Dr. Tom Franken

A postdoctoral position is available in Dr. Tom Franken’s laboratory in the Department of Neuroscience at the Washington University School of Medicine in St. Louis. The project will study the neural circuits that parse visual scenes into organized collections of objects. We use a variety of techniques including high-density electrophysiology, behavior, optogenetics, and viral targeting in non-human primates. For more information on the lab, please visit sites.wustl.edu/frankenlab/. The PI is committed to mentoring and to nurturing a creative, thoughtful and collaborative lab culture. The laboratory is in an academic setting in the Department of Neuroscience at the Washington University School of Medicine in St. Louis, a large and collaborative scientific community. This provides an ideal environment to train, conduct research, and launch a career in science. Postdoctoral appointees at Washington University receive a competitive salary and a generous benefits package (hr.wustl.edu/benefits/). WashU Neuroscience is consistently ranked as one of the top 10 places worldwide for neuroscience research and offers an outstanding interdisciplinary training environment for early career researchers. In addition to high-quality research facilities, career and professional development training for postdoctoral researchers is provided through the Career Center, Teaching Center, Office of Postdoctoral Affairs, and campus groups. St. Louis is a city rich in culture, green spaces, free museums, world-class restaurants, and thriving music and arts scenes. On top of it all, St. Louis is affordable and commuting to campus is stress-free, whether you go by foot, bike, public transit, or car. The area combines the attractions of a major city with affordable lifestyle opportunities (postdoc.wustl.edu/prospective-postdocs/why-st-louis/). Washington University is dedicated to building a diverse community of individuals who are committed to contributing to an inclusive environment – fostering respect for all and welcoming individuals from diverse backgrounds, experiences and perspectives. Individuals with a commitment to these values are encouraged to apply. Additional information on being a postdoc at Washington University in St. Louis can be found at neuroscience.wustl.edu/education/postdoctoral-research/ and postdoc.wustl.edu/prospective-postdocs. Required Qualifications Ph.D. (or equivalent doctoral) degree in neuroscience (broadly defined). Strong background in either electrophysiology, behavioral techniques or scientific programming/machine learning. Preferred Qualifications Experience with training of larger animals. Experience with electrophysiology. Experience with studies of the visual system. Ability to think creatively to solve problems. Well organized and attention to detail. Excellent oral and written communication skills. Team player with a high level of initiative and motivation. Working Conditions This position works in a laboratory environment with potential exposure to biological and chemical hazards. The individual must be physically able to wear protective equipment and to provide standard care to research animals. Salary Range Base pay is commensurate with experience. Applicant Special Instructions Applicants should submit the following materials to Dr. Tom Franken at ftom@wustl.edu: 1) A cover letter explaining how their interest in the position matches their background and career goals. 2) CV or Biosketch. 3) Contact information for at least three professional references. Accommodation If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request. Pre-Employment Screening All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening. Benefits Statement Washington University in St. Louis is committed to providing a comprehensive and competitive benefits package to our employees. Benefits eligibility is subject to employment status, full-time equivalent (FTE) workload, and weekly standard hours. Please visit our website at https://hr.wustl.edu/benefits/ to view a summary of benefits. EEO/AA Statement Washington University in St. Louis is committed to the principles and practices of equal employment opportunity and especially encourages applications by those from underrepresented groups. It is the University’s policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity, color, national origin, age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information. Diversity Statement Washington University is dedicated to building a diverse community of individuals who are committed to contributing to an inclusive environment – fostering respect for all and welcoming individuals from diverse backgrounds, experiences and perspectives. Individuals with a commitment to these values are encouraged to apply.

IMPRS for Brain & Behavior

Join our unique transatlantic PhD program in neuroscience! The International Max Planck Research School (IMPRS) for Brain and Behavior is a unique transatlantic collaboration between two Max Planck Neuroscience institutes – the Max Planck-associated research center caesar and the Max Planck Florida Institute for Neuroscience – and the partner universities, University of Bonn and Florida Atlantic University. It offers a completely funded international PhD program in neuroscience in either Bonn, Germany, or Jupiter, Florida. We offer an exciting opportunity to outstanding Bachelor's and/or Master's degree holders (or equivalent) from any field (life sciences, mathematics, physics, computer science, engineering, etc.) to be immersed in a stimulating environment that provides novel technologies to elucidate the function of brain circuits from molecules to animal behavior. The comprehensive and diverse expertise of the faculty in the exploration of brain-circuit function using advanced imaging and optogenetic techniques combined with comprehensive training in fundamental neurobiology will provide students with an exceptional level of knowledge to pursue a successful independent research career. Apply to Bonn, Germany by November 15, 2020 or to Florida, USA by December 1, 2020!

Go with the visual flow: circuit mechanisms for gaze control during locomotion

Continuity and segmentation - two ends of a spectrum or independent processes?

Representational drift in human visual cortex

“Brain theory, what is it or what should it be?”

n the neurosciences the need for some 'overarching' theory is sometimes expressed, but it is not always obvious what is meant by this. One can perhaps agree that in modern science observation and experimentation is normally complemented by 'theory', i.e. the development of theoretical concepts that help guiding and evaluating experiments and measurements. A deeper discussion of 'brain theory' will require the clarification of some further distictions, in particular: theory vs. model and brain research (and its theory) vs. neuroscience. Other questions are: Does a theory require mathematics? Or even differential equations? Today it is often taken for granted that the whole universe including everything in it, for example humans, animals, and plants, can be adequately treated by physics and therefore theoretical physics is the overarching theory. Even if this is the case, it has turned out that in some particular parts of physics (the historical example is thermodynamics) it may be useful to simplify the theory by introducing additional theoretical concepts that can in principle be 'reduced' to more complex descriptions on the 'microscopic' level of basic physical particals and forces. In this sense, brain theory may be regarded as part of theoretical neuroscience, which is inside biophysics and therefore inside physics, or theoretical physics. Still, in neuroscience and brain research, additional concepts are typically used to describe results and help guiding experimentation that are 'outside' physics, beginning with neurons and synapses, names of brain parts and areas, up to concepts like 'learning', 'motivation', 'attention'. Certainly, we do not yet have one theory that includes all these concepts. So 'brain theory' is still in a 'pre-newtonian' state. However, it may still be useful to understand in general the relations between a larger theory and its 'parts', or between microscopic and macroscopic theories, or between theories at different 'levels' of description. This is what I plan to do.

Seeing a changing world through the eyes of coral fishes

From Spiking Predictive Coding to Learning Abstract Object Representation

In a first part of the talk, I will present Predictive Coding Light (PCL), a novel unsupervised learning architecture for spiking neural networks. In contrast to conventional predictive coding approaches, which only transmit prediction errors to higher processing stages, PCL learns inhibitory lateral and top-down connectivity to suppress the most predictable spikes and passes a compressed representation of the input to higher processing stages. We show that PCL reproduces a range of biological findings and exhibits a favorable tradeoff between energy consumption and downstream classification performance on challenging benchmarks. A second part of the talk will feature our lab’s efforts to explain how infants and toddlers might learn abstract object representations without supervision. I will present deep learning models that exploit the temporal and multimodal structure of their sensory inputs to learn representations of individual objects, object categories, or abstract super-categories such as „kitchen object“ in a fully unsupervised fashion. These models offer a parsimonious account of how abstract semantic knowledge may be rooted in children's embodied first-person experiences.

The Unconscious Eye: What Involuntary Eye Movements Reveal About Brain Processing

Neuro-Optometric Rehabilitation - an introduction to the diagnosis and treatment of vision disorders secondary to neurological impairment

Cognitive maps, navigational strategies, and the human brain

The hippocampus, visual perception and visual memory

Reading Scenes

Plasticity of the adult visual system

Retinal input integration in excitatory and inhibitory neurons in the mouse superior colliculus in vivo

The speed of prioritizing information for consciousness: A robust and mysterious human trait

Altered grid-like coding in early blind people and the role of vision in conceptual navigation

Contentopic mapping and object dimensionality - a novel understanding on the organization of object knowledge

Our ability to recognize an object amongst many others is one of the most important features of the human mind. However, object recognition requires tremendous computational effort, as we need to solve a complex and recursive environment with ease and proficiency. This challenging feat is dependent on the implementation of an effective organization of knowledge in the brain. Here I put forth a novel understanding of how object knowledge is organized in the brain, by proposing that the organization of object knowledge follows key object-related dimensions, analogously to how sensory information is organized in the brain. Moreover, I will also put forth that this knowledge is topographically laid out in the cortical surface according to these object-related dimensions that code for different types of representational content – I call this contentopic mapping. I will show a combination of fMRI and behavioral data to support these hypotheses and present a principled way to explore the multidimensionality of object processing.

Guiding Visual Attention in Dynamic Scenes

Rethinking Attention: Dynamic Prioritization

Decades of research on understanding the mechanisms of attentional selection have focused on identifying the units (representations) on which attention operates in order to guide prioritized sensory processing. These attentional units fit neatly to accommodate our understanding of how attention is allocated in a top-down, bottom-up, or historical fashion. In this talk, I will focus on attentional phenomena that are not easily accommodated within current theories of attentional selection – the “attentional platypuses,” as they allude to an observation that within biological taxonomies the platypus does not fit into either mammal or bird categories. Similarly, attentional phenomena that do not fit neatly within current attentional models suggest that current models need to be revised. I list a few instances of the ‘attentional platypuses” and then offer a new approach, the Dynamically Weighted Prioritization, stipulating that multiple factors impinge onto the attentional priority map, each with a corresponding weight. The interaction between factors and their corresponding weights determines the current state of the priority map which subsequently constrains/guides attention allocation. I propose that this new approach should be considered as a supplement to existing models of attention, especially those that emphasize categorical organizations.

Traumatic brain injury and the visual sequela

Mind Perception and Behaviour: A Study of Quantitative and Qualitative Effects

Perceptual illusions we understand well, and illusions which aren’t really illusions

Imagining and seeing: two faces of prosopagnosia

Reactivation in the human brain connects the past with the present

Attending to moments in time

Visuomotor learning of location, action, and prediction

Retinal Photoreceptor Diversity Across Mammals

Generative models for video games (rescheduled)

Developing agents capable of modeling complex environments and human behaviors within them is a key goal of artificial intelligence research. Progress towards this goal has exciting potential for applications in video games, from new tools that empower game developers to realize new creative visions, to enabling new kinds of immersive player experiences. This talk focuses on recent advances of my team at Microsoft Research towards scalable machine learning architectures that effectively capture human gameplay data. In the first part of my talk, I will focus on diffusion models as generative models of human behavior. Previously shown to have impressive image generation capabilities, I present insights that unlock applications to imitation learning for sequential decision making. In the second part of my talk, I discuss a recent project taking ideas from language modeling to build a generative sequence model of an Xbox game.

Characterizing the causal role of large-scale network interactions in supporting complex cognition

Neuroimaging has greatly extended our capacity to study the workings of the human brain. Despite the wealth of knowledge this tool has generated however, there are still critical gaps in our understanding. While tremendous progress has been made in mapping areas of the brain that are specialized for particular stimuli, or cognitive processes, we still know very little about how large-scale interactions between different cortical networks facilitate the integration of information and the execution of complex tasks. Yet even the simplest behavioral tasks are complex, requiring integration over multiple cognitive domains. Our knowledge falls short not only in understanding how this integration takes place, but also in what drives the profound variation in behavior that can be observed on almost every task, even within the typically developing (TD) population. The search for the neural underpinnings of individual differences is important not only philosophically, but also in the service of precision medicine. We approach these questions using a three-pronged approach. First, we create a battery of behavioral tasks from which we can calculate objective measures for different aspects of the behaviors of interest, with sufficient variance across the TD population. Second, using these individual differences in behavior, we identify the neural variance which explains the behavioral variance at the network level. Finally, using covert neurofeedback, we perturb the networks hypothesized to correspond to each of these components, thus directly testing their casual contribution. I will discuss our overall approach, as well as a few of the new directions we are currently pursuing.

Vision Unveiled: Understanding Face Perception in Children Treated for Congenital Blindness

Generative models for video games

Developing agents capable of modeling complex environments and human behaviors within them is a key goal of artificial intelligence research. Progress towards this goal has exciting potential for applications in video games, from new tools that empower game developers to realize new creative visions, to enabling new kinds of immersive player experiences. This talk focuses on recent advances of my team at Microsoft Research towards scalable machine learning architectures that effectively capture human gameplay data. In the first part of my talk, I will focus on diffusion models as generative models of human behavior. Previously shown to have impressive image generation capabilities, I present insights that unlock applications to imitation learning for sequential decision making. In the second part of my talk, I discuss a recent project taking ideas from language modeling to build a generative sequence model of an Xbox game.

Inhibition in the retina

Perception in Autism: Testing Recent Bayesian Inference Accounts

Computer vision and image processing applications on astrocyte-glioma interactions in 3D cell culture

FENS Forum 2024

Oculomotor vergence system through fMRI in persons with binocularly normal vision and persistent post-concussive symptoms with convergence insufficiency

FENS Forum 2024

Scalable microelectrode arrays: moving beyond time division multiplexing

Bernstein Conference 2024

Timing and transmission: the role of axonal action potential propagation speed in the synchronization of foveal vision

Bernstein Conference 2024

Evaluating Noise Tolerance in Drosophila Vision

COSYNE 2022

An insect vision-based flight control model with a plastic efference copy

COSYNE 2022

An insect vision-based flight control model with a plastic efference copy

COSYNE 2022

Organization of local directionally selective neurons informs global motion vision encoding

COSYNE 2022

Organization of local directionally selective neurons informs global motion vision encoding

COSYNE 2022

A two-way luminance gain control in the fly brain ensures luminance invariance in dynamic vision

COSYNE 2022

A two-way luminance gain control in the fly brain ensures luminance invariance in dynamic vision

COSYNE 2022

Inferring the order of stable and context dependent perceptual biases in human vision

COSYNE 2023

Leveraging computational and animal models of vision to probe atypical emotion recognition in autism

COSYNE 2023

Biologically Realistic Computational Primitives of Neocortex Implemented on Neuromorphic Hardware Improve Vision Transformer Performance

COSYNE 2025

Enhancing Vision Robustness to Adversarial Attacks through Foveal-Peripheral and Saccadic Mechanisms

COSYNE 2025

Recurrent connectivity supports motion detection in connectome-constrained models of fly vision

COSYNE 2025

TweetyBERT, a self-supervised vision transformer to automate birdsong annotation

COSYNE 2025

Analyzing animal behavior with domain-adapted vision-language models

FENS Forum 2024

Compromised binocular vision and reduced binocularity in the visual cortex of postsynaptic density 95 (PSD-95) knock-out mice

FENS Forum 2024

Connectional subdivisions reflect neuronal features of the various sectors of the macaque ventrolateral prefrontal cortex

FENS Forum 2024

Exploring laryngeal effects of dorsolateral periaqueductal grey stimulation in anesthetized rats: Implications for c-Fos and FOXP2 expression in the nucleus ambiguus subdivisions

FENS Forum 2024

Exploring pupil dynamics in freely moving rats during active integration of vision and posture

FENS Forum 2024

Impact of barrel cortex lesions and sensory deprivation on perceptual decision-making: Insights from computer vision and time series clustering of freely moving behavioral strategies

FENS Forum 2024

The impact of the retinotopic subdivisions of area V1 on shaping the macaque connectome

FENS Forum 2024

Optogenetic stimulation in the visual thalamus for future brain vision prostheses

FENS Forum 2024

Projections from the ventral nucleus of the trapezoid body to all subdivisions of the rat cochlear nucleus

FENS Forum 2024

REST as a target for vision restoration

FENS Forum 2024

A retinotopic-and-orientation-based stimulation strategy induces neural activity patterns mimicking natural vision

FENS Forum 2024

Searching for input-output connectivity streams in the various subdivisions of mouse orbitofrontal cortex

FENS Forum 2024

Study of brain plasticity following loss of monocular vision in mice

FENS Forum 2024

Vision revival: NGF’s role in restoring retinal balance and activating BDNF’s lifesaving routes in diabetic retinopathy

FENS Forum 2024

When auditory rules over vision: The impact of temporal synchrony for auditory-visual sensory attenuation effects

FENS Forum 2024

AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time

Neuromatch 5