Kenneth T. Kishida

Self responses along cingulate cortex reveal quantitative neural phenotype for high-functioning autism.

Attributing behavioral outcomes correctly to oneself or to other agents is essential for all productive social exchange. We approach this issue in high-functioning males with autism spectrum disorder (ASD) using two separate fMRI paradigms. First, using a visual imagery task, we extract a basis set for responses along the cingulate cortex of control subjects that reveals an agent-specific eigenvector (self eigenmode) associated with imagining oneself executing a specific motor act. Second, we show that the same self eigenmode arises during ones own decision (the self phase) in an interpersonal exchange game (iterated trust game). Third, using this exchange game, we show that ASD males exhibit a severely diminished cingulate self response when playing the game with a human partner. This diminishment covaries parametrically with their behaviorally assessed symptom severity, suggesting its value as an objective endophenotype. These findings may provide a quantitative assessment tool for high-functioning ASD.

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

Previous studies have shown that N‐methyl‐d‐aspartate (NMDA) receptor activation results in production of reactive oxygen species (ROS) and activation of extracellular signal‐regulated 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 p47phox, 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.

Synaptic Plasticity Deficits and Mild Memory Impairments in Mouse Models of Chronic Granulomatous Disease

ABSTRACT Reactive oxygen species (ROS) are required in a number of critical cellular signaling events, including those underlying hippocampal synaptic plasticity and hippocampus-dependent memory; however, the source of ROS is unknown. We previously have shown that NADPH oxidase is required for N-methyl-d-aspartate (NMDA) receptor-dependent signal transduction in the hippocampus, suggesting that NADPH oxidase may be required for NMDA receptor-dependent long-term potentiation (LTP) and hippocampus-dependent memory. Herein we present the first evidence that NADPH oxidase is involved in hippocampal synaptic plasticity and memory. We have found that pharmacological inhibitors of NADPH oxidase block LTP. Moreover, mice that lack the NADPH oxidase proteins gp91phox and p47phox, both of which are mouse models of human chronic granulomatous disease (CGD), also lack LTP. We also found that the gp91phox and p47phox mutant mice have mild impairments in hippocampus-dependent memory. The gp91phox mutant mice exhibited a spatial memory deficit in the Morris water maze, and the p47phox mutant mice exhibited impaired context-dependent fear memory. Taken together, our results are consistent with NADPH oxidase being required for hippocampal synaptic plasticity and memory and are consistent with reports of cognitive dysfunction in patients with CGD.

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.

Subsecond dopamine fluctuations in human striatum encode superposed error signals about actual and counterfactual reward

Significance There is an abundance of circumstantial evidence (primarily work in nonhuman animal models) suggesting that dopamine transients serve as experience-dependent learning signals. This report establishes, to our knowledge, the first direct demonstration that subsecond fluctuations in dopamine concentration in the human striatum combine two distinct prediction error signals: (i) an experience-dependent reward prediction error term and (ii) a counterfactual prediction error term. These data are surprising because there is no prior evidence that fluctuations in dopamine should superpose actual and counterfactual information in humans. The observed compositional encoding of “actual” and “possible” is consistent with how one should “feel” and may be one example of how the human brain translates computations over experience to embodied states of subjective feeling. In the mammalian brain, dopamine is a critical neuromodulator whose actions underlie learning, decision-making, and behavioral control. Degeneration of dopamine neurons causes Parkinson’s disease, whereas dysregulation of dopamine signaling is believed to contribute to psychiatric conditions such as schizophrenia, addiction, and depression. Experiments in animal models suggest the hypothesis that dopamine release in human striatum encodes reward prediction errors (RPEs) (the difference between actual and expected outcomes) during ongoing decision-making. Blood oxygen level-dependent (BOLD) imaging experiments in humans support the idea that RPEs are tracked in the striatum; however, BOLD measurements cannot be used to infer the action of any one specific neurotransmitter. We monitored dopamine levels with subsecond temporal resolution in humans (n = 17) with Parkinson’s disease while they executed a sequential decision-making task. Participants placed bets and experienced monetary gains or losses. Dopamine fluctuations in the striatum fail to encode RPEs, as anticipated by a large body of work in model organisms. Instead, subsecond dopamine fluctuations encode an integration of RPEs with counterfactual prediction errors, the latter defined by how much better or worse the experienced outcome could have been. How dopamine fluctuations combine the actual and counterfactual is unknown. One possibility is that this process is the normal behavior of reward processing dopamine neurons, which previously had not been tested by experiments in animal models. Alternatively, this superposition of error terms may result from an additional yet-to-be-identified subclass of dopamine neurons.

Nonpolitical Images Evoke Neural Predictors of Political Ideology

Summary 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 machine-learning 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 animal-reminder 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.

Imaging Models of Valuation During Social Interaction in Humans

The role of dopamine neurons in value-guided behavior has been described in computationally explicit terms. These developments have motivated new model-based probes of reward processing in healthy humans, and in recent years these same models have also been used to design and understand neural responses during simple social exchange. These latter applications have opened up the possibility of identifying new endophenotypes characteristic of biological substrates underlying psychiatric disease. In this report, we review model-based approaches to functional magnetic resonance imaging in healthy individuals and the application of these paradigms to psychiatric disorders. We show early results from the application of model-based human interaction at three disparate levels: 1) interaction with a single human, 2) interaction within small groups, and 3) interaction with signals generated by large groups. In each case, we show how reward-prediction circuitry is engaged by abstract elements of each paradigm with blood oxygen level-dependent imaging as a read-out; and, in the last case (i.e., signals generated by large groups) we report on direct electrochemical dopamine measurements during decision making in humans. Lastly, we discuss how computational approaches can be used to objectively assess and quantify elements of complex and hidden social decision-making processes.

BOLD and its connection to dopamine release in human striatum: a cross-cohort comparison.

Activity in midbrain dopamine neurons modulates the release of dopamine in terminal structures including the striatum, and controls reward-dependent valuation and choice. This fluctuating release of dopamine is thought to encode reward prediction error (RPE) signals and other value-related information crucial to decision-making, and such models have been used to track prediction error signals in the striatum as encoded by BOLD signals. However, until recently there have been no comparisons of BOLD responses and dopamine responses except for one clear correlation of these two signals in rodents. No such comparisons have been made in humans. Here, we report on the connection between the RPE-related BOLD signal recorded in one group of subjects carrying out an investment task, and the corresponding dopamine signal recorded directly using fast-scan cyclic voltammetry in a separate group of Parkinsons disease patients undergoing DBS surgery while performing the same task. The data display some correspondence between the signal types; however, there is not a one-to-one relationship. Further work is necessary to quantify the relationship between dopamine release, the BOLD signal and the computational models that have guided our understanding of both at the level of the striatum. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

New approaches to investigating social gestures in autism spectrum disorder

The combination of economic games and human neuroimaging presents the possibility of using economic probes to identify biomarkers for quantitative features of healthy and diseased cognition. These probes span a range of important cognitive functions, but one new use is in the domain of reciprocating social exchange with other humans - a capacity perturbed in a number of psychopathologies. We summarize the use of a reciprocating exchange game to elicit neural and behavioral signatures for subjects diagnosed with autism spectrum disorder (ASD). Furthermore, we outline early efforts to capture features of social exchange in computational models and use these to identify quantitative behavioral differences between subjects with ASD and matched controls. Lastly, we summarize a number of subsequent studies inspired by the modeling results, which suggest new neural and behavioral signatures that could be used to characterize subtle deficits in information processing during interactions with other humans.

Single-Stimulus Functional MRI Produces a Neural Individual Difference Measure for Autism Spectrum Disorder

Functional MRI typically makes inferences about neural substrates of cognitive phenomena at the group level. We report the use of a single-stimulus blood-oxygen-level-dependent (BOLD) response in the cingulate cortex that differentiates individual children with autism spectrum disorder from matched typically developing control children with sensitivity and specificity of 63.6% and 73.7%, respectively. The approach consists of passive viewing of self and other faces from which an individual difference measure is derived from the BOLD response to the first self-face image only. The method, penalized logistic regression, requires no averaging over stimulus presentations or individuals. These findings show that single-stimulus functional MRI responses can be extracted from individual subjects and used profitably as a neural individual difference measure. The results suggest that single-stimulus functional MRI can be developed to produce quantitative neural biomarkers for other developmental disorders and may even be useful in the rapid typing of cognition in healthy individuals.