Writing, Reading, and Translating the Clustered Protocadherin Cell Surface Recognition Code for Neural Circuit Assembly.

The ability of neurites of individual neurons to distinguish between themselves and neurites from other neurons and to avoid self (self-avoidance) plays a key role in neural circuit assembly in both invertebrates and vertebrates. Similarly, when individual neurons of the same type project into receptive fields of the brain, they must avoid each other to maximize target coverage (tiling). Counterintuitively, these processes are driven by highly specific homophilic interactions between cell surface proteins that lead to neurite repulsion rather than adhesion. Among these proteins in vertebrates are the clustered protocadherins (Pcdhs), and key to their function is the generation of enormous cell surface structural diversity. Here we review recent advances in understanding how a Pcdh cell surface code is generated by stochastic promoter choice; how this code is amplified and read by homophilic interactions between Pcdh complexes at the surface of neurons; and, finally, how the Pcdh code is translated to cellular function, which mediates self-avoidance and tiling and thus plays a central role in the development of complex neural circuits. Not surprisingly, Pcdh mutations that diminish homophilic interactions lead to wiring defects and abnormal behavior in mice, and sequence variants in the Pcdh gene cluster are associated with autism spectrum disorders in family-based genetic studies in humans.

Co-occurring ripple oscillations facilitate neuronal interactions between cortical locations in humans.

How the human cortex integrates ("binds") information encoded by spatially distributed neurons remains largely unknown. One hypothesis suggests that synchronous bursts of high-frequency oscillations ("ripples") contribute to binding by facilitating integration of neuronal firing across different cortical locations. While studies have demonstrated that ripples modulate local activity in the cortex, it is not known whether their co-occurrence coordinates neural firing across larger distances. We tested this hypothesis using local field-potentials and single-unit firing from four 96-channel microelectrode arrays in the supragranular cortex of 3 patients. Neurons in co-rippling locations showed increased short-latency co-firing, prediction of each other's firing, and co-participation in neural assemblies. Effects were similar for putative pyramidal and interneurons, during non-rapid eye movement sleep and waking, in temporal and Rolandic cortices, and at distances up to 16 mm (the longest tested). Increased co-prediction during co-ripples was maintained when firing-rate changes were equated, indicating that it was not secondary to non-oscillatory activation. Co-rippling enhanced prediction was strongly modulated by ripple phase, supporting the most common posited mechanism for binding-by-synchrony. Co-ripple enhanced prediction is reciprocal, synergistic with local upstates, and further enhanced when multiple sites co-ripple, supporting re-entrant facilitation. Together, these results support the hypothesis that trans-cortical co-occurring ripples increase the integration of neuronal firing of neurons in different cortical locations and do so in part through phase-modulation rather than unstructured activation.

Contributions of repeated learning to memory in humans: insights from single-neuron recordings in the hippocampus and amygdala.

Despite the well-established phenomenon of improved memory performance through repeated learning, studies investigating the associated neural mechanisms have yielded complex and sometimes contradictory findings, and direct evidence from human neuronal recordings has been lacking. This study employs single-neuron recordings with exceptional spatial-temporal resolution, combined with representational similarity analysis, to explore the neural dynamics within the hippocampus and amygdala during repeated learning. Our results demonstrate that in the hippocampus, repetition enhances both representational specificity and fidelity, with these features predicting learning times. Conversely, the amygdala exhibits heightened representational specificity and fidelity during initial learning but does not show improvement with repetition, suggesting functional specialization of the hippocampus and amygdala during different stages of the learning repetition. Specifically, the hippocampus appears to contribute to sustained engagement necessary for benefiting from repeated learning, while the amygdala may play a role in the representation of novel items. These findings contribute to a comprehensive understanding of the intricate interplay between these brain regions in memory processes. Significance statement  For over a century, understanding how repetition contributes to memory enhancement has captivated researchers, yet direct neuronal evidence has been lacking, with a primary focus on the hippocampus and a neglect of the neighboring amygdala. Employing advanced single-neuron recordings and analytical techniques, this study unveils a nuanced functional specialization within the amygdala-hippocampal circuit during various learning repetition. The results highlight the hippocampus's role in sustaining engagement for improved memory with repetition, contrasting with the amygdala's superior ability in representing novel items. This exploration not only deepens our comprehension of memory enhancement intricacies but also sheds light on potential interventions to optimize learning and memory processes.

Representation of Motion Direction in Visual Area MT Accounts for High Sensitivity to Centripetal Motion, Aligning with Efficient Coding of Retinal Motion Statistics.

The overrepresentation of centrifugal motion in the middle temporal visual area (area MT) has long been thought to provide an efficient coding strategy for optic flow processing. However, this overrepresentation compromises the detection of approaching objects, which is essential for survival. In the present study, we revisited this long-held notion by reanalyzing motion selectivity in area MT of three macaque monkeys (two males, one female) using random-dot stimuli instead of spot stimuli. We found no differences in the number of neurons tuned to centrifugal versus centripetal motion; however, centrifugally tuned neurons showed stronger tuning than centripetally tuned neurons. This was attributed to the heightened suppression of responses in centrifugal neurons to centripetal motion compared with that of centripetal neurons to centrifugal motion. Our modeling implies that this intensified suppression accounts for superior detection performance for weak centripetal motion stimuli. Moreover, through Fisher information analysis, we establish that the population sensitivity to motion direction in peripheral vision corresponds well with retinal motion statistics during forward locomotion. While these results challenge established concepts, considering the interplay of logarithmic Gaussian receptive fields and spot stimuli can shed light on the previously documented overrepresentation of centrifugal motion. Significantly, our findings reconcile a previously found discrepancy between MT activity and human behavior, highlighting the proficiency of peripheral MT neurons in encoding motion direction efficiently.SIGNIFICANCE STATEMENT The efficient coding hypothesis states that sensory neurons are tuned to specific, frequently experienced stimuli. Whereas previous work has found that neurons in the middle temporal (MT) area favor centrifugal motion, which results from forward locomotion, we show here that there is no such bias. Moreover, we found that the response of centrifugal neurons for centripetal motion was more suppressed than that of centripetal neurons for centrifugal motion. Combined with modeling, this provides a solution to a previously known discrepancy between reported centrifugal bias in MT and better detection of centripetal motion by human observers. Additionally, we show that population sensitivity in peripheral MT neurons conforms to an efficient code of retinal motion statistics during forward locomotion.

Neuronal Spiking Responses to Direct Electrical Microstimulation in the Human Cortex.

Microstimulation can modulate the activity of individual neurons to affect behavior, but the effects of stimulation on neuronal spiking are complex and remain poorly understood. This is especially challenging in the human brain where the response properties of individual neurons are sparse and heterogeneous. Here we use microelectrode arrays in the human anterior temporal lobe in 6 participants (3 female) to examine the spiking responses of individual neurons to microstimulation delivered through multiple distinct stimulation sites. We demonstrate that individual neurons can be driven with excitation or inhibition using different stimulation sites, which suggests an approach for providing direct control of spiking activity at the single-neuron level. Spiking responses are inhibitory in neurons that are close to the site of stimulation, while excitatory responses are more spatially distributed. Together, our data demonstrate that spiking responses of individual neurons can be reliably identified and manipulated in the human cortex.SIGNIFICANCE STATEMENT One of the major limitations in our ability to interface directly with the human brain is that the effects of stimulation on the activity of individual neurons remain poorly understood. This study examines the spiking responses of neurons in the human temporal cortex in response to pulses of microstimulation. This study finds that individual neurons can either be excited or inhibited depending on the site of stimulation. These data suggest an approach for modulating the spiking activity of individual neurons in the human brain.

Multimodal convergence in the pedunculopontine tegmental nucleus: Motor, sensory and theta-frequency inputs influence activity of single neurons.

The pedunculopontine tegmental nucleus of the brainstem (PPTg) has extensive interconnections and neuronal-behavioural correlates. It is implicated in movement control and sensorimotor integration. We investigated whether single neuron activity in freely moving rats is correlated with components of skilled forelimb movement, and whether individual neurons respond to both motor and sensory events. We found that individual PPTg neurons showed changes in firing rate at different times during the reach. This type of temporally specific modulation is like activity seen elsewhere in voluntary movement control circuits, such as the motor cortex, and suggests that PPTg neural activity is related to different specific events occurring during the reach. In particular, many neuronal modulations were time-locked to the end of the extension phase of the reach, when fine distal movements related to food grasping occur, indicating strong engagement of PPTg in this phase of skilled individual forelimb movements. In addition, some neurons showed brief periods of apparent oscillatory firing in the theta range at specific phases of the reach-to-grasp movement. When movement-related neurons were tested with tone stimuli, many also responded to this auditory input, allowing for sensorimotor integration at the cellular level. Together, these data extend the concept of the PPTg as an integrative structure in generation of complex movements, by showing that this function extends to the highly coordinated control of the forelimb during skilled reach to grasp movement, and that sensory and motor-related information converges on single neurons, allowing for direct integration at the cellular level.

A biophysical and statistical modeling paradigm for connecting neural physiology and function.

To understand single neuron computation, it is necessary to know how specific physiological parameters affect neural spiking patterns that emerge in response to specific stimuli. Here we present a computational pipeline combining biophysical and statistical models that provides a link between variation in functional ion channel expression and changes in single neuron stimulus encoding. More specifically, we create a mapping from biophysical model parameters to stimulus encoding statistical model parameters. Biophysical models provide mechanistic insight, whereas statistical models can identify associations between spiking patterns and the stimuli they encode. We used public biophysical models of two morphologically and functionally distinct projection neuron cell types: mitral cells (MCs) of the main olfactory bulb, and layer V cortical pyramidal cells (PCs). We first simulated sequences of action potentials according to certain stimuli while scaling individual ion channel conductances. We then fitted point process generalized linear models (PP-GLMs), and we constructed a mapping between the parameters in the two types of models. This framework lets us detect effects on stimulus encoding of changing an ion channel conductance. The computational pipeline combines models across scales and can be applied as a screen of channels, in any cell type of interest, to identify ways that channel properties influence single neuron computation.

Consciousness: a neurosurgical perspective.

Neurosurgeons are in a unique position to shed light on the neural basis for consciousness, not only by their clinical care of patients with compromised states of consciousness, but also by employing neurostimulation and neuronal recordings through intracranial electrodes in awake surgical patients, as well as during stages of sleep and anethesia. In this review, we discuss several aspects of consciousness, i.e., perception, memory, and willed actions, studied by electrical stimulation and single neuron recordings in the human brain. We demonstrate how specific neuronal activity underlie the emergence of concepts, memories, and intentions in human consciousness. We discuss the representation of specific conscious content by temporal lobe neurons and present the discovery of "concept cells" and the encoding and retrieval of memories by neurons in the medial temporal lobe. We review prefrontal and parietal neuronal activation that precedes conscious intentions to act. Taken together with other studies in the field, these findings suggest that specific conscious experience may arise from stochastic fluctuations of neuronal activity, reaching a dynamic threshold. Advances in brain recording and stimulation technology coupled with the rapid rise in artificial intelligence are likely to increase the amount and analysis capabilities of data obtained from the human brain, thereby improving the decoding of conscious and preconscious states and open new horizons for modulation of human cognitive functions such as memory and volition.

Behavioral and Neuronal Representation of Numerosity Zero in the Crow.

Different species of animals can discriminate numerosity, the countable number of objects in a set. The representations of countable numerosities have been deciphered down to the level of single neurons. However, despite its importance for human number theory, a special numerical quantity, the empty set (numerosity zero), has remained largely unexplored. We explored the behavioral and neuronal representation of the empty set in carrion crows. Crows were trained to discriminate small numerosities including the empty set. Performance data showed a numerical distance effect for the empty set in one crow, suggesting that the empty set and countable numerosities are represented along the crows' "mental number line." Single-cell recordings in the endbrain region nidopallium caudolaterale (NCL) showed a considerable proportion of NCL neurons tuned to the preferred numerosity zero. As evidenced by neuronal distance and size effects, NCL neurons integrated the empty set in the neural number line. A subsequent neuronal population analysis using a statistical classifier approach showed that the neuronal numerical representations were predictive of the crows' success in the task. These behavioral and neuronal data suggests that the conception of the empty set as a cognitive precursor of a zero-like number concept is not an exclusive property of the cerebral cortex of primates. Zero as a quantitative category cannot only be implemented in the layered neocortex of primates, but also in the anatomically distinct endbrain circuitries of birds that evolved based on convergent evolution.SIGNIFICANCE STATEMENT The conception of "nothing" as number "zero" is celebrated as one of the greatest achievements in mathematics. To explore whether precursors of zero-like concepts can be found in vertebrates with a cerebrum that anatomically differs starkly from our primate brain, we investigated this in carrion crows. We show that crows can grasp the empty set as a null numerical quantity that is mentally represented next to number one. Moreover, we show that single neurons in an associative avian cerebral region specifically respond to the empty set and show the same physiological characteristics as for countable quantities. This suggests that zero as a quantitative category can also be implemented in the anatomically distinct endbrain circuitries of birds that evolved based on convergent evolution.

Temporal Prediction Signals for Periodic Sensory Events in the Primate Central Thalamus.

Prediction of periodic event timing is an important function for everyday activities, while the exact neural mechanism remains unclear. Previous studies in nonhuman primates have demonstrated that neurons in the cerebellar dentate nucleus and those in the caudate nucleus exhibit periodic firing modulation when the animals attempt to detect a single omission of isochronous repetitive audiovisual stimuli. To understand how these subcortical signals are sent and processed through the thalamocortical pathways, we examined single-neuron activities in the central thalamus of two macaque monkeys (one female and one male). We found that three types of neurons responded to each stimulus in the sequence in the absence of movements. Reactive-type neurons showed sensory adaptation and gradually waned the transient response to each stimulus. Predictive-type neurons steadily increased the magnitude of the suppressive response, similar to neurons previously reported in the cerebellum. Switch-type neurons initially showed a transient response, but after several cycles, the direction of firing modulation reversed and the activity decreased for each repetitive stimulus. The time course of Switch-type activity was well explained by the weighted sum of activities of the other types of neurons. Furthermore, for only Switch-type neurons the activity just before stimulus omission significantly correlated with behavioral latency, indicating that this type of neuron may carry a more advanced signal in the system detecting stimulus omission. These results suggest that the central thalamus may transmit integrated signals to the cerebral cortex for temporal information processing, which are necessary to accurately predict rhythmic event timing.SIGNIFICANCE STATEMENT Several cortical and subcortical regions are involved in temporal information processing, and the thalamus will play a role in functionally linking them. The present study aimed to clarify how the paralaminar part of the thalamus transmits and modifies signals for temporal prediction of rhythmic events. Three types of thalamic neurons exhibited periodic activity when monkeys attempted to detect a single omission of isochronous repetitive stimuli. The activity of one type of neuron correlated with the behavioral latency and appeared to be generated by integrating the signals carried by the other types of neurons. Our results revealed the neuronal signals in the thalamus for temporal prediction of sensory events, providing a clue to elucidate information processing in the thalamocortical pathways.

Neural Code of Motor Planning and Execution during Goal-Directed Movements in Crows.

The planning and execution of head-beak movements are vital components of bird behavior. They require integration of sensory input and internal processes with goal-directed motor output. Despite its relevance, the neurophysiological mechanisms underlying action planning and execution outside of the song system are largely unknown. We recorded single-neuron activity from the associative endbrain area nidopallium caudolaterale (NCL) of two male carrion crows (Corvus corone) trained to plan and execute head-beak movements in a spatial delayed response task. The crows were instructed to plan an impending movement toward one of eight possible targets on the left or right side of a touchscreen. In a fraction of trials, the crows were prompted to plan a movement toward a self-chosen target. NCL neurons signaled the impending motion direction in instructed trials. Tuned neuronal activity during motor planning categorically represented the target side, but also specific target locations. As a marker of intentional movement preparation, neuronal activity reliably predicted both target side and specific target location when the crows were free to select a target. In addition, NCL neurons were tuned to specific target locations during movement execution. A subset of neurons was tuned during both planning and execution period; these neurons experienced a sharpening of spatial tuning with the transition from planning to execution. These results show that the avian NCL not only represents high-level sensory and cognitive task components, but also transforms behaviorally-relevant information into dynamic action plans and motor execution during the volitional perception-action cycle of birds.SIGNIFICANCE STATEMENT Corvid songbirds have become exciting new models for understanding complex cognitive behavior. As a key neural underpinning, the endbrain area nidopallium caudolaterale (NCL) represents sensory and memory-related task components. How such representations are converted into goal-directed motor output remained unknown. In crows, we report that NCL neurons are involved in the planning and execution of goal-directed movements. NCL neurons prospectively signaled motion directions in instructed trials, but also when the crows were free to choose a target. NCL neurons showed a target-specific sharpening of tuning with the transition from the planning to the execution period. Thus, the avian NCL not only represents high-level sensory and cognitive task components, but also transforms relevant information into action plans and motor execution.

Neuronal Firing and Waveform Alterations through Ictal Recruitment in Humans.

Analyzing neuronal activity during human seizures is pivotal to understanding mechanisms of seizure onset and propagation. These analyses, however, invariably using extracellular recordings, are greatly hindered by various phenomena that are well established in animal studies: changes in local ionic concentration, changes in ionic conductance, and intense, hypersynchronous firing. The first two alter the action potential waveform, whereas the third increases the "noise"; all three factors confound attempts to detect and classify single neurons. To address these analytical difficulties, we developed a novel template-matching-based spike sorting method, which enabled identification of 1239 single neurons in 27 patients (13 female) with intractable focal epilepsy, that were tracked throughout multiple seizures. These new analyses showed continued neuronal firing with widespread intense activation and stereotyped action potential alterations in tissue that was invaded by the seizure: neurons displayed increased waveform duration (p < 0.001) and reduced amplitude (p < 0.001), consistent with prior animal studies. By contrast, neurons in "penumbral" regions (those receiving intense local synaptic drive from the seizure but without neuronal evidence of local seizure invasion) showed stable waveforms. All neurons returned to their preictal waveforms after seizure termination. We conclude that the distinction between "core" territories invaded by the seizure versus "penumbral" territories is evident at the level of single neurons. Furthermore, the increased waveform duration and decreased waveform amplitude are neuron-intrinsic hallmarks of seizure invasion that impede traditional spike sorting and could be used as defining characteristics of local recruitment.SIGNIFICANCE STATEMENT Animal studies consistently show marked changes in action potential waveform during epileptic discharges, but acquiring similar evidence in humans has proven difficult. Assessing neuronal involvement in ictal events is pivotal to understanding seizure dynamics and in defining clinical localization of epileptic pathology. Using a novel method to track neuronal firing, we analyzed microelectrode array recordings of spontaneously occurring human seizures, and here report two dichotomous activity patterns. In cortex that is recruited to the seizure, neuronal firing rates increase and waveforms become longer in duration and shorter in amplitude as the neurons are recruited to the seizure, while penumbral tissue shows stable action potentials, in keeping with the "dual territory" model of seizure dynamics.

The Architecture of Human Memory: Insights from Human Single-Neuron Recordings.

Deciphering the mechanisms of human memory is a central goal of neuroscience, both from the point of view of the fundamental biology of memory and for its translational relevance. Here, we review some contributions that recordings from neurons in humans implanted with electrodes for clinical purposes have made toward this goal. Recordings from the medial temporal lobe, including the hippocampus, reveal the existence of two classes of cells: those encoding highly selective and invariant representations of abstract concepts, and memory-selective cells whose activity is related to familiarity and episodic retrieval. Insights derived from observing these cells in behaving humans include that semantic representations are activated before episodic representations, that memory content and memory strength are segregated, and that the activity of both types of cells is related to subjective awareness as expected from a substrate for declarative memory. Visually selective cells can remain persistently active for several seconds, thereby revealing a cellular substrate for working memory in humans. An overarching insight is that the neural code of human memory is interpretable at the single-neuron level. Jointly, intracranial recording studies are starting to reveal aspects of the building blocks of human memory at the single-cell level. This work establishes a bridge to cellular-level work in animals on the one hand, and the extensive literature on noninvasive imaging in humans on the other hand. More broadly, this work is a step toward a detailed mechanistic understanding of human memory that is needed to develop therapies for human memory disorders.

Interactome analysis of Caenorhabditis elegans synapses by TurboID-based proximity labeling.

Proximity labeling provides a powerful in vivo tool to characterize the proteome of subcellular structures and the interactome of specific proteins. The nematode Caenorhabditis elegans is one of the most intensely studied organisms in biology, offering many advantages for biochemistry. Using the highly active biotin ligase TurboID, we optimize here a proximity labeling protocol for C. elegans. An advantage of TurboID is that biotin's high affinity for streptavidin means biotin-labeled proteins can be affinity-purified under harsh denaturing conditions. By combining extensive sonication with aggressive denaturation using SDS and urea, we achieved near-complete solubilization of worm proteins. We then used this protocol to characterize the proteomes of the worm gut, muscle, skin, and nervous system. Neurons are among the smallest C. elegans cells. To probe the method's sensitivity, we expressed TurboID exclusively in the two AFD neurons and showed that the protocol could identify known and previously unknown proteins expressed selectively in AFD. The active zones of synapses are composed of a protein matrix that is difficult to solubilize and purify. To test if our protocol could solubilize active zone proteins, we knocked TurboID into the endogenous elks-1 gene, which encodes a presynaptic active zone protein. We identified many known ELKS-1-interacting active zone proteins, as well as previously uncharacterized synaptic proteins. Versatile vectors and the inherent advantages of using C. elegans, including fast growth and the ability to rapidly make and functionally test knock-ins, make proximity labeling a valuable addition to the armory of this model organism.

Properties and hemispheric differences of theta oscillations in the human hippocampus.

The left and right primate hippocampi (LH and RH) are thought to support distinct functions, but little is known about differences between the hemispheres at the neuronal level. We recorded single-neuron and local field potentials from the human hippocampus in epilepsy patients implanted with depth electrodes. We detected theta-frequency bouts of oscillatory activity while patients performed a visual recognition memory task. Theta appeared in bouts of 3.16 cycles, with sawtooth-shaped oscillations that had a prolonged downswing period. Outside the seizure onset zone, the average frequency of theta bouts was higher in the RH compared to the LH (6.0 vs. 5.3 Hz). LH theta bouts had lower amplitudes and a higher prevalence compared to the RH (26% vs. 21% of total time). Additionally, the RH contained a population of thin spiking visually tuned neurons that were not present in the LH. These data show that human theta appears in short oscillatory bouts whose properties vary between hemispheres, thereby revealing neurophysiological properties of the hippocampus that differ between the hemispheres.

A User's Guide to Generalized Integrate-and-Fire Models.

The generalized integrate-and-fire (GIF) neuron model accounts for some of the most fundamental behaviours of neurons within a compact and extensible mathematical framework. Here, we introduce the main concepts behind the design of the GIF model in terms that will be familiar to electrophysiologists, and show why its simple design makes this model particularly well suited to mimicking behaviours observed in experimental data. Along the way, we will build an intuition for how specific neuronal behaviours, such as spike-frequency adaptation, or electrical properties, such as ionic currents, can be formulated mathematically and used to extend integrate-and-fire models to overcome their limitations. This chapter will provide readers with no previous exposure to modelling a clear understanding of the strengths and limitations of GIF models, along with the mathematical intuitions required to digest more detailed and technical treatments of this topic.

Dendritic computations captured by an effective point neuron model.

Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent viewpoint simplifies the neuronal morphology as a point representing the soma, and the excitatory and inhibitory synaptic currents originated from the dendrites are treated as linearly summed at the soma. Despite its extensive applications, the validity of the synaptic current description remains unclear, and the existing point neuron framework fails to characterize the spatiotemporal aspects of dendritic integration supporting specific computations. Using electrophysiological experiments, realistic neuronal simulations, and theoretical analyses, we demonstrate that the traditional assumption of linear summation of synaptic currents is oversimplified and underestimates the inhibition effect. We then derive a form of synaptic integration current within the point neuron framework to capture dendritic effects. In the derived form, the interaction between each pair of synaptic inputs on the dendrites can be reliably parameterized by a single coefficient, suggesting the inherent low-dimensional structure of dendritic integration. We further generalize the form of synaptic integration current to capture the spatiotemporal interactions among multiple synaptic inputs and show that a point neuron model with the synaptic integration current incorporated possesses the computational ability of a spatial neuron with dendrites, including direction selectivity, coincidence detection, logical operation, and a bilinear dendritic integration rule discovered in experiment. Our work amends the modeling of synaptic inputs and improves the computational power of a modeling neuron within the point neuron framework.

Extent of Single-Neuron Activity Modulation by Hippocampal Interictal Discharges Predicts Declarative Memory Disruption in Humans.

Memory deficits are common in epilepsy patients. In these patients, the interictal EEG commonly shows interictal epileptiform discharges (IEDs). While IEDs are associated with transient cognitive impairments, it remains poorly understood why this is. We investigated the effects of human (male and female) hippocampal IEDs on single-neuron activity during a memory task in patients with medically refractory epilepsy undergoing depth electrode monitoring. We quantified the effects of hippocampal IEDs on single-neuron activity and the impact of this modulation on subjectively declared memory strength. Across all recorded neurons, the activity of 50 of 728 neurons were significantly modulated by IEDs, with the strongest modulation in the medial temporal lobe (33 of 416) and in particular the right hippocampus (12 of 58). Putative inhibitory neurons, as identified by their extracellular signature, were more likely to be modulated by IEDs than putative excitatory neurons (19 of 157 vs 31 of 571). Behaviorally, the occurrence of hippocampal IEDs was accompanied by a disruption of recognition of familiar images only if they occurred up to 2 s before stimulus onset. In contrast, IEDs did not impair encoding or recognition of novel images, indicating high temporal and task specificity of the effects of IEDs. The degree of modulation of individual neurons by an IED correlated with the declared confidence of a retrieval trial, with higher firing rates indicative of reduced confidence. Together, these data link the transient modulation of individual neurons by IEDs to specific declarative memory deficits in specific cell types, thereby revealing a mechanism by which IEDs disrupt medial temporal lobe-dependent declarative memory retrieval processes.SIGNIFICANCE STATEMENT Interictal epileptiform discharges (IEDs) are thought to be a cause of memory deficits in chronic epilepsy patients, but the underlying mechanisms are not understood. Utilizing single-neuron recordings in epilepsy patients, we found that hippocampal IEDs transiently change firing of hippocampal neurons and disrupted selectively the retrieval, but not encoding, of declarative memories. The extent of the modulation of the individual firing of hippocampal neurons by an IED predicted the extent of reduction of subjective retrieval confidence. Together, these data reveal a specific kind of transient cognitive impairment caused by IEDs and link this impairment to the modulation of the activity of individual neurons. Understanding the mechanisms by which IEDs impact memory is critical for understanding memory impairments in epilepsy patients.

Neural Signals in Red Nucleus during Reactive and Proactive Adjustments in Behavior.

The ability to adjust behavior is an essential component of cognitive control. Much is known about frontal and striatal processes that support cognitive control, but few studies have investigated how motor signals change during reactive and proactive adjustments in motor output. To address this, we characterized neural signals in red nucleus (RN), a brain region linked to motor control, as male and female rats performed a novel variant of the stop-signal task. We found that activity in RN represented the direction of movement and was strongly correlated with movement speed. Additionally, we found that directional movement signals were amplified on STOP trials before completion of the response and that the strength of RN signals was modulated when rats exhibited cognitive control. These results provide the first evidence that neural signals in RN integrate cognitive control signals to reshape motor outcomes reactively within trials and proactivity across them.SIGNIFICANCE STATEMENT Healthy human behavior requires the suppression or inhibition of errant or maladaptive motor responses, often called cognitive control. While much is known about how frontal brain regions facilitate cognitive control, less is known about how motor regions respond to rapid and unexpected changes in action selection. To address this, we recorded from neurons in the red nucleus, a motor region thought to be important for initiating movement in rats performing a cognitive control task. We show that red nucleus tracks motor plans and that selectivity was modulated on trials that required shifting from one motor response to another. Collectively, these findings suggest that red nucleus contributes to modulating motor behavior during cognitive control.

Choice-related activity and neural encoding in primary auditory cortex and lateral belt during feature-selective attention.

Selective attention is necessary to sift through, form a coherent percept of, and make behavioral decisions on the vast amount of information present in most sensory environments. How and where selective attention is employed in cortex and how this perceptual information then informs the relevant behavioral decisions is still not well understood. Studies probing selective attention and decision-making in visual cortex have been enlightening as to how sensory attention might work in that modality; whether or not similar mechanisms are employed in auditory attention is not yet clear. Therefore, we trained rhesus macaques on a feature-selective attention task, where they switched between reporting changes in temporal (amplitude modulation, AM) and spectral (carrier bandwidth) features of a broadband noise stimulus. We investigated how the encoding of these features by single neurons in primary (A1) and secondary (middle lateral belt, ML) auditory cortex was affected by the different attention conditions. We found that neurons in A1 and ML showed mixed selectivity to the sound and task features. We found no difference in AM encoding between the attention conditions. We found that choice-related activity in both A1 and ML neurons shifts between attentional conditions. This finding suggests that choice-related activity in auditory cortex does not simply reflect motor preparation or action and supports the relationship between reported choice-related activity and the decision and perceptual process.NEW & NOTEWORTHY We recorded from primary and secondary auditory cortex while monkeys performed a nonspatial feature attention task. Both areas exhibited rate-based choice-related activity. The manifestation of choice-related activity was attention dependent, suggesting that choice-related activity in auditory cortex does not simply reflect arousal or motor influences but relates to the specific perceptual choice.