Classical Pavlovian Conditioning Research Articles

Analog‐Digital Hybridity of Resistive Switching in Ion‐Irradiated BiFeO3 Memristor for Synergistic Neuromorphic Functionality and Artificial Learning

AbstractMemristors‐based neuromorphic devices represent emerging computing architectures to perform complex tasks by outpacing the traditional Von‐Neumann architectures in terms of speed, and energy efficiency. In this work, the resistive switching (RS) behavior of sol‐gel grown and ion‐irradiated BFO films is investigated under electrical stimulus. The Ag/BFO/FTO memristors emulate a combination of digital and analog RS behavior within a single device. The possible mechanism of analog digital hybridity is addressed by considering the formation of the conducting filament by oxygen vacancies, Ag+ ions and Schottky barrier height modulation. The ion‐irradiated BFO samples are analyzed using the Raman, XRD, and XPS studies. To uphold bioinspired synaptic actions, crucial synaptic functionalities like pair‐pulse facilitation and long‐term potentiation/depression are effectively achieved. More intricate synaptic behaviors are also demonstrated such as spike‐time‐dependent plasticity and Pavlovian classical conditioning, which represent the prominent attributes of both learning and forgetting behavior. Additionally, high pattern recognition accuracy (96.1%) is achieved in an artificial neural network simulation by using the synaptic weights of the memristors. This synergistic effect of digital and analog RS in ion‐irradiated BFO can be beneficial for the emulation of complex learning behavior as well as its incorporation into low‐power neuromorphic computing.

Retina-Inspired Large-Area Solution-Processed flexible Multi-Band organic neuromorphic synaptic transistor arrays

The proliferation of high-efficacy, pliable organic neuromorphic synaptic transistors is quintessential for the integration into wearable artificial intelligence ecosystems. Nevertheless, their development is hindered by substantial energy demands and suboptimal charge carrier mobility. To surmount these obstacles, we exploit solution-processed poly(amic acid) (PAA) dielectrics and organic semiconductors to engineer pliable arrays of organic neuromorphic synaptic transistors atop a polyethylene terephthalate (PET) matrix. The polar group and nanogroove structure of PAA obtain excellent semiconductor crystal structure, and the excellent dielectric properties enable these engineered arrays to show a charge carrier mobility peak of 29.83 cm2 V−1 s−1 an aggregate mean mobility of 15.87 cm2 V−1 s−1 (standard deviation is 6.71) at a voltage of −3 V and the energy expenditure per synaptic transaction was only 0.26 fJ. Additionally, the transistors possess the aptitude for photodetection across ultraviolet–visible to near-infrared spectral bands. The successful execution of flexible imaging, Pavlovian classical conditioning reflex associative learning, coupled with a 93.9 % accuracy in handwritten numeral recognition, corroborates the viability of these high-mobility, low-power organic neuromorphic synaptic transistor arrays.

SiC@NiO Core-Shell Nanowire Networks-Based Optoelectronic Synapses for Neuromorphic Computing and Visual Systems at High Temperature.

1D nanowire networks, sharing similarities of structure, information transfer, and computation with biological neural networks, have emerged as a promising platform for neuromorphic systems. Based on brain-like structures of 1D nanowire networks, neuromorphic synaptic devices can overcome the von Neumann bottleneck, achieving intelligent high-efficient sensing and computing function with high information processing rates and low power consumption. Here, high-temperature neuromorphic synaptic devices based on SiC@NiO core-shell nanowire networks optoelectronic memristors (NNOMs) are developed. Experimental results demonstrate that NNOMs attain synaptic short/long-term plasticity and modulation plasticity under both electrical and optical stimulation, and exhibit advanced functions such as short/long-term memory and "learning-forgetting-relearning" under optical stimulation at both room temperature and 200°C. Based on the advanced functions under light stimulus, the constructed 5×3 optoelectronic synaptic array devices exhibit a stable visual memory function up to 200°C, which can be utilized to develop artificial visual systems. Additionally, when exposed to multiple electronic or optical stimuli, the NNOMs effectively replicate the principles of Pavlovian classical conditioning, achieving visual heterologous synaptic functionality and refining neural networks. Overall, with abundant synaptic characteristics and high-temperature thermal stability, these neuromorphic synaptic devices offer a promising route for advancing neuromorphic computing and visual systems.

Changes in responses of the amygdala and hippocampus during fear conditioning are associated with persecutory beliefs

The persecutory delusion is the most common symptom of psychosis, yet its underlying neurobiological mechanisms are poorly understood. Prior studies have suggested that abnormalities in medial temporal lobe-dependent associative learning may contribute to this symptom. In the current study, this hypothesis was tested in a non-clinical sample of young adults without histories of psychiatric treatment (n = 64), who underwent classical Pavlovian fear conditioning while fMRI data were collected. During the fear conditioning procedure, participants viewed images of faces which were paired (the CS+) or not paired (the CS−) with an aversive stimulus (a mild electrical shock). Fear conditioning-related neural responses were measured in two medial temporal lobe regions, the amygdala and hippocampus, and in other closely connected brain regions of the salience and default networks. The participants without persecutory beliefs (n = 43) showed greater responses to the CS− compared to the CS+ in the right amygdala and hippocampus, while the participants with persecutory beliefs (n = 21) failed to exhibit this response. These between-group differences were not accounted for by symptoms of depression, anxiety or a psychosis risk syndrome. However, the severity of subclinical psychotic symptoms overall was correlated with the level of this aberrant response in the amygdala (p = .013) and hippocampus (p = .033). Thus, these findings provide evidence for a disruption of medial temporal lobe-dependent associative learning in young people with subclinical psychotic symptoms, specifically persecutory thinking.

CK2 negatively regulates the extinction of remote fear memory

Cognitive behavioral therapy, rooted in exposure therapy, is currently the primary approach employed in the treatment of anxiety-related conditions, including post-traumatic stress disorder (PTSD). In laboratory settings, fear extinction in animals is a commonly employed technique to investigate exposure therapy; however, the precise mechanisms underlying fear extinction remain elusive. Casein kinase 2 (CK2), which regulates neuroplasticity via phosphorylation of its substrates, has a significant influence in various neurological disorders, such as Alzheimer’s disease and Parkinson’s disease, as well as in the process of learning and memory. In this study, we adopted a classical Pavlovian fear conditioning model to investigate the involvement of CK2 in remote fear memory extinction and its underlying mechanisms. The results indicated that the activity of CK2 in the medial prefrontal cortex (mPFC) of mice was significantly upregulated after extinction training of remote cued fear memory. Notably, administration of the CK2 inhibitor CX-4945 prior to extinction training facilitated the extinction of remote fear memory. In addition, CX-4945 significantly upregulated the expression of p-ERK1/2 and p-CREB in the mPFC. Our results suggest that CK2 negatively regulates remote fear memory extinction, at least in part, by inhibiting the ERK-CREB pathway. These findings contribute to our understanding of the underlying mechanisms of remote cued fear extinction, thereby offering a theoretical foundation and identifying potential targets for the intervention and treatment of PTSD.

High precision of sign language recognition based on In2O3 transistors gated by AlLiO solid electrolyte

In recent years, the synaptic properties of transistors have been extensively studied. Compared with liquid or organic material-based transistors, inorganic solid electrolyte-gated transistors have the advantage of better chemical stability. This study uses a simple, low-cost solution technology to prepare In2O3 transistors gated by AlLiO solid electrolyte. The electrochemical performance of the device is achieved by forming a double electric layer and electrochemical doping, which can mimic basic functions of biological synapses, such as excitatory postsynaptic current, paired-pulse promotion, and spiking time-dependent plasticity. Furthermore, complex synaptic behaviors such as Pavlovian classical conditioning is successfully emulated. With a 95% identification accuracy, an artificial neural network based on transistors is built to recognize sign language and enable sign language interpretation. Additionally, the handwriting digit’s identification accuracy is 94%. Even with various levels of Gaussian noise, the recognition rate is still above 84%. The above findings demonstrate the potential of In2O3/AlLiO TFT in shaping the next generation of artificial intelligence.

Emulation of Pavlovian conditioning and pattern recognition through fully connected neural networks using Holmium oxide (Ho2O3) based synaptic RRAM device.

In this manuscript, we report on the paramagnetic Ho2O3 -based synaptic resistive random-access memory (RRAM) device for the implementation of neuronal functionalities such as long-term potentiation (LTP), long-term depression (LTD) and spike timing dependent plasticity (STDP) respectively. The plasticity of the artificial synapse is also studied by varying pulse amplitude, pulse width, and pulse interval. In addition, we could classify handwritten Modified National Institute of Standards and Technology (MNIST) data set using a fully connected neural network (FCN). The device-based FCN records a high classification accuracy of 93.47% which is comparable to the software-based test accuracy of 97.97%. This indicates the highly optimized behavior of our synaptic device for hardware neuromorphic applications. Successful emulation of Pavlovian classical conditioning for associative learning of the biological brain is achieved. We believe that the present device consists the potential to utilize in neuromorphic applications.

Electrophysiological Activity from the Eye Muscles, Cerebellum and Cerebrum During Reflexive (Classical Pavlovian) Versus Voluntary (Ivanov-Smolensky) Eye-Blink Conditioning

We report an experiment to investigate the role of the cerebellum and cerebrum in motor learning of timed movements. Eleven healthy human subjects were recruited to perform two experiments, the first was a classical eye-blink conditioning procedure with an auditory tone as conditional stimulus (CS) and vestibular unconditional stimulus (US) in the form of a double head-tap. In the second experiment, subjects were asked to blink voluntarily in synchrony with the double head-tap US preceded by a CS, a form of Ivanov-Smolensky conditioning in which a command or instruction is associated with the US. Electrophysiological recordings were made of extra-ocular EMG and EOG at infra-ocular sites (IO1/2), EEG from over the frontal eye fields (C3’/C4’) and from over the posterior fossa over the cerebellum for the electrocerebellogram (ECeG). The behavioural outcomes of the experiments showed weak reflexive conditioning for the first experiment despite the double tap but robust, well-synchronised voluntary conditioning for the second. Voluntary conditioned blinks were larger than the reflex ones. For the voluntary conditioning experiment, a contingent negative variation (CNV) was also present in the EEG leads prior to movement, and modulation of the high-frequency EEG occurred during movement. US-related cerebellar activity was prominent in the high-frequency ECeG for both experiments, while conditioned response-related cerebellar activity was additionally present in the voluntary conditioning experiment. These results demonstrate a role for the cerebellum in voluntary (Ivanov-Smolensky) as well as in reflexive (classical Pavlovian) conditioning.

Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition.

Recent research extends our understanding of brain processes beyond just action potentials and chemical transmissions within neural circuits, emphasizing the mechanical forces generated by excitatory synapses on dendritic spines to modulate presynaptic function. From in vivo and in vitro studies, we outline five central principles of synaptic mechanics in brain function: P1: Stability - Underpinning the integral relationship between the structure and function of the spine synapses. P2: Extrinsic dynamics - Highlighting synapse-selective structural plasticity which plays a crucial role in Hebbian associative learning, distinct from pathway-selective long-term potentiation (LTP) and depression (LTD). P3: Neuromodulation - Analyzing the role of G-protein-coupled receptors, particularly dopamine receptors, in time-sensitive modulation of associative learning frameworks such as Pavlovian classical conditioning and Thorndike's reinforcement learning (RL). P4: Instability - Addressing the intrinsic dynamics crucial to memory management during continual learning, spotlighting their role in "spine dysgenesis" associated with mental disorders. P5: Mechanics - Exploring how synaptic mechanics influence both sides of synapses to establish structural traces of short- and long-term memory, thereby aiding the integration of mental functions. We also delve into the historical background and foresee impending challenges.

Bio-inspired artificial heterosynapse based on carbon nanotubes memtransistor with dynamically tunable analog switching behavior

The swift advancement of artificial intelligence necessitates the exigency for a proficient information processing system. Taking inspiration from the intricate synapses of the human brain, we have crafted an artificial heterosynapse utilizing carbon nanotube (CNT) memtransistors. The multi-terminal heterosynaptic plasticity of CNTs memtransistor could be effectively modulated by gate voltage or drain voltage, which resembles the biological synapses affected by external neuromodulators. The artificial synapse skillfully replicates neuromorphic functionalities in response to pulse stimuli. This enables tunable analog switching behavior, multiple memory states, and complex neuromorphic learning. Furthermore, the Pavlovian classical conditioning experiments were conducted utilizing the synaptic device to achieve associative learning. The introduction of the CNTs memtransistor will propel the advancement of neuromorphic device technology and unlock novel opportunities for designing learning schemes with an additional degree of freedom.

Fully Photon Controlled Synaptic Memristor for Neuro‐Inspired Computing

AbstractThe emerging optoelectronic memristive synapses having the advantages of both optics and electronics exhibit a great potential in neuro‐inspired computing, which is a new generation of artificial intelligence. Herein, a light stimulated synaptic memristor (LSSM) based on ZnO/Zn2SnO4 heterostructure is prepared with the characteristics of reversibly tunable conductance states by varying the wavelength of the incident light. The synaptic feature of this fully photon controlled memristive synapse is revealed by potentiation and depression behaviors stimulated by violet and red light pulses, respectively. Similar to biological brain, the device demonstrates the dynamic learning and forgetting behavior. All‐optically driven and bio‐vision inspired image processing function such as contrast enhancement is exemplified. The international Morse code for Arabic numerals (0–9) is also successfully conveyed by patterned light pulses and suggests the device's potential in the field of optical wireless communication for human–machine interface. Classical Pavlovian conditioning (associative learning) is successfully demonstrated through visible light induction. Finally, the device can realize the recognition application of Zalando's article image through the simulation based on Hopfield neural network (HNN). This work provides a promising approach toward optoelectronic neural systems and human–machine interaction technologies.

Bipolar Resistive Switching in TiO2 Artificial Synapse Mimicking Pavlov's Associative Learning.

Memristive devices are among the most emerging electronic elements to realize artificial synapses for neuromorphic computing (NC) applications and have potential to replace the traditional von-Neumann computing architecture in recent times. In this work, pulsed laser deposition-manufactured Ag/TiO2/Pt memristor devices exhibiting digital and analog switching behavior are considered for NC. The TiO2 memristor shows excellent performance of digital resistive switching with a memory window of order ∼103. Furthermore, the analog resistive switching offers multiple conductance levels supporting the development of the bioinspired synapse. A possible mechanism for digital and analog switching behavior in our device is proposed. Remarkably, essential synaptic functions such as pair-pulse facilitation, long-term potentiation (LTP), and long-term depression (LTD) are successfully realized based on the change in conductance through analog memory characteristics. Based on the LTP-LTD, a neural network simulation for the pattern recognition task using the MNIST data set is investigated, which shows a high recognition accuracy of 95.98%. Furthermore, more complex synaptic behavior such as spike-time-dependent plasticity and Pavlovian classical conditioning is successfully emulated for associative learning of the biological brain. This work enriches the TiO2-based resistive random-access memory, which provides information about the simultaneous existence of digital and analog behavior, thereby facilitating the further implementation of memristors in low-power NC.

Classical Conditioning for Pain: The Development of a Customized Single-Case Experimental Design

Single-case experiments are increasingly popular in the behavioral sciences. Due to their flexibility, single-case designs can be customized to test a variety of experimental hypotheses. We were interested in using a single-case experimental approach to test whether pain thresholds can be influenced by Pavlovian classical conditioning. Following the example of earlier studies into this topic, we planned to measure whether participants would more frequently report specific electrocutaneous stimuli as painful when they were presented with specific vibrotactile stimuli that had previously been associated with painful electrocutaneous stimuli. First, we decided on a mean difference effect size measure derived from the Sensation and Pain Rating Scale ratings for the electrocutaneous stimuli provided by the participants. Next, we discussed several possible single-case designs and evaluated their benefits and shortcomings. Then, we ran pilot tests with a few participants based on the possible single-case designs. We also conducted a simulation study to estimate the power of a randomization test to test our hypothesis using different values for effect size, number of participants, and number of measurements. Finally, we decided on a sequentially replicated AB phase design with 30 participants based on the results from the pilot tests and the power study. We plan to implement this single-case design in a future experiment to test our hypothesis

Photonic synapses with ultralow energy consumption for artificial visual perception and brain storage

The human visual system, dependent on retinal cells, can be regarded as a complex combination of optical system and nervous system. Artificial retinal system could mimic the sensing and processing function of human eyes. Optically stimulated synaptic devices could serve as the building blocks for artificial retinas and subsequent information transmission system to brain. Herein, photonic synaptic transistors based on polycrystalline MoS₂, which could simulate human visual perception and brain storage, are presented. Moreover, the photodetection range from visible light to near-infrared light of MoS₂ multilayer could extend human eyes’ vision limitation to near-infrared light. Additionally, the photonic synaptic transistor shows an ultrafast speed within 5 μs and ultralow power consumption under optical stimuli about 40 aJ, several orders of magnitude lower than biological synapses (50 ms and 10 fJ). Furthermore, the backgate control could act as emotional modulation of the artificial brain to enhance or suppress memory function, i.e. the intensity of photoresponse. The proposed carrier trapping/detrapping as the main working mechanism is presented for the device. In addition, synaptic functionalities including short synaptic plasticity, long synaptic plasticity and paired-pulse facilitation could be successfully simulated based on the prepared device. Furthermore, the large difference between short synaptic plasticity and long synaptic plasticity reveals the better image pre-processing function of the prepared photonic synapses. The classical Pavlovian conditioning associated with the associative learning is successfully implemented as well. Therefore, the efficient and rich functionalities demonstrate the potential of the MoS₂ synaptic device that integrates sensing-memory-preprocessing capabilities for realizing artificial neural networks with different emotions that mimic human retina and brain.

Spreading depolarization induced by amygdala micro-injury prevents disruption of fear memory extinction in rats

Spreading depolarization (SD), a self-propagating wave of near-complete breakdown of the transmembrane ion gradients with water influx, regularly occurs in traumatized human brain. Here, we investigated long-term neurobehavioral consequences of injury-triggered SDs. Recently, we revealed that SD is reliably triggered by micro-injury of the amygdala, a key brain structure involved in fear processing. Using the classical Pavlovian fear conditioning paradigm, we investigated effects of the post-retrieval amygdala micro-injury and associated SD on fear memory in rats. We found that neither SD nor micro-injury alone affect fear response 24 h later but profoundly change it in subsequent extinction phase. If bilateral injury of the amygdala did not induce SD, fear extinction was severely impaired, while conditioned fear in rats with the identical amygdala injury triggering SD was successfully extinguished similarly to naïve rats. Our study provides first experimental evidence for involvement of injury-induced SD in extinction of traumatic fear memory.

Impaired reward-related learning signals in remitted unmedicated patients with recurrent depression.

One of the core symptoms of major depressive disorder is anhedonia, an inability to experience pleasure. In patients with major depressive disorder, a dysfunctional reward-system may exist, with blunted temporal difference reward-related learning signals in the ventral striatum and increased temporal difference-related (dopaminergic) activation in the ventral tegmental area. Anhedonia often remains as residual symptom during remission; however, it remains largely unknown whether the abovementioned reward systems are still dysfunctional when patients are in remission. We used a Pavlovian classical conditioning functional MRI task to explore the relationship between anhedonia and the temporal difference-related response of the ventral tegmental area and ventral striatum in medication-free remitted recurrent depression patients (n = 36) versus healthy control subjects (n = 27). Computational modelling was used to obtain the expected temporal difference errors during this task. Patients, compared to healthy controls, showed significantly increased temporal difference reward learning activation in the ventral tegmental area (PFWE,SVC = 0.028). No differences were observed between groups for ventral striatum activity. A group × anhedonia interaction [t(57) = -2.29, P = 0.026] indicated that in patients, higher anhedonia was associated with lower temporal difference activation in the ventral tegmental area, while in healthy controls higher anhedonia was associated with higher ventral tegmental area activation. These findings suggest impaired reward-related learning signals in the ventral tegmental area during remission in patients with depression. This merits further investigation to identify impaired reward-related learning as an endophenotype for recurrent depression. Moreover, the inverse association between reinforcement learning and anhedonia in patients implies an additional disturbing influence of anhedonia on reward-related learning or vice versa, suggesting that the level of anhedonia should be considered in behavioural treatments.

Attention to a threat-related feature does not interfere with concurrent attentive feature selection.

Visual features associated with a task and those that predict noxious events both prompt selectively heightened visuocortical responses. Conflicting views exist regarding how the competition between a task-related and a threat-related feature is resolved when they co-occur in time and space. Utilizing aversive classical Pavlovian conditioning, we investigated the visuocortical representation of two simultaneously presented, fully overlapping visual stimuli. Isoluminant red and green random dot kinematogram (RDK) stimuli were flickered at distinct tagging frequencies (8.57Hz, 12Hz) to elicit distinguishable steady-state visual evoked potentials (ssVEPs). Occasional coherent motion events prompted a motor response (task) or predicted a noxious noise (threat). These events occurred either in the green (task cue), the red (threat cue), or in both RDKs simultaneously. In the initial habituation phase, participants responded to coherent motion of the green RDK with a key press, but no loud noise was presented at any time. Here, selective amplification was seen for the task-relevant (green) RDK, and interference was observed when both RDKs simultaneously showed coherent motion. Upon pairing the threat cue with the noxious noise in the subsequent acquisition phase, the threat cue-evoked ssVEP (red RDK) was also amplified, but this amplification did not interact with amplification of the task cue or alter the behavioral or visuocortical interference effect observed during simultaneous coherent motion. Although competing feature conjunctions resulted in interference in the visual cortex, the acquisition of a bias toward an individual threat-related feature did not result in additional cost effects.

Sniffer Bees as a Reliable Tool for Andrographis paniculata Detection

Honey bees of Apis mellifera could be trained to be highly reliable sniffers for the detection of Andrographis paniculata using the classical Pavlovian conditioning training method with high success rate, > 80% based on the proboscis extension reflex as a positive response to the presence of the herb. The success rate of sniffer bees was found to be in a temperature dependent manner, but not significantly affected by the heating duration (5–110 min). The variance of 7.7% success rate was observed for the heating temperature ranged 50–120 °C with the highest success rate (92.7%) at 100 °C. This could be due to the content of signature compounds released from the heated herbal samples. Three signature compounds such as dihydroactinidiolide, apiol and 6,10,14-trimethyl-2-pentadecanone were proposed to be the volatile marker of the herb since their concentrations changed in accordance with the temperature profile and success rate of sniffer bees. The volatile compounds were extracted by divinylbenzene and carboxen coated polydimethylsiloxane fiber in the headspace of solid phase micro-extraction before analyzed by GC–MS for identification. Almost 50% success rate could be achieved using the minimum amount of 20 mg herbal samples. High selectivity of the sniffer bees has also been proven by no response to another morphologically similar herb, Clinacanthus nutans which was also heat-treated in the similar manner. The sniffer bees also showed to exhibit 80% success rate to detect A. paniculata mixed with 50% C. nutans as interference in a mixture.

Protocols to Study Declarative Memory Formation in Mice and Humans:Optogenetics and Translational Behavioral Approaches.

Declarative memory formation depends on the hippocampus and declines in aging. Two functions of the hippocampus, temporal binding and relational organization (Rawlins and Tsaltas, 1983; Eichenbaum et al., 1992 ; Cohen et al., 1997 ), are known to decline in aging (Leal and Yassa, 2015). However, in the literature distinct procedures have been used to study these two functions. Here, we describe the experimental procedures used to investigate how these two processes are related in the formation of declarative memory and how they are compromised in aging ( Sellami et al., 2017 ). First, we studied temporal binding using a one-trial learning procedure: trace fear conditioning. It is classical Pavlovian conditioning requiring temporal binding since a brief temporal gap separates the conditioned stimulus (CS) and unconditioned stimulus (US) presentations. We combined the trace fear condition procedure with an optogenetic approach, and we showed that the temporal binding relies on dorsal (d)CA1 activity over temporal gaps. Then, we studied the interaction between temporal binding and relational organization in declarative memory formation using a two-phase radial-maze task in mice and its virtual analog in humans. The behavioral procedure comprises an initial learning phase where subjects learned the constant rewarding /no rewarding valence of each arm, followed by a test phase where the reward contingencies among the arms remained unchanged but where the arms were recombined to assess flexibility, a cardinal property of declarative memory. We demonstrated that dCA1-dependent temporal binding is necessary for the development of a relational organization of memories that allows flexible declarative memory expression. Furthermore, in aging, the degradation of declarative memory is due to a reduction of temporal binding capacity that prevents relation organization.

Propranolol Degrades Memory Reconsolidation in Conditions of Single and Multiple Combinations of Tones with Pain

The effects of propranolol on the state of memory after its reactivation (in the reconsolidation phase) were studied using two approaches – classical Pavlovian conditioning and acquisition of a two-way escape reaction. The difference between them was that in the first case, the tone was combined with painful electrocutaneous stimulation just once, while in the latter it was combined multiple times. Reminding in the former case was induced by placing the animals in the same context in which primary training was performed, while in the latter the number of combinations of the conditioned and unconditioned stimuli was the same as that used on the first day of training. Administration of propranolol decreased the duration of freezing episodes by 25% compared with the baseline level in classical conditioning and led to essentially complete loss of memory and complete regression of the two-way escape reaction. It is suggested that the effects of blockade of the noradrenergic system on loss of memory in the reconsolidation stage in these learning models have different mechanisms.