Planning-to-binge: Time allocation for future media consumption.

The prevalence of streaming media has led firms to embrace the phenomenon of "binge-watching" by offering entire multipart series simultaneously. Such "on-demand" availability allows consumers to choose how to allocate future viewing time, but such decisions have received little attention in the literature. Across several studies, we show that individuals can plan binging in advance by allocating time in ways that aggregate episode consumption. Thus, we expand our understanding of media consumption to a new timepoint, distinct from "in-the-moment" viewing. We demonstrate that planning-to-binge preferences are flexible and shaped by perceptions of the media of interest. In particular, they are greater for content whose episodes are perceived as more sequential and connected, as opposed to independent. Since our framework focuses on the media's structural continuity, it applies across hedonic and utilitarian time use, motivations, and content, including "binge-learning" plans for online education. Furthermore, increased plans-to-binge can be triggered by merely framing content as more sequential versus independent. Finally, consumers are willing to spend both money and time for the future opportunity to binge, and more so for sequential content. These findings suggest ways media companies may strategically emphasize content structure to influence consumer decisions and media viewing styles. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gender differences in "optimistic" information processing in uncertain decisions.

Decision-makers often are faced with uncertain situations in which they have incomplete information. While risky decisions include the probabilities of the possible outcomes, ambiguous decisions involve both unknown probabilities and unknown outcomes. Prior research has suggested that there are differences in how men and women evaluate risk, but evidence related to gender and ambiguity is mixed. The present work approaches this problem from a novel angle, focusing on the use of information that is present rather than the impact of information that is absent. It examines how individuals assign value in uncertain decisions based on the partial information they do have. While a main effect of gender on value is not observed, there is an enhanced "optimism bias" in how both favorable and unfavorable information influences the subjective value of ambiguous financial prospects for male compared to female participants. Unpacking these effects suggests multiple mechanisms, including a significant contribution of risk processing. Specifically, favorable and unfavorable information are over- and underweighted respectively in male participants' estimated likelihood of a winning outcome, and unfavorable information is underweighted in estimating certainty. There also is an interaction of gender and risk preferences, such that value increases more for male participants as the subjectively estimated likelihood of winning increases. A second experiment demonstrates this risk interaction effect is also observed for objective probabilities of winning, suggesting that the relationship between value and risk uses similar mechanisms across layers of uncertainty.

The unlikelihood effect: When knowing more creates the perception of less.

People face increasingly detailed information related to a range of risky decisions. To aid individuals in thinking through such risks, various forms of policy and health messaging often enumerate their causes. Whereas some prior literature suggests that adding information about causes of an outcome increases its perceived likelihood, we identify a novel mechanism through which the opposite regularly occurs. Across seven primary and six supplementary experiments, we find that the estimated likelihood of an outcome decreases when people learn about the (by- definition lower) probabilities of the pathways that lead to that outcome. This "unlikelihood" bias exists despite explicit communication of the outcome's total objective probability and occurs for both positive and negative outcomes. Indeed, awareness of a low-probability pathway decreases subjective perceptions of the outcome's likelihood even when its addition objectively increases the outcome's actual probability. These findings advance the current understanding of how people integrate information under uncertainty and derive subjective perceptions of risk. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Category Congruence of Display-Only Products Influences Attention and Purchase Decisions.

In e-commerce settings, shoppers can navigate to product-specific pages on which they are asked to make yes-or-no decisions about buying a particular item. Beyond that target, there are often other products displayed on the page, such as those suggested by the retailers' recommendation systems, that can influence consumers' buying behavior. We propose that display items that come from the same category as the target product (matched) may enhance target purchase by increasing the attractiveness of the presented opportunity. Contrasting this, mismatched display items may reduce purchase by raising awareness of opportunity costs. Eye-tracking was used to explore this framework by examining how different types of displays influenced visual attention. Although target purchase rates were higher for products with matched vs. mismatched displays, there was no difference in fixation time for the target images. However, participants attended to mismatched display items for more time than they did for matched ones consistent with the hypothesized processes. In addition, increases in display attractiveness increased target purchase, but only for matched items, in line with supporting the target category. Given the importance of relative attention and information in determining the impact of display items, we replicated the overall purchase effect across varying amounts of available display information in a second behavioral study. This demonstration of robustness supports the translational relevance of these findings for application in industry.

Dissociable components of the reward circuit are involved in appraisal versus choice.

People can evaluate a set of options as a whole, or they can approach those same options with the purpose of making a choice between them. A common network has been implicated across these two types of evaluations, including regions of ventromedial prefrontal cortex and the posterior midline. We test the hypothesis that sub-components of this reward circuit are differentially involved in triggering more automatic appraisal of one's options (Dorsal Value Network) versus explicitly comparing between those options (Ventral Value Network). Participants undergoing fMRI were instructed to appraise how much they liked a set of products (Like) or to choose the product they most preferred (Choose). Activity in the Dorsal Value Network consistently tracked set liking, across both task-relevant (Like) and task-irrelevant (Choose) trials. In contrast, the Ventral Value Network was particularly sensitive to evaluation condition (more active during Choose than Like trials). Within vmPFC, anatomically distinct regions were dissociated in their sensitivity to choice (ventrally, in medial OFC) versus appraisal (dorsally, in pregenual ACC). Dorsal regions additionally tracked decision certainty across both types of evaluation. These findings suggest that separable mechanisms drive decisions about how good one's options are versus decisions about which option is best.

The evil of banality: When choosing between the mundane feels like choosing between the worst.

Our most important decisions often provoke the greatest anxiety, whether we seek the better of two prizes or the lesser of two evils. Yet many of our choices are more mundane, such as selecting from a slate of mediocre but acceptable restaurants. Previous research suggests that choices of decreasing value should provoke decreasing anxiety. Here we show that this is not the case. Across three behavioral studies and one fMRI study, we find that anxiety and its neural correlates demonstrate a U-shaped function of choice set value, greatest when choosing between both the highest value and lowest value sets. Intermediate (moderate-value) choice sets provoke the least anxiety, even when they are just as difficult to select between as the choice sets at the two extremes. We show that these counterintuitive findings are accounted for by decision makers perceiving low-value items as aversive (i.e., negatively motivationally salient) rather than simply unrewarding. Importantly, though, neural signatures of these anxious reactions only appear when participants are required to choose one item from a set and not when simply appraising that set's overall value. Decision makers thus experience anxiety from competing avoidance motivations when forced to select among low-value options, comparable to the competing approach motivations they experience when choosing between high-value items. We further show that a common method of measuring subjective values (willingness to pay) can inadvertently censor a portion of this quadratic pattern, creating the misperception that anxiety simply increases linearly with set value. Collectively, these findings reveal the surprising costs of seemingly banal decisions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Timing in the absence of clocks: encoding time in neural network states.

Decisions based on the timing of sensory events are fundamental to sensory processing. However, the mechanisms by which the brain measures time over ranges of milliseconds to seconds remain unclear. The dominant model of temporal processing proposes that an oscillator emits events that are integrated to provide a linear metric of time. We examine an alternate model in which cortical networks are inherently able to tell time as a result of time-dependent changes in network state. Using computer simulations we show that within this framework, there is no linear metric of time, and that a given interval is encoded in the context of preceding events. Human psychophysical studies were used to examine the predictions of the model. Our results provide theoretical and experimental evidence that, for short intervals, there is no linear metric of time, and that time may be encoded in the high-dimensional state of local neural networks.

Experience-dependent plasticity in adult visual cortex.

Experience-dependent plasticity is a prominent feature of the mammalian visual cortex. Although such neural changes are most evident during development, adult cortical circuits can be modified by a variety of manipulations, such as perceptual learning and visual deprivation. Elucidating the underlying mechanisms at the cellular and synaptic levels is an essential step in understanding neural plasticity in the mature animal. Although developmental and adult plasticity share many common features, notable differences may be attributed to developmental cortical changes at multiple levels. These range from shifts in the molecular profiles of cortical neurons to changes in the spatiotemporal dynamics of network activity. In this review, we will discuss recent progress and remaining challenges in understanding adult visual plasticity, focusing on the primary visual cortex.

Different forms of homeostatic plasticity are engaged with distinct temporal profiles.

Global changes in network activity have been reported to induce homeostatic plasticity at multiple synaptic and cellular loci. Though individual types of plasticity are normally examined in isolation, it is their interactions and net effect that will ultimately determine their functional consequences. Here we examine homeostatic plasticity of both inhibition and intrinsic excitability in parallel in rat organotypic hippocampal slices. As previous studies have not examined inhibitory plasticity using a functional measure, inhibition was measured by the ability of evoked inhibitory postsynaptic potentials (IPSPs) to suppress action potentials, as well as IPSP amplitude. We show that manipulations of network activity can both up- and downregulate functional inhibition, as well as intrinsic excitability. However, these forms of plasticity are dissociable. Specifically, robust changes in intrinsic excitability were observed in the absence of inhibitory plasticity, and shifts in inhibition, but not excitability, appear to be sensitive to developmental stage. Our data establish that while the two forms of homeostatic plasticity can be engaged in parallel, there is a specific order in which they are expressed, with changes in excitability preceding those in inhibition. We propose that changes in intrinsic excitability occur first in order to stabilize network activity while optimizing the preservation of information stored in synaptic strengths by restricting changes that will disrupt the balance of synaptic excitation and inhibition.

Temporal specificity of perceptual learning in an auditory discrimination task.

Although temporal processing is used in a wide range of sensory and motor tasks, there is little evidence as to whether a single centralized clock or a distributed system underlies timing in the range of tens to hundreds of milliseconds. We investigated this question by studying whether learning on an auditory interval discrimination task generalizes across stimulus types, intervals, and frequencies. The degree to which improvements in timing carry over to different stimulus features constrains the neural mechanisms underlying timing. Human subjects trained on a 100- or 200-msec interval discrimination task showed an improvement in temporal resolution. This learning generalized to a perceptually distinct duration stimulus, as well as to the trained interval presented with tones at untrained spectral frequencies. The improvement in performance did not generalize to untrained intervals. To determine if spectral generalization was dependent on the importance of frequency information in the task, subjects were simultaneously trained on two different intervals identified by frequency. As a whole, our results indicate that the brain uses circuits that are dedicated to specific time spans, and that each circuit processes stimuli across nontemporal stimulus features. The patterns of generalization additionally indicate that temporal learning does not rely on changes in early, subcortical processing, because the nontemporal features are encoded by different channels at early stages.

Mechanisms and significance of spike-timing dependent plasticity.

Hebb's original postulate left two important issues unaddressed: (i) what is the effective time window between pre- and postsynaptic activity that will result in potentiation? and (ii) what is the learning rule that underlies decreases in synaptic strength? While research over the past 2 decades has addressed these questions, several studies within the past 5 years have shown that synapses undergo long-term depression (LTD) or long-term potentiation (LTP) depending on the order of activity in the pre- and postsynaptic cells. This process has been referred to as spike-timing dependent plasticity (STDP). Here we discuss the experimental data on STDP, and develop models of the mechanisms that may underlie it. Specifically, we examine whether the standard model of LTP and LTD in which high and low levels of Ca(2+) produce LTP and LTD, respectively, can also account for STDP. We conclude that the standard model can account for a type of STDP in which, counterintuitively, LTD will be observed at some intervals in which the presynaptic cell fires before the postsynaptic cell. This form of STDP will also be sensitive to parameters such as the presence of an after depolarization following an action potential. Indeed, the sensitivity of this type of STDP to experimental parameters suggests that it may not play an important physiological role in vivo. We suggest that more robust forms of STDP, which do not exhibit LTD at pre-before-post intervals, are not accounted for by the standard model, and are likely to rely on a second coincidence detector in addition to the NMDA receptor.

A model of spike-timing dependent plasticity: one or two coincidence detectors?

In spike-timing dependent plasticity (STDP), synapses exhibit LTD or LTP depending on the order of activity in the presynaptic and postsynaptic cells. LTP occurs when a single presynaptic spike precedes a postsynaptic one (a positive interspike interval, or ISI), while the reverse order of activity (a negative ISI) produces LTD. A fundamental question is whether the "standard model" of plasticity in which moderate increases in Ca(2+) influx through the N-methyl-D-aspartate (NMDA) channels induce LTD and large increases induce LTP, can account for the order and interval sensitivity of STDP. To examine this issue we developed a model that captures postsynaptic Ca(2+) influx dynamics and the associativity of the NMDA receptors. While this model can generate both LTD and LTP, it predicts that LTD will be observed at both negative and positive ISIs. This is because longer and longer positive ISIs induce monotonically decreasing levels of Ca(2+), which eventually fall into the same range that produced LTD at negative ISIs. A second model that incorporated a second coincidence detector in addition to the NMDA receptor generated LTP at positive intervals and LTD only at negative ones. Our findings suggest that a single coincidence detector model based on the standard model of plasticity cannot account for order-specific STDP, and we predict that STDP requires two coincidence detectors.

How do we tell time?

Animals time events on scales that range more than 10 orders of magnitude-from microseconds to days. This review focuses on timing that occurs in the range of tens to hundreds of milliseconds. It is within this range that virtually all the temporal cues for speech discrimination, and haptic and visual processing, occur. Additionally, on the motor side, it is on this scale that timing of fine motor movements takes place. To date, psychophysical data indicate that for many tasks there is a centralized timing mechanism, but that there are separate networks for different intervals. These data are supported by experiments that show that training to discriminate between two intervals generalizes to different modalities, but not different intervals. The mechanistic underpinnings of timing are not known. However various models have been proposed, they can be divided into labeled-line models and population clocks. In labeled-line models, different intervals are coded by activity in independent and discrete populations of neurons. In population models, time is coded by the population activity of a large group of neurons, and timing requires dynamic interaction between neurons. Population models are generally better suited for parallel processing of interval, duration, order, and sequence cues and are thus more likely to underlie timing in the range of tens to hundreds of milliseconds.