Functional Organization of Social Perception and Cognition in the Superior Temporal Sulcus

The superior temporal sulcus (STS) is considered a hub for social perception and cognition, including the perception of faces and human motion, as well as understanding others' actions, mental states, and language. However, the functional organization of the STS remains debated: Is this broad region composed of multiple functionally distinct modules, each specialized for a different process, or are STS subregions multifunctional, contributing to multiple processes? Is the STS spatially organized, and if so, what are the dominant features of this organization? We address these questions by measuring STS responses to a range of social and linguistic stimuli in the same set of human participants, using fMRI. We find a number of STS subregions that respond selectively to certain types of social input, organized along a posterior-to-anterior axis. We also identify regions of overlapping response to multiple contrasts, including regions responsive to both language and theory of mind, faces and voices, and faces and biological motion. Thus, the human STS contains both relatively domain-specific areas, and regions that respond to multiple types of social information.David & Lucile Packard FoundationNational Science Foundation (U.S.). Graduate Research FellowshipNational Science Foundation (U.S.) (CCF-1231216

Know your audience: specializing grounded language models with listener subtraction

Effective communication requires adapting to the idiosyncrasies of each communicative context--such as the common ground shared with each partner. Humans demonstrate this ability to specialize to their audience in many contexts, such as the popular game Dixit. We take inspiration from Dixit to formulate a multi-agent image reference game where a (trained) speaker model is rewarded for describing a target image such that one (pretrained) listener model can correctly identify it among distractors, but another listener cannot. To adapt, the speaker must exploit differences in the knowledge it shares with the different listeners. We show that finetuning an attention-based adapter between a CLIP vision encoder and a large language model in this contrastive, multi-agent setting gives rise to context-dependent natural language specialization from rewards only, without direct supervision. Through controlled experiments, we show that training a speaker with two listeners that perceive differently, using our method, allows the speaker to adapt to the idiosyncracies of the listeners. Furthermore, we show zero-shot transfer of the specialization to real-world data. Our experiments demonstrate a method for specializing grounded language models without direct supervision and highlight the interesting research challenges posed by complex multi-agent communication.Comment: 28 pages, 9 figure

Greenhouse gas considerations in rail infrastructure in the UK

Transportation-related greenhouse gas (GHG) emissions account for an increasing proportion of total emissions in the UK and globally. The provision of rail transit is popularly proposed to reduce transport GHG emissions, but the provision of new infrastructure is itself GHG intensive. Understanding of the GHG emissions impact of rail projects is limited and very few longitudinal studies have been carried out. Existing assessments are often limited both in their scope and the factors considered. A holistic understanding of GHG impacts must include an assessment of capital GHG emissions, operational energy and maintenance as well as an assessment of ridership mode shift and mode share impacts and the relationship between transit infrastructure and land use. This paper explores rail infrastructure projects and their associated GHG emissions. Guidance is given on the aspects of rail planning, design and construction that must be considered to more fully understand the associated GHG impacts.The authors would like to thank The Commonwealth Scholarship Commission in the UK for the scholarship funding that facilitated this work

Know your audience: specializing grounded language models with listener subtraction

Effective communication requires adapting to the idiosyncrasies of each communicative context—such as the common ground shared with each partner. Humans demonstrate this ability to specialize to their audience in many contexts, such as the popular game Dixit. We take inspiration from Dixit to formulate a multiagent image reference game where a (trained) speaker model is rewarded for describing a target image such that one (pretrained) listener model can correctly identify it among distractors, but another listener cannot. To adapt, the speaker must exploit differences in the knowledge it shares with the different listeners. We show that finetuning an attention-based adapter between a CLIP vision encoder and a large language model in this contrastive, multi-agent setting gives rise to context-dependent natural language specialization from rewards only, without direct supervision. Through controlled experiments, we show that training a speaker with two listeners that perceive differently, using our method, allows the speaker to adapt to the idiosyncracies of the listeners. Furthermore, we show zero-shot transfer of the specialization to real-world data. Our experiments demonstrate a method for specializing grounded language models without direct supervision and highlight the interesting research challenges posed by complex multi-agent communicatio

The Transient Nature of Emergent In-Context Learning in Transformers

Transformer neural networks can exhibit a surprising capacity for in-context learning (ICL) despite not being explicitly trained for it. Prior work has provided a deeper understanding of how ICL emerges in transformers, e.g. through the lens of mechanistic interpretability, Bayesian inference, or by examining the distributional properties of training data. However, in each of these cases, ICL is treated largely as a persistent phenomenon; namely, once ICL emerges, it is assumed to persist asymptotically. Here, we show that the emergence of ICL during transformer training is, in fact, often transient. We train transformers on synthetic data designed so that both ICL and in-weights learning (IWL) strategies can lead to correct predictions. We find that ICL first emerges, then disappears and gives way to IWL, all while the training loss decreases, indicating an asymptotic preference for IWL. The transient nature of ICL is observed in transformers across a range of model sizes and datasets, raising the question of how much to "overtrain" transformers when seeking compact, cheaper-to-run models. We find that L2 regularization may offer a path to more persistent ICL that removes the need for early stopping based on ICL-style validation tasks. Finally, we present initial evidence that ICL transience may be caused by competition between ICL and IWL circuits.Comment: 19 pages, 16 figure

Structural Connectivity of the Developing Human Amygdala

<div><p>A large corpus of research suggests that there are changes in the manner and degree to which the amygdala supports cognitive and emotional function across development. One possible basis for these developmental differences could be the maturation of amygdalar connections with the rest of the brain. Recent functional connectivity studies support this conclusion, but the structural connectivity of the developing amygdala and its different nuclei remains largely unstudied. We examined age related changes in the DWI connectivity fingerprints of the amygdala to the rest of the brain in 166 individuals of ages 5-30. We also developed a model to predict age based on individual-subject amygdala connectivity, and identified the connections that were most predictive of age. Finally, we segmented the amygdala into its four main nucleus groups, and examined the developmental changes in connectivity for each nucleus. We observed that with age, amygdalar connectivity becomes increasingly sparse and localized. Age related changes were largely localized to the subregions of the amygdala that are implicated in social inference and contextual memory (the basal and lateral nuclei). The central nucleus’ connectivity also showed differences with age but these differences affected fewer target regions than the basal and lateral nuclei. The medial nucleus did not exhibit any age related changes. These findings demonstrate increasing specificity in the connectivity patterns of amygdalar nuclei across age.</p></div

A Phenotypic Small-Molecule Screen Identifies an Orphan Ligand-Receptor Pair that Regulates Neural Stem Cell Differentiation

SummaryHigh-throughput identification of small molecules that selectively modulate molecular, cellular, or systems-level properties of the mammalian brain is a significant challenge. Here we report the chemical genetic identification of the orphan ligand phosphoserine (P-Ser) as an enhancer of neurogenesis. P-Ser inhibits neural stem cell/progenitor proliferation and self-renewal, enhances neurogenic fate commitment, and improves neuronal survival. We further demonstrate that the effects of P-Ser are mediated by the group III metabotropic glutamate receptor 4 (mGluR4). siRNA-mediated knockdown of mGluR4 abolished the effects of P-Ser and increased neurosphere proliferation, at least in part through upregulation of mTOR pathway activity. We also found that P-Ser increases neurogenesis in human embryonic stem cell-derived neural progenitors. This work highlights the tremendous potential of developing effective small-molecule drugs for use in regenerative medicine or transplantation therapy

Operating costs: pbs vs conventional heavy vehicles in south africa

Road transport is a highly competitive industry and is renowned for low profit margins. Road transport however accounts for almost 6% of the Gross Domestic Product (GDP) and is the backbone of the economy. The Performance-Based Standards (PBS) or Smart Truck Pilot project has existed in South Africa since 2007 and monitoring data has shown substantial savings including a 34% reduction in crash rates, 18.3 million litres of fuel and 534 840 trips being saved since the start of the project. The Australian PBS programme is projected to save more than AUS$17 billion by 2034. The potential financial impact of PBS in South Africa has not yet been fully quantified using actual operational costs from operators participating in the trial. In this study a questionnaire was used to collect operational costs from PBS operators and has compared the costs of PBS and baseline vehicles. The most significant finding is that on a per tonne-km basis, the weighted average overall cost savings was 18.8% for the all PBS versus baseline vehicles. Not all PBS operators showed a reduction in operating costs but this could be attributed to having only one PBS vehicle and operating in a specialized industry with short lead distances. PBS however, appears as a viable solution to reduce transport costs, reduce crashes and emissions and also save the road infrastructure and should be considered for regulated implementation in South Africa.Papers presented virtually at the 39th International Southern African Transport Conference on 05 -07 July 202

Are all beliefs equal? Implicit belief attributions recruiting core brain regions of theory of mind

Humans possess efficient mechanisms to behave adaptively in social contexts. They ascribe goals and beliefs to others and use these for behavioural predictions. Researchers argued for two separate mental attribution systems: an implicit and automatic one involved in online interactions, and an explicit one mainly used in offline deliberations. However, the underlying mechanisms of these systems and the types of beliefs represented in the implicit system are still unclear. Using neuroimaging methods, we show that the right temporo-parietal junction and the medial prefrontal cortex, brain regions consistently found to be involved in explicit mental state reasoning, are also recruited by spontaneous belief tracking. While the medial prefrontal cortex was more active when both the participant and another agent believed an object to be at a specific location, the right temporo-parietal junction was selectively activated during tracking the false beliefs of another agent about the presence, but not the absence of objects. While humans can explicitly attribute to a conspecific any possible belief they themselves can entertain, implicit belief tracking seems to be restricted to beliefs with specific contents, a content selectivity that may reflect a crucial functional characteristic and signature property of implicit belief attribution