Dopamine neurons in the ventral tegmental area use glutamate as a cotransmitter. To elucidate the behavioral role of the cotransmission, we targeted the glutamate-recycling enzyme glutaminase (gene Gls1). In mice with a dopamine transporter (Slc6a3)-driven conditional heterozygous (cHET) reduction of Gls1 in their dopamine neurons, dopamine neuron survival and transmission were unaffected, while glutamate cotransmission at phasic firing frequencies was reduced, enabling a selective focus on the cotransmission. The mice showed normal emotional and motor behaviors, and an unaffected response to acute amphetamine. Strikingly, amphetamine sensitization was reduced and latent inhibition potentiated. These behavioral effects, also seen in global GLS1 HETs with a schizophrenia resilience phenotype, were not seen in mice with an Emx1-driven forebrain reduction affecting most brain glutamatergic neurons. Thus, a reduction in dopamine neuron glutamate cotransmission appears to mediate significant components of the GLS1 HET schizophrenia resilience phenotype, and glutamate cotransmission appears to be important in attribution of motivational salience.DOI: http://dx.doi.org/10.7554/eLife.27566.001

Microsaccades are high-velocity fixational eye movements, with special roles in perception and cognition. The default microsaccade detection method is to determine when the smoothed eye velocity exceeds a threshold. We have developed a new method, Bayesian microsaccade detection (BMD), which performs inference based on a simple statistical model of eye positions. In this model, a hidden state variable changes between drift and microsaccade states at random times. The eye position is a biased random walk with different velocity distributions for each state. BMD generates samples from the posterior probability distribution over the eye state time series given the eye position time series. Applied to simulated data, BMD recovers the “true” microsaccades with fewer errors than alternative algorithms, especially at high noise. Applied to EyeLink eye tracker data, BMD detects almost all the microsaccades detected by the default method, but also apparent microsaccades embedded in high noise—although these can also be interpreted as false positives. Next we apply the algorithms to data collected with a Dual Purkinje Image eye tracker, whose higher precision justifies defining the inferred microsaccades as ground truth. When we add artificial measurement noise, the inferences of all algorithms degrade; however, at noise levels comparable to EyeLink data, BMD recovers the “true” microsaccades with 54% fewer errors than the default algorithm. Though unsuitable for online detection, BMD has other advantages: It returns probabilities rather than binary judgments, and it can be straightforwardly adapted as the generative model is refined. We make our algorithm available as a software package.

In many studies of attention-deficit hyperactivity disorder (ADHD), stimulus encoding and processing (perceptual function) and response selection (executive function) have been intertwined. To dissociate these functions, we introduced a task that parametrically varied low-level stimulus features (orientation and color) for fine-grained analysis of perceptual function, and that also required participants to switch their attention between feature dimensions on a trial-by-trial basis, thus taxing executive processes. Our response paradigm captured task-irrelevant motor output (TIMO), reflecting failures to use the correct stimulus-response rule. ADHD patients had substantially worse perceptual function than Controls, especially for orientation. ADHD participants had also higher TIMO; this measure was strongly affected by the switch manipulation. Across participants, the perceptual variability parameter was correlated with TIMO, suggesting that perceptual deficits could underlie executive function deficits. Based on perceptual variability alone, we were able to classify participants into ADHD and Controls with a mean accuracy of about 77%. Participants' self-reported General Executive Composite score correlated not only with TIMO but also with the perceptual variability parameter. Our results highlight the role of perceptual deficits in ADHD and the usefulness of computational modeling of behavior in dissociating perceptual from executive processes.In Attention Deficit Hyperactivity Disorder (ADHD), self-reported behavioral deficits have been attributed to differences in executive function, attention, and perceptual function. These brain functions can be objectively quantified with behavioral paradigms, but the individual components are often not well separated. ADHD patients tend to have worse executive function than Controls according to several metrics [1][2][3][4], predominantly in response execution and inhibition [5][6][7], but also in switching between stimulus-response rules [8][9][10][11]. It has been pointed out that non-executive processes, such as alertness, accumulation of evidence or drift rate, motivation, or reward processing, might interact with executive ones [12][13][14][15][16]. In the realm of visual attention, differences in accuracy or reaction time have been found in some visual search tasks but not in others [17,18], and no consistent deficits have been found in visuo-spatial orienting [19][20][21][22]. Despite evidence of impaired perceptual function in ADHD from psychiatric assessments [23,24], behavioral studies that examined the quality of perceptual encoding in ADHD in the absence of executive or attentional involvement found small and inconsistent differences (see [25] for a review). There have been attempts to dissociate executive from perceptual function in ADHD within a single task, but the results have been mixed [26][27][28][29]. One complicating factor could be that commonly used stimuli such as faces, letters, or numbers are high-dimensional and have content at many levels. Anot...

25Dopamine neurons in the ventral tegmental area use glutamate as a cotransmitter. To 26 elucidate the behavioral role of the cotransmission, we targeted the glutamate-recycling 27 enzyme glutaminase (gene GLS1). In mice with a DAT-driven conditional heterozygous 28 (cHET) reduction of GLS1 in their dopamine neurons, dopamine neuron survival and 29 transmission were unaffected, while glutamate cotransmission at phasic firing frequencies 30 was reduced, enabling focusing the cotransmission. DAT GLS1 cHET mice showed 31 normal emotional and motor behaviors, and an unaffected response to acute 32 amphetamine. Strikingly, amphetamine sensitization was reduced and latent inhibition 33 potentiated. These behavioral effects, also seen in global GLS1 HETs with a schizophrenia 34 resilience phenotype, were not seen in mice with an Emx1-driven forebrain reduction 35 affecting most brain glutamatergic neurons. Thus, a reduction in dopamine neuron 36 glutamate cotransmission appears to mediate significant components of the GLS1 HET 37 schizophrenia resilience phenotype, and glutamate cotransmission appears to be 38 important in attribution of motivational salience. 39

In many studies of attention-deficit hyperactivity disorder (ADHD), stimulus encoding and processing (perceptual function) and response selection (executive function) have been intertwined. To dissociate deficits in these functions, we introduced a task that parametrically varied low-level stimulus features (orientation and color) for fine-grained analysis of perceptual function. It also required participants to switch their attention between feature dimensions on a trial-by-trial basis, thus taxing executive processes. Furthermore, we used a response paradigm that captured task-irrelevant motor output (TIMO), reflecting failures to use the correct stimulus-response rule. ADHD participants had substantially higher perceptual variability than controls, especially for orientation, as well as higher TIMO. In both ADHD and controls, TIMO was strongly affected by the switch manipulation. Across participants, the perceptual variability parameter was correlated with TIMO, suggesting that perceptual deficits are associated with executive function deficits. Based on perceptual variability alone, we were able to classify participants into ADHD and controls with a mean accuracy of about 77%. Participants’ self-reported General Executive Composite score correlated not only with TIMO but also with the perceptual variability parameter. Our results highlight the role of perceptual deficits in ADHD and the usefulness of computational modeling of behavior in dissociating perceptual from executive processes.

Complex psychiatric disorders, such as schizophrenia, arise from a combination of genetic, developmental, environmental and social factors. These vulnerabilities can be mitigated by adaptive factors in each of these domains engendering resilience. Modeling resilience in mice using transgenic approaches offers a direct path to intervention, as resilience mutations point directly to therapeutic targets. As prototypes for this approach, we discuss the three mouse models of schizophrenia resilience, all based on modulating glutamatergic synaptic transmission. This motivates the broader development of schizophrenia resilience mouse models independent of specific pathophysiological hypotheses as a strategy for drug discovery. Three guiding validation criteria are presented. A resilience-oriented approach should identify pharmacologically tractable targets and in turn offer new insights into pathophysiological mechanisms.

Glutaminase-deficient mice (GLS1 hets), with reduced glutamate recycling, have a focal reduction in hippocampal activity, mainly in CA1, and manifest behavioral and neurochemical phenotypes suggestive of schizophrenia resilience. To address the basis for the hippocampal hypoactivity, we examined synaptic plastic mechanisms and glutamate receptor expression. While baseline synaptic strength was unaffected in Schaffer collateral inputs to CA1, we found that long-term potentiation was attenuated. In wild-type mice, GLS1 gene expression was highest in the hippocampus and cortex, where it was reduced by about 50% in GLS1 hets. In other brain regions with lower wild-type GLS1 gene expression there were no genotypic reductions. In adult GLS1 hets, NMDA receptor NR1 subunit gene expression was reduced, but not AMPA receptor GluR1 subunit gene expression. In contrast, juvenile GLS1 hets showed no reductions in NR1 gene expression. In concert with this, adult GLS1 hets showed a deficit in hippocampal-dependent contextual fear conditioning while juvenile GLS1 hets did not. These alterations in glutamatergic synaptic function may partly explain the hippocampal hypoactivity seen in the GLS1 hets. The maturity-onset reduction in NR1 gene expression and in contextual learning supports the premise that glutaminase inhibition in adulthood should prove therapeutic in schizophrenia.

Visual search is one of the most ecologically important perceptual task domains. One research tradition has studied visual search using simple, parametric stimuli and a signal detection theory or Bayesian modeling framework. However, this tradition has mostly focused on homogeneous distractors (distractors that are identical to each other), which are not very realistic. In a different tradition, Duncan and Humphreys (1989) conducted a landmark study on visual search in the presence of heterogeneous distractors. However, they used complex stimuli, making modeling and dissociation of component processes more difficult. Here, we attempt to unify these research traditions by systematically examining visual search with heterogeneous distractors using simple, parametric stimuli and a Bayesian modeling framework. Specifically, our experiment varied multiple factors that could potentially influence performance: set size, task (N-AFC localization vs detection), whether the target was revealed before or after the search array (perception versus memory), and stimulus spacing. Across all conditions, we found that performance decreased with increasing set size. We then examined various within-trial summary statistics, and found that the minimum target-to-distractor feature difference was a stronger predictor of behavior than the mean target-to-distractor difference and than distractor variance. To move from summary statistics to process-level understanding, we formulated a Bayesian optimal-observer model with a variable-precision encoding stage. This model, which makes trial-by-trial predictions, accurately accounted for all summary statistics. This was still the case when we fitted the model jointly to the localization and detection data. We replicated these results in a separate experiment with reduced stimulus spacing. Together, our results represent a critique of Duncan and Humphrey's purely descriptive approach, bring visual search with heterogeneous distractors firmly within the reach of quantitative process models, and affirm the unreasonable effectiveness of Bayesian models in explaining visual search.