Locally Measured Neuronal Correlates of Functional MRI Signals

Abstract

Functional brain imaging techniques, such as functional MRI (fMRI), are commonly employed to estimate local changes in neuronal activity in response to stimuli or experimental tasks. However, fMRI signals are not direct measures of neuronal activity such as spikes or dendritic potentials. Instead, fMRI is used to infer changes in neuronal activity based on local metabolic and blood-based (hemodynamic) responses via intermediary processes such as neurovascular coupling and MRI contrast. This chapter reviews current concepts on the neuronal basis of fMRI signals. Although the exact relationship between the fMRI blood oxygenation level-dependent (BOLD) signal and local neural activity remains a topic of ongoing research, there is a consensus among existing studies that graded increases in neuronal responses result in a monotonous increase in metabolic and hemodynamic activity. Many of these measurements further indicate that the relationship between local neural activity and the fMRI response is approximately linear. In line with this observation, negative BOLD responses have been shown to be associated with decreases in neuronal activity. Spontaneous fluctuations in fMRI signals have been shown to reflect both endogenous changes in locally measured neuronal activity and components of nonneuronal origin, such as respiration. The cortical BOLD response appears to be similarly related to the local synaptic activity that is caused by local processing and the combined ascending and descending inputs to a region, as well as to the resulting spiking output under most experimental conditions. However, in cases where synaptic and spiking activity can be dissociated, the BOLD response seems to reflect local synaptic currents more closely than the population’s spike rate changes.KeywordsCerebral Blood FlowNeuronal ActivityHemodynamic ResponseCerebral Blood VolumeSpike ActivityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.