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Brain rhythms provide the timing for recruitment of brain activity required for linking together neuronal ensembles engaged in specific tasks. The γ-oscillations (30 to 120 Hz) orchestrate neuronal circuits underlying cognitive processes and working memory. These oscillations are reduced in numerous neurological and psychiatric disorders, including early cognitive decline in Alzheimers disease (AD). Here, we report on a potent brain-permeable small molecule, DDL-920 that increases γ-oscillations and improves cognition/memory in a mouse model of AD, thus showing promise as a class of therapeutics for AD. We employed anatomical, in vitro and in vivo electrophysiological, and behavioral methods to examine the effects of our lead therapeutic candidate small molecule. As a novel in central nervous system pharmacotherapy, our lead molecule acts as a potent, efficacious, and selective negative allosteric modulator of the γ-aminobutyric acid type A receptors most likely assembled from α1β2δ subunits. These receptors, identified through anatomical and pharmacological means, underlie the tonic inhibition of parvalbumin (PV) expressing interneurons (PV+INs) critically involved in the generation of γ-oscillations. When orally administered twice daily for 2 wk, DDL-920 restored the cognitive/memory impairments of 3- to 4-mo-old AD model mice as measured by their performance in the Barnes maze. Our approach is unique as it is meant to enhance cognitive performance and working memory in a state-dependent manner by engaging and amplifying the brains endogenous γ-oscillations through enhancing the function of PV+INs.

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject's engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions. [ABSTRACT FROM AUTHOR]

The objectives of this machine-learning (ML) resting-state magnetoencephalography (rs-MEG) study involving children with mild traumatic brain injury (mTBI) and orthopedic injury (OI) controls were to define a neural injury signature of mTBI and to delineate the pattern(s) of neural injury that determine behavioral recovery. Children ages 8-15 years with mTBI (n = 59) and OI (n = 39) from consecutive admissions to an emergency department were studied prospectively for parent-rated post-concussion symptoms (PCS) at: 1) baseline (average of 3 weeks post-injury) to measure pre-injury symptoms and also concurrent symptoms; and 2) at 3-months post-injury. rs-MEG was conducted at the baseline assessment. The ML algorithm predicted cases of mTBI versus OI with sensitivity of 95.5 ± 1.6% and specificity of 90.2 ± 2.7% at 3-weeks post-injury for the combined delta-gamma frequencies. The sensitivity and specificity were significantly better (p

Gamma band synchronization can facilitate local and long-range neural communication. In the primary visual cortex, visual stimulus properties within a specific location determine local synchronization strength, while the match of stimulus properties between distant locations controls long-range synchronization. The neural basis for the differential control of local and global gamma band synchronization is unknown. Combining electrophysiology, optogenetics, and computational modeling, we found that VIP disinhibitory interneurons in mouse cortex linearly scale gamma power locally without changing its stimulus tuning. Conversely, they suppress long-range synchronization when two regions process non-matched stimuli, tuning gamma coherence globally. Modeling shows that like-to-like connectivity across space and specific VIP→SST inhibition capture these opposing effects. VIP neurons thus differentially impact local and global properties of gamma rhythms depending on visual stimulus statistics. They may thereby construct gamma-band filters for spatially extended but continuous image features, such as contours, facilitating the downstream generation of coherent visual percepts.

This meta-analysis investigates auditory steady-state responses (ASSRs) as potential biomarkers of schizophrenia, focusing on previously unexplored clinical populations, frequencies, and variables. We examined 37 studies, encompassing a diverse cohort of 1788 patients with schizophrenia, including 208 patients with first-episode psychosis, 281 at-risk individuals, and 1603 healthy controls. The results indicate moderate reductions in 40 Hz ASSRs in schizophrenia patients, with significantly greater reductions in first-episode psychosis patients and minimal changes in at-risk individuals. These results call into question the expected progression of ASSR alterations across all stages of schizophrenia. The analysis also revealed the sensitivity of ASSR alterations at 40 Hz to various factors, including stimulus type, level of analysis, and attentional focus. In conclusion, our research highlights ASSRs, particularly at 40 Hz, as potential biomarkers of schizophrenia, revealing varied implications across different stages of the disorder. This study enriches our understanding of ASSRs in schizophrenia, highlighting their potential diagnostic and therapeutic relevance, particularly in the early stages of the disease. [ABSTRACT FROM AUTHOR]

Prefrontal cortex (PFC) is postulated to exert "top-down control" on information processing throughout the brain to promote specific behaviors. However, pathways mediating top-down control remain poorly understood. In particular, knowledge about direct prefrontal connections that might facilitate top-down control of hippocampal information processing remains sparse. Here we describe monosynaptic long-range GABAergic projections from PFC to hippocampus. These preferentially inhibit vasoactive intestinal polypeptide-expressing interneurons, which are known to disinhibit hippocampal microcircuits. Indeed, stimulating prefrontal-hippocampal GABAergic projections increases hippocampal feedforward inhibition and reduces hippocampal activity in vivo. The net effect of these actions is to specifically enhance the signal-to-noise ratio for hippocampal encoding of object locations and augment object-induced increases in spatial information. Correspondingly, activating or inhibiting these projections promotes or suppresses object exploration, respectively. Together, these results elucidate a top-down prefrontal pathway in which long-range GABAergic projections target disinhibitory microcircuits, thereby enhancing signals and network dynamics underlying exploratory behavior.

Electroencephalography (EEG) wearable devices are particularly suitable for monitoring a subject’s engagement while performing daily cognitive tasks. EEG information provided by wearable devices varies with the location of the electrodes, the suitable location of which can be obtained using standard multi-channel EEG recorders. Cognitive engagement can be assessed during working memory (WM) tasks, testing the mental ability to process information over a short period of time. WM could be impaired in patients with epilepsy. This study aims to evaluate the cognitive engagement of nine patients with epilepsy, coming from a public dataset by Boran et al., during a verbal WM task and to identify the most suitable location of the electrodes for this purpose. Cognitive engagement was evaluated by computing 37 engagement indexes based on the ratio of two or more EEG rhythms assessed by their spectral power. Results show that involvement index trends follow changes in cognitive engagement elicited by the WM task, and, overall, most changes appear most pronounced in the frontal regions, as observed in healthy subjects. Therefore, involvement indexes can reflect cognitive status changes, and frontal regions seem to be the ones to focus on when designing a wearable mental involvement monitoring EEG system, both in physiological and epileptic conditions.

Impaired synaptic neurotransmission may underly circuit alterations contributing to behavioral autism spectrum disorder (ASD) phenotypes. A critical component of impairments reported in somatosensory and prefrontal cortex of ASD mouse models are parvalbumin (PV)-expressing fast-spiking interneurons. However, it remains unknown whether PV interneurons mediating hippocampal networks crucial to navigation and memory processing are similarly impaired. Using PV-labeled transgenic mice, a battery of behavioral assays, in vitro patch-clamp electrophysiology, and in vivo 32-channel silicon probe local field potential recordings, we address this question in a Cntnap2-null mutant mouse model representing a human ASD risk factor gene. Cntnap2-/- mice show a reduction in hippocampal PV interneuron density, reduced inhibitory input to CA1 pyramidal cells, deficits in spatial discrimination ability, and frequency-dependent circuit changes within the hippocampus, including alterations in gamma oscillations, sharp-wave ripples, and theta-gamma modulation. Our findings highlight hippocampal involvement in ASD and implicate interneurons as a potential therapeutical target.

Inter-areal information transmission in the brain cortex relates to cognitive functions. Researches used to pay attention to activity pattern transmission, signals gating, or routing in neuronal networks. However, the underlying mechanism of simultaneous transmission of multiple neural signals in the same channel across networks remains unclear. In this work, we construct a two-layer feedforward neuronal network (sender-receiver) with each layer's intrinsic rhythms consisting of slow- (low-frequency) and fast- gamma rhythms (high-frequency), investigating how to realize simultaneous transmission of multiple signals in neuronal systems. With the aid of resonance and frequency analysis, it is shown that low- and high-frequency signals can be transmitted simultaneously in such a feedforward network through frequency division multiplexing (FDM) communication. The transmission performance is related to the local resonance, connectivity, as well as background noise. Moreover, low- and high-frequency signals can also be gated or selected with appropriate adjustments of recurrent connection strength and delay, and background noise. Our model might provide a novel insight into the underlying mechanism of complex signals communication between different cortex areas. [ABSTRACT FROM AUTHOR]

Combat-related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active-duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep-learning neural network method, 3D-MEGNET, and applied it to resting-state magnetoencephalography (rs-MEG) source-magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat-deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All-frequency model, which combined delta-theta (1-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D-MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver-operator-characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta-theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta-theta and gamma-band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta-band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source-imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all-frequency model offered more discriminative power than each frequency-band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.

Gamma-band (40-Hz) activity is critical for cortico-cortical transmission and the integration of information across neural networks during sensory and cognitive processing. Patients with schizophrenia show selective reductions in the capacity to support synchronized gamma-band oscillations in response to auditory stimulation presented 40-Hz. Despite widespread application of this 40-Hz auditory steady-state response (ASSR) as a translational electroencephalographic biomarker for therapeutic development for neuropsychiatric disorders, the spatiotemporal dynamics underlying the ASSR have not been fully characterized. In this study, a novel Granger causality analysis was applied to assess the propagation of gamma oscillations in response to 40-Hz steady-state stimulation across cortical sources in schizophrenia patients (n = 426) and healthy comparison subjects (n = 293). Both groups showed multiple ASSR source interactions that were broadly distributed across brain regions. Schizophrenia patients showed distinct, hierarchically sequenced connectivity abnormalities. During the response onset interval, patients exhibited abnormal increased connectivity from the inferior frontal gyrus to the superior temporal gyrus, followed by decreased connectivity from the superior temporal to the middle cingulate gyrus. In the later portion of the ASSR response (300-500 ms), patients showed significantly increased connectivity from the superior temporal to the middle frontal gyrus followed by decreased connectivity from the left superior frontal gyrus to the right superior and middle frontal gyri. These findings highlight both the orchestration of distributed multiple sources in response to simple gamma-frequency stimulation in healthy subjects as well as the patterns of deficits in the generation and maintenance of gamma-band oscillations across the temporo-frontal sources in schizophrenia patients.

Cognitive impairment is a hallmark of schizophrenia and a robust predictor of functional outcomes. Impairments are found in all phases of the illness and are only moderately attenuated by currently approved therapeutics. Neurophysiological indices of sensory discrimination (ie, mismatch negativity (MMN) and P3a amplitudes) and gamma-band auditory steady-state response (ASSR; power and phase locking) are translational biomarkers widely used in the development of novel therapeutics for neuropsychiatric disorders. It is unclear whether laboratory-based EEG measures add explanatory power to well-established models that use only cognitive, clinical, and functional outcome measures. Moreover, it is unclear if measures of sensory discrimination and gamma-band ASSR uniquely contribute to putative causal pathways linking sensory discrimination, neurocognition, negative symptoms, and functional outcomes in schizophrenia. To answer these questions, hierarchical associations among sensory processing, neurocognition, clinical symptoms, and functional outcomes were assessed via structural equation modeling in a large sample of schizophrenia patients (n = 695) and healthy comparison subjects (n = 503). The results showed that the neurophysiologic indices of sensory discrimination and gamma-band ASSR both significantly contribute to and yield unique hierarchical, "bottom-up" effects on neurocognition, symptoms, and functioning. Measures of sensory discrimination showed direct effects on neurocognition and negative symptoms, while gamma-band ASSR had a direct effect on neurocognition in patients. Continued investigation of the neural mechanisms underlying abnormal networks of MMN/P3a and gamma-band ASSR is needed to clarify the pathophysiology of schizophrenia and the development of novel therapeutic interventions.

Visual perception in natural environments depends on the ability to focus on salient stimuli while ignoring distractions. This kind of selective visual attention is associated with gamma activity in the visual cortex. While the nucleus reticularis thalami (nRT) has been implicated in selective attention, its role in modulating gamma activity in the visual cortex remains unknown. Here, we show that somatostatin- (SST) but not parvalbumin-expressing (PV) neurons in the visual sector of the nRT preferentially project to the dorsal lateral geniculate nucleus (dLGN), and modulate visual information transmission and gamma activity in primary visual cortex (V1). These findings pinpoint the SST neurons in nRT as powerful modulators of the visual information encoding accuracy in V1 and represent a novel circuit through which the nRT can influence representation of visual information.

The objectives of this machine-learning (ML) resting-state magnetoencephalography (rs-MEG) study involving children with mild traumatic brain injury (mTBI) and orthopedic injury (OI) controls were to define a neural injury signature of mTBI and to delineate the pattern(s) of neural injury that determine behavioral recovery. Children ages 8-15 years with mTBI (n = 59) and OI (n = 39) from consecutive admissions to an emergency department were studied prospectively for parent-rated post-concussion symptoms (PCS) at: 1) baseline (average of 3 weeks post-injury) to measure pre-injury symptoms and also concurrent symptoms; and 2) at 3-months post-injury. rs-MEG was conducted at the baseline assessment. The ML algorithm predicted cases of mTBI versus OI with sensitivity of 95.5 ± 1.6% and specificity of 90.2 ± 2.7% at 3-weeks post-injury for the combined delta-gamma frequencies. The sensitivity and specificity were significantly better (p < 0.0001) for the combined delta-gamma frequencies compared with the delta-only and gamma-only frequencies. There were also spatial differences in rs-MEG activity between mTBI and OI groups in both delta and gamma bands in frontal and temporal lobe, as well as more widespread differences in the brain. The ML algorithm accounted for 84.5% of the variance in predicting recovery measured by PCS changes between 3 weeks and 3 months post-injury in the mTBI group, and this was significantly lower (p < 10−4) in the OI group (65.6%). Frontal lobe pole (higher) gamma activity was significantly (p < 0.001) associated with (worse) PCS recovery exclusively in the mTBI group. These findings demonstrate a neural injury signature of pediatric mTBI and patterns of mTBI-induced neural injury related to behavioral recovery. [ABSTRACT FROM AUTHOR]

The functional consequences of ischemic stroke in the remote brain regions are not well characterized. The current study sought to determine changes in hippocampal oscillatory activity that may underlie the cognitive impairment observed following distal middle cerebral artery occlusion (dMCAO) without causing hippocampal structural damage. Local field potentials were recorded from the dorsal hippocampus and cortex in urethane-anesthetized rats with multichannel silicon probes during dMCAO and reperfusion, or mild ischemia induced by bilateral common carotid artery occlusion (CCAO). Bilateral change of brain state was evidenced by reduced theta/delta amplitude ratio and shortened high theta duration following acute dMCAO but not CCAO. An aberrant increase in the occurrence of sharp-wave-associated ripples (150-250 Hz), crucial for memory consolidation, was only detected after dMCAO reperfusion, coinciding with an increased occurrence of high-frequency discharges (250-450 Hz). dMCAO also significantly affected the modulation of gamma amplitude in the cortex coupled to hippocampal theta phase, although both hippocampal theta and gamma power were temporarily decreased during dMCAO. Our results suggest that MCAO may disrupt the balance between excitatory and inhibitory circuits in the hippocampus and alter the function of cortico-hippocampal network, providing a novel insight in how cortical stroke affects function in remote brain regions.

Organisms must learn new strategies to adapt to changing environments. Activity in different neurons often exhibits synchronization that can dynamically enhance their communication and might create flexible brain states that facilitate changes in behavior. We studied the role of gamma-frequency (~40 Hz) synchrony between prefrontal parvalbumin (PV) interneurons in mice learning multiple new cue-reward associations. Voltage indicators revealed cell-type-specific increases of cross-hemispheric gamma synchrony between PV interneurons when mice received feedback that previously learned associations were no longer valid. Disrupting this synchronization by delivering out-of-phase optogenetic stimulation caused mice to perseverate on outdated associations, an effect not reproduced by in-phase stimulation or out-of-phase stimulation at other frequencies. Gamma synchrony was specifically required when new associations used familiar cues that were previously irrelevant to behavioral outcomes, not when associations involved new cues or for reversing previously learned associations. Thus, gamma synchrony is indispensable for reappraising the behavioral salience of external cues.

Fragile X syndrome (FXS) is a leading genetic cause of autism with symptoms that include sensory processing deficits. In both humans with FXS and a mouse model [Fmr1 knockout (KO) mouse], electroencephalographic (EEG) recordings show enhanced resting state gamma power and reduced sound-evoked gamma synchrony. We previously showed that elevated levels of matrix metalloproteinase-9 (MMP-9) may contribute to these phenotypes by affecting perineuronal nets (PNNs) around parvalbumin (PV) interneurons in the auditory cortex of Fmr1 KO mice. However, how different cell types within local cortical circuits contribute to these deficits is not known. Here, we examined whether Fmr1 deletion in forebrain excitatory neurons affects neural oscillations, MMP-9 activity, and PV/PNN expression in the auditory cortex. We found that cortical MMP-9 gelatinase activity, mTOR/Akt phosphorylation, and resting EEG gamma power were enhanced in CreNex1/Fmr1Flox/y conditional KO (cKO) mice, whereas the density of PV/PNN cells was reduced. The CreNex1/Fmr1Flox/y cKO mice also show increased locomotor activity, but not the anxiety-like behaviors. These results indicate that fragile X mental retardation protein changes in excitatory neurons in the cortex are sufficient to elicit cellular, electrophysiological, and behavioral phenotypes in Fmr1 KO mice. More broadly, these results indicate that local cortical circuit abnormalities contribute to sensory processing deficits in autism spectrum disorders.

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members and veterans. Recent animal studies show that GABA-ergic parvalbumin-positive interneurons are susceptible to brain injury, with damage causing abnormal increases in spontaneous gamma-band (30-80 Hz) activity. We investigated spontaneous gamma activity in individuals with mTBI using high-resolution resting-state magnetoencephalography source imaging. Participants included 25 symptomatic individuals with chronic combat-related blast mTBI and 35 healthy controls with similar combat experiences. Compared with controls, gamma activity was markedly elevated in mTBI participants throughout frontal, parietal, temporal, and occipital cortices, whereas gamma activity was reduced in ventromedial prefrontal cortex. Across groups, greater gamma activity correlated with poorer performances on tests of executive functioning and visuospatial processing. Many neurocognitive associations, however, were partly driven by the higher incidence of mTBI participants with both higher gamma activity and poorer cognition, suggesting that expansive upregulation of gamma has negative repercussions for cognition particularly in mTBI. This is the first human study to demonstrate abnormal resting-state gamma activity in mTBI. These novel findings suggest the possibility that abnormal gamma activities may be a proxy for GABA-ergic interneuron dysfunction and a promising neuroimaging marker of insidious mild head injuries.

Schizophrenia is a neurocognitive illness characterized by behavioral and neural impairments in both early auditory processing and higher order verbal working memory. Previously we have shown intervention-specific cognitive performance improvements with computerized, targeted training of auditory processing (AT) when compared to a computer games (CG) control intervention that emphasized visual processing. To investigate spatiotemporal changes in patterns of neural activity specific to the AT intervention, the current study used magnetoencephalography (MEG) imaging to derive induced high gamma band oscillations (HGO) during auditory encoding, before and after 50 h (∼10 weeks) of exposure to either the AT or CG intervention. During stimulus encoding, AT intervention-specific changes in high gamma activity occurred in left middle frontal and left middle-superior temporal cortices. In contrast, CG intervention-specific changes were observed in right medial frontal and supramarginal gyri during stimulus encoding, and in bilateral temporal cortices during response preparation. These data reveal that, in schizophrenia, intensive exposure to either training of auditory processing or exposure to visuospatial activities produces significant but complementary patterns of cortical function plasticity within a distributed fronto-temporal network. These results underscore the importance of delineating the specific neuroplastic effects of targeted behavioral interventions to ensure desired neurophysiological changes and avoid unintended consequences on neural system functioning.

This meta-analysis investigates auditory steady-state responses (ASSRs) as potential biomarkers of schizophrenia, focusing on previously unexplored clinical populations, frequencies, and variables. We examined 37 studies, encompassing a diverse cohort of 1788 patients with schizophrenia, including 208 patients with first-episode psychosis, 281 at-risk individuals, and 1603 healthy controls. The results indicate moderate reductions in 40 Hz ASSRs in schizophrenia patients, with significantly greater reductions in first-episode psychosis patients and minimal changes in at-risk individuals. These results call into question the expected progression of ASSR alterations across all stages of schizophrenia. The analysis also revealed the sensitivity of ASSR alterations at 40 Hz to various factors, including stimulus type, level of analysis, and attentional focus. In conclusion, our research highlights ASSRs, particularly at 40 Hz, as potential biomarkers of schizophrenia, revealing varied implications across different stages of the disorder. This study enriches our understanding of ASSRs in schizophrenia, highlighting their potential diagnostic and therapeutic relevance, particularly in the early stages of the disease.

Patients with Parkinson disease (PD) often experience nonmotor symptoms including cognitive deficits, depression, and anxiety. Cognitive and affective processes are thought to be mediated by prefrontal cortico-basal ganglia circuitry. However, the topography and neurophysiology of prefrontal cortical activity during complex tasks are not well characterized. We used high-resolution electrocorticography in pFC of patients with PD and essential tremor, during implantation of deep brain stimulator leads in the awake state, to understand disease-specific changes in prefrontal activity during an emotional face processing task. We found that patients with PD had less task-related theta-alpha power and greater task-related gamma power in the dorsolateral pFC, inferior frontal cortex, and lateral OFC. These findings support a model of prefrontal neurophysiological changes in the dopamine-depleted state, in which focal areas of hyperactivity in prefrontal cortical regions may compensate for impaired long-range interactions mediated by low-frequency rhythms. These distinct neurophysiological changes suggest that nonmotor circuits undergo characteristic changes in PD.

Brain-machine interfaces (BMIs) translate brain signals into control signals for an external device, such as a computer cursor or robotic limb. These signals can be obtained either noninvasively or invasively. Invasive recordings, using electrocorticography (ECoG) or intracortical microelectrodes, provide higher bandwidth and more informative signals. Rehabilitative BMIs, which aim to drive plasticity in the brain to enhance recovery after brain injury, have almost exclusively used non-invasive recordings, such electroencephalography (EEG) or magnetoencephalography (MEG), which have limited bandwidth and information content. Invasive recordings provide more information and spatiotemporal resolution, but do incur risk, and thus are not usually investigated in people with stroke or traumatic brain injury (TBI). Here, in this paper, we describe a new BMI paradigm to investigate the use of higher frequency signals in brain-injured subjects without incurring significant risk. We recorded EEG in TBI subjects who required hemicraniectomies (removal of a part of the skull). EEG over the hemicraniectomy (hEEG) contained substantial information in the high gamma frequency range (65-115 Hz). Using this information, we decoded continuous finger flexion force with moderate to high accuracy (variance accounted for 0.06 to 0.52), which at best approaches that using epidural signals. These results indicate that people with hemicraniectomies can provide a useful resource for developing BMI therapies for the treatment of brain injury.

Beta and gamma frequency neuronal oscillations have been implicated in top-down and bottom-up attention. In this study, we used rhythmic TMS to modulate ongoing beta and gamma frequency neuronal oscillations in frontal and parietal cortex while human participants performed a visual search task that manipulates bottom-up and top-down attention (single feature and conjunction search). Both task conditions will engage bottom-up attention processes, although the conjunction search condition will require more top-down attention. Gamma frequency TMS to superior precentral sulcus (sPCS) slowed saccadic RTs during both task conditions and induced a response bias to the contralateral visual field. In contrary, beta frequency TMS to sPCS and intraparietal sulcus decreased search accuracy only during the conjunction search condition that engaged more top-down attention. Furthermore, beta frequency TMS increased trial errors specifically when the target was in the ipsilateral visual field for the conjunction search condition. These results indicate that beta frequency TMS to sPCS and intraparietal sulcus disrupted top-down attention, whereas gamma frequency TMS to sPCS disrupted bottom-up, stimulus-driven attention processes. These findings provide causal evidence suggesting that beta and gamma oscillations have distinct functional roles for cognition.

This study examined the effects of stimulation targeting dorsolateral prefrontal cortex (DLPFC) on behavioral and neural oscillatory markers of proactive cognitive control in healthy adults. We hypothesized that active stimulation targeting the DLPFC would enhance proactive control compared to sham, leading to changes in the pattern of error rates and gamma-band power on the Dot Pattern Expectancy (DPX) task. We recorded EEG while participants completed the DPX, after receiving either 20 minutes of active DLPFC stimulation at 2 mA or sham stimulation in a counterbalanced within-participants design. The results showed significant tDCS-induced changes in the pattern of error rates on the DPX task indicative of enhanced proactive control, as well as predicted increases in gamma power associated with the engagement of proactive control. These results provide support for the role of DLPFC-mediated gamma activity in proactive cognitive control, and further, indicate that proactive control can be enhanced with non-invasive neurostimulation.

Some individuals with schizophrenia report similar feelings of positive affect "in the moment" compared to control participants but report decreased trait positive affect overall. One possible explanation for this disconnection between state and trait positive affect is the extent to which individuals with schizophrenia engage in elaborative processing of positive stimuli. To assess this, we examined evoked gamma band activity in response to positive words over several seconds in a group with schizophrenia, a group with major depressive disorder, and a healthy control group. From a pre-stimulus baseline to 2000 ms after onset of the stimulus (henceforth, "early period"), the schizophrenia group showed a reliable increase in gamma activity compared to both the control and depressed groups, who did not differ from each other. In contrast, the depressed group showed a reliable increase in gamma activity from 2001 to 8000 ms (henceforth, "late period") compared to the other groups, who did not differ from each other. At the same time, the schizophrenia group showed a reliable decrease from the early to late period while the depressed group showed the opposite pattern. In addition, self-reported depression and social anhedonia in the schizophrenia group were related to decreased gamma band activity over the entire processing window. Overall, these results suggest that schizophrenia is associated with increased initial reactivity but decreased sustained elaborative processing over time, which could be related to decreased trait positive affect. The results also highlight the importance of considering depressive symptomology and anhedonia when examining emotional abnormalities in schizophrenia.

BackgroundThe synchronous ionic currents that give rise to neural oscillations have complex influences on neuronal spiking activity that are challenging to characterize.New methodHere we present a method to estimate probabilistic relationships between neural spiking activity and the phase of field oscillations using a generalized linear model (GLM) with an overcomplete basis of circular functions. We first use an L1-regularized maximum likelihood procedure to select an active set of regressors from the overcomplete set and perform model fitting using standard maximum likelihood estimation. An information theoretic model selection procedure is then used to identify an optimal subset of regressors and associated coefficients that minimize overfitting. To assess goodness of fit, we apply the time-rescaling theorem and compare model predictions to original data using quantile-quantile plots.ResultsSpike-phase relationships in synthetic data were robustly characterized. When applied to in vivo hippocampal data from an awake behaving rat, our method captured a multimodal relationship between the spiking activity of a CA1 interneuron, a theta (5-10 Hz) rhythm, and a nested high gamma (65-135 Hz) rhythm.Comparison with existing methodsPrevious methods for characterizing spike-phase relationships are often only suitable for unimodal relationships, impose specific relationship shapes, or have limited ability to assess the accuracy or fit of their characterizations.ConclusionsThis method advances the way spike-phase relationships are visualized and quantified, and captures multimodal spike-phase relationships, including relationships with multiple nested rhythms. Overall, our method is a powerful tool for revealing a wide range of neural circuit interactions.

Despite many behavioral and neuroimaging investigations, it remains unclear how the human cortex represents spectrotemporal sound features during auditory imagery, and how this representation compares to auditory perception. To assess this, we recorded electrocorticographic signals from an epileptic patient with proficient music ability in 2 conditions. First, the participant played 2 piano pieces on an electronic piano with the sound volume of the digital keyboard on. Second, the participant replayed the same piano pieces, but without auditory feedback, and the participant was asked to imagine hearing the music in his mind. In both conditions, the sound output of the keyboard was recorded, thus allowing precise time-locking between the neural activity and the spectrotemporal content of the music imagery. This novel task design provided a unique opportunity to apply receptive field modeling techniques to quantitatively study neural encoding during auditory mental imagery. In both conditions, we built encoding models to predict high gamma neural activity (70-150 Hz) from the spectrogram representation of the recorded sound. We found robust spectrotemporal receptive fields during auditory imagery with substantial, but not complete overlap in frequency tuning and cortical location compared to receptive fields measured during auditory perception.

Background:Angelman syndrome (AS) is a neurodevelopmental disorder characterized by intellectual disability, speech and motor impairments, epilepsy, abnormal sleep, and phenotypic overlap with autism. Individuals with AS display characteristic EEG patterns including high-amplitude rhythmic delta waves. Here, we sought to quantitatively explore EEG architecture in AS beyond known spectral power phenotypes. We were motivated by studies of functional connectivity and sleep spindles in autism to study these EEG readouts in children with AS. Methods:We analyzed retrospective wake and sleep EEGs from children with AS (age 4-11) and age-matched neurotypical controls. We assessed long-range and short-range functional connectivity by measuring coherence across multiple frequencies during wake and sleep. We quantified sleep spindles using automated and manual approaches. Results:During wakefulness, children with AS showed enhanced long-range EEG coherence across a wide range of frequencies. During sleep, children with AS showed increased long-range EEG coherence specifically in the gamma band. EEGs from children with AS contained fewer sleep spindles, and these spindles were shorter in duration than their neurotypical counterparts. Conclusions:We demonstrate two quantitative readouts of dysregulated sleep composition in children with AS-gamma coherence and spindles-and describe how functional connectivity patterns may be disrupted during wakefulness. Quantitative EEG phenotypes have potential as biomarkers and readouts of target engagement for future clinical trials and provide clues into how neural circuits are dysregulated in children with AS.

Background: The number of patients with Alzheimer's disease (AD) worldwide is increasing yearly, but the existing treatment methods have poor efficacy. Transcranial alternating current stimulation (tACS) is a new treatment for AD, but the offline effect of tACS is insufficient. To prolong the offline effect, we designed to combine tACS with sound stimulation to maintain the long-term post-effect. Materials and methods: To explore the safety and effectiveness of tACS combined with sound stimulation and its impact on the cognition of AD patients. This trial will recruit 87 patients with mild to moderate AD. All patients were randomly divided into three groups. The change in Alzheimer's Disease Assessment Scale-Cognitive (ADAS-Cog) scores from the day before treatment to the end of treatment and 3months after treatment was used as the main evaluation index. We will also explore the changes in the brain structural network, functional network, and metabolic network of AD patients in each group after treatment. Discussion: We hope to conclude that tACS combined with sound stimulation is safe and tolerable in 87 patients with mild to moderate AD under three standardized treatment regimens. Compared with tACS alone or sound alone, the combination group had a significant long-term effect on cognitive improvement. To screen out a better treatment plan for AD patients. tACS combined with sound stimulation is a previously unexplored, non-invasive joint intervention to improve patients' cognitive status. This study may also identify the potential mechanism of tACS combined with sound stimulation in treating mild to moderate AD patients. Clinical Trial Registration: Clinicaltrials.gov, NCT05251649. Registered on February 22, 2022. [ABSTRACT FROM AUTHOR]

Even during sustained attention, enhanced processing of attended stimuli waxes and wanes rhythmically, with periods of enhanced and relatively diminished visual processing (and subsequent target detection) alternating at 4 or 8 Hz in a sustained visual attention task. These alternating attentional states occur alongside alternating dynamical states, in which lateral intraparietal cortex (LIP), the frontal eye field (FEF), and the mediodorsal pulvinar (mdPul) exhibit different activity and functional connectivity at α, β, and γ frequencies—rhythms associated with visual processing, working memory, and motor suppression. To assess whether and how these multiple interacting rhythms contribute to periodicity in attention, we propose a detailed computational model of FEF and LIP. When driven by θ-rhythmic inputs simulating experimentally-observed mdPul activity, this model reproduced the rhythmic dynamics and behavioral consequences of observed attentional states, revealing that the frequencies and mechanisms of the observed rhythms allow for peak sensitivity in visual target detection while maintaining functional flexibility.

Cognitive control refers to the ability to produce flexible, goal-oriented behavior in the face of changing task demands and conflicting response tendencies. A classic cognitive control experiment is the Stroop-color naming task, which requires participants to name the color in which a word is written while inhibiting the tendency to read the word. By comparing stimuli with conflicting word-color associations to congruent ones, control processes over response tendencies can be isolated. We assessed the spatial specificity and temporal dynamics in the theta and gamma bands for regions engaged in detecting and resolving conflict in a cohort of 13 patients using a combination of high-resolution surface and depth recordings. We show that cognitive control manifests as a sustained increase in gamma band power, which correlates with response time. Conflict elicits a sustained gamma power increase but a transient theta power increase, specifically localized to the left cingulate sulcus and bilateral dorsolateral prefrontal cortex (DLPFC). Additionally, activity in DLPFC is affected by trial-by-trial modulation of cognitive control (the Gratton effect). Altogether, the sustained local neural activity in dorsolateral and medial regions is what determines the timing of the correct response.

Gamma oscillations that occur within the entorhinal cortex-hippocampal circuitry play important roles in the formation and retrieval of memory in healthy brains. Recent studies report that gamma oscillations are impaired in the entorhinal-hippocampal circuit of Alzheimer's disease (AD) patients and AD animal models. Here we review the latest advancements in studies of entorhinal-hippocampal gamma oscillations in healthy memory and dementia. This review is especially salient for readers in Alzheimer's research field not familiar with in vivo electrophysiology. Recent studies have begun to show a causal link between gamma oscillations and AD pathology, suggesting that gamma oscillations may even offer a plausible future therapeutic target.

OBJECTIVE:Direct electrical stimulation (DES) is a clinical gold standard for human brain mapping and readily evokes conscious percepts, yet the neurophysiological changes underlying these percepts are not well understood. APPROACH:To determine the neural correlates of DES, we stimulated the somatosensory cortex of ten human participants at frequency-amplitude combinations that both elicited and failed to elicit conscious percepts, meanwhile recording neural activity directly surrounding the stimulation site. We then compared the neural activity of perceived trials to that of non-perceived trials. MAIN RESULTS:We found that stimulation evokes distributed high gamma activity, which correlates with conscious perception better than stimulation parameters themselves. SIGNIFICANCE:Our findings suggest that high gamma activity is a reliable biomarker for perception evoked by both natural and electrical stimuli.

Distinct anatomical and spectral channels are thought to play specialized roles in the communication within cortical networks. While activity in the alpha and beta frequency range (7 - 40 Hz) is thought to predominantly originate from infragranular cortical layers conveying feedback-related information, activity in the gamma range (>40 Hz) dominates in supragranular layers communicating feedforward signals. We leveraged high precision MEG to test this proposal, directly and non-invasively, in human participants performing visually cued actions. We found that visual alpha mapped onto deep cortical laminae, whereas visual gamma predominantly occurred more superficially. This lamina-specificity was echoed in movement-related sensorimotor beta and gamma activity. These lamina-specific pre- and post- movement changes in sensorimotor beta and gamma activity suggest a more complex functional role than the proposed feedback and feedforward communication in sensory cortex. Distinct frequency channels thus operate in a lamina-specific manner across cortex, but may fulfill distinct functional roles in sensory and motor processes.

Higher-order visual thalamus plays a fundamental but poorly understood role in attention-demanding tasks. To investigate how neuronal dynamics in higher-order visual thalamus are modulated by sustained attention, we performed multichannel electrophysiological recordings in the lateral posterior-pulvinar complex (LP/pulvinar) in the ferret (Mustela putorius furo). We recorded single unit activity and local field potential (LFP) during the performance of the five-choice serial reaction time task (5-CSRTT), which is used in both humans and animals as an assay of sustained attention. We found that half of the units exhibited an increasing firing rate during the delay period before stimulus onset (attention-modulated units). In contrast, the non-attention-modulated units responded to the stimulus, but not during the delay period. Spike-field coherence (SFC) of only the attention-modulated neurons significantly increased from the start of the delay period until screen touch, predominantly in the θ frequency band. In addition, θ power and θ/γ phase amplitude coupling (PAC) were elevated throughout the delay period. Our findings suggest that the θ oscillation plays a central role in orchestrating thalamic signaling during sustained attention.

ObjectiveTo develop a reliable software method using a topographic analysis of time-frequency plots to distinguish ripple (80-200 Hz) oscillations that are often associated with EEG sharp waves or spikes (RonS) from sinusoid-like waveforms that appear as ripples but correspond with digital filtering of sharp transients contained in the wide bandwidth EEG.MethodsA custom algorithm distinguished true from false ripples in one second intracranial EEG (iEEG) recordings using wavelet convolution, identifying contours of isopower, and categorizing these contours into sets of open or closed loop groups. The spectral and temporal features of candidate groups were used to classify the ripple, and determine its duration, frequency, and power. Verification of detector accuracy was performed on the basis of simulations, and visual inspection of the original and band-pass filtered signals.ResultsThe detector could distinguish simulated true from false ripple on spikes (RonS). Among 2934 visually verified trials of iEEG recordings and spectrograms exhibiting RonS the accuracy of the detector was 88.5% with a sensitivity of 81.8% and a specificity of 95.2%. The precision was 94.5% and the negative predictive value was 84.0% (N = 12). Among, 1,370 trials of iEEG recording exhibiting RonS that were reviewed blindly without spectrograms the accuracy of the detector was 68.0%, with kappa equal to 0.01 ± 0.03. The detector successfully distinguished ripple from high spectral frequency 'fast ripple' oscillations (200-600 Hz), and characterize ripple duration and spectral frequency and power. The detector was confounded by brief bursts of gamma (30-80 Hz) activity in 7.31 ± 6.09% of trials, and in 30.2 ± 14.4% of the true RonS detections ripple duration was underestimated.ConclusionsCharacterizing the topographic features of a time-frequency plot generated by wavelet convolution is useful for distinguishing true oscillations from false oscillations generated by filter ringing.SignificanceCategorizing ripple oscillations and characterizing their properties can improve the clinical utility of the biomarker.

The medial prefrontal cortex plays a key role in higher order cognitive functions like decision making and social cognition. These complex behaviors emerge from the coordinated firing of prefrontal neurons. Fast-spiking interneurons (FSIs) control the timing of excitatory neuron firing via somatic inhibition and generate gamma (30-100 Hz) oscillations. Therefore, factors that regulate how FSIs respond to gamma-frequency input could affect both prefrontal circuit activity and behavior. Here, we show that serotonin (5HT), which is known to regulate gamma power, acts via 5HT2A receptors to suppress an inward-rectifying potassium conductance in FSIs. This leads to depolarization, increased input resistance, enhanced spiking, and slowed decay of excitatory post-synaptic potentials (EPSPs). Notably, we found that slowed EPSP decay preferentially enhanced temporal summation and firing elicited by gamma frequency inputs. These findings show how changes in passive membrane properties can affect not only neuronal excitability but also the temporal filtering of synaptic inputs.

Aberrant gamma-band (30-80 Hz) oscillations may underlie cognitive deficits in schizophrenia (SZ). Gamma oscillations and their regulation by NMDA receptors can be studied via their evoked power (γEP) and phase locking (γPL) in response to auditory steady-state stimulation; these auditory steady-state responses (ASSRs) may be biomarkers for target engagement and early therapeutic effects. We previously reported that memantine, an NMDA receptor antagonist, enhanced two biomarkers of early auditory information processing: prepulse inhibition and mismatch negativity (MMN) in SZ patients and healthy subjects (HS). Here, we describe memantine effects on γEP and γPL in those subjects. SZ patients (n=18) and HS (n=14) received memantine 20 mg (p.o.) and placebo over 2 test days in a double-blind, randomized, counterbalanced, cross-over design. The ASSR paradigm (1 ms, 85 dB clicks in 250-0.5 s trains at a frequency of 40 Hz; 0.5 s inter-train interval) was used to assess γEP and γPL. SZ patients had reduced γEP and γPL; memantine enhanced γEP and γPL (p

Transcranial alternating current stimulation (tACS) is a relatively new non-invasive brain electrical stimulation method for the treatment of patients with Alzheimer's disease (AD), but it has poor offline effects. Therefore, we applied a new combined stimulation method to observe the offline effect on the cognitive function of patients with AD. Here, we describe the clinical results of a case in which tACS combined with sound stimulation was applied to treat moderate AD. The patient was a 73-year-old woman with a 2-year history of persistent cognitive deterioration despite the administration of Aricept and Sodium Oligomannate. Therefore, the patient received tACS combined with sound stimulation. Her cognitive scale scores improved after 15 sessions and continued to improve at 4 months of follow-up. Although the current report may provide a new alternative therapy for patients with AD, more clinical data are needed to support its efficacy. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that open-loop transcranial ultrasound stimulation (TUS) can modulate theta and gamma rhythms of the local field potentials (LFPs) in the mouse hippocampus; however, the manner in which closed-loop TUS with different pressures based on phase-locking of theta rhythms modulates theta and gamma rhythm remains unclear. In this study, we established a closed-loop TUS system, which can perform closed-loop TUS by predicting the peaks and troughs of the theta rhythm. Comparison of the power, sample entropy and complexity, and phaseamplitude coupling (PAC) between the theta and gamma rhythms under peak and trough stimulation of the theta rhythm revealed the following: (1) the variation in the absolute power of the gamma rhythm and the relative power of the theta rhythm under TUS at 0.6-0.8 MPa differ between peak and trough stimulation; (2) the relationship of the sample entropy of the theta and gamma rhythms with ultrasound pressure depends on peak and trough stimulation; and (3) peak and trough stimulation affect the PAC strength between the theta and gamma rhythm as a function of ultrasound pressure. These results demonstrate that the modulation of the theta and gamma rhythms by ultrasound pressure depends on peak and trough stimulation of the theta rhythm in the mouse hippocampus. [ABSTRACT FROM AUTHOR]

The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3-6 Hz), high theta (~6-12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations., Competing Interests: Declaration of interests. The authors declare no competing interest.

Gamma-band activity, peaking around 30–100 Hz in the local field potential's power spectrum, has been found and intensively studied in many brain regions. Although gamma is thought to play a critical role in processing neural information in the brain, its cognitive functions and neural mechanisms remain unclear or debatable. Experimental studies showed that gamma rhythms are stochastic in time and vary with visual stimuli. Recent studies further showed that multiple rhythms coexist in V1 with distinct origins in different species. While all these experimental facts are a challenge for understanding the functions of gamma in the visual cortex, there are many signs of progress in computational studies. This review summarizes and discusses studies on gamma in the visual cortex from multiple perspectives and concludes that gamma rhythms are still a mystery. Combining experimental and computational studies seems the best way forward in the future. [ABSTRACT FROM AUTHOR]

The mechanism by which the human primary motor cortex (M1) encodes upper extremity movement kinematics is not fully understood. For example, human electrocorticogram (ECoG) signals have been shown to modulate with upper extremity movements; however, this relationship has not been explicitly characterized. To address this issue, we recorded high-density ECoG signals from patients undergoing epilepsy surgery evaluation as they performed elementary upper extremity movements while systematically varying movement speed and duration. Specifically, subjects performed intermittent pincer grasp/release, elbow flexion/extension, and shoulder flexion/extension at slow, moderate, and fast speeds. In all movements, bursts of power in the high-[Formula: see text] band (80-160 Hz) were observed in M1. In addition, the amplitude of these power bursts and the area of M1 with elevated high-[Formula: see text] activity were directly proportional to the movement speed. Likewise, the duration of elevated high-[Formula: see text] activity increased with movement duration. Based on linear regression, M1 high-[Formula: see text] power amplitude and duration covaried with movement speed and duration, respectively, with an average [Formula: see text] of [Formula: see text] and [Formula: see text]. These findings indicate that the encoding of upper extremity movement speed by M1 high-[Formula: see text] activity is primarily linear. Also, the fact that this activity remained elevated throughout a movement suggests that M1 does not merely generate transient instructions for a specific movement duration, but instead is responsible for the entirety of the movement. Finally, the spatial distribution of high-[Formula: see text] activity suggests the presence of a recruitment phenomenon in which higher speeds or increased muscle activity involve activation of larger M1 areas.

Direct intracranial recording of human brain activity is an important approach for deciphering neural mechanisms of cognition. Such recordings, usually made in patients with epilepsy undergoing inpatient monitoring for seizure localization, are limited in duration and depend on patients' tolerance for the challenges associated with recovering from brain surgery. Thus, typical intracranial recordings, similar to most non-invasive approaches in humans, provide snapshots of brain activity in acute, highly constrained settings, limiting opportunities to understand long timescale and natural, real-world phenomena. A new device for treating some forms of drug-resistant epilepsy, the NeuroPace RNS® System, includes a cranially-implanted neurostimulator and intracranial electrodes that continuously monitor brain activity and respond to incipient seizures with electrical counterstimulation. The RNS System can record epileptic brain activity over years, but whether it can record meaningful, behavior-related physiological responses has not been demonstrated. Here, in a human subject with electrodes implanted over high-level speech-auditory cortex (Wernicke's area; posterior superior temporal gyrus), we report that cortical evoked responses to spoken sentences are robust, selective to phonetic features, and stable over nearly 1.5 years. In a second subject with RNS System electrodes implanted over frontal cortex (Broca's area, posterior inferior frontal gyrus), we found that word production during a naming task reliably evokes cortical responses preceding speech onset. The spatiotemporal resolution, high signal-to-noise, and wireless nature of this system's intracranial recordings make it a powerful new approach to investigate the neural correlates of human cognition over long timescales in natural ambulatory settings.

The capacity for using external cues to guide behavior ("cue detection") constitutes an essential aspect of attention and goal-directed behavior. The cortical cholinergic input system, via phasic increases in prefrontal acetylcholine release, plays an essential role in attention by mediating such cue detection. However, the relationship between cholinergic signaling during cue detection and neural activity dynamics in prefrontal networks remains unclear. Here we combined subsecond measures of cholinergic signaling, neurophysiological recordings, and cholinergic receptor blockade to delineate the cholinergic contributions to prefrontal oscillations during cue detection in rats. We first confirmed that detected cues evoke phasic acetylcholine release. These cholinergic signals were coincident with increased neuronal synchrony across several frequency bands and the emergence of theta-gamma coupling. Muscarinic and nicotinic cholinergic receptors both contributed specifically to gamma synchrony evoked by detected cues, but the effects of blocking the two receptor subtypes were dissociable. Blocking nicotinic receptors primarily attenuated high-gamma oscillations occurring during the earliest phases of the cue detection process, while muscarinic (M1) receptor activity was preferentially involved in the transition from high to low gamma power that followed and corresponded to the mobilization of networks involved in cue-guided decision making. Detected cues also promoted coupling between gamma and theta oscillations, and both nicotinic and muscarinic receptor activity contributed to this process. These results indicate that acetylcholine release coordinates neural oscillations during the process of cue detection.SIGNIFICANCE STATEMENT The capacity of learned cues to direct attention and guide responding ("cue detection") is a key component of goal-directed behavior. Rhythmic neural activity and increases in acetylcholine release in the prefrontal cortex contribute to this process; however, the relationship between these neuronal mechanisms is not well understood. Using a combination of in vivo neurochemistry, neurophysiology, and pharmacological methods, we demonstrate that cue-evoked acetylcholine release, through distinct actions at both nicotinic and muscarinic receptors, triggers a procession of neural oscillations that map onto the multiple stages of cue detection. Our data offer new insights into cholinergic function by revealing the temporally orchestrated changes in prefrontal network synchrony modulated by acetylcholine release during cue detection.

Gamma activity in the subthalamic nucleus (STN) is widely viewed as a pro-kinetic rhythm. Here we test the hypothesis that rather than being specifically linked to movement execution, gamma activity reflects dynamic processing in this nucleus. We investigated the role of gamma during fast stopping and recorded scalp electroencephalogram and local field potentials from deep brain stimulation electrodes in 9 Parkinson's disease patients. Patients interrupted finger tapping (paced by a metronome) in response to a stop-signal sound, which was timed such that successful stopping would occur only in ~50% of all trials. STN gamma (60-90 Hz) increased most strongly when the tap was successfully stopped, whereas phase-based connectivity between the contralateral STN and motor cortex decreased. Beta or theta power seemed less directly related to stopping. In summary, STN gamma activity may support flexible motor control as it did not only increase during movement execution but also during rapid action-stopping.

γ oscillations, which can be identified by rhythmic electrical signals ∼30-100 Hz, consist of interactions between excitatory and inhibitory neurons that result in rhythmic inhibition capable of entraining firing within local cortical circuits. Many possible mechanisms have been described through which γ oscillations could act on cortical circuits to modulate their responses to input, alter their patterns of activity, and/or enhance the efficacy of their outputs onto downstream targets. Recently, several studies have observed changes in behavior after optogenetically manipulating neocortical γ oscillations. Now, future studies should determine whether these manipulations elicit physiological correlates associated with specific mechanisms through which γ oscillations are hypothesized to modulate cortical circuit function. There are numerous such mechanisms, so identifying which ones are actually engaged by optogenetic manipulations known to affect behavior would help flesh out exactly how γ oscillations contribute to cortical circuit function under normal and/or pathological conditions.

ObjectiveThe superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography.ApproachThe system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder.Main resultsThe performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system.SignificanceThese results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

ObjectiveElectrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram.ApproachFive subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient.Main resultsThe correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (