review);

restored more normal patterns of response in an attribution-
of-source task (Subramaniam et al., 2012; see Figure 1); recov-
ered more normal amygdala and ventral-lateral-frontal cortical

responses in an emotion recognition task (Hooker et al., 2012,
2013); recovered more normal BDNF expression (Vinogradov
et al., 2009); among other physical and functional neurological
measures of plastic training-driven recovery.
While these studies are still a work in progress, taken together,

they indicate that this form of computerized, neuroplasticity-
based training is effective for broadly driving behavioral

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Merzenich et al. Brain plasticity-based therapeutics

FIGURE 1 | Illustrating positive far-transfer chemical, behavioral, and
brain response changes attributable to intensive brain training in
patients with chronic schizophrenia (SZ). Tasks targeted the auditory-aural
language/perceptual-cognitive system. Training was via computers, over a
40–50 hour-long training period. (A) Brain-Derived Neurotrophin Factor
(BDNF) in its “pro” and mature (“m”) forms is down-regulated in
schizophrenia and in other chronic neurological and psychiatric illnesses (e.g.,
healthy aging). As a result of this brain plasticity-based training, serum levels
of BDNF were elevated to normal levels; no changes were recorded in
subjects who worked with equivalent intensity on progressive control video
games. The up-regulated of BDNF to near-normal levels was sustained for
more than a year following training program completion. Similar effects have
been recorded in aging brains. Data are from Vinogradov et al. (2009). (B)

Left: Re-normalization of abilities in a behavioral task in which subjects with
SZ identify whether they or an outside agent was the source of an
immediate-past action. Again, this is a transfer effect of training; no aspect of
this task is represented in the completed training regime. Right:
Strengthening of BOLD responses in a medial prefrontal cortical area
hypothesized to be the primary cortical site for the assignment of agency in
the brain. No measurable task-related activity was recorded in this area in
subjects with SZ prior to training, or in computer brain-engaged SZ controls
before or after training. From Subramaniam et al. (2012). (C) Brain images
showing changes in responses recorded in this task. Abbreviations: CG,
computer games control; AT, auditory training; SZ-AT, schizophrenia patients
in the auditory training group; SZ-CG, schizophrenia patients in the computer
games group; HC, healthy controls.

and physiological changes in a normal-ward direction in the
schizophrenic brain. On this basis, we are now conducting a
multi-site FDA medical device trial to further document these
medical outcomes on the path to establishing medical claims for

program use. Our longer-term goal is to progressively improve
our training strategies to drive stronger and more complete and
reliable changes in all key domains of dysfunction and loss in
patients with this very complexly neurologically distorting illness.

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Merzenich et al. Brain plasticity-based therapeutics

It might be noted that given its bi-directional nature, training-
driven plasticity processes are not riskless. Because we have a

relatively complete understanding of the principles governing
plasticity in our own medial therapeutic applications, we have not
recorded negative consequences resulting from the application of

any of our training tools. At the same time, an FDA approval pro-
cess is important for assuring the affirmed positive values of the

medical delivery of this new approach.
HEMISPATIAL NEGLECT SYNDROME

Approximately half to two thirds of patients with right hemi-
sphere injury exhibit a complex, debilitating array of spatial

and non-spatial (attention) neurological deficits (Mesulam, 1990;

Heilman et al., 1993). Those deficits arise from damage or dis-
connection to interconnected inferior parietal or lateral frontal

cortical areas, or from the subcortical basal ganglia or thala-
mus. Patients with neglect do not respond to stimuli on the

contra-lesional side of visual space, often seemingly unaware that
anything in that space exists. For example, they may lose or fail
to see or find objects located in neglected space, commonly suffer
from poor navigation, and disregard significant events arising in
the neglected field.
In addition to this manifest visual-field-localized impairment,

patients with neglect exhibit deficits in attention that are not later-
alized (Husain and Rorden, 2003; Van Vleet and Degutis, 2014).

Those more general deficits are general in this population, and
on that basis have been argued to be fundamental to the disorder
(Corbetta and Shulman, 2011). They include deficits in arousal
(particularly strong in the acute phase of recovery); attention
to transient events; working memory updating; spatial working
memory span; and alertness and sustained attention. Importantly,
these non-spatial deficits are stronger predictors of chronic spatial
neglect in the post-acute recovery phase than are the visuo-spatial
deficits themselves (Hjaltason et al., 1996; Husain et al., 1997;
Robertson et al., 1997; Duncan et al., 1999; Peers et al., 2006).
Several recent studies show that the poor regulation of intrinsic
alertness is correlated with—and plausibly explains—the degree
of spatial field loss (“spatial bias”) in these patients (Robertson
et al., 1997).
From a brain plasticity perspective, this is a particularly clear
instance in which neuro-modulatory dysregulation contributing
to attention control has been argued to be a strong contributor
to disability. A pharmacological approach to recovery in such a
case would be the administration of a stimulant drug; such drugs
have been applied in this population with limited success (Fleet

et al., 1987; Geminiani et al., 1998; Barrett et al., 2012). A cogni-
tive behavioral approach would be to engage patients by heavily

stimulating them to do what they can’t do: respond to stimuli

presented in the contralesional visual field. Again, that therapeu-
tic approach has been applied with significant but limited success

(Weinberg et al., 1977). Our neuroplasticity-based approach has

applied training specifically designed to up-regulate both pha-
sic and chronic alertness, combined with training designed to

assure the recovery of more normal spatial working memory
and representational salience for visual inputs arising from the
affected visual field area. That approach is, again, predicated on
our understanding of the normal modulatory processes in play.

In the neglect patient, deficits in both tonic and phasic alertness
are recorded. Tonic alertness (the background state of arousal)
is highly correlated with the background level of expression of
NA arising primarily from the midbrain LC (Sturm et al., 1999;
Sturm and Willmes, 2001; Thiel et al., 2004). Tonic alertness is
supported by a right-lateralized supra-modal network that feeds
back to the LC, including the right inferior frontal, right inferior
parietal and anterior cingulate regions. In contrast to the slowly
changing tonic alertness, phasic alertness is the rapid modulation

in alertness arising in any briefly engaging event, vital for oper-
ations such as orienting, selective attention, and the enabling of

plasticity that is dependent upon these processes. This neuro-
modulation is largely attributed to the forebrain expression of

ACh originating from the dorsal nucleus of Meynert, as well as
by the phasic release of NA, again from the LC; their activation

is again influenced by recurrent projections from a complex fore-
brain network. Phasic alertness is stronger against a platform of

higher tonic alertness; both can be substantially amplified in an
enduring way by relatively simple forms of training (DeGutis and
Van Vleet, 2010; Van Vleet and DeGutis, 2013).
The primary strategy that we deploy to “exercise” this impaired
neuromodulatory machinery is a continuous performance task
in which subjects maintain a specific visual or auditory target in

working memory (setting up the conditions for “top-down” neu-
romodulatory engagement), with those targets presented as rare

events within a series of novel stimuli that are known to strongly
activate limbic system sources of ACh (Richardson and DeLong,
1990; Sarter et al., 2001, 2006) and NA (Bouret and Sara, 2005). In
the training task, subjects demonstrate that they are continuously
attending to novel background stimuli by responding to them one

by one; they demonstrate that they are holding a target stimu-
lus in working memory by withholding their responding when

it occurs (DeGutis and Van Vleet, 2010; Van Vleet and DeGutis,
2013). It might be noted that stimuli are also presented in this
training in time-jittered sequences (see Wodka et al., 2009; Ryan
et al., 2010) and that patients are progressively time-challenged in
their responding to novel non-target stimuli (they must withhold

responses for target stimuli), again because neurological stud-
ies indicate that this will drive more rapid and more enduring

neurological remodeling.
With the application of this neuro-modulatory- (attention-)
targeted computerized training strategy alone, most neglect
patients—including individuals with brain injury arising from
almost any cause—rapidly recover their ability to “see” in the
affected hemifield (Van Vleet and DeGutis, 2013; see Figure 2).
Given this initial recovery, training is now more effectively
extended to more completely recover representational fidelity and
spatial working memory by directly re-refining the brain systems

representing spatial and spatial sequencing and working mem-
ory deficits of neglect patients as well. A brain plasticity-based

program based on these principles is now the subject of a large
multi-site FDA medical device trial.
AGE-RELATED IMPAIRMENT; RESILIENCE AGAINST
NEURODEGENERATIVE DISEASE ONSET
By contrast to relatively sharply targeted training applied to
address the problems that frustrate neglect syndrome patients,

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Merzenich et al. Brain plasticity-based therapeutics

FIGURE 2 | Hemispatial neglect syndrome patients are slow to identify
target stimuli arising in the neglected visual hemifield. Training
designed to recover the functionality of intrincsic alertness over a period of
6 h was adequate for achieving recovery when examined within 48 h
post-training. Data from 20 neglect patients with a wide panoply of
brain-injury etiologies. (e.g., tumor, stroke, TBI). Display time significantly
shortened following training. Note that this is a “transfer” effect, as training
involving the identification of objects, scenes, or tones was presented at
central fixation (i.e., not in the neglected field). Redrawn from DeGutis and
Van Vleet (2010) and Van Vleet and DeGutis (2013).

neurological and behavioral changes in aging, like those in

schizophrenia, are almost brain wide. The documentation of age-
related deficits—and the path of the progression to an ultimately

catastrophic decline to senility—have been the subject of sev-
eral hundred thousand scientific reports. The average aging brain

expresses major progressively-growing behavioral deficits in all of
its major processing systems in perception; speed of action and
fluency; phasic, sustained and divided attention; different aspects
of memory; social cognition; and executive, social and action
control (see Salthouse, 2000, 2012; Reitz et al., 2011; Merzenich,
2013, for review). Losses translate to about an average of one third
of a standard deviation per decade in ability after ability past the
age of 30 for men, and beyond the age of about 45 in women.
In neurological terms, substantial degradation is recorded in
all great representational systems—again, on the average—in
representational accuracy; processing speed; local response and

system coordination; excitatory and especially inhibitory pow-
ers (and the complex machinery that support them); tracking

of rapidly successive inputs; representation of temporal details

of inputs(durations, intervals, rhythmic sequences, et al.); accu-
rate representations of sequenced inputs, scenes, scenarios; the

sustained responses supporting “working memory”/“selective
attention”/“associative memory” and prediction; and the more
complex “mental” neurological activities supporting executive,
social and motor control, ideation, and thought (see Merzenich,
2013 and Nahum et al., 2013c, for review). All of these processes,

and their degradation in aging, are again contributed to by paral-
lel atrophy of the neuro-modulatory centers regulating the release

of dopamine, norepinephrine, ACh, serotonin, et alia (Barili et al.,
1998; Mufson et al., 2002; Backman et al., 2010)—which crucially
support the plasticity processes that account for both functional
maintenance and learning-based remodeling.

These neurological changes are “cognitive aging”: from a phys-
ical view, they are the basis of connectional dis-elaboration and

disconnection, de-myelination, reduced blood flow, and neuropil
and cortical shrinkage reduction attributable to dendrite, axonal
arbor, glial process and synaptic simplification (e.g., see Mufson
et al., 2002; Lo et al., 2011; Hahn et al., 2013; Jagust, 2013).
Because of the broad picture of decline, both behaviorally and
neurologically, there is a lot of re-engagement required to drive
the brain broadly in a rejuvenating direction, conferring greater
resilience re the onset of senile dimension and neurodegenerative
diseases. At the same time, there is no simple pharmaceutical or

cognitive behavioral strategy that could possibly drive the requi-
site, broad-scale corrections. The training program that we have

designed to address these broad issues requires up to about 200 h
to complete (dosing is dependent on the depth and breadth of
neurological loss), with additional training on a lighter schedule

required for many individuals to sustain a safe position over sub-
sequent years. Again, all training is progressive and adaptive, and

presented in game-like training formats on computers or other

mobile devices. Our goal is to recover, insofar as possible, neuro-
logical representational accuracy, speed, coordination, sequenc-
ing, recording (remembering, selectively attending), noise control

(distractor suppression) and executive processes in the brain. At
the same time, exercises are designed to up-regulate, re-refine and
re-invigorate modulatory control processes controlling learning,
memory, attention states and mood.
As noted earlier, an important goal of this training is to
increase resilience against the onset of neurodegenerative disease.
Because we know the patterns of progression in pathology across
a long epoch of time before frank “disease” onset, we increasingly

understand how it relates to progressive changes in brain engage-
ment. This understanding is also richly informed by the many

factors that can accelerate the advance to Alzheimer’s, Parkinson’s

and other neurodegenerative diseases (e.g., decreased noradrener-
gic activity; see Marien et al., 2004; Jardanhazi-Kurutz et al., 2010,

2011; Kong et al., 2010; McNamee et al., 2010; Koffie et al., 2011;
Kalinin et al., 2012). We have extensively relied on this literature
in the designs of programs to try to assure that training programs
address the neurological, immunological, and vascular aspects of
age-related impairment.
We have collaborated with university-based scientists who
have conducted controlled studies in thousands of normally
aging individuals to evaluate the effectiveness of this approach.
Completed studies are still piecemeal, evaluating both the
modality-specific and the general cognitive and neurological

impacts of training in vision, hearing, executive control, atten-
tion, and related neuro-modulatory systems function. Studies of

social cognition training are underway. All studies reveal a sig-
nificant level of positive, enduring computerized training-driven

improvements. To briefly summarize: (1) Training targeting the
aural speech/language system have been shown to substantially

improve measured listening, memory and related cognitive abil-
ities, with significant far-transfer effects shown in quality of

life/everyday life assessments (Mahncke et al., 2006; Smith et al.,

2009; Zelinski et al., 2011). (Note that more than 250 addi-
tional studies demonstrating the behavioral and neurological

values of this form of training have documented in studies in

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Merzenich et al. Brain plasticity-based therapeutics

children and young adults. See Merzenich et al. (1998); and www.
scientificlearning.com. In studies conducted in individuals of all

ages, recoveries in perceptual abilities in listening have repeat-
edly documented rejuvenated speed of processing, accuracy, and

attention control in processing abilities). (2) Training target-
ing visual perception and related cognition abilities resulted, in

controlled trials, in significant improvements in visual process-
ing (e.g., Ball et al., 2007; Berry et al., 2010; Wolinsky et al.,

2013; see Figure 3). Improvements in speed and accuracy of

processing and improvements in spatial vision (saccade sam-
pling rates; multitasking; local and global reconstructions; scene

reconstruction; useful field of view) were repeatedly recorded in
these studies. These aural language and visual training studies
also extensively documented improvements in attention, working

memory, and immediate and delayed recall, and associative mem-
ory/syntactic abilities. (3) Studies document benefits of training

for executive control and temporal and spatial navigation pro-
cesses in training (e.g., see Ball et al., 2007; Smith et al., 2009;

Merzenich, 2013). With working memory and with the highest
levels of operation in social cognition, these explicit behaviors
normally directly engage frontal, posterior parietal, anterior and
posterior cingulate, medial ventral and hippocampal zones that

undergo disconnection as a pre-amble to AD onset. (4) Broad far-
transfer effects of training are recorded—e.g., to everyday quality

of life (Ball et al., 2007; Smith et al., 2009) to sustained confi-
dent independence (Edwards et al., 2009; Wolinsky et al., 2010a),

to resilience impacts against the onset of depression (Wolinsky

FIGURE 3 | Illustrating the magnitudes of gains for a limited computer
delivered epoch of training (about 10 h) in a large (n = 670) cohort of
healthy aged participants. Training was conducted “at home” or in a
clinical center at the University of Iowa. One population in the clinical
center completed a 4-h “booster” training session 6 months after initial
training program completion. All patients were behaviorally assessed
before, immediately after, and 1 year after training program completion.
Here, gains are expressed as an estimate of the number of years before
assessment scores would be predicted to fall below pre-training scores;
these highly significant gains had an average endurance of 3–4 years. Note
that the “UFOV composite” reflects the approximately 1 SD gain in brain
speed and visual control within an expanded visual field achieved directly
from the training. All other measures represent near and far-transfer effects
(i.e., benefits shown in untrained cognitive domains). Adapted from
Wolinsky et al. (2013).

et al., 2009), to measures documenting improved brain health
(Wolinsky et al., 2006, 2010b) and to sustained (Edwards et al.,
2009) and safer automobile driving (Ball et al., 2010)—among
other indices (Wolinsky et al., 2006, 2009, 2010a,b; Edwards et al.,
2009; Ball et al., 2010). (5) Positive improvements have been
shown to endure for many months to years following training
completion (e.g., Wolinsky et al., 2006, 2009, 2013; Zelinski et al.,
2011) (see Figure 3).
Does this form of training delay AD onset? Does it block, and

can it reverse neuropathology progressions? Answering that ques-
tion is the current goal of a large controlled internet-delivered

trial currently underway. A growing body of evidence provides
increasingly compelling evidence that this may, indeed, be the
case. By training thousands of individuals at risk for AD onset,

this question should be answerable, with finality, in the immedi-
ate future.

IMPEDIMENTS FOR DELIVERING THESE NEW TREATMENT
STRATEGIES TO PATIENTS IN NEED

The evolution of this new medical strategy for treating neu-
rological and psychiatric illness is a “textbook example” of a

disruptive technology. Its medicine is delivered via computers

and other smart devices, at very low cost, without any require-
ment for the immediate presence of a medical professional. The

scientific principles that support its use are poorly understood
by most of the professionals who would normally prescribe and

deliver this medicine. Most medical schools still focus on chemi-
cal and anatomical aspects of neuroscience on the path to creating

pharmaceutically-focused medicine. Most graduate training in

the psychology help professions still focus on “cognitive ther-
apy” approaches to rehabilitation, with limited formal training in

fundamental or integrative neuroscience on a level that informs
this brain plasticity-based translational approach. Technological
approaches are not the norm for a majority of practitioners in
both of these large professional communities (see McMinn et al.,
1999); even the minimum requirements in automated patient

monitoring of compliance and progress potentially requiring pro-
fessional participation and response delivered via the internet is

beyond routine clinical practice for many specialists.
The delivery of these programs has also been confounded by

a difficulty that the clinical community and public has in distin-
guishing between more classical cognitive therapeutic approaches

delivered by computer from programs developed with application
of a brain plasticity-based approach. Professional scientists have
repeatedly described the limitations of the former—for example
for achieving generalization beyond the directly trained tasks—
describing their findings as demonstrating the limited values
of any computer-delivered therapy. A result is great confusion

for the professional community and public about the valid-
ity of all computer-delivered therapeutics in the brain health

field.
Finally, the delivery of this form of medicine is impacted by
the demands for compliance required of the patient. As we have

noted earlier, driving the brain of an individual with schizophre-
nia or an individual at high risk for Alzheimer’s Disease onset

in a broadly re-strengthening direction can require many hours
of intensive training potentially only achieved over a period of

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Merzenich et al. Brain plasticity-based therapeutics

months. To substantially delay and to potentially achieve reliable
prophylaxis against the onset of neurodegenerative disease, or to
prevent schizophrenic onset, some almost-daily exercise may have
to be undertaken for the rest of the patient’s life. From a health

perspective, the gains from this form of medicine often com-
pletely justify that effort; about 50–100 h to improve the level of

cognitive ability for a patient with schizophrenia, for example (as
was applied, for example, in Fisher et al., 2009a,b), is, after all,

only about 1/100th the span of 1 year in their life. Clinical tri-
als requiring this level of participation are now underway. Still, a

public that is educated in ways that result in the broader patient
acceptance of these forms of treatment as medicine is a key to
their more successful, wider application.
Toward that end, the evaluation of program effectiveness
through an FDA medical device process or its equivalent is a
crucial part of our implementation strategy, and FDA-level trials
are now underway for treatments designed to improve or recover
the neurological status of patients with schizophrenia, traumatic
brain injury, and stroke.
AN ALTERNATIVE VISION OF PREDOMINANT FUTURE
TREATMENT MODES IN NEUROLOGICAL AND PSYCHIATRIC
MEDICINE
As our understanding of our fundamental human neurology
grows, the more we can expect it to be brought to bear as the basis
of neurotherapeutic medicine. Up to this point, brain medicine
has primarily followed a chemical therapeutics approach. When
deficits are attributable to processes operating across complexly
self-organizing brain systems whose functionality is impacted by

several dozen major variables and is implemented through hun-
dreds or thousands of gene-regulated chemicals, drug treatments

necessarily have limited impacts that can rarely if ever be regarded
as curative. Any “real cure” invariably requires complex brain
rewiring that only the brain itself can achieve. This is the primary
reason why there has been no major fundamentally new drug
approved for use for more than 20 years. It is also the primary
reason why addressing issues of aged infirmity that occur at an
end stage of functional deterioration shall be a failure. In the end,
only the brain, through its intrinsic plastic processes, can sustain

or repair itself, at the level required to sustain high functional-
ity. Those same good reasons explain that while pharmaceutical

treatments can often rescue individuals with major neurologically
and/or psychiatrically illness, the distortions manifested in their
illnesses including the neurological alterations that are the basis
of their disease routinely remain unaddressed (e.g., Opler et al.,
2014).
In part because of the unsatisfactory clinical outcomes from
chemical medicine, equally flourishing clinical practices try to

address neurological impairment and psychiatric illness by doc-
umenting behavioral abnormalities as a premise for engaging the

patient to directly address them. Again, the therapist commonly
looks for a linchpin in behavior that can ameliorate the broader
clinical symptoms. Because this strategy is usually removed from
the underlying etiological causes of system distortions or failures

in the brain, it again often fails to face up to the mechanis-
tic realities that account for the clinical problems borne by the

patient.

Brain plasticity-based therapeutics, still in its infancy, repre-
sents an attempt to address those real neurological distortions,

on a level at which something closer to a fundamental neu-
rological correction can potentially be achieved. As we under-
stand how brain systems organize themselves, in detail, through

their native plasticity processes, we understand with increasing

clarity what plasticity itself has contributed to disease symp-
toms. Even more importantly, we understand how to harness

these powerful intrinsic brain change processes to drive posi-
tive neurological corrections, on the path to something closer

to a “cure.” Initial attempts to drive neurological correction on
the requisite broad scale have usually generated still-incomplete

brain remodeling; this translational science is still at a prim-
itive stage, and very much a work in progress. At the same

time, the brains of individuals with clinical conditions as com-
plex as those that apply to the patient who is schizophrenic,

is frail and struggling and at risk for collapse in aging, or has

suffered from formerly-inexplicable visual field “blindness” fol-
lowing brain injury or stroke are clearly driven in a significantly

improving—indeed, at least in most neurological respects re-
normalizing—direction, by intensive computer-based training

designed on these scientific bases. This form of medicine is

inexpensive to deliver, as all it requires for operation is internet-
connected tablet/computer/smart-phone (see Fernandez, 2011),

and it is rapidly scalable for immediate application across the
world.
We believe that this represents the advent of a new era in
brain health medicine. In the future, we can expect to see
a healthy re-integration of chemical, cognitive-behavioral, and
brain plasticity-based therapeutic strategies. At the core, brain

plasticity-based therapeutics can be expected to drive fundamen-
tal re-normalizing corrections for distorted brain systems. Those

treatments shall be often supplemented in their actions by drugs

or gene therapies that help patients overcome specific biologi-
cal weaknesses assignable to genetic faults, or that augment the

power of plasticity processes to accelerate positive neurological
recovery. They shall also be supplemented by cognitive behavior

approaches that more appropriately and more powerfully local-
ize therapies to treat plasticity-induced distortions that spring

from each patient’s unique biographical history. With these novel
therapeutics, treatment of the distorted chemical brain merges
with treatment of the distorted behavior, on the grounds of brain
plasticity based therapeutics.
REFERENCES
Adcock, R. A., Dale, C., Fisher, M., Aldebot, S., Genevsky, A., Simpson,
G. V., et al. (2009). When top-down meets bottom-up: auditory training
enhances verbal memory in schizophrenia. Schizophr. Bull. 35, 1132–1141. doi:
10.1093/schbul/sbp068
Ahissar, E., Vaadia, E., Ahissar, M., Bergman, H., Arieli, A., and Abeles, M.

(1992). Dependence of cortical plasticity on correlated activity of single neu-
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Ahissar, M., Nahum, M., Nelken, I., and Hockstein, S. (2009). Reverse hierarchies
and sensory learning. Philos. Trans. R. Soc. Lond. B Biol. Sci. 364, 285–299. doi: 1.
Research Aim:
Understand the purpose of the study. What is the researcher trying to investigate?


2.
Hypothesis: 
Identify the hypothesis or predictions made by the researchers.


3.
Methodology




Participants: Note the sample size, demographics, and selection method.




Design: Understand whether the study is experimental, correlational, longitudinal, etc.




Procedures: Look at how the study was conducted, including any materials or tasks used.


4.
Results
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5.
Conclusion: 
Analyze the interpretations made by the researchers. Do they support the hypothesis?


6. 
Limitations: 
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7. 
Ethical Considerations
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8. 
Application: 
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9. 
Critical Evaluation:
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10.
Additional comments/notes (if any)