Daniel Ari Friedman

Dr. Daniel Ari Friedman

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Research Focus & Metrics

Academic Career Length

33Years (1994-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 October 2014 in Molecular Biology and Evolution
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WJWilliam Cameron Jasper
William Cameron Jasper
TLTimothy A. Linksvayer
Timothy A. Linksvayer
JAJoel Atallah
Joel Atallah
DFDaniel Ari Friedman
Daniel Ari Friedman
JCJoanna C. Chiu
Joanna C. Chiu
Brian R. JohnsonBrian R. Johnson
Brian R. Johnson
Whether coding or regulatory sequence change is more important to the evolution of phenotypic novelty is one of biology’s major unresolved questions. The field of evo–devo has shown that in early development changes to regulatory regions are the dominant mode of genetic change, but whether this extends to the evolution of novel phenotypes in the adult organism is unclear. Here, we conduct ten RNA-Seq experiments across both novel and conserved tissues in the honey bee to determine to what extent postdevelopmental novelty is based on changes to the coding regions of genes. We make several discoveries. First, we show that with respect to novel physiological functions in the adult animal, positively selected tissue-specific genes of high expression underlie novelty by conferring specialized cellular functions. Such genes are often, but not always taxonomically restricted genes (TRGs). We further show that positively selected genes, whether TRGs or conserved genes, are the least connected genes within gene expression networks. Overall, this work suggests that the evo–devo paradigm is limited, and that the evolution of novelty, postdevelopment, follows additional rules. Specifically, evo–devo stresses that high network connectedness (repeated use of the same gene in many contexts) constrains coding sequence change as it would lead to negative pleiotropic effects. Here, we show that in the adult animal, the converse is true: Genes with low network connectedness (TRGs and tissue-specific conserved genes) underlie novel phenotypes by rapidly changing coding sequence to perform new-specialized functions.

1 October 2018 in iScience
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Journal Article
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DFDaniel Ari Friedman
Daniel Ari Friedman
APAnna Pilko
Anna Pilko
DSDorota Skowronska-Krawczyk
Dorota Skowronska-Krawczyk
KKKarolina Krasinska
Karolina Krasinska
JPJacqueline W. Parker
Jacqueline W. Parker
DGDeborah M. Gordon
Deborah M. Gordon
Colonies of the red harvester ant (Pogonomyrmex barbatus) differ in how they regulate collective foraging activity in response to changes in humidity. We used transcriptomic, physiological, and pharmacological experiments to investigate the molecular basis of this ecologically important variation in collective behavior among colonies. RNA sequencing of forager brain tissue showed an association between colony foraging activity and differential expression of transcripts related to biogenic amine and neurohormonal metabolism and signaling. In field experiments, pharmacological increases in forager brain dopamine titer caused significant increases in foraging activity. Colonies that were naturally most sensitive to humidity were significantly more responsive to the stimulatory effect of exogenous dopamine. In addition, forager brain tissue significantly varied among colonies in biogenic amine content. Neurophysiological variation among colonies associated with individual forager sensitivity to humidity may reflect the heritable molecular variation on which natural selection acts to shape the collective regulation of foraging.

1 June 2020 in Hormones and Behavior
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Journal Article
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DFDaniel Ari Friedman
Daniel Ari Friedman
BJB.R. Johnson
B.R. Johnson
TLT.A. Linksvayer
T.A. Linksvayer

5 December 2023 in Neuroscience & Biobehavioral Reviews
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KFKarl Friston Friston
Karl Friston Friston
Thomas ParrThomas Parr
Thomas Parr
CHConor Heins
Conor Heins
ACAxel Constant
Axel Constant
DFDaniel Ari Friedman
Daniel Ari Friedman
CFChristopher D. Frith
Christopher D. Frith
This paper concerns the distributed intelligence or federated inference that emerges under belief-sharing among agents who share a common world-and world model. Imagine, for example, several animals keeping a lookout for predators. Their collective surveillance rests upon being able to communicate their beliefs-about what they see-among themselves. But, how is this possible? Here, we show how all the necessary components arise from minimising free energy. We use numerical studies to simulate the generation, acquisition and emergence of language in synthetic agents. Specifically, we consider inference, learning and selection as minimising the variational free energy of posterior (i.e., Bayesian) beliefs about the states, parameters and structure of generative models, respectively. The common theme-that attends these optimisation processes-is the selection of actions that minimise expected free energy, leading to active inference, learning and model selection (a.k.a., structure learning). We first illustrate the role of communication in resolving uncertainty about the latent states of a partially observed world, on which agents have complementary perspectives. We then consider the acquisition of the requisite language-entailed by a likelihood mapping from an agent's beliefs to their overt expression (e.g., speech)-showing that language can be transmitted across generations by active learning. Finally, we show that language is an emergent property of free energy minimisation, when agents operate within the same econiche. We conclude with a discussion of various perspectives on these phenomena; ranging from cultural niche construction, through federated learning, to the emergence of complexity in ensembles of self-organising systems.

21 June 2023 in Entropy
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KFKarl Friston Friston
Karl Friston Friston
DFDaniel Ari Friedman
Daniel Ari Friedman
ACAxel Constant
Axel Constant
VKV. Bleu Knight
V. Bleu Knight
CFChris Fields
Chris Fields
JCJohn O. Campbell
John O. Campbell
This paper introduces a variational formulation of natural selection, paying special attention to the nature of ‘things’ and the way that different ‘kinds’ of ‘things’ are individuated from—and influence—each other. We use the Bayesian mechanics of particular partitions to understand how slow phylogenetic processes constrain—and are constrained by—fast, phenotypic processes. The main result is a formulation of adaptive fitness as a path integral of phenotypic fitness. Paths of least action, at the phenotypic and phylogenetic scales, can then be read as inference and learning processes, respectively. In this view, a phenotype actively infers the state of its econiche under a generative model, whose parameters are learned via natural (Bayesian model) selection. The ensuing variational synthesis features some unexpected aspects. Perhaps the most notable is that it is not possible to describe or model a population of conspecifics per se. Rather, it is necessary to consider populations of distinct natural kinds that influence each other. This paper is limited to a description of the mathematical apparatus and accompanying ideas. Subsequent work will use these methods for simulations and numerical analyses—and identify points of contact with related mathematical formulations of evolution.

31 August 2016 in Proceedings Of The Royal Society B-Biological Sciences
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Journal Article
Open access
KIKrista K. Ingram
Krista K. Ingram
DGDeborah M. Gordon
Deborah M. Gordon
DFDaniel Ari Friedman
Daniel Ari Friedman
MGMichael Greene
Michael Greene
JKJohn Kahler
John Kahler
SPSwetha Peteru
Swetha Peteru
Task allocation among social insect workers is an ideal framework for studying the molecular mechanisms underlying behavioural plasticity because workers of similar genotype adopt different behavioural phenotypes. Elegant laboratory studies have pioneered this effort, but field studies involving the genetic regulation of task allocation are rare. Here, we investigate the expression of the foraging gene in harvester ant workers from five age- and task-related groups in a natural population, and we experimentally test how exposure to light affects foraging expression in brood workers and foragers. Results from our field study show that the regulation of the foraging gene in harvester ants occurs at two time scales: levels of foraging mRNA are associated with ontogenetic changes over weeks in worker age, location and task, and there are significant daily oscillations in foraging expression in foragers. The temporal dissection of foraging expression reveals that gene expression changes in foragers occur across a scale of hours and the level of expression is predicted by activity rhythms: foragers have high levels of foraging mRNA during daylight hours when they are most active outside the nests. In the experimental study, we find complex interactions in foraging expression between task behaviour and light exposure. Oscillations occur in foragers following experimental exposure to 13 L : 11 D (LD) conditions, but not in brood workers under similar conditions. No significant differences were seen in foraging expression over time in either task in 24 h dark (DD) conditions. Interestingly, the expression of foraging in both undisturbed field and experimentally treated foragers is also significantly correlated with the expression of the circadian clock gene, cycle . Our results provide evidence that the regulation of this gene is context-dependent and associated with both ontogenetic and daily behavioural plasticity in field colonies of harvester ants. Our results underscore the importance of assaying temporal patterns in behavioural gene expression and suggest that gene regulation is an integral mechanism associated with behavioural plasticity in harvester ants.