Memory formation, consolidation and retrieval are well-known functions that support memory expression; however, the processes that limit these functions—including forgetting—are less understood. Forgetting has been characterized as either passive or active, and is crucial for memory removal, flexibility and updating1,2,3. Memory may be removed completely, resulting in permanent forgetting; or temporarily irretrievable, resulting in transient forgetting.

One form of active forgetting—known as intrinsic forgetting—involves one dopamine neuron (DAN) that innervates the γ2α′1 compartment of the axons of mushroom body neurons (MBNs) and the dendrites of the downstream, compartment-specific mushroom-body output neurons (MBONs)4,5,6. This DAN resides in a cluster of 12 DANs in each brain hemisphere that is known as the protocerebral posterior lateral 1 (PPL1) cluster4. Current evidence indicates that the ongoing activity of these DANs after aversive olfactory conditioning slowly and chronically erodes labile and nonconsolidated behavioural memory5, as well as a corresponding cellular memory trace that forms in the MBONs6. This intrinsic forgetting mechanism is shaped by external sensory stimulation and sleep or rest7, and is mediated by a signalling cascade in the MBNs that is initiated by the activation of the dopamine receptor DAMB, which leads to the downstream activation of the actin-binding protein Cofilin and the postulated reorganization of the synaptic cytoskeleton1,8,9.

By contrast, there is little understanding of the mechanisms that arbitrate transient forgetting. Neuropsychological studies of failures or delays in retrieval in humans have primarily focused on lexical access. Phonological blockers or interfering stimuli produce a tip-of-the-tongue state10—the failure to recall the appropriate word or phrase. Tip-of-the-tongue states are resolved when the distracting signals dissipate10. Several brain regions have been implicated in tip-of-the-tongue states from functional magnetic resonance imaging studies11, but the neurobiological mechanisms that produce a temporary state of impaired retrieval are unknown. Our study offers an entry point into this area of brain function...

Wild-type flies that were subjected to aversive olfactory conditioning (an odour coupled with an electric shock) using several, spaced training cycles displayed robust long-term memory (LTM) by 72 h after training (Fig. 1a, b). To determine how exposure to an interfering stimulus might affect expression of LTM, flies were briefly stimulated with airflow, electric shock or blue light before the memory retrieval test. Memory expression was weakened with increasing stimulus strength after experiencing these distractors (Extended Data Fig. 1a–c). These effects were observed only on cycloheximide-sensitive memory (Fig. 1b, c). As cycloheximide blocks protein-synthesis-dependent LTM (PSD-LTM), the difference in performance index between untreated and cycloheximide-treated flies represents the magnitude of PSD-LTM. The expression of PSD-LTM resurfaced at significant levels by 1 h after presentation of airflow, shock or blue light (Fig. 1b, c, Supplementary Information), which indicates that the memory impairments were temporary and produced by transient forgetting.

a, Aversive olfactory conditioning paradigm used to generate PSD-LTM. b–d, Cycloheximide (CXM)-treated wild-type (Canton-S) flies were exposed to interfering stimuli: airflow (b), electric shock (c) or blue light (d), and tested for 72-h or 73-h memory. Box-and-whisker plots show the range of individual data points, with the interquartile spread as the box and the median as the line bisecting each box. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; n = 12 (b–d), two-way analysis of variance (ANOVA) with Tukey’s test. Exact P values and comparisons are given in Supplementary Information.

Transient forgetting through dopamine

Because DANs of the PPL1 cluster (PPL1 DANs) are involved in intrinsic forgetting, we asked whether they might also be involved in the processes that underlie transient forgetting. Pilot experiments demonstrated that strong, prolonged thermogenetic stimulation of all 12 PPL1 DANs per hemisphere (TH-D′>TrpA1 flies; for a full list of fly lines with their genotypes, see Supplementary Information) significantly reduced expression of PSD-LTM (Extended Data Fig. 2a–c) even 24 h before retrieval. We observed the opposite effect upon blocking synaptic output from PPL1 DANs (TH-D′>Shibire), which suggested the existence of a memory reserve that remains hidden unless synaptic output from the DAN is suppressed (Extended Data Fig. 2c). We used these assays and a collection of split-gal4 fly lines to spatially restrict TrpA1 expression to subpopulations of the PPL1 DANs

a, Schematic depicting the right hemisphere of a fly brain. One DAN (dark grey circle) in the PPL1 cluster synapses onto the MBN α2α′2 compartment (dark grey). Brief stimulation of PPL1-α2α′2 (058B>TrpA1) immediately before retrieval transiently suppressed, whereas blocking synaptic output (058B>Shibire) temporarily enhanced, expression of PSD-LTM. b, Conditioned flies were fed with RU486 to induce RNAi expression in the MBN. Knocking down DAMB, but not dDA1, blocked the PPL1-α2α′2-induced suppression of memory. PPL1-α2α′2-lexA, MB-GeneSwitch>uas-RNAi, lexAop-TrpA1 flies. Box-and-whisker plots show the range of individual data points, with the interquartile spread as the box and the median as the line bisecting each box. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001; n = 12, two-way ANOVA with Tukey’s test. Exact P values and comparisons are shown in Supplementary Information.

a, Flies were subjected to spaced training using OCT (O) as the CS+ and BEN (B) as the CS−. MBON-α2sc dendrites were imaged with or without a 6-h TrpA1 stimulation of PPL1-α2α′2 (R82C10-gal4). b, Group differential traces and quantification of the odour responses to OCT (CS+) and BEN (CS− ) in flies kept at 23 °C or treated at 30 °C between 42 and 48 h. Left, middle, activity as a function of time with odour stimulation. Right, average response magnitude within the first 5 s of odour onset (odour delivery duration). Calculations are provided in the Methods. The differential reflects the difference in odour response between CS+ and CS−. No PPL1-α2α′2: R34B02-lexA>lexAop-GCaMP6f, uas-TrpA1 flies. With PPL1-α2α′2: R82C10-gal4, R34B02-lexA>uas-TrpA1, lexAop-GCaMP6f flies. Ectopic activation of PPL1-α2α′2 did not alter the training-induced calcium transient differential. c, MBON-α2sc dendrites in the flies with PPL1-α2α′2 were imaged before (pre) and after (post) a 5-min TrpA1 stimulation. Brief stimulation of PPL1-α2α′2 did not change the training-induced calcium transient differential. Box-and-whisker plots show the range of individual data points, with the interquartile spread as the box and the median as the line bisecting each box. P > 0.05; n = 12 (b), n = 4 (c, no TrpA1 stimulation), n = 7 (c, TrpA1 stimulation), two-way ANOVA with Tukey’s test. Exact P values and comparisons are shown in Supplementary Information.

a, Blocking synaptic release from PPL1-α2α′2 and normalizing LTM expression by differential spaced conditioning. Flies were exposed to airflow (Fig. 1b) or blue light (Fig. 1d), but at 30 °C (for 20 min) to concurrently block PPL1-α2α′2 output. Stimuli exposure and heat treatment terminated 5 min before a memory retrieval test at 23 °C. Inhibiting synaptic release from PPL1-α2α′2 blocked the transient forgetting induced by airflow (left) or blue light (right). b, Flies were trained with different number of spaced sessions at 18 °C and shifted to 30 °C for 2 d, 24 h after training to induce DAMBRNAi in the α/β MBN (c739-gal4, gal80ts>uas-RNAi, uas-dicer2 flies). Flies were then exposed to airflow, electric shock or blue light immediately before retrieval. DAMB knockdown fully blocked the transient forgetting from exposure to external stimuli. c, Working model for transient forgetting. The expanded version contrasting permanent and transient forgetting is shown in Extended Data Fig. 7. Box-and-whisker plots show the range of individual data points, with the interquartile spread as the box and the median as the line bisecting each box. *P < 0.05, **P < 0.01, ***P < 0.001, **** P < 0.0001; n = 12 (a, b), two-way ANOVA with Tukey’s test. Exact P values and comparisons are shown in Supplementary Information.

We found no robust decrement in expression of PSD-LTM after PPL1-γ2α′1 stimulation (Extended Data Fig. 2), which points to the existence of two separate dopamine-based circuits for permanent and transient forgetting. This functional separation may indicate a fundamental principle in the organization of circuits that mediate several forms of forgetting.

However, the DAMB receptor is used for both permanent and transient forgetting. DAMB is widely expressed across the MBN axons12 but alters synaptic plasticity differently across MBN compartments29. It is possible that DAMB signalling may be distinct for the two forms of forgetting. DAMB preferentially couples with Gq, the knockdown of which inhibits the potent erasure of memory13, but its potential role in transient forgetting is unknown. The scaffolding protein Scribble orchestrates the activities of Rac1, Pak3 and Cofilin8, all of which are important for the permanent forgetting pathway (Extended Data Fig. 7). However, Scribble knockdown or inhibition of Rac1 does not enhance the PSD-LTM8,9 as is the case in DAMB-knockdown flies, which suggests that this scaffolding signalosome does not have a large role in transient forgetting. In summary, the two distinct forms of forgetting—transient and permanent—share a dopaminergic mechanism and a common dopamine receptor, but differ in upstream and downstream neural circuits and in downstream signalling pathways within MBNs.

The resulting life cycle GHG emissions range, based on location, from 2,283 to 5,184 kg CO2-equivalent per kg of dried flower. The life cycle GHG emissions are largely attributed to electricity production and natural gas consumption from indoor environmental controls, high-intensity grow lights and the supply of carbon dioxide for accelerated plant growth.

Understanding the greenhouse gas (GHG) emissions of commercial cannabis production is essential for consumers, the general public and policy makers to improve decision making to mitigate the effects of climate change. Since recreational legalization was pioneered in Colorado in 2012, the US legal cannabis industry has rapidly grown from a US$3.5 billion industry to US$13.6 billion in annual sales, with states like Colorado selling more than 530 tonnes of legally grown cannabis product every year1,2. Additionally, with 48% of adults in the United States having tried cannabis at some point in their life and 13% of adults having consumed in the last year, substantial demand exists at the consumer level3. Despite its rapid growth and widespread use, there is minimal quantitative understanding of the GHG emissions from legal indoor cannabis cultivation.

The initial amendment legalizing recreational cannabis in Colorado required the majority of cannabis product to be sold at a collocated retail location4. This restriction led to cultivation practices occurring within the city limits of Denver, CO. This, along with security, theft and quality concerns, consequently led to the cultivation of cannabis indoors. Although data concerning the exact amount of cannabis by cultivation method are not currently publicly available for the United States, a recent survey of producers in North America showed that 41% of respondents indicated that their grow operations occur solely indoors5. It is well known that indoor cannabis cultivation requires significant energy input, reflected in high utility bills and industry reports4,6,7,8,9. However, many of these large energy loads, along with other material inputs required to cultivate indoor cannabis, have not yet been equated to GHG emissions.

Previously, rudimentary quantifications of GHG emissions from indoor cannabis have been performed by equating emissions with electricity use from monthly bills6,7. However, this approach omits additional GHG emissions from other energy sources, such as natural gas, upstream GHG emissions from the production and use of material inputs, and downstream GHG emissions from the handling of waste. The most thorough report quantifying GHG emissions from indoor cannabis is from Mills10, which states that growing 1 kg of cannabis indoors releases 4,600 kg of carbon dioxide equivalent (CO2e). However, the scope of the work was intended to be a central estimate, representing a singular US location case study for the industry’s general practices. Furthermore, Mills10 conducted this study prior to legalization and only used data from small-scale experimental systems, thus lacking validation of full-scale commercial grow operations...

...An indoor cannabis cultivation model was developed to track the necessary energy and materials required to grow cannabis year-round in an indoor, warehouse-like environment. This environment maintains climate conditions as required for the cannabis plants, yielding a consistent product regardless of weather conditions. The model calculates the necessary energy to maintain these indoor climate conditions by using a year’s worth of hourly weather data from more than 1,000 locations in the United States11. The analysed locations are independent of current legal status and represent hypothetical grow facilities in all 50 US states. The model then converts the required energy, supplied from electricity and natural gas, into GHG emissions through electrical grid emissions data from 26 regions in the United States12 and life cycle inventory (LCI) data13,14...

a, Cumulative GHG emissions from cultivating cannabis indoors interpolated within eGRID electricity region boundaries. eGRID, Emissions and Generation Resource Integrated Database. b, Natural gas required to maintain indoor environmental conditions. c, Electricity required to maintain indoor environmental conditions and high-intensity grow lights. d, GHG emissions for the US electricity regions modelled. Full resolution figures are provided in Supplementary Figs. 1–4.

GHG emissions from indoor cannabis production at ten of the 1,011 locations modelled. The GHG emissions totals represent individual simulation results based on modelling input parameters specific to each location. The positive values represent released GHG emissions and the negative value represents stored GHG emissions based upon the model system boundary. The HVAC labels in the main figure refer to the major equipment used to manipulate outside air to meet inside condition criteria, whereas the indoor environmental controls in ‘Other’ are supplemental (suppl.) systems representing additional equipment located inside grow rooms that aid in maintaining environmental conditions.

The HVAC systems are responsible for modifying air temperature and humidity to an allowable range before being supplied to the cannabis plants. This is critical to maintaining plant health as sudden changes in temperature and humidity can shock the plants and ultimately lead to crop damage and product loss. Additionally, cannabis plants require a regular supply of fresh air to help moderate humidity and oxygen levels. In this work, an air supply rate of 30 volumetric air changes per hour (ACH) was assumed. This value represents the average value from the literature, which reports values as high as 60 ACH and as low as 12 ACH (Supplementary Table 1). For comparison, the recommended ventilation for homes is 0.35 ACH and operating rooms in hospitals require a minimum of 15 ACH15,16. Air condition modifications and supply by HVAC are cumulatively shown to be the largest contributor to overall GHG emissions regardless of location (see Supplementary Table 2 for all contributions).

Impact of ACH on GHG emissions from indoor cannabis cultivation for the same ten locations displayed in Fig. 2. The baseline assumption for this study was 30 ACH, shown in red.

Although there are many hurdles associated with shifting cannabis growth to legal and well-regulated greenhouse and outdoor cultivation practices, preliminary investigations into the potential difference in GHG emissions when switching to greenhouse and outdoor cultivation practices indicated reductions of 42 and 96%, respectively6,7. It is important to note that these reports are limited in scope and resolution as the GHG emissions are based primarily on electricity consumption through monthly bills. Therefore, the current state of the industry would benefit from understanding the true GHG emissions of greenhouse and outdoor cultivation at a similar resolution to the work presented here to allow real comparison between the three cultivation methods. The results of this study affirm that more than 80% of the GHG emissions from all indoor cannabis locations assessed are caused by practices directly linked to indoor cultivation methods, specifically indoor environmental control, high-intensity grow lights and the supply of CO2 for increased plant growth. If indoor cannabis cultivation were to be fully converted to outdoor production, these preliminary estimates show that the state of Colorado, for example, would see a reduction of more than 1.3% in the state’s annual GHG emissions (2.1 MtCO2e)24.

WASHINGTON (The Borowitz Report)—Calling the $1.9 trillion American Rescue Plan “a fever dream of the cancel-culture crew,” Senator Ted Cruz accused Democrats of a “politically correct plot to cancel poverty.”

“Poverty has been a part of American life since this country was founded, in 1776, but that apparently means nothing to the Democrat Cancel Culture Gang,” Cruz said. “In their intolerant view, poverty is somehow no longer appropriate.”

He warned that, far from being Democrats’ ultimate goal, “cancelling poverty is just the beginning.”

“If you read the fine print, they also want to cancel hunger and homelessness,” he said. “And, if you’re used to living without health insurance, sorry—that’s yet another American tradition they want to cancel.”

“We should have seen this coming,” he added. “First they came for Mr. Potato Head.”

Advice My Parents Gave Me: Go to college and major in what you love.

Advice I Will Give My Kids: Go to college only if you’ll major in science, engineering, or money. It’s a bleak job market, and majoring in English literature or anything with the word “English” in it has been useless since the Taft Administration.



My Parents: Never show up to a party empty-handed.

Me: Never show up to a party. Send a text to the host twenty minutes before the party starts to say that you’re “sooooooo sorry” to cancel but your stomach is feeling “weird.”



My Parents: To find a job, walk into the offices of ABC News’s “This Week with George Stephanopoulos” and ask for one.

Me: Apply to jobs via LinkedIn, ZipRecruiter, or nepotism. Write a cover letter and attach your résumé, then manually enter the same information through the company’s portal, which looks as though it was designed in Microsoft Paint. Do this twenty times a day for two years, and you’re bound to make it to a third round of phone interviews before getting ghosted.



My Parents: Don’t put photos of yourself on the Internet. You’ll get kidnapped!

Me: Post thousands of carefully curated photos of your life on Instagram so you can build a following and attract sponsors who reflect your core values, such as Bacardi and MeUndies.



My Parents: Spend your twenties finding true love within a two-mile radius of your village.

Me: Spend your twenties moving between L.A. and New York to figure out what you want in your ideal partner by dating all the worst people from both coasts and Austin, Texas.



My Parents: Show how much you appreciate your friends by making them elaborate, cellophane-wrapped gift baskets. Fill the baskets with gourmet biscuits, teas, and an ornate sugar spoon that says “Gimme a little sugar, baby.”

Me: Just Venmo them five dollars.

My Parents: Never date someone who rides a motorcycle.

Me: Never date someone who rides a unicycle ironically (unless the person got a MacArthur “genius” grant for it)...

The group considered Texas’ oldest and largest electricity cooperative has filed for Chapter 11 bankruptcy protection, saying it can’t pay money wanted by the state’s grid operator in connection with power outages during a major winter storm that hit in February.

Brazos Electric Power Cooperative filed its bankruptcy petition March 1 in the U.S. Bankruptcy Court for the Southern District of Texas. The company said it received a $2.1 billion charge from the Electric Reliability Council of Texas (ERCOT), the group that maintains and operates much of the state’s electricity grid. Brazos Electric is the wholesale energy provider for its 16-member cooperative.

Texas’ deregulated power market, which is not connected to other U.S. electricity transmission systems, means that most of the state’s power customers are not beholden to any one energy provider. Instead, customers can choose among dozens of electricity retailers on an open market.

Electricity generators—companies such as NRG and Vistra—produce power, which can then be sold by retail electric providers. Those retail companies include Griddy, which is being sued by the state attorney general’s office for sending customers bills for as much as $5,000 for the cost of power during the weeklong storm.

State officials said they received more than 400 complaints about Griddy in less than two weeks. Texas Attorney General Ken Paxton in the lawsuit said Griddy deceived customers when it promised low “wholesale” energy prices...