Dendritic calcium spikes are clearly detectable at the cortical surface

Fabrication of micro-wire stent electrode as a minimally invasive endovascular neural interface for vascular electrocorticography using laser ablation method

Objective. Minimally invasive endovascular stent electrode is a currently emerging technology in neural engineering with minimal damage to the neural tissue. However, the typical stent electrode still requires resistive welding and is relatively large, limiting its application mainly on the large animal or thick vessels. In this study, we investigated the feasibility of laser ablation of micro-wire stent electrode with a diameter as small as 25μmand verified it in the superior sagittal sinus (SSS) of a rat.Approach. We have developed a laser ablation technology to expose the electrode sites of the micro-wire on both sides without damaging the wire itself. During laser ablation, we applied a new method to fix and realign the micro-wires. The micro-wire stent electrode was fabricated by carefully assemble the micro-wire and stent. We tested the electrochemical performances of the electrodes as a neural interface. Finally, we deployed the stent electrode in a rat to verified the feasibility.Main result. Based on the proposed micro-wire stent electrode, we demonstrated that the stent electrode could be successfully deployed in a rat. With the benefit of the smaller design and laser fabrication technology, it can be fitted into a catheter with an inner diameter of 0.6mm. The vascular electrocorticography can be detected during the acute recording, making it promising in the application of small animals and thin vessels.Significance. The method we proposed combines the advantages of endovascular micro-wire electrode and stent, helping make the electrodes smaller. This study provided an alternative method for deploying micro-wire electrodes into thinner vessels as an endovascular neural interface.

Touch-evoked traveling waves establish a translaminar spacetime code

Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked traveling waves and underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a late wave that lasted hundreds of milliseconds poststimulus. Notably, late waves were modulated by perceived value and predicted behavioral choice in a two-whisker discrimination task. We found that the late wave feature was (i) modulated by motor feedback, (ii) differentially engaged a sparse ensemble reactivation pattern across layer 2/3, which a balanced-state network model reconciled via feedback-induced inhibitory stabilization, and (iii) aligned to regenerative layer 5 apical dendritic Ca2+ events. Our results reveal that translaminar spacetime patterns organized by cortical feedback support sparse touch-evoked traveling waves.

Filtered Point Processes Tractably Capture Rhythmic And Broadband Power Spectral Structure in Neural Electrophysiological Recordings

Neural electrophysiological recordings arise from interacting rhythmic (oscillatory) and broadband (aperiodic) biological subprocesses. Both rhythmic and broadband processes contribute to the neural power spectrum, which decomposes the variance of a neural recording across frequencies. Although an extensive body of literature has successfully studied rhythms in various diseases and brain states, researchers only recently have systematically studied the characteristics of broadband effects in the power spectrum. Broadband effects can generally be categorized as 1) shifts in power across all frequencies, which correlate with changes in local firing rates and 2) changes in the overall shape of the power spectrum, such as the spectral slope or power law exponent. Shape changes are evident in various conditions and brain states, influenced by factors such as excitation to inhibition balance, age, and various diseases. It is increasingly recognized that broadband and rhythmic effects can interact on a sub-second timescale. For example, broadband power is time-locked to the phase of <1 Hz rhythms in propofol induced unconsciousness. Modeling tools that explicitly deal with both rhythmic and broadband contributors to the power spectrum and that capture their interactions are essential to help improve the interpretability of power spectral effects. Here, we introduce a tractable stochastic forward modeling framework designed to capture both narrowband and broadband spectral effects when prior knowledge or theory about the primary biophysical processes involved is available. Population-level neural recordings are modeled as the sum of filtered point processes (FPPs), each representing the contribution of a different biophysical process such as action potentials or postsynaptic potentials of different types. Our approach builds on prior neuroscience FPP work by allowing multiple interacting processes and time-varying firing rates and by deriving theoretical power spectra and cross-spectra. We demonstrate several properties of the models, including that they divide the power spectrum into frequency ranges dominated by rhythmic and broadband effects, and that they can capture spectral effects across multiple timescales, including sub-second cross-frequency coupling. The framework can be used to interpret empirically observed power spectra and cross-frequency coupling effects in biophysical terms, which bridges the gap between theoretical models and experimental results.

Differential neural mechanisms underlie cortical gating of visual spatial attention mediated by alpha-band oscillations

Selective attention relies on neural mechanisms that facilitate processing of behaviorally relevant sensory information while suppressing irrelevant information, consistently linked to alpha-band oscillations in human M/EEG studies. We analyzed cortical alpha responses from intracranial electrodes implanted in eight epilepsy patients, who performed a visual spatial attention task. Electrocorticographic data revealed a spatiotemporal dissociation between attention-modulated alpha desynchronization, associated with the enhancement of sensory processing, and alpha synchronization, associated with the suppression of sensory processing, during the cue-target interval. Dorsal intraparietal areas contralateral to the attended hemifield primarily exhibited a delayed and sustained alpha desynchronization, while ventrolateral extrastriatal areas ipsilateral to the attended hemifield primarily exhibited an earlier and sustained alpha synchronization. Analyses of cross-frequency coupling between alpha phase and broadband high-frequency activity (HFA) further revealed cross-frequency interactions along the visual hierarchy contralateral to the attended locations. Directionality analyses indicate that alpha phase in early and extrastriatal visual areas modulated HFA power in downstream visual areas, thus potentially facilitating the feedforward processing of an upcoming, spatially predictable target. In contrast, in areas ipsilateral to the attended locations, HFA power modulated local alpha phase in early and extrastriatal visual areas, with suppressed interareal interactions, potentially attenuating the processing of distractors. Our findings reveal divergent alpha-mediated neural mechanisms underlying target enhancement and distractor suppression during the deployment of spatial attention, reflecting enhanced functional connectivity at attended locations, while suppressed functional connectivity at unattended locations. The collective dynamics of these alpha-mediated neural mechanisms play complementary roles in the efficient gating of sensory information.

Effect of Electrode Distance and Size on Electrocorticographic Recordings in Human Sensorimotor Cortex

Subdural electrocorticography (ECoG) is a valuable technique for neuroscientific research and for emerging neurotechnological clinical applications. As ECoG grids accommodate increasing numbers of electrodes and higher densities with new manufacturing methods, the question arises at what point the benefit of higher density ECoG is outweighed by spatial oversampling. To clarify the optimal spacing between ECoG electrodes, in the current study we evaluate how ECoG grid density relates to the amount of non-shared neurophysiological information between electrode pairs, focusing on the sensorimotor cortex. We simultaneously recorded high-density (HD, 3 mm pitch) and ultra-high-density (UHD, 0.9 mm pitch) ECoG, obtained intraoperatively from six participants. We developed a new metric, the normalized differential root mean square (ndRMS), to quantify the information that is not shared between electrode pairs. The ndRMS increases with inter-electrode center-to-center distance up to 15 mm, after which it plateaus. We observed differences in ndRMS between frequency bands, which we interpret in terms of oscillations in frequencies below 32 Hz with phase differences between pairs, versus (un)correlated signal fluctuations in the frequency range above 64 Hz. The finding that UHD recordings yield significantly higher ndRMS than HD recordings is attributed to the amount of tissue sampled by each electrode. These results suggest that ECoG densities with submillimeter electrode distances are likely justified.

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation

Objective.Micro-electrocorticographic (μECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to useμECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach. μECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results.Single-unit spikes could be extracted during chronic recording fromμECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively.Significance. μECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

Dysfunctions of cellular context-sensitivity in neurodevelopmental learning disabilities

Pyramidal neurons have a pivotal role in the cognitive capabilities of neocortex. Though they have been predominantly modeled as integrate-and-fire point processors, many of them have another point of input integration in their apical dendrites that is central to mechanisms endowing them with the sensitivity to context that underlies basic cognitive capabilities. Here we review evidence implicating impairments of those mechanisms in three major neurodevelopmental disabilities, fragile X, Down syndrome, and fetal alcohol spectrum disorders. Multiple dysfunctions of the mechanisms by which pyramidal cells are sensitive to context are found to be implicated in all three syndromes. Further deciphering of these cellular mechanisms would lead to the understanding of and therapies for learning disabilities beyond any that are currently available.

High-speed optical imaging with sCMOS pixel reassignment

Fluorescence microscopy has undergone rapid advancements, offering unprecedented visualization of biological events and shedding light on the intricate mechanisms governing living organisms. However, the exploration of rapid biological dynamics still poses a significant challenge due to the limitations of current digital camera architectures and the inherent compromise between imaging speed and other capabilities. Here, we introduce sHAPR, a high-speed acquisition technique that leverages the operating principles of sCMOS cameras to capture fast cellular and subcellular processes. sHAPR harnesses custom fiber optics to convert microscopy images into one-dimensional recordings, enabling acquisition at the maximum camera readout rate, typically between 25 and 250 kHz. We have demonstrated the utility of sHAPR with a variety of phantom and dynamic systems, including high-throughput flow cytometry, cardiomyocyte contraction, and neuronal calcium waves, using a standard epi-fluorescence microscope. sHAPR is highly adaptable and can be integrated into existing microscopy systems without requiring extensive platform modifications. This method pushes the boundaries of current fluorescence imaging capabilities, opening up new avenues for investigating high-speed biological phenomena.

An integrative, multiscale view on neural theories of consciousness

How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other. Instead, several of them may converge on fundamental neuronal mechanisms and be partly compatible and complementary, so that multiple theories can simultaneously contribute to our understanding. Here, we consider unifying, integration-oriented approaches that have so far been largely neglected, seeking to combine valuable elements from various theories.

A Translaminar Spacetime Code Supports Touch-Evoked Traveling Waves

Linking sensory-evoked traveling waves to underlying circuit patterns is critical to understanding the neural basis of sensory perception. To form this link, we performed simultaneous electrophysiology and two-photon calcium imaging through transparent NeuroGrids and mapped touch-evoked cortical traveling waves and their underlying microcircuit dynamics. In awake mice, both passive and active whisker touch elicited traveling waves within and across barrels, with a fast early component followed by a variable late wave that lasted hundreds of milliseconds post-stimulus. Strikingly, late-wave dynamics were modulated by stimulus value and correlated with task performance. Mechanistically, the late wave component was i) modulated by motor feedback, ii) complemented by a sparse ensemble pattern across layer 2/3, which a balanced-state network model reconciled via inhibitory stabilization, and iii) aligned to regenerative Layer-5 apical dendritic Ca 2+ events. Our results reveal a translaminar spacetime pattern organized by cortical feedback in the sensory cortex that supports touch-evoked traveling waves.

GRAPHICAL ABSTRACT AND HIGHLIGHTS

Whisker touch evokes both early- and late-traveling waves in the barrel cortex over 100's of millisecondsReward reinforcement modulates wave dynamics Late wave emergence coincides with network sparsity in L23 and time-locked L5 dendritic Ca 2+ spikes Experimental and computational results link motor feedback to distinct translaminar spacetime patterns.

Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response. Individualized biophysical models were built to achieve selective engagement of two target bundles: either the forceps minor (FM) or cingulum bundle (CB). Unilateral 2 Hz stimulation was performed in seven patients with treatment-resistant depression who responded to SCC DBS, and EPs were recorded using 256-sensor scalp electroencephalography. Two distinct EPs were observed: a 120 ms symmetric response spanning both hemispheres and a 60 ms asymmetrical EP. Activation of FM correlated with the symmetrical EPs, while activation of CB was correlated with the asymmetrical EPs. These results support prior model predictions that these two pathways are predominantly activated by clinical SCC DBS and provide first evidence of a link between cortical EPs and selective fiber bundle activation.

A neurophysiological basis for aperiodic EEG and the background spectral trend

Electroencephalograms (EEGs) display a mixture of rhythmic and broadband fluctuations, the latter manifesting as an apparent 1/f spectral trend. While network oscillations are known to generate rhythmic EEG, the neural basis of broadband EEG remains unexplained. Here, we use biophysical modelling to show that aperiodic neural activity can generate detectable scalp potentials and shape broadband EEG features, but that these aperiodic signals do not significantly perturb brain rhythm quantification. Further model analysis demonstrated that rhythmic EEG signals are profoundly corrupted by shifts in synapse properties. To examine this scenario, we recorded EEGs of human subjects being administered propofol, a general anesthetic and GABA receptor agonist. Drug administration caused broadband EEG changes that quantitatively matched propofol's known effects on GABA receptors. We used our model to correct for these confounding broadband changes, which revealed that delta power, uniquely, increased within seconds of individuals losing consciousness. Altogether, this work details how EEG signals are shaped by neurophysiological factors other than brain rhythms and elucidates how these signals can undermine traditional EEG interpretation.

NADOL: Neuromorphic Architecture for Spike-Driven Online Learning by Dendrites

Biologically plausible learning with neuronal dendrites is a promising perspective to improve the spike-driven learning capability by introducing dendritic processing as an additional hyperparameter. Neuromorphic computing is an effective and essential solution towards spike-based machine intelligence and neural learning systems. However, on-line learning capability for neuromorphic models is still an open challenge. In this study a novel neuromorphic architecture with dendritic on-line learning (NADOL) is presented, which is a novel efficient methodology for brain-inspired intelligence on embedded hardware. With the feature of distributed processing using spiking neural network, NADOL can cut down the power consumption and enhance the learning efficiency and convergence speed. A detailed analysis for NADOL is presented, which demonstrates the effects of different conditions on learning capabilities, including neuron number in hidden layer, dendritic segregation parameters, feedback connection, and connection sparseness with various levels of amplification. Piecewise linear approximation approach is used to cut down the computational resource cost. The experimental results demonstrate a remarkable learning capability that surpasses other solutions, with NADOL exhibiting superior performance over the GPU platform in dendritic learning. This study's applicability extends across diverse domains, including the Internet of Things, robotic control, and brain-machine interfaces. Moreover, it signifies a pivotal step in bridging the gap between artificial intelligence and neuroscience through the introduction of an innovative neuromorphic paradigm.

Latent neural dynamics encode temporal context in speech

Direct neural recordings from human auditory cortex have demonstrated encoding for acoustic-phonetic features of consonants and vowels. Neural responses also encode distinct acoustic amplitude cues related to timing, such as those that occur at the onset of a sentence after a silent period or the onset of the vowel in each syllable. Here, we used a group reduced rank regression model to show that distributed cortical responses support a low-dimensional latent state representation of temporal context in speech. The timing cues each capture more unique variance than all other phonetic features and exhibit rotational or cyclical dynamics in latent space from activity that is widespread over the superior temporal gyrus. We propose that these spatially distributed timing signals could serve to provide temporal context for, and possibly bind across time, the concurrent processing of individual phonetic features, to compose higher-order phonological (e.g. word-level) representations.

Transient Oscillations of Neural Firing Rate Associated With Routing of Evidence in a Perceptual Decision

To form a perceptual decision, the brain must acquire samples of evidence from the environment and incorporate them in computations that mediate choice behavior. While much is known about the neural circuits that process sensory information and those that form decisions, less is known about the mechanisms that establish the functional linkage between them. We trained monkeys of both sexes to make difficult decisions about the net direction of visual motion under conditions that required trial-by-trial control of functional connectivity. In one condition, the motion appeared at different locations on different trials. In the other, two motion patches appeared, only one of which was informative. Neurons in the parietal cortex produced brief oscillations in their firing rate at the time routing was established: upon onset of the motion display when its location was unpredictable across trials, and upon onset of an attention cue that indicated in which of two locations an informative patch of dots would appear. The oscillation was absent when the stimulus location was fixed across trials. We interpret the oscillation as a manifestation of the mechanism that establishes the source and destination of flexibly routed information, but not the transmission of the information per se Significance Statement It has often been suggested that oscillations in neural activity might serve a role in routing information appropriately. We observe an oscillation in neural firing rate in the lateral intraparietal area consistent with such a role. The oscillations are transient. They coincide with the establishment of routing, but they do not appear to play a role in the transmission (or conveyance) of the routed information itself.

Relative Contributions of Different Neural Sources to the EEG

Dogma dictates that the EEG signal is generated by postsynaptic currents (PSCs) because there are an enormous number of synapses in the brain, and PSCs have relatively long durations. However, PSCs are not the only potential source of electric fields in the brain. Action potentials, afterpolarizations, and presynaptic activity can also generate electric fields. Experimentally it is exceedingly difficult to delineate the contributions of different sources because they are casually linked. However, using computational modeling, we can interrogate the relative contributions of different neural elements to the EEG. We used a library of neuron models with morphologically realistic axonal arbors to quantify the relative contributions of PSCs, action potentials, and presynaptic activity to the EEG signal. Consistent with prior assertions, PSCs were the largest contributor to the EEG, but action potentials and afterpolarizations can also make appreciable contributions. For a population of neurons generating simultaneous PSCs and action potentials, we found that the action potentials accounted for up to 20% of the source strength while PSCs accounted for the other 80% and presynaptic activity negligibly contributed. Additionally, L5 PCs generated the largest PSC and action potential signals indicating that they the dominant EEG signal generator. Further, action potentials and afterpolarizations were sufficient to generate physiological oscillations, indicating that they are valid source contributors to the EEG. The EEG emerges from a combination of multiple different source, and, while PSCs are the largest contributor, other sources are non-negligible and should be included in modeling, analysis and interpretation of the EEG.

Transparent neural interfaces: challenges and solutions of microengineered multimodal implants designed to measure intact neuronal populations using high-resolution electrophysiology and microscopy simultaneously

The aim of this review is to present a comprehensive overview of the feasibility of using transparent neural interfaces in multimodal in vivo experiments on the central nervous system. Multimodal electrophysiological and neuroimaging approaches hold great potential for revealing the anatomical and functional connectivity of neuronal ensembles in the intact brain. Multimodal approaches are less time-consuming and require fewer experimental animals as researchers obtain denser, complex data during the combined experiments. Creating devices that provide high-resolution, artifact-free neural recordings while facilitating the interrogation or stimulation of underlying anatomical features is currently one of the greatest challenges in the field of neuroengineering. There are numerous articles highlighting the trade-offs between the design and development of transparent neural interfaces; however, a comprehensive overview of the efforts in material science and technology has not been reported. Our present work fills this gap in knowledge by introducing the latest micro- and nanoengineered solutions for fabricating substrate and conductive components. Here, the limitations and improvements in electrical, optical, and mechanical properties, the stability and longevity of the integrated features, and biocompatibility during in vivo use are discussed.

Ketamine triggers a switch in excitatory neuronal activity across neocortex

The brain can become transiently disconnected from the environment while maintaining vivid, internally generated experiences. This so-called 'dissociated state' can occur in pathological conditions and under the influence of psychedelics or the anesthetic ketamine (KET). The cellular and circuit mechanisms producing the dissociative state remain poorly understood. We show in mice that KET causes spontaneously active neurons to become suppressed while previously silent neurons become spontaneously activated. This switch occurs in all cortical layers and different cortical regions, is induced by both systemic and cortical application of KET and is mediated by suppression of parvalbumin and somatostatin interneuron activity and inhibition of NMDA receptors and HCN channels. Combined, our results reveal two largely non-overlapping cortical neuronal populations-one engaged in wakefulness, the other contributing to the KET-induced brain state-and may lay the foundation for understanding how the brain might become disconnected from the surrounding environment while maintaining internal subjective experiences.

Resolving the mesoscopic missing link: Biophysical modeling of EEG from cortical columns in primates

Event-related potentials (ERP) are among the most widely measured indices for studying human cognition. While their timing and magnitude provide valuable insights, their usefulness is limited by our understanding of their neural generators at the circuit level. Inverse source localization offers insights into such generators, but their solutions are not unique. To address this problem, scientists have assumed the source space generating such signals comprises a set of discrete equivalent current dipoles, representing the activity of small cortical regions. Based on this notion, theoretical studies have employed forward modeling of scalp potentials to understand how changes in circuit-level dynamics translate into macroscopic ERPs. However, experimental validation is lacking because it requires in vivo measurements of intracranial brain sources. Laminar local field potentials (LFP) offer a mechanism for estimating intracranial current sources. Yet, a theoretical link between LFPs and intracranial brain sources is missing. Here, we present a forward modeling approach for estimating mesoscopic intracranial brain sources from LFPs and predict their contribution to macroscopic ERPs. We evaluate the accuracy of this LFP-based representation of brain sources utilizing synthetic laminar neurophysiological measurements and then demonstrate the power of the approach in vivo to clarify the source of a representative cognitive ERP component. To that end, LFP was measured across the cortical layers of visual area V4 in macaque monkeys performing an attention demanding task. We show that area V4 generates dipoles through layer-specific transsynaptic currents that biophysically recapitulate the ERP component through the detailed forward modeling. The constraints imposed on EEG production by this method also revealed an important dissociation between computational and biophysical contributors. As such, this approach represents an important bridge between laminar microcircuitry, through the mesoscopic activity of cortical columns to the patterns of EEG we measure at the scalp.

Columnar Localization and Laminar Origin of Cortical Surface Electrical Potentials

Electrocorticography (ECoG) methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. To address this gap, we recorded from rat auditory cortex using customized μECoG, and simulated cortical surface electrical potentials with a full-scale, biophysically detailed cortical column model. Experimentally, μECoG-derived auditory representations were tonotopically organized and signals were anisotropically localized to less than or equal to ±200 μm, that is, a single cortical column. Biophysical simulations reproduce experimental findings and indicate that neurons in cortical layers V and VI contribute ∼85% of evoked high-gamma signal recorded at the surface. Cell number and synchrony were the primary biophysical properties determining laminar contributions to evoked μECoG signals, whereas distance was only a minimal factor. Thus, evoked μECoG signals primarily originate from neurons in the infragranular layers of a single cortical column.SIGNIFICANCE STATEMENT ECoG methodologically bridges basic neuroscience and understanding of human brains in health and disease. However, the localization of ECoG signals across the surface of the brain and the spatial distribution of their generating neuronal sources are poorly understood. We investigated the localization and origins of sensory-evoked ECoG responses. We experimentally found that ECoG responses were anisotropically localized to a cortical column. Biophysically detailed simulations revealed that neurons in layers V and VI were the primary sources of evoked ECoG responses. These results indicate that evoked ECoG high-gamma responses are primarily generated by the population spike rate of pyramidal neurons in layers V and VI of single cortical columns and highlight the possibility of understanding how microscopic sources produce mesoscale signals.

Alpha and broadband high-frequency activity track task dynamics and predict performance in controlled decision-making

Intracranial recordings in human subjects provide a unique, fine-grained temporal and spatial resolution inaccessible to conventional non-invasive methods. A prominent signal in these recordings is broadband high-frequency activity (approx. 70-150 Hz), generally considered to reflect neuronal excitation. Here we explored the use of this broadband signal to track, on a single-trial basis, the temporal and spatial distribution of task-engaged areas involved in decision-making. We additionally focused on the alpha rhythm (8-14 Hz), thought to regulate the (dis)engagement of neuronal populations based on task demands. Using these signals, we characterized activity across cortex using intracranial recordings in patients with intractable epilepsy performing the Multi-Source Interference Task, a Stroop-like decision-making paradigm. We analyzed recordings both from grid electrodes placed over cortical areas including frontotemporal and parietal cortex, and depth electrodes in prefrontal regions, including cingulate cortex. We found a widespread negative relationship between alpha power and broadband activity, substantiating the gating role of alpha in regions beyond sensory/motor cortex. Combined, these signals reflect the spatio-temporal pattern of task-engagement, with alpha decrease signifying task-involved regions and broadband increase temporally locking to specific task aspects, distributed over cortical sites. We report sites that only respond to stimulus presentation or to the decision report and, interestingly, sites that reflect the time-on-task. The latter predict the subject's reaction times on a trial-by-trial basis. A smaller subset of sites showed modulation with task condition. Taken together, alpha and broadband signals allow tracking of neuronal population dynamics across cortex on a fine temporal and spatial scale.

Emergence of stochastic resonance in a two-compartment hippocampal pyramidal neuron model

In vitro studies have shown that hippocampal pyramidal neurons employ a mechanism similar to stochastic resonance (SR) to enhance the detection and transmission of weak stimuli generated at distal synapses. To support the experimental findings from the perspective of multicompartment model analysis, this paper aimed to elucidate the phenomenon of SR in a noisy two-compartment hippocampal pyramidal neuron model, which was a variant of the Pinsky-Rinzel neuron model with smooth activation functions and a hyperpolarization-activated cation current. With a bifurcation analysis of the model, we demonstrated the underlying dynamical structure responsible for the occurrence of SR. Furthermore, using a stochastically generated biphasic pulse train and broadband noise generated by the Orenstein-Uhlenbeck process as noise perturbation, both SR and suprathreshold SR were observed and quantified. Spectral analysis revealed that the distribution of spectral power under noise perturbations, in addition to inherent neurodynamics, is the main factor affecting SR behavior. The research results suggested that noise enhances the transmission of weak stimuli associated with elongated dendritic structures of hippocampal pyramidal neurons, thereby providing support for related laboratory findings.

Long anisotropic absolute refractory periods with rapid rise times to reliable responsiveness

Refractoriness is a fundamental property of excitable elements, such as neurons, indicating the probability for re-excitation in a given time lag, and is typically linked to the neuronal hyperpolarization following an evoked spike. Here we measured the refractory periods (RPs) in neuronal cultures and observed that an average anisotropic absolute RP could exceed 10 ms and its tail is 20 ms, independent of a large stimulation frequency range. It is an order of magnitude longer than anticipated and comparable with the decaying membrane potential time scale. It is followed by a sharp rise-time (relative RP) of merely ∼1 md to complete responsiveness. Extracellular stimulations result in longer absolute RPs than solely intracellular ones, and a pair of extracellular stimulations from two different routes exhibits distinct absolute RPs, depending on their order. Our results indicate that a neuron is an accurate excitable element, where the diverse RPs cannot be attributed solely to the soma and imply fast mutual interactions between different stimulation routes and dendrites. Further elucidation of neuronal computational capabilities and their interplay with adaptation mechanisms is warranted.

Double-μPeriscope, a tool for multilayer optical recordings, optogenetic stimulations or both

Intelligent behavior and cognitive functions in mammals depend on cortical microcircuits made up of a variety of excitatory and inhibitory cells that form a forest-like complex across six layers. Mechanistic understanding of cortical microcircuits requires both manipulation and monitoring of multiple layers and interactions between them. However, existing techniques are limited as to simultaneous monitoring and stimulation at different depths without damaging a large volume of cortical tissue. Here, we present a relatively simple and versatile method for delivering light to any two cortical layers simultaneously. The method uses a tiny optical probe consisting of two microprisms mounted on a single shaft. We demonstrate the versatility of the probe in three sets of experiments: first, two distinct cortical layers were optogenetically and independently manipulated; second, one layer was stimulated while the activity of another layer was monitored; third, the activity of thalamic axons distributed in two distinct cortical layers was simultaneously monitored in awake mice. Its simple-design, versatility, small-size, and low-cost allow the probe to be applied widely to address important biological questions.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

Decoding of cortex-wide brain activity from local recordings of neural potentials

Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain-computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions.Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings.Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials.Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

Dendritic Branch-constrained N-Methyl-d-Aspartate Receptor-mediated Spikes Drive Synaptic Plasticity in Hippocampal CA3 Pyramidal Cells

N-methyl-d-aspartate receptor-mediated ( spikes can be causally linked to the induction of synaptic long-term potentiation (LTP) in hippocampal and cortical pyramidal cells. However, it is unclear if they regulate plasticity at a local or global scale in the dendritic tree. Here, we used dendritic patch-clamp recordings and calcium imaging to investigate the integrative properties of single dendrites of hippocampal CA3 cells. We show that local hyperpolarization of a single dendritic segment prevents NMDA spikes, their associated calcium transients, as well as LTP in a branch-specific manner. This result provides direct, causal evidence that the single dendritic branch can operate as a functional unit in regulating CA3 pyramidal cell plasticity.

Broadening the definition of a nervous system to better understand the evolution of plants and animals

Most textbook definitions recognize only animals as having nervous systems. However, for the past couple decades, botanists have been meticulously studying long-distance signaling systems in plants, and some researchers have stated that plants have a simple nervous system. Thus, an academic conflict has emerged between those who defend and those who deny the existence of a nervous system in plants. This article analyses that debate, and we propose an alternative to answering yes or no: broadening the definition of a nervous system to include plants. We claim that a definition broader than the current one, which is based only on a phylogenetic viewpoint, would be helpful in obtaining a deeper understanding of how evolution has driven the features of signal generation, transmission and processing in multicellular beings. Also, we propose two possible definitions and exemplify how broader a definition allows for new viewpoints on the evolution of plants, animals and the nervous system.

Characteristic changes in EEG spectral powers of patients with opioid-use disorder as compared with those with methamphetamine- and alcohol-use disorders

Electroencephalography (EEG) likely reflects activity of cortical neurocircuits, making it an insightful estimation for mental health in patients with substance use disorder (SUD). EEG signals are recorded as sinusoidal waves, containing spectral amplitudes across several frequency bands with high spatio-temporal resolution. Prior work on EEG signal analysis has been made mainly at individual electrodes. These signals can be evaluated from advanced aspects, including sub-regional and hemispheric analyses. Due to limitation of computational techniques, few studies in earlier work could conduct data analyses from these aspects. Therefore, EEG in patients with SUD is not fully understood. In the present retrospective study, spectral powers from a data house containing opioid (OUD), methamphetamine/stimulants (MUD), and alcohol use disorder (AUD) were extracted, and then converted into five distinct topographic data (i.e., electrode-based, cortical subregion-based, left-right hemispheric, anterior-posterior based, and total cortex-based analyses). We found that data conversion and reorganization in the topographic way had an impact on EEG spectral powers in patients with OUD significantly different from those with MUD or AUD. Differential changes were observed from multiple perspectives, including individual electrodes, subregions, hemispheres, anterior-posterior cortices, and across the cortex as a whole. Understanding the differential changes in EEG signals may be useful for future work with machine learning and artificial intelligence (AI), not only for diagnostic but also for prognostic purposes in patients with SUD.

Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.

Microscale Physiological Events on the Human Cortical Surface

Despite ongoing advances in our understanding of local single-cellular and network-level activity of neuronal populations in the human brain, extraordinarily little is known about their "intermediate" microscale local circuit dynamics. Here, we utilized ultra-high-density microelectrode arrays and a rare opportunity to perform intracranial recordings across multiple cortical areas in human participants to discover three distinct classes of cortical activity that are not locked to ongoing natural brain rhythmic activity. The first included fast waveforms similar to extracellular single-unit activity. The other two types were discrete events with slower waveform dynamics and were found preferentially in upper cortical layers. These second and third types were also observed in rodents, nonhuman primates, and semi-chronic recordings from humans via laminar and Utah array microelectrodes. The rates of all three events were selectively modulated by auditory and electrical stimuli, pharmacological manipulation, and cold saline application and had small causal co-occurrences. These results suggest that the proper combination of high-resolution microelectrodes and analytic techniques can capture neuronal dynamics that lay between somatic action potentials and aggregate population activity. Understanding intermediate microscale dynamics in relation to single-cell and network dynamics may reveal important details about activity in the full cortical circuit.

Perirhinal input to neocortical layer 1 controls learning

Hippocampal output influences memory formation in the neocortex, but this process is poorly understood because the precise anatomical location and the underlying cellular mechanisms remain elusive. Here, we show that perirhinal input, predominantly to sensory cortical layer 1 (L1), controls hippocampal-dependent associative learning in rodents. This process was marked by the emergence of distinct firing responses in defined subpopulations of layer 5 (L5) pyramidal neurons whose tuft dendrites receive perirhinal inputs in L1. Learning correlated with burst firing and the enhancement of dendritic excitability, and it was suppressed by disruption of dendritic activity. Furthermore, bursts, but not regular spike trains, were sufficient to retrieve learned behavior. We conclude that hippocampal information arriving at L5 tuft dendrites in neocortical L1 mediates memory formation in the neocortex.

The Cellular Electrophysiological Properties Underlying Multiplexed Coding in Purkinje Cells

Neuronal firing patterns are crucial to underpin circuit level behaviors. In cerebellar Purkinje cells (PCs), both spike rates and pauses are used for behavioral coding, but the cellular mechanisms causing code transitions remain unknown. We use a well-validated PC model to explore the coding strategy that individual PCs use to process parallel fiber (PF) inputs. We find increasing input intensity shifts PCs from linear rate-coders to burst-pause timing-coders by triggering localized dendritic spikes. We validate dendritic spike properties with experimental data, elucidate spiking mechanisms, and predict spiking thresholds with and without inhibition. Both linear and burst-pause computations use individual branches as computational units, which challenges the traditional view of PCs as linear point neurons. Dendritic spike thresholds can be regulated by voltage state, compartmentalized channel modulation, between-branch interaction and synaptic inhibition to expand the dynamic range of linear computation or burst-pause computation. In addition, co-activated PF inputs between branches can modify somatic maximum spike rates and pause durations to make them carry analog signals. Our results provide new insights into the strategies used by individual neurons to expand their capacity of information processing.

SIGNIFICANCE STATEMENT Understanding how neurons process information is a fundamental question in neuroscience. Purkinje cells (PCs) were traditionally regarded as linear point neurons. We used computational modeling to unveil their electrophysiological properties underlying the multiplexed coding strategy that is observed during behaviors. We demonstrate that increasing input intensity triggers localized dendritic spikes, shifting PCs from linear rate-coders to burst-pause timing-coders. Both coding strategies work at the level of individual dendritic branches. Our work suggests that PCs have the ability to implement branch-specific multiplexed coding at the cellular level, thereby increasing the capacity of cerebellar coding and learning.

Simultaneous Ca2+ Imaging and Optogenetic Stimulation of Cortical Astrocytes in Adult Murine Brain Slices

Astrocytes are actively involved in a neuroprotective role in the brain, which includes scavenging reactive oxygen species to minimize tissue damage. They also modulate neuroinflammation and reactive gliosis prevalent in several brain disorders like epilepsy, Alzheimer's, and Parkinson's disease. In animal models, targeted manipulation of astrocytic function via modulation of their calcium (Ca²⁺ ) oscillations by incorporating light-sensitive cation channels like Channelrhodopsin-2 (ChR2) offers a promising avenue in influencing the long-term progression of these disorders. However, using adult animals for Ca²⁺ imaging poses major challenges, including accelerated deterioration of in situ slice health and age- related changes. Additionally, optogenetic preparations necessitate usage of a red-shifted Ca²⁺ indicator like Rhod-2 AM to avoid overlapping light issues between ChR2 and the Ca²⁺ indicator during simultaneous optogenetic stimulation and imaging. In this article, we provide an experimental setting that uses live adult murine brain slices (2-5 months) from a knock-in model expressing Channelrhodopsin-2 (ChR2(C128S)) in cortical astrocytes, loaded with Rhod-2 AM to elicit robust Ca²⁺ response to light stimulation. We have developed and standardized a protocol for brain extraction, sectioning, Rhod-2 AM loading, maintenance of slice health, and Ca²⁺ imaging during light stimulation. This has been successfully applied to optogenetically control adult cortical astrocytes, which exhibit synchronous patterns of Ca²⁺ activity upon light stimulation, drastically different from resting spontaneous activity. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Experimental preparation, setup, slice preparation and Rhod-2 AM staining Basic Protocol 2: Image acquisition and analysis.

A Minimal Biophysical Model of Neocortical Pyramidal Cells: Implications for Frontal Cortex Microcircuitry and Field Potential Generation

Ca²⁺ spikes initiated in the distal trunk of layer 5 pyramidal cells (PCs) underlie nonlinear dynamic changes in the gain of cellular response, critical for top-down control of cortical processing. Detailed models with many compartments and dozens of ionic channels can account for this Ca²⁺ spike-dependent gain and associated critical frequency. However, current models do not account for all known Ca²⁺-dependent features. Previous attempts to include more features have required increasing complexity, limiting their interpretability and utility for studying large population dynamics. We overcome these limitations in a minimal two-compartment biophysical model. In our model, a basal-dendrites/somatic compartment included fast-inactivating Na⁺ and delayed-rectifier K⁺ conductances, while an apical-dendrites/trunk compartment included persistent Na⁺, hyperpolarization-activated cation (I _h ), slow-inactivating K⁺, muscarinic K⁺, and Ca²⁺ L-type. The model replicated the Ca²⁺ spike morphology and its critical frequency plus three other defining features of layer 5 PC synaptic integration: linear frequency-current relationships, back-propagation-activated Ca²⁺ spike firing, and a shift in the critical frequency by blocking I _h Simulating 1000 synchronized layer 5 PCs, we reproduced the current source density patterns evoked by Ca²⁺ spikes and describe resulting medial-frontal EEG on a male macaque monkey. We reproduced changes in the current source density when I _h was blocked. Thus, a two-compartment model with five crucial ionic currents in the apical dendrites reproduces all features of these neurons. We discuss the utility of this minimal model to study the microcircuitry of agranular areas of the frontal lobe involved in cognitive control and responsible for event-related potentials, such as the error-related negativity.SIGNIFICANCE STATEMENT A minimal model of layer 5 pyramidal cells replicates all known features crucial for distal synaptic integration in these neurons. By redistributing voltage-gated and returning transmembrane currents in the model, we establish a theoretical framework for the investigation of cortical microcircuit contribution to intracranial local field potentials and EEG. This tractable model will enable biophysical evaluation of multiscale electrophysiological signatures and computational investigation of cortical processing.

General Anesthesia Decouples Cortical Pyramidal Neurons

The mystery of general anesthesia is that it specifically suppresses consciousness by disrupting feedback signaling in the brain, even when feedforward signaling and basic neuronal function are left relatively unchanged. The mechanism for such selectiveness is unknown. Here we show that three different anesthetics have the same disruptive influence on signaling along apical dendrites in cortical layer 5 pyramidal neurons in mice. We found that optogenetic depolarization of the distal apical dendrites caused robust spiking at the cell body under awake conditions that was blocked by anesthesia. Moreover, we found that blocking metabotropic glutamate and cholinergic receptors had the same effect on apical dendrite decoupling as anesthesia or inactivation of the higher-order thalamus. If feedback signaling occurs predominantly through apical dendrites, the cellular mechanism we found would explain not only how anesthesia selectively blocks this signaling but also why conscious perception depends on both cortico-cortical and thalamo-cortical connectivity.

Cellular Mechanisms of Conscious Processing

Recent breakthroughs in neurobiology indicate that the time is ripe to understand how cellular-level mechanisms are related to conscious experience. Here, we highlight the biophysical properties of pyramidal cells, which allow them to act as gates that control the evolution of global activation patterns. In conscious states, this cellular mechanism enables complex sustained dynamics within the thalamocortical system, whereas during unconscious states, such signal propagation is prohibited. We suggest that the hallmark of conscious processing is the flexible integration of bottom-up and top-down data streams at the cellular level. This cellular integration mechanism provides the foundation for Dendritic Information Theory, a novel neurobiological theory of consciousness.

Dissociation of broadband high-frequency activity and neuronal firing in the neocortex

Broadband high-frequency activity (BHA; 70 to 150 Hz), also known as "high gamma," a key analytic signal in human intracranial (electrocorticographic) recordings, is often assumed to reflect local neural firing [multiunit activity (MUA)]. As the precise physiological substrates of BHA are unknown, this assumption remains controversial. Our analysis of laminar multielectrode data from V1 and A1 in monkeys outlines two components of stimulus-evoked BHA distributed across the cortical layers: an "early-deep" and "late-superficial" response. Early-deep BHA has a clear spatial and temporal overlap with MUA. Late-superficial BHA was more prominent and accounted for more of the BHA signal measured near the cortical pial surface. However, its association with local MUA is weak and often undetectable, consistent with the view that it reflects dendritic processes separable from local neuronal firing.

Illuminating dendritic function with computational models

Dendrites have always fascinated researchers: from the artistic drawings by Ramon y Cajal to the beautiful recordings of today, neuroscientists have been striving to unravel the mysteries of these structures. Theoretical work in the 1960s predicted important dendritic effects on neuronal processing, establishing computational modelling as a powerful technique for their investigation. Since then, modelling of dendrites has been instrumental in driving neuroscience research in a targeted manner, providing experimentally testable predictions that range from the subcellular level to the systems level, and their relevance extends to fields beyond neuroscience, such as machine learning and artificial intelligence. Validation of modelling predictions often requires - and drives - new technological advances, thus closing the loop with theory-driven experimentation that moves the field forward. This Review features the most important, to our understanding, contributions of modelling of dendritic computations, including those pending experimental verification, and highlights studies of successful interactions between the modelling and experimental neuroscience communities.

Perspective on the Multiple Pathways to Changing Brain States

In this review article, we highlight several disparate ideas that are linked to changes in brain state (i.e., sleep to arousal, Down to Up, synchronized to de-synchronized). In any discussion of the brain state, we propose that the cortical pyramidal neuron has a central position. EEG recordings, which typically assess brain state, predominantly reflect the activity of cortical pyramidal neurons. This means that the dominant rhythmic activity that characterizes a particular brain state ultimately has to manifest globally across the pyramidal neuron population. During state transitions, it is the long-range connectivity of these neurons that broadcast the resultant changes in activity to many subcortical targets. Structures like the thalamus, brainstem/hypothalamic neuromodulatory systems, and respiratory systems can also strongly influence brain state, and for many decades we have been uncovering bidirectional pathways that link these structures to state changes in the cerebral cortex. More recently, movement and active behaviors have emerged as powerful drivers of state changes. Each of these systems involve different circuits distributed across the brain. Yet, for a system-wide change in brain state, there must be a collaboration between these circuits that reflects and perhaps triggers the transition between brain states. As we expand our understanding of how brain state changes, our current challenge is to understand how these diverse sets of circuits and pathways interact to produce the changes observed in cortical pyramidal neurons.

Probing Cortical Activity During Head-Fixed Behavior

The cortex is crucial for many behaviors, ranging from sensory-based behaviors to working memory and social behaviors. To gain an in-depth understanding of the contribution to these behaviors, cellular and sub-cellular recordings from both individual and populations of cortical neurons are vital. However, techniques allowing such recordings, such as two-photon imaging and whole-cell electrophysiology, require absolute stability of the head, a requirement not often fulfilled in freely moving animals. Here, we review and compare behavioral paradigms that have been developed and adapted for the head-fixed preparation, which together offer the needed stability for live recordings of neural activity in behaving animals. We also review how the head-fixed preparation has been used to explore the function of primary sensory cortices, posterior parietal cortex (PPC) and anterior lateral motor (ALM) cortex in sensory-based behavioral tasks, while also discussing the considerations of performing such recordings. Overall, this review highlights the head-fixed preparation as allowing in-depth investigation into the neural activity underlying behaviors by providing highly controllable settings for precise stimuli presentation which can be combined with behavioral paradigms ranging from simple sensory detection tasks to complex, cross-modal, memory-guided decision-making tasks.

Stimulus Driven Single Unit Activity From Micro-Electrocorticography

High-fidelity measurements of neural activity can enable advancements in our understanding of the neural basis of complex behaviors such as speech, audition, and language, and are critical for developing neural prostheses that address impairments to these abilities due to disease or injury. We develop a novel high resolution, thin-film micro-electrocorticography (micro-ECoG) array that enables high-fidelity surface measurements of neural activity from songbirds, a well-established animal model for studying speech behavior. With this device, we provide the first demonstration of sensory-evoked modulation of surface-recorded single unit responses. We establish that single unit activity is consistently sensed from micro-ECoG electrodes over the surface of sensorimotor nucleus HVC (used as a proper name) in anesthetized European starlings, and validate responses with correlated firing in single units recorded simultaneously at surface and depth. The results establish a platform for high-fidelity recording from the surface of subcortical structures that will accelerate neurophysiological studies, and development of novel electrode arrays and neural prostheses.

Neurophysiological Face Processing Deficits in Patients With Chronic Schizophrenia: An MEG Study

BACKGROUND

Neuropsychological studies have revealed that patients with schizophrenia (SZ) have facial recognition difficulties and a reduced visual evoked N170 response to human faces. However, detailed neurophysiological evidence of this face processing deficit in SZ with a higher spatial resolution has yet to be acquired. In this study, we recorded visual evoked magnetoencephalography (MEG) and examined whether M170 (a magnetic counterpart of the N170) activity deficits are specific to faces in patients with chronic SZ.

METHODS

Participants were 26 patients with SZ and 26 healthy controls (HC). The M170 responses to faces and cars were recorded from whole-head MEG, and global field power over each temporal cortex was analyzed. The distributed M170 sources were also localized using a minimum-norm estimation (MNE) method. Correlational analyses between M170 responses and demographics/symptoms were performed.

RESULTS

As expected, the M170 was significantly smaller in the SZ compared with the HC group in response to faces, but not to cars (faces: p = 0.01; cars: p = 0.55). The MNE analysis demonstrated that while the M170 was localized over the fusiform face area (FFA) in the HC group, visual-related brain regions other than the FFA were strongly activated in the SZ group in both stimulus conditions. The severity of negative symptoms was negatively correlated with M170 power (rho = -0.47, p = 0.01) in SZ. Within HC, there was a significant correlation between age and the M170 responses to faces averaged for both hemispheres (rho = 0.60, p = 0.001), while such a relationship was not observed in patients with SZ (rho = 0.09, p = 0.67).

CONCLUSION

The present study showed specific reductions in the M170 response to human faces in patients with SZ. Our findings could suggest that SZ is characterized by face processing deficits that are associated with the severity of negative symptoms. Thus, we suggest that social cognition impairments in SZ might, at least in part, be caused by this functional face processing deficit.

From cells to sensations: A window to the physics of mind

Principles of methods for studying particles and fields that cannot be sensed by third-person observers by routine methods can be used to understand the physics of first-person properties of mind. Accordingly, whenever a system exhibits disparate features at multiple levels, unique combination of constraints offered by them direct us towards a solution that will be the first principle of that system. Using this method, it was possible to arrive at a third-person observable solution-point of brain-mind interface. Examination of this location identified a set of unique features that can allow an associatively learned (cue) stimulus to spark hallucinations that form units of first-person internal (inner) sensations reminiscent of stimuli from the associatively learned second item in timescales of milliseconds. It allows us to peep into a virtual space of mind where different modifications and integrations of units of internal sensations generate their different net conformations ranging from perception to an inner sense of hidden relationships that form a hypothesis. Since sparking of inner sensations of the late arriving (when far away) or non-arriving (when hidden) features of items started providing survival advantage, the focus of evolution might have been to optimize this property. Hence, the circuity that generates it can be considered as the primary circuitry of the system. The solution provides several testable predictions. By taking readers through the process of deriving the solution and by explaining how it interconnects disparate findings, it is hoped that the factors determining the physics of mind will become evident.

Coupling the State and Contents of Consciousness

One fundamental feature of consciousness is that the contents of consciousness depend on the state of consciousness. Here, we propose an answer to why this is so: both the state and the contents of consciousness depend on the activity of cortical layer 5 pyramidal (L5p) neurons. These neurons affect both cortical and thalamic processing, hence coupling the cortico-cortical and thalamo-cortical loops with each other. Functionally this coupling corresponds to the coupling between the state and the contents of consciousness. Together the cortico-cortical and thalamo-cortical loops form a thalamo-cortical broadcasting system, where the L5p cells are the central elements. This perspective makes one quite specific prediction: cortical processing that does not include L5p neurons will be unconscious. More generally, the present perspective suggests that L5p neurons have a central role in the mechanisms underlying consciousness.

A potential mechanism for first-person internal sensation of memory provides evidence for the relationship between learning and LTP induction

Studies conducted to verify learning-induced changes anticipated from Hebb's postulate led to the finding of long-term potentiation (LTP). Even though several correlations have been found between behavioural markers of memory retrieval and LTP, it is not known how memories are retrieved using learning-induced changes. In this context, the following non-correlated findings between learning and LTP induction provide constraints for discovering the mechanism: 1) Requirement of high stimulus intensity for LTP induction in contrast to what is expected for a learning mechanism, 2) Delay of at least 20 to 30 s from stimulation to LTP induction, in contrast to mere milliseconds for associative learning, and 3) A sudden drop in peak-potentiated effect (short-term potentiation) that matches with short-lasting changes expected during working memory and occurs only at the time of delayed LTP induction. When memories are viewed as first-person internal sensations, a newly uncovered mechanism provides explanation for the relationship between memory and LTP. This work interconnects large number of findings from the fields of neuroscience and psychology and provides a further verifiable mechanism of learning.

Dendritic solutions to the credit assignment problem

Guaranteeing that synaptic plasticity leads to effective learning requires a means for assigning credit to each neuron for its contribution to behavior. The 'credit assignment problem' refers to the fact that credit assignment is non-trivial in hierarchical networks with multiple stages of processing. One difficulty is that if credit signals are integrated with other inputs, then it is hard for synaptic plasticity rules to distinguish credit-related activity from non-credit-related activity. A potential solution is to use the spatial layout and non-linear properties of dendrites to distinguish credit signals from other inputs. In cortical pyramidal neurons, evidence hints that top-down feedback signals are integrated in the distal apical dendrites and have a distinct impact on spike-firing and synaptic plasticity. This suggests that the distal apical dendrites of pyramidal neurons help the brain to solve the credit assignment problem.

A Perspective on Cortical Layering and Layer-Spanning Neuronal Elements

This review article addresses the function of the layers of the cerebral cortex. We develop the perspective that cortical layering needs to be understood in terms of its functional anatomy, i.e., the terminations of synaptic inputs on distinct cellular compartments and their effect on cortical activity. The cortex is a hierarchical structure in which feed forward and feedback pathways have a layer-specific termination pattern. We take the view that the influence of synaptic inputs arriving at different cortical layers can only be understood in terms of their complex interaction with cellular biophysics and the subsequent computation that occurs at the cellular level. We use high-resolution fMRI, which can resolve activity across layers, as a case study for implementing this approach by describing how cognitive events arising from the laminar distribution of inputs can be interpreted by taking into account the properties of neurons that span different layers. This perspective is based on recent advances in measuring subcellular activity in distinct feed-forward and feedback axons and in dendrites as they span across layers.