My brain—and yours—is blessed with neuroplasticity. More than other species’ brains, ours can adapt by reorganizing after damage or by building new experience-based pathways. Although neuroplasticity is greatest in childhood, adult brains also change with experience. Master pianists, ballerinas, and jugglers have enlarged brain networks that manifest their acquired knowledge and skills. Brain plasticity is also at work in those of us who experience a new world of sound, enabled by a cochlear implant (CI). For many, the initial result of CI activation is underwhelming—squeaky high-pitched sounds rather than understood speech—followed by several months of gradually increasing voice comprehension as the brain adapts. Recalibrating voices. My immediate response to CI activation was happily more rewarding. “What is your middle name?” I heard the audiologist ask my previously deaf ear (reminding me of Alexander Graham Bell’s first telephone words: “Mr. Watson—come here—I want to see you”). To be sure, her words were barely—and not always—discernible. And they came with the squeaky voice of the little girl who had seemingly occupied her body. But now my plastic brain had something to work on. The ENT surgeon attributed the high-pitched voice to implant’s disproportionately high-pitched stimulation. (The cochlear wire only reaches through about 1.5 of the cochlea’s 2.5 turns—its high-frequency region—beyond which the electrodes would need to be so close that they would interfere with each other.) But with time, I am assured, my brain will recalibrate, and already that's happening. Aural rehabilitation. As pianists, ballerinas, and jugglers can train their plastic brains, so too those experiencing disabilities can, to some extent, retrain their brains. By prescribing a stroke patient to use only the “bad” hand or leg—constraint-induced therapy, it’s called—dexterity will often increase. One person who had been partially paralyzed by a stroke gradually learned, by cleaning tables with their good hand restrained, to write again and even play tennis with the affected hand. Ditto for CI recipients, who are told to anticipate up to a year of gradually improving speech perception as their plastic brain adjusts to the new input. To assist that process, I am advised to dedicate time each day to watching captioned TV, or listening to speech with just the CI. If needed, recipients can also undergo word-recognition training. Happily, I seem not to need word training. Within the first week of receiving the CI’s input, some adaption was already evident, with speech becoming increasingly intelligible. Even with the hearing aid in my other ear replaced with an earplug, I can, in a quiet room, converse with someone via the CI alone. And with the enhanced binaural hearing I can again attend department meetings and chat with folks amid a coffee hour. I also seemingly benefit from a curious phenomenon of auditory selective attention. I can listen to what sounds like a) squeaky voices with my left, CI-assisted ear, b) normal voices with my right, hearing-aid assisted ear, or c) the improved hearing from both inputs combined—yet with normal voice perception predominating. Moreover, I am experiencing . . . A new world of sound. An unanticipated outcome of my CI activation has been various objects coming to life. My implant activation has caused my silent office clock to start audibly clicking the seconds. my congregation’s tepid singing to become more vibrant. our previously inaudible garbage disposal and car—both of which I have left running overnight—to make noticeable sound. (Not that you’ve ever wondered, but a running car, when left unattended for 10 hours, drinks about a quarter tank.) What strange CI powers are these . . . to cause previously silent objects to make sound! Honestly, however, I am awestruck by those of you with normal hearing. You swim amid an ocean of inescapable sound, yet somehow manage, without constant distraction, to filter and attend to pertinent sounds, such as one particular voice. You are amazing. But then for us all, hearing is a  wonder. Imagine a science fiction novel in which alien creatures transferred thoughts from one head to another by pulsating air molecules. That is us! As we converse, we are—in ways we don’t comprehend—converting what’s in our mind into vocal apparatus vibrations that send air molecules bumping through space, creating waves of compressed and expanded air. On reaching our recipient’s eardrums, the resulting vibrations jiggle the middle ear bones, triggering fluid waves down the adjacent cochlea. These bend the hair cell receptors, which trigger neural impulses up the auditory nerve to our brain—which somehow decodes the pulsations into meaning. From mind to air pressure waves to mechanical waves to fluid waves to electrochemical waves to mind, we communicate. Mind-to-mind communication via jostling air molecules: As the Psalmist exclaimed, we are “wonderfully made.” (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com or his new essay collection, How Do We Know Ourselves: Curiosities and Marvels of the Human Mind. Follow him on Twitter: @davidgmyers.) ... View more

“I am among [Michigan’s] 300 plus ‘Juvenile Lifers,’” a prisoner known to his friends as Chan wrote me in 1994, kindly passing along a math error he had caught in one of my textbooks. More than half a lifetime ago, Chan, as a 17-year-old, had joined a friend in committing an armed robbery and murder. He expressed “great remorse and regret” for his crime, as well as his hope to learn and grow with the goal of contributing “something of substance and worth.” In the ensuing six years of our occasional correspondence, Chan—an intelligent and now deeply religious man—has been described to me by others, including the retired superintendent of his former prison, as a model prisoner. He is excelling in prison-taught college courses. After taking introductory psychology with my text, he alerted me that Aristotle’s Apothegems is actually spelled Apothegms. Chan, now in his mid-40s, would much rather be contributing to society and paying taxes than having his room and board funded by Michigan taxpayers, whose $2.06 billion prison budget impedes our governor’s fulfilling her campaign pledge to “fix the damn roads.” But does society somehow benefit from keeping those who have committed an impulsive juvenile crime endlessly locked up? Might Chan, if released, still be a risk? Hardly. Teens’ inhibitory frontal lobes lag the development of their emotional limbic system. With brains not yet fully prepared to calculate long-term consequences, the result is teen impulsiveness and emotionality. No wonder arrest rates for rape, assault, and murder soar during the teen years and decline after age 20—to a much lower level by the mid-40s. As psychologist David Lykken noted, “We could avoid two-thirds of all crime simply by putting all able-bodied young men in cryogenic sleep from the age of 12 through 28.” By that time, the frontal lobes have matured, testosterone is subsiding, and men are mellowing. Middle-aged men are not just adolescents with inflated waistlines. But if the incarceration of juvenile lifers like Chan is costly to society, might it nevertheless deter future Chans from violent acts? Alas, when committing an impulsive act or a crime of passion, people seldom pause to calmly calculate the long-term consequences. (Even the threat of capital punishment does not predict lower state homicide rates.) Any deterrence effect lies less with the length of a punishment than with its probability—its swiftness and sureness. The immaturity of the teen brain and the diminishing risk of violence with age, as explained in Supreme Court briefs by the American Psychological Association and other health associations, contributed to the Court’s 2012 ruling that mandatory life-without-parole sentences for juveniles violated the constitutional prohibition of cruel and unusual punishment. Even discretionary life-without-parole sentences were unconstitutional, it ruled, except for “the rarest of juvenile offenders, those whose crimes reflect permanent incorrigibility.” Then, last week, the Court qualified that judgment by affirming the life sentence of Mississippian Brett Jones, who—when barely age 15, and after a lifetime of abuse—responded to his grandfather’s reportedly hitting him by impulsively stabbing his grandfather to death. Like Chan, Jones, now 31, is said to be “remorseful for his crime, hardworking and a ‘good kid’” who gets along with everybody. How ironic, commentators noted, that the majority opinion—that teens can forever be held responsible for their juvenile misdeeds—was written by Justice Brett Kavanaugh, who had argued during his confirmation hearings that holding him responsible for his high school yearbook page was “a new level of absurdity.” Moreover, responded Justice Sonia Sotomayor, this decision will prevent hundreds of other juvenile defendants, 70 percent of whom are people of color, from securing early release. zodebala/E+/Getty Images Nevertheless, there has been increasing bipartisan concern about the human and financial costs of lengthy mass incarceration for long-ago transgressions. The Smarter Sentencing Act, co-sponsored by Senators Mike Lee (R-Utah) and Dick Durbin (D-Illinois), responds to the reality that the seven-fold increased federal prison population since 1980 makes such incarceration “one of our nation’s biggest expenditures, dwarfing the amount spent on law enforcement.” Surely, we can say yes to public protection, but also yes to smarter sentencing—sentencing that holds the Chans and Brett Joneses accountable for their acts, while also recognizing that the impulsive, momentary act of an immature teen needn’t predict one’s distant future. Indeed, how many of us would like to be judged today by the worst moments of our immature adolescence? (For David Myers’ other essays on psychological science and everyday life, visit TalkPsych.com; follow him on Twitter: @DavidGMyers.) ... View more

At long last, artificial intelligence (AI)—and its main subset, machine learning—is beginning to fulfill its promise. When fed massive amounts of data, computers can discern patterns (as in speech recognition) and make predictions or decisions. AlphaZero, a Google-related computer system, started playing chess, shogi (Japanese chess), and GO against itself. Before long, thanks to machine learning, AlphaZero progressed from no knowledge of each game to “the best player, human or computer, the world has ever seen.” DrAfter123/DigitalVision Vectors/Getty Images I’ve had recent opportunities to witness the growing excitement about machine learning in the human future, through conversations with Adrian Weller (a Cambridge University scholar who is program director for the UK’s national institute for data science and AI). Andrew Briggs (Oxford’s Professor of Nanomaterials, who is using machine learning to direct his quantum computing experiments and, like Weller, is pondering what machine learning portends for human flourishing). Brian Odegaard (a UCLA post-doc psychologist who uses machine learning to identify brain networks that underlie human consciousness and perception). Two new medical ventures (to which—full disclosure—my family foundation has given investment support) illustrate machine learning’s potential: Fifth Eye, a University of Michigan spinoff, has had computers mine data on millions of heartbeats from critically ill hospital patients—to identify invisible, nuanced signs of deterioration. By detecting patterns that predict patient crashes, the system aims to provide a potentially life-saving early warning system (well ahead of doctors or nurses detecting anything amiss). Delphinus, which offers a new ultrasound alternative to mammography, will similarly use machine learning from thousands of breast scans to help radiologists spot potent cancer cells. Other machine-learning diagnostic systems are helping physicians to identify strokes, retinal pathology, and (using sensors and language predictors) the risk of depression or suicide. Machine learning of locked-in ALS patients’ brain wave patterns associated with “Yes” and “No” answers has enabled them to communicate their thoughts and feelings. And it is enabling researchers to translate brain activity into speech.   Consider, too, a new Pew Research Center study of gender representation in Google images. Pew researchers first harvested an archive of 26,981 gender-labeled human faces from different countries and ethnic groups. They fed 80 percent of these images into a computer, which used machine learning to discriminate male and female faces. When tested on the other 20 percent, the system achieved 95 percent accuracy.   Pew researchers next had the system use its new human-like gender-discrimination ability to  identify the gender of persons shown in 10,000 Google images associated with 105 common occupations. Would the gender representation in the image search results overrepresent, underrepresent, or accurately represent their proportions, as reported by U.S. Bureau of Labor Statistics (BLS) data summaries?   The result? Women, relative to their presence in the working world, were significantly underrepresented in some categories and overrepresented in others. For example, the BLS reports that 57 percent of bartenders are female—as are only 29 percent of the first 100 people shown in Google image searches of “bartender” (as you can see for yourself). Searches for “medical records technician,” “probation officer,” “general manager,” “chief executive,” and “security guard” showed a similar underrepresentation. But women were overrepresented, relative to their working proportion, in Google images for “police,” “computer programmer,” “mechanic,” and “singer.” Across all 105 jobs, men are 54 percent of those employed and 60 percent of those pictured. The bottom line: Machine learning reveals (in Google users’ engagement) a subtle new form of gender bias.   As these examples illustrate, machine learning holds promise for helpful application and research. But it will also entail some difficult ethical questions.   Imagine, for example, that age, race, gender, or sexual orientation are incorporated into algorithms that predict recidivism among released prisoners. Would it be discriminatory, or ethical, to use such demographic predictors in making parole decisions?   Such questions already exist in human judgments, but may become more acute if and when we ask machines to make these decisions. Or is there reason to hope that it will be easier to examine and tweak the inner workings of an algorithmic system than to do so with a human mind?   (For David Myers’ other essays on psychological science and everyday life visit www.TalkPsych.com.) ... View more

Psychological science delights us with its occasional surprises. For example, who would have imagined that electroconvulsive therapy—shocking the brain into mild convulsions—would often be an effective antidote to otherwise intractable depression? massive losses in brain tissue early in life could have minimal later effects? siblings’ shared home environment would have such a small effect on their later traits? after brain damage, a person may learn new skills yet be unaware of such? visual information is deconstructed into distinct components (motion, form, depth, and color), processed by distinct brain regions, and then reintegrated into a perceived whole?   The latest who-would-have-believed-it finding is that the microbiology of the gut may influence the moods of the brain. Digestive-system bacteria reportedly influence human emotions and even social interactions, perhaps by producing neurotransmitters. Moreover, we are told (such as here and here), healthy gut microbes can reduce anxiety, depression, and PTSD.   New articles on this supposedly “revolutionary” and “paradigm-shifting” microbiota-gut-brain (MGB) research are accumulating, report Katarzyna Hooks, Jan Pieter Konsman, and Maureen O’Malley in a forthcoming (yet-to-be-edited) review. By comparing rodents or humans with or without intestinal microbiota, researchers have indeed found “suggestive” effects on how organisms respond to stress and display emotions. Some researchers are exploring microbiota-related interventions (such as with probiotics versus placebos) as a possible treatment for depression, anxiety, and anorexia nervosa.   The findings are intriguing and worth pursuing but haven’t yet definitively demonstrated “the impact of the microbiota itself on behavior,” say Hooks, Konsman, and O’Malley. Nevertheless, the popular press, sometimes aided by university press offices, has hyped the research in more than 300 articles. People love the news of this research, say Hooks et al., because it lends hope that a natural, healthy diet can provide a simple DIY solution to troubling emotions.   Reading this analysis triggers déjà vu. This cycle of (a) an intriguing finding, followed by (b) hype, followed by (c) reassessment, is an occasional feature of our science’s history. Mind-blowing experiments on people with split brains yielded (a) believe-it-or-not findings, leading to (b) overstated claims about left-brained and right-brained people, which (c) finally settled into a more mature understanding of how distinct brain areas function as a whole integrated system.   Despite the “large helpings of overinterpretation” and the overselling of “currently limited findings,” the Hooks team encourages researchers to press on. “We see MGB research as a field full of promise, with important implications for understanding the relationship between the brain and the rest of the body.” The body (brain included) is one whole system.   (For David Myers’ other weekly essays on psychological science and everyday life visit TalkPsych.com) ... View more

Originally posted on July 15, 2014. Most of us have read over and again that the human brain has 100 billion neurons.  With no source but legend for that big round number—and not wanting merely to echo an undocumented estimate from other books—I set off in search of a more precise estimate.  Surely someone must have sampled brain tissue, counted neurons, and extrapolated a nerve cell estimate for the whole brain.  (It’s not that the number affects our understanding of how the brain works, but we might as well get the facts right.) One researcher whose name I was disposed to trust—Gabrielle De Courten-Myers—explained to me by e-mail how she used “histological neuronal density and cortical thickness measurements in 30 cortical samples each from 6 males 12 to 24 years old,” from which she extrapolated an estimate of 23 billion neurons for the male cerebral cortex.  Although she didn’t have data for the rest of the brain, her guess in 2005 was that a whole-brain total would be “somewhere around 40 billion neurons.” Later, a different research team, using a method that is beyond my pay grade to understand (but apparently involved making a “brain soup” of four male brains, postmortem, and counting neural nuclei) estimated 86 billion neurons in the male brain (though yet another expert with whom I corresponded questioned the validity of their method). So, how many neurons have we in our human brains?  Apparently something less than 100 billion, but the number is uncertain.  What’s more certain is that we should be suspicious of unsourced big round numbers:  “The brain has 100 billion neurons.” “Ten percent of people are gay.”  “We typically use but 10 percent of our brains.”  ... View more

Originally posted on September 23, 2014. In the September Observer (from the Association for Psychological Science), Nathan explains why “Brain Size Matters.”  He summarizes, and suggests how to teach, Robin Dunbar’s conclusion that “Our brain size evolved to accommodate social groups that contain roughly 150 people.” In the same issue, David’s essay on “Inspiring Interest in Interests” recaps research on the stability and motivational power of career-related interests, and offers students links to inventories that can assess their own interests and well-matched vocations. ... View more