Social Minds Sync Alike.

In this issue of Cell, Zhang and Yatsev, 2019 and Kingsbury et al. (2019) provide insight into the emergence of synchronized neuronal activity between prefrontal cortices of two brains that share the same social context via electrophysiology recordings in bats and calcium-imaging in mice.

Dynamic Patterns of Spontaneous Ongoing Activity in the Visual Cortex of Anesthetized and Awake Monkeys are Different.

Ongoing internal cortical activity plays a major role in perception and behavior both in animals and humans. Previously we have shown that spontaneous patterns resembling orientation-maps appear over large cortical areas in the primary visual-cortex of anesthetized cats. However, it remains unknown 1) whether spontaneous-activity in the primate also displays similar patterns and 2) whether a significant difference exists between cortical ongoing-activity in the anesthetized and awake primate. We explored these questions by combining voltage-sensitive-dye imaging with multiunit and local-field-potential recordings. Spontaneously emerging orientation and ocular-dominance maps, spanning up to 6 × 6 mm2, were readily observed in anesthetized but not in awake monkeys. Nevertheless, spontaneous correlated-activity involving orientation-domains was observed in awake monkeys. Under both anesthetized and awake conditions, spontaneous correlated-activity coincided with traveling waves. We found that spontaneous activity resembling orientation-maps in awake animals spans smaller cortical areas in each instance, but over time it appears across all of V1. Furthermore, in the awake monkey, our results suggest that the synaptic strength had been completely reorganized including connections between dissimilar elements of the functional architecture. These findings lend support to the notion that ongoing-activity has many more fast switching representations playing an important role in cortical function and behavior.

Critical dynamics, anesthesia and information integration: Lessons from multi-scale criticality analysis of voltage imaging data.

Critical dynamics are thought to play an important role in neuronal information-processing: near critical networks exhibit neuronal avalanches, cascades of spatiotemporal activity that are scale-free, and are considered to enhance information capacity and transfer. However, the exact relationship between criticality, awareness, and information integration remains unclear. To characterize this relationship, we applied multi-scale avalanche analysis to voltage-sensitive dye imaging data collected from animals of various species under different anesthetics. We found that anesthesia systematically varied the scaling behavior of neural dynamics, a change that was mirrored in reduced neural complexity. These findings were corroborated by applying the same analyses to a biophysically realistic cortical network model, in which multi-scale criticality measures were associated with network properties and the capacity for information integration. Our results imply that multi-scale criticality measures are potential biomarkers for assessing the level of consciousness.

Imaging the Dynamics of Mammalian Neocortical Population Activity In-Vivo.

Neural computations underlying sensory perception, cognition and motor control are performed by populations of neurons at different anatomical and temporal scales. Few techniques are currently available for exploring dynamics of local and large range populations. Voltage-sensitive dye imaging (VSDI) reveals neural population activity in areas ranging from a few tens of microns to a couple of centimeters, or two areas up to ~10 cm apart. VSDI provides a sub-millisecond temporal resolution, and a spatial resolution of about 50 µm. The dye signal emphasizes subthreshold synaptic potentials. VSDI has been applied in the mouse, rat, gerbil, ferret, tree shrew, cat and monkey cortices, in order to explore lateral spread of retinotopic or somatotopic activation, the dynamic spatiotemporal pattern resulting from sensory activation, including the somatosensory, olfactory, auditory, and visual modalities, as well as motor preparation and the properties of spontaneously-occurring population activity. In this chapter we focus on VSDI in-vivo and review results obtained mostly in the visual system in our laboratory.

Vocal labeling of others by nonhuman primates.

Humans, dolphins, and elephants are the only known species that vocally label their conspecifics. It remains unclear whether nonhuman primates share this ability. We recorded spontaneous "phee-call" dialogues between pairs of marmoset monkeys. We discovered that marmosets use these calls to vocally label their conspecifics. Moreover, they respond more consistently and correctly to calls that are specifically directed at them. Analysis of calls from multiple monkeys revealed that family members use similar calls and acoustic features to label others and perform vocal learning. These findings shed light on the complexities of social vocalizations among nonhuman primates and suggest that marmoset vocalizations may provide a model for understanding aspects of human language, thereby offering new insights into the evolution of social communication.

Temporally-structured acquisition of multidimensional optical imaging data facilitates visualization of elusive cortical representations in the behaving monkey.

Fundamental understanding of higher cognitive functions can greatly benefit from imaging of cortical activity with high spatiotemporal resolution in the behaving non-human primate. To achieve rapid imaging of high-resolution dynamics of cortical representations of spontaneous and evoked activity, we designed a novel data acquisition protocol for sensory stimulation by rapidly interleaving multiple stimuli in continuous sessions of optical imaging with voltage-sensitive dyes. We also tested a new algorithm for the "temporally structured component analysis" (TSCA) of a multidimensional time series that was developed for our new data acquisition protocol, but was tested only on simulated data (Blumenfeld, 2010). In addition to the raw data, the algorithm incorporates prior knowledge about the temporal structure of the data as well as input from other information. Here we showed that TSCA can successfully separate functional signal components from other signals referred to as noise. Imaging of responses to multiple visual stimuli, utilizing voltage-sensitive dyes, was performed on the visual cortex of awake monkeys. Multiple cortical representations, including orientation and ocular dominance maps as well as the hitherto elusive retinotopic representation of orientation stimuli, were extracted in only 10s of imaging, approximately two orders of magnitude faster than accomplished by conventional methods. Since the approach is rather general, other imaging techniques may also benefit from the same stimulation protocol. This methodology can thus facilitate rapid optical imaging explorations in monkeys, rodents and other species with a versatility and speed that were not feasible before.

Contextual and pure time coding for self and other in the hippocampus.

Navigation and episodic memory depend critically on representing temporal sequences. Hippocampal 'time cells' form temporal sequences, but it is unknown whether they represent context-dependent experience or time per se. Here we report on time cells in bat hippocampal area CA1, which, surprisingly, formed two distinct populations. One population of time cells generated different temporal sequences when the bat hung at different locations, thus conjunctively encoding spatial context and time-'contextual time cells'. A second population exhibited similar preferred times across different spatial contexts, thus purely encoding elapsed time. When examining neural responses after the landing moment of another bat, in a social imitation task, we found time cells that encoded temporal sequences aligned to the other's landing. We propose that these diverse time codes may support the perception of interval timing, episodic memory and temporal coordination between self and others.

Entorhinal grid-like codes and time-locked network dynamics track others navigating through space.

Navigating through crowded, dynamically changing environments requires the ability to keep track of other individuals. Grid cells in the entorhinal cortex are a central component of self-related navigation but whether they also track others' movement is unclear. Here, we propose that entorhinal grid-like codes make an essential contribution to socio-spatial navigation. Sixty human participants underwent functional magnetic resonance imaging (fMRI) while observing and re-tracing different paths of a demonstrator that navigated a virtual reality environment. Results revealed that grid-like codes in the entorhinal cortex tracked the other individual navigating through space. The activity of grid-like codes was time-locked to increases in co-activation and entorhinal-cortical connectivity that included the striatum, the hippocampus, parahippocampal and right posterior parietal cortices. Surprisingly, the grid-related effects during observation were stronger the worse participants performed when subsequently re-tracing the demonstrator's paths. Our findings suggests that network dynamics time-locked to entorhinal grid-cell-related activity might serve to distribute information about the location of others throughout the brain.

Embedding of cortical representations by the superficial patch system.

Pyramidal cells in layers 2 and 3 of the neocortex of many species collectively form a clustered system of lateral axonal projections (the superficial patch system--Lund JS, Angelucci A, Bressloff PC. 2003. Anatomical substrates for functional columns in macaque monkey primary visual cortex. Cereb Cortex. 13:15-24. or daisy architecture--Douglas RJ, Martin KAC. 2004. Neuronal circuits of the neocortex. Annu Rev Neurosci. 27:419-451.), but the function performed by this general feature of the cortical architecture remains obscure. By comparing the spatial configuration of labeled patches with the configuration of responses to drifting grating stimuli, we found the spatial organizations both of the patch system and of the cortical response to be highly conserved between cat and monkey primary visual cortex. More importantly, the configuration of the superficial patch system is directly reflected in the arrangement of function across monkey primary visual cortex. Our results indicate a close relationship between the structure of the superficial patch system and cortical responses encoding a single value across the surface of visual cortex (self-consistent states). This relationship is consistent with the spontaneous emergence of orientation response-like activity patterns during ongoing cortical activity (Kenet T, Bibitchkov D, Tsodyks M, Grinvald A, Arieli A. 2003. Spontaneously emerging cortical representations of visual attributes. Nature. 425:954-956.). We conclude that the superficial patch system is the physical encoding of self-consistent cortical states, and that a set of concurrently labeled patches participate in a network of mutually consistent representations of cortical input.

Arousal increases the representational capacity of cortical tissue.

Arousal patently transforms the faculties of complex organisms. Although typical changes in cortical activity such as seen in EEG and LFP measurements are associated with change in state of arousal, it remains unclear what in the constitution of such state dependent activity enables this profound enhancement of ability. We put forward the hypothesis that arousal modulates cortical activity by rendering it more fit to represent information. We argue that representational capacity is of a dual nature-it requires not only that cortical tissue generate complex activity (i.e. spatiotemporal neuronal events), but also a complex cortical activity space (which is comprised of such spatiotemporal events). We explain that the topological notion of complexity-homology-is the pertinent measure of the complexity of neuronal activity spaces, as homological structure indicates not only the degree to which underlying activity is inherently clustered but also registers the effective dimensionality of the configurations formed by such clusters. Changes of this sort in the structure of cortical activity spaces can serve as the basis of the enhanced capacity to make perceptual/behavioral distinctions brought about by arousal. To show the feasibility of these ideas, we analyzed voltage sensitive dye imaging (VSDI) data acquired from primate visual cortex in disparate states of arousal. Our results lend some support to the theory: first as arousal increased so did the complexity of activity (that is the complexity of VSDI movies). Moreover, the complexity of structure of activity space (that is VSDI movie space) as measured by persistent homology-a multi scale topological measure of complexity-increased with arousal as well.

Removal of spatial biological artifacts in functional maps by local similarity minimization.

Functional maps obtained by various technologies, including optical imaging techniques, f-MRI, PET, and others, may be contaminated with biological artifacts such as vascular patterns or large patches of parenchyma. These artifacts originate mostly from changes in the microcirculation that result from either activity-dependent changes in volume or from oximetric changes that do not co-localize with neuronal activity per se. Standard methods do not always suffice to reduce such artifacts, in which case conspicuous spatial artifacts mask details of the underlying activity patterns. Here we propose a simple algorithm that efficiently removes spatial biological artifacts contaminating high-resolution functional maps. We validated this procedure by applying it to cortical maps resulting from optical imaging, based either on voltage-sensitive dye signals or on intrinsic signals. To remove vascular spatial patterns we first constructed a template of typical artifacts (vascular/cardiac pulsation/vasomotion), using principle components derived from baseline information obtained in the absence of stimulation. Next, we modified this template by means of local similarity minimization (LSM), achieved by measuring neighborhood similarity between contaminated data and the artifact template and then abolishing the similarity. LSM thus removed spatial patterns originating from the cortical vasculature components, including large fields of capillary parenchyma, helping to unveil details of neuronal activity patterns that were otherwise masked by these vascular artifacts. Examples obtained from our imaging experiments with anaesthetized cats and behaving monkeys showed that the LSM method is both general and reproducible, and is often superior to other available procedures.

Columnar resolution of blood volume and oximetry functional maps in the behaving monkey; implications for FMRI.

The ultimate goal of high-resolution functional brain mapping is single-condition (stimulus versus no-stimulus maps) rather than differential imaging (comparing two "stimulus maps"), because the appropriate ("orthogonal") stimuli are rarely available. This requires some component(s) of activity-dependent hemodynamic signals to closely colocalize with electrical activity, like the early increase in deoxyhemoglobin, shown previously to yield high-quality functional single-condition maps. Conversely, nonlocal vascular responses dominate in cerebral blood volume (CBV)-based single-condition maps. Differential CBV maps are largely restricted to the parenchyma, implying that part of the CBV response does colocalize with electrical activity at fine spatial scale. By removing surface vascular activation from optical imaging data, we document the existence of a capillary CBV response component, regulated at fine spatial scale and yielding single-condition maps exhibiting approximately 100 microm resolution. Blood volume and -flow based single-condition functional mapping at columnar level should thus be feasible, provided that the capillary response component is selectively imaged.

Social place-cells in the bat hippocampus.

Social animals have to know the spatial positions of conspecifics. However, it is unknown how the position of others is represented in the brain. We designed a spatial observational-learning task, in which an observer bat mimicked a demonstrator bat while we recorded hippocampal dorsal-CA1 neurons from the observer bat. A neuronal subpopulation represented the position of the other bat, in allocentric coordinates. About half of these "social place-cells" represented also the observer's own position-that is, were place cells. The representation of the demonstrator bat did not reflect self-movement or trajectory planning by the observer. Some neurons represented also the position of inanimate moving objects; however, their representation differed from the representation of the demonstrator bat. This suggests a role for hippocampal CA1 neurons in social-spatial cognition.

Imaging the Neocortex Functional Architecture Using Multiple Intrinsic Signals: Implications for Hemodynamic-Based Functional Imaging.

Optical imaging based on intrinsic signals has provided a new level of understanding of the principles underlying cortical development, organization, and function, providing a spatial resolution of up to 20 µm for mapping cortical columns in vivo. This introduction briefly reviews the development of this technique, the types of applications that have been pursued, and the general implications of some findings for other neuroimaging techniques based on hemodynamic responses (e.g., functional magnetic resonance imaging).

Voltage-Sensitive Dye Imaging of Neocortical Activity.

Neural computations underlying sensory perception, cognition, and motor control are performed by populations of neurons at different anatomical and temporal scales. Few techniques are currently available for exploring the dynamics of local and large range populations. Voltage-sensitive dye imaging (VSDI), based on organic voltage probes, reveals neural population activity in areas ranging from a few tens of micrometers to a couple of centimeters, or two areas up to ~10 cm apart. VSDI provides a submillisecond temporal resolution and a spatial resolution of ~50 µm. The dye signal emphasizes subthreshold synaptic potentials. VSDI has been applied in the mouse, rat, gerbil, ferret, tree shrew, cat, and monkey cortices to explore the lateral spread of retinotopic or somatotopic activation; the dynamic spatiotemporal pattern resulting from sensory activation, including the somatosensory, olfactory, auditory, and visual modalities; and motor preparation and the properties of spontaneously occurring population activity. In this introduction, we focus on VSDI in vivo and review results obtained mostly in the visual system in our laboratory.

Independent component analysis of high-resolution imaging data identifies distinct functional domains.

In the vertebrate brain external stimuli are often represented in distinct functional domains distributed across the cortical surface. Fast imaging techniques used to measure patterns of population activity record movies with many pixels and many frames, i.e., data sets with high dimensionality. Here we demonstrate that principal component analysis (PCA) followed by spatial independent component analysis (sICA), can be exploited to reduce the dimensionality of data sets recorded in the olfactory bulb and the somatosensory cortex of mice as well as the visual cortex of monkeys, without loosing the stimulus-specific responses. Different neuronal populations are separated based on their stimulus-specific spatiotemporal activation. Both, spatial and temporal response characteristics can be objectively obtained, simultaneously. In the olfactory bulb, groups of glomeruli with different response latencies can be identified. This is shown for recordings of olfactory receptor neuron input measured with a calcium-sensitive axon tracer and for network dynamics measured with the voltage-sensitive dye RH 1838. In the somatosensory cortex, barrels responding to the stimulation of single whiskers can be automatically detected. In the visual cortex orientation columns can be extracted. In all cases artifacts due to movement, heartbeat or respiration were separated from the functional signal by sICA and could be removed from the data set. sICA following PCA is therefore a powerful technique for data compression, unbiased analysis and dissection of imaging data of population activity, collected with high spatial and temporal resolution.