Biology subjects

Kristensen, S. S.

Publications and source records attributed to Kristensen, S. S..

3 recordsLinked to original sources

bioRxiv2024

High-dimensional cortical signals reveal rich bimodal and working memory-like representations among S1 neuron populations

Complexity is important for flexibility of natural behavior and for the remarkably efficient learning of the brain. Here we assessed the signal complexity among neuron populations in somatosensory cortex (S1). To maximize our chances of capturing population level signal complexity, we used highly repeatable resolvable visual, tactile and visuo-tactile inputs and neuronal unit activity recorded at high temporal resolution. We found the state space of the spontaneous activity to be extremely high-dimensional in S1 populations. Their processing of tactile inputs was profoundly modulated by visual inputs and even fine nuances of visual input patterns were separated. Moreover, the dynamic activity states of the S1 neuron population signaled the preceding specific input long after the stimulation had terminated, i.e. resident information that could be a substrate for a working memory. Hence, the recorded high dimensional representations carried rich multimodal and internal working memory-like signals supporting high complexity in cortical circuitry operation.

neuroscience↗

bioRxiv2023

Local field potential sharp waves with diversified impact on cortical neuronal encoding of haptic input

Cortical sensory processing is greatly impacted by internally generated activity. But controlling for that activity is difficult since the thalamocortical network is a high-dimensional system with rapid state changes. Therefore, to unwind the cortical computational architecture there is a need for physiological landmarks that can be used as frames of reference for computational state. Here we use a waveshape transform method to identify conspicuous local field potential sharp waves (LFP-SPWs) in the somatosensory cortex (S1). LFP-SPW events triggered short-lasting but massive neuronal activation in all recorded neurons with a subset of neurons initiating their activation up to 20 ms before the LFP-SPW onset. In contrast, LFP-SPWs differentially impacted the neuronal spike responses to ensuing tactile inputs, depressing the tactile responses in some neurons and enhancing them in others. When LFP-SPWs coactivated with more distant ECoG-SPWs, suggesting an involvement of these SPWs in global cortical signaling, the impact of the LFP-SPW on the neuronal tactile response could change substantially, including inverting its impact to the opposite. These cortical SPWs had similar overall activity patterns as reported for hippocampal SPWs and may be a biomarker for a particular type of state change that possibly involves both hippocampus and neocortex.

neuroscience↗

bioRxiv2022

Visual Input Dynamically Changes Responses to Spatiotemporal Tactile Input Patterns in S1 Neurons

To understand how sensory events are represented in and perceived by the brain, one must understand how varying internal brain states affect neuronal decoding of sensory input. Recent studies indicate global state changes in the brain impact the representation of haptic events in neurons of the primary somatosensory cortex (S1). It could be argued that the manipulations used so far to alter the cortical circuitry behavior were artificial and not reflective of normal information processing in the neocortex. In the present study we therefore wanted to explore if natural visual stimulation also could impact the interpretation of given tactile input patterns. We recorded the unitary extracellular responses to a set of spatiotemporal tactile input patterns presented either alone or together with simultaneously multicolor flashing lights from a large number of neurons in parallel in the rat primary somatosensory cortex (S1). We found that the visual input, mildly but consistently altered the temporal spike outputs to tactile input patterns in S1 neurons. We argue that the visual input change the global cortical state to an extent that it affects the cortical representation of haptic events even within the S1 and that this is an indication that the cortical network in its information processing may be far more reliant on globally distributed network dynamics than traditionally thought.

neuroscience↗