Since the popularization of GPUs for machine learning (ML) workloads, several dedicated accelerator chips have emerged, offering architectures optimized for common ML operations and requirements. The

The natural world is full of noise, but the brain’s capacity for information transmission is severely limited. Therefore, discarding irrelevant information contained in sensory inputs while retaining

Background: The balance of excitation and inhibition (E-I) is a key functional property of cortical microcircuits [1] which changes through lifespan. Adolescence is considered a crucial period for the

The prefrontal cortex (PFC) plays an important role in working memory [1], however, the underlying neural processes remains elusive. Studies on the hippocampus revealed that place cell sequences encod

Even with complete knowledge of the underlying wiring diagram using electron microscopy and the neuronal activity through $in~vivo$ recordings, we can only ever correlate neuron function with particip

Understanding how tasks are processed across the entire brain is a central yet complex question in neuroscience. Recently, the release of brainwide electrophysiological recordings in a standardized be

Despite the large number of active neurons in the cortex, the activity of neuronal populations is expected to lie on a low-dimensional manifold for different brain regions [1]. Variants of principal c

Robotic-assisted rehabilitation therapies play a crucial role in improving motor recovery by providing precise, repeatable, and intensive therapeutic interventions that traditional methods often lack

Transcranial magnetic stimulation (TMS) is a promising tool for neuromodulatory interventions in research and clinical settings, yet its effects are highly variable. Real-time EEG-TMS seeks to mitigat

Perceivers benefit from integrating their prior beliefs with sensory signals based on their relative reliability to mitigate the effects of stochastic noise. However, in volatile environments, one sho

Central place foraging insects like the honeybee (Apis mellifera) are the masters of visual navigation of the insect world: They are able to reliably return to their nest under a wide range of visual

Background: Biophysical network modeling (BNM) of the brain is a promising technique for bridging macro- and microscale levels of investigation, enabling inferences about latent features of brain acti

Neuronal cultures in vitro are a versatile system for studying the basic properties of individual neurons and neuronal networks that recently gained additional attention as a precision medicine tool.

Rodents and primates exhibit trade-offs between exploitation and exploration. Understanding how different behavioral states modulate neural activities remains a critical question. Previous research ha

Cognitive maps have been proposed as an essential relational structure for human memory and thought (Tolman, 1948; Constantinescu et al., 2016). In this format, remembered entities are embedded in spa

How does the brain process and integrate information from different sensory modalities? This intriguing question has been explored in this study by recording the activity of the Ventral Premotor Corte

The mammalian neocortex possesses the remarkable ability to translate complex sensory inputs into abstract representations through the coordinated activity of large neuronal ensembles across the senso

Artificial recurrent neural networks (RNNs) have become a customary research tool in theoretical neuroscience, being used as models of biological neural networks performing cognitive tasks. While RNNs

Animals make decisions based on high-dimensional sensory inputs. Obtaining their low-dimensional disentangled representations, ideally in an unsupervised manner, is essential for straightforward downs

Artificial recurrent neural networks (RNNs) are difficult to train due to their tendency towards instability, and common training algorithms that tame such networks are not biologically plausible, i.e

For more than 20 years, a growing body of evidence indicates that the brain functions near a critical point, where neural activity is balanced between damping and amplification. One of the appealing b

Activity dependent synaptic plasticity is widely believed to play the major role in learning and memory. Moreover, the robustness of formed memories is dependent on the stability of synapses. However,

A fundamental problem in neuroscience is how neuronal activity in the brain generates organized and stable behaviors across multiple timescales. Recent research in many model organisms, e.g. in monkey

The ability to accurately localize sound sources is crucial for human and other animals. An important question is: how could the brain calibrate its space map in response to changes to acoustic cu

Experimental techniques now make it possible to measure the structure and function of neural circuits at an unprecedented scale and resolution. How can we leverage this wealth of data to understand ho

Every day we make decisions critical for adaptation and survival. We repeat actions with known consequences. But we can also infer associations between loosely related events to infer and imagine the

Biophysical neuron models provide mechanistic insight about empirically observed phenomena. However, biophysical neuron models are expensive to simulate, thereby limiting the scale of biophysical mode

Among the brain structures affected in Schizophrenia is the hippocampus. In addition to structural changes [1], dysfunctions of the synaptic plasticity have also been observed supporting cognitive imp

Integrating information is particularly crucial when decisions contain complex information. In decision neuroscience, it has been widely studied how overall decision value is encoded in the brain, but

To understand network computation, we usually focus on the connectivity among neurons. In this talk, however, I demonstrate how the biophysics of action-potential generation can have a decisive impact

Ongoing neural activity fluctuates over a broad range of timescales. Variations in intrinsic timescales across the forebrain relate to the functional specialization of cortical areas along the visual

Neuronal cultures and human stem-cell-derived organoids are fundamental building blocks of neuroscientific research and future personalized medicine. However, in-vitro networks show considerably more

Analog neuromorphic circuits emulate the dynamic properties of biological neural systems through their physics [1], sharing similarities and constraints with them [2,3]. This alignment can be leverage

Synaptic plasticity is thought to underlie learning and memory [1]. Plasticity rules can be active in different synaptic connection types, such as excitatory-excitatory (EE) and inhibitory-excitatory

Healthy brains exhibit a rich dynamical repertoire with flexible and varied spatiotemporal patterns replays on both microscopic and large scales. Neurodegenerative diseases reduce this functional repe

The relationship between vergence and accommodation remains relatively unexplored. The frequent co-occurrence of non-strabismic accommodation and vergence disorders suggests a link between the two pro

Our research explores the neural mechanisms underlying flexibility during natural social interactions - how animals process dynamic sensory cues from a partner, make decisions, and pattern the appropr

Brain-computer interfaces (BCIs) are a powerful tool in both clinical applications and basic science research. Traditionally, BCIs rely on electrical signals collected by electrode arrays, which usual

The involvement of early visual cortex during the short-term maintenance of visual information has been demonstrated in human fMRI studies [1,2]. However, evidence for sustained, stimulus-related neur

Contrary to typical artificial neural network (ANN) design, biological neurons are not identical. Neurons differ substantially in their physiological properties. Heterogeneity has been hypothesized to

Animals often make use of information from multiple sensory systems, such as vision, proprioception, olfaction, and audition to guide their behavior. They must thus integrate these different sensory i

There has been a long-lasting debate on whether the function of the hippocampal formation is to store and retrieve episodic memory, supported by experiments in humans, or to code for space, suggested

Optogenetic inhibition of excitatory subpopulations of the hippocampus has been suggested as a new approach in the treatment of temporal lobe epilepsy (TLE), one of the most common types of drug-resis

Olfaction facilitates a large variety of animal behaviors such as feeding, mating, and communication. In the mammal olfactory system, the olfactory bulb (OB) and piriform cortex (PCx) are responsible

Motor control is a complex, high-dimensional task. It has been suggested that the brain may reduce the dimensionality of this control problem by using a set of motor primitives (or muscle synergies) t

A model for NMDA-receptor-mediated synaptic currents generating persistent activity proposed by Wang and Brunel [1–3] has been widely adopted in computational neuroscience, both for spiking-neuron and

Information in sensory neurons is conveyed by spiking activity varying in time. This is quantified by the mutual-information rate (MIR), given by $\mathrm{MIR}:=\underset{\Delta t\rightarrow\infty}{\l

Dopaminergic Reward Prediction Errors (RPEs) are a key motivation and inspiration for model free, temporal difference reinforcement learning methods. Originally, the correlation of RPEs with model fre

Hippocampal granule cell (GC) models exhibit degeneracy with different ion channel parameters resulting in comparable functional behaviour [1,2]. However, it is unknown how the degenerate models are f

Error-related potentials (ErrPs) represent the neural signature of error processing in the brain and numerous studies have demonstrated their reliable detection using non-invasive techniques such as e