Computational Modeling of Information Propagation during the Sleep–Waking Cycle

Non-threatening familiar sounds can go unnoticed during sleep despite the fact that they enter our brain by exciting the auditory nerves. Extracellular cortical recordings in the primary auditory cortex of rodents show that an increase in firing rate in response to pure tones during deep phases of sleep is comparable to those evoked during wakefulness. This result challenges the hypothesis that during sleep cortical responses are weakened through thalamic gating. An alternative explanation comes from the observation that the spatiotemporal spread of the evoked activity by transcranial magnetic stimulation in humans is reduced during non-rapid eye movement (NREM) sleep as compared to the wider propagation to other cortical regions during wakefulness. Thus, cortical responses during NREM sleep remain local and the stimulus only reaches nearby neuronal populations. We aim at understanding how this behavior emerges in the brain as it spontaneously shifts between NREM sleep and wakefulness. To do so, we have used a computational neural-mass model to reproduce the dynamics of the sensory auditory cortex and corresponding local field potentials in these two brain states. Following the synaptic homeostasis hypothesis, an increase in a single parameter, namely the excitatory conductance g¯AMPA, allows us to place the model from NREM sleep into wakefulness. In agreement with the experimental results, the endogenous dynamics during NREM sleep produces a comparable, even higher, response to excitatory inputs to the ones during wakefulness. We have extended the model to two bidirectionally connected cortical columns and have quantified the propagation of an excitatory input as a function of their coupling. We have found that the general increase in all conductances of the cortical excitatory synapses that drive the system from NREM sleep to wakefulness does not boost the effective connectivity between cortical columns. Instead, it is the inter-/intra-conductance ratio of cortical excitatory synapses that should raise to facilitate information propagation across the brain.

Modelling neural entrainment and its persistence: influence of frequency of stimulation and phase at the stimulus offset

The entrainment (synchronization) of brain oscillations to the frequency of sensory stimuli is a key mechanism that shapes perceptual and cognitive processes, such that atypical neural entrainment leads to neuro-psychological deficits.ObjectiveWe investigated the dynamic of neural entrainment. Particular attention was paid to the oscillatory behavior that succeed the end of the stimulation, since the persistence (reverberation) of neural entrainment may condition future sensory representations based on predictions about stimulus rhythmicity.ApproachA modified Jansen-Rit neural mass model of coupled cortical columns generated a time series whose frequency spectrum resembled that of the electroencephalogram. We evaluated spectro-temporal features of entrainment, during and after rhythmic stimulation of different frequencies, as a function of the resonance frequency of the neural population and the coupling strength between cortical columns. We tested if the duration of the entrainment persistence depended on the state of the neural network at the time the stimulus ends.Main ResultsThe entrainment of the column that received the stimulation was maximum when the frequency of the entrainer was within a narrow range around the resonance frequency of the column. When this occurred, entrainment persisted for several cycles after the stimulus terminated, and the propagation of the entrainment to other columns was facilitated. Propagation depended on the resonance frequency of the second column, and the coupling strength between columns. The duration of the persistence of the entrainment depended on the phase of the neural oscillation at the time the entrainer terminated, such that falling phases (from π/2 to 3π/2 in a sine function) led to longer persistence than rising phases (from 0 to π/2 and 3π/2 to 2π).SignificanceThe study bridges between models of neural oscillations and empirical electrophysiology, and provides insights to the use of rhythmic sensory stimulation for neuroenhancement.

Modulation of intercolumnar synchronization by endogenous electric fields in cerebral cortex

Neurons synaptically interacting in a conductive medium generate extracellular endogenous electric fields (EFs) that reciprocally affect membrane potential. Exogenous EFs modulate neuronal activity, and their clinical applications are being profusely explored. However, whether endogenous EFs contribute to network synchronization remains unclear. We analyzed spontaneously generated slow-wave activity in the cerebral cortex network in vitro, which allowed us to distinguish synaptic from nonsynaptic mechanisms of activity propagation and synchronization. Slow oscillations generated EFs that propagated independently of synaptic transmission. We demonstrate that cortical oscillations modulate spontaneous rhythmic activity of neighboring synaptically disconnected cortical columns if layers are aligned. We provide experimental evidence that these EF-mediated effects are compatible with electric dipoles. With a model of interacting dipoles, we reproduce the experimental measurements and predict that endogenous EF–mediated synchronizing effects should be relevant in the brain. Thus, experiments and models suggest that electric-dipole interactions contribute to synchronization of neighboring cortical columns.

Sources of widefield fluorescence from the brain

Widefield fluorescence microscopy is used to monitor the spiking of populations of neurons in the brain. Widefield fluorescence can originate from indicator molecules at all depths in cortex and the relative contributions from somata, dendrites, and axons are often unknown. Here, I simulate widefield illumination and fluorescence collection and determine the main sources of fluorescence for several GCaMP mouse lines. Scattering strongly affects illumination and collection. One consequence is that illumination intensity is greatest ~300–400 µm below the pia, not at the brain surface. Another is that fluorescence from a source deep in cortex may extend across a diameter of 3–4 mm at the brain surface, severely limiting lateral resolution. In many mouse lines, the volume of tissue contributing to fluorescence extends through the full depth of cortex and fluorescence at most surface locations is a weighted average across multiple cortical columns and often more than one cortical area.

Multiplane Mesoscope reveals distinct cortical interactions following expectation violations

Cortical columns interact through dynamic routing of neuronal activity. To monitor these interactions, we developed the Multiplane Mesoscope which combines three established microscopy technologies: time-division multiplexing, remote focusing, and random-access mesoscopy. The Multiplane Mesoscope allowed us to study cortical column interactions in excitatory and inhibitory subpopulations in behaving mice. We found that distinct cortical subnetworks represent expected and unexpected events, suggesting that expectation violations modify signal routing across cortical columns, and establishing the Multiplane Mesoscope as a unique platform to study signal routing.

Open Questions

This chapter addresses open, unsolved questions in neuroscience, such as the complexity of the network (which is larger than described in this book), the issue of perception, and the central role of emotions. The book's model has ignored the external globus pallidus because it simplifies the interactions and the dynamic properties of the indirect pathway. Meanwhile, considering specific properties of the cortical columns allows us to briefly address a whole new topic in neuroscience: perception. However, the chapter argues that decision-making cannot be considered as a continuation of the perception process; this is rather a different process with its own dynamics. The chapter also examines the idea that there are no ‘cold’ decisions, but simply decisions influenced by different kinds of emotions. These add an extra dimension by modulating the scalars on which the decision-making system is based to make its choices.

Ultra-high resolution fMRI reveals origins of feedforward and feedback activity within laminae of human ocular dominance columns

Ultra-high field MRI can functionally image the cerebral cortex of human subjects at the submillimeter scale of cortical columns and laminae. Here, we investigate both in concert, by, for the first time, imaging ocular dominance columns (ODCs) in primary visual cortex (V1) across different cortical depths. We ensured that putative ODC patterns in V1 (a) are stable across runs, sessions, and scanners located in different continents (b) have a width (∼1.3 mm) expected from post-mortem and animal work and (c) are absent at the retinotopic location of the blind spot. We then dissociated the effects of bottom-up thalamo-cortical input and attentional feedback processes on activity in V1 across cortical depth. Importantly, the separation of bottom-up information flows into ODCs allowed us to validly compare attentional conditions while keeping the stimulus identical throughout the experiment. We find that, when correcting for draining vein effects and using both model-based and model-free approaches, the effect of monocular stimulation is largest at deep and middle cortical depths. Conversely, spatial attention influences BOLD activity exclusively near the pial surface. Our findings show that simultaneous interrogation of columnar and laminar dimensions of the cortical fold can dissociate thalamocortical inputs from top-down processing, and allow the investigation of their interactions without any stimulus manipulation.Significance StatementThe advent of ultra-high field fMRI allows for the study of the human brain non-invasively at submillimeter resolution, bringing the scale of cortical columns and laminae into focus. De Hollander et al imaged the ocular dominance columns and laminae of V1 in concert, while manipulating top-down attention. This allowed them to separate feedforward from feedback processes in the brain itself, without resorting to the manipulation of incoming information. Their results show how feedforward and feedback processes interact in the primary visual cortex, highlighting the different computational roles separate laminae play.