Cortical dynamics by layers

The effects of acute and chronic noise trauma on stimulus-evoked activity across primary auditory cortex layers

Exposure to intense noise environments is a major cause of sensorineural hearing loss and auditory perception disorders, such as tinnitus and hyperacusis, which may have a central origin. The effects of noise-induced hearing loss on the auditory cortex have been documented in many studies. One limitation of these studies, however, is that the effects of noise trauma have been mostly studied at the granular layer (i.e, the main cortical recipient of thalamic input), while the cortex is a very complex structure, with six different layers each having its own pattern of connectivity and role in sensory processing. The present study aims to investigate the effects of acute and chronic noise trauma on the laminar pattern of stimulus-evoked activity in the primary auditory cortex of the anesthetized guinea pig. We show that acute and chronic noise trauma are both followed by an increase in stimulus-evoked cortical responses, mostly in the granular and supragranular layers. The cortical responses are more monotonic as a function of the intensity level after noise trauma. There was minimal change, if any, in local field potential (LFP) amplitude after acute noise trauma, while LFP amplitude was enhanced after chronic noise trauma. Finally, LFP and the current source density analysis suggest that acute but more specifically chronic noise trauma is associated with the emergence of a new sink in the supragranular layer. This result suggests that supragranular layers become a major input recipient. We discuss the possible mechanisms and functional implications of these changes.NEW & NOTEWORTHY Our study shows that cortical activity is enhanced after trauma and that the sequence of cortical column activation during stimulus-evoked response is altered, i.e. the supragranular layer becomes a major input recipient. We speculate that these large cortical changes may play a key role in the auditory hypersensitivity (hyperacusis) that can be triggered after noise trauma in human subjects.

Synaptic zinc potentiates AMPA receptor function in mouse auditory cortex

Synaptic zinc signaling modulates synaptic activity and is present in specific populations of cortical neurons, suggesting that synaptic zinc contributes to the diversity of intracortical synaptic microcircuits and their functional specificity. To understand the role of zinc signaling in the cortex, we performed whole-cell patch-clamp recordings from intratelencephalic (IT)-type neurons and pyramidal tract (PT)-type neurons in layer 5 of the mouse auditory cortex during optogenetic stimulation of specific classes of presynaptic neurons. Our results show that synaptic zinc potentiates AMPA receptor (AMPAR) function in a synapse-specific manner. We performed in vivo 2-photon calcium imaging of the same classes of neurons in awake mice and found that changes in synaptic zinc can widen or sharpen the sound-frequency tuning bandwidth of IT-type neurons but only widen the tuning bandwidth of PT-type neurons. These results provide evidence for synapse- and cell-type-specific actions of synaptic zinc in the cortex.

Understanding ethanol's acute effects on medial prefrontal cortex neural activity using state-space approaches

Acute ethanol (EtOH) intoxication results in several maladaptive behaviors that may be attributable, in part, to the effects of EtOH on neural activity in medial prefrontal cortex (mPFC). The acute effects of EtOH on mPFC function have been largely described as inhibitory. However, translating these observations on function into a mechanism capable of delineating acute EtOH's effects on behavior has proven difficult. This review highlights the role of acute EtOH on electrophysiological measurements of mPFC function and proposes that interpreting these changes through the lens of dynamical systems theory is critical to understand the mechanisms that mediate the effects of EtOH intoxication on behavior. Specifically, the present review posits that the effects of EtOH on mPFC N-methyl-d-aspartate (NMDA) receptors are critical for the expression of impaired behavior following EtOH consumption. This hypothesis is based on the observation that recurrent activity in cortical networks is supported by NMDA receptors, and, when disrupted, may lead to impairments in cognitive function. To evaluate this hypothesis, we discuss the representation of mPFC neural activity in low-dimensional, dynamic state spaces. This approach has proven useful for identifying the underlying computations necessary for the production of behavior. Ultimately, we hypothesize that EtOH-related alterations to NMDA receptor function produces alterations that can be effectively conceptualized as impairments in attractor dynamics and provides insight into how acute EtOH disrupts forms of cognition that rely on mPFC function. This article is part of the special Issue on 'Neurocircuitry Modulating Drug and Alcohol Abuse'.

An Indexing Theory for Working Memory Based on Fast Hebbian Plasticity

Working memory (WM) is a key component of human memory and cognition. Computational models have been used to study the underlying neural mechanisms, but neglected the important role of short-term memory (STM) and long-term memory (LTM) interactions for WM. Here, we investigate these using a novel multiarea spiking neural network model of prefrontal cortex (PFC) and two parietotemporal cortical areas based on macaque data. We propose a WM indexing theory that explains how PFC could associate, maintain, and update multimodal LTM representations. Our simulations demonstrate how simultaneous, brief multimodal memory cues could build a temporary joint memory representation as an “index” in PFC by means of fast Hebbian synaptic plasticity. This index can then reactivate spontaneously and thereby also the associated LTM representations. Cueing one LTM item rapidly pattern completes the associated uncued item via PFC. The PFC–STM network updates flexibly as new stimuli arrive, thereby gradually overwriting older representations.

Traumatic Brain Injury and Neuronal Functionality Changes in Sensory Cortex

Traumatic brain injury (TBI), caused by direct blows to the head or inertial forces during relative head-brain movement, can result in long-lasting cognitive and motor deficits which can be particularly consequential when they occur in young people with a long life ahead. Much is known of the molecular and anatomical changes produced in TBI but much less is known of the consequences of these changes to neuronal functionality, especially in the cortex. Given that much of our interior and exterior lives are dependent on responsiveness to information from and about the world around us, we have hypothesized that a significant contributor to the cognitive and motor deficits seen after TBI could be changes in sensory processing. To explore this hypothesis, and to develop a model test system of the changes in neuronal functionality caused by TBI, we have examined neuronal encoding of simple and complex sensory input in the rat’s exploratory and discriminative tactile system, the large face macrovibrissae, which feeds to the so-called “barrel cortex” of somatosensory cortex. In this review we describe the short-term and long-term changes in the barrel cortex encoding of whisker motion modeling naturalistic whisker movement undertaken by rats engaged in a variety of tasks. We demonstrate that the most common form of TBI results in persistent neuronal hyperexcitation specifically in the upper cortical layers, likely due to changes in inhibition. We describe the types of cortical inhibitory neurons and their roles and how selective effects on some of these could produce the particular forms of neuronal encoding changes described in TBI, and then generalize to compare the effects on inhibition seen in other forms of brain injury. From these findings we make specific predictions as to how non-invasive extra-cranial electrophysiology can be used to provide the high-precision information needed to monitor and understand the temporal evolution of changes in neuronal functionality in humans suffering TBI. Such detailed understanding of the specific changes in an individual patient’s cortex can allow for treatment to be tailored to the neuronal changes in that particular patient’s brain in TBI, a precision that is currently unavailable with any technique.

Layer-specific interhemispheric functional connectivity in the somatosensory cortex of rats: resting state electrophysiology and fMRI studies

The spontaneous cerebral hemodynamic fluctuations observed during the resting state have been frequently visualized using functional magnetic resonance imaging (rsfMRI). However, the neuronal populations and neuroelectric characteristics underlying the functional connectivity of cerebrohemodynamic activities are poorly understood. We investigated the characteristics of bi-hemispheric functional connectivity via electrophysiology and rsfMRI in the primary sensory cortex of rats anesthetized by α-chloralose. Unlike the evoked responses, the spontaneous electrophysiological activity was concentrated in the infragranular layers and could be classified into subtypes with distinctive current sources and sinks. Both neuroelectric and rsfMRI signals were interhemispherically correlated in a layer-specific manner, suggesting that there are independent neural inputs to infragranular and granular/supragranular layers. The majority of spontaneous electrophysiological activities were bilaterally paired with delays of up to ~50 ms between each pair. The variable interhemispheric delay implies the involvement of indirect, multi-neural pathways. Our findings demonstrated the diverse activity patterns of layer-specific electrophysiological substrates and suggest the recruitment of multiple, non-specific brain regions in construction of interhemispheric functional connectivity.

Monosynaptic functional connectivity in cerebral cortex during wakefulness and under graded levels of anesthesia

The balance between excitation and inhibition is considered to be of significant importance for neural computation and cognitive function. Excitatory and inhibitory functional connectivity in intact cortical neuronal networks in wakefulness and graded levels of anesthesia has not been systematically investigated. We compared monosynaptic excitatory and inhibitory spike transmission probabilities using pairwise cross-correlogram (CCG) analysis. Spikes were measured at 64 sites in the visual cortex of rats with chronically implanted microelectrode arrays during wakefulness and three levels of anesthesia produced by desflurane. Anesthesia decreased the number of active units, the number of functional connections, and the strength of excitatory connections. Connection probability (number of connections per number of active unit pairs) was unaffected until the deepest anesthesia level, at which a significant increase in the excitatory to inhibitory ratio of connection probabilities was observed. The results suggest that the excitatory–inhibitory balance is altered at an anesthetic depth associated with unconsciousness.

Differential functional constraints on the evolution of postsynaptic density proteins in neocortical laminae

The postsynaptic density (PSD) is a protein dense complex on the postsynaptic membrane of excitatory synapses that is implicated in normal nervous system functions such as synaptic plasticity, and also contains an enrichment of proteins involved in neuropsychiatric disorders. It has recently been reported that the genes encoding PSD proteins evolved more slowly than other genes in the human brain, but the underlying evolutionary advantage for this is not clear. Here, we show that cortical gene expression levels could explain most of this effect, indicating that expression level is a primary contributor to the evolution of these genes in the brain. Furthermore, we identify a positive correlation between the expression of PSD genes and cortical layers, with PSD genes being more highly expressed in deep layers, likely as a result of layer-enriched transcription factors. As the cortical layers of the mammalian brain have distinct functions and anatomical projections, our results indicate that the emergence of the unique six-layered mammalian cortex may have provided differential functional constraints on the evolution of PSD genes. More superficial cortical layers contain PSD genes with less constraint and these layers are primarily involved in intracortical projections, connections that may be particularly important for evolved cognitive functions. Therefore, the differential expression and evolutionary constraint of PSD genes in neocortical laminae may be critical not only for neocortical architecture but the cognitive functions that are dependent on this structure.

Synergistic Coding by Cortical Neural Ensembles

An essential step towards understanding how the brain orchestrates information processing at the cellular and population levels is to simultaneously observe the spiking activity of cortical neurons that mediate perception, learning, and motor processing. In this paper, we formulate an information theoretic approach to determine whether cooperation among neurons may constitute a governing mechanism of information processing when encoding external covariates. Specifically, we show that conditional independence between neuronal outputs may not provide an optimal encoding strategy when the firing probability of a neuron depends on the history of firing of other neurons connected to it. Rather, cooperation among neurons can provide a "message-passing" mechanism that preserves most of the information in the covariates under specific constraints governing their connectivity structure. Using a biologically plausible statistical learning model, we demonstrate the performance of the proposed approach in synergistically encoding a motor task using a subset of neurons drawn randomly from a large population. We demonstrate its superiority in approximating the joint density of the population from limited data compared to a statistically independent model and a maximum entropy (MaxEnt) model.