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Human brain imaging has revealed that stimulus-induced activity does generally not simply add to the pre-stimulus activity, but rather builds in a non-additive way on this activity. Here we investigate this subject at the single neuron level and address the question whether and to what extent a strong form of non-additivity where activity drops post-cue is present in different areas of monkey cortex, including prefrontal and agranular frontal areas, during a perceptual decision making task involving action and tactic selection. Specifically we analyze spike train data recorded in vivo from the posterior dorsomedial prefrontal cortex (pmPFC), the supplementary motor area (SMA) and the presupplementary motor area (pre-SMA). For each neuron, we compute the ratio of the trial-averaged pre-stimulus spike count to the trial-averaged post-stimulus count. We also perform the ratio and averaging procedures in reverse order. We find that the statistics of these quantities behave differently across areas. pmPFC involved in tactic selection shows stronger non-additivity compared to the two other areas which more generically just increase their firing rate pos-stimulus. pmPFC behaved more similarly to pre-SMA, a likely consequence of the reciprocal connections between these areas. The trial-averaged ratio statistic was reproduced by a surrogate inhomogeneous Poisson process in which the measured trial-averaged firing rate for a given neuron is used as its time-dependent rate. Principal component analysis (PCA) of the trial-averaged firing rates of neuronal ensembles further reveals area-specific time courses of response to the stimulus, including latency to peak neural response, for the typical population activity. Our work demonstrates subtle forms of area-specific non-additivity based on the fine variability structure of pre- and post-stimulus spiking activity on the single neuron level. It also reveals significant differences between areas for PCA and surrogate analysis, complementing previous observations of regional differences based solely on post-stimulus responses. Moreover, we observe regional differences in non-additivity which are related to the monkey’s successful tactic selection and decision making.

The knowledge on real‐time neurophysiological effects of acetazolamide is still far behind the wide clinical use of this drug. Acetazolamide – a carbonic anhydrase inhibitor – has been shown to affect the neuromuscular transmission, implying a pH‐mediated influence on the central synaptic transmission. To start filling such a gap, we chose a central substrate: hippocampal‐prefrontal cortical projections; and a synaptic phenomenon: paired‐pulse facilitation (a form of synaptic plasticity) to probe this drug's effects on interareal brain communication in chronically implanted rats. We observed that systemic acetazolamide potentiates the hippocampal‐prefrontal paired‐pulse facilitation. In addition to this field electrophysiology data, we found that acetazolamide exerts a net inhibitory effect on prefrontal cortical single‐unit firing. We propose that systemic acetazolamide reduces the basal neuronal activity of the prefrontal cortex, whereas increasing the afferent drive it receives from the hippocampus. In addition to being relevant to the clinical and side effects of acetazolamide, these results suggest that exogenous pH regulation can have diverse impacts on afferent signaling across the neocortex. We show that the carbonic anhydrase inhibitor acetazolamide enhances paired‐pulse facilitation – a short‐term form of synaptic plasticity – in hippocampal‐prefrontal cortical projections in vivo. Also, acetazolamide induces a net inhibitory effect on prefrontal unit activity. Thus, buffer regulation by this drug seems to reduce the spontaneous activity of the neocortex while increasing its responsiveness to afferent inputs. These findings reveal a new way of looking into the systemic effects of acetazolamide in the brain.

Direct brain recordings have provided important insights into how high-frequency activity captured through intracranial EEG (iEEG) supports human memory retrieval. The extent to which such activity is comprised of transient fluctuations that reflect the dynamic coordination of underlying neurons, however, remains unclear. Here, we simultaneously record iEEG, local field potential (LFP), and single unit activity in the human temporal cortex. We demonstrate that fast oscillations within the previously identified 80–120 Hz ripple band contribute to broadband high-frequency activity in the human cortex. These ripple oscillations exhibit a spectrum of amplitudes and durations related to the amount of underlying neuronal spiking. Ripples in the macro-scale iEEG are related to the number and synchrony of ripples in the micro-scale LFP, which in turn are related to the synchrony of neuronal spiking. Our data suggest that neural activity in the human temporal lobe is organized into transient bouts of ripple oscillations that reflect underlying bursts of spiking activity.

Prior studies of the neural representation of episodic memory in the human hippocampus have identified generic memory signals representing the categorical status of test items (novel vs. repeated), whereas other studies have identified item specific memory signals representing individual test items. Here, we report that both kinds of memory signals can be detected in hippocampal neurons in the same experiment. We recorded single-unit activity from four brain regions (hippocampus, amygdala, anterior cingulate, and prefrontal cortex) of epilepsy patients as they completed a continuous recognition task. The generic signal was found in all four brain regions, whereas the item-specific memory signal was detected only in the hippocampus and reflected sparse coding. That is, for the item-specific signal, each hippocampal neuron responded strongly to a small fraction of repeated words, and each repeated word elicited strong responding in a small fraction of neurons. The neural code was sparse, pattern-separated, and limited to the hippocampus, consistent with longstanding computational models.We suggest that the item-specific episodic memory signal in the hippocampus is fundamental, whereas the more widespread generic memory signal is derivative and is likely used by different areas of the brain to perform memory-related functions that do not require itemspecific information.

Interaction with a rapidly changing world relies on dynamically integrating sensory inflows and motor outflows. Numerous studies have shed light on sensorimotor transformations in the posterior parietal cortex (PPC), but most have emphasized reactive movements toward static targets, in which the relationship between the sensory cues and the motor goals is fixed, making it difficult to distinguish neural activity relating to the movement from that reflecting the stimulus. To resolve this, we recorded single-neuron activity from the PPC in monkeys performing a manual interception task in which the instantaneous stimulus location is decoupled from the impending movement direction by different target speeds. Intriguingly, the results suggest that the PPC explicitly conveys information concerned with the forthcoming movement, rather than the instantaneous stimuli, suggesting an intimate role in motor planning.

Encoding activity in the medial temporal lobe, presumably evoked by the presentation of stimuli (postonset activity), is known to predict subsequent memory. However, several independent lines of research suggest that preonset activity also affects subsequent memory.We investigated the role of preonset and postonset single-unit and multiunit activity recorded from epilepsy patients as they completed a continuous recognition task. In this task, words were presented in a continuous series and eventually began to repeat. For each word, the patient’s task was to decide whether it was novel or repeated. We found that preonset spiking activity in the hippocampus (when the word was novel) predicted subsequent memory (when the word was later repeated). Postonset activity during encoding also predicted subsequent memory, but was simply a continuation of preonset activity. The predictive effect of preonset spiking activitywasmuch stronger in the hippocampus than in three other brain regions (amygdala, anterior cingulate, and prefrontal cortex). In addition, preonset and postonset activity around the encoding of novel words did not predict memory performance for novel words (i.e., correctly classifying the word as novel), and preonset and postonset activity around the time of retrieval did not predict memory performance for repeated words (i.e., correctly classifying the word as repeated). Thus, the only predictive effect was between preonset activity (along with its postonset continuation) at the time of encoding and subsequent memory. Taken together, these findings indicate that preonset hippocampal activity does not reflect general arousal/attention but instead reflects what we term “attention to encoding.”

The efficacy of deep brain stimulation (DBS) therapy in Parkinson's disease (PD) patients is highly dependent on the precise localization of the target structures such as subthalamic nucleus (STN). Most commonly, microelectrode single unit activity (SUA) recordings are performed to refine the target. This process is heavily experience based and can be technically challenging. Local field potentials (LFPs), representing the activity of a population of neurons, can be obtained from the same microelectrodes used for SUA recordings and allow flexible online processing with less computational complexity due to lower sampling rate requirements. Although LFPs have been shown to contain biomarkers capable of predicting patients' symptoms and differentiating various structures, their use in the localization of the STN in the clinical practice is not prevalent. Here we present, for the first time, a randomized and double-blinded pilot study with intraoperative online LFP processing in which we compare the clinical benefit from SUA- versus LFP-based implantation. Ten PD patients referred for bilateral STN-DBS were randomly implanted using either SUA or LFP guided targeting in each hemisphere. Although both SUA and LFP were recorded for each STN, the electrophysiologist was blinded to one at a time. Three months postoperatively, the patients were evaluated by a neurologist blinded to the intraoperative recordings to assess the performance of each modality. While SUA-based decisions relied on the visual and auditory inspection of the raw traces, LFP-based decisions were given through an online signal processing and machine learning pipeline. We found a dramatic agreement between LFP- and SUA-based localization (16/20 STNs) providing adequate clinical improvement (51.8% decrease in 3-month contralateral motor assessment scores), with LFP-guided implantation resulting in greater average improvement in the discordant cases (74.9%, = 3 STNs). The selected tracks were characterized by higher activity in beta (11-32 Hz) and high-frequency (200-400 Hz) bands ( < 0.01) of LFPs and stronger non-linear coupling between these bands ( < 0.05). Our pilot study shows equal or better clinical benefit with LFP-based targeting. Given the robustness of the electrode interface and lower computational cost, more centers can utilize LFP as a strategic feedback modality intraoperatively, in conjunction to the SUA-guided targeting.

Cervical dystonia (CD) is a movement disorder characterized by a stereotyped pattern of involuntary turning or tilting of the head, often combined with jerky or tremulous movements. Hypotheses for the origin of CD have traditionally focused on the basal ganglia, but the contemporary discussion has considered the potential role of altered cerebellar function. As basal ganglia and the cerebellum largely project to the different thalamic nuclei, alterations in pallidal versus cerebellar output could be reflected in the activity of these thalamic regions. In this study, we analyzed a unique historic database where the single-unit activity of pallidal and cerebellar receiving thalamic nuclei was measured en route to the mesencephalon. We compared the single-unit activity of pallidal and cerebellar receiving thalamic neurons in three groups of CD patients manifesting as pure dystonia, pure jerky head oscillations, and dystonia plus jerky head oscillations. We found that among different CD manifestations, the characteristics of neuronal firing, such as burst versus a single-spike pattern, vary in cerebellar thalamic receiving nuclei. The cerebellar receiving region in patients with jerky oscillations had single-spikes neurons primarily. Wherein the manifestation of CD did not influence pattern distribution in the pallidal receiving thalamic area. We also found increased neuronal firing rate correlated with strength of theta-band neuronal oscillations during muscle contractions associated with dystonia. These results demonstrate that the manifestations of CD, such as pure dystonia, pure jerky head oscillations, or dystonia and jerky head oscillations, determine the thalamic neuronal properties.

Spreading depolarizations (SDs) are major pathophysiological events in several brain diseases, including migraine, brain ischemia, trauma, and epilepsy. However, the electrophysiological detection of SDs remains challenging. In this study, we examined changes in spikes (action potentials (APs) and action currents (ACs)) in layer 5 neurons of the somatosensory cortex of anesthetized rats during transient excitation at the onset of high-potassium-induced SDs. During whole-cell recordings, spike amplitude progressively decreased while spike duration increased during gradual neuronal depolarization at SD onset, culminating in depolarization block. A similar decrease in spike amplitude and increase in spike duration were observed during the pre-SD excitation phase in loose cell-attached recordings from single neurons and in cluster analysis of extracellular spikes. Multiple (non-clustered) unit activity also showed decrease in spike amplitude and spike broadening during pre-SD excitation. These findings suggest that dynamic changes in spike amplitude and duration at SD onset could serve as markers for SD detection.

Primate vision is reported to detect snakes and emotional faces faster than many other tested stimuli. Because the amygdala has been implicated in avoidance and emotional behaviors to biologically relevant stimuli and has neural connections with subcortical nuclei involved with vision, amygdalar neurons would be sensitive to snakes and emotional faces. In this study, neuronal activity in the amygdala was recorded from Japanese macaques (Macaca fuscata) during discrimination of eight categories of visual stimuli including snakes, monkey faces, human faces, carnivores, raptors, non-predators, monkey hands, and simple figures. Of 527 amygdalar neurons, 95 responded to one or more stimuli. Response characteristics of the amygdalar neurons indicated that they were more sensitive to the snakes and emotional faces than other stimuli. Response magnitudes and latencies of amygdalar neurons to snakes and monkey faces were stronger and faster than those to the other categories of stimuli, respectively. Furthermore, response magnitudes to the low pass-filtered snake images were larger than those to scrambled snake images. Finally, analyses of population activity of amygdalar neurons suggest that snakes and emotional faces were represented separately from the other stimuli during the 50-100 ms period from stimulus onset, and neutral faces during the 100-150 ms period. These response characteristics indicate that the amygdala processes fast and coarse visual information from emotional faces and snakes (but not other predators of primates) among the eight categories of the visual stimuli, and suggest that, like anthropoid primate visual systems, the amygdala has been shaped over evolutionary time to detect appearance of potentially threatening stimuli including both emotional faces and snakes, the first of the modern predators of primates.