Unraveling Brain Functional Connectivity of encoding and retrieval in the context of education

Human memory is an enigmatic component of cognition which many researchers have attempted to comprehend. Accumulating studies on functional connectivity see brain as a complex dynamic unit with positively and negatively correlated networks in perfect coherence during a task. We aimed to examine coherence of network connectivity during visual memory encoding and retrieval in the context of education. School Educated (SE) and College Educated (CE) healthy volunteers (n = 60) were recruited and assessed for visual encoding and retrieval. Functional connectivity using seed to voxel based connectivity analysis of the posterior cingulate cortex (PCC) was evaluated. We noticed that there were reciprocal dynamic changes in both dorsolateral prefrontal cortex (DLPFC) region and PCC regions during working memory encoding and retrieval. In agreement with the previous studies, there were more positively correlated regions during retrieval compared to encoding. The default mode network (DMN) networks showed greater negative correlations during more attentive task of visual encoding. In tune with the recent studies on cognitive reserve we also found that number of years of education was a significant factor influencing working memory connectivity. SE had higher positive correlation to DLPFC region and lower negative correlation to DMN in comparison with CE during encoding and retrieval.     

Rotating With Rotated Text: A Natural Behavior Approach to Investigating Cognitive Offloading

Determining how we use our body to support cognition represents an important part of understanding the embodied and embedded nature of cognition. In the present investigation, we pursue this question in the context of a common perceptual task. Specifically, we report a series of experiments investigating head tilt (i.e., external normalization) as a strategy in letter naming and reading stimuli that are upright or rotated. We demonstrate that the frequency of this natural behavior is modulated by the cost of stimulus rotation on performance. In addition, we demonstrate that external normalization can benefit performance. All of the results are consistent with the notion that external normalization represents a form of cognitive offloading and that effort is an important factor in the decision to adopt an internal or external strategy.     

Evaluations Versus Expectations: Children's Divergent Beliefs About Resource Distribution

Past research reveals a tension between children's preferences for egalitarianism and ingroup favoritism when distributing resources to others. Here we investigate how children's evaluations and expectations of others' behaviors compare. Four‐ to 10‐year‐old children viewed events where individuals from two different groups distributed resources to their own group, to the other group, or equally across groups. Groups were described within a context of intergroup competition over scarce resources. In the Evaluation condition, children were asked to evaluate which resource distribution actions were nicer. In the Expectation condition, children were asked to predict which events were more likely to occur. With age, children's evaluations and expectations of others' actions diverged: Children evaluated egalitarian actions as nicer yet expected others to behave in ways that benefit their own group. Thus, children's evaluations about the way human social actors should behave do not mirror their expectations concerning those individuals' actions.     

SAwSu: An Integrated Model of Associative and Reinforcement Learning

Successfully explaining and replicating the complexity and generality of human and animal learning will require the integration of a variety of learning mechanisms. Here, we introduce a computational model which integrates associative learning (AL) and reinforcement learning (RL). We contrast the integrated model with standalone AL and RL models in three simulation studies. First, a synthetic grid‐navigation task is employed to highlight performance advantages for the integrated model in an environment where the reward structure is both diverse and dynamic. The second and third simulations contrast the performances of the three models in behavioral experiments, demonstrating advantages for the integrated model in accounting for behavioral data.     

Constructive criticism: An evaluation of Buller and Hardcastle's genetic and neuroscientific arguments against Evolutionary Psychology

David Buller and Valerie Hardcastle have argued that various discoveries about the genetics and nature of brain development show that most “central” psychological mechanisms cannot be adaptations because the nature of the contribution from the environment on which they are based shows they are not heritable. Some philosophers and scientists have argued that a strong role for the environment is compatible with high heritability as long as the environment is highly stable down lineages. In this paper I support this view by arguing that the discoveries Buller and Hardcastle refer to either do not show as strong a role for the environment as they suggest, or these discoveries show that the brain's developmental process depends in many cases on input from the environment that is highly stable across generations.     

Nonconceptualism and the cognitive impenetrability of early vision

This paper examines the relationship between cognitive impenetrability and perceptual nonconceptualism. I argue against the view, recently defended by Raftopoulos, that the (alleged) cognitive impenetrability of early vision is a necessary and sufficient condition for states of early vision and their content to be nonconceptual. I show that that view, here dubbed ‘the mutually entailing thesis’, admits two different standard interpretations depending on how we understand the property of being nonconceptual—corresponding to the distinction between the state and the content views of perceptual nonconceptualism. I first argue for the falsity of the state-nonconceptualist reading of the mutually entailing thesis, on the grounds that it mistakenly takes being nonconceptual to be a causal instead of a constitutive relationship. The content-nonconceptualist understanding of the thesis, I then argue, is disproved by plausible views regarding the content of experience. The mutually entailing thesis could only be true, I conclude, on a non-standard, causal interpretation of the notion of nonconceptual content. Yet, on that reading, the thesis would either be trivially true or would entirely fail to engage with the contemporary literature on perceptual nonconceptualism. Some potential relationships between the causal reading of the mutually entailing thesis and psychological research in this area are also briefly discussed.     

Why there might be a moral faculty: A reply to Johnson

Is there a cognitive faculty dedicated to the moral domain? Mark Johnson has developed a number of arguments against the existence of such a faculty. I claim that these arguments are not persuasive and that there may be a moral faculty.     

The myth of the moral faculty: Response to Kirkby

David Kirkby argues that I have misrepresented Marc Hauser's conception of a moral faculty, in a way that invalidates my chief arguments against the existence and necessity of such a faculty. The core of Kirkby's challenge is that what Hauser lists as necessary conditions for the moral faculty to do its work are not themselves components of that faculty. I argue that there is no useful way to distinguish necessary conditions of moral judgments from the alleged moral faculty itself, and that even if we could do this, we would be left with an empty non-explanation of the supposed moral faculty that amounts to nothing more than the claim that we have a faculty that generates judgments of right versus wrong.     

The cognitive impenetrability of the content of early vision is a necessary and sufficient condition for purely nonconceptual content

I elaborate on Pylyshyn's definition of the cognitive impenetrability (CI) of early vision, and draw on the role of concepts in perceptual processing, which links the problem of the CI or cognitive penetrability (CP) of early vision with the problem of the nonconceptual content (NCC) of perception. I explain, first, the sense in which the content of early vision is CI and I argue that if some content is CI, it is conceptually encapsulated, that is, it is NCC. Then, I examine the definitions of NCC and argue that they lead to the view that the NCC of perception is retrieved in a stage of visual processing that is CI. Thus, the CI of a state and content is a sufficient and necessary condition for the state and its content to be purely NCC, the CI?≡?NCC thesis. Since early vision is CI, the purely NCC of perception is formed in early vision. I defend the CI?≡?NCC thesis by arguing against objections raised against both the sufficient and the necessary part of the thesis.     

A neural cognitive model of argumentation with application to legal inference and decision making

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data).