Controlling neuronal assemblies: a fundamental function of respiration-related brain oscillations in neuronal networks.

Respiration exerts profound influence on cognition, which is presumed to rely on the generation of local respiration-coherent brain oscillations and the entrainment of cortical neurons. Here, we propose an addition to that view by emphasizing the role of respiration in pacing cortical assemblies (i.e., groups of synchronized, coactive neurons). We review recent findings of how respiration directly entrains identified assembly patterns and discuss how respiration-dependent pacing of assembly activations might be beneficial for cognitive functions.

Disrupted-in-schizophrenia-1 is required for normal pyramidal cell-interneuron communication and assembly dynamics in the prefrontal cortex.

We interrogated prefrontal circuit function in mice lacking Disrupted-in-schizophrenia-1 (Disc1-mutant mice), a risk factor for psychiatric disorders. Single-unit recordings in awake mice revealed reduced average firing rates of fast-spiking interneurons (INTs), including optogenetically identified parvalbumin-positive cells, and a lower proportion of INTs phase-coupled to ongoing gamma oscillations. Moreover, we observed decreased spike transmission efficacy at local pyramidal cell (PYR)-INT connections in vivo, suggesting a reduced excitatory effect of local glutamatergic inputs as a potential mechanism of lower INT rates. On the network level, impaired INT function resulted in altered activation of PYR assemblies: While assembly activations defined as coactivations within 25 ms were observed equally often, the expression strength of individual assembly patterns was significantly higher in Disc1-mutant mice. Our data, thus, reveal a role of Disc1 in shaping the properties of prefrontal assembly patterns by setting INT responsiveness to glutamatergic drive.

Phase-specific pooling of sparse assembly activity by respiration-related brain oscillations.

Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. Current theories emphasize the role of neuronal assemblies, coalitions of transiently active pyramidal cells, as the core unit of cortical network computations. Here, we show that the phase of respiration-related oscillations (RROs) influences the likelihood of activation of a subset of neuronal assemblies in the medial prefrontal cortex of awake mice. RROs bias the activation of neuronal assemblies more efficiently than that of individual neurons by entraining the coactivity of assembly neurons. Moreover, the activation of assemblies is moderately biased towards the descending phase of RROs. Despite the enriched activation of assemblies during descending RRO, the overlap between individual assemblies remains constant across RRO phases. Putative GABAergic interneurons are shown to coactivate with assemblies and receive enhanced excitatory drive from assembly neurons during descending RRO, suggesting that the phase-specific recruitment of putative interneurons might help to keep the activation of different assemblies separated from each other during times of preferred assembly activation. Our results thus identify respiration-synchronized brain rhythms as drivers of neuronal assemblies and point to a role of RROs in defining time windows of enhanced yet segregated assembly activity. KEY POINTS: Activation of neuronal assemblies is phase-coupled to ongoing respiration-related oscillations (RROs) in the medial prefrontal cortex of mice. The phase coupling strength of assemblies exceeds that of individual neurons. Assemblies preferentially activate during the descending phase of RRO. Despite higher assembly frequency during descending RRO, overlap between active assemblies remains constant across RRO phase. Putative GABAergic interneurons are preferentially recruited by assembly neurons during descending RRO, suggesting that interneurons might contribute to the segregation of active assemblies during the descending phase of RRO.

Can Neuroscientists Test a New Physicalist Mind/Body View: DiCoToP (Diachronic Conjunctive Token Physicalism)?

Given that disparate mind/body views have interfered with interdisciplinary research in psychoanalysis and neuroscience, the mind/body problem itself is explored here. Adding a philosophy of mind framework, problems for both dualists and physicalists are presented, along with essential concepts including: independent mental causation, emergence, and multiple realization. To address some of these issues in a new light, this article advances an original mind/body account-Diachronic Conjunctive Token Physicalism (DiCoToP). Next, puzzles DiCoTop reveals, psychoanalytic problems it solves, and some empirical evidence accrued for views consistent with DiCoToP are presented. In closing, this piece challenges/appeals for neuroscience research to gain evidence for (or against) the DiCoToP view.

Brain-mind operational architectonics: At the boundary between quantum physics and Eastern metaphysics.

The Operational Architectonics (OA) of brain-mind functioning is a theory that unifies brain and mind through nested and dynamic hierarchy of electromagnetic brain fields. Recently, it has been enriched by concepts from physics like time, space, entropy, and self-organized criticality. This review paper advances OA theory further by delving into the foundations of quantum physics and Eastern metaphysics in relation to mind function. We aim to show that the brain-mind OA is the boundary between and integration point of quantum physics and Eastern metaphysics, and that it may inspire building a richer and more inclusive paradigm of the brain-mind relation, where quantum physics and Eastern metaphysics are inherently intertwined.

Motion contrast in primary visual cortex: a direct comparison of single neuron and population encoding.

Features from outside the classical receptive field (CRF) can modulate the stimulus-driven activity of single cells in the primary visual cortex. This modulation, mediated by horizontal and feedback networks, has been extensively described as a variation of firing rate and is considered the basis of processing features as, for example, motion contrast. However, surround influences have also been identified in pairwise spiking or local field coherence. Yet, evidence about co-existence and integration of different neural signatures remains elusive. To compare multiple signatures, we recorded spiking and LFP activity evoked by stimuli exhibiting a motion contrast in the CRFs surround in anesthetized cat primary visual cortex. We chose natural-like scenes over gratings to avoid predominance of simple visual features, which could be easily represented by a rate code. We analyzed firing rates and phase-locking to low-gamma frequency in single cells and neuronal assemblies. Motion contrast was reflected in all measures but in semi-independent populations. Whereas activation of assemblies accompanied single neuron rates, their phase relations were modulated differently. Interestingly, only assembly phase relations mirrored the direction of movement of the surround and were selectively affected by thermal deactivation of visual interhemispheric connections. We argue that motion contrast can be reflected in complementary and superimposed neuronal signatures that can represent different surround features in independent neuronal populations.

The Sensory Neocortex and Associative Memory.

Most behaviors in mammals are directly or indirectly guided by prior experience and therefore depend on the ability of our brains to form memories. The ability to form an association between an initially possibly neutral sensory stimulus and its behavioral relevance is essential for our ability to navigate in a changing environment. The formation of a memory is a complex process involving many areas of the brain. In this chapter we review classic and recent work that has shed light on the specific contribution of sensory cortical areas to the formation of associative memories. We discuss synaptic and circuit mechanisms that mediate plastic adaptations of functional properties in individual neurons as well as larger neuronal populations forming topographically organized representations. Furthermore, we describe commonly used behavioral paradigms that are used to study the mechanisms of memory formation. We focus on the auditory modality that is receiving increasing attention for the study of associative memory in rodent model systems. We argue that sensory cortical areas may play an important role for the memory-dependent categorical recognition of previously encountered sensory stimuli.

Activity Dynamics and Signal Representation in a Striatal Network Model with Distance-Dependent Connectivity.

The striatum is the main input nucleus of the basal ganglia. Characterizing striatal activity dynamics is crucial to understanding mechanisms underlying action selection, initiation, and execution. Here, we studied the effects of spatial network connectivity on the spatiotemporal structure of striatal activity. We show that a striatal network with nonmonotonically changing distance-dependent connectivity (according to a gamma distribution) can exhibit a wide repertoire of spatiotemporal dynamics, ranging from spatially homogeneous, asynchronous-irregular (AI) activity to a state with stable, spatially localized activity bumps, as in "winner-take-all" (WTA) dynamics. Among these regimes, the unstable activity bumps [transition activity (TA)] regime closely resembles the experimentally observed spatiotemporal activity dynamics and neuronal assemblies in the striatum. In contrast, striatal networks with monotonically decreasing distance-dependent connectivity (in a Gaussian fashion) can exhibit only an AI state. Thus, given the observation of spatially compact neuronal clusters in the striatum, our model suggests that recurrent connectivity among striatal projection neurons should vary nonmonotonically. In brain disorders such as Parkinson's disease, increased cortical inputs and high striatal firing rates are associated with a reduction in stimulus sensitivity. Consistent with this, our model suggests that strong cortical inputs drive the striatum to a WTA state, leading to low stimulus sensitivity and high variability. In contrast, the AI and TA states show high stimulus sensitivity and reliability. Thus, based on these results, we propose that in a healthy state the striatum operates in a AI/TA state and that lack of dopamine pushes it into a WTA state.

Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations.