Multi-sensory models

Extracted Attributes

• Key Developer

  Thinking Machines

• Core Capability

  Real-time audio-visual reasoning

• Learning Modalities

  Visual, Auditory, Kinesthetic, Tactile (VAKT)

• Integration Principles

  Spatial rule, temporal rule, inverse effectiveness rule

• Computational Framework

  Bayesian models

• Memory Model Components

  Sensory register, short-term store, long-term store

Timeline

• Richard Atkinson and Richard Shiffrin propose the multi-store model of memory. (Source: Wikipedia)

  1968-01-01

• Ernst and Banks demonstrate optimal multisensory integration for visual-haptic size estimation. (Source: Web Search)

  2002-01-01

• Startup Thinking Machines releases a multi-sensory model capable of real-time audio-visual reasoning. (Source: Document 9bd37466-ff80-4f45-9371-0f58ab15a813)

  2024-01-01

Atkinson–Shiffrin memory model

The Atkinson–Shiffrin model (also known as the multi-store model or modal model) is a model of memory proposed in 1968 by Richard Atkinson and Richard Shiffrin. The model asserts that human memory has three separate components: a sensory register, where sensory information enters memory, a short-term store, also called working memory or short-term memory, which receives and holds input from both the sensory register and the long-term store, and a long-term store, where information which has been rehearsed (explained below) in the short-term store is held indefinitely. Since its first publication this model has come under much scrutiny and has been criticized for various reasons (described below). But it is notable for the significant influence it had in stimulating memory research.

Web Search Results

• Multisensory Integration and the Society for Neuroscience: Then and Now - PMC

  Bayesian frameworks have been used to explore how multisensory integration can combine individual sensory estimates to provide overall estimates that make best use of all available information. In a classic Bayesian model of sensory function, sensory estimates of environmental features are combined with prior knowledge to produce a “posterior” probability distribution from which the most likely value of the external feature can be inferred. In a multisensory model, signals obtained from different sensory sources are combined as independent indicators of the same feature. When the signals are congruent, this combination improves the accuracy of the inferred estimates (Fig. 5). These models have been applied to multiple functional domains, including visual-auditory, visual-haptic, and [...] At the same time, neural network models have been developed at multiple levels of abstraction to examine the validity of posited verbal theories of circuit function. These have extended from early work in which single modality-specific units sent direct projections onto multisensory targets, to increasingly more elaborate architectures. In each case, efforts have been made to link the operation of these models to Bayesian frameworks and to focus on incorporating more extensive biological constraints to explain broader empirical findings. This has led to modern models that provide a moment-by-moment accounting of the multisensory transform, circuit models to explain normal and abnormal function and development, whole-brain models linking multisensory circuit computations to behavior, and [...] in sophistication from simple, abstract architectures involving three areas (e.g., two unisensory areas and one multisensory area) to models that include multiple biologically realistic inputs. In this diagram, ovals represent processing areas containing multiple units (circles). There are a total of four modeled input areas: two derived from cortical regions AES (AEV, visual; FAES, auditory) and two derived from non-AES sources (V, visual; A, auditory). These areas extend projections to integrating neurons in the SC. Right, Models of single units performing multisensory integration no longer seek to describe the responses of a “canonical” or “average” multisensory product calculated over a wide window of time but can successfully predict the responses of individual neurons at a

• Multisensory learning - Wikipedia

  Learning with the use of more than one sense Multisensory learning is the assumption that individuals learn better if they are taught using more than one sense (modality). The senses usually employed in multisensory learning are visual, auditory, kinesthetic, and tactile – VAKT (i.e. seeing, hearing, doing, and touching). Other senses might include smell, taste and balance "Balance (ability)") (e.g. making vegetable soup or riding a bicycle). [...] 1. ^ "Multisensory instruction: what you need to know, Amanda Morin, www.understood.org". 5 August 2019. 2. ^ "The New Handbook of Multisensory Processing, 2012, edited by Barry E. Stein, Professor and Chair of the Department of Neurobiology and Anatomy at Wake Forest University School of Medicine". 3. ^ Chandrasekaran, C. (2017). "Computational principles and models of multisensory integration., Chandrasekaran C1.April 2017". Current Opinion in Neurobiology. 43: 25–34. doi "Doi (identifier)"):10.1016/j.conb.2016.11.002. PMC "PMC (identifier)") 5447489. PMID "PMID (identifier)") 27918886. [...] Some studies conclude that the benefits of multisensory learning are greatest if the senses are engaged concurrently (see Multisensory integration) and the instruction is direct (explicit) and systematic (see Pre-attentive processing § Multisensory integration). However, some neurologists question whether more is "actually better for learners who are struggling". The rationale is that learners with developmental disorders may have impairments in cognitive control, planning, and attention, so multisensory integration might place additional demands on systems that are already straining. Consequently, it is suggested that it may be better to narrow the alternatives to one that works. Other studies suggest that multisensory integration only develops optimally by middle childhood (i.e. eight

• Multisensory Learning: How Combining Senses Builds Memory

  Research has found that the multi-sensory approach creates more constructive brain responses than when just one sense is used. Multi-sensory techniques teach the brain to respond to a variety of inputs, which results in better overall learning. The use of multiple senses can also help reduce stress and makes it easier for learners to focus. Additionally, stimulating several senses at once can make learning more enjoyable and significantly improve recall and retention. [...] Multi-sensory techniques can be used and adapted to support students learning in any topic area or subject. It is suitable for every student from the early years, to secondary and higher education. The traditional learning process of some subjects involves multisensory learning as a normal way to teach relevant subjects to the students. Birch (2009) found multisensory methods teach alphabets in early years. Combining touch, hearing, and sight helps introduce letters. Research by Smith (2010) suggests learners connect sounds and letters quicker. Willis (2012) recommends multisensory teaching for phonemic awareness. [...] Multisensory approaches in secondary school ‍ ## What are the benefits of using multisensory instruction in the classroom? The major benefit of using the multisensory method of teaching is that it helps learners to retain more knowledge. The best way to apply multisensory instruction for students is integrating a variety of sensory experiences in a fun activity to ensure that all of the learners can access and engage in the learning. 'Thinking with hands' activities can engage learners. These activities involve learners handling objects, as suggested by various researchers (e.g. Smith, 2001). Sensory elements can enhance the experience (Jones & Brown, 2005). Multisensory activities are also an option (Patel, 2012).

• What Is Multisensory Learning in Education? | HMH

  ## Multisensory Learning Definition At its core, multisensory learning is an approach to education that leverages the interconnected nature of the human sensory experience. As a pedagogical philosophy, it recognizes that when learners engage multiple senses simultaneously, they enhance understanding and solidify long-term retention. A practical definition of multisensory education is learning that engages more than one of the following senses at a time: [...] A single sense approach can present real disadvantages for learners. Instruction that uses only auditory (listening to the teacher) or visual (reading) techniques creates barriers to learning for students who may not be able to access meaning as easily through these modalities. A multisensory approach creates paths that allow learners to access instruction. Due to the compounding effects of learning, this can make a significant difference. [...] ## Benefits of a Multisensory Approach to Learning One of the primary benefits of a multisensory approach to learning is that it helps students gain more knowledge. Sensory stimulation is associated with improved memory retention and mental cognition. When students are able to use more than one sensory input to make connections between facts and ideas, they are better able to interpret, comprehend, synthesize, and store information. In addition to helping students understand concepts, multisensory learning helps them develop their own ideas. Kinesthetic activities such as role-play, dance, and scientific experiments provide students with valuable hands-on experiences that help them make connections to what they already know and take ownership of their learning.

• Multisensory Integration — Cognitive Psychology Reference

  ## Bayesian Models of Integration The Bayesian framework has been remarkably successful in predicting multisensory integration behavior. When localizing a sound accompanied by a flash of light, observers weight visual and auditory information in proportion to their relative reliability — more weight to vision in good visibility, more to audition when the visual signal is degraded. The resulting combined estimate is statistically optimal, achieving lower variance than either sense alone. Ernst and Banks (2002) provided a compelling demonstration of this optimal integration for visual-haptic size estimation. ## Illusions of Integration [...] ## Principles of Multisensory Integration Barry Stein and Alex Meredith identified three fundamental principles governing multisensory integration in individual neurons (primarily studied in the superior colliculus). The spatial rule states that stimuli from different modalities must originate from approximately the same location to be integrated. The temporal rule requires that stimuli occur within a temporal window (typically a few hundred milliseconds). The inverse effectiveness rule states that multisensory enhancement is greatest when the individual unisensory signals are weak or ambiguous — precisely when combining information is most useful. ## Bayesian Models of Integration