13 papers · ranked by Valyu relevance
Yuru Song, Marcus K. Benna
Cortical neurons often establish multiple synaptic contacts with the same postsynaptic neuron. To avoid functional redundancy of these parallel synapses, it is crucial that each synapse exhibits distinct computational properties. Here we model the current to the soma contributed by each synapse as a sigmoidal…
Willem A.M. Wybo, Leander Ewert, Charl Linssen, Pooja Babu + 3 more
While the implementation of learning and memory in the brain is governed in large part by subcellular mechanims in the dendrites of neurons, large-scale network simulations featuring such processes remain challenging to achieve. This can be attributed to a lack of appropriate software tools, as neuroscientific…
Matteo De Matola, Giorgio Arcara
Convolutional neural networks (CNNs) are a class of artificial neural networks (ANNs). Since the early 2010s, they have been widely adopted as models of primate vision and classifiers of neuroimaging data, becoming relevant for a wealth of neuroscientific fields. However, the majority of neuroscience researchers come…
Yuma Osako, Aineias Arango, Toshitake Asabuki
Animals flexibly combine learned behaviors into novel actions without practicing their combinations, yet the computational mechanisms that enable independently acquired computations to be expressed in parallel remain unclear. Here we show that feedback geometry during learning determines whether recurrent dynamics can…
Santiago Galella, Salva Ardid
Our brain can filter and integrate external information with internal representations to accomplish goal-directed behavior. The ability to switch between tasks effectively in response to context and external stimuli is a hallmark of cognitive control. Task switching occurs rapidly and efficiently, allowing us to…
Patrick W. Hullett, Matthew K. Leonard, Maria Luisa Gorno-Tempini, Maria Luisa Mandelli + 1 more
Models of speech perception are centered around a hierarchy in which auditory representations in the thalamus propagate to primary auditory cortex, then to the lateral temporal cortex, and finally through dorsal and ventral pathways to sites in the frontal lobe. However, evidence for short latency speech responses and…
Marcus Ghosh, Dan F. M. Goodman
Neural circuits are sparse and bidirectional. Meaning that signals flow from early sensory areas to later regions and back. Yet, between connected areas there exist some but not all pathways. How does this structure, somewhere between feedforward and fully recurrent, shape circuit function? To address this question, we…
G. Kandemir, D. H. Duncan, D. van Moorselaar, J. Theeuwes
For almost half a century, target-distractor similarity has been known to induce different visual search modes. When a target is highly salient, it can pop out, suggesting parallel processing of all items irrespective of set size. By contrast, high similarity among items requires item-by-item comparison with an…
Tianwei Wang, Yun Chen, Yiheng Zhang, He Cui
Although motor cortex has been found to be modulated by sensory or cognitive sequences, the linkage between multiple movement elements and sequence-related responses is not yet understood. Here, we recorded neuronal activity from the motor cortex with implanted micro-electrode arrays and single electrodes while monkeys…
Varun Sanjay Birari, Ithai Rabinowitch
The brain is overall bilaterally symmetrical, but exhibits also considerable asymmetry. While symmetry may endow neural networks with robustness and resilience, asymmetry may enable parallel information processing and functional specialization. How is this functional tradeoff between symmetrical and asymmetrical brain…
Camilo J. Mininni, B. Silvano Zanutto
A main goal in neuroscience is to understand the computations carried out by neural populations that give animals their cognitive skills. Neural network models allow to formulate explicit hypothesis regarding the algorithms instantiated in the dynamic of a neural population, its firing statistics, and the underlying…
Laura E. Suárez, Agoston Mihalik, Filip Milisav, Kenji Marshall + 4 more
The connection patterns of neural circuits form a complex network. How signaling in these circuits manifests as complex cognition and adaptive behaviour remains the central question in neuroscience. Concomitant advances in connectomics and artificial intelligence open fundamentally new opportunities to understand how…
Xiaohan Zhang, Mohamad Altrabulsi, Wenqi Xu, Ralf Wimmer + 2 more
The mammalian forebrain is the seat of higher cognition with architectural parallels to modern machine learning systems. Specifically, the cortex resembles recurrent neural networks (RNNs) while the thalamus resembles feedforward neural networks (FNNs). How such architectural features endow the forebrain with its…