Optogenetic drive of neocortical pyramidal neurons generates fMRI signals that are correlated with spiking activity

Optogenetic brain interfaces

The brain is a large network of interconnected neurons where each cell functions as a nonlinear processing element. Unraveling the mysteries of information processing in the complex networks of the brain requires versatile neurostimulation and imaging techniques. Optogenetics is a new stimulation method which allows the activity of neurons to be modulated by light. For this purpose, the cell-types of interest are genetically targeted to produce light-sensitive proteins. Once these proteins are expressed, neural activity can be controlled by exposing the cells to light of appropriate wavelengths. Optogenetics provides a unique combination of features, including multimodal control over neural function and genetic targeting of specific cell-types. Together, these versatile features combine to a powerful experimental approach, suitable for the study of the circuitry of psychiatric and neurological disorders. The advent of optogenetics was followed by extensive research aimed to produce new lines of light-sensitive proteins and to develop new technologies: for example, to control the distribution of light inside the brain tissue or to combine optogenetics with other modalities including electrophysiology, electrocorticography, nonlinear microscopy, and functional magnetic resonance imaging. In this paper, the authors review some of the recent advances in the field of optogenetics and related technologies and provide their vision for the future of the field.

Spatiotemporal dissociation of brain activity underlying subjective awareness, objective performance and confidence

Despite intense recent research, the neural correlates of conscious visual perception remain elusive. The most established paradigm for studying brain mechanisms underlying conscious perception is to keep the physical sensory inputs constant and identify brain activities that correlate with the changing content of conscious awareness. However, such a contrast based on conscious content alone would not only reveal brain activities directly contributing to conscious perception, but also include brain activities that precede or follow it. To address this issue, we devised a paradigm whereby we collected, trial-by-trial, measures of objective performance, subjective awareness, and the confidence level of subjective awareness. Using magnetoencephalography recordings in healthy human volunteers, we dissociated brain activities underlying these different cognitive phenomena. Our results provide strong evidence that widely distributed slow cortical potentials (SCPs) correlate with subjective awareness, even after the effects of objective performance and confidence were both removed. The SCP correlate of conscious perception manifests strongly in its waveform, phase, and power. In contrast, objective performance and confidence were both contributed by relatively transient brain activity. These results shed new light on the brain mechanisms of conscious, unconscious, and metacognitive processing.

Scale-free brain activity: past, present, and future

Brain activity observed at many spatiotemporal scales exhibits a 1/f-like power spectrum, including neuronal membrane potentials, neural field potentials, noninvasive electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) signals. A 1/f-like power spectrum is indicative of arrhythmic brain activity that does not contain a predominant temporal scale (hence, 'scale-free'). This characteristic of scale-free brain activity distinguishes it from brain oscillations. Although scale-free brain activity and brain oscillations coexist, our understanding of the former remains limited. Recent research has shed light on the spatiotemporal organization, functional significance, and potential generative mechanisms of scale-free brain activity, as well as its developmental and clinical relevance. A deeper understanding of this prevalent brain signal should provide new insights into, and analytical tools for, cognitive neuroscience.

Neural circuit modulation during deep brain stimulation at the subthalamic nucleus for Parkinson's disease: what have we learned from neuroimaging studies?

Deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) represents a powerful clinical tool for the alleviation of many motor symptoms that are associated with Parkinson's disease. Despite its extensive use, the underlying therapeutic mechanisms of STN-DBS remain poorly understood. In the present review, we integrate and discuss recent literature examining the network effects of STN-DBS for Parkinson's disease, placing emphasis on neuroimaging findings, including functional magnetic resonance imaging, positron emission tomography, and single-photon emission computed tomography. These techniques enable the noninvasive detection of brain regions that are modulated by DBS on a whole-brain scale, representing a key experimental strength given the diffuse and far-reaching effects of electrical field stimulation. By examining these data in the context of multiple hypotheses of DBS action, generally developed through clinical and physiological observations, we define a multitude of consistencies and inconsistencies in the developing literature of this rapidly moving field.

Study of the spatial correlation between neuronal activity and BOLD fMRI responses evoked by sensory and channelrhodopsin-2 stimulation in the rat somatosensory cortex

In this work, we combined optogenetic tools with high-resolution blood oxygenation level-dependent functional MRI (BOLD fMRI), electrophysiology, and optical imaging of cerebral blood flow (CBF), to study the spatial correlation between the hemodynamic responses and neuronal activity. We first investigated the spatial and temporal characteristics of BOLD fMRI and the underlying neuronal responses evoked by sensory stimulations at different frequencies. The results demonstrated that under dexmedetomidine anesthesia, BOLD fMRI and neuronal activity in the rat primary somatosensory cortex (S1) have different frequency-dependency and distinct laminar activation profiles. We then found that localized activation of channelrhodopsin-2 (ChR2) expressed in neurons throughout the cortex induced neuronal responses that were confined to the light stimulation S1 region (<500 μm) with distinct laminar activation profile. However, the spatial extent of the hemodynamic responses measured by CBF and BOLD fMRI induced by both ChR2 and sensory stimulation was greater than 3 mm. These results suggest that due to the complex neurovascular coupling, it is challenging to determine specific characteristics of the underlying neuronal activity exclusively from the BOLD fMRI signals.

Progress with optogenetic functional MRI and its translational implications

Changes in brain dynamics accompany many, if not all, neuropsychiatric and neurological disorders. Even in health, however, the activity of global brain networks remains poorly understood. Although great progress has been made over the last decade in probing specific brain circuits, it has proven challenging to probe systems at the cellular level, while also observing their global causal effect. The recent development of optogenetic functional MRI has provided a key technological advancement in overcoming this problem. Using optogenetic functional MRI, it is now possible to observe whole-brain level network activity that results from modulating with millisecond timescale resolution the activity of genetically, spatially and topologically defined cell populations. This technology opens the doors for many new studies of neurological disease.

A generative spike train model with time-structured higher order correlations

Emerging technologies are revealing the spiking activity in ever larger neural ensembles. Frequently, this spiking is far from independent, with correlations in the spike times of different cells. Understanding how such correlations impact the dynamics and function of neural ensembles remains an important open problem. Here we describe a new, generative model for correlated spike trains that can exhibit many of the features observed in data. Extending prior work in mathematical finance, this generalized thinning and shift (GTaS) model creates marginally Poisson spike trains with diverse temporal correlation structures. We give several examples which highlight the model's flexibility and utility. For instance, we use it to examine how a neural network responds to highly structured patterns of inputs. We then show that the GTaS model is analytically tractable, and derive cumulant densities of all orders in terms of model parameters. The GTaS framework can therefore be an important tool in the experimental and theoretical exploration of neural dynamics.