Neural activation increases blood flow locally. This vascular signal is used by functional imaging techniques to infer the location and strength of neural activity. However, the precise spatial scale over which neural and vascular signals are correlated is unknown. Furthermore, the relative role of synaptic and spiking activity in driving haemodynamic signals is controversial. Previous studies recorded local field potentials as a measure of synaptic activity together with spiking activity and low-resolution haemodynamic imaging. Here we used two-photon microscopy to measure sensory-evoked responses of individual blood vessels (dilation, blood velocity) while imaging synaptic and spiking activity in the surrounding tissue using fluorescent glutamate and calcium sensors. In cat primary visual cortex, where neurons are clustered by their preference for stimulus orientation, we discovered new maps for excitatory synaptic activity, which were organized similarly to those for spiking activity but were less selective for stimulus orientation and direction. We generated tuning curves for individual vessel responses for the first time and found that parenchymal vessels in cortical layer 2/3 were orientation selective. Neighbouring penetrating arterioles had different orientation preferences. Pial surface arteries in cats, as well as surface arteries and penetrating arterioles in rat visual cortex (where orientation maps do not exist), responded to visual stimuli but had no orientation selectivity. We integrated synaptic or spiking responses around individual parenchymal vessels in cats and established that the vascular and neural responses had the same orientation preference. However, synaptic and spiking responses were more selective than vascular responses--vessels frequently responded robustly to stimuli that evoked little to no neural activity in the surrounding tissue. Thus, local neural and haemodynamic signals were partly decoupled. Together, these results indicate that intrinsic cortical properties, such as propagation of vascular dilation between neighbouring columns, need to be accounted for when decoding haemodynamic signals.
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http://dx.doi.org/10.1038/nature17965 | DOI Listing |
Transl Psychiatry
January 2025
Research Center Juelich, Institute of Neuroscience and Medicine 10, Research Center Juelich, Juelich, Germany.
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View Article and Find Full Text PDFJ Neurophysiol
January 2025
Department of Integrative Physiology, University of Colorado Boulder.
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View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
School of Information Science and Technology, Fudan University, Shanghai 200433, China.
To date, various kinds of memristors have been proposed as artificial neurons and synapses for neuromorphic computing to overcome the so-called von Neumann bottleneck in conventional computing architectures. However, related working principles are mostly ascribed to randomly distributed conductive filaments or traps, which usually lead to high stochasticity and poor uniformity. In this work, a heterostructure with a two-dimensional WS monolayer and a ferroelectric PZT film were demonstrated for memristors and artificial synapses, triggered by in-plane ferroelectric polarization.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
School of Materials Science and Engineering, Gyeongsang National University, Jinju, Gyeongsangnam-do 52828, Republic of Korea.
Advances in the semiconductor industry have been limited owing to the constraints imposed by silicon-based CMOS technology; hence, innovative device design approaches are necessary. This study focuses on "more than Moore" approaches, specifically in neuromorphic computing. Although MoS devices have attracted attention as neuromorphic computing candidates, their performances have been limited due to environment-induced perturbations to carrier dynamics and the formation of defect states.
View Article and Find Full Text PDFBiological memory networks are thought to store information by experience-dependent changes in the synaptic connectivity between assemblies of neurons. Recent models suggest that these assemblies contain both excitatory and inhibitory neurons (E/I assemblies), resulting in co-tuning and precise balance of excitation and inhibition. To understand computational consequences of E/I assemblies under biologically realistic constraints we built a spiking network model based on experimental data from telencephalic area Dp of adult zebrafish, a precisely balanced recurrent network homologous to piriform cortex.
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