@article {5085, title = {Brain-like functional specialization emerges spontaneously in deep neural networks}, journal = {Science Advances}, volume = {8}, year = {2022}, month = {03/2023}, abstract = {

The human brain contains multiple regions with distinct, often highly specialized functions, from recognizing faces to understanding language to thinking about what others are thinking. However, it remains unclear why the cortex exhibits this high degree of functional specialization in the first place. Here, we consider the case of face perception using artificial neural networks to test the hypothesis that functional segregation of face recognition in the brain reflects a computational optimization for the broader problem of visual recognition of faces and other visual categories. We find that networks trained on object recognition perform poorly on face recognition and vice versa and that networks optimized for both tasks spontaneously segregate themselves into separate systems for faces and objects. We then show functional segregation to varying degrees for other visual categories, revealing a widespread tendency for optimization (without built-in task-specific inductive biases) to lead to functional specialization in machines and, we conjecture, also brains.

}, doi = {10.1126/sciadv.abl8913}, url = {https://www.science.org/doi/10.1126/sciadv.abl8913}, author = {Dobs, Katharina and Julio Martinez-Trujillo and Kell, Alexander J. E. and Nancy Kanwisher} } @conference {4525, title = {Using task-optimized neural networks to understand why brains have specialized processing for faces }, booktitle = {Computational and Systems Neurosciences}, year = {2020}, month = {02/2020}, address = {Denver, CO, USA}, author = {Dobs, Katharina and Alexander J. E. Kell and Julio Martinez-Trujillo and Michael Cohen and Nancy Kanwisher} } @conference {4524, title = {Why Are Face and Object Processing Segregated in the Human Brain? Testing Computational Hypotheses with Deep Convolutional Neural Networks }, booktitle = {Conference on Cognitive Computational Neuroscience}, year = {2020}, month = {09/2020}, address = {Berlin, Germany}, author = {Dobs, Katharina and Alexander J. E. Kell and Julio Martinez-Trujillo and Michael Cohen and Nancy Kanwisher} } @article {4066, title = {Neuronal population coding of perceived and memorized visual features in the lateral prefrontal cortex}, journal = {Nature Communications}, volume = {8}, year = {2017}, month = {June 2017}, type = {Article No. 15471}, abstract = {

The primate lateral prefrontal cortex (LPFC) encodes visual stimulus features while they are perceived and while they are maintained in working memory. However, it remains unclear whether perceived and memorized features are encoded by the same or different neurons and population activity patterns. Here we record LPFC neuronal activity while monkeys perceive the motion direction of a stimulus that remains visually available, or memorize the direction if the stimulus disappears. We find neurons with a wide variety of combinations of coding strength for perceived and memorized directions: some neurons encode both to similar degrees while others preferentially or exclusively encode either one. Reading out the combined activity of all neurons, a machine-learning algorithm reliably decode the motion direction and determine whether it is perceived or memorized. Our results indicate that a functionally diverse population of LPFC neurons provides a substrate for discriminating between perceptual and mnemonic representations of visual features.

}, url = {https://doi.org/10.1038/ncomms15471}, author = {Diego Mendoza-Halliday and Julio Martinez-Trujillo} } @inbook {4069, title = {Working Memory Representations of Visual Motion along the Primate Dorsal Visual Pathway}, booktitle = {Mechanisms of Sensory Working Memory: Attention and Performance XXV.}, year = {2015}, publisher = {Elsevier Inc. }, organization = {Elsevier Inc. }, abstract = {

Mechanisms of Sensory Working Memory: Attention and Performance XXV provides an update on the research surrounding the memory processes that are crucial for many facets of cognitive processing and experience, with new coverage of emerging areas of study, including a new understanding of working memory for features of stimuli devoid of verbal, phonological, or long-term memory content, such as memory for simple visual features (e.g., texture or color), simple auditory features (e.g., pitch), or simple tactile features (e.g., vibration frequency), now called sensory memory to distinguish from verbal memory.

This contemporary focus on sensory memory is just beginning, and this collection of original contributions provides a foundational reference for the study mechanisms of sensory memory.

}, issn = {978-0-12-801371-7}, url = {https://www.sciencedirect.com/book/9780128013717/mechanisms-of-sensory-working-memory}, author = {Diego Mendoza-Halliday and Torres, S. and Julio Martinez-Trujillo} } @article {1910, title = {Sharp emergence of feature-selective sustained activity along the dorsal visual pathway}, journal = {Nature Neuroscience}, volume = {7}, year = {2014}, month = {09/2014}, chapter = {1255}, abstract = {

Sustained activity encoding visual working memory representations has been observed in several cortical areas of primates. Where along the visual pathways this activity emerges remains unknown. Here we show in macaques that sustained spiking activity encoding memorized visual motion directions is absent in direction-selective neurons in early visual area middle temporal (MT). However, it is robustly present immediately downstream, in multimodal association area medial superior temporal (MST), as well as and in the lateral prefrontal cortex (LPFC). This sharp emergence of sustained activity along the dorsal visual pathway suggests a functional boundary between early visual areas, which encode sensory inputs, and downstream association areas, which additionally encode mnemonic representations. Moreover, local field potential oscillations in MT encoded the memorized directions and, in the low frequencies, were phase-coherent with LPFC spikes. This suggests that LPFC sustained activity modulates synaptic activity in MT, a putative top-down mechanism by which memory signals influence stimulus processing in early visual cortex.

}, doi = {doi:10.1038/nn.3785}, url = {http://www.nature.com/neuro/journal/v17/n9/abs/nn.3785.html}, author = {Diego Mendoza-Halliday and Santiago Torres and Julio Martinez-Trujillo} } @article {2637, title = {Combined effects of feature-based working memory and feature-based attention on the perception of visual motion direction}, journal = {Journal of Vision}, volume = {11}, year = {2011}, chapter = {11}, author = {Diego Mendoza-Halliday and Megan Schneiderman and Christian Kaul and Julio Martinez-Trujillo} } @article {4065, title = {Combined effects of feature-based working memory and feature-based attention on the perception of visual motion direction}, journal = {Journal of Vision}, volume = {11}, year = {2011}, abstract = {

We investigated whether human subjects{\textquoteright}ability to identify the direction of a brief pulse of coherent motion in a random-dotpattern (RDP) was influenced by: (a) maintaining in working memory the direction of motion of an RDP previously presentedfar from the pulse (feature-based working memory or FBWM,Experiment 1), (b) attending to the direction of an RDPco-occurring with but far from the pulse (feature-based attention or FBA,Experiment 2), and (c) both FBWM and FBA actingsimultaneously (Experiment 3). In thefirst two experiments, pulse direction identification performance was higher when theremembered direction (FBWM) or the direction of the concurrently attended RDP (FBA) matched the pulse direction thanwhen it was opposite. InExperiment 3, performance was highest when both the remembered and the attended directionsmatched the pulse direction (combined effects of FBWM and FBA), it was intermediate when only one of them matched thepulse direction, and it was lowest when neither matched the pulse direction. Our results demonstrate that both feature-based working memory and feature-based attention can individually modulate the perception of motion direction and thatwhen acting together they produce an even larger modulation.

}, keywords = {feature-based attention, motion direction, motion perception, Psychophysics, working memory}, doi = {doi:10.1167/11.1.11}, url = {http://www.journalofvision.org/content/11/1/11}, author = {Diego Mendoza-Halliday and Schneiderman, M. and Kaul, C. and Julio Martinez-Trujillo} }