Communication among neocortical areas is largely thought to be mediated by long-range synaptic interactions between cortical neurons, with the thalamus providing only an initial relay of information from the sensory periphery. Higher-order thalamic nuclei receive strong synaptic inputs from the cortex and send robust projections back to other cortical areas, providing a distinct and potentially critical route for corticocortical communication. However, the relative contributions of corticocortical and thalamocortical inputs to higher-order cortical function remain unclear. Using imaging of neurons and axon terminals in combination with optogenetic manipulations, we find that the higher-order visual thalamus of mice has a unique impact on the posterior medial visual cortex (PM). Whereas corticocortical projections from lower cortical areas convey robust visual information to PM, higher-order thalamocortical projections convey information about global arousal state. Together, these findings suggest a key role for the higher-order thalamus in providing contextual signals that may flexibly modulate cortical sensory processing.

Recent work suggests an important role for cortical-subcortical networks in seizure-related loss of consciousness. Temporal lobe seizures disrupt subcortical arousal systems, which may lead to depressed cortical function and loss of consciousness. Extracellular recordings show ictal neocortical slow waves at about 1 Hz, but it is not known whether these simply represent seizure propagation or alternatively deep sleep-like activity, which should include cortical neuronal Up and Down states. In this study, using in vivo whole-cell recordings in a rat model of focal limbic seizures, we directly examine the electrophysiological properties of cortical neurons during seizures and deep anesthesia. We found that during seizures, the membrane potential of frontal cortical secondary motor cortex layer 5 neurons fluctuates between Up and Down states, with decreased input resistance and increased firing rate in Up states when compared to Down states. Importantly, Up and Down states in seizures are not significantly different from those in deep anesthesia, in terms of membrane potential, oscillation frequency, firing rate, and input resistance. By demonstrating these fundamental similarities in cortical electrophysiology between deep anesthesia and seizures, our results support the idea that a state of decreased cortical arousal may contribute to mechanisms of loss of consciousness during seizures.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multiunit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during high arousal with locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior. SIGNIFICANCE STATEMENT Cortical sensory processing strongly depends on arousal. In the mouse visual system, locomotion (associated with high arousal) has previously been shown to enhance the sensory responses of neurons in primary visual cortex (V1). Yet, arousal fluctuates on a moment-to-moment basis, even during quiescent periods. The characteristics of V1 sensory processing across the continuum of arousal are unclear. Furthermore, the arousal level corresponding to optimal visual detection performance is unknown. We show that the magnitude and reliability of sensory-evoked V1 responses are monotonic increasing functions of arousal, and largest during locomotion. Visual detection behavior, however, is suboptimal during high arousal with locomotion, and usually best during intermediate arousal. Our study provides a more complete picture of the dependence of V1 sensory processing on arousal.

Focal limbic seizures often impair consciousness/awareness with major negative impact on quality of life. Recent work has shown that limbic seizures depress brainstem arousal systems, including reduced action potential firing in a key node: cholinergic neurons of the pedunculopontine tegmental nucleus (PPT). In vivo whole-cell recordings have not previously been achieved in PPT, but are used here with the goal of elucidating the mechanisms of reduced PPT cholinergic neuronal activity. An established model of focal limbic seizures was used in rats following brief hippocampal stimulation under light anesthesia. Whole-cell in vivo recordings were obtained from PPT neurons using custom -fabricated 9-10 mm tapered patch pipettes, and cholinergic neurons were identified histologically. Average membrane potential, input resistance, membrane potential fluctuations and variance were analyzed during seizures. A subset of PPT neurons exhibited reduced firing and hyperpolarization during seizures and stained positive for choline acetyltransferase. These PPT neurons showed a mean membrane potential hyperpolarization of -3.82 mV (+/- 0.81 SEM, P < .05) during seizures, and also showed significantly increased input resistance, fewer excitatory post-synaptic potential (EPSP)-like events (P<.05), and reduced membrane potential variance (P < .01). The combination of increased input resistance, decreased EPSP-like events and decreased variance weigh against active ictal inhibition and support withdrawal of excitatory input as the dominant mechanism of decreased activity of cholinergic neurons in the PPT. Further identifying synaptic mechanisms of depressed arousal during seizures may lead to new treatments to improve ictal and postictal cognition.

Slow, synchronized neuronal oscillations in thalamocortical systems are hallmarks of sleep and inattentiveness. Sleep rhythms, such as slow (<1 Hz), delta (1–4 Hz), and spindle (7–14) oscillations, are associated with alternating periods of neuronal activation and quiescence that are

During even the most quiescent behavioral periods, the cortex and thalamus express rich spontaneous activity in the form of slow (<1 Hz), synchronous network state transitions. Throughout this so-called slow oscillation, cortical and thalamic neurons fluctuate between periods of intense synaptic activity (Up states) and almost complete silence (Down states). The two decades since the original characterization of the slow oscillation in the cortex and thalamus have seen considerable advances in deciphering the cellular and network mechanisms associated with this pervasive phenomenon. There are, nevertheless, many questions regarding the slow oscillation that await more thorough illumination, particularly the mechanisms by which Up states initiate and terminate, the functional role of the rhythmic activity cycles in unconscious or minimally conscious states, and the precise relation between Up states and the activated states associated with waking behavior. Given the substantial advances in multineuronal recording and imaging methods in both in vivo and in vitro preparations, the time is ripe to take stock of our current understanding of the slow oscillation and pave the way for future investigations of its mechanisms and functions. My aim in this Review is to provide a comprehensive account of the mechanisms and functions of the slow oscillation, and to suggest avenues for further exploration.

Synaptic inhibition plays a crucial role in the precise timing of spiking activity in the cerebral cortex. Synchronized, rhythmic inhibitory activity in the gamma (30-80 Hz) range is thought to be especially important for the active, information-processing neocortex, but the circuit mechanisms that give rise to synchronized inhibition are uncertain. In particular, the relative contributions of reciprocal inhibitory connections, excitatory-inhibitory interactions, and electrical synapses to precise spike synchrony among inhibitory interneurons are not well understood. Here we describe experiments on mouse barrel cortex in vitro as it spontaneously generates slow (<1 Hz) oscillations (Up and Down states). During Up states, inhibitory postsynaptic currents (IPSCs) are generated at gamma frequencies and are more synchronized than excitatory postsynaptic currents (EPSCs) among neighboring pyramidal cells. Furthermore, spikes in homotypic pairs of interneurons are more synchronized than in pairs of pyramidal cells. Comparing connexin36 knockout and wild-type animals, we found that electrical synapses make a minimal contribution to synchronized inhibition during Up states. Estimations of the delays between EPSCs and IPSCs in single pyramidal cells showed that excitation often preceded inhibition by a few milliseconds. Finally, tonic optogenetic activation of different interneuron subtypes in the absence of excitation led to only weak synchrony of IPSCs in pairs of pyramidal neurons. Our results suggest that phasic excitatory inputs are indispensable for synchronized spiking in inhibitory interneurons during Up states and that electrical synapses play a minimal role.

During cortical network activity, recurrent synaptic excitation among pyramidal neurons is approximately balanced by synaptic inhibition, which is provided by a vast diversity of inhibitory interneurons. The relative contributions of different interneuron subtypes to inhibitory tone during cortical network activity is not well-understood. We previously showed that many of the major interneuron subtypes in mouse barrel cortex are highly active during Up states (Neske et al., 2015); while fast-spiking (FS), parvalbumin (PV)-positive cells were the most active interneuron subtype, many non-fast-spiking (NFS), PV-negative interneurons were as active or more active than neighboring pyramidal cells. This suggests that the NFS cells could play a role in maintaining or modulating Up states. Here, using optogenetic techniques, we further dissected the functional roles during Up states of two major NFS, PV-negative interneuron subtypes: somatostatin (SOM)-positive cells and vasoactive intestinal peptide (VIP)-positive cells. We found that while pyramidal cell excitability during Up states significantly increased when SOM cells were optogenetically silenced, VIP cells did not influence pyramidal cell excitability either upon optogenetic silencing or activation. VIP cells failed to contribute to Up states despite their ability to inhibit SOM cells strongly. We suggest that the contribution of VIP cells to the excitability of pyramidal cells may vary with cortical state.

The recurrent synaptic architecture of neocortex allows for self-generated network activity. One form of such activity is the Up state, in which neurons transiently receive barrages of excitatory and inhibitory synaptic inputs that depolarize many neurons to spike threshold before returning to a relatively quiescent Down state. The extent to which different cell types participate in Up states is still unclear. Inhibitory interneurons have particularly diverse intrinsic properties and synaptic connections with the local network, suggesting that different interneurons might play different roles in activated network states. We have studied the firing, subthreshold behavior, and synaptic conductances of identified cell types during Up and Down states in layers 5 and 2/3 in mouse barrel cortexin vitro. We recorded from pyramidal cells and interneurons expressing parvalbumin (PV), somatostatin (SOM), vasoactive intestinal peptide (VIP), or neuropeptide Y. PV cells were the most active interneuron subtype during the Up state, yet the other subtypes also received substantial synaptic conductances and often generated spikes. In all cell types except PV cells, the beginning of the Up state was dominated by synaptic inhibition, which decreased thereafter; excitation was more persistent, suggesting that inhibition is not the dominant force in terminating Up states. Compared with barrel cortex, SOM and VIP cells were much less active in entorhinal cortex during Up states. Our results provide a measure of functional connectivity of various neuron types in barrel cortex and suggest differential roles for interneuron types in the generation and control of persistent network activity.

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30–40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30–40 Hz was not effective in increasing exploration of novel images. Stimulation at 10–15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally.SIGNIFICANCE STATEMENTRecognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of the PER could increase or decrease exploration of novel and familiar images depending on the frequency of stimulation. Our findings suggest that optical stimulation of PER at specific frequencies can predictably alter recognition memory.

On Perceived Conceptual and Methodological Divergences in Linguistic Theory and Cognitive Science: Distributional Analyses, Universal Grammar, and Language Acquisition Authors Garrett Neske New York University PDF Article info Impact Citations Published at 24. March 2010 https://doi.org/10.5964/bioling.8761 Issue: Vol. 4 No. 1 (2010) Section: Briefs Keywords: language acquisition learning computational linguistics universal grammar development Share: Z PlumX Dimensions Views: Total Abstract PDF 10 7 3

The increasing sophistication of the tools and results of cellular and molecular neuroscience would appear to suggest that explanatory force in neuroscience is defined by reduction to molecular biology. This view, however, is mistaken in that it loses sight of the goal of neuroscience proper: the characterization of the information content of biophysical variables and the transformation of these variables that lead to behaviors. Neuroscience is thus distinguished from applied molecular and cellular biology by the notion of computation. In this commentary, I will show how the notion of computation in neuroscience differs from that of other fields that investigate complex systems and argue that computation at various levels of neural organization is the paramount goal of neuroscientific explanation and not the so-called reduction of “mind to molecules.” © 2009 Wiley Periodicals, Inc. Complexity, 16,10–19, 2010

The acquisition of the rule systems of natural language and the real-time parsing of linguistic data in the fully developed language faculty are phenomena that elicit different explanations from different researchers, largely depending on whether one appeals to an innate universal grammar or a general-purpose learning scheme. This divergence can arguably be traced back to the origins of Noam Chomsky's generative grammar (Chomsky, 1957) and its departure from the distributionalist research program of Zellig Harris (Harris, 1951). That is, not only did this divergence give rise to differing conceptions on what the analysis of linguistic structures should look like, with Chomsky focusing on the transformations mapping meaning from form and Harris focusing on the formation of structure from phonemic and morphemic primitives, but it also became manifested in the cognitive-science debate of innate expectations versus sufficiency of statistical learning in language acquisition and parsing. The positions in this debate, however, can be shown not to be mutually contradictory. In fact, each position needs the other to explain the development of a grammar in language acquisition. In the years prior to the publication of Chomsky (1957), the new field of information theory introduced a principled, mathematical description of coding and transmission over a noisy channel (Shannon, 1948), which, to Harris, and initially to Chomsky, seemed to bear on linguistic analysis. The aim of linguistic analysis from the distributionalist perspective, which predated the formal conception of information theory in the work of Bloomfield (Huck & Goldsmith, 1986), is to extract structure and constraints on linguistic representation from the distribution of formal objects such as phonemes. That is, the focus should be on the probability of occurrence of a particular object given the occurrence of another object. Shannon's notion of information content, termed entropy as analogous to statistical mechanics, provided a way to predict letters in a text given the previous letters (Shannon, 1951). While the linguistic applications of information-theoretic analysis have been used to great effect by computational and corpus linguists for parsing, machine translation, and other tasks, Harris imagined that an assignment of probability or information content to utterances could constitute an