Rules : the basis of morality...?

Most theories of moral knowledge, throughout history, have focused on behavior-guiding rules. Those theories attempt to identify which rules are the morally valid ones, and to identify the source or ground of that privileged set. The variations on this theme are many and familiar. But there is a problem here. In fact, there are several. First, many of the higher animals display a complex social order, one crucial to their biological success, and the members of such species typically display a sophisticated knowledge of what is and what is not acceptable social behavior—but those creatures have no language at all. They are unable even to express a single rule, let alone evaluate it for moral validity. Second, when we examine most other kinds of behavioral skills—playing basketball, playing the piano, playing chess—we discover that it is surpassingly difficult to articulate a set of discursive rules, which, if followed, would produce a skilled athlete, pianist, or chess master. And third, it would be physically impossible for a biological creature to identify which of its myriad rule are relevant to a given situation, and then apply them, in real time, in any case. All told, we would seem to need a new account of how our moral knowledge is stored, accessed, and applied. The present paper explores the potential, in these three regards, of recent alternative models from the computational neurosciences. The possibilities, it emerges, are considerable

Integration of Direction Cues Is Invariant to the Temporal Gap between Them

Many decisions involve integration of evidence conferred by discrete cues over time. However, the neural mechanism of this integration is poorly understood. Several decision-making models suggest that integration of evidence is implemented by a dynamic system whose state evolves toward a stable point representing the decision outcome. The internal dynamics of such point attractor models render them sensitive to the temporal gaps between cues because their internal forces push the state forward once it is dislodged from the initial stable point. We asked whether human subjects are as sensitive to such temporal gaps. Subjects reported the net direction of stochastic random dot motion, which was presented in one or two brief observation windows (pulses). Pulse strength and interpulse interval varied randomly from trial to trial. We found that subjects' performance was largely invariant to the interpulse intervals up to at least 1 s. The findings question the implementation of the integration process via mechanisms that rely on autonomous changes of network state. The mechanism should be capable of freezing the state of the network at a variety of firing rate levels during temporal gaps between the cues, compatible with a line of stable attractor states

Vacillation, indecision and hesitation in moment-by-moment decoding of monkey motor cortex

When choosing actions, we can act decisively, vacillate, or suffer momentary indecision. Studying how individual decisions unfold requires moment-by-moment readouts of brain state. Here we provide such a view from dorsal premotor and primary motor cortex. Two monkeys performed a novel decision task while we recorded from many neurons simultaneously. We found that a decoder trained using 'forced choices' (one target viable) was highly reliable when applied to 'free choices'. However, during free choices internal events formed three categories. Typically, neural activity was consistent with rapid, unwavering choices. Sometimes, though, we observed presumed 'changes of mind': the neural state initially reflected one choice before changing to reflect the final choice. Finally, we observed momentary 'indecision': delay forming any clear motor plan. Further, moments of neural indecision accompanied moments of behavioral indecision. Together, these results reveal the rich and diverse set of internal events long suspected to occur during free choice

Different population dynamics in the supplementary motor area and motor cortex during reaching

Neural populations perform computations through their collective activity. Different computations likely require different population-level dynamics. We leverage this assumption to examine neural responses recorded from the supplementary motor area (SMA) and motor cortex. During visually guided reaching, the respective roles of these areas remain unclear; neurons in both areas exhibit preparation-related activity and complex patterns of movement-related activity. To explore population dynamics, we employ a novel “hypothesis-guided” dimensionality reduction approach. This approach reveals commonalities but also stark differences: linear population dynamics, dominated by rotations, are prominent in motor cortex but largely absent in SMA. In motor cortex, the observed dynamics produce patterns resembling muscle activity. Conversely, the non-rotational patterns in SMA co-vary with cues regarding when movement should be initiated. Thus, while SMA and motor cortex display superficially similar single-neuron responses during visually guided reaching, their different population dynamics indicate they are likely performing quite different computations

Posterior parietal cortex guides visual decisions in rats

Neurons in putative decision-making structures can reflect both sensory and decision signals, making their causal role in decisions unclear. Here, we tested whether rat posterior parietal cortex (PPC) is causal for processing visual sensory signals or instead for accumulating evidence for decision alternatives. We optogenetically disrupted PPC activity during decision-making and compared effects on decisions guided by auditory vs. visual evidence. Deficits were largely restricted to visual decisions. To further test for visual dominance in PPC, we evaluated electrophysiological responses following individual sensory events and observed much larger response modulation following visual stimuli than auditory stimuli. Finally, we measured trial-to-trial spike count variability during stimulus presentation and decision formation. Variability sharply decreased, suggesting the network is stabilized by inputs, unlike what would be expected if sensory signals were locally accumulated. Our findings argue that PPC plays a causal role in processing visual signals that are accumulated elsewhere.SIGNIFICANCE STATEMENTDefining the neural circuits that support decision-making bridges a gap between our understanding of simple sensorimotor reflexes and our understanding of truly complex behavior. However, identifying brain areas which play a causal role in decision-making has proved challenging. We tested the causal role of a candidate component of decision circuits, the rat posterior parietal cortex (PPC). Our interpretation of the data benefitted from our use of animals trained to make decisions guided by either visual or auditory evidence. Our results argue that PPC plays a causal role specifically in visual decision-making, and that PPC may support sensory aspects of the decision, such as interpreting the visual signals so that evidence for a decision can be accumulated elsewhere

The Cost of Accumulating Evidence in Perceptual Decision Making

Decision making often involves the accumulation of information over time, but acquiring information typically comes at a cost. Little is known about the cost incurred by animals and humans for acquiring additional information from sensory variables due, for instance, to attentional efforts. Through a novel integration of diffusion models and dynamic programming, we were able to estimate the cost of making additional observations per unit of time from two monkeys and six humans in a reaction time (RT) random-dot motion discrimination task. Surprisingly, we find that the cost is neither zero nor constant over time, but for the animals and humans features a brief period in which it is constant but increases thereafter. In addition, we show that our theory accurately matches the observed reaction time distributions for each stimulus condition, the time-dependent choice accuracy both conditional on stimulus strength and independent of it, and choice accuracy and mean reaction times as a function of stimulus strength. The theory also correctly predicts that urgency signals in the brain should be independent of the difficulty, or stimulus strength, at each trial

The Explication Defence of Arguments from Reference

In a number of influential papers, Machery, Mallon, Nichols and Stich have presented a powerful critique of so-called arguments from reference, arguments that assume that a particular theory of reference is correct in order to establish a substantive conclusion. The critique is that, due to cross-cultural variation in semantic intuitions supposedly undermining the standard methodology for theorising about reference, the assumption that a theory of reference is correct is unjustified. I argue that the many extant responses to Machery et al.’s critique do little for the proponent of an argument from reference, as they do not show how to justify the problematic assumption. I then argue that it can in principle be justified by an appeal to Carnapian explication. I show how to apply the explication defence to arguments from reference given by Andreasen (for the biological reality of race) and by Churchland (against the existence of beliefs and desires)