Cortical and subcortical substrates of minutes and days-long object value memory in humans.

Obtaining valuable objects motivates many of our daily decisions. However, the neural underpinnings of object processing based on human value memory are not yet fully understood. Here, we used whole-brain functional magnetic resonance imaging (fMRI) to examine activations due to value memory as participants passively viewed objects before, minutes after, and 1-70 days following value training. Significant value memory for objects was evident in the behavioral performance, which nevertheless faded over the days following training. Minutes after training, the occipital, ventral temporal, interparietal, and frontal areas showed strong value discrimination. Days after training, activation in the frontal, temporal, and occipital regions decreased, whereas the parietal areas showed sustained activation. In addition, days-long value responses emerged in certain subcortical regions, including the caudate, ventral striatum, and thalamus. Resting-state analysis revealed that these subcortical areas were functionally connected. Furthermore, the activation in the striatal cluster was positively correlated with participants' performance in days-long value memory. These findings shed light on the neural basis of value memory in humans with implications for object habit formation and cross-species comparisons.

Value-Based Search Efficiency Is Encoded in the Substantia Nigra Reticulata Firing Rate, Spiking Irregularity and Local Field Potential.

Recent results show that valuable objects can pop out in visual search, yet its neural mechanisms remain unexplored. Given the role of substantia nigra reticulata (SNr) in object value memory and control of gaze, we recorded its single-unit activity while male macaque monkeys engaged in efficient or inefficient search for a valuable target object among low-value objects. The results showed that efficient search was concurrent with stronger inhibition and higher spiking irregularity in the target-present (TP) compared with the target-absent (TA) trials in SNr. Importantly, the firing rate differentiation of TP and TA trials happened within ∼100 ms of display onset, and its magnitude was significantly correlated with the search times and slopes (search efficiency). Time-frequency analyses of local field potential (LFP) after display onset revealed significant modulations of the gamma band power with search efficiency. The greater reduction of SNr firing in TP trials in efficient search can create a stronger disinhibition of downstream superior colliculus, which in turn can facilitate saccade to obtain valuable targets in competitive environments.

Prefrontal cortex encodes value pop-out in visual search.

Recent evidence demonstrates that long-term object value association can enhance visual search efficiency, a phenomenon known as value pop-out. However, the neural mechanism underlying this effect is not fully understood. Given the known role of the ventrolateral prefrontal cortex (vlPFC) in visual search and value memory, we recorded its single-unit activity (n = 526) in two macaque monkeys while they engaged in the value-driven search. Monkeys had to determine whether a high-value target was present within a variable number of low-value objects. Differential neural firing, as well as gamma-band power, indicated the presence of a target within ∼150ms of display onset. Notably, this differential activity was negatively correlated with search time and had reduced set-size dependence during efficient search. On the other hand, neural firing and its variability were higher in inefficient search. These findings implicate vlPFC in rapid detection of valuable targets which would be a crucial skill in competitive environments.

The Covid-19 pandemic had polarizing effects on trait scores depending on a person's resilience and predispositions: A longitudinal prospective study.

While Covid-19 is, first and foremost, a pernicious physical illness, its highly contagious nature has led to significant disruption in social life and psychological stress, occasionally resulting in dire mental health consequences that are still not fully understood. To address this issue, a prospective longitudinal design study was conducted by administering standard self-reporting questionnaires covering the NEO-five factor inventory (NEO-FFI), shyness, alexithymia, autism quotient, anxiety, depression, and sensory processing sensitivity (SPS). A total of 114 participants (of which 71.93% were females) with an average age of 30.29 (standard deviation = 11.04) completed the survey before and a few months after the pandemic. Results revealed the distribution of population scores to become more extreme in either positive or negative trait directions despite the stability of average trait scores across the population. Higher resilience was found to be positively correlated with improved trait scores post-pandemic but corona anxiety score was not correlated with trait score changes. In addition, in the subjects with moderate negative trait scores, agreeableness and autism scores and in subjects with high negative trait scores, openness, SPS and shyness scores were significantly correlated with trait scores changes post-pandemic. These results reveal the nuanced effects of the pandemic on the people's psychological well-being and highlight vulnerabilities for certain groups despite the overall stability of population that needs to be taken into account for mental health policies going forward.

A novel methodology for exact targeting of human and non-human primate brain structures and skull implants using atlas-based 3D reconstruction.

BACKGROUND: Accurate targeting of brain areas for stimulation and/or electrophysiological recording is key in many therapeutic applications and basic neuroscience research. Nevertheless, there are currently no end-to-end packages that accommodate all steps required for exact localization, visualization, and targeting regions of interest (ROIs) using standard atlases and for designing skull implants. NEW METHOD: We have implemented a new processing pipeline that addresses this issue in macaques and humans including various preprocessing, registration, warping procedures, and 3D reconstructions, and provide a noncommercial open-source graphical software which we refer to as the MATLAB-based reconstruction for recording and stimulation (MATres). RESULTS: The results of skull stripping were shown to work seamlessly in humans and monkeys. Linear and nonlinear warping of the standard atlas to the native space outperformed state-of-the-art using AFNI with improvements being more prominent in humans which had a more complex gyration geometry. The skull surface extracted by MATres using MRI images had more than 90% match with CT ground truth and could be used to design skull implants that conformed well to the skull's local curvature. COMPARISON WITH EXISTING METHOD(S): The accuracy of the various steps including skull stripping, standard atlas registration, and skull reconstruction in MATres was compared with and shown to outperform the AFNI. The localization accuracy of the recording chambers designed with MATres and implanted in two macaque monkeys was further confirmed using MRI imaging. CONCLUSIONS: Precise localization of ROIs offered by MATres can be used to plan electrode penetrations for recording and shallow or deep brain stimulation (DBS).

Salience memories formed by value, novelty and aversiveness jointly shape object responses in the prefrontal cortex and basal ganglia.

Ecological fitness depends on maintaining object histories to guide future interactions. Recent evidence shows that value memory changes passive visual responses to objects in ventrolateral prefrontal cortex (vlPFC) and substantia nigra reticulata (SNr). However, it is not known whether this effect is limited to reward history and if not how cross-domain representations are organized within the same or different neural populations in this corticobasal circuitry. To address this issue, visual responses of the same neurons across appetitive, aversive and novelty domains were recorded in vlPFC and SNr. Results showed that changes in visual responses across domains happened in the same rather than separate populations and were related to salience rather than valence of objects. Furthermore, while SNr preferentially encoded outcome related salience memory, vlPFC encoded salience memory across all domains in a correlated fashion, consistent with its role as an information hub to guide behavior.

EEG artifact removal using sub-space decomposition, nonlinear dynamics, stationary wavelet transform and machine learning algorithms.

Blind source separation (BSS) methods have received a great deal of attention in electroencephalogram (EEG) artifact elimination as they are routine and standard signal processing tools to remove artifacts and reserve desired neural information. On the other hand, a classifier should follow BSS methods to automatically identify artifactual sources and remove them in the following steps. In addition, removing all detected artifactual components leads to loss of information since some desired information related to neural activity leaks to these sources. So, an approach should be employed to detect and suppress the artifacts and reserve neural activity. This study introduces a novel method based on EEG and Poincare planes in the phase space to detect artifactual components estimated by second-order blind identification (SOBI). Artifacts are detected using a mixture of well-known conventional classifiers and were removed employing stationary wavelet transform (SWT) to reserve neural information. The proposed method is a combination of signal processing techniques and machine learning algorithms, including multi-layer perceptron (MLP), K-nearest neighbor (KNN), naïve Bayes, and support vector machine (SVM) which have significant results while applying our proposed method to different scenarios. Simulated, semi-simulated, and real EEG signals are employed to evaluate the proposed method, and several evaluation criteria are calculated. We achieved acceptable results, for example, 98% average accuracy and 97% average sensitivity in artifactual EEG component detection or about 2% as mean square error in EEG reconstruction after artifact removal. Results showed that the proposed method is effective and can be used in future studies as we have considered different real-world scenarios to evaluate it.

The effects of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) on the cognitive and motor functions in rodents: A systematic review and meta-analysis.

Memory and motor deficits are commonly identified in Parkinson's disease (PD). 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is transformed to MPP+ via monoamine oxidase B (MAOB), which causes oxidative stress and destroys dopaminergic (DA) neurons in substantia nigra pars compacta (SNc) and is widely used to create animal models of PD. However, to-date, a comprehensive analysis of the MPTP effects on various aspects of PD does not exist. Here, we provide a systematic review and meta-analysis on the MPTP effects on memory and motor functions by analyzing 51 studies on more than one thousand animals mainly including rats and mice. The results showed that in addition to motor functions such as coordination, balance and locomotor activity, MPTP significantly affects various mnemonic processes including spatial memory, working memory, recognition memory, and associative memory compared with the control group with some differences between systemic and intra-nigral injections on spatial memory, familiar object recognition, and anxiety-like behaviors. Nevertheless, our analysis failed to find systematic relationship between MPTP injection protocol parameters reported and the extent of the induced PD symptoms that can be a cause of concern for replicability of MPTP studies.

Stimulus presentation can enhance spiking irregularity across subcortical and cortical regions.

Stimulus presentation is believed to quench neural response variability as measured by fano-factor (FF). However, the relative contributions of within-trial spike irregularity and trial-to-trial rate variability to FF fluctuations have remained elusive. Here, we introduce a principled approach for accurate estimation of spiking irregularity and rate variability in time for doubly stochastic point processes. Consistent with previous evidence, analysis showed stimulus-induced reduction in rate variability across multiple cortical and subcortical areas. However, unlike what was previously thought, spiking irregularity, was not constant in time but could be enhanced due to factors such as bursting abating the quench in the post-stimulus FF. Simulations confirmed plausibility of a time varying spiking irregularity arising from within and between pool correlations of excitatory and inhibitory neural inputs. By accurate parsing of neural variability, our approach reveals previously unnoticed changes in neural response variability and constrains candidate mechanisms that give rise to observed rate variability and spiking irregularity within brain regions.

Gustatory Cortex Is Involved in Evidence Accumulation during Food Choice.

Food choice is one of the most fundamental and most frequent value-based decisions for all animals including humans. However, the neural circuitry involved in food-based decisions is only recently being addressed. Given the relatively fast dynamics of decision formation, electroencephalography (EEG)-informed fMRI analysis is highly beneficial for localizing this circuitry in humans. Here, by using the EEG correlates of evidence accumulation in a simultaneously recorded EEG-fMRI dataset, we found a significant role for the right temporal-parietal operculum (PO) and medial insula including gustatory cortex (GC) in binary choice between food items. These activations were uncovered by using the "EEG energy" (power 2 of EEG) as the BOLD regressor and were missed if conventional analysis with the EEG signal itself were to be used, in agreement with theoretical predictions for EEG and BOLD relations. No significant positive correlations were found with higher powers of EEG (powers 3 or 4) pointing to specificity and sufficiency of EEG energy as the main correlate of the BOLD response. This finding extends the role of cortical areas traditionally involved in palatability processing to value-based decision-making and offers the "EEG energy" as a key regressor of BOLD response in simultaneous EEG-fMRI designs.

Coordinated multivoxel coding beyond univariate effects is not likely to be observable in fMRI data.

Simultaneous recording of activity across brain regions can contain additional information compared to regional recordings done in isolation. In particular, multivariate pattern analysis (MVPA) across voxels has been interpreted as evidence for distributed coding of cognitive or sensorimotor processes beyond what can be gleaned from a collection of univariate effects (UVE) using functional magnetic resonance imaging (fMRI). Here, we argue that regardless of patterns revealed, conventional MVPA is merely a decoding tool with increased sensitivity arising from considering a large number of 'weak classifiers' (i.e., single voxels) in higher dimensions. We propose instead that 'real' multivoxel coding should result in changes in higher-order statistics across voxels between conditions such as second-order multivariate effects (sMVE). Surprisingly, analysis of conditions with robust multivariate effects (MVE) revealed by MVPA failed to show significant sMVE in two species (humans and macaques). Further analysis showed that while both MVE and sMVE can be readily observed in the spiking activity of neuronal populations, the slow and nonlinear hemodynamic coupling and low spatial resolution of fMRI activations make the observation of higher-order statistics between voxels highly unlikely. These results reveal inherent limitations of fMRI signals for studying coordinated coding across voxels. Together, these findings suggest that care should be taken in interpreting significant MVPA results as representing anything beyond a collection of univariate effects.

Localizing sensory processing sensitivity and its subdomains within its relevant trait space: a data-driven approach.

Sensitivity arising from enhanced processing of external and internal stimuli or sensory processing sensitivity (SPS) is known to be present in a sizable portion of the population. Yet a clear localization of SPS and its subdomains with respect to other relevant traits is currently lacking. Here, we used a data-driven approach including hierarchical clustering, t-distributed stochastic neighbor embedding (t-SNE) and graph learning to portrait SPS as measured by Highly Sensitive Person Scale (HSPS) in relation to the Big-Five Inventory (neuroticism, extraversion, openness, agreeableness, and conscientiousness) as well as to shyness, alexithymia, autism quotient, anxiety, and depression (11 total traits) using data from more than 800 participants. Analysis revealed SPS subdomains to be divided between two trait clusters with questions related to aesthetic sensitivity (AES) falling within a cluster of mainly positive traits and neighbored by openness while questions addressing ease of excitation (EOE) and low sensory threshold (LST) to be mostly contained within a cluster of negative traits and neighbored by neuroticism. A similar spread across clusters was seen for questions addressing autism consistent with it being a spectrum disorder, in contrast, alexithymia subdomains were closely fit within the negative cluster. Together, our results support the view of SPS as a distinct yet non-unitary trait and provide insights for further refinements of the current SPS concept and scales.

Common coding of expected value and value uncertainty memories in the prefrontal cortex and basal ganglia output.

Recent evidence implicates both basal ganglia and ventrolateral prefrontal cortex (vlPFC) in encoding value memories. However, comparative roles of cortical and basal nodes in value memory are not well understood. Here, single-unit recordings in vlPFC and substantia nigra reticulata (SNr), within macaque monkeys, revealed a larger value signal in SNr that was nevertheless correlated with and had a comparable onset to the vlPFC value signal. The value signal was maintained for many objects (>90) many weeks after reward learning and was resistant to extinction in both regions and to repetition suppression in vlPFC. Both regions showed comparable granularity in encoding expected value and value uncertainty, which was paralleled by enhanced gaze bias during free viewing. The value signal dynamics in SNr could be predicted by combining responses of vlPFC neurons according to their value preferences consistent with a scheme in which cortical neurons reached SNr via direct and indirect pathways.

Brain Networks Sensitive to Object Novelty, Value, and Their Combination.

Novel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain responses to visual fractal patterns varying in either novelty or value dimensions and compared the results with the structure of functionally connected brain networks determined at rest. The results show that different brain networks possess unique combinations of novelty and value coding. One network identified in the ventral temporal cortex preferentially encoded object novelty, whereas another in the parietal cortex encoded the learned value. A third network, broadly composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, encoded both dimensions with similar activation dynamics. Our results support the emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

Drift-diffusion explains response variability and capacity for tracking objects.

Being able to track objects that surround us is key for planning actions in dynamic environments. However, rigorous cognitive models for tracking of one or more objects are currently lacking. In this study, we asked human subjects to judge the time to contact (TTC) a finish line for one or two objects that became invisible shortly after moving. We showed that the pattern of subject responses had an error variance best explained by an inverse Gaussian distribution and consistent with the output of a biased drift-diffusion model. Furthermore, we demonstrated that the pattern of errors made when tracking two objects showed a level of dependence that was consistent with subjects using a single decision variable for reporting the TTC for two objects. This finding reveals a serious limitation in the capacity for tracking multiple objects resulting in error propagation between objects. Apart from explaining our own data, our approach helps interpret previous findings such as asymmetric interference when tracking multiple objects.

Prefrontal Cortex Represents Long-Term Memory of Object Values for Months.

As a central hub for cognitive control, prefrontal cortex (PFC) is thought to utilize memories. However, unlike working or short-term memory, the neuronal representation of long-term memory in PFC has not been systematically investigated. Using single-unit recordings in macaques, we show that PFC neurons rapidly update and maintain responses to objects based on short-term reward history. Interestingly, after repeated object-reward association, PFC neurons continue to show value-biased responses to objects even in the absence of reward. This value-biased response is retained for several months after training and is resistant to extinction and to interference from new object-reward learning for many complex objects (>90). Accordingly, the monkeys remember the values of the learned objects for several months in separate testing. These findings reveal that in addition to flexible short-term and low-capacity memories, primate PFC represents stable long-term and high-capacity memories, which could prioritize valuable objects far into the future.

Temporal-prefrontal cortical network for discrimination of valuable objects in long-term memory.

Remembering and discriminating objects based on their previously learned values are essential for goal-directed behaviors. While the cerebral cortex is known to contribute to object recognition, surprisingly little is known about its role in retaining long-term object-value associations. To address this question, we trained macaques to arbitrarily associate small or large rewards with many random fractal objects (>100) and then used fMRI to study the long-term retention of value-based response selectivity across the brain. We found a pronounced long-term value memory in core subregions of temporal and prefrontal cortex where, several months after training, fractals previously associated with high reward ("good" stimuli) elicited elevated fMRI responses compared with those associated with low reward ("bad" stimuli). Similar long-term value-based modulation was also observed in subregions of the striatum, amygdala, and claustrum, but not in the hippocampus. The value-modulated temporal-prefrontal subregions showed strong resting-state functional connectivity to each other. Moreover, for areas outside this core, the magnitude of long-term value responses was predicted by the strength of resting-state functional connectivity to the core subregions. In separate testing, free-viewing gaze behavior indicated that the monkeys retained stable long-term memory of object value. These results suggest an implicit and high-capacity memory mechanism in the temporal-prefrontal circuitry and its associated subcortical regions for long-term retention of object-value memories that can guide value-oriented behavior.

Parallel basal ganglia circuits for decision making.

The basal ganglia control body movements, mainly, based on their values. Critical for this mechanism is dopamine neurons, which sends unpredicted value signals, mainly, to the striatum. This mechanism enables animals to change their behaviors flexibly, eventually choosing a valuable behavior. However, this may not be the best behavior, because the flexible choice is focused on recent, and, therefore, limited, experiences (i.e., short-term memories). Our old and recent studies suggest that the basal ganglia contain separate circuits that process value signals in a completely different manner. They are insensitive to recent changes in value, yet gradually accumulate the value of each behavior (i.e., movement or object choice). These stable circuits eventually encode values of many behaviors and then retain the value signals for a long time (i.e., long-term memories). They are innervated by a separate group of dopamine neurons that retain value signals, even when no reward is predicted. Importantly, the stable circuits can control motor behaviors (e.g., hand or eye) quickly and precisely, which allows animals to automatically acquire valuable outcomes based on historical life experiences. These behaviors would be called 'skills', which are crucial for survival. The stable circuits are localized in the posterior part of the basal ganglia, separately from the flexible circuits located in the anterior part. To summarize, the flexible and stable circuits in the basal ganglia, working together but independently, enable animals (and humans) to reach valuable goals in various contexts.

Flexible and Stable Value Coding Areas in Caudate Head and Tail Receive Anatomically Distinct Cortical and Subcortical Inputs.

Anatomically distinct areas within the basal ganglia encode flexible- and stable-value memories for visual objects (Hikosaka et al., 2014), but an important question remains: do they receive inputs from the same or different brain areas or neurons? To answer this question, we first located flexible and stable value-coding areas in the caudate head (CDh) and caudate tail (CDt) of two rhesus macaque monkeys, and then injected different retrograde tracers into these areas of each monkey. We found that CDh and CDt received different inputs from several cortical and subcortical areas including temporal cortex, prefrontal cortex, cingulate cortex, amygdala, claustrum and thalamus. Superior temporal cortex and inferior temporal cortex projected to both CDh and CDt, with more CDt-projecting than CDh-projecting neurons. In superior temporal cortex and dorsal inferior temporal cortex, layers 3 and 5 projected to CDh while layers 3 and 6 projected to CDt. Prefrontal and cingulate cortex projected mostly to CDh bilaterally, less to CDt unilaterally. A cluster of neurons in the basolateral amygdala projected to CDt. Rostral-dorsal claustrum projected to CDh while caudal-ventral claustrum projected to CDt. Within the thalamus, different nuclei projected to either CDh or CDt. The medial centromedian nucleus and lateral parafascicular nucleus projected to CDt while the medial parafascicular nucleus projected to CDh. The inferior pulvinar and lateral dorsal nuclei projected to CDt. The ventral anterior and medial dorsal nuclei projected to CDh. We found little evidence of neurons projecting to both CDh and CDt across the brain. These data suggest that CDh and CDt can control separate functions using anatomically separate circuits. Understanding the roles of these striatal projections will be important for understanding how value memories are created and stored.

Ecological Origins of Object Salience: Reward, Uncertainty, Aversiveness, and Novelty.

Among many objects around us, some are more salient than others (i.e., attract our attention automatically). Some objects may be inherently salient (e.g., brighter), while others may become salient by virtue of their ecological relevance through experience. However, the role of ecological experience in automatic attention has not been studied systematically. To address this question, we let subjects (macaque monkeys) view a large number of complex objects (>300), each experienced repeatedly (>5 days) with rewarding, aversive or no outcome association (mere-perceptual exposure). Test of salience was done on separate days using free viewing with no outcome. We found that gaze was biased among the objects from the outset, affecting saccades to objects or fixations within objects. When the outcome was rewarding, gaze preference was stronger (i.e., positive) for objects with larger or equal but uncertain rewards. The effects of aversive outcomes were variable. Gaze preference was positive for some outcome associations (e.g., airpuff), but negative for others (e.g., time-out), possibly due to differences in threat levels. Finally, novel objects attracted gaze, but mere perceptual exposure of objects reduced their salience (learned negative salience). Our results show that, in primates, object salience is strongly influenced by previous ecological experience and is supported by a large memory capacity. Owing to such high capacity for learned salience, the ability to rapidly choose important objects can grow during the entire life to promote biological fitness.