Faculty Bibliography

The Drift-Diffusion Model (DDM) is the prevalent computational model of the speed-accuracy trade-off in decision making. The DDM provides an explanation of behavior by optimally balancing reaction times and error rates. However, when applied to value-based decision making, the DDM makes the stark prediction that reaction times depend only on the relative utility difference between the options and not on absolute utility magnitudes. This prediction runs counter to evidence that reaction times decrease with higher utility magnitude. Here, we ask if and how it could be optimal for reaction times to show this observed pattern. We study an algorithmic framework that balances the cost of delaying rewards against the utility of obtained rewards. We find that the functional form of the cost of delay plays a key role, with the empirically observed pattern becoming optimal under multiplicative discounting. We add to the empirical literature by testing whether utility magnitude affects reaction times using a novel methodology that does not rely on functional form assumptions for the subjects' utilities. Our results advance the understanding of how and why reaction times are sensitive to the magnitude of rewards.

Most odors are not composed of a single volatile chemical species, but rather are mixtures of many different volatile molecules, the perception of which is dependent on the identity and relative concentrations of the components. Changing either the identity or ratio of components can lead to shifts between configural and elemental perception of the mixture. For example, a 30/70 ratio of ethyl isobutyrate (odorant A, a strawberry scent) and ethyl maltol (odorant B, a caramel scent) is perceived as pineapple by humans - a configural percept distinct from the components. In contrast, a 68/32 ratio of the same odorants is perceived elementally, and is identified as the component odors. Here, we examined single-unit responses in the anterior and posterior piriform cortex (aPCX and pPCX) of mice to these A and B mixtures. We first demonstrate that mouse behavior is consistent with a configural/elemental perceptual shift as concentration ratio varies. We then compared responses to the configural mixture to those evoked by the elemental mixture, as well as to the individual components. Hierarchical cluster analyses suggest that in the mouse aPCX, the configural mixture was coded as distinct from both components, while the elemental mixture was coded as similar to the components. In contrast, mixture perception did not predict pPCX ensemble coding. Similar electrophysiological results were also observed in rats. The results suggest similar perceptual characteristics of the AB mixture across species, and a division in the roles of aPCX and pPCX in the coding of configural and elemental odor mixtures.

Cochlear implants are one of the most successful neuroprosthetic devices that have been developed to date. Profoundly deaf patients can achieve speech perception after complete loss of sensory input. Despite the improvements many patients experience, there is still a large degree of outcome variability. It has been proposed that central plasticity may be a major factor in the different levels of benefit that patients experience. However, the neural mechanisms of how plasticity impacts cochlear implant learning and the degree of plasticity's influence remain unknown. Here, we review the human and animal research on three of the main ways that central plasticity affects cochlear implant outcomes.

Spiking activity of place cells in the hippocampus encodes the animal's position as it moves through an environment. Within a cell's place field, both the firing rate and the phase of spiking in the local theta oscillation contain spatial information. We propose a position-theta-phase (PTP) model that captures the simultaneous expression of the firing-rate code and theta-phase code in place cell spiking. This model parametrically characterizes place fields to compare across cells, time, and conditions; generates realistic place cell simulation data; and conceptualizes a framework for principled hypothesis testing to identify additional features of place cell activity. We use the PTP model to assess the effect of running speed in place cell data recorded from rats running on linear tracks. For the majority of place fields, we do not find evidence for speed modulation of the firing rate. For a small subset of place fields, we find firing rates significantly increase or decrease with speed. We use the PTP model to compare candidate mechanisms of speed modulation in significantly modulated fields and determine that speed acts as a gain control on the magnitude of firing rate. Our model provides a tool that connects rigorous analysis with a computational framework for understanding place cell activity.

Spatial navigation is influenced by cues from nearly every sensory modality and thus provides an excellent model for understanding how different sensory streams are integrated to drive behavior. Here we review recent work on multisensory control of navigation in the model organism Drosophila melanogaster, which allows for detailed circuit dissection. We identify four modes of integration that have been described in the literature-suppression, gating, summation, and association-and describe regions of the larval and adult brain that have been implicated in sensory integration. Finally we discuss what circuit architectures might support these different forms of integration. We argue that Drosophila is an excellent model to discover these circuit and biophysical motifs.

When resources, such as food, territory, and potential mates are limited, competition among animals of the same species is inevitable. Over bouts of agonistic interactions, winners and losers are determined. Losing is a traumatic experience, both physically and psychologically. Losers not only need to deploy a set of species-specific defensive behaviors to minimize the physical damage during defeat, but also adjust their behavior towards the winners to avoid future fights in which they are likely disadvantaged. The expression of defensive behaviors and the fast and long-lasting changes in behaviors accompanying defeat must be supported by a complex neural circuit. This review summarizes the brain regions that have been implicated in coping with social defeat, one centered on basolateral amygdala and the other on ventromedial hypothalamus. Gaps in our knowledge and hypotheses that may help guide future experiments are also discussed.

Most single units recorded from macaque secondary visual cortex (V2) respond with higher firing rates to synthetic texture images containing "naturalistic" higher-order statistics than to spectrally matched "noise" images lacking these statistics. In contrast, few single units in V1 show this property. We explored how the strength and dynamics of response vary across the different layers of visual cortex by recording multiunit (defined as high-frequency power in the local field potential) and gamma-band activity evoked by brief presentations of naturalistic and noise images in V1 and V2 of anesthetized macaque monkeys of both sexes. As previously reported, recordings in V2 showed consistently stronger responses to naturalistic texture than to spectrally matched noise. In contrast to single-unit recordings, V1 multiunit activity showed a preference for images with naturalistic statistics, and in gamma-band activity this preference was comparable across V1 and V2. Sensitivity to naturalistic image structure was strongest in the supragranular and infragranular layers of V1, but weak in granular layers, suggesting that it might reflect feedback from V2. Response timing was consistent with this idea. Visual responses appeared first in V1, followed by V2. Sensitivity to naturalistic texture emerged first in V2, followed by the supragranular and infragranular layers of V1, and finally in the granular layers of V1. Our results demonstrate laminar differences in the encoding of higher-order statistics of natural texture, and suggest that this sensitivity first arises in V2 and is fed back to modulate activity in V1.SIGNIFICANCE STATEMENT The circuit mechanisms responsible for visual representations of intermediate complexity are largely unknown. We used a well validated set of synthetic texture stimuli to probe the temporal and laminar profile of sensitivity to the higher-order statistical structure of natural images. We found that this sensitivity emerges first and most strongly in V2 but soon after in V1. However, sensitivity in V1 is higher in the laminae (extragranular) and recording modalities (local field potential) most likely affected by V2 connections, suggesting a feedback origin. Our results show how sensitivity to naturalistic image structure emerges across time and circuitry in the early visual cortex.