Jessey Wright

Independent Scholar

Data must be manipulated for their evidential import to be assessed. However, data analysis is regarded as a source of inferential errors by scientists and critics of neuroscience alike. In this chapter I argue that of data analysis is epistemically challenged in part because data are causally separated from the events that they are intended to pro...

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc pre...

Open data allows researchers to explore pre-existing datasets in new ways. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. We go on to discuss a number of correct...

Open data allows researchers to explore pre-existing datasets in new ways. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. We go on to discuss a number of correct...

Open data allows researchers to explore pre-existing datasets in new ways. However, if many researchers reuse the same dataset, multiple statistical testing may increase false positives. Here we demonstrate that sequential hypothesis testing on the same dataset by multiple researchers can inflate error rates. We go on to discuss a number of correct...

In network neuroscience, temporal network models have gained popularity. In these models, network properties have been related to cognition and behavior. Here, we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as the participation coefficient [PC]) in time‐varying contexts can potentially lead...

Arguments in support of open science tend to focus on confirmatory research practices. Here we argue that exploratory research should also be encouraged within the framework of open science. We lay out the benefits of 'open exploration' and propose two complementary ways to implement this with little infrastructural change.

The argument from inductive risk (AIR) is perhaps the most common argument against the value-free ideal of science. Brian MacGillivray rejects the AIR (at least as it would apply to risk assessment) and embraces the value-free ideal. We clarify the issues at stake and argue that MacGillivray's criticisms, although effective against some formulation...

The current neuroimaging workflow has matured into a large chain of processing and analysis steps involving a large number of experts, across imaging modalities and applications. The development and fast adoption of fMRIPrep [1] have revealed that neuroscientists need tools that simplify their research workflow, provide visual reports and checkpoin...

Open data has two principal uses: (i) to reproduce original findings and (ii) to allow researchers to ask new questions with existing data. The latter enables discoveries by allowing a more diverse set of viewpoints and hypotheses to approach the data, which is self-evidently advantageous for the progress of science. However, if many researchers re...

Functional magnetic resonance imaging (fMRI) is widely used to investigate the neural correlates of cognition. fMRI non-invasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc prepro...

Brain activity can be modelled as a temporal network of interconnected regions. Recently, in network neuroscience, temporal network models have gained popularity and their network properties have been related to cognition and behaviour. Here we demonstrate that calculating nodal properties that are dependent on temporal community structure (such as...

Interacting sets of nodes and fluctuations in their interaction are important properties of a dynamic network system. In some cases the edges reflecting these interactions are directly quantifiable from the data collected, however in many cases (such as functional magnetic resonance imaging (fMRI) data) the edges must be inferred from statistical r...

One way for an experience to provide an effective scaffold for learning is when the concepts and theories it is intended to help students grasp and understand can be used to productively analyze, make sense of, and discuss the experience itself. In this essay I propose that games and game mechanics can be used to create learning experiences amenabl...

Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances i...

Data must be manipulated for their evidential import to be assessed. However, data analysis is regarded as a source of inferential errors by scientists and critics of neuroscience alike. In this chapter I argue that of data analysis is epistemically challenged in part because data are causally separated from the events that they are intended to pro...

Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed with rapid advances in MR data...

Functional magnetic resonance imaging research is often associated with images of brains overlaid with patterns of color that indicate significant activity. These images are one of the most salient and recognizable pieces of evidence neuroscientists appeal to as justification for claims about the relationship between cognitive processes and human b...

A role of perirhinal cortex (PrC) in recognition memory for objects has been well established. Contributions of parahippocampal cortex (PhC) to this function, while documented, remain less well understood. Here, we used fMRI to examine whether the organization of item-based recognition memory signals across these two structures is shaped by object...

The problem of inadequate professional training for graduate students in teaching and pedagogy has recently come into sharp relief. Providing teacher training for philosophy graduate students through for-credit courses has been recommended as a solution to this problem. This paper provides an overview of the problem, identifies several aims such a...

Evidence from a large body of research suggests that perirhinal cortex (PrC), which interfaces the medial temporal lobe with the ventral visual pathway for object identification, plays a critical role in item-based recognition memory. The precise manner in which PrC codes for the prior occurrence of objects, however, remains poorly understood. In t...

In this article, I will show that a general and inclusive model for participation is one that includes: (1) explaining to students what participation is; (2) explaining why it is important to participate; (3) providing a list of modes of participation; and (4) methods for encouraging students to identify and pursue the modes that suit their individ...