Dan Goodman @neural-reckoning.org · 1hIt's that time of year where the view from my window gets quite distracting. #photography 040
Dan Goodman @neural-reckoning.org · 01/10/2026This was my first time going to #BernsteinConference and I really enjoyed it. Would definitely recommend going next year. Particularly enjoyed the workshops and posters. Overall vibe was 👇 311314
Dan Goodman @neural-reckoning.org · 01/10/2026I hardly ever take flights any more, but I have to admit that coming in to land in London at sunset with a window seat is a pretty spectacular experience. 1170
Dan Goodman @neural-reckoning.org · 30/09/2026My contribution to the black and white photography in fog (well in this case, from inside a cloud). 110
Dan Goodman @neural-reckoning.org · 25/09/2026Nicolas Dundov has poster 4-38 (first floor) on Wednesday (14:00-15:30) on "Blood and modularity: a brain-inspired approach to functional disentangled neural representations" neural-reckoning.org/nicolas_dund... 030
Dan Goodman @neural-reckoning.org · 25/09/2026Abdal AlKilany has poster 4-3 (ground floor) on Wednesday (14:00-15:30) on "Neuromodulation improves robust and efficient sensory processing in spiking neural networks" neural-reckoning.org/abdelqader_a... Preprint: neural-reckoning.org/pub_neuromod... Talk: neural-reckoning.org/talk_2026_ne... 130
Dan Goodman @neural-reckoning.org · 25/09/2026Yishu Zhang has poster P1-44 (first floor) on Tuesday (16:30-18:00) on "Do heterogeneous brains remember better?" neural-reckoning.org/yishu_zhang.... 120
Dan Goodman @neural-reckoning.org · 24/09/2026Not a terrible evening to go for a run home though the city. 040
Dan Goodman @neural-reckoning.org · 07/09/2026Dappled sunlight in the woods is challenging to photograph. Most of my shots didn't come out that well, but I kinda like this one. #photography 0160
Dan Goodman @neural-reckoning.org · 03/09/2026#SpikingNeuralNetwork people - this year's SNUFA workshop is live! Talks by: ⭐ Eugene Izhikevich ⭐ @giuliadangelo.bsky.social ⭐ Mihai Petrovici ⭐ Susanne Schreiber Submit your abstracts by Sept 25th. Registration is open! More info at: snufa.net/2026/ cc @fzenke.bsky.social @albada.bsky.social 02416
Dan Goodman @neural-reckoning.org · 29/08/2026This was totally worth staying up until 2am for. Word frequency analysis for the abstracts of my papers over time. You can read off my career from that, including my gradual reduction of interest in SNNs and then their sudden resurgence when surrogate gradient descent appeared. 0190
Dan Goodman @neural-reckoning.org · 23/08/2026There's so many beautiful parks in London I sometimes forget about parkland walk, but I shouldn't because it's absolutely lovely. #photography #london 0100
Dan Goodman @neural-reckoning.org · 18/08/2026Paddington station. Which is better, night or day? #photography 370
Dan Goodman @neural-reckoning.org · 17/08/2026@neuromatch.bsky.social retreat in Oxfordshire. #photography 0141
Dan Goodman @neural-reckoning.org · 12/08/2026The results. I didn't have the right filter for my bigger zoom lens so quite low resolution, but still pretty happy with that. 2100
Dan Goodman @neural-reckoning.org · 12/08/2026The glasses I ordered arrived just in time, and they actually delivered twice as many as I'd ordered so I got to spread the joy to a few lucky neighbours. #eclipse 1170
Dan Goodman @neural-reckoning.org · 11/08/2026Any guesses as to what I'm doing at 7.15 pm BST taking a photo like this? 😂 170
Dan Goodman @neural-reckoning.org · 03/08/2026Sometimes a lazy river can feel a bit like an alien landscape. #photography 170
Dan Goodman @neural-reckoning.org · 16/07/2026Modulation (top curve, red) also lets us reduce firing rates by orders of magnitude without hurting performance, unlike unmodulated networks (bottom curve, blue). Fewer spikes means less energy. Important both for real brains and neuromorphic devices! 130
Dan Goodman @neural-reckoning.org · 16/07/2026In a neuromorphic or machine learning context, neuromodulation is very parameter efficient. This figure shows every variant of the modulated and unmodulated models in our paper, comparing parameter count versus accuracy. You can see that the frontier of modulated networks is much higher. 130
Dan Goodman @neural-reckoning.org · 16/07/2026Our model allows for setting a number of neuromodulator types, that can have interactions between each other, and making neuromodulator release diffuse in space and time. This actually turns out to further improve performance! 120
Dan Goodman @neural-reckoning.org · 16/07/2026And we can understand how it's doing it: it dials up the sensitivity when the noise level is low, and dials it down when the noise is high. This sort of dynamic gain control is the "listening in the dips" strategy that has been hypothesised to be used by humans. We didn't put this in, it learned it! 120
Dan Goodman @neural-reckoning.org · 16/07/2026The performance enhancement is particularly large in a noisy background, in the range where human speech recognition is much better than state-of-the-art automatic speech recognition systems. 120
Dan Goodman @neural-reckoning.org · 16/07/2026With this model, performance at a variety of tasks goes up (in the picture, an auditory task). A small network with modulation performs much better than a much larger network without modulation. We can also see here that modulation at medium timescales is best. Spatial scale not very important here. 120
Dan Goodman @neural-reckoning.org · 16/07/2026Our model is simple at the core: we let a modulatory neuron modify the underlying parameters of another neuron (like threshold or time constant), and train end to end. We can make this more realistic in various ways (different types of neuromodulators, spatial release and diffusion) - see later. 120
Dan Goodman @neural-reckoning.org · 18/06/2026The hardware version gets higher throughput (4x better) and energy efficiency (5x better) at comparable area. 120
Dan Goodman @neural-reckoning.org · 18/06/2026We see that across a range of tasks we get state-of-the-art performance at a lower memory cost (M) compared to other models (look for the stars in the figure). 110
Dan Goodman @neural-reckoning.org · 18/06/2026We think of this as a biologically inspired fast-slow structure where the SNNs are acting fast, and the memory buffer (a Legendre memory unit) acts as a slow working memory. We co-designed this to work as a neural model and in neuromorphic hardware. 110
Dan Goodman @neural-reckoning.org · 12/04/2026Second joyful nature photo for today to celebrate election result in Hungary. #photography 070
Dan Goodman @neural-reckoning.org · 10/04/2026The kids had fun making paths on the ground in the local wood. #photography 642532
Dan Goodman @neural-reckoning.org · 08/04/2026Not normally into bird #photography but quite pleased that I managed to get a shot of a woodpecker! Even managed to get a video of it pecking. 0142
Dan Goodman @neural-reckoning.org · 13/03/2026In this sort of case I often think of Kent Anderson's hilarious article on "102 things journal publishers do" (to add value). One of which is to have a fancy office. That's not needed for science. 110
Dan Goodman @neural-reckoning.org · 09/02/2026Today may not have been the best day to go off piste on my run... 020
Dan Goodman @neural-reckoning.org · 21/01/2026What I'm aiming at is roughly half way between these. 😂 210
Dan Goodman @neural-reckoning.org · 19/01/2026Some days you just wish you had your big fancy camera with you. #photography 1130