Towards an atlas of canonical cognitive mechanisms

A central goal in Cognitive Science is understanding the mechanisms that underlie cognition. Here, we contend that Cognitive Science, despite intense multidisciplinary efforts, has furnished surprisingly few mechanistic insights. We attribute this slow mechanistic progress to the fact that cognitive scientists insist on performing underdetermined exercises, deriving overparametrised mechanistic theories of complex behaviours and seeking validation of these theories to the elusive notions of optimality and biological plausibility. We propose that mechanistic progress in Cognitive Science will accelerate once cognitive scientists start focusing on simpler explananda that will enable them to chart an atlas of elementary cognitive operations. Looking forward, the next challenge for Cognitive Science will be to understand how these elementary cognitive processes are pieced together to explain complex behaviour

Building Bridges between Perceptual and Economic Decision-Making: Neural and Computational Mechanisms

Investigation into the neural and computational bases of decision-making has proceeded in two parallel but distinct streams. Perceptual decision-making (PDM) is concerned with how observers detect, discriminate, and categorize noisy sensory information. Economic decision-making (EDM) explores how options are selected on the basis of their reinforcement history. Traditionally, the sub-fields of PDM and EDM have employed different paradigms, proposed different mechanistic models, explored different brain regions, disagreed about whether decisions approach optimality. Nevertheless, we argue that there is a common framework for understanding decisions made in both tasks, under which an agent has to combine sensory information (what is the stimulus) with value information (what is it worth). We review computational models of the decision process typically used in PDM, based around the idea that decisions involve a serial integration of evidence, and assess their applicability to decisions between good and gambles. Subsequently, we consider the contribution of three key brain regions – the parietal cortex, the basal ganglia, and the orbitofrontal cortex (OFC) – to perceptual and EDM, with a focus on the mechanisms by which sensory and reward information are integrated during choice. We find that although the parietal cortex is often implicated in the integration of sensory evidence, there is evidence for its role in encoding the expected value of a decision. Similarly, although much research has emphasized the role of the striatum and OFC in value-guided choices, they may play an important role in categorization of perceptual information. In conclusion, we consider how findings from the two fields might be brought together, in order to move toward a general framework for understanding decision-making in humans and other primates

Information integration in perceptual and value-based decisions

Research on the psychology and neuroscience of simple, evidence-based choices has led to an impressive progress in capturing the underlying mental processes as optimal mechanisms that make the fastest decision for a specified accuracy. The idea that decision-making is an optimal process stands in contrast with findings in more complex, motivation-based decisions, focussed on multiple goals with trade-offs. Here, a number of paradoxical and puzzling choice behaviours have been revealed, posing a serious challenge to the development of a unified theory of choice. These choice anomalies have been traditionally attributed to oddities at the representation of values and little is known about the role of the process under which information is integrated towards a decision. In a series of experiments, by controlling the temporal distribution of the decision-relevant information (i.e., sensory evidence or value), I demonstrate that the characteristics of this process cause many puzzling choice paradoxes, such as temporal, risk and framing biases, as well as preference reversal. In Chapter 3, I show that information integration is characterized by temporal biases (Experimental Studies 1-2, Computational Studies 1-3). In Chapter 4, I examine the way the integration process is affected by the immediate decision context (Experimental Studies 3-4, Computational Study 4), demonstrating that prior to integration, the momentary ranking of a sample modifies its magnitude. This principle is further scrutinized in Chapter 5, where a rank-dependent accumulation model is developed (Computational Study 5). The rank-dependent model is shown to underlie preference reversal in multi-attribute choice problems and to predict that choice is sensitive, not only to the mean strength of the information, but also to its variance, favouring riskier options (Computational Study 6). This prediction is further confirmed in Chapter 6, in a number of experiments (Experimental Studies 5-7) while the direction of risk preferences is found to be modulated by the cognitive perspective induced by the task framing (Experimental Study 8). I conclude that choice arises from a deliberative process which gathers samples of decision-relevant information, weighs them according to their salience and subsequently accumulates them. The salience of a sample is determined by i) its temporal order and ii) its local ranking in the decision context, while the direction of the weighting is controlled by the task framing. The implications of this simple, microprocess model are discussed with respect to choice optimality while directions for future research, towards the development of a unified theory of choice, are suggested

Идеологија, људскост и вредност. О Адорновом Стравинском

Theodor W. Adorno’s critique of Igor Stravinsky has itself been repeatedly criticised. Following the same line, the present article takes as its point of departure the philosophical anthropology of Helmuth Plessner, which challenges the premises of Marxist anthropology, on which Adorno based his critique of Stravinsky. Far from regressing to the inhuman and primitive, Stravinsky’s music affirms, in historically adequate modern terms, the constitutive reflectivity of the human embodied condition, thus becoming more “human”, i.e. meaningful and expressive, than Adorno could have even conceived. Additionally, an account is provided of some groundbreaking musical qualities that underpin the artistic value of Stravinsky’s music, which Adorno also contested.Адорнова критика Стравинског и сама је претрпела бројне критике. Пратећи ту исту линију, овај чланак као полазиште узима филозофску антропологију Хелмута Плеснера, која оспорава премисе марксистичке антропологије, на којој Адорно заснива своју критику Стравинског. Не регресирајући у нељудско и примитивно, музика Стравинског потврђује, у историјски адекватним модерним терминима, конститутивну рефлексивност људског отелотвореног стања, постајући тако више „људска”, тј. смислена и изражајна, него што је Адорно могао појмити. Осим тога, пажња је посвећена и неким револуционарним музичким квалитетима који подупиру уметничку вредност музике Стравинског, коју је Адорно такође оспоравао.Усвајајући марксистичко разумевање људске природе као нечега што је историјски варијабилно, Адорно сматра да Стравински, оповргавајући у својој музици модерни облик ове природе на идеолошки бременит начин, потврђује аспекте нељудскости и варваризма. Ипак, према филозофској антропологији Хелмута Плеснера, самосвесност и самоопредељење, наводно аспекти модерне хуманости, у ствари су неваријабилни аспекти сваке људскости. Као такви, они не нестају чак и у случају „примитивног” или инфантилног понашања, нарочито када је такво понашање добровољно и рефлексивно усвојено, као у случају музике Стравинског. Самосвесност и самоопредељење овде се разматрају као есенцијалне карактеристике специјалног, људског облика живота који се карактерише „ексцентричним позиционирањем”, термином који се користи како би се означила структурална дистанца живог бића у односу на себе. Структурална дистанца људи од њихових тела омогућава истовремено прагматичну и естетску контролу њихових тела и структура њихове перцепције у погледу материјалне форме, експресије и значења. Тако је музика Стравинског увек – већ експресивна и смислена, има „душу” и „дух”, без обзира на интенције композитора или било кога другог. Осим тога, управо се у плесном ставу – који није оријентисан ка циљу него има суштинско значење – хуманост показује с највећом јасноћом. То је још очигледније у плесним ставовима као оним у музици Стравинског, где неправилности и варијабилност метра и акцента изискују највећу могућу контролу над телом које плеше. У сваком случају, ритмичке неправилности, препознатљив идентитет који дисонантни акорди и секвенце тих акорада постижу кроз репетицију, слободно обликовање форме у погледу структуре које резултира импулсима игре њених елемената изван мотивско-тематске елаборације, развојних варијација или формалне телеологије, отварање неограниченог хоризонта звучних комбинација које дају фактор естетске релевантности не само интервалској, него и тимбралној артикулацији хармонских комплекса, само су неки од нових уметничких особина које подржавају уметничку вредност музике Стравинског и чувају је од напада пристрасне критике

Using time-varying evidence to test models of decision dynamics: bounded diffusion vs. the leaky competing accumulator model

When people make decisions, do they give equal weight to evidence arriving at different times? A recent study (Kiani et al., 2008) using brief motion pulses (superimposed on a random moving dot display) reported a primacy effect: pulses presented early in a motion observation period had a stronger impact than pulses presented later. This observation was interpreted as supporting the bounded diffusion (BD) model and ruling out models in which evidence accumulation is subject to leakage or decay of early-arriving information. We use motion pulses and other manipulations of the timing of the perceptual evidence in new experiments and simulations that support the leaky competing accumulator (LCA) model as an alternative to the BD model. While the LCA does include leakage, we show that it can exhibit primacy as a result of competition between alternatives (implemented via mutual inhibition), when the inhibition is strong relative to the leak. Our experiments replicate the primacy effect when participants must be prepared to respond quickly at the end of a motion observation period. With less time pressure, however, the primacy effect is much weaker. For 2 (out of 10) participants, a primacy bias observed in trials where the motion observation period is short becomes weaker or reverses (becoming a recency effect) as the observation period lengthens. Our simulation studies show that primacy is equally consistent with the LCA or with BD. The transition from primacy-to-recency can also be captured by the LCA but not by BD. Individual differences and relations between the LCA and other models are discussed

Dynamics of decision-making: from evidence accumulation to preference and belief

Decision-making is a dynamic process that begins with the accumulation of evidence and ends with the adjustment of belief. Each step is itself subject to a number of dynamic processes, such as planning, information search and evaluation. Furthermore, choice behavior reveals a number of challenging patterns, such as order effects and contextual preference reversal. Research in this field has converged toward a standard computational framework for the process of evidence integration and belief updating, based on sequential sampling models, which under some conditions are equivalent to normative Bayesian theory (Gold and Shadlen, 2007). A variety of models have been developed within the sequential sampling framework that can account for accuracy, response-time distributional data, and the speed-accuracy trade-off (Busemeyer and Townsend, 1993; Usher and Mcclelland, 2001; Brown and Heathcote, 2008; Ratcliff and McKoon, 2008). Yet there are differences between these models with regard to the mechanism of decision-termination, the optimality of the decision and the temporal weighting of the evidence. There is also a need to extend this framework to preference type of decisions (where the criteria are up to the judge) and to enrich it so as to include control processes (such as exploration/exploitation), information search, and adaptation to the environment, thereby allowing it to capture richer decision problems; for example, when alternatives are not pre-defined, or when the decision-maker is not just accumulating evidence but also adapting beliefs about the data-generating process. This Research Topic presents new work that investigates the dynamical and mathematical properties of evidence integration and its neural mechanisms and extends this framework to more complex decisions, such as those that occur during risky choice, preference formation, and belief updating. We hope these articles will encourage researchers to explore the computational and normative aspects of the decision process and the observed deviations. We briefly review here the contributions in this collection, starting from simple perceptual decisions in which the information flow is externally controlled to more complex decisions, which allow the observer to control the information flow and other learning strategies, and following on with preference formation

Human optional stopping in a heteroscedastic world

When making decisions, animals must trade off the benefits of information harvesting against the opportunity cost of prolonged deliberation. Deciding when to stop accumulating information and commit to a choice is challenging in natural environments, where the reliability of decision-relevant information may itself vary unpredictably over time (variable variance or "heteroscedasticity"). We asked humans to perform a categorization task in which discrete, continuously valued samples (oriented gratings) arrived in series until the observer made a choice. Human behavior was best described by a model that adaptively weighted sensory signals by their inverse prediction error and integrated the resulting quantities with a linear urgency signal to a decision threshold. This model approximated the output of a Bayesian model that computed the full posterior probability of a correct response, and successfully predicted adaptive weighting of decision information in neural signals. Adaptive weighting of decision information may have evolved to promote optional stopping in heteroscedastic natural environments. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

The influence of attention on value integration

People often have to make decisions based on many pieces of information. Previous work has found that people are able to integrate values presented in a Rapid Serial Visual Presentation (RSVP) stream to make informed judgements on the overall stream value (Tsetsos et al., 2012). It is also well known that attentional mechanisms influence how people process information. However, it is unknown how attentional factors impact value judgements of integrated material. The current study is the first of its kind to investigate whether value judgements are influenced by attentional processes when assimilating information. Experiments 1 to 3 examined whether the attentional salience of an item within an RSVP stream affected judgements of overall stream value. The results showed that the presence of an irrelevant high or low value salient item biased people to judge the stream as having a higher or lower overall mean value, respectively. Experiments 4 to 7 directly tested Tsetsos et al.’s (2012) theory examining whether extreme values in an RSVP stream become over-weighted, thereby capturing attention more than other values in the stream. The results showed that the presence of both a high (Experiments 4, 6 and 7) and a low (Experiment 5) value outlier captures attention leading to less accurate report of subsequent items in the stream. Taken together the results showed that valuations can be influenced by attentional processes, and can lead to less accurate subjective judgements