Biology subjects

Paz, R.

Publications and source records attributed to Paz, R..

16 recordsLinked to original sources

bioRxiv2025

Sleep Renormalizes Negative Emotional Generalization

Overgeneralization of negative experiences, in which aversive responses spread to otherwise safe stimuli, often co-occurs with sleep disruption, and both are central features of anxiety and posttraumatic stress disorder (PTSD). Here, we show that sleep shifts emotional generalization away from the negative and toward the positive. Across three experiments combining behavior, fMRI, and sleep electrophysiology, participants learned to associate three faces with positive, negative, or neutral outcomes. Participants were tested using morphed faces that blended the original stimuli in varying proportions. Immediate generalization was assessed post-learning, and delayed generalization was assessed after overnight sleep or daytime wakefulness. Behaviorally, we found that sleep selectively promotes positive generalization, whereas prolonged daytime wakefulness favors generalization of the negative face. In the fMRI scanner, amygdala and limbic activity during outcome processing predicted stronger immediate generalization of the negative face, and subsequent shift from negative to positive face generalization that occurred only after sleep. Overnight sleep spindle activity, extracted from high-density sleep EEG, positively correlated both with positive face generalization and with the shift from negative to positive generalization following sleep. These findings reveal a potential neural mechanism by which sleep attenuates negative bias and enhances positive representations, suggesting a potential method to buffer against maladaptive generalization in anxiety and PTSD.

neuroscience↗

bioRxiv2024

Integrated Ising Model with global inhibition for decision making

Humans and other organisms make decisions choosing between different options, with the aim to maximize the reward and minimize the cost. The main theoretical framework for modeling the decision-making process has been based on the highly successful drift-diffusion model, which is a simple tool for explaining many aspects of this process. However, new observations challenge this model. Recently, it was found that inhibitory tone increases during high cognitive load and situations of uncertainty, but the origin of this phenomenon is not understood. Motivated by this observation, we extend a recently developed model for decision making while animals move towards targets in real space. We introduce an integrated Ising-type model, that includes global inhibition, and use it to explore its role in decision-making. This model can explain how the brain may utilize inhibition to improve its decision-making accuracy. Compared to experimental results, this model suggests that the regime of the brains decision-making activity is in proximity to a critical transition line between the ordered and disordered. Within the model, the critical region near the transition line has the advantageous property of enabling a significant decrease in error with a small increase in inhibition and also exhibits unique properties with respect to learning and memory decay.

biophysics↗

bioRxiv2024

Inhibitory mechanisms in the prefrontal-cortex differentially mediate Putamen activity during valence-based learning

Learning from appetitive and aversive stimuli involves interactions between the prefrontal cortex and subcortical structures. Preclinical and theoretical studies indicate that inhibition is essential in regulating the relevant neural circuitry. Here, we demonstrate that GABA, the main inhibitory neurotransmitter in the central nervous system, differentially affects how the dACC interacts with subcortical structures during appetitive and aversive learning in humans. Participants engaged in tasks involving appetitive and aversive learning, while using functional magnetic resonance spectroscopy (MRS) at 7T to track GABA concentrations in the dACC, alongside whole-brain fMRI scans to assess BOLD activation. During appetitive learning, dACC GABA concentrations were negatively correlated with learning performance and BOLD activity measured from the dACC and the Putamen. These correlations were absent during aversive learning, where dACC GABA concentrations negatively correlated with the connectivity between the dACC and the Putamen. Our results show that inhibition in the dACC mediates appetitive and aversive learning in humans through distinct mechanisms.

neuroscience↗

bioRxiv2021

Emotion increases the similarity between neural representations of pictures, but not their perceived similarity.

Stimuli that evoke the same feelings can nevertheless look different and have different semantic meanings. Although we know much about the neural representation of emotion, the neural underpinnings that govern judgements of emotional similarity are unknown. One possibility is that the same brain regions will represent similarity between emotional and neutral stimuli, perhaps with different strengths. Alternatively, emotional similarity could be coded in separate regions, possibly those known to express emotional valence and arousal preferentially. In behaviour, the extent to which people consider similarity along the emotional dimension when they evaluate the overall similarity between stimuli has never been investigated. While the emotional features of stimuli may dominate explicit ratings of similarity, it is also possible that people neglect the emotional dimension as irrelevant. We contrasted these hypotheses with two measures of similarity and two different databases of complex negative and neutral pictures, the second of which afforded exquisite control over semantic and visual attributes. Emotion increased neural similarity in a set of regions that represented both emotional and neutral stimuli, including the inferior temporal cortex, the fusiform face area, and the precuneus. Emotion also increased neural similarity in early visual cortex, anterior insula and dorsal anterior cingulate cortex, despite no increase in BOLD-signal amplitudes in these regions. Despite the stronger neural similarity between emotional stimuli, participants rated pictures taken from two distinct emotional categories as equally similar. These results contribute to our understanding of how emotion is represented within a general conceptual workspace.

neuroscience↗

bioRxiv2021

Automatic recognition of macaque facial expressions for detection of affective states

Internal affective states produce external manifestations such as facial expressions. In humans, the Facial Action Coding System (FACS) is widely used to objectively quantify the elemental facial action-units (AUs) that build complex facial expressions. A similar system has been developed for macaque monkeys - the Macaque Facial Action Coding System (MaqFACS); yet unlike the human counterpart, which is already partially replaced by automatic algorithms, this system still requires labor-intensive coding. Here, we developed and implemented the first prototype for automatic MaqFACS coding. We applied the approach to the analysis of behavioral and neural data recorded from freely interacting macaque monkeys. The method achieved high performance in recognition of six dominant AUs, generalizing between conspecific individuals (Macaca mulatta) and even between species (Macaca fascicularis). The study lays the foundation for fully automated detection of facial expressions in animals, which is crucial for investigating the neural substrates of social and affective states.

neuroscience↗

bioRxiv2020

Frequency matters: Up- and Down-Regulation of Dopamine Tone Induces Similar Frequency Shifts in Cortico-Basal Ganglia Beta Oscillations

Beta oscillatory activity (13-30Hz) is pervasive within the cortico-basal ganglia (CBG) network. Studies in Parkinsons disease (PD) patients and animal models suggested that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine-tone remains unclear. We recorded neural activity in the CBG network of non-human-primates (NHP) while acutely up- and down-modulating dopamine levels. Further, we assessed changes in beta oscillations of PD patients following acute and chronic changes in dopamine-tone. Beta oscillation frequency was strongly coupled with dopamine-tone in both NHPs and human patients. In contrast, power, coherence between single-units and LFP, and spike-LFP phase-locking were not systematically regulated by dopamine levels. These results demonstrate via causal manipulations that frequency, rather than other properties, is the key property of pathological oscillations in the CBG networks. These insights can lead to improvements in understanding of CBG physiology, PD progression tracking and patient care.

neuroscience↗

bioRxiv2020

Behavioral elements and neural circuits underlying exploratory decisions in normative anxiety

Exploration reduces uncertainty about the environment and improves the quality of future decisions, but at the cost of provisional uncertain and suboptimal outcomes. Although anxiety promotes intolerance to uncertainty, it remains unclear whether and by which mechanisms anxiety modulates exploratory decision-making. We use a dynamic three-armed-bandit task and find that higher trait-anxiety increases exploration, which in turn harms overall performance. We identify two distinct behavioral sources: first, decisions made by anxious individuals were guided towards reduction of uncertainty; and second, decisions were less guided by immediate value gains. Imaging (fMRI) revealed that anxiety correlated negatively with the representation of expected-value in the dorsal-anterior-cingulate-cortex, and in contrast, positively with the representation of uncertainty in the anterior-insula. Moreover, the findings were similar in both loss and gain domains, and demonstrated that affective trait modulates exploration and results in an inverse-U-shaped relationship between anxiety and overall performance. We conclude that a shift in balance towards representation of uncertainty in the insula prevails over reduced value representation in the dACC, and entails maladaptive decision-making in individuals with higher normal-range anxiety.

neuroscience↗

bioRxiv2020

Deep learning enables the design of functional de novo antimicrobial proteins

Protein sequences are highly dimensional and present one of the main problems for the optimization and study of sequence-structure relations. The intrinsic degeneration of protein sequences is hard to follow, but the continued discovery of new protein structures has shown that there is convergence in terms of the possible folds that proteins can adopt, such that proteins with sequence identities lower than 30% may still fold into similar structures. Given that proteins share a set of conserved structural motifs, machine-learning algorithms can play an essential role in the study of sequence-structure relations. Deep-learning neural networks are becoming an important tool in the development of new techniques, such as protein modeling and design, and they continue to gain power as new algorithms are developed and as increasing amounts of data are released every day. Here, we trained a deep-learning model based on previous recurrent neural networks to design analog protein structures using representations learning based on the evolutionary and structural information of proteins. We test the capabilities of this model by creating de novo variants of an antifungal peptide, with sequence identities of 50% or lower relative to the wild-type (WT) peptide. We show by in silico approximations, such as molecular dynamics, that the new variants and the WT peptide can successfully bind to a chitin surface with comparable relative binding energies. These results are supported by in vitro assays, where the de novo designed peptides showed antifungal activity that equaled or exceeded the WT peptide.

bioengineering↗

bioRxiv2019

Energy-based and energy-free food-consumption are correlated in captive non-human-primates: A novel dispenser for feeding and behavioral enrichment

Non-human primates (NHP) provide an important model for studying biological mechanisms that underlie behavior and cognition, and are crucial for supplying translational knowledge that can aid the development of new clinical approaches. At the same time, the importance of the 3Rs to minimize suffering during experiments encouraged the development of environmental enrichment programs. Among them, tools for feeding and foraging are central. However, it remains unclear whether the behavioral enrichment tools are used by the animals only for feeding and to satisfy hunger (and hence for survival), or whether these feeding tools serve also as behavioral enrichment in itself (namely, the animals enjoy it per-se). To answer this, we designed a novel dispenser method - that requires significant yet reasonable energetic effort to obtain food - and tested food consumption via the dispenser compared to free-access, namely that did not require any effort on the animal side. We found that primates consumed food from both the dispenser and when presented in free-access, and importantly, that the consumption via the dispenser was in correlation with the consumption in free-access. This was similar across different subjects, different times during the day, and different types of food. We suggest that monkeys can benefit from using the dispenser for food consumption, but also benefit from it for play (i.e. as behavioral enrichment in itself). Such an approach allows non-human-primates to preserve their natural food procurement activities.

animal behavior and cognition↗

bioRxiv2019

Right on time: prediction-errors bidirectionally bias time perception

The brain updates internal representation of the environment by using the mismatch between the predicted state/outcome and the actual one, termed prediction-error. In parallel, time perception in the sub-second range is crucial for many behaviors such as movement, learning, memory, attention and speech. Both time-perception and prediction-errors are essential for everyday life function of an organism, and interestingly, the striatum was shown to be independently involved in both functions. We therefore hypothesized that the putative shared circuitry might induce behavioral interaction, namely that prediction-errors might bias time perception. To examine this, participants performed a time-duration discrimination task in the presence of positive and negative prediction-errors that were irrelevant and independent of the main task. We find that positive/negative prediction-errors induce a bias in time perception by increasing/decreasing the perceived time, respectively. Using functional imaging, we identify an interaction in Putamen activity between encoding of prediction-error and performance in the discrimination task. A model that accounts for the behavioral and physiological observations confirms that the interaction in regional activations for prediction-errors and time-estimation underlies the observed bias. Our results demonstrate that these two presumably independent roles of the striatum can actually interfere or aid one another in specific scenarios.

neuroscience↗

bioRxiv2019

Shared neural codes for eye-gaze and valence

The eye-gaze of others is a prominent social cue in primates and crucial for communication1-7, and atypical processing occurs in several conditions as autism-spectrum-disorder (ASD)1,9-14. The neural mechanisms that underlie eye-gaze remain vague, and it is still debated if these computations developed in dedicated neural circuits or shared with non-social elements. In many species, eye-gaze signals a threat and elicits anxiety, yet can also serve as a predictor for the outcome of the encounter: negative or positive2,4,8. Here, we hypothesized and find that neural codes overlap between eye-gaze and valence. Monkeys participated in a modified version of the human-intruder-test8,15 that includes direct and averted eye-gaze and interleaved with blocks of aversive and appetitive conditioning16,17. We find that single-neurons in the amygdala encode gaze18, whereas neurons in the anterior-cingulate-cortex encode the social context19,20 but not gaze. We identify a shared amygdala circuitry where neural responses to averted and direct gaze parallel the responses to appetitive and aversive value, correspondingly. Importantly, we distinguish two shared coding mechanisms: a shared-intensity scheme that is used for gaze and the unconditioned-stimulus, and a shared-activity scheme that is used for gaze and the conditioned-stimulus. The shared-intensity points to overlap in circuitry, whereas the shared-activity requires also correlated activity. Our results demonstrate that eye-gaze is coded as a signal of valence, yet also as the expected value of the interaction. The findings may suggest new insights into the mechanisms that underlie the malfunction of eye-gaze in ASD and the comorbidity with impaired social skills and anxiety.

neuroscience↗

bioRxiv2019

A geometric representation unveils rule-learning dynamics in primate neurons

Primates can quickly and advantageously adopt new behaviors based on changing stimuli relationships. We studied acquisition of a classification task while recording single neurons in the dorsal-anterior-cingulate-cortex (dACC) and the Striatum. Monkeys performed trial-by-trial classification on a rich set of multi-cue patterns, allowing de-novo learning every few days. To examine neural dynamics during the learning itself, we represent each rule with a spanning set of the space formed by the stimuli features. Because neural preference can be expressed by feature combinations, we can track neural dynamics in geometrical terms in this space, allowing a compact description of neural trajectories by observing changes in either vector-magnitude and/or angle-to- rule. We find that a large fraction of cells in both regions follow the behavior during learning. Neurons in the dACC mainly rotate towards the policy, suggesting an increase in selectivity that approximates the rule; whereas in the Putamen we also find a prominent magnitude increase, suggesting strengthening of confidence. Additionally, magnitude increases in the striatum followed rotation in the dACC. Finally, the neural representation at the end of the session predicted next-day behavior. The use of this novel framework enables tracking of neural dynamics during learning and suggests differential yet complementing roles for these brain regions.

neuroscience↗

bioRxiv2018

Inhibitory and excitatory mechanisms in the human cingulate-cortex support reinforcement learning

The dorsal anterior cingulate cortex (dACC) is crucial for motivation, reward- and error-guided decision-making, yet its excitatory and inhibitory mechanisms remain poorly explored in humans. In particular, the balance between excitation and inhibition (E/I), demonstrated to play a role in animal studies, is difficult to measure in behaving humans. Here, we used magnetic-resonance-spectroscopy (1H-MRS) to examine these mechanisms during reinforcement learning with three different conditions: high cognitive load (uncertainty); probabilistic discrimination learning; and a control null-condition. Subjects learned to prefer the gain option in the discrimination phase and had no preference in the other conditions. We found increased GABA levels during the uncertainty condition, suggesting recruitment of inhibitory systems during high cognitive load when trying to learn. Further, higher GABA levels during the null (baseline) condition correlated with improved discrimination learning. Finally, excitatory and inhibitory levels were correlated during high cognitive load. The result suggests that availability of dACC inhibitory resources enables successful learning. Our approach establishes a novel way to examine the contribution of the balance between excitation and inhibition to learning and motivation in behaving humans.

neuroscience↗

bioRxiv2018

Long time-scales in primate amygdala neurons support aversive learning

Associative learning forms when there is temporal relationship between a stimulus and a reinforcer, yet the inter-trial-interval (ITI), which is usually much longer than the stimulus-reinforcer-interval, contributes to learning-rate and memory strength. The neural mechanisms that enable maintenance of time between trials remain unknown, and it is unclear if the amygdala can support time scales at the order of dozens of seconds. We show that the ITI indeed modulates rate and strength of aversive-learning, and that single-units in the primate amygdala and dorsal-anterior-cingulate-cortex signal confined periods within the ITI, strengthen this coding during acquisition of aversive-associations, and diminish during extinction. Additionally, pairs of amygdala-cingulate neurons synchronize during specific periods suggesting a shared circuit that maintains the long temporal gap. The results extend the known roles of this circuit and suggest a mechanism that maintains trial-structure and temporal-contingencies for learning. It further suggests a novel model for maladaptive behaviors.

neuroscience↗

bioRxiv2017

Oscillations synchronize amygdala-to-prefrontal primate circuits during aversive learning

The contribution of oscillatory synchrony in the primate amygdala-prefrontal pathway to aversive learning remains unknown. We found increased power and phase synchrony in the theta range during aversive conditioning. The synchrony was linked to single-unit spiking and exhibited specific directionality between input and output measures in each region. Although it was correlated with the development of conditioned responses, it declined once the association stabilized. The results suggest that amygdala spikes aid to synchronize ACC activity and transfer error-signal information to support memory formation.\n\nHighlightsO_LITone-odor conditioning induces theta phase-reset in primate amygdala and dACC\nC_LIO_LIA directional phase-locking develops between amygdala spikes and dACC Theta\nC_LIO_LIInformation transfer from Amygdala to dACC decreases once memory stabilizes\nC_LI

neuroscience↗

bioRxiv2017

Prestimulus Activity in the Cingulo-Opercular Network Predicts Memory for Naturalistic Episodic Experience

Human memory is strongly influenced by brain states occurring before an event, yet we know little about the underlying mechanisms. We found that activity in the cingulo-opercular network (including bilateral anterior insula and anterior prefrontal cortex) seconds before an event begins can predict whether this event will subsequently be remembered. We then tested how activity in the cingulo-opercular network shapes memory performance. Our findings indicate that prestimulus cingulo-opercular activity affects memory performance by opposingly modulating subsequent activity in two sets of regions previously linked to encoding and retrieval of episodic information. Specifically, higher prestimulus cingulo-opercular activity was associated with a subsequent increase in activity in temporal regions previously linked to encoding and with a subsequent reduction in activity within a set of regions thought to play a role in retrieval and self-referential processing. Together, these findings suggest that prestimulus attentional states modulate memory for real-life events by enhancing encoding and possibly by dampening interference from competing memory substrates.

neuroscience↗