Economic probes of mental function and the extraction of computational phenotypes

AbstractEconomic games are now routinely used to characterize human cognition across multiple dimensions. These games allow for effective computational modeling of mental function because they typically come equipped with notions of optimal play, which provide quantitatively prescribed target functions that can be tracked throughout an experiment. The combination of these games, computational models, and neuroimaging tools open up the possibility for new ways to characterize normal cognition and associated brain function. We propose that these tools may also be used to characterize mental dysfunction, such as that found in a range of psychiatric illnesses. We describe early efforts using a multi-round trust game to probe brain responses associated with healthy social exchange and review how this game has provided a novel and useful characterization of autism spectrum disorder. Lastly, we use the multi-round trust game as an example to discuss how these kinds of games could produce novel bases for representing healthy behavior and brain function and thus provide objectively identifiable subtypes within a broad spectrum of mental function

An efficiency framework for valence processing systems inspired by soft cross-wiring

Recent experiments suggest that subsecond dopamine delivery to human striatum encodes a combination of reward prediction errors and counterfactual errors thus composing the actual with the possible into one neurochemical signal. Here, we present a model where the counterfactual part of these striatal dopamine fluctuations originates in another valuation system that shadows the dopamine system by acting as its near-antipode in terms of spike-rate encoding yet co-releases dopamine alongside its own native neurotransmitter. We show that such a hypothesis engenders important representational consequences where valence processing appears subject to the efficient encoding considerations common to the visual and auditory systems. This new perspective opens up important computational consequences for understanding how value-predicting information should integrate with sensory processing streams

Nonpolitical Images Evoke Neural Predictors of Political Ideology

Political ideologies summarize dimensions of life that define how a person organizes their public and private behavior, including their attitudes associated with sex, family, education, and personal autonomy [1, 2]. Despite the abstract nature of such sensibilities, fundamental features of political ideology have been found to be deeply connected to basic biological mechanisms [3–7] that may serve to defend against environmental challenges like contamination and physical threat [8–12]. These results invite the provocative claim that neural responses to nonpolitical stimuli (like contaminated food or physical threats) should be highly predictive of abstract political opinions (like attitudes toward gun control and abortion) [13]. We applied a machinelearning method to fMRI data to test the hypotheses that brain responses to emotionally evocative images predict individual scores on a standard political ideology assay. Disgusting images, especially those related to animalreminder disgust (e.g., mutilated body), generate neural responses that are highly predictive of political orientation even though these neural predictors do not agree with participants’ conscious rating of the stimuli. Images from other affective categories do not support such predictions. Remarkably, brain responses to a single disgusting stimulus were sufficient to make accurate predictions about an individual subject’s political ideology. These results provide strong support for the idea that fundamental neural processing differences that emerge under the challenge of emotionally evocative stimuli may serve to structure political beliefs in ways formerly unappreciated

Dopamine and serotonin in human substantia nigra track social context and value signals during economic exchange

Dopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson’s disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players. They rejected more offers in the human than the computer condition, an effect of social context associated with higher overall levels of dopamine but not serotonin. Regardless of the social context, relative changes in dopamine tracked trial-by-trial changes in offer value—akin to reward prediction errors—whereas serotonin tracked the current offer value. These results show that dopamine and serotonin fluctuations in one of the basal ganglia’s main output structures reflect distinct social context and value signals

Sub-Second Dopamine Detection in Human Striatum

Fast-scan cyclic voltammetry at carbon fiber microelectrodes allows rapid (sub-second) measurements of dopamine release in behaving animals. Herein, we report the modification of existing technology and demonstrate the feasibility of making sub-second measurements of dopamine release in the caudate nucleus of a human subject during brain surgery. First, we describe the modification of our electrodes that allow for measurements to be made in a human brain. Next, we demonstrate in vitro and in vivo, that our modified electrodes can measure stimulated dopamine release in a rat brain equivalently to previously determined rodent electrodes. Finally, we demonstrate acute measurements of dopamine release in the caudate of a human patient during DBS electrode implantation surgery. The data generated are highly amenable for future work investigating the relationship between dopamine levels and important decision variables in human decision-making tasks

The Protective Action Encoding of Serotonin Transients in the Human Brain

The role of serotonin in human brain function remains elusive due, at least in part, to our inability to measure rapidly the local concentration of this neurotransmitter. We used fast-scan cyclic voltammetry to infer serotonergic signaling from the striatum of fourteen brains of human patients with Parkinson's disease. Here we report these novel measurements and show that they correlate with outcomes and decisions in a sequential investment game. We find that serotonergic concentrations transiently increase as a whole following negative reward prediction errors, while reversing when counterfactual losses predominate. This provides initial evidence that the serotonergic system acts as an opponent to dopamine signaling, as anticipated by theoretical models. Serotonin transients on one trial were also associated with actions on the next trial in a manner that correlated with decreased exposure to poor outcomes. Thus, the fluctuations observed for serotonin appear to correlate with the inhibition of over-reactions and promote persistence of ongoing strategies in the face of short-term environmental changes. Together these findings elucidate a role for serotonin in the striatum, suggesting it encodes a protective action strategy that mitigates risk and modulates choice selection particularly following negative environmental events

Nanotools for Neuroscience and Brain Activity Mapping

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function

Neuroeconomic Approaches to Mental Disorders

The pervasiveness of decision-making in every area of human endeavor highlights the importance of understanding choice mechanisms and their detailed relationship to underlying neurobiological function. This review surveys the recent and productive application of game-theoretic probes (economic games) to mental disorders. Such games typically possess concrete concepts of optimal play, thus providing quantitative ways to track when subjects' choices match or deviate from optimal. This feature equips economic games with natural classes of control signals that should guide learning and choice in the agents that play them. These signals and their underlying physical correlates in the brain are now being used to generate objective biomarkers that may prove useful for exposing and understanding the neurogenetic basis of normal and pathological human cognition. Thus, game-theoretic probes represent some of the first steps toward producing computationally principled, objective measures of cognitive function and dysfunction useful for the diagnosis, treatment, and understanding of mental disorders

NADPH oxidase is required for NMDA receptor-dependent activation of ERK in hippocampal area CA1

Abstract Previous studies have shown that N-methyl-D-aspartate (NMDA) receptor activation results in production of reactive oxygen species (ROS) and activation of extracellular signalregulated kinase (ERK) in hippocampal area CA1. In addition, application of ROS to hippocampal slices has been shown to result in activation of ERK in area CA1. To determine whether these events were linked causally, we investigated whether ROS are required for NMDA receptor-dependent activation of ERK. In agreement with previous studies, we found that treatment of hippocampal slices with NMDA resulted in activation of ERK in area CA1. The NMDA receptor-dependent activation of ERK was either blocked or attenuated by a number of antioxidants, including the general antioxidant N-acetyl-L-cysteine (L-NAC), the superoxide-scavenging enzyme superoxide dismutase (SOD), the membrane-permeable SOD mimetic Mn(III) tetrakis (4-benzoic acid) porphyrin (MnTBAP), the hydrogen peroxide-scavenging enzyme catalase, and the catalase mimetic ebselen. The NMDA receptor-dependent activation of ERK also was blocked by the NADPH oxidase inhibitor diphenylene iodonium (DPI) and was absent in mice that lacked p47 phox , one of the required protein components of NADPH oxidase. Taken together, our results suggest that ROS production, especially superoxide production via NADPH oxidase, is required for NMDA receptor-dependent activation of ERK in hippocampal area CA1