Transitions in cognitive evolution.

The evolutionary history of animal cognition appears to involve a few major transitions: major changes that opened up new phylogenetic possibilities for cognition. Here, we review and contrast current transitional accounts of cognitive evolution. We discuss how an important feature of an evolutionary transition should be that it changes what is evolvable, so that the possible phenotypic spaces before and after a transition are different. We develop an account of cognitive evolution that focuses on how selection might act on the computational architecture of nervous systems. Selection for operational efficiency or robustness can drive changes in computational architecture that then make new types of cognition evolvable. We propose five major transitions in the evolution of animal nervous systems. Each of these gave rise to a different type of computational architecture that changed the evolvability of a lineage and allowed the evolution of new cognitive capacities. Transitional accounts have value in that they allow a big-picture perspective of macroevolution by focusing on changes that have had major consequences. For cognitive evolution, however, we argue it is most useful to focus on evolutionary changes to the nervous system that changed what is evolvable, rather than to focus on specific cognitive capacities.

Holistic resource-rational analysis.

We argue that Lieder and Griffiths' method for analyzing rational process models cannot capture an important constraint on resource allocation, which is competition between different processes for shared resources (Klein 2018, Biology and Philosophy33:36). We suggest that holistic interactions between processes on at least three different timescales - episodic, developmental, and evolutionary - must be taken into account by a complete resource-bounded explanation.

What insects can tell us about the origins of consciousness.

How, why, and when consciousness evolved remain hotly debated topics. Addressing these issues requires considering the distribution of consciousness across the animal phylogenetic tree. Here we propose that at least one invertebrate clade, the insects, has a capacity for the most basic aspect of consciousness: subjective experience. In vertebrates the capacity for subjective experience is supported by integrated structures in the midbrain that create a neural simulation of the state of the mobile animal in space. This integrated and egocentric representation of the world from the animal's perspective is sufficient for subjective experience. Structures in the insect brain perform analogous functions. Therefore, we argue the insect brain also supports a capacity for subjective experience. In both vertebrates and insects this form of behavioral control system evolved as an efficient solution to basic problems of sensory reafference and true navigation. The brain structures that support subjective experience in vertebrates and insects are very different from each other, but in both cases they are basal to each clade. Hence we propose the origins of subjective experience can be traced to the Cambrian.

Ghosts in machine learning for cognitive neuroscience: Moving from data to theory.

The application of machine learning methods to neuroimaging data has fundamentally altered the field of cognitive neuroscience. Future progress in understanding brain function using these methods will require addressing a number of key methodological and interpretive challenges. Because these challenges often remain unseen and metaphorically "haunt" our efforts to use these methods to understand the brain, we refer to them as "ghosts". In this paper, we describe three such ghosts, situate them within a more general framework from philosophy of science, and then describe steps to address them. The first ghost arises from difficulties in determining what information machine learning classifiers use for decoding. The second ghost arises from the interplay of experimental design and the structure of information in the brain - that is, our methods embody implicit assumptions about information processing in the brain, and it is often difficult to determine if those assumptions are satisfied. The third ghost emerges from our limited ability to distinguish information that is merely decodable from the brain from information that is represented and used by the brain. Each of the three ghosts place limits on the interpretability of decoding research in cognitive neuroscience. There are no easy solutions, but facing these issues squarely will provide a clearer path to understanding the nature of representation and computation in the human brain.

Interpreting the dimensions of neural feature representations revealed by dimensionality reduction.

Recent progress in understanding the structure of neural representations in the cerebral cortex has centred around the application of multivariate classification analyses to measurements of brain activity. These analyses have proved a sensitive test of whether given brain regions provide information about specific perceptual or cognitive processes. An exciting extension of this approach is to infer the structure of this information, thereby drawing conclusions about the underlying neural representational space. These approaches rely on exploratory data-driven dimensionality reduction to extract the natural dimensions of neural spaces, including natural visual object and scene representations, semantic and conceptual knowledge, and working memory. However, the efficacy of these exploratory methods is unknown, because they have only been applied to representations in brain areas for which we have little or no secondary knowledge. One of the best-understood areas of the cerebral cortex is area MT of primate visual cortex, which is known to be important in motion analysis. To assess the effectiveness of dimensionality reduction for recovering neural representational space we applied several dimensionality reduction methods to multielectrode measurements of spiking activity obtained from area MT of marmoset monkeys, made while systematically varying the motion direction and speed of moving stimuli. Despite robust tuning at individual electrodes, and high classifier performance, dimensionality reduction rarely revealed dimensions for direction and speed. We use this example to illustrate important limitations of these analyses, and suggest a framework for how to best apply such methods to data where the structure of the neural representation is unknown.

Taxonomising delusions: content or aetiology?

INTRODUCTION: Many theoretical treatments assume (often implicitly) that delusions ought to be taxonomised by the content of aberrant beliefs. A theoretically sound, and comparatively under-explored, alternative would split and combine delusions according to their underlying cognitive aetiology. METHODS: We give a theoretical review of several cases, focusing on monothematic delusions of misidentification and on somatoparaphrenia. RESULTS: We show that a purely content-based taxonomy is empirically problematic. It does not allow for projectability of discoveries across all members of delusions so delineated, and lumps together delusions that ought to be separated. We demonstrate that an aetiological approach is defensible, and further that insofar as content-based approaches are plausible, it is only to the extent that they implicitly link content to aetiology. CONCLUSIONS: We recommend a more explicit focus on cognitive aetiology as the grounds for delusion taxonomy, even when that would undermine traditional content-based boundaries. We also highlight the iterative and complex nature of evidence about aetiologically grounded taxonomies.

Comparing cognition across major transitions using the hierarchy of formal automata.

The evolution of cognition can be understood in terms of a few major transitions-changes in the computational architecture of nervous systems that changed what cognitive capacities could be evolved by downstream lineages. We demonstrate how the idea of a major cognitive transition can be modeled in terms of where a system's effective computational architecture falls on the well-studied hierarchy of formal automata (HFA). We then use recent work connecting artificial neural networks to the HFA, which provides a way to make the structure-architecture link in natural systems. We conclude with reflections on the power and the challenges of traditional thinking when applied to neural architectures. This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition Psychology > Comparative Philosophy > Foundations of Cognitive Science.

Polarization and trust in the evolution of vaccine discourse on Twitter during COVID-19.

Trust in vaccination is eroding, and attitudes about vaccination have become more polarized. This is an observational study of Twitter analyzing the impact that COVID-19 had on vaccine discourse. We identify the actors, the language they use, how their language changed, and what can explain this change. First, we find that authors cluster into several large, interpretable groups, and that the discourse was greatly affected by American partisan politics. Over the course of our study, both Republicans and Democrats entered the vaccine conversation in large numbers, forming coalitions with Antivaxxers and public health organizations, respectively. After the pandemic was officially declared, the interactions between these groups increased. Second, we show that the moral and non-moral language used by the various communities converged in interesting and informative ways. Finally, vector autoregression analysis indicates that differential responses to public health measures are likely part of what drove this convergence. Taken together, our results suggest that polarization around vaccination discourse in the context of COVID-19 was ultimately driven by a trust-first dynamic of political engagement.

Attention and counter-framing in the Black Lives Matter movement on Twitter.

The social media platform Twitter platform has played a crucial role in the Black Lives Matter (BLM) movement. The immediate, flexible nature of tweets plays a crucial role both in spreading information about the movement's aims and in organizing individual protests. Twitter has also played an important role in the right-wing reaction to BLM, providing a means to reframe and recontextualize activists' claims in a more sinister light. The ability to bring about social change depends on the balance of these two forces, and in particular which side can capture and maintain sustained attention. The present study examines 2 years worth of tweets about BLM (about 118 million in total). Timeseries analysis reveals that activists are better at mobilizing rapid attention, whereas right-wing accounts show a pattern of moderate but more sustained activity driven by reaction to political opponents. Topic modeling reveals differences in how different political groups talk about BLM. Most notably, the murder of George Floyd appears to have solidified a right-wing counter-framing of protests as arising from dangerous "terrorist" actors. The study thus sheds light on the complex network and rhetorical effects that drive the struggle for online attention to the BLM movement.

The coordination dilemma for epidemiological modelers.

Epidemiological models directly shape policy responses to public health crises. We argue that they also play a less obvious but important role in solving certain coordination problems and social dilemmas that arise during pandemics. This role is both ethically and epistemically valuable. However, it also gives rise to an underappreciated dilemma, as the features that make models good at solving coordination problems are often at odds with the features that make for a good scientific model. We examine and develop this dilemma in the context of the COVID-19 pandemic, and suggest extensions to other domains.

How experimental neuroscientists can fix the hard problem of consciousness.

For the materialist, the hard problem is fundamentally an explanatory problem. Solving it requires explaining why the relationship between brain and experience is the way it is and not some other way. We use the tools of the interventionist theory of explanation to show how a systematic experimental project could help move beyond the hard problem. Key to this project is the development of second-order interventions and invariant generalizations. Such interventions played a crucial scientific role in untangling other scientific mysteries, and we suggest that the same will be true of consciousness. We further suggest that the capacity for safe and reliable self-intervention will play a key role in overcoming both the hard and meta-problems of consciousness. Finally, we evaluate current strategies for intervention, with an eye to how they might be improved.

Admission of Parkinsonian patients to a neurological ward in a community hospital.

Hospitalization is a significant factor contributing to health care costs related to management of Parkinson's disease (PD) patients. We reviewed reasons for admission of PD patients to our Neurological Department over a 6-year period. Thereafter, we applied an "open door" policy to try to diminish the number of hospitalizations. Case records including patient data, disease duration, staging, reasons for admission, and motor, mental and general medical status of PD patients admitted to the Neurology Department over a 6-year period were reviewed. Out of 1,920 admissions, 143 were PD patients. All PD admissions were through the emergency department (non-elective). Motor complications were the reason for admission in 37%, psychosis in 24%, general medical problems in 14%, and a combination of motor and psychiatric in 25%. Drug-induced psychosis was the most significant cause of repeated and prolonged admissions (29% of patients). As motor and psychiatric complications are the commonest causes for admission, improved community-based care to "fine tune" medication appeared to be a priority. After analyzing our results, we instituted an "open door" policy, where patients are free to come to the Parkinson's clinic without appointment. This policy should improve control of PD symptoms and diminish hospitalizations.

Pathways to conspiracy: The social and linguistic precursors of involvement in Reddit's conspiracy theory forum.

Many individuals who engage with conspiracy theories come to do so through a combination of individual and social factors. The interaction between these factors is challenging to study using traditional experimental designs. Reddit.com is a large connected set of online discussion forums, including one (r/conspiracy) devoted to wide-ranging discussion of conspiracy theories. The availability of large datasets of user comments from Reddit give a unique opportunity to observe human behavior in social spaces and at scale. Using a retrospective case control study design, we analyzed how Reddit users who would go on to engage with a conspiracy-related forum differed from other users in the language they use, differences in the social environments where they posted, and potential interactions between the two factors. Together, the analyses provide evidence for self-selection into communities with a shared set of interests which can feed into a conspiratorial world-view, and that these differences are detectable relative to controls even before users begin to post in r/conspiracy. We also suggest that survey-based and experimental studies may benefit from differentiating between passive private endorsement by individuals and active engagement with conspiracy theories in social spaces.

Decoding the Brain: Neural Representation and the Limits of Multivariate Pattern Analysis in Cognitive Neuroscience.

Since its introduction, multivariate pattern analysis (MVPA), or 'neural decoding', has transformed the field of cognitive neuroscience. Underlying its influence is a crucial inference, which we call the decoder's dictum: if information can be decoded from patterns of neural activity, then this provides strong evidence about what information those patterns represent. Although the dictum is a widely held and well-motivated principle in decoding research, it has received scant philosophical attention. We critically evaluate the dictum, arguing that it is false: decodability is a poor guide for revealing the content of neural representations. However, we also suggest how the dictum can be improved on, in order to better justify inferences about neural representation using MVPA. 1Introduction2A Brief Primer on Neural Decoding: Methods, Application, and Interpretation 2.1What is multivariate pattern analysis?2.2The informational benefits of multivariate pattern analysis3Why the Decoder's Dictum Is False 3.1We don't know what information is decoded3.2The theoretical basis for the dictum3.3Undermining the theoretical basis4Objections and Replies 4.1Does anyone really believe the dictum?4.2Good decoding is not enough4.3Predicting behaviour is not enough5Moving beyond the Dictum6Conclusion.

Phenytoin intoxication in a clozapine-related prolonged seizure.

Phenytoin is a first-line drug for the treatment of status epilepticus. We report a case of phenytoin intoxication after intravenous phenytoin loading in a patient with clozapine-related seizures. To our knowledge, this is the first description of phenytoin intoxication due to CYP2C9 inhibition by clozapine. This case report is important because it supports the use of a lower intravenous loading dose of phenytoin in patients with clozapine-related status epilepticus.

Carotid artery stenting in high risk patients with carotid artery stenosis not eligible for endarterectomy: clinical outcome after 5 years.

BACKGROUND: Carotid artery stenting is used as an alternative to surgical endarterectomy. OBJECTIVES: To determine the outcome of CAS in a retrospective cohort of patients. METHODS: Between July 1999 and March 2003, 56 consecutive patients with carotid artery stenosis who were considered ineligible for surgery were treated (45 males, 11 females, mean age 69). All underwent the procedure prior to the introduction of distal protective devices in Israel. RESULTS: Intraprocedural complications included transient neurological findings in 5 patients (8%), cerebrovascular accident in 2 (3%), hemodynamic changes in 11 (18%), and 4 procedural failures. Post-procedural complications included transient ischemic attack in 3 patients and cardiovascular accident in 6 (10%). At 30 days follow-up, three patients (5%) remained with signs of CVA. Two patients (3%) died during the post-procedural period and 16 (28%) during the 5 year follow-up, one due to recurrent CVA and the remainder to non-neurological causes. Five-year carotid Doppler follow-up was performed in 25 patients (45%), which revealed normal stent flow in 21 (84%), 50-60% restenosis in 3 (12%) and > 70% restenosis in one patient (4%). CONCLUSIONS: This study confirms that stent procedures are beneficial for symptomatic carotid stenosis in patients not eligible for surgery.

Topic Modeling Reveals Distinct Interests within an Online Conspiracy Forum.

Conspiracy theories play a troubling role in political discourse. Online forums provide a valuable window into everyday conspiracy theorizing, and can give a clue to the motivations and interests of those who post in such forums. Yet this online activity can be difficult to quantify and study. We describe a unique approach to studying online conspiracy theorists which used non-negative matrix factorization to create a topic model of authors' contributions to the main conspiracy forum on Reddit.com. This subreddit provides a large corpus of comments which spans many years and numerous authors. We show that within the forum, there are multiple sub-populations distinguishable by their loadings on different topics in the model. Further, we argue, these differences are interpretable as differences in background beliefs and motivations. The diversity of the distinct subgroups places constraints on theories of what generates conspiracy theorizing. We argue that traditional "monological" believers are only the tip of an iceberg of commenters. Neither simple irrationality nor common preoccupations can account for the observed diversity. Instead, we suggest, those who endorse conspiracies seem to be primarily brought together by epistemological concerns, and that these central concerns link an otherwise heterogenous group of individuals.

Opsoclonus myoclonus ataxia associated with West Nile virus infection: A dramatic presentation with benign prognosis?

Opsoclonus myoclonus and ataxia is a combination of severe neurological signs associated with several pathologic agents and conditions. Only few cases of opsoclonus have been related to West Nile virus infection. We report on a 61-year-old woman and on a 55-year-old man who had history of recent fever, who were hospitalized because of acute severe truncal ataxia, opsoclonus and tremor with minimal myoclonic jerks. A through work-up revealed the presence of both IgM and IgG antibodies against West Nile virus both in the serum and Cerebrospinal Fluid and excluded other causes known to be associated with this combination of neurological signs. The first case was treated with corticosteroids, followed by significant improvement, and the second recovered spontaneously. The acute combination of opsoclonus, severe truncal ataxia and tremor with a history of recent fever requires, during the relevant season and in the relevant geographic area, a search for a recent infection with West Nile virus. Though initially suffering from a devastating sickness, our patients eventually recovered.

Long-term follow-up (24 months) of quetiapine treatment in drug-induced Parkinson disease psychosis.

OBJECTIVES: To evaluate the long-term outcome of quetiapine (QTP) use for drug-induced psychosis in Parkinson disease as assessed by the primary caregiver using the Clinical Global Impression Scale. METHODS: Thirty-five patients (mean age+/-SD, 76.1+/-5.9 years; mean disease duration+/-SD, 10.3+/-5.3 years; 19 with dementia) were followed up over a 24-month period. RESULTS: At 6 months, 20 (57%) responded to QTP, of whom 11 (31%) maintained their improvement in the long term (for 24 months). Altogether, 15 patients (43%) responded to QTP in the long term (11 were still on treatment at 24 months, 3 stopped because of improvement and medication was no longer required, and 3 stopped because of financial reasons [one was responding positively by the time of stopping medication]). The medications of nonresponding patients (n=15) were switched to clozapine, with a positive response in 12 patients (80%). CONCLUSIONS: In long-term follow-up, 31% of parkinsonian patients with psychosis treated with QTP were still on QTP therapy at 24 months. For those failing to respond to QTP, clozapine was an effective alternative therapy.