Unique Effects of Sedatives, Dissociatives, Psychedelics, Stimulants, and Cannabinoids on Episodic Memory: A Review and Reanalysis of Acute Drug Effects on Recollection, Familiarity, and Metamemory

Abstract

Despite distinct classes of psychoactive drugs producing putatively unique states of consciousness, there is surprising overlap in terms of their effects on episodic memory and cognition more generally. Episodic memory is supported by multiple subprocesses that have been mostly overlooked in psychopharmacology and could differentiate drug classes. Here, we reanalyzed episodic memory confidence data from 10 previously published datasets (28 drug conditions total) using signal detection models to estimate 2 conscious states involved in episodic memory and 1 consciously-controlled metacognitive process of memory: the retrieval of specific details from one's past (recollection), noetic recognition in the absence of retrieved details (familiarity), and accurate introspection of memory decisions (metamemory). We observed that sedatives, dissociatives, psychedelics, stimulants, and cannabinoids had unique patterns of effects on these mnemonic processes dependent on which phase of memory (encoding, consolidation, or retrieval) was targeted. All drugs at encoding except stimulants impaired recollection, and sedatives, dissociatives, and cannabinoids at encoding impaired familiarity. The effects of sedatives on metamemory were mixed, whereas dissociatives and cannabinoids at encoding tended to enhance metamemory. Surprisingly, psychedelics at encoding tended to enhance familiarity and did not impact metamemory. Stimulants at encoding and retrieval enhanced metamemory, but at consolidation, they impaired metamemory. Together, these findings may have relevance to mechanisms underlying unique subjective phenomena under different drug classes, such as blackouts from sedatives or deja vu from psychedelics. This study provides a framework for interrogating drug effects within a domain of cognition beyond the global impairments on task performance typically reported in psychopharmacology.

Trajectories of sentiment in 11,816 psychoactive narratives

“…a 1D CNN for EEGs or ECGs (Khurshid et al., 2022; Liu et al., 2021)). Excitingly, such modalities can be sampled uniformly in time, and independently from the subject's recollection, mitigating uncertainties inherent in self‐reported datasets like Erowid about dosage, chronology, and drugs' impact on memory (Doss et al, 2018, 2022). Likely the best representations of acute drug states will be built by multimodally combining subjective and biometric data since both physiological responses and the qualia of experience are critical to understand psychoactive effects.…”

Language Models Learn Sentiment and Substance from 11,000 Psychoactive Experiences

“…a 1D CNN for EEGs or ECGs [37,38]). Excitingly, such modalities can be sampled with high temporal resolution and independently from the patient’s recollection, mitigating the issues inherent in self-reported datasets like Erowid, where there is uncertainty about dosage, chronology, and drugs’ impact on memory [39,40]. On the other hand, given that recent machine learning models trained on cross-modal representations have shown improved phenotype prediction [29], combining parallel subjective and neuroimaging datastreams may build more useful and holistic representations of acute drug states.…”

Language Models Learn Sentiment and Substance from 11,000 Psychoactive Experiences

“…a 1D CNN for EEGs or ECGs 40,41 ). Excitingly, such modalities can be sampled uniformly in time, and independently from the patient's recollection, mitigating uncertainties inherent in self-reported datasets like Erowid about dosage, chronology, and drugs' impact on memory 42,43 . Likely the best representations of acute drug states will be built by multimodally combining subjective and biometric data since both physiological responses and the qualia of experience are critical to understand psychoactive interventions 32 .…”