Topic: high-density electrophysiology

The availability of high-density electrophysiology is transforming systems neuroscience and enables virtually any experimental lab to simultaneously acquire activity from hundreds of neurons throughout the brain. However, extracting single-cell activity from the resulting large datasets remains a major challenge: different experimental settings introduce various sources of contaminating noise, and even optimized spike-sorting algorithms still require manual evaluation of the resulting spike clusters. Establishing a pre-processing pipeline and manual evaluation requires expert knowledge and is

Effective decision-making requires not just resolving difficult choices but evaluating the quality of decisions once they are made. The orbitofrontal cortex (OFC) plays a key role in decision-making and has been shown to perform metacognitive computations such as post-decision confidence, i.e. the probability of being correct given the subjective evidence. How and where OFC calculations of decision confidence are output to other cortical and sub-cortical circuits is as yet unclear.Here we examined the activity of neurons in the OFC of rats, while they were performing an auditory choice task wi

The availability of high-density electrophysiology techniques is transforming systems neuroscience, enabling experimental labs to record activity from hundreds of neurons throughout the brain simultaneously. However, extracting single-cell activity from the resulting large datasets remains challenging, as various experimental conditions introduce sources of contaminating noise, and even optimized spike-sorting algorithms may produce false positive units. This requires labor-intensive manual evaluation of spike clusters.To address this challenge, we extended existing analyses and incorporated m

Functional ultrasound imaging (fUSI) can record neuronal activity down to 20 mm depth in the brain, at finer resolution than functional magnetic resonance imaging. We developed an acquisition add-on, analysis and visualization pipeline that allows efficient identification of anatomical and functional layout of the brain in 3D. Leveraging the high signal quality of fUSI, we asked whether the acquisition of multi-cm 3D functional maps can be made compatible with chronic anesthetized experiment design. Since availability of large-brained species is low and their behavioral training can be prohibi

Individuals with autism spectrum disorder (ASD) present with core deficits in social interaction and communication. The goal of the current study is to decipher the neural mechanisms underlying impaired speech and language processing in autism. Using a linear neural encoding framework, we analyzed the temporal response function (TRF) to continuous audiovisual speech stimulation at different levels of the speech processing hierarchy, ranging from acoustic to phonetic, to understand the stages at which information processing breaks down in individuals with ASD. We recorded high-density electroph

The neural mechanisms behind movement have been puzzling for decades. While much focus has been on trying to explain the generation of locomotion little attention has been given to the ability to pause ongoing movement at any point while keeping posture. Here, we argue that within this ability to pause movement lies the key to understanding the generation of movement itself. The prevailing view suggests the existence of specialized modules for distinct functions. Nevertheless, recent observations, including rotational neural activity during rhythmic limb movements, challenge this perspective (

Traditionally, vision has been largely treated as a bottom-up system that tries to make sense of the incoming input. However, contemporary accounts of active inference and predictive coding see the visual system as a goal-oriented system in which internal knowledge and learning fundamentally influence perception through top-down interactions. To study how internal visuo-motor predictions guide object visual processing, we combined high-density electrophysiology and a sequential learning task (N=41) in which subjects statistically learn the association between a sequence of objects (faces, scen