Following Schrödinger's Code: A Personal Journey.

On a wintery afternoon over 60 years ago, I was browsing the Baker Library stacks at Dartmouth College and stumbled across a small book with an arresting title: What Is Life? [Schrödinger, E. What is Life? The physical aspect of the living cell and mind. Cambridge: Cambridge University Press, 1944]. This small volume contained numerous concepts that would transform the future of the biological sciences, giving rise to new fields, dogmas, approaches, and debates. Here, I present the core concepts of Schrödinger's book, the influence they have had on biology, and the influence they may continue to have on the cognitive neurosciences.

Harm to self outweighs benefit to others in moral decision making.

How we make decisions that have direct consequences for ourselves and others forms the moral foundation of our society. Whereas economic theory contends that humans aim at maximizing their own gains, recent seminal psychological work suggests that our behavior is instead hyperaltruistic: We are more willing to sacrifice gains to spare others from harm than to spare ourselves from harm. To investigate how such egoistic and hyperaltruistic tendencies influence moral decision making, we investigated trade-off decisions combining monetary rewards and painful electric shocks, administered to the participants themselves or an anonymous other. Whereas we replicated the notion of hyperaltruism (i.e., the willingness to forego reward to spare others from harm), we observed strongly egoistic tendencies in participants' unwillingness to harm themselves for others' benefit. The moral principle guiding intersubject trade-off decision making observed in our study is best described as egoistically biased altruism, with important implications for our understanding of economic and social interactions in our society.

On the research of time past: the hunt for the substrate of memory.

The search for memory is one of the oldest quests in written human history. For at least two millennia, we have tried to understand how we learn and remember. We have gradually converged on the brain and looked inside it to find the basis of knowledge, the trace of memory. The search for memory has been conducted on multiple levels, from the organ to the cell to the synapse, and has been distributed across disciplines with less chronological or intellectual overlap than one might hope. Frequently, the study of the mind and its memories has been severely restricted by technological or philosophical limitations. However, in the last few years, certain technologies have emerged, offering new routes of inquiry into the basis of memory. The 2016 Kavli Futures Symposium was devoted to the past and future of memory studies. At the workshop, participants evaluated the logic and data underlying the existing and emerging theories of memory. In this paper, written in the spirit of the workshop, we briefly review the history of the hunt for memory, summarizing some of the key debates at each level of spatial resolution. We then discuss the exciting new opportunities to unravel the mystery of memory.

Polyethylene glycol hydrogel rectal spacer implantation in patients with prostate cancer undergoing combination high-dose-rate brachytherapy and external beam radiotherapy.

PURPOSE: To present rectal toxicity rates in patients administered a polyethylene glycol (PEG) hydrogel rectal spacer in conjunction with combination high-dose-rate brachytherapy and external beam radiotherapy. METHODS AND MATERIALS: Between February 2010 and April 2015, 326 prostate carcinoma patients underwent combination high-dose-rate brachytherapy of 16 Gy (average dose 15.5 Gy; standard deviation [SD] = 1.6 Gy) and external beam radiotherapy of 59.4 Gy (average dose 60.2 Gy; SD = 2.9 Gy). In conjunction with the radiation therapy regimen, each patient was injected with 10 mL of a PEG hydrogel in the anterior perirectal fat space. The injectable spacer (rectal spacer) creates a gap between the prostate and the rectum. The rectum is displaced from the radiation field, and rectal dose is substantially reduced. The goal is a reduction in rectal radiation toxicity. Clinical efficacy was determined by measuring acute and chronic rectal toxicity using the National Cancer Center Institute Common Terminology Criteria for Adverse Events v4.0 grading scheme. RESULTS: Median followup was 16 months. The mean anterior-posterior separation achieved was 1.6 cm (SD = 0.4 cm). Rates of acute Grade 1 and 2 rectal toxicity were 37.4% and 2.8%, respectively. There were no acute Grade 3/4 toxicities. Rates of late Grade 1, 2, and 3 rectal toxicity were 12.7%, 1.4%, and 0.7%, respectively. There were no late Grade 4 toxicities. CONCLUSIONS: PEG rectal spacer implantation is safe and well tolerated. Acute and chronic rectal toxicities are low despite aggressive dose escalation.

The posteromedial region of the default mode network shows attenuated task-induced deactivation in psychopathic prisoners.

OBJECTIVE: Psychopathy is a personality disorder with symptoms that include lack of empathy or remorse, antisocial behavior, and excessive self-focus. Previous neuroimaging studies have linked psychopathy to dysfunction in the default mode network (DMN), a brain network that deactivates during externally focused tasks and is more engaged during self-referential processing. Specifically, the DMN has been found to remain relatively active in individuals with psychopathic tendencies during externally focused tasks, suggesting a failure to properly deactivate. However, the exact extent and nature of task-induced DMN dysfunction is poorly understood, including (a) the degree to which specific DMN subregions are affected in criminal psychopaths, and (b) how activity in these subregions relates to affective/interpersonal and antisocial/lifestyle traits of psychopathy. METHOD: We performed a group independent component analysis to assess DMN activation during a Go/NoGo task in a group of 22 high-psychopathy and 22 low-psychopathy prisoners. The identified group-level DMN was parcellated into 6 subregions, and group differences in task-induced activity were examined. RESULTS: In general, DMN subregions failed to deactivate beneath baseline in the high-psychopathy group. A group comparison with the low-psychopathy group localized this attenuated task-induced deactivation to the posteromedial cortical (mPC) region of the DMN. Moreover, multiple regression analyses revealed that activity in the mPC was associated with affective/interpersonal traits of psychopathy. CONCLUSION: These findings suggest that attenuated deactivation of the mPC subregion of the DMN is intrinsic to psychopathy, and is a pattern that may be more associated with affective psychopathic traits, including lack of concern for others.

Divergent hemispheric reasoning strategies: reducing uncertainty versus resolving inconsistency.

Converging lines of evidence from diverse research domains suggest that the left and right hemispheres play distinct, yet complementary, roles in inferential reasoning. Here, we review research on split-brain patients, brain-damaged patients, delusional patients, and healthy individuals that suggests that the left hemisphere tends to create explanations, make inferences, and bridge gaps in information, while the right hemisphere tends to detect conflict, update beliefs, support mental set-shifts, and monitor and inhibit behavior. Based on this evidence, we propose that the left hemisphere specializes in creating hypotheses and representing causality, while the right hemisphere specializes in evaluating hypotheses, and rejecting those that are implausible or inconsistent with other evidence. In sum, we suggest that, in the domain of inferential reasoning, the left hemisphere strives to reduce uncertainty while the right hemisphere strives to resolve inconsistency. The hemispheres' divergent inferential reasoning strategies may contribute to flexible, complex reasoning in the healthy brain, and disruption in these systems may explain reasoning deficits in the unhealthy brain.

Predictive accuracy in the neuroprediction of rearrest.

A recently published study by the present authors reported evidence that functional changes in the anterior cingulate cortex within a sample of 96 criminal offenders who were engaged in a Go/No-Go impulse control task significantly predicted their rearrest following release from prison. In an extended analysis, we use discrimination and calibration techniques to test the accuracy of these predictions relative to more traditional models and their ability to generalize to new observations in both full and reduced models. Modest to strong discrimination and calibration accuracy were found, providing additional support for the utility of neurobiological measures in predicting rearrest.

Neuroprediction of future rearrest.

Identification of factors that predict recurrent antisocial behavior is integral to the social sciences, criminal justice procedures, and the effective treatment of high-risk individuals. Here we show that error-related brain activity elicited during performance of an inhibitory task prospectively predicted subsequent rearrest among adult offenders within 4 y of release (N = 96). The odds that an offender with relatively low anterior cingulate activity would be rearrested were approximately double that of an offender with high activity in this region, holding constant other observed risk factors. These results suggest a potential neurocognitive biomarker for persistent antisocial behavior.

Shifting gears: seeking new approaches for mind/brain mechanisms.

Using an autobiographical approach, I review several animal and human split-brain studies that have led me to change my long-term view on how best to understand mind/brain interactions. Overall, the view is consistent with the idea that complex neural systems, like other complex information processing systems, are highly modular. At the same time, how the modules come to interact and produce unitary goals is unknown. Here, I review the importance of self-cueing in that process of producing unitary goals from disparate functions. The role of self-cueing is demonstrably evident in the human neurologic patient and especially in patients with hemispheric disconnection. When viewed in the context of modularity, it may provide insights into how a highly parallel and distributed brain locally coordinates its activities to produce an apparent unitary output. Capturing and understanding how this is achieved will require shifting gears away from standard linear models and adopting a more dynamical systems view of brain function.

Why share data? Lessons learned from the fMRIDC.

Neuroimaging and the discipline of cognitive neuroscience have grown together in lock-step with each pushing the other toward an improved ability to explore and examine brain function and form. However successful neuroimaging and the examination of cognitive processes may seem today, the culture of data sharing in these fields remains underdeveloped. In this article, we discuss our own experience in the development of the fMRI Data Center (fMRIDC) - a large-scale effort to gather, curate, and openly share the complete data sets from published research articles of brain activation studies using fMRI. We outline the fMRIDC effort's beginnings, how it operated, note some of the sociological reactions we received, and provide several examples of prominent new studies performed using data drawn from the archive. Finally, we provide comment on what considerations are needed for successful neuroimaging databasing and data sharing as existing and emerging efforts take the next steps in archiving and disseminating the field's valuable and irreplaceable data.

Dynamic network structure of interhemispheric coordination.

Fifty years ago Gazzaniga and coworkers published a seminal article that discussed the separate roles of the cerebral hemispheres in humans. Today, the study of interhemispheric communication is facilitated by a battery of novel data analysis techniques drawn from across disciplinary boundaries, including dynamic systems theory and network theory. These techniques enable the characterization of dynamic changes in the brain's functional connectivity, thereby providing an unprecedented means of decoding interhemispheric communication. Here, we illustrate the use of these techniques to examine interhemispheric coordination in healthy human participants performing a split visual field experiment in which they process lexical stimuli. We find that interhemispheric coordination is greater when lexical information is introduced to the right hemisphere and must subsequently be transferred to the left hemisphere for language processing than when it is directly introduced to the language-dominant (left) hemisphere. Further, we find that putative functional modules defined by coherent interhemispheric coordination come online in a transient manner, highlighting the underlying dynamic nature of brain communication. Our work illustrates that recently developed dynamic, network-based analysis techniques can provide novel and previously unapproachable insights into the role of interhemispheric coordination in cognition.

Neuroprediction, Violence, and the Law: Setting the Stage.

In this paper, our goal is to (a) survey some of the legal contexts within which violence risk assessment already plays a prominent role, (b) explore whether developments in neuroscience could potentially be used to improve our ability to predict violence, and (c) discuss whether neuropredictive models of violence create any unique legal or moral problems above and beyond the well worn problems already associated with prediction more generally. In "Violence Risk Assessment and the Law", we briefly examine the role currently played by predictions of violence in three high stakes legal contexts: capital sentencing ("Violence Risk Assessment and Capital Sentencing"), civil commitment hearings ("Violence Risk Assessment and Civil Commitment"), and "sexual predator" statutes ("Violence Risk Assessment and Sexual Predator Statutes"). In "Clinical vs. Actuarial Violence Risk Assessment", we briefly examine the distinction between traditional clinical methods of predicting violence and more recently developed actuarial methods, exemplified by the Classification of Violence Risk (COVR) software created by John Monahan and colleagues as part of the MacArthur Study of Mental Disorder and Violence [1]. In "The Neural Correlates of Psychopathy", we explore what neuroscience currently tells us about the neural correlates of violence, using the recent neuroscientific research on psychopathy as our focus. We also discuss some recent advances in both data collection ("Cutting-Edge Data Collection: Genetically Informed Neuroimaging") and data analysis ("Cutting-Edge Data Analysis: Pattern Classification") that we believe will play an important role when it comes to future neuroscientific research on violence. In "The Potential Promise of Neuroprediction", we discuss whether neuroscience could potentially be used to improve our ability to predict future violence. Finally, in "The Potential Perils of Neuroprediction", we explore some potential evidentiary ("Evidentiary Issues"), constitutional ("Constitutional Issues"), and moral ("Moral Issues") issues that may arise in the context of the neuroprediction of violence.

Understanding complexity in the human brain.

Although the ultimate aim of neuroscientific enquiry is to gain an understanding of the brain and how its workings relate to the mind, the majority of current efforts are largely focused on small questions using increasingly detailed data. However, it might be possible to successfully address the larger question of mind-brain mechanisms if the cumulative findings from these neuroscientific studies are coupled with complementary approaches from physics and philosophy. The brain, we argue, can be understood as a complex system or network, in which mental states emerge from the interaction between multiple physical and functional levels. Achieving further conceptual progress will crucially depend on broad-scale discussions regarding the properties of cognition and the tools that are currently available or must be developed in order to study mind-brain mechanisms.

Right hemisphere dominance in visual statistical learning.

Several studies report a right hemisphere advantage for visuospatial integration and a left hemisphere advantage for inferring conceptual knowledge from patterns of covariation. The present study examined hemispheric asymmetry in the implicit learning of new visual feature combinations. A split-brain patient and normal control participants viewed multishape scenes presented in either the right or the left visual fields. Unbeknownst to the participants, the scenes were composed from a random combination of fixed pairs of shapes. Subsequent testing found that control participants could discriminate fixed-pair shapes from randomly combined shapes when presented in either visual field. The split-brain patient performed at chance except when both the practice and the test displays were presented in the left visual field (right hemisphere). These results suggest that the statistical learning of new visual features is dominated by visuospatial processing in the right hemisphere and provide a prediction about how fMRI activation patterns might change during unsupervised statistical learning.